This manuscript is an overview of the research that is currently being performed as part of a 2009 NSF Office of Emerging Frontiers in Research and Innnovation (EFRI) grant on BioSensing and BioActuation (BSBA). The objectives of this multi-university collaborative research are to achieve a greater understanding of the hierarchical organization and structure of the sensory, muscular, and control systems of fish, and to develop advanced biologically-inspired material systems having distributed sensing, actuation, and intelligent control. New experimental apparatus have been developed for performing experiments involving live fish and robotic devices, and new bio-inspired haircell sensors and artificial muscles are being developed using carbonaceous nanomaterials, bio-derived molecules, and composite technology. Results demonstrating flow sensing and actuation are presented.

Over the past several years, wireless network systems and sensing technologies have been developed significantly. This has resulted in the broad application of wireless sensor networks (WSNs) in many engineering fields and in particular structural health monitoring (SHM). The movement of traditional SHM toward the new generation of SHM, which utilizes WSNs, relies on the advantages of this new approach such as relatively low costs, ease of implementation and the capability of onboard data processing and management. In the particular case of long span bridge monitoring, a WSN should be capable of transmitting commands and measurement data over long network geometry in a reliable manner. While using single-hop data transmission in such geometry requires a long radio range and consequently a high level of power supply, multi-hop communication may offer an effective and reliable way for data transmissions across the network. Using a multi-hop communication protocol, the network relays data from a remote node to the base station via intermediary nodes. We have proposed a data-transmission pipelining algorithm to enable an effective use of the available bandwidth and minimize the energy consumption and the delay performance by the multi-hop communication protocol. This paper focuses on the implementation aspect of the pipelining algorithm on Imote2 platforms for SHM applications, describes its interaction with underlying routing protocols, and presents the solutions to various implementation issues of the proposed pipelining algorithm. Finally, the performance of the algorithm is evaluated based on the results of an experimental implementation.

Rapid advancement of sensor technology has been changing the paradigm of Structural Health Monitoring (SHM) toward a wireless smart sensor network (WSSN). While smart sensors have the potential to be a breakthrough to current SHM research and practice, the smart sensors also have several important issues to be resolved that may include robust power supply, stable communication, sensing capability, and in-network data processing algorithms. This study is a hybrid WSSN that addresses those issues to realize a full-scale SHM system for civil infrastructure monitoring. The developed hybrid WSSN is deployed on the Jindo Bridge, a cable-stayed bridge located in South Korea as a continued effort from the previous year's deployment. Unique features of the new deployment encompass: (1) the world's largest WSSN for SHM to date, (2) power harvesting enabled for all sensor nodes, (3) an improved sensing application that provides reliable data acquisition with optimized power consumption, (4) decentralized data aggregation that makes the WSSN scalable to a large, densely deployed sensor network, (5) decentralized cable tension monitoring specially designed for cable-stayed bridges, (6) environmental monitoring. The WSSN implementing all these features are experimentally verified through a long-term monitoring of the Jindo Bridge.

This paper compares the performance of various feature extraction methods applied to structural sensor measurements acquired in-situ, from a decommissioned bridge under realistic damage scenarios. Three feature extraction methods are applied to sensor data to generate feature vectors for normal and damaged structure data patterns. The investigated feature extraction methods include identification of both time domain methods as well as frequency domain methods. The evaluation of the feature extraction methods is performed by examining distance values among different patterns, distance values among feature vectors in the same pattern, and pattern recognition success rate. The test data used in the comparison study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case data sets, including undamaged cases and pier settlement cases (different depths), are used to test the separation of feature vectors among different patterns and the pattern recognition success rate for different feature extraction methods is reported.

This paper presents further advancements made in an ongoing project following a series of presentations made at the same SPIE conference in the past. Compared with traditional microprocessor-based systems, rapidly advancing field-programmable gate array (FPGA) technology offers a more powerful, efficient and flexible hardware platform. An FPGA-based design is developed to classify three types of nonlinearities (including linear, hardening and softening) of a single-degree-of-freedom (SDOF) system subjected to free vibration. This significantly advances the team's previous work on using FPGAs for wireless structural health monitoring. The classification is achieved by embedding two important algorithms - empirical mode decomposition (EMD) and backbone curve analysis. A series of systematic efforts is made to embed EMD, which involves cubic spline fitting, in an FPGA-based hardware design. Throughout the process, we take advantage of concurrent operation and strive for a trade-off between computational efficiency and resource utilization. We have started to pursue our work in the context of FPGA-based computation. In particular, handling fixed-point precision is framed under data-path optimization. Our approach for data-path optimization is necessarily manual and thus may not guarantee an optimal design. Nonetheless, our study could provide a baseline case for future work using analytical data-path optimization for this and numerous other powerful algorithms for wireless structural health monitoring.

Fiber-reinforced polymers (FRP) composites are widely used in aerospace and civil structures due to its unique material properties. However, damage can still occur and typically manifests itself from within the composite material that is invisible to the naked eye. So as to be able to monitor the performance of FRPs, numerous sensing systems have been proposed for embedment within FRP composites. One such methodology involves the embedment of carbon nanotube-based thin films within FRP laminates for strain monitoring and potentially even damage detection. Unlike other sensors, these piezoresistive thin films possess small form factors (and thus do not serve as stress concentration or damage initiation points) and can be easily integrated during composite manufacturing. In this study, a series of laboratory tests have been conducted to characterize the static and dynamic strain sensing performance of these nanocomposites for monitoring glass fiber-reinforced polymer (GFRP) components. Specifically, monotonic uniaxial, cyclic, and fatigue tests have been conducted, while both time- and frequency-domain measurements have also been obtained. The characterization results obtained from this study indicates bi-functional strain sensitivity to monotonic loading until failure, which is found to be reproducible in cyclic dynamic loadings to amplitudes in both functional ranges.

Researchers have made significant progress in recent years towards realizing long-term structural health monitoring (SHM) utilizing wireless smart sensor networks (WSSNs). These efforts have focused on improving the performance and robustness of such networks to achieve high quality data acquisition and in-network processing. One of the primary challenges still facing the use of smart sensors for long-term monitoring deployments is their limited power resources. Periodically accessing the sensor nodes to change batteries is not feasible or economical in many deployment cases. While energy harvesting techniques show promise for prolonging unattended network life, low-power design and operation are still critically important. This research presents a new, fully integrated ultra-low power wireless smart sensor node and a flexible base station, both designed for long-term SHM applications. The power consumption of the sensor nodes and base station has been minimized through careful hardware selection and the implementation of power-aware network software, without sacrificing flexibility and functionality.

Recent water shortages, particularly evident in the state of California, are calling for better predictive capabilities, and improved management techniques for existing water distribution infrastructure. One particular example involves large-scale water distribution systems (on the scale of reservoirs and dams) in the Sierra Nevada, where the majority of the state's water is obtained from melting snow. Current control strategies at this scale rely on sparse data sets, and are often based on statistical predictions of snowmelt. Sudden, or unexpected, snowmelt can thus often lead to dam-overtopping, or downstream flooding. This paper assesses the feasibility of employing real-time hydrologic data, acquired by large-scale wireless sensor networks (WSNs), to improve current water management strategies. A sixty node WSN, spanning a square kilometer, was deployed in the Kings River Experimental Watershed, a research site in the Southern Sierra Nevada, at an elevation of 1,600-2,000 m. The network provides real time information on a number of hydrologic variables, with a particular emphasis on parameters pertaining to snowmelt processes. We lay out a system architecture that describes how this real-time data could be coupled with hydrologic models, estimation-, optimization-, and control-techniques to develop an automated water management infrastructure. We also investigate how data obtained by such networks could be used to improve predictions of water quantities at nearby reservoirs.

We have developed a novel relative-story displacement sensor capable of measuring the 5-degree-of-freedom movement of building layers for structural health monitoring. Three pairs of infrared-light emitting diode arrays and positionsensitive detector units were used for simultaneously measuring the relative-story displacement, the inclination angle of the lower layer, and the torsion angle between two adjacent layers. For verification, laboratory tests were carried out using a shaking table, a motorized micrometer and a rotation stage. In the static experiment, it is verified that the local inclination angle and the torsion angle can be measured as well as the relative-story displacement using the sensor system. The resolution of the sensor system in the displacement measurement, that in the inclination angle measurement, and that in the torsion angle measurement were evaluated to be 0.10 mm, 34.4 μrad, and 14.6 μrad, respectively. In the dynamic response experiment, the accuracy of the sensor system was experimentally evaluated to be 0.20 mm in the relative-displacement measurement, 110 μrad in the inclination angle measurement, and 90 μrad in the torsion angle measurement, respectively. These results indicate that the developed sensor system has a sufficient accuracy for the structural health diagnostics of buildings.

Energy harvesting technologies have been extensively researched to develop long-lived wireless sensor networks. To better utilize the harvested energy, various energy storage systems are proposed. A simple circuit model is developed to describe supercapacitor behavior, which uses two resistor-capacitor branches with different time constants to characterize the charging and redistribution processes, and a variable leakage resistance (VLR) to characterize the self-discharge process. The voltage and temperature dependence of the VLR values is also discussed. Results show that the VLR model is more accurate than the energy recursive equation (ERE) models for short term wireless sensor network applications.

This paper presents hybrid structural health monitoring of steel girder connections using wireless acceleration and impedance sensor nodes based on Imote2-platform. To achieve the research objective, the feasibility of the sensor nodes is examined about its performance for vibration-based global monitoring and impedance-based local monitoring in the structural systems as the following approaches. First, a damage monitoring scheme is described in parallel with global vibration-based methods and local impedance-based methods. Second, multi-scale sensor nodes that enable combined acceleration-impedance monitoring are described on the design of hardware components and embedded software to operate. Third, the performances of the multi-scale sensor nodes are experimentally evaluated from damage monitoring in a lab-scaled steel girder with bolted connection joints.

In this paper, we will summarize our efforts on exploring guided acoustic waves generated by MEMS ultrasonic transducers enabling a non-destructive, ultra-low powered, wireless SHM system. State-of-the-art SHM systems employ bulk piezoelectric transducers. However, they are not environmentally benign (contain lead), not cost feasible for monitoring every bridge in the U.S., require significant power for operation, lack integration capability for wireless interrogation, need precise matching layers, and have only 25-50 percent fractional bandwidth, limiting the detection resolution. To alleviate most of these shortcomings, a low impedance MEMS transducer, called a capacitive micromachined ultrasonic transducer (CMUT), is explored.

There is a dire need to develop novel robust and reliable sensing technologies for identifying the onset of structural damage and for preventing sudden catastrophic structure failures. While numerous sensors (e.g., fiber optics, wireless sensors, piezoelectrics, and remote sensing, among others) have been proposed for structural health monitoring, the current generation of sensing systems suffer from some fundamental limitations such as discrete sensing and high energy demand. In this study, a new paradigm for strain sensing and structural monitoring is proposed by developing a novel optoelectronic nanocomposite that can generate strain-sensitive photocurrent. Unlike other common sensing transducers, the proposed nanocomposite sensor is a self-sensing material, is conformable to structural surfaces, is of small form factor, and does not require an external power source. First, regioregular poly(3-hexylthiophene) (P3HT) conductive polymer (i.e., the main photoactive component of the nanocomposite) is synthesized in the laboratory and characterized via nuclear magnetic resonance (NMR). Second, thin films comprising of P3HT and carbon nanotubes are fabricated via spin coating. Upon specimen fabrication, the nanocomposite's photocurrent generation capabilities are investigated and evaluated. Finally, thin film specimens are loaded in an electromechanical load frame, and the preliminary results show that the magnitude of generated photocurrent varies in tandem with applied tensile strains.

To advance wireless structural monitoring systems mature into a reliable substitute to wired structural monitoring systems, efforts should be paid to investigate their in-field performance on real civil structures, especially complex mega structures. This study carries out an investigation into a vibration monitoring wireless sensor network (WSN) for modal identification of a huge cantilever structure. The testbed under study is the New Headquarters of Shenzhen Stock Exchange (NHSSE). One outstanding feature of NHSSE is its huge floating platform, which is a steel truss structure with an overall plan dimension of 98x162 m and a total height of 24 m. It overhangs from the main tower 36 m along the long axis and 22 m along the short axis at a height of 36 m above the ground, making it the largest cantilever structure in the world. Recognizing the uniqueness of this floating platform, the performance of the WSN for ambient vibration measurement of this structure is examined. A preliminary two-point simultaneous acceleration measurement using the WSN is reported in this paper. The preliminary study demonstrates that the WSN is capable of measuring the ambient vibration and identifying the modal properties of a huge cantilever structure.

Triboluminescence (TL) is a mechanical and luminescent phenomena enabling damage sensing capabilities in materials. Depending on material compound, various excitation mechanisms result in emissions stimulated by rubbing or fracture, and give an indication of internal stress. Design of Experiments helped ascertain experimental knowledge of the multiphase composite system containing ZnS:Mn phosphors (0 - 40%) and vinyl ester resin (VER). This statistical approach proffered an empirical model used to validate triboluminescent production. Data shows concentration compiled with impact energy has a significant effect on the luminous intensity. Light intensity was measured by a photomultiplier tube and a photo-voltaic detector. The signal intensity range was determined for each. The photovoltaic detector acts as a low-light sensor in the range of 0.61 - 0.116 A for impacts less than 0.4 J. Microscopy revealed plates with reasonable dispersion and view of micro-structural inclusions. DMA indicates the inclusion of ZnS:Mn produces a moderate change in Young's modulus and thermo-kinetic properties.

Wireless smart sensor technology offers many opportunities to advance infrastructure monitoring and maintenance by providing pertinent information regarding the condition of a structure at a lower cost and higher density than traditional monitoring approaches. Many civil structures, especially long-span bridges, have low fundamental response frequencies that are challenging to accurately measure with sensors that are suitable for integration with low-cost, low-profile, and power-constrained wireless sensor networks. Existing displacement sensing technology is either not practical for wireless sensor implementations, does not provide the necessary accuracy, or is simply too cost-prohibitive for dense sensor deployments. This paper presents the development and integration of an accurate, low-cost radar-based sensor for the enhancement of low-frequency vibration-based bridge monitoring and the measurement of static bridge deflections. The sensors utilize both a nonlinear vibrometer mode and an arctangent-demodulated interferometry mode to achieve sub-millimeter measurement accuracy for both periodic and non-periodic displacement. Experimental validation results are presented and discussed.

Monitoring load levels in multi-wire steel strands is crucial to ensuring the proper structural performance of post-tensioned concrete structures, suspension bridges and cable-stayed bridges. The post-tensioned box-girder structural scheme is widely used in several bridges, including 90% of the California inventory. In this structural typology, prestressing tendons are the main load-carrying components. Therefore loss of prestress as well as the presence of structural defects (e.g. corrosion and broken wires) affecting these elements are critical for the performance of the entire structure and may conduct to catastrophic failures. Unfortunately, at present there is no well-established methodology for the monitoring of prestressing (PS) tendons able to provide simultaneous and continuous information about the presence of defects as well as prestress levels. In this paper the authors develop a methodology to assess the level of load applied to the strands through the use of ultrasonic nonlinearity. Since an axial load on a multi-wire strand generates proportional contact stresses between adjacent wires, ultrasonic nonlinearity from the inter-wire contact must be related to the level of axial load. The work presented shows that the higher-harmonic generation of ultrasonic guided waves propagating in individual wires of the strand varies monotonically with the applied load, with smaller higher-harmonic amplitudes with increasing load levels. This trend is consistent with previous studies on higher-harmonic generation from ultrasonic plane waves incident on a contact interface under a changing contact pressure. The paper presents the results of experimental researches on free strands and embedded strands, and numerical studies (nonlinear Finite Element Analysis) on free strands.

Ultrasonic Consolidation (UC) is a manufacturing technique based on the ultrasonic joining of a sequence of metal foils which are bonded to one another. Due to moderate pressures and low temperatures, UC operates as a solid-state process. This research investigates the use of UC to fabricate smart material structures by integration of sensors, actuators and reinforcement by means of different types of fibres such as Silicon Carbide (SiC). Previous problems with the optimal placement of fibres directly between foils have been identified. Research on new capabilities to consolidate fibres securely and more accurately during UC will be presented. Channels created by laser processing prior to UC within metal matrix composites are investigated as a method to aid the embedding of high volume fractions of different fibres in unison without damage. Laser processing is conducted with a Fiber laser which has been identified as a promising method to create narrow channels with regard to beam profile, spot size and focusing capability. Microstructural studies such as cross-sectioning perpendicular to the fibre axial direction have been carried out to observe secure integration such as the amount of plastic flow around fibres and potential voids.

Loblolly pine (Pinus taeda) wood cube specimens were exposed to Gloeophyllum fungus (Gloeophyllum trabeum) for increasing periods of time ranging from one week to twelve weeks. The corresponding mass of each of these specimens was recorded before and after they were subjected to the controlled decay. Using X-ray computed tomography (CT) the specimens' corresponding mass loss due to decay and corresponding densities were calculated. For each of the three principal material directions of these specimens with controlled decay, ultrasonic longitudinal and (polarized) shear velocity measurements along with the corresponding attenuation measurements are presented. The measurements were carried out using longitudinal and shear ultrasonic transducers with a center frequency of 100 kHz. A steel delay line was used because of the relative small size of the wooden specimens relative to the used wavelengths. Waveform averaging was used along with the phase-slope method to measure velocities. It was observed that the velocities increase with increasing frequency and decrease with increasing amount of decay, while the corresponding attenuations increase with increasing frequency and with amount of decay.

One of the first piezoelectric motor designs with significant rotational speeds was outlined by Barth. This device used extensional piezoelectric elements to produce a time varying force at a distance r from the center of a centrally supported disk. These extensional actuators produced micro-steps at a high frequency with the end result being macroscopic rotation of the disk and high torque. The rotation direction is controlled by the choice of the actuators and the direction of the extension about the rotor center. A recent advancement in producing pre-stressed power ultrasonic horns using flexures allows for the development of high torque ultrasonic motors based on the Barth's idea that can be fabricated in a 2D plate or in more complicated 3D structures. In addition to the pre-stress flexures the design also allows for the use of flexures to produce the rotor/horn normal force. The torque can be controlled by the number of actuators in the plane and the amplitude of the normal force. This paper will present analytical and experimental results obtained from testing prototype planar motors.

A damage detection capability based on a flexible ultrasonic transducer (FUT) array bonded onto a planar and a curved surface is presented. The FUT array was fabricated on a 75 μm titanium substrate using sol-gel spray technique. Room temperature curable adhesive is used as the bonding agent and ultrasonic couplant between the transducer and the test article. The bonding agent was successfully tested for aircraft environmental temperatures between -80 °C and 100 °C. For a planar test article, selected FUT arrays were able to detect fasteners damage within a planar distance of 176 mm, when used in the pulse-echo mode. Such results illustrate the effectiveness of the developed FUT transducer as compared to commercial 10MHz ultrasonic transducer (UT). These FUT arrays were further demonstrated on a curved test article. Pulse-echo measurements confirmed the reflected echoes from the specimen. Such measurement was not possible with commercial UTs due to the curved nature of the test article and its accessibility, thus demonstrating the suitability and superiority of the developed flexible ultrasonic transducer capability.

Base isolation has been widely investigated and used in civil infrastructures all over the world. However, it still has some problems need to be solved. For example, extra buffers are needed for some types of isolators to prevent them from generating too large deformation. These buffers increase the cost of isolators and make them more complicated. In addition, some isolators may have residual deformation and need to be repaired or replaced after large earthquake. This also induces large cost. In order to develop novel isolators with self buffer and with residual deformation self-recovery ability, two types of materials, stainless steel metallic pseudo-rubber (SS-MPR) and shape memory alloy metallic pseudo-rubber (SMA-MPR), were fabricated and investigated in this study. Mechanical behaviors of these two materials were investigated, together with deformation self-recovery ability of SMA-MPR material. Meanwhile, three types of SMA-MPR specimens with various processing procedures were fabricated. Mechanical behavior of the SS-MPR and SMA-MPR specimens under cyclic sinusoidal compression loadings with various loading frequencies were test. After that, the three types of SMA-MPR specimens with residual deformation were put into a temperature controlled stove and their deformation recovery ability were tested. In order to address if these SMA-MPR specimens still have stable mechanical properties after deformation recovery, they were installed in the test machine and their stress-strain behavior under cyclic sinusoidal loads were tested again. Experimental results indicated that both SS-MPR and SMA-MPR are good potential material to develop novel seismic isolators for civil infrastructures.

Thermal insulating properties of doors and widows are important parameter to measure the quality of windows and doors. This paper develops the thermal insulating test system of doors and windows for large temperature difference in winter in north of China according to national standards. This system is integrated with temperature measurement subsystem, temperature control subsystem, the heating power measurement subsystem, and heat transfer coefficient calculated subsystem. The temperature measurement subsystem includes temperature sensor which is implemented by sixty-four thermocouple sensors to measure the key positions of cold room and hot room, and the temperature acquisition unit which adopts Agilent 34901A data acquisition card to achieve self-compensation and accurate temperature capture. The temperature control subsystem including temperature controller and compressor system is used to control the temperature between 0 degree to 20 degree for hot room and -20 degree to 0 degree for cold room. The hot room controller uses fuzzy control algorithm to achieve accurate control of temperature and the cold room controller firstly uses compressor to achieve coarse control and then uses more accurate temperature controller unit to obtain constant temperature(-20 degree). The heating power measurement is mainly to get the heat power of hot room heating devices. After above constant temperature environment is constructed, software of the test system is developed. Using software, temperature data and heat power data can be accurately got and then the heat transfer coefficient, representing the thermal insulating properties of doors and widows, is calculated using the standard formula. Experimental results show that the test system is simple, reliable and precise. It meets the testing requirements of national standard and has a good application prospect.

We consider the effects of acoustic pressure on the curing of a two-part epoxy, which can be considered analogous to the polymer healing process. An epoxy sample is loaded into a tube and monitored throughout the curing process by measuring the amplitudes of its natural frequencies in response to periodic mechanical impulses. The progress of the curing process can be quantified by tracing the natural frequencies and temperature of the epoxy-tube system. Studies described in our last report continue and work completed in this reporting period has sought and achieved repeatable test results by making slight modifications to existing procedures and protocol.

This paper investigates the potential of a non linear wave modulation SHM methodology with piezoelectric wafers as actuators and sensors to reveal impact damage in cross-ply Glass/ Epoxy composite plates. In the experimental procedure an electromechanical shaker and piezoceramic wafers are simultaneously used to provide the low and high frequency wave excitation, respectively, while for the acquisition of the modulated carrier wave a piezoceramic sensor was used. Two sets of piezoceramic actuators-sensor pairs are used to propagate the ultrasonic carrier wave into two directions, one parallel and transversely to the fibers of the outer unidirectional ply. Nonlinearities induced by the damage are detected as sidebands in the spectral components of the carrier signal. Experimental results quantify the potential of the method in detecting damage created by very low energy impacts (4 Joules). Additionally, the modulation factor of the sensor signal is proposed as damage index, and is shown to be a consistent and sensitive damage indicator in the impacted plates, for a broad range of carrier wave frequencies.

An optimization based technique for detecting the impact point on isotropic and anisotropic flat plates developed by Kundu and his associates is extended here to the cylindrical geometry. An objective function is defined that uses the cylindrical coordinates of four sensors attached to the cylinder and four arrival times to locate the point of impact by minimizing the objective function that gives the least squares error. The proposed technique is experimentally verified by predicting the points of impact and comparing the predicted points with the actual points of impact.

A novel two-stage signal reconstruction approach is proposed to analyze raw thermal image sequences for damage detection purposes by Infrared Thermographic NDE. The first stage involves low-pass filtering using Wavelets. In the second stage, a Multivariate Outlier Analysis is performed on filtered data using a set of signal features. The proposed approach significantly enhances the defective area contrast against the background in infrared thermography NDE. The two-stage approach has some advantages in comparison to the traditionally used methods, including automation in the defect detection process and better defective area isolation through increased contrast. The method does not require a reference area to function. The results are presented for the case of a composite plate with simulated delaminations, and a composite sandwich plate with skin-core disbonds.

The evaluation of seismic damage is today almost exclusively based on visual inspection, as building owners are generally reluctant to install permanent sensing systems, due to their high installation, management and maintenance costs. To overcome this limitation, the EU-funded MEMSCON project aims to produce small size sensing nodes for measurement of strain and acceleration, integrating Micro-Electro-Mechanical Systems (MEMS) based sensors and Radio Frequency Identification (RFID) tags in a single package that will be attached to reinforced concrete buildings. To reduce the impact of installation and management, data will be transmitted to a remote base station using a wireless interface. During the project, sensor prototypes were produced by assembling pre-existing components and by developing ex-novo miniature devices with ultra-low power consumption and sensing performance beyond that offered by sensors available on the market. The paper outlines the device operating principles, production scheme and working at both unit and network levels. It also reports on validation campaigns conducted in the laboratory to assess system performance. Accelerometer sensors were tested on a reduced scale metal frame mounted on a shaking table, back to back with reference devices, while strain sensors were embedded in both reduced and full-scale reinforced concrete specimens undergoing increasing deformation cycles up to extensive damage and collapse. The paper assesses the economical sustainability and performance of the sensors developed for the project and discusses their applicability to long-term seismic monitoring.

This paper deals with electrostatically actuated micro and nano-electromechanical (MEMS/NEMS) circular plates. The system under investigation consists of two bodies, a deformable and conductive circular plate placed above a fixed, rigid and conductive ground plate. The deformable circular plate is electrostatically actuated by applying an AC voltage between the two plates. Nonlinear parametric resonance and pull-in occur at certain frequencies and relatively large AC voltage, respectively. Such phenomena are useful for applications such as sensors, actuators, switches, micro-pumps, micro-tweezers, chemical and mass sensing, and micro-mirrors. A mathematical model of clamped circular MEMS/NEMS electrostatically actuated plates has been developed. Since the model is in the micro- and nano-scale, surface forces, van der Waals and/or Casimir, acting on the plate are included. A perturbation method, the Method of Multiple Scales (MMS), is used for investigating the case of weakly nonlinear MEMS/NEMS circular plates. Two time scales, fast and slow, are considered in this work. The amplitude-frequency and phase-frequency response of the plate in the case of primary resonance are obtained and discussed.

Much work has been reported on the use of piezoceramic patch sensors in structural health monitoring due to their simple structure and moderate performance. However, the patch uses the inherent electromechanical properties of a piezoceramic element itself. Once the piezoceramic element is given, not much controllability is available on its operation frequency, directionality, and sensitivity. This paper proposes and verifies the feasibility of a new ultrasonic sensor to estimate the quantitative configuration of cracks on a plate: an inter-digital transducer (IDT) type Lamb wave sensor. This IDT sensor is more readily controllable than conventional patch sensors in terms of its operation frequency and directionality by altering the IDT pattern on a given piezoceramic element. In this work, two different types of IDT sensors are designed and fabricated: annular IDT and rectangular IDT sensors. The IDT sensors are implemented in the experiments to investigate the length, the number and the inclination angle of the cracks artificially imposed on an aluminum plate. The variation of amplitude and time-of-flight (TOF) of Lamb waves are measured and analyzed to estimate the crack configurations. The results show that the annular IDT sensor is similar to the conventional patch sensors in terms of its omni-directional beam pattern. The rectangular IDT sensor is highly directional, thus the sensor has superior sensitivity to a particular direction, which means more robust to environmental noise coming from arbitrary directions. The measured configuration shows excellent correlation with real configuration of the cracks, which confirms the efficacy of the IDT sensors.

The University of California at San Diego (UCSD), under a Federal Railroad Administration (FRA) Office of Research and Development (R&D) grant, is developing a system for high-speed and non-contact rail defect detection. A prototype has been designed and field tested with the support of Volpe National Transportation Systems Center and ENSCO, Inc. The goal of this project is to develop a rail defect detection system that provides (a) better defect detection reliability (including internal transverse head defects under shelling and vertical split head defects), and (b) higher inspection speed than achievable by current rail inspection systems. This effort is also in direct response to Safety Recommendations issued by the National Transportation Safety Board (NTSB) following the disastrous train derailments at Superior, WI in 1992 and Oneida, NY in 2007 among others. The UCSD prototype uses non-contact ultrasonic probing of the rail head (laser and air-coupled), ultrasonic guided waves, and a proprietary real-time statistical analysis algorithm that maximizes the sensitivity to defects while minimizing false positives. The current design allows potential inspection speeds up to 40 mph, although all field tests have been conducted up to 15 mph so far. This paper summarizes (a) the latest technology development test conducted at the rail defect farm of Herzog, Inc. in St Joseph, MO in June 2010, and (b) the completion of the new Rail Defect Farm facility at the UCSD Camp Elliott Field Station with partial in-kind donations from the Burlington Northern Santa Fe (BNSF) Railway.

This paper deals with electrostatically actuated Carbon NanoTubes (CNT) cantilevers for sensor applications. There are three kinds of forces acting on the CNT cantilever: electrostatic, elastostatic, and van der Waals. The van der Waals forces are significant for values of 50 nm or lower of the gap between the CNT and the ground plate. As both forces, electrostatic and van der Waals, are nonlinear, and the CNT electrostatic actuation is given by AC voltage, the CNT dynamics is nonlinear parametric. The method of multiple scales is used to investigate the system under soft excitations and/or weakly nonlinearities. The frequency-amplitude and frequency-phase behavior are found in the case of primary resonance.

Ultrasound transducers have been used in various applications such as nondestructive testing, acoustic response analysis of vascular tissues, and medical imaging. Most recent applications lead to a demand of more advanced ultrasound generators featuring higher central frequency, wider bandwidth and miniature size. In this paper, a novel ultrasound generator on an optical fiber tip is designed, fabricated and characterized. The ultrasound generator was fabricated by coating several layers of gold nanoparticles (Au NPs) on the end face of a piece of commercially available optical fiber via a layer-by-layer (L-b-L) technique. The Au NPs were synthesized by a traditional sodium citrate reduction method and the diameter of Au NPs was controlled at 20 nm. The ultrasound is generated through photoacoustic procedure. By introducing excitation laser pulses on the Au NPs layer, the energy of laser is converted into the heat through photothermal mechanism. Then, the heat transforms into kinetic energy through thermalelastic mechanism. Thus, ultrasound can be generated. The experiment results showed that this kind of ultrasound generator shows wide bandwidth, high frequency and miniature size. By comparing to the conventional energy absorption material such as graphite, the Au NPs show high energy absorption efficiency and high thermal expansion rate. Therefore, the generator exhibits great potentials in intravascular imaging due to its miniature size.

In recent years, guided wave based structural health monitoring (SHM) techniques have attracted much attention, because they are not only sensitive to small defects but also capable to cover a wide range in plate and pipe like structures. The guided waves in a structure can be generated and sensed by a variety of techniques. This study proposes a new wireless scheme for PZT excitation and sensing where power as well as data can be transmitted via laser. A generated waveform by modulation of a laser is wirelessly transmitted to a photodiode connected to a PZT on the structures. Then, the photodiode converts the light into an electrical signal and excite the PZT and the structure. Then, the reflected response signal received at the sensing PZT is re-converted into a laser, which is wirelessly transmitted back to another photodiode located in the data acquisition unit for damage diagnosis. The feasibility of the proposed power and data transmission scheme has been experimentally investigated in a laboratory setup. Using the proposed technology, a PZT transducer can be attached to a structure without complex electronic components and a power supply.

In this study, a Non-Destructive Evaluation (NDE) method is introduced for evaluating the effects of FRP adhesive joint bond strength subjected to various environmental conditions using electromechanical impedance (EMI) method. The applicability of Fibre Reinforced Plastics (FRP) as a construction material is being globally recognized for their high stiffness and strength to weight ratio and this method proposes a possibility of detecting any strength loss to the adhesive bond without damaging the structure, such as FRP joint itself. PZT (Lead-Zirconate-Titanate) patches were utilized to detect any changes to the bond strength of the FRP adhesive joint exposed to different kinds of environmental conditions by measuring the electrical admittance of the PZT sensors. In addition, a re-usable technique has been introduced with a utilization of magnet to allow multiple sensing of specimens with a single sensor. The results show a possibility of detecting decrease in the bond strength of FRP adhesive using the EMI method.

Recently structural health monitoring (SHM) systems are being focused because they make it possible to assess the health of structures at real-time in many application fields such as aircraft, aerospace, civil and so on. Piezoelectric materials are widely used for sensors of SHM system to monitor damage of critical parts such as bolted joints. Bolted joints could be loosened by vibration, thermal cycling, shock, corrosion, and they cause serious mechanical failures. In this paper, impedance-based method using piezoelectric sensors was applied for real-time SHM. A steel beam specimen fastened by bolts was tested, and polymer type piezoelectric materials, PVDFs were used for sensors to monitor the condition of bolted joint connections. When structure has some damage, for example loose bolts, the impedance of PVDF sensors showed different tendency with normal structure which has no loose bolts. In the case of loose bolts, impedance values are decreased and admittance values are increased.

The impregnated active carbon used in air purification systems degrades over time due to exposure to contamination and mechanical effects (packing, settling, flow channeling, etc.). A novel approach is proposed to detect contamination in active carbon filters by combining the electromechanical impedance spectroscopy (EMIS) and electrochemical impedance spectroscopy (ECIS). ECIS is currently being used to evaluate active carbon filtration material; however, it cannot differentiate the impedance changes due to chemical contamination from those due to mechanical changes. EMIS can detect impedance changes due to mechanical changes. For the research work presented in this paper, Piezoelectric wafer active sensor (PWAS) was used for the EMIS method. Some remarkable new phenomena were unveiled in the detection of carbon filter status. 1. PWAS EMIS can detect the presence of contaminants, such as water and kerosene in the carbon bed 2. PWAS EMIS can monitor changes in mechanical pressure that may be associated with carbon bed packing, settling and flow channeling 3. EMIS and ECIS measurements are consistent with each other and complimentary A tentative simplified impedance model was created to simulate the PWAS-carbon bed system under increasing pressure. Similar impedance change pattern was observed when comparing the simulation results with experimental data.

Surface acoustic wave (SAW) devices are solid-state components in which a wave propagates along the surface of a piezoelectric material. Changes in strain or temperature cause shifts in the acoustic wave speed and/or the path length, enabling SAW devices to act as sensors. We present experimental studies on lithium niobate SAW devices acting as passively-powered devices. Sensitivity, reproducibility, and linearity are excellent when measuring strain at constant temperature, but the devices are also sensitive to temperature changes. We show experimental results of strain measurement incorporating temperature compensation.

This paper explores folded patch antennas for the development of low-cost and wireless smart-skin sensors that monitor the strain in metallic structures. When the patch antenna is under strain/deformation, its resonance frequency varies accordingly. The variation can be easily interrogated and recorded by a wireless reader that also provides power for the antenna operation. The patch antenna adopts a specially selected substrate material with low dielectric constant, as well as an inexpensive off-the-shelf radiofrequency identification (RFID) chip for signal modulation. A thicker substrate increases RFID signal-to-noise ratio, but reduces the strain transfer efficiency. To experimentally study the effect of substrate thickness, two prototype folded patch antennas with different substrate thicknesses have been designed and manufactured. For both prototypes, tensile testing results show strong linearity between the interrogated resonance frequency and the strain experienced by the antenna. Longer interrogation range is achieved with the larger substrate thickness.

Single-walled carbon nanotubes (SWNTs) with their unique electrical properties and large surface area are remarkable materials for detecting low concentration of toxic and hazardous chemicals (both from the gaseous and liquid phases). Ionic adsorbates in water will attach on to SWNTs and drastically alter their electrical properties. Several SWNTs based pH and chemical sensors have been demonstrated. However, most of them require external components to test and analyze the response of SWNTs to ions inside the liquid samples. Here, we report a water quality monitoring sensor composed of SWNTs integrated inside microfluidic channels and on-chip testing components with a wireless transmission board. To detect multiple analytes in water requires the functionalization of SWNTs with different chemistries. In addition, microfluidic channels are used to guide liquid samples to individual nanotube sensors in an efficient manner. Furthermore, the microfluidic system enables sample mixing and separation before testing. To realize the nanosensors, first microelectrodes were fabricated on an oxidized silicon substrate. Next, PDMS micro channels were fabricated and bonded on the substrate. These channels can be incorporated with a microfluidic system which can be designed to manipulate different analytes for specific molecule detection. Low temperature, solution based Dielectrophoretic (DEP) assembly was conducted inside this microfluidic system which successfully bridged SWNTs between the microelectrodes. The SWNTs sensors were next characterized with different pH buffer solutions. The resistance of SWNTs had a linearly increase as the pH values ranged from 5 to 8. The nanosensor incorporated within the microfluidic system is a versatile platform and can be utilized to detect numerous water pollutants, including toxic organics and microorganisms down to low concentrations. On-chip processing and wireless transmission enables the realization of a full autonomous system for real time monitoring of water quality.

Bridges undergo dynamic vehicle-bridge interaction when heavy vehicles drive over them at high speeds. Traditionally, analytical models representing the dynamics of the bridge and vehicle have been utilized to understand the complex vehicle-bridge interaction. Analytical approaches have dominated the field due to the numerous challenges associated with field testing. Foremost among the challenges is the cost and difficulties associated with the measurement of two different systems, i.e. mobile vehicle and static bridge. The recent emergence of wireless sensors in the field of structural monitoring has created an opportunity to directly monitor the vehicle-bridge interaction. In this study, the unrestricted mobility of wireless sensors is utilized to monitor the dynamics of test vehicle driving over a bridge. The integration of the mobile wireless sensor network in the vehicle with a static wireless monitoring system installed in the bridge provides a time-synchronized data set from which vehicle-bridge interaction can be studied. A network of Narada wireless sensor nodes are installed in a test truck to measure vertical vibrations, rotational pitching, and horizontal acceleration. A complementary Narada wireless sensor network is installed on the Geumdang Bridge (Icheon, Korea) to measure the vertical acceleration response of the bridge under the influence of the truck. The horizontal acceleration of the vehicle is used to estimate the position trajectory of the truck on the bridge using Kalman filtering techniques. Experimental results reveal accurate truck position estimation and highly reliable wireless data collection from both the vehicle and the bridge.

Acoustic Emission (AE) sensing was employed to assess the rate of corrosion of steel strands in small scale concrete block specimens. The corrosion process was accelerated in a laboratory environment using a potentiostat to supply a constant potential difference with a 3% NaCl solution as the electrolyte. The embedded prestressing steel strand served as the anode, and a copper plate served as the cathode. Corrosion rate, half-cell potential measurements, and AE activity were recorded continuously throughout each test and examined to assess the development of corrosion and its rate. At the end of each test the steel strands were cleaned and re-weighed to determine the mass loss and evaluate it vis-á-vis the AE data. The initiation and propagation phases of corrosion were correlated with the percentage mass loss of steel and the acquired AE signals. Results indicate that AE monitoring may be a useful aid in the detection and differentiation of the steel deterioration phases, and estimation of the locations of corroded areas.

Corrosion processes in the steel reinforced structures can result in structural deficiency and with time create a threat to human lives. Millions of dollars are lost each year because of corrosion. According to the U. S. Federal Highway Administration (FHWA) the average annual cost of corrosion in the infrastructure sector by the end of 2002 was estimated to be $22.6 billion. Timely remediation/retrofit and effective maintenance can extend the structure's live span for much less expense. Thus the considerable effort should be done to deploy corrosion monitoring techniques to have realistic information on the location and the severity of damage. Nowadays commercially available techniques for corrosion monitoring require costly equipment and certain interpretational skills. In addition, none of them is designed for the real time quality assessment. In this study the crack sensor developed at Missouri University of Science and Technology is proposed as a distributed sensor for real time corrosion monitoring. Implementation of this technology may ease the pressure on the bridge owners restrained with the federal budget by allowing the timely remediation with the minimal financial and labor expenses. The sensor is instrumented in such a way that the location of any discontinuity developed along its length can be easily detected. When the sensor is placed in immediate vicinity to the steel reinforcement it is subjected to the same chemical process as the steel reinforcement. And corrosion pitting is expected to develop on the sensor exactly at the same location as in the rebar. Thus it is expected to be an effective tool for active corrosion zones detection within reinforced concrete (RC) members. A series of laboratory tests were conducted to validate the effectiveness of the proposed methodology. Nine sensors were manufactured and placed in the artificially created corrosive environment and observed over the time. To induce accelerated corrosion 3% and 5% NaCL solutions were used. Based on the test results, the proposed/corrosion distributed sensor is capable of delivering fairly accurate information on the location of a discontinuity along the sensor caused by corrosion pitting. Forensic study was also conducted to validate the concept. In order to test the sensors in real live condition, 27 sensors were prepared to be placed into RC beams. The beams will be subjected to corrosive environment. After that the sensors will be monitored over the time for signs of corrosion.

Offshore platforms' security is concerned since in 1950s and 1960s, and in the early 1980s some important specifications and standards are built, and all these provide technical basis of fixed platform design, construction, installation and evaluation. With the condition that more and more platforms are in serving over age, the research about the evaluation and detection technology of offshore platform has been a hotspot, especially underwater detection, and assessment method based on the finite element calculation. For fixed platform structure detection, conventional NDT methods, such as eddy current, magnetic powder, permeate, X-ray and ultrasonic, etc, are generally used. These techniques are more mature, intuitive, but underwater detection needs underwater robot, the necessary supporting tools of auxiliary equipment, and trained professional team, thus resources and cost used are considerable, installation time of test equipment is long. This project presents a new kind of fast wireless detection and damage diagnosis system for fixed offshore platform using wireless sensor networks, that is, wireless sensor nodes can be put quickly on the offshore platform, detect offshore platform structure global status by wireless communication, and then make diagnosis. This system is operated simply, suitable for offshore platform integrity states rapid assessment. The designed system consists in intelligence acquisition equipment and 8 wireless collection nodes, the whole system has 64 collection channels, namely every wireless collection node has eight 16-bit accuracy of A/D channels. Wireless collection node, integrated with vibration sensing unit, embedded low-power micro-processing unit, wireless transceiver unit, large-capacity power unit, and GPS time synchronization unit, can finish the functions such as vibration data collection, initial analysis, data storage, data wireless transmission. Intelligence acquisition equipment, integrated with high-performance computation unit, wireless transceiver unit, mobile power unit and embedded data analysis software, can totally control multi-wireless collection nodes, receive and analyze data, parameter identification. Data is transmitted at the 2.4GHz wireless communication channel, every sensing data channel in charge of data transmission is in a stable frequency band, control channel responsible for the control of power parameters is in a public frequency band. The test is initially conducted for the designed system, experimental results show that the system has good application prospects and practical value with fast arrangement, high sampling rate, high resolution, capacity of low frequency detection.

In order to be able to monitor the performance and health of a civil structure it is essential to understand how it behaves under different environmental conditions. It is a well documented fact that the structural performance of bridges can be altered considerably when they are subjected to changes in environmental conditions. This paper presents a study investigating the longitudinal movement of the road deck on Tamar Suspension Bridge in Plymouth in the UK over six months. The expansion joint of the bridge deck was instrumented with pull-wire type extensometers. The data were transmitted wirelessly using commercial wireless sensor nodes and collected at a data acquisition laptop computer, which was accessible online for remote monitoring. In addition, position data of various locations on the bridge deck were collected using a Robotic Total Station (RTS). Environmental data, such as the temperature, and structural data, such as cable tension, were acquired from other monitoring systems. Conclusions drawn from a fusion of the bridge deck's longitudinal displacement with other structural and environmental data are discussed in this paper.

This paper presents a technique for local structural health monitoring (SHM) of multiple structural connections by using multi-channel wireless impedance sensor nodes based on Imote2 platform. To achieve the objective, following approaches are implemented. Firstly, an Imote2-based multi-channel wireless impedance sensor node is designed for automated and cost-efficient impedance-based SHM of structural connections. Secondly, an interface washer associate with impedance measurements is designed to monitor bearing stress which is considered as main effect on structural connections. Finally, performances of the multi-channel wireless impedance sensor node and the interface washer are experimentally validated for a bolted connection model. A damage monitoring method using RMSD index of electro-mechanical impedance signatures is used to examine the strength of each individual bolted connection.

Electro-mechanical impedances and guided waves have been widely studied for detecting localized structural damages due to their sensitivity to small structural changes. In this paper, an integrated impedance and guided wave (IIG) based monitoring system is developed to improve the detectability of various damage types under varying temperature. First, a hardware system, called the IIG system, was designed to achieve simultaneous measurements of electro-mechanical impedance and guided wave signals. Then, the effects of temperature on guided waves and electro-mechanical impedances were compensated using the passive imaginary part of the impedance signal. Finally, an automated damage classification algorithm which incorporates temperature compensation was developed. To validate the proposed algorithm, experimental investigations were performed for the detection of bolt loosening and crack in metallic structures subjected to the temperature varying condition, in the range of -20 to 70°C.

A defect detection technique based on time-reversal concept is proposed to detect and locate the defects in a plate structure. Time-reversal imaging method is widely use as an advanced, robust data processing and imaging technique in structure health monitoring to detect the defects. Physically, the time reversed signal will retrace its original path precisely, which means that the signals will be refocused back on the source and defects after we record, time reverse and back propagate the wave signal experimentally or numerically. In this paper, a distributed actuator/sensor network is placed on a square homogeneous plate to generate and collect the wave signals in the plate. The time-reversal technique is then used to interpret the physical meaning of the recorded data and image the defects in the plate. Computer simulations are presented to illustrate the feasibility of the technique in this paper.

Evaluating and recording building conditions in a quantitative manner such as level of deterioration and level of safety has been recognized an important research area and is called structural health monitoring (SHM). The (SHM) system has been studied and developed in our laboratory for many years. Our SHM system consists of a smart sensor network (for data acquisition), a database server, and a diagnosis and prognosis server. The SHM, however, can be extended to more novel roles - detecting and recording the histories of environmental conditions of building structures and flexibly adjust to the environments. Living matter has very flexible and smart adaption mechanisms in nature as categorized into four, sensory adaption, adaption by learning, physiological adaption, and evolutionary adaption. We would like to implement these adaption mechanisms into buildings. We call this concept "biofied building" or "biofication of living spaces" and are working to integrate the concept. We are particularly interested in using robots as sensor agents to gather information of buildings and residents and interact with them. The information obtained by the sensor agent robots is used to record all aspects of life phases of the environment relevant to buildings. This paper presents some aspects of the "biofied building" research conducted at our laboratory.

Wireless sensing technologies have recently emerged as an inexpensive and robust method of data collection in a variety of structural monitoring applications. In comparison with cabled monitoring systems, wireless systems offer low-cost and low-power communication between a network of sensing devices. Wireless sensing networks possess embedded data processing capabilities which allow for data processing directly at the sensor, thereby eliminating the need for the transmission of raw data. In this study, the Volterra/Weiner neural network (VWNN), a powerful modeling tool for nonlinear hysteretic behavior, is decentralized for embedment in a network of wireless sensors so as to take advantage of each sensor's processing capabilities. The VWNN was chosen for modeling nonlinear dynamic systems because its architecture is computationally efficient and allows computational tasks to be decomposed for parallel execution. In the algorithm, each sensor collects it own data and performs a series of calculations. It then shares its resulting calculations with every other sensor in the network, while the other sensors are simultaneously exchanging their information. Because resource conservation is important in embedded sensor design, the data is pruned wherever possible to eliminate excessive communication between sensors. Once a sensor has its required data, it continues its calculations and computes a prediction of the system acceleration. The VWNN is embedded in the computational core of the Narada wireless sensor node for on-line execution. Data generated by a steel framed structure excited by seismic ground motions is used for validation of the embedded VWNN model.

The superacute ear of the parasitoid fly Ormia ochracea has inspired the development of a variety of novel miniature directional microphones for sound source localization, in which the effects of air cavity backing the eardrums are often neglected without validation. In the original testing on the fly ear, the integrity of the air space is shown not to be the key to the intertympnal coupling. However, it does not necessarily mean that the tympanum can be treated as in vacuo, and the effects of the air cavity backing the eardrums have yet to be fully understood. In this article, a normalized version of our previous model of air-backed circular membranes is derived to study the conditions under which the air cavity can be indeed neglected. This model is then used to study a fly-ear inspired directional microphone design with two clamped circular membranes mechanically coupled by a bridge. The performance of the directional microphone with air cavity is evaluated in comparison to its counterpart in vacuo. This article not only provides more insights into the fly ear phenomena, but builds a theoretical foundation on whether and how to take the air cavity into account in the design of pressure sensors and directional microphones in general.

A 2D-axisymmetric finite element analysis (FEA) model was built to simulate an optical fiber-based photoacoustic generator. A layer of absorbing film deposited on the tip of an optical fiber converts the pulsed-laser energy into vibrations, which excite broadband ultrasound waves in the adjacent fluid. Instead of 1D or simplified 2D theoretical solution, this multi-physics FEA model successfully calculates the ultrasound generated by film vibration and fluid heating. Another advantage of this numerical calculation is that the dimensions of fiber and film can be optimized to achieve high photoacoustic conversion efficiency. Two major conclusions were obtained from the simulation: 1) Thicker absorbing film has higher photoacoustic conversion efficiency than thinner film; 2) Shorter laser pulse leads to higher conversion efficiency and higher ultrasound central-frequency. The FEA results provide a practical support to the design of this type of optical fiber photoacoustic generator, and make it possible to have a miniaturized non-destructive testing transducer in the intravascular and intraluminal applications.

This paper presents a study of the variation of natural frequencies and damping ratios of a reinforced concrete building identified from earthquake records during a period of four years. The three storey reinforced concrete building is instrumented with five tri-axial accelerometers. The state-space subspace system identification technique was used to ascertain the natural frequencies and damping ratios considering 50 recorded earthquake response time histories. Correlations were developed between the peak ground acceleration at the base level and peak response acceleration at roof level with identified frequencies and damping ratios. It was found that modal characteristics of the building are sensitive to the level of excitation and response. A general trend of decreasing fundamental frequencies and increasing damping ratios with increased level of shaking was observed. A three dimensional finite element model of the building was developed to study the influences of soil and various structural and non-structural components. To incorporate real in-situ conditions, soil underneath the foundation was modeled using spring elements and non-structural components (cladding, in-fills and partitions) were also included. It was concluded from the investigation that participation of soil and non-structural components towards the seismic response of the building is significant and these should be considered in models to simulate the real behavior.

Modal analysis is an important tool for structural health monitoring based on measured acceleration data, which affects the result of damage identification, safety evaluation and prediction. This paper starts with a brief review of modal identification methods, and then introduces a rigid continuous bridge-Dongying Yellow River Bridge (DYRB) and its structure health monitoring system. Amounts of acceleration data was collected from August to December 2006. The peak picking method is adopted and enhanced with selected accelerometers using average and fitting methods. As a result, the 1st transverse and first 3 vertical frequencies were identified accurately and efficiently. More researches are needed to analyze the different appearance of different mode frequencies and to verify the influence of temperature, moisture, wind, traffic load, etc.

The bolt joints on steel structures are exposed to the possibility of damage, and thus, require intensive care. Usually, periodic inspections are conducted at the cost of time and money. However, it is very difficult to check so many bolts carefully. The purpose of this study is to propose a system that can more efficiently monitor the tightness/looseness of these bolts. The proposed bolt fastening monitoring system is comprised of sensors that are attached to nuts and a data receiving terminal, which gathers information. The reed switch consists of two thin, metallic contacts enveloped in a glass tube and is an electrical switching sensor that is triggered ON or OFF by changes in the surrounding magnetic field. The verification tests showed that bolt loosening can be effectively detected, proving the applicability of this system to the maintenance of the bolt joints of steel structures. The newly developed sensor system is expected to solve conventional sensor problems by enabling measurement of structural members which was not previously possible, thus providing a basis for a new technology in the construction industry by applying IT to construction technology.

Currently 90% of bridges built in California are post-tensioned box-girder. In such structures the steel tendons are the main load-carrying components. The loss of prestress, as well as the presence of defects or the tendon breakage, can be catastrophic for the entire structure. Unfortunately, today there is no well-established method for the monitoring of prestressing (PS) tendons that can provide simultaneous information related to the presence of defects and the level of prestress in a continuous, real time manner. If such a monitoring system were available, considerable savings would be achieved in bridge maintenance since repairs would be implemented in a timely manner without traffic disruptions. This paper presents a health monitoring system for PS tendons in post-tensioned structures of interest to Caltrans. Such a system uses ultrasonic guided waves and embedded sensors to provide simultaneously and in real time, (a) measurements of the level of applied prestress, and (b) defect detection at early grow stages. The proposed PS measurement technique exploits the sensitivity of ultrasonic waves to the inter-wire contact developing in a multi-wire strand as a function of prestress level. In particular the nonlinear ultrasonic behavior of the tendon under changing levels of prestress is monitored by tracking higher-order harmonics at (nω) arising under a fundamental guided-wave excitation at (ω). Moreover this paper also present real-time damage detection and location in post-tensioned bridge joints using Acoustic Emission techniques. Experimental tests on large-scale single-tendon PT joint specimens, subjected to multiple load cycles, will be presented to validate the monitoring of PS loads (through nonlinear ultrasonic probing) and the monitoring of damage progression and location (through acoustic emission techniques). Issues and potential for the use of such techniques to monitor post-tensioned bridges in the field will be discussed.

Our current environment and architecture are mainly static even though our surrounding society is constantly changing. This is why the Biofication of Living Spaces field was created, to get more adaptive and suitable living spaces. On the other hand, human was naturally empowered with a lot of features responding to the environment. His/her 2 ears are powerful tools from which he/she can acquire a lot of information such as the source localization of a sound. Interaural (between both ears) time differences enable a lateral localization and this function can be technologically reproduced. However, the sound localization in the median plane of the head provided amongst others by our external ear called the pinna is yet to be imitated in robotics. The idea of this paper is to build some biomimetic ear prototypes and to analyze theirs influences on a transfer function called Interaural Transfer Function (ITF). Once achieved, attaching these prototyped ears to a sensor agent robot, we aim particularly at a sound localization in the median plane of the robot. However, we will have a quick look at the horizontal sound localization too. Finally, these "ears" on the sensor agent robot will be convenient to get a" much accurate and useful information as possible with only 2 microphones and to use this agent for biofication of living spaces issues.

Current smart buildings are based on scenarios, so they are not prepared for unexpected events. We focus our attention on high adaptability of living matters to environmental changes. "Biofication of Living Spaces" is the concept of creating pleasant living environments using this high adaptability. Biofied room is integrated with sensor agent robots to interact with residents and acquire environmental information. In this research, we propose a highly adaptive algorithm to control the devices automatically. Based on physiological adaption, we can make the algorithm very flexible. As the first step in this research, a prototype of the sensor agent robot is built. Camera, microphone, proximity sensor, laser range-finder are mounted on the robot. As a sensor agent robot follows the residents, it acquires environmental information, and records the interaction between the robot and human. In a suggested control model, a resident is built in the control loop and his/her uncomfortable feeling plays a role of control signal. Following its signal, devices are controlled. Results obtained from the computer simulation show that models are able to maintain the human comfort feeling adaptively. This research suggests an adaptive, fault-tolerant, and energy-saving control models for building spaces, using simple algorithms based on physiological adaption.

The human nervous system (HNS) provides one of the most advanced examples of how to monitor the structural state of a complex system. In attempts to mimic the HNS, a key component has been the development of the sensory receptor. This paper reports on the development of a triboluminescence (TL)-based sensory receptor that converts mechanical energy from fatigue or impact loads and cracks propagation, into optical signals. This sensor system has potential for wireless, in-situ and distributed sensing (WID). The approach differs from existing fiber optic methods in that it does not require any external light source to function. The optical signal is generated through mechanical excitation of the highly triboluminescent ZnS:Mn. It is then transmitted through optical fibers to photomultiplier tubes (PMT) for detecting, quantifying and locating (with further analysis), intrinsic damage in critical engineering structures like concrete bridges. The TL sensory receptor consists of a sensitized portion of a polymer optical fiber (POF) coated with epoxy containing ZnS:Mn crystals. The sensory receptors were then incorporated into cementitious and polymer samples. Results from preliminary investigation showed that the TL sensory receptor gives repeatable responses under multiple impact loads. The triboluminescent intensity of the signal is directly related to the magnitude of the impact load. Results from dynamic mechanical analysis show a reduction in the Tg of the ITOF coating (TSR) with higher concentration of the triboluminescent (ZnS:Mn) crystals for the epoxy system used. There was however significant enhancement of the modulus with increase in the TL crystals. High-performance epoxy system with the principles of particulate composites would be applied in subsequent work to optimize the properties and performance of the TL sensor system.

In the simultaneous localization and mapping (SLAM) problem, one addresses the problem of using mobile sensor platforms or robotic systems to map unknown environments while simultaneously localizing the mobile systems relative to the map. Applications include mapping in oil storage tanks, oil pipes, search and rescue operations, surveillance operations, exploration operations. In this effort, a previously proposed multi-robot localization algorithm is extended to implement SLAM. The decentralized algorithm is demonstrated to work in dynamic robot networks. Experimental and numerical studies conducted with multiple networked mobile platforms are also discussed to validate the analytical findings.

Noise and interference in sensor measurements degrade the quality of data and have a negative impact on the performance of structural damage diagnosis systems. In this paper, a novel adaptive measurement screening approach is presented to automatically select the most informative measurements and use them intelligently for structural damage estimation. The method is implemented efficiently in a sequential Monte Carlo (SMC) setting using particle filtering. The noise suppression and improved damage estimation capability of the proposed method is demonstrated by an application to the problem of estimating progressive fatigue damage in an aluminum compact-tension (CT) sample using noisy PZT sensor measurements.

A damage localization method for plate-like structure is developed based on Lamb waves and matching pursuits method with chirplet dictionary. The matching pursuits method is employed to decompose Lamb wave signals into a linear expansion of several chirplet atoms with a fast realization algorithm. The relationship between Lamb wave's dispersion and chirplet's chirp rate is established, which can be used to identify the modes of Lamb waves. Then a method for damage localization is developed based on the difference between the baseline signals and the damaged signals. The effectiveness and accuracy of the proposed method for identifying the modes and locating defects are demonstrated by the simulation and experimental results of isotropic plate structure and honeycomb sandwich composite structure.

This paper focuses on damage detection, localization and quantification in metallic plates using an array of sensors and an advanced feature extraction algorithm. The Matching Pursuit Decomposition (MPD) algorithm is used for timefrequency signal analysis. Using MPD, measured signals are decomposed into multiple wave modes. The individual wave modes are analyzed to determine the cause of signal changes and the location of the damage. An aluminum plate made of 6061 alloy was instrumented with piezoelectric transducers and used for testing and validation of the proposed concept.

In metallic structures, the first and second most frequent damages incurred are generally cracks and corrosions. Correct damage classification for these two damages is important since their phases can be developed with dissimilar patterns. In this research, damage classification using the Adaboost machine learning algorithm is investigated. To accomplish this, the physical differences of the two types of damages are defined and the most appropriate excitation signal is also determined. Various time-frequency methods are examined with the sensed damage signals to obtain a suitable signal processing method for damage classification. Among the methods examined, the spectrogram is chosen since it provides reliable results for these types of damages. With these results, the damage classification is performed through the Adaboost machine learning algorithm. The training samples for the algorithm are obtained from a finite element tool and experiments are also performed to get the testing samples. The analysis results show that correct damage classification is feasible using time-frequency representations and the Adaboost machine learning algorithm.

The Streicker Bridge at Princeton University campus has been equipped with two fiber-optic sensing technologies: discrete long-gauge sensing, based on Fiber Bragg-Gratings (FBG), and truly-distributed sensing, based on Brillouin Optical Time Domain Analysis (BOTDA). The sensors were embedded in concrete during the construction. The early age measurements, including hydration swelling and contraction, and post-tensioning of concrete were registered by both systems and placed side by side in order to compare their performances. Aside from the usual behavior, an unusual increase in strain was detected by several sensors in various cross-sections. The nature of this event is still under investigation, but preliminary study indicates early-age cracking as the cause. The comparison between the two monitoring systems shows good agreement in the areas where no unusual behavior was detected, but some discrepancies are noticed at locations where unusual behavior occurred and during the early age of concrete. These discrepancies are attributed to the spatial resolution of the distributed monitoring system and the temperature influences at early age. In this paper, general information concerning the Streicker Bridge project is given. The monitoring systems and their specifications are briefly presented. The monitoring data are analyzed and a comparison between the two systems is performed.

Recently a challenging project has been carried out for construction of a national network for safety management and monitoring of civil infrastructures in Korea. As a part of the project, structural health monitoring (SHM) systems have been established on railroad bridges employing various types of sensors such as accelerometers, optical fiber sensors, and piezoelectric sensors. This paper presents the current status of railroad bridge health monitoring testbeds. Emerging sensors and monitoring technologies are under investigation. They are local damage detection using PZT-based electro-mechanical impedances; vibration-based global monitoring using accelerations, FBG-based dynamic strains; and wireless sensor data acquisition systems. The monitoring systems provide real-time measurements under train-transit and environmental loadings, and can be remotely accessible and controllable via the web. Long-term behaviors of the railroad bridge testbeds are investigated, and guidelines for safety management are to be established by combining numerical analysis and signal processing of the measured data.

In consideration of the important role that bridges play as transportation infrastructures, their safety, durability and serviceability have always been deeply concerned. Structural Health Monitoring Systems (SHMS) have been installed to many long-span bridges to provide bridge engineers with the information needed in making rational decisions for maintenance. However, SHMS also confronted bridge engineers with the challenge of efficient use of monitoring data. Thus, methodologies which are robust to random disturbance and sensitive to damage become a subject on which many researches in structural condition assessment concentrate. In this study, an innovative probabilistic approach for condition assessment of bridge structures was proposed on the basis of long-term strain monitoring on steel girder of a cable-stayed bridge. First, the methodology of damage detection in the vicinity of monitoring point using strain-based indices was investigated. Then, the composition of strain response of bridge under operational loads was analyzed. Thirdly, the influence of temperature and wind on strains was eliminated and thus strain fluctuation under vehicle loads is obtained. Finally, damage evolution assessment was carried out based on the statistical characteristics of rain-flow cycles derived from the strain fluctuation under vehicle loads. The research conducted indicates that the methodology proposed is qualified for structural condition assessment so far as the following respects are concerned: (a) capability of revealing structural deterioration; (b) immunity to the influence of environmental variation; (c) adaptability to the random characteristic exhibited by long-term monitoring data. Further examination of the applicability of the proposed methodology in aging bridge may provide a more convincing validation.

This study proposes a new hybrid macro fiber composite/fiber Bragg grating (MFC/FBG) system that can excite and measure guided waves for pipeline monitoring using a single laser source and optical cables removing the need for conventional wire cables. Among various ultrasonic transducers, piezoelectric transducers and FBG sensors have been widely used because of their light weight, non-intrusive nature and compactness. Particularly for pipeline monitoring, a MFC transducer among other piezoelectric transducers is used because of its flexibility and conformability to a curved surface. In addition, conventional electric cables needed for power and data transmission are all replaced by optical cables, alleviating problems such as electromagnetic interference, signal attenuation and vulnerability to noise. A tunable laser is used as a common power source for guided wave generation and sensing. One of two laser beams split from the tunable laser, is used to actuate MFC transducers, and the other beam is used with FBG sensors to measure generated guided waves. The measured signals are processed to identify the existence of defects in pipeline structures such as wall thinning and longitudinal cracks. The feasibility of the proposed hybrid measurement system has been experimentally verified in a laboratory setup.

As the size of wind turbines increases, the early detection of structural instability becomes increasingly important for safety. This paper introduces a fiber Bragg grating-based sensing system for use in multi-MW scale wind turbine health monitoring, and describes the results of preliminary field tests of dynamic strain monitoring of the tower structure of an onshore wind turbine. For this research, the Korea Institute of Energy Research (KIER) and the FiberPro, Inc. cooperated on the development of a wavelength division multiplexing (WDM) Bragg grating sensing system for high-speed strain sensing. The FBG interrogator thus developed can be used in the sensing of high-speed vibration as well as low-speed dynamic strain. In the case of high-speed sensing, the interrogator allows a sampling ratio of over 40 kHz for six linearly arrayed FBG sensors per channel. To monitor the dynamic strain behavior of the tower and substructure of onshore and offshore wind turbines, 41 FBGs were installed on the supporting structures of the wind turbines. As a result, the Bragg grating sensing system showed stable, accurate performance in the thermal chamber test and good dynamic strain sensing performances during the strain monitoring of the tower structure at the Woljeong test-bed wind turbine in Jeju Island.

The importance of real-time detection of cable force during stretching construction can hardly be overstated, especially in long-span space cable system. In this paper, a novel approach to monitor the cable structure health using fiber Bragg grating (FBG) sensors was elaborated and applied in monitoring the tensioning process of suspend-cable dome of Dalian Gymnasium under construction. The encapsulated FBG strain sensors were adhered to the anchor to detect the cable force. Calibration tests conducted prior to leaving factory in order to get the cable force sensitivity coefficient were also presented. The monitoring results of stage stretching construction prove that this cable force monitoring method based on FBG sensors has advantages of easy installation, non-destruction to structure and high precision, showing promising potential in cable structure health monitoring.

This paper demonstrates that existing Structural Health Monitoring (SHM) techniques have potential during the production phase in addition to their application for maintenance and for in-flight monitoring. Flaws occur during composite fabrication in industry, due to an imperfect process control and human errors. This decreases production efficiency and increases costs. In this paper, the monitoring of Lamb waves in unidirectional carbon fibre (UD-CFRP) prepreg material is demonstrated using both Fibre Bragg Gratings (FBG)s and piezolectric acoustic sensors, and that these SHM sensors may be used for flaw detection and production monitoring. The detection of Lamb waves in a one ply thick sheet of prepreg UD-CFRP material is demonstrated for an FBG sensor aligned with the carbon fibre orientation and bonded to the surface of the prepreg, Furthermore, the velocity of Lamb waves in prepreg UD-CFRP in different orientations is investigated. Finally the successful detection of a material crack in a prepreg UD-CFRP sheet using the Lamb wave detection method is demonstrated.

The objective of this work is to develop a system for monitoring the structural integrity of composite airframe structures by strain mapping over the entire lifecycle of the structure. Specifically, we use fiber Bragg grating sensors to measure strain in a pressure bulkhead made of carbon fiber reinforced plastics (CFRPs) through a sequence of lifecycle stages (molding, machining, assembly, operation and maintenance) and detect the damage, defects, and deformation that occurs at each stage from the obtained strain distributions. In previous work, we have evaluated strain monitoring at each step in the FRP molding and machining stages of the lifecycle. In the work reported here, we evaluate the monitoring of the changes in strain that occur at the time of bolt fastening during assembly. The results show that the FBG sensors can detect the changes in strain that occur when a load is applied to the structure during correction of thermal deformation or when there is an offset in the hole position when structures are bolted together. We also conducted experiments to evaluate the detection of damage and deformation modes that occur in the pressure bulkhead during operation. Those results show that the FBG sensors detect the characteristic changes in strain for each mode.

This paper describes the application of a novel actuator/sensor technology for monitoring concrete at early age. A device is designed to generate and detect highly nonlinear solitary waves (HNSWs) in a chain of steel beads. Two experiments were conducted. In the first experiment, the propagation of the HNSWs in the chain was recorded. In particular, the reflections at the interface between the chain and a composite layer consisting of a thin aluminum plate and the concrete were observed. It was found that the travelling time of HNSWs of the reflected pulses depend on the boundary conditions of the chain, so it changes as the stiffness and strength of concrete develop during the hydration process. In the second experiment, a similar actuator was used to transmit mechanical waves inside concrete. These waves were then detected by an embedded commercial transducer. The change of frequency components of the stress waves in the fresh concrete was monitored and used to interpret the initial set of the concrete. The results of these two experiments were compared to outcomes of the penetration resistance test (ASTM C403) conventionally used to determine the time of setting. We found that the proposed nondestructive evaluation method can be used in fresh concrete although more tests are needed to prove repeatability under various concrete mixtures.

This paper proposed a distributed seismic damage sensing network using PZT-based smart aggregates for RC building structures, aiming to monitor the structural local seismic response. The stress history and the crack patterns of the structure under earthquake load in positions of interest are the two key issues to be monitored. The concept of the seismic damage mechanism monitoring by means of direct piezoelectric effect and stress wave propagation evaluation is proposed. The proposed smart aggregates consist of PZT sensing element and the stone holding matrix. Its senssitivity for dynamic compressive stress induced by earthquake load and the influence of pre-stress from dead load of building structures after embedment are discussed. It is shown that the proposed smart aggregates suits for seismic stress monitoring and the static pre-stress has no significant influence on its performance.

An objective of the structural health monitoring system is to identify the state of the structure and to detect its damages after a major event, such as the earthquake, to ensure the reliability and safety of structures. Innovative analysis techniques for the damage detection of structures have been extensively studied recently. However, practical and effective damage identification techniques remain to be developed for nonlinear structures, in particular nonlinear hysteretic reinforced concrete (RC) structures. In this paper, in addition to the equivalent time-varying linear model, a smooth hysteretic model with stiffness and strength degradations and with the pinching effect is used to represent the dynamic characteristics of reinforced concrete (RC) frames. A system identification technique capable of detecting damages in nonlinear structures, referred to as the adaptive quadratic sum-square error with unknown inputs (AQSSE-UI), is used to track the degradation of the time-varying parameters of nonlinear RC frames. The performance of the AQSSE-UI technique is also demonstrated by the experimental data. Six identical 1/2-scale one-story two-bay RC frames have been designed and tested on the shake table at NCREE, Taiwan. Each RC frame was subject to different levels of seismic excitations followed by cyclic loads until failure. Test data were used to verify the capability of the AQSSE-UI technique in detecting structural damages. Experimental results demonstrate that the AQSSE-UI technique is quite effective in tracking (i) the stiffness degradation of equivalent linear time-varying structure, and (ii) the non-linear hysteretic parameters with stiffness and strength degradations.

Many civil and mechanical engineering structures exhibit nonlinear hysteretic behavior when subject to dynamic loads, such as earthquakes. The modeling and identification of non-linear hysteretic systems with stiffness and strength degradations is a practical but challenging problem encountered in the engineering field. A recently developed technique, referred to as the adaptive quadratic sum-square error with unknown inputs (AQSSE-UI), is capable of identifying time dependant parameters of nonlinear hysteretic structures. In this paper, the AQSSE-UI technique is applied to the parametric identification of nonlinear hysteretic reinforced concrete structures with stiffness and strength degradations, and the performance of the AQSSE technique is demonstrated by the experimental test data. A 1/3 scaled 2-story RC frame has been tested experimentally on the shake table at NCREE, Taiwan. This 2-story RC frame was subject to different levels of ground excitations back to back. The structure is firstly considered as an equivalent linear model with time-varying stiffness parameters, and the tracking of the degradation of the stiffness parameters is carried out using the AQSSE-UI technique. Then the same RC frame is considered as a nonlinear hysteretic model with inelastic hinges following the generalized Bouc-Wen model, and the time-varying nonlinear parameters are identified again using the AQSSE-UI technique. Experimental results demonstrate that the AQSSE technique is quite effective for the tracking of: (i) the stiffness degradation of linear structures, and (ii) the non-linear hysteretic parameters with stiffness and strength degradations.

Helicopter uses a rotor system to generate lift, thrust and forces, and its aerodynamic environment is generally complex. Unsteady aerodynamic environment arises such as blade vortex interaction. This unsteady aerodynamic environment induces vibratory aerodynamic loads and high aeroacoustic noise. The aerodynamic load and aeroacoustic noise is at N times the rotor blade revolutions (N/rev). But conventional rotor control system composed of pitch links and swash plate is not capable of adjusting such vibratory loads because its control is restricted to 1/rev. Many active control methodologies have been examined to alleviate the problem. The blade using active control device manipulates the blade pitch angle with N/rev. In this paper, Active Trailing-edge Flap blade, which is one of the active control methods, is designed to reduce the unsteady aerodynamic loads. Active Trailing-edge Flap blade uses a trailing edge flap manipulated by an actuator to change camber line of the airfoil. Piezoelectric actuators are installed inside the blade to manipulate the trailing edge flap.

This paper presents an investigation of 2-D power and energy transduction in piezoelectric wafer active sensors (PWAS) for structural health monitoring (SHM). After a literature review of the state of the art, we developed a model of 2-D power and energy transduction of PWAS attached to structure. The model is an extension of our previously presented 1-D model. It allows examination of power and energy flow for a circular crested wave pattern. The model assumptions include: (a) 2-D axial and flexural wave propagation; (b) ideal bonding (line-force) connection between PWAS and structure; (c) ideal excitation source at the transmitter PWAS and fully-resistive external load at the receiver PWAS (d) crested wave energy spread out. Wave propagation method for an infinite boundary plate, electromechanical energy transformation of PWAS and structure, and wave propagation energy spread out in 2-D plate were considered. The parametric study of PWAS size, impedance match gives the PWAS design guideline for PWAS sensing and power harvesting applications. In pitch-catch PWAS application, the frequency response functions of a circular PWAS are developed for voltage in consideration with the receiver capacitance and external resistive loads.

Recently, novel methods to monitor the strength development of concrete during curing process have been reported based on electro-mechanical impedance measurement using piezoelectric sensors. However, the previous research works could not provide the information about the absolute strength of concrete. In order to estimate the absolute strength directly, an embedded piezoelectric sensor system based strength monitoring technique was proposed in this study. To avoid the degradation of a piezoelectric sensor due to external and internal impacts and/or environmental variations, the piezoelectric sensor soldered with a lead wire is inserted into a small concrete block and then this block is embedded in larger concrete specimen. While the concrete is cured, the electro-mechanical impedance and guided wave signals, self-measured from the embedded piezoelectric sensor, would be changed because those are related to the material properties of the concrete such as the strength and the stiffness. Hence, the strength of concrete can be monitored by analyzing the root-mean-square-deviation (RMSD) of the impedance signals and the amplitude variation of the guided wave signals. Specific equations to estimate the strength of the concrete are derived using a regression analysis based on the features extracted from the signal variations. Finally, to verify the effectiveness of the proposed approach, a series of experimental studies using miscellaneous concrete specimens are conducted and further research issues will be discussed for real-world implementation of the proposed approach.

A method for monitoring fatigue cracks in thin-walled shell-structures using piezoelectric polyvinylidene fluoride (PVDF) films is presented. By means of a spatially resolved measurement, it allows the simultaneously localization of the crack tip and determination of the K - factors by solving the resulting inverse problem. In previous publications [1], [2] only the K_I - factor as well as the position of the crack tip could be determined with sufficient accuracy but not the K_II- factor. Therefore, the concept will be tested and verified using the example of a crack in an infinite plate. From that we deduce some recommendations for the electrode placement and the solution of the inverse problem. In addition, a first experiment of a cracked aluminum specimen is reported.

Lead Zirconate Titanate Oxide (PbZr_xTi_1-xO₃ or PZT) thin films have been widely used in various microsensors and microactuators for their high bandwidth and sensitivity. A typical configuration is to use a Pt/Ti bi-layer as the bottom electrode. Before the PZT film is deposited, Pt/Ti bi-layer must be annealed at high temperature (e.g., 800°C) to obtain a condensed structure with a rough micro surface texture. A condensed Pt/Ti structure prevents delamination of the bottom electrode, while a rough micro surface texture ensures PZT thin films anchored firmly onto the bottom electrodes. Although the annealing process is necessary, its high temperature causes Pt/Ti bi-layer to become porous, thus degrading electrical and ferroelectric properties of the PZT thin films. In this paper, we present a non-porous Pt/Ti bottom electrode via a two-step deposition and annealing process. The first step is the traditional fabrication process that leads to a porous Pt/Ti electrode. A second round of deposition and annealing then seals the pores and strengthens the electrode. To evaluate the performance of the non-porous bottom electrode, PZT thin films with porous and non-porous bottom electrodes are fabricated simultaneously. Experimental measurements show that piezoelectric constant d₃₃ of the PZT film increases from 10 pC/N to 20 pC/N when the bottom electrode is changed from the porous to non-porous electrode.

A monitoring human breath has been seen as an important source of factor for vital status for emergency medical service. The monitoring of breathing has been tested and evaluated in a possible breath condition of a person to be monitored. A hetero-core optical fiber humidity sensor was developed for in order to monitor relative humidity in a medial mask. Elements for determent breath condition were extracted from the light intensity changing at some human breath condition, which were Breath depth, Breath cycle, Breath time and Check breathing. It is found that the elements had differences relative to normal breathing.

We present a surface-mountable miniature Fabry-Perot (FP) pressure sensor that exploits the total internal reflection at a polished 45° angled fiber end face to swerve the optical axis by 90°. Optical analysis of the sensor system is performed based in ABCD method in terms of intensity of the beams reflected from each mirror and visibility of the sensor compared to conventional sensor system. One unique feature of the surface-mountable sensor is its embeddability with minimum intrusiveness to the system. By using the fiber as a waveguide, as well as an inherent mask for photolithography, a self-aligned FP cavity is constructed. A polymer-metal composite diaphragm is employed as a deflection diaphragm for pressure sensing which enables achieving higher sensitivity and low-cost fabrication over silicon diaphragm. The sensor exhibits a good linearity over the designed pressure range. Fiber Bragg grating is embedded in the vicinity of the pressure sensor to solve the problem of cross sensitivity between pressure and temperature by measuring the temperature of the system and compensating the temperature effect. This sensor is expected to impact many fronts where temperature effect should be considered to perform reliable and accurate pressure measurement with minimum intrusiveness.

Power transformers are among the most valuable assets of the electrical grid. Since the largest units cost in the order of millions of dollars, it is desirable to operate them in such a manner that extends their remaining lives. Operating these units at high temperature will cause excessive insulation ageing in the windings. Consequently, it is necessary to study the thermal performance of these expensive items. Measuring or estimating the winding temperature of power transformers is beneficial to a utility because this provides them with the data necessary to make informed decisions on how best to use their assets. Fiber optic sensors have recently become viable for the direct measurement of winding temperatures while a transformer is energized. However, it is only practical to install a fiber optic temperature sensor during the manufacture of a transformer. For transformers operating without fiber optic sensors, the winding temperature can be estimated with calculations using the temperature of the oil at the top of the transformer tank. When the oil temperature measurement is not easily available, the temperature of the tank surface may be used as an alternative. This paper shows how surface temperature may be utilized to estimate the winding temperature within a transformer designed for research purposes.

Condition and growth of trees are considered to be important in monitoring global circulation with heat and water, additionally growth of trees are affected by CO₂ and air pollutants. On the other hand, since growth of plants is affected by surrounding climates, it is expected that real-time monitoring of crop plants growing makes possible quantitative agricultural management. This study proposed methods in measuring tree growth using hetero-core optical fiber sensors which are suitable for long-term, remote and real-time monitoring in wide area due to their features such as independence from temperature fluctuation and weather condition in addition to advantages of an optical fiber. Two types of sensors were used for that purpose. One of them was a dendrometer which measured radial changes of a tree stem and the other was elastic sensor which was to measure growth of smaller tree such as crop plant. In our experiment, it was demonstrated that the dendrometer was capable of measuring the differences of tree growing trend in period of different seasons such as growing rates 2.08 mm between spring and summer and 0.21 mm between autumn and winter, respectively. Additionally, this study had proposed the method of measuring crop plant growing by the elastic sensor because of its compact and light design and monotonious changes in optical loss to the amount of expansion and contraction.

In this paper, we demonstrate a fabrication method for ordered self-assembly using pre-programmed shape memory polymer (SMP) as the substrate in an organic-inorganic bi-layer structure. By heating the hybrid structure above the SMP's shape recovery temperature, the substrate expands because of positive CTE in one direction, while in the perpendicular direction it shrinks due to shape memory effect overpowering thermal expansion. Consequently, the thin film is subjected to an orthogonal compression-tension stress field and forms unidirectional wavy patterns. We further validate our conceptual design by adjusting the strain level of pre-programmed SMP substrates. The present study is expected to offer a convenient and simple path of fabricating unidirectional wavy patterns. Moreover, selective growth and ordering of patterns can become possible.

This paper quantifies the sensing capabilities of novel smart materials in an effort to improve the performance, better understand the physics, and enhance the safety of parachutes. Based upon a recent review of actuation technologies for parachute applications, it was surmised that the actuators reviewed could not be used to effectively alter the drag or lift (i.e. geometry, porosity, or air vent openings) of a parachute during flight. However, several materials showed potential for sensing applications within a parachute, specifically electrically conductive fabrics and dielectric electro-active polymers. This paper introduces several new conductive fabrics and provides an evaluation of the sensing performance of these smart materials based upon test results using mechanical testing and digital image correlation for comparison.

Integrity of in-service engineering structures is prone to fatigue damage over their lifespan. Majority of the currently existing elastic-wave-based damage identification techniques have been developed and validated for damage at macroscopic levels, by canvassing linear properties of elastic waves such as attenuation, transmission, reflection and mode conversion. However the real damage in engineering structures often initiates from fatigue crack, presenting highly nonlinear characteristics under cyclic loads. It is of great significance but vast challenge to detect fatigue damage of small dimension at its initial stage. In this study, traditional elastic-wave-based damage identification techniques were first employed with an attempt to detect fatigue crack initiated from a notch in an aluminium plate with the assistance of a signal correlation analysis, to observe the deficiency of the approach. Then the higher-order harmonic wave generation was used to exploit the nonlinear characteristics of acousto-ultrasonic waves (Lamb waves), whereby the fatigue damage was characterised. Results show that nonlinear characteristics of acousto-ultrasonic waves can facilitate more effective detection of fatigue damage than linear signal features such as wave reflection, transmission or mode conversion.

A nanoscale active fiber composites (NAFCs) based acoustic emission (AE) sensor with high sensitivity is developed. The lead zirconate titanate (PZT) nanofibers, with the diameter of approximately 80 nm, were electrospun on a silicon substrate. Nanofibers were parallel aligned on the substrate under a controlled electric field. The interdigitated electrodes were deposited on the PZT nanofibers and packaged by spinning a thin soft polymer layer on the top of the sensor. The hysteresis loop shows a typical ferroelectric property of as-spun PZT nanofibers. The mathematical model of the voltage generation when the elastic waves were reaching to sensor was studied. The sensor was tested by mounting on a steel surface and the measured output voltage under the periodic impact of a grounded steel bar was over 35 mV. The small size of the developed PZT NAFCs AE sensor shows a promising application in monitoring the structures by integrated into composites.

A Frequency Steerable Acoustic Transducer (FSAT) is proposed for directional sensing of guided waves. The considered FSAT design is characterized by a spiral configuration in wavenumber domain, which leads to a spatial arrangement of the sensing material producing output signals whose dominant frequency component is uniquely associated with the direction of incoming waves. The resulting spiral FSAT can be employed both for directional sensing and generation of guided waves, without relying on phasing and control of a large number of channels. The analytical expression of the shape of the spiral FSAT is obtained through the theoretical formulation for continuously distributed active material as part of a shaped piezoelectric device. Testing is performed by forming a discrete array through the points of the measurement grid of a Scanning Laser Doppler Vibrometer. The discrete array approximates the continuous spiral FSAT geometry, and provides the flexibility to test several configurations. The experimental results demonstrate the strong frequency dependent directionality of the spiral FSAT and suggest its application for frequency selective acoustic sensors, to be employed for the localization of broadband acoustic events, or for the directional generation of Lamb waves for active interrogation of structural health.

In this paper, a tele-gait monitoring system which consists of an inertial measurement unit (IMU) and Smart Shoes is proposed for gait monitoring and rehabilitation. In our previous works, a mobile gait monitoring system (MGMS) was proposed, which utilized the ground reaction forces (GRFs) measured by Smart Shoes. Although the GRF patterns measured by the MGMS provide useful information for the diagnoses of a patient's walking motions, Smart Shoes do not measure the position of the feet, which is necessary for a complete walking motion diagnosis. In the proposed tele-gait monitoring system, an IMU is used in addition to Smart Shoes for a complete observation of walking motions. By analyzing the signals measured by the IMU and Smart Shoes, it is possible to thoroughly diagnose the patient's walking motion, including: the trajectory of the foot, the walking distance, and the length of each stride. Furthermore, the proposed gait monitoring system makes use of the Internet such that physical therapists can monitor their patients' status anywhere anytime.

Harvested vibration energy is typically considered as an alternative power source for sensors' networks for health and usage monitoring in civil and mechanical structures. The longevity, and hence the efficacy, of these sensors is severely limited by the levels of generated power. Piezoelectric vibration harvesters have been widely used given their energy conversion ability and relatively high mechanical to electrical coupling properties. Several techniques can be applied to improve these properties and to cancel external environmental effects such as temperature variations. In this paper, the temperature compensation of the response characteristics of a bimorph cantilever Lead zirconate titanate (PZT) piezoelectric beam, through a combination with shape memory alloys, is studied. A mathematical model, based on onedimensional linear piezoelectricity equations and one dimensional constitutive behavior of shape memory alloys, is derived. The model describes the effect of temperature deviations on the theoretical harvestable energy levels as well as the compensation methodology. Proof of concept experimental results are also presented. The voltage response transfer functions are measured at different temperatures to show the induced effect by shape memory alloys.

In this paper, we propose a new decentralized method for structural health monitoring based on substructure dynamical parameter identification, which can be executed in parallel on multiple smart sensor nodes. A decentralized Kalman filter algorithm is applied for modal parameter identification of structures using multi-input and multi-output ARX model. Furthermore, network communication topology is investigated using the substructure approach for finding a practical application of the decentralized algorithm. Numerical simulation studies are carefully performed for three types of network topologies and two types of model structures. Identification tests using the seismic observation data of existing 5-story building are also conducted. The results show the feasibility of the proposed decentralized method.

A comprehensive physics-based model for predicting the performance of the miniature wind turbine (MWT) for power wireless sensor systems was proposed in this paper. An approximation of the power coefficient of the turbine rotor was made after the turbine rotor performance was measured. Incorporation of the approximation with the equivalent circuit model which was proposed according to the principles of the MWT, the overall system performance of the MWT was predicted. To demonstrate the prediction, the MWT system comprised of a 7.6 cm thorgren plastic propeller as turbine rotor and a DC motor as generator was designed and its performance was tested experimentally. The predicted output voltage, power and system efficiency are matched well with the tested results, which imply that this study holds promise in estimating and optimizing the performance of the MWT.

Unmanned Aerial Vehicles (UAVs) have gained popularity over the past few years to become an indispensable part of aerial missions that include reconnaissance, surveillance, and communication [1]. As a result, advancements in small jet-engine performance are needed to increase the performance (range, payload and efficiency) of the UAV. These jet engines designed especially for UAV's are characterized by thrust force on the order of 100N and due to their size and weight limitations, may lack advanced flow control devices such as IGV [2]. The goal of the current study was to present a conceptual design of an IGV smart-material based actuation mechanism that would be simple, compact and lightweight. The compressor section of an engine increases the pressure and conditions the flow before the air enters the combustion chamber [3]. The airflow entering the compressor is often turbulent due to the high angle of incidence between engine inlet and free-stream velocity, or existing atmospheric turbulence. Actuated IGV are used to help control the relative angle of incidence of the flow that enters the engine compressor, thereby preventing flow separation, compressor stall and thus extending the compressor's operating envelope [4]. Turbine jet- engines which employ variable IGV were developed by Rolls Royce (Trent DR-900) and General Electric (J79).

As wind energy plays an increasingly important role in the US and world electricity supply, maintenance of wind turbines emerges as a critical issue. Because of the remote nature of wind turbines, autonomous and robust health monitoring techniques are necessary. Detecting faults in complex systems such as wind turbine gearboxes remains challenging, even with the recently significant advancement of sensing and signal processing technologies. In this paper, we collect time domain signals from a gearbox test bed on which either a healthy or a faulty gear is installed. Then a harmonic wavelet based method is used to extract time-frequency features. We also develop a speed profile masking technique to account for tachometer readings and gear meshing relationship. Features from multiple sources are then fused together through a statistical weighting approach based on principal component analysis. Using the fused timefrequency features, we demonstrate that different gear faults can be effectively identified through a simple decision making algorithm.

Recently, vibration requirements are getting stricter as precise equipments need more improved vibration environment to realize their powerful performance. Though the passive pneumatic vibration isolation tables are frequently used to satisfy the rigorous vibration requirements, the specific vibration problem, especially continuous sinusoidal or periodic vibration induced by a rotor system of other precise equipment, a thermo-hygrostat or a ventilation system, is still left. In this research, the application procedure of Filtered-X LMS algorithm to pneumatic vibration isolation table with piezo-stack actuators is proposed to enhance the isolation performance for the continuous sinusoidal or periodic vibration. In addition, the experimental results to show the isolation performance of proposed system are also presented together with the isolation performance of passive pneumatic isolation table.

Eight different nonlinear systems are considered in order to overcome the main drawback of existing vibration generator, the narrow bandwidth problem. Based on the static and dynamic analysis of these systems, the typical nonlinear softening and hardening Duffing oscillator systems have been selected for further consideration. The limitations of the selected systems are presented here. The softening system becomes unstable when the forcing amplitude exceeds the critical value, and the response amplitudes of the hardening system will be reduced by the extra stiffness introduced by the nonlinear term. Therefore, a mechanical system, which exhibits the dynamic characteristics of the softening system at the low force level while showing as the hardening with the increasing forcing, is proposed. With the assistance of the numerical method, it can be observed that the frequency response curves (FRCs) of the system will lean to left hand side of the linear resonance frequency when the forcing amplitude is comparatively low, and lean to the right when the input force can burst the energy barrier. More dynamic behaviors are discussed. According to the analysis, the proposed nonlinear system can be the solution to the narrow bandwidth problem.

Identifying variations in system parameters is a crucial task in many diagnostic engineering applications. Although modal methods are typically employed to quantify such parametric variations in dynamical systems, sensitivity vector fields (SVFs) provide an alternative that can be more effective under certain circumstances. Currently, the application of SVFs has been restricted to systems in which it is possible to know the entire state. For physical systems where only a few components of the state can be measured, this represents a significant obstacle to the adoption of SVFs. Fortunately, even with only partial knowledge of the state, time-delay coordinate embedding can be used to reconstruct the attractors of a nonlinear system. This paper presents techniques for computing SVFs in such embedded coordinates, making their application practical in a much wider range of physical systems. Successful construction of embedded SVFs for various simulated time series demonstrate the reliability of the techniques proposed.

The purpose of this study is to develop a better understanding of the damage progression in composite materials undergoing tension loading, while pushing the boundaries on measurements to identify material damage. Several SHM methods are used to detect the types of damage that are observed in each test. A Digital Image Correlation system is used to measure the surface strain throughout the test and also the residual strain after each loading cycle. The residual strain is used as an indicator for the presence of damage in the structure. Piezoelectric wafer active sensors (PWAS) are bonded to the composite material and are used to detect damage using Electromechanical Impedance Spectroscopy (EMIS). The EMIS method analyzes the changes in the structural resonances and anti-resonances. The Electrochemical Impedance Spectroscopy (ECIS) method is also used to detect damage. This method uses the impedance of the structure to determine the state of the structure. As the damage progresses in the composite, the impedance across the thickness will change.

A methodology based on Lamb wave analysis and time-frequency signal processing has been developed for damage detection and structural health monitoring of composite structures. Because the Lamb wave signals are complex in nature, robust signal processing techniques are required to extract damage features. In this paper, Lamb wave mode conversion is used to detect the damage in composite structures. Matching pursuit decomposition algorithm is used to represent each Lamb wave mode in the time-frequency domain. Results from numerical Lamb wave propagation simulations and experiments using orthotropic composite plate structures are presented. The capability of the proposed algorithm is demonstrated by detecting seeded delaminations in the composite plate samples. The advantages of the methodology include accurate time-frequency resolution, robustness to noise, high computational efficiency and ease of post-processing.

With research in structural health monitoring (SHM) moving towards increasingly complex structures for damage interrogation, the placement of sensors is becoming a key issue in the performance of the damage detection methodologies. For ultrasonic wave based approaches, this is especially important because of the sensitivity of the travelling Lamb waves to material properties, geometry and boundary conditions that may obscure the presence of damage if they are not taken into account during sensor placement. The framework proposed in this paper defines a sensing region for a pair of piezoelectric transducers in a pitch-catch damage detection approach by taking into account the material attenuation and probability of false alarm. Using information about the region interrogated by a sensoractuator pair, a simulated annealing optimization framework was implemented in order to place sensors on complex metallic geometries such that a selected minimum damage type and size could be detected with an acceptable probability of false alarm anywhere on the structure. This approach was demonstrated on a lug joint to detect a crack and on a large Naval SHM test bed and resulted in a placement of sensors that was able to interrogate all parts of the structure using the minimum number of transducers.

While semi-active suspension systems have been shown to be effective in the real-time optimization of vehicle ride and handling, these systems also present a means for system interrogation and damage detection. This research demonstrates the ability to monitor the condition of a ground vehicle by utilizing a passively tunable suspension system to systematically alter the suspension parameters in order to probe the system response. By modulating the suspension parameters at a particular corner of the vehicle, or combinations of corners, selected operational modes of the sprung and unsprung masses can be probed providing an increased ability to detect and locate damage in certain vehicle components. The experimental data presented demonstrates that the ability to detect damage was increased by 16.3% and 22.5% for the two simulated damage conditions using the suspension probing technique. A major benefit of the active probing method described in this paper is that the associated damage index is based only on one specific vehicle's response over time. A massive database of historical data from similar vehicles is not required. The active probing method also benefits from transducers already integrated for the control of a typical semi-active suspension system. The benefits of an on-board health monitoring system can be realized with minimal added cost, by adding only a small number of additional sensors. The ability to detect vehicle damage during operation can be extremely advantageous in terms of safety and condition-based maintenance.

In order to maintain healthy structures, it is important to find means of Structural Health Monitoring (SHM) that are effective, economical, and easy to implement. A localized damage detection algorithm based on measured data from a densely clustered sensor network has been previously presented. This method has been validated using both wired and wireless accelerometers applied to a small-scale idealized beam-column connection. However, to progress towards realworld implementation, there is a need to verify that this algorithm is effective and applicable for full-scale structures with unknown progressive damage. Moreover, it is important to verify the use of other commonly used sensor types, in this case strain gauges, which represent different response parameters. In this paper, the performance of the damage detection algorithm is evaluated for a large-scale steel moment connection constructed at the ATLSS Center at Lehigh University, which was being tested for use in an earthquake-prone structure. This test specimen was instrumented with a network of strain gauges and cyclically loaded to failure. The strain responses from the test are analyzed using the local damage detection algorithm. The resulting changes in the damage indicating parameters compared to the damage observations to both determine the point of earliest detection and to verify the locations of the damage. By successfully implementing this local damage detection algorithm using strain gauges instrumented on a large-scale structure, the versatility of this method is demonstrated.

Damage identification still remains a challenging but critical task in structural health monitoring field though many algorithms have been proposed in the past decades. Among them, methods based on elemental modal strain energy (MSE) change between pre- and post-damage are promising ones owing to their precision and robustness according to the studies conducted in the literature. Stubbs damage index method (SDIM) and Modal strain energy change ratio (MSECR) method are two representative approaches because of their different but original assumptions, having attracted considerable attention and thus been continuously improved by researchers. In this paper their efficiencies of damage localization and quantification in single- and multi- damage scenarios are compared through numerical study. Results show that, in general, MSECR method performs better than SDIM, especially in damage quantification. Theoretical discussion and improvements for SDIM are proposed and verified.

Most modern railways use Continuous Welded Rail (CWR). A major problem is the almost total absence of expansion joints that can create buckling in hot weather and breakage in cold weather due to the rail thermal stresses. In June 2008 the University of California, San Diego (UCSD), under the sponsorship of a Federal Railroad Administration (FRA) Office of Research and Development (R&D) grant, began work to develop a technique for in-situ measurement of stress and detection of incipient buckling in CWR. The method under investigation is based on ultrasonic guided waves, and the ultimate goal is to develop a prototype that can be used in motion. A large-scale full rail track (70 feet in length) has been constructed at UCSD's Powell Structural Laboratories, the largest laboratories in the country for structural testing, to validate the CWR stress measurement and buckling detection technique under rail heating conditions well controlled in the laboratory. This paper will report on the results obtained from this unique large-scale test track to date. These results will pave the road for the future development of the rail stress measurement & buckling detection prototype.

Developing technologies that would enable NASA to sample rock, soil, and ice by coring, drilling or abrading at a significant depth is of great importance for a large number of in-situ exploration missions as well as for earth applications. Proven techniques to sample Mars subsurface will be critical for future NASA astrobiology missions that will search for records of past and present life on the planet, as well as the search of water and other resources. A deep corer, called Auto-Gopher, is currently being developed as a joint effort of the JPL's NDEAA laboratory and Honeybee Robotics Corp. The Auto-Gopher is a wire-line rotary- hammer drill that combines rock breaking by hammering using an ultrasonic actuator and cuttings removal by rotating a fluted bit. The hammering mechanism is based on the Ultrasonic/Sonic Drill/Corer (USDC) that has been developed as an adaptable tool for many of drilling and coring applications. The USDC uses an intermediate free-flying mass to transform the high frequency vibrations of the horn tip into a sonic hammering of a drill bit. The USDC concept was used in a previous task to develop an Ultrasonic/Sonic Ice Gopher. The lessons learned from testing the ice gopher were implemented into the design of the Auto-Gopher by inducing a rotary motion onto the fluted coring bit. A wire-line version of such a system would allow penetration of significant depth without a large increase in mass. A laboratory version of the corer was developed in the NDEAA lab to determine the design and drive parameters of the integrated system. The design configuration lab version of the design and fabrication and preliminary testing results are presented in this paper.

Mating parts often experience repetitive relative motion termed fretting which results in friction, wear, as well as acoustic emission signals. Acoustic emission signals have the potential for monitoring the condition of the surfaces participating in the frictional process. In structural health monitoring studies, where the focus is on quantifying crack growth related acoustic emission signals, the signals generated by other mechanisms give rise to undesirable false positives. A major source of such false positives are fretting related signals. The present paper describes an experimental approach for characterizing the friction related acoustic emission signals. A test fixture is developed to obtain fretting related signals under controlled conditions. The waveforms are analyzed to extract features common to these signals. A comparison of acoustic emission signals related to fretting and crack growth is provided.

Shape Memory Alloy (SMA) spring has great potential as a component of compact actuating system. Trade-off between recovery force and deformation range due to phase transformation is possible through the control of spring design parameters such as spring diameter. Deformation behavior of SMA spring is complicated function in three-dimensional space because its behavior is a combination of torsion, bending and stretching action. Therefore, three dimensional analysis of SMA spring is the most accurate simulation procedure. In this paper, modified one-dimensional Brinson model for SMA spring is proposed for more efficient and accurate simulation. In addition, numerical simulation of SMA spring is validated by comparing it with the results of experiment.

Current smart buildings are designed based on prescribed scenarios so that they cannot deal with unexpected events. Moreover, they do not evolve by themselves. "Biofication of Living Spaces" is a concept in which we aim to make living spaces safer and more comfortable by embedding autonomous mechanisms in them. The key technologies for biofication are sensor networks to acquire information and data-processing technologies for effective utilization of information. As a first step towards the realization of "Biofication of Living Spaces", a system for acquiring and storing information must be developed. This research will propose a system database to control a comfortable space. As a first step towards realizing "Biofication of Living Spaces", a system for acquiring and storing information must be developed. This system is similar to the functions of physiological adaption. This research suggests a data model and a database for biofication. This database system is built for living space control based on physiological action. It focuses on "hormone". Hormone is an important factor for transmitting information. While human is in a room, he/she emits unpleasant information to the environment. A sensor agent robot collects these data, and change to "unpleasant hormone". In this system, a sensor agent robot collects data. It can follow residents and acquire data at any point. From these hormones, this system controls all devices in the room. At last, evidence, scalability and robustness are tested.

This paper presents an effort that is aimed at addressing two challenges in the monitoring of some bridges and roads: poor wireless signal transmission and low real-world survivability of wireless sensors. A product is proposed; a prototype is designed and made to protect some off-the-shelf wireless sensors and improve their performance. The design is based on numerical simulations of the electromagnetic field including using finitedifference time-domain method. To protect the wireless sensors and all other components, basic structural analysis is exercised to obtain an enclosure design that tends to optimize the load-carrying capacity given the design constraints. All materials used for the enclosure have low electrical conductivities limiting or nullifying their negative imprint on wireless communication. Off-the-shelf components are utilized as often as possible to minimize the overall cost and expedite the manufacturing process. The problem encountered in the real-world testing of the design is presented, analyzed and solved.

In this work, we consider optimal design of Modal Power Distribution (MPD) based fiber optic sensors and compare power-meter and CCD camera based techniques for strain measurements. To the best of authors' knowledge, majority of the power-meter based MPD sensors use a single photo detector, and there is only one known work where two photodetectors are used with no optimization on photo-detector locations. Optimal measurement location selection problem and comparison of power-meter and CCD camera based sensor measurements were both addressed in this work. Based on our experimental data, more than 100% increased sensitivity is observed in the newly designed optimal strain sensor. It was also shown that there is a fixed nonlinear relationship between CCD based and power-meter based fiber optic sensor measurements. This allows estimation of power-meter measurements utilizing CCD camera images, which in turn simplifies the optimal detector location selection problem.

The cost and size of the state-of-the-art health and usage monitoring systems (HUMS) are determined by capacity of on-board energy storage which limits their large scale deployment. In this paper, we present a miniature low-cost mechanical HUMS integrated circuit (IC) based on the concept of hybrid energy harvesting where continuous monitoring is achieved by self-powering, where as the programming, localization and communication with the sensor is achieved using remote RF powering. The self-powered component of the proposed HUMS is based on our previous result which used a controllable hot electron injection on floatinggate transistor as an ultra-low power signal processor. We show that the HUMS IC can seamlessly switch between different energy harvesting modes based on the availability of ambient RF power and that the configuration, programming and communication functions can be remotely performed without physically accessing the HUMS device. All the measured results presented in this paper have been obtained from prototypes fabricated in a 0.5 micron standard CMOS process and the entire system has been successfully integrated on a 1.5cm x 1.5cm package.

Fatigue is a progressive and localised damage that occurs when a material is subjected to cyclic loading. Historical cases have shown that undetected fatigue cracks often lead to catastrophic failure, including loss of lives and assets. It is therefore important to have a robust Structural Health Monitoring (SHM) technique to detect and monitor these cracks. The Lamb Wave technique for SHM is promising due to its ability to interrogate a large area of the structure from only a few locations. The feasibility of fatigue crack detection in wide specimens, where the effect of boundary reflections is not significant in the signal processing and damage quantification process, have been investigated by other researchers7-9. However, in a narrow structural component, the boundary reflection has a significant role in the sensor signal and the damage quantifier from available literatures cannot be applied readily. The main focus of this study is to investigate the feasibility of monitoring fatigue crack growth in a narrow structural component using the Lamb Wave technique. Experimental study conducted on lab-sized aluminum beam finds that as crack propagates amplitude of the sensor signal decreases. A damage index is proposed, and a linear relationship between the damage index and the crack length is identified. With the proposed damage index, a crack length can be estimated from the acquired sensor signals through a correlation factor.

This paper presents the multiplexing of unpowered wireless antenna sensors for crack monitoring at multiple locations. Four antenna sensors were multiplexed to form a sensor array based on two multiplexing principles, namely frequency division and spatial division. For frequency division, a dual-antenna sensor array with each sensor operating at different frequencies was designed and implemented. Simultaneous interrogation of these two sensor elements has been achieved. For spatial division, two single antenna sensors with the same resonant frequencies as the dual-antenna sensor array were installed at different locations. By steering the illumination light toward their wireless impedance-switch circuits, these two single antenna sensors can be interrogated individually. The capability of the antenna sensor array to monitor multiple crack growth in a fatigue specimen was evaluated. Compared to a single antenna sensor, the antenna sensor array enables us to track the status of cracks over a large area.

The diagnostics of cracks in structures has been gaining importance in recent years. In the past decade, numerous sensors were developed to detect and monitor the crack propagation, but very few sensors can extract quantified information about the crack such as its size and orientation. Recently, we have presented a passive wireless antenna sensor that can detect sub-millimeter crack growth when the crack is parallel to one edge of the antenna patch. This paper studies the capability of the antenna sensor to detect crack orientation. Based on the principle of microstrip patch antenna, an antenna sensor with a rectangular patch radiates at two resonant frequencies. Cracks in the ground plane of the sensor with different orientations influence these two resonant frequencies in two different ways. Thus by monitoring the changes in both resonant frequencies of the antenna sensor, quantitative information about the crack orientations can be obtained. The resonant frequencies of the antenna sensor were first simulated using an EM simulation tool by modeling the crack as a 0.7 mm wide slot oriented at various angles. Simulation results confirmed that the resonant frequencies of the antenna sensor are sensitive to the crack orientation. Subsequently, the antenna sensor's capability to detect crack orientation was experimentally validated by fabricating an antenna sensor on a double-clad circuit board. A mini-milling machine was employed to produce cracks in the ground plane at different angles. The resonant frequencies of the antenna sensor were then measured at different crack lengths to study the effect of crack orientation and length on both frequencies of the antenna sensor. The principle of operation will be discussed first, followed by detailed descriptions on the simulation model, sensor design and fabrication, experimental setup and procedure, results and analysis.

The effective detection and classification of damage in complex structures is an important task in the realization of structural health monitoring (SHM) systems. Conventional information processing techniques utilize statistical modeling machinery that requires large amounts of 'training' data which is usually difficult to obtain, leading to compromised system performance under these data-scarce conditions. However, in many SHM scenarios a modest amount of data may be available from a few different but related experiments. In this paper, a new structural damage classification method is proposed that makes use of statistics from related task(s) to improve the classification performance on a data set with limited training examples. The approach is based on the framework of transfer learning (TL) which provides a mechanism for information transfer between related learning tasks. The utility of the proposed method is demonstrated for the classification of fatigue damage in an aluminum lug joint.

A method for automatically classifying the monitoring data into two categories, normal and anomaly, is developed in order to remove anomalous data included in the enormous amount of monitoring data, applying the relevance vector machine (RVM) to a probabilistic discriminative model with basis functions and their weight parameters whose posterior PDF (probabilistic density function) conditional on the learning data set is given by Bayes' theorem. The proposed framework is applied to actual monitoring data sets containing some anomalous data collected at two buildings in Tokyo, Japan, which shows that the trained models discriminate anomalous data from normal data very clearly, giving high probabilities of being normal to normal data and low probabilities of being normal to anomalous data.

In this study an output-only system identification technique for civil structures under ambient vibrations is carried out, mainly focused on the Subspace System Identification (SSI) based algorithms. With the aim of finding accurate and true modal parameters, a stabilization diagram is constructed by plotting the identified poles of the system with increasing the size of data matrix. Comparative study between different approach, with and without Singular Spectrum Analysis to preprocess the data, on determining the model order and selecting the true system poles is examined in this study. Identification task of the real large scale structure: Guangzhou New TV Tower (GNTVT), a benchmark problem for structural health monitoring of high-rise slender structures is carried out, for which the capacity of SSI-based algorithm is demonstrated.

Evaluation of damage of structures after large earthquake is an important task for health assessment. Vibrations of buildings give us valuable information on it. Among the representative structural characteristics, natural frequencies provide the global information. However they are relatively simple, accurate to measure and easy to obtain. Besides, the changes in frequencies must be considered to identify a damage of structures. This study will consider the frequencies and mode shapes shifts with various levels of seismic excitations. The excitations are represented by different intensity levels of the 1995 Hyogoken Nanbu Earthquake that are obtained in JR - Takatori Station. The acceleration data of E- Defense tests on full scale 4-story steel building will be analyzed. These will allow us detecting and localizing structural damage as well as evaluating the structural performances. The changes in frequencies and mode shapes are achieved from multi-input multi-output (MIMO) models. Those will be compared so as to get the results with reasonable accuracy. The aim of this paper is to propose a damage identification method in order to give correlation between the models and real damage of a steel building using real-size shake table tests.

In this paper, dynamic characteristics of a medium-height office building with passive dampers is investigated. The building considered here is equipped with two kinds of passive dampers, viscous vibration control walls and low yield point steel-based buckling resistant braces. Eleven accelerometers are installed on basement, 1st, 5th, 10th and 14th floor. Two displacement meters for measuring the response of dampers are installed. To know the real performance of the building, we consider not only horizontal components but also vertical components. Dynamic characteristics of the building under several earthquakes are analyzed using multi-input and multi-output models for system identification. Using acceleration responses of multiple observation points, dynamic characteristics are estimated more precisely. The estimation errors of modal parameters are obtained simultaneously. Applying the method, it is indicated that vertical input has a significant influence on translational components.

Proliferation of new and upgrade of existing industrial technologies is impossible without the development of efficient systems and algorithms of automatic control of technological processes that rely on modern monitoring approaches. Typically, the monitoring tools, which include various sensors and other devices, have to be tightly integrated with automatic control systems of industrial processes to reduce service expenses and downtime, increase capacity and optimize production as a whole. While designing technological and automation lines, it is necessary to carefully select parameters to be monitored such that optimal operation is achieved. At the same time, every step of industrial production has to be monitored to assure that each particular process is properly executed and resources are utilized in an efficient manner. An example presented in this paper is based on an ac electric drive equipped with control and monitoring systems. The result of a properly designed monitoring system is a simplified architecture of the control devices. The overall method can be implemented on the basis of a microprocessor, which offers several advantages including the possibility of designing intelligent control loops, expanding the fault-tolerant range of operation, extending the resource of operation, and coordinating interaction between different systems.

The objective of this study is to develop a numerical model of a stay cable interacted with deck, and to examine the vibration suppression technique of the stayed cable subject to external loading. First, a numerical model based on the finite difference method and the finite element method has been developed to simulate the effects of the bending stiffness and its sag-extensibility characteristics of the cable. Accurate vibration mode shapes and modal frequency of the interaction between stay cable and deck are examined. For the vibration control of cable, a MR-damper is used as control device. This damper can be achieved either through the passive control strategy or the semi-active control strategy employing decentralized sliding mode control (DSMC) and maximum energy dissipation (MED) on the staycable. To verify this study, a scaled-down cable structure is designed and constructed in NCREE, Taiwan. A small shaker is designed and mounted onto the cable to generate the sinusoid excitation with different amplitudes and frequencies. Dynamic characteristics of the cable-deck system are identified and the system model is developed for control purpose. The DSMC algorithm using MR damper was studied to reduce the cable vibration under different excitation frequencies.

The formation of scour patterns at bridge piers is driven by the forces at the boundary of the water flow. In most experimental scour studies, indirect processes have been applied to estimate the shear and normal stress using measured velocity profiles. The estimations are based on theoretical models and associated assumptions. However, the turbulence flow fields and boundary layer in the pier-scour region are very complex. In addition, available turbulence models cannot account accurately for the bed roughness effect. Direct measurement of the boundary shear and normal stress and their fluctuations are attractive alternatives. However, this approach is a challenging one especially for high spatial resolution and high fidelity measurements. The authors designed and fabricated a prototype miniature shear stress sensor including an EDM machined floating plate and a high-resolution optical encoder. Tests were performed both in air as well as operation in water with controlled flow. The sensor sensitivity, stability and signal-to-noise level were measured and evaluated. The detailed test results and a discussion of future work will be presented in this paper.

Recently, printed electronics have received growing attention as a new method to produce low-cost large-area electronics on flexible substrates. Much of the current research relies mainly on an inkjet printing technique to deposit electrically functional material solutions onto plastic substrates in order to fabricate various electronic components such as resistors, capacitors and transistors. In this paper, we propose to apply the printed electronics technology to the development of strain sensors for the purpose of measuring structural vibration. To accomplish this, we have developed an aerosol printing system that exhibits better performance in printing on various types of substrates. The system consists of a moving platform, an ultrasonic atomizer, and a shutter to control the flow of the aerosol. Using the system, we demonstrate that a functional strain sensor can be printed directly on the surface of a nonmetallic structure. To form a strain sensor, a water-based conductive polymer, PEDOT-PSS, was deposited on a plastic substrate using the aerosol printer. Then, the piezoresistive response of the printed strain sensor was measured for three different low frequency dynamic strain loadings. The results showed that this type of printed strain sensor can be used to measure the vibration of the host structure. The result of this research will serve as a critical step toward the fabrication of self-sensing structures with printed sensors and accompanying electronics.

A sensing configuration based on commercially available triple-core photonic crystal fiber (PCF) for the image-based collection of thermal information is presented. Detection of thermal phenomena on the micro and nano scale is important for monitoring thermodynamic processes including cooling mechanisms for industry and basic research in both civil and mechanical systems. The thermal characteristics of the PCF combined with coupled-mode theory principles are used to construct a three core PCF with a 1-D core arrangement to simultaneously measure heat flux and temperature. The PCF sensor demonstrated high detection sensitivity (<1°C) and fast response times (<30μs), which is a significant improvement to current commercial standards. PCFs are specialty optical fibers that contain carefully spaced micronsized cavities that provide extraordinary waveguide characteristics not demonstrated by standard optical fiber. The three core PCF has a core diameter of 3.9μm, outer diameter of 132.5μm and varied inter core spacing. A single mode fiber is fusion spliced with the multi-core PCF such that the optical field is confined and launched into the PCF core. The output end of the fiber is inspected and imaged with a CCD camera. A 25mm section of the PCF is surrounded by a guarded hotplate configuration to control the thermal conditions for sensor characterization. Evanescent wave coupling occurs whereby power is transferred from the central core to a neighboring core. Minimum detection sensitivities of 0.2 °C were recorded. Theoretical sensitivities on the order of 10^-2 °C are possible. Experimental results were in agreement with coupled-mode theoretical results.

This paper describes an optimized version of the mechanical version of the monolithic tunable folded pendulum, developed at the University of Salerno, configurable both as seismometer and, in a force-feedback configuration, as accelerometer. Typical application of the sensors are in the field of geophysics, including the study of seismic and newtonian noise for characterization of suitable sites for underground interferometer for gravitational waves detection. The sensor, shaped with precision machining and electric-discharge-machining, like the previous version, is a very compact instrument, very sensitive in the low-frequency seismic noise band, with a very good immunity to environmental noises. Important characteristics are the tunability of the resonance frequency and the integrated laser optical readout, consisting of an optical lever and an interferometer. The theoretical sensitivity curves, largely improved due to a new design of the pendulum arms and of the electronics, are in a very good agreement with the measurements. The very large measurement band (10^-6 ± 10Hz) is couple to a very good sensitivity (10^-12 m/√Hz in the band 0.1 ± 10Hz), as seismometer. Prototypes of monolithic seismometers are already operational in selected sites around the world both to acquire seismic data for scientific analysis of seismic noise and to collect all the useful information to understand their performances in the very low frequency band (f < 1mHz). The results of the monolithic sensor as accelerometer (force feed-back configuration) are also presented and discussed. Particular relevance has their sensitivity that is better than 10^-11 m/s²/√Hz in the band 0.1 ± 10Hz. Finally, hypotheses are made on further developments and improvements of monolithic sensors.

A silica based three core photonic crystal fiber (PCF) force meter with fast response times (<30μs) for low wind speed detection is presented. Results are provided for PCF structures containing cores with varied lattice spacing. Force meters with high spatial resolution (sample regions <10cm) specially outfitted for extreme environmental conditions are of interest to both industry and basic research institutions. The featured PCF force meter exhibited sensitivities that agreed with theoretical predictions that are useful for the detection of minimum displacements for wind speeds <30m/s. The results of this investigation are relevant to civil engineering applications including urban sensing technologies that involve air quality monitoring. The deflection of the PCF detection interface was measured as a function of the fiber deflection or the applied force (e.g. wind speed). The three core PCF has a core diameter of 3.9μm, outer diameter of 132.5μm and 7.56μm core-core spacing. A 4cm length of the PCF is attached to the surface of a thin metal beam. One end of the PCF section is fusion spliced to a single mode fiber (SMF) at the fiber input. The remaining fiber end is coupled to a CCD camera with a lens at the PCF output. The applied force deflects the supported PCF such that the intensity distribution of the optical field for the multiple cores changes as a function of displacement. Experimental results from static deflection measurements are in agreement with coupled-mode theory and simple beam deflection theory models.

In this paper two modal identification approaches appropriate for use in a distributed computing environment are applied to a full-scale, complex structure. The natural excitation technique (NExT) is used in conjunction with a condensed eigensystem realization algorithm (ERA), and the frequency domain decomposition with peak-picking (FDD-PP) are both applied to sensor data acquired from a 57.5-ft, 10 bay highway sign truss structure. Monte-Carlo simulations are performed on a numerical example to investigate the statistical properties and sensitivity to noise of the two distributed algorithms. Experimental results are provided and discussed.

This paper introduces a data compression method using the K-SVD algorithm and its application to experimental ambient vibration data for structural health monitoring purposes. Because many damage diagnosis algorithms that use system identification require vibration measurements of multiple locations, it is necessary to transmit long threads of data. In wireless sensor networks for structural health monitoring, however, data transmission is often a major source of battery consumption. Therefore, reducing the amount of data to transmit can significantly lengthen the battery life and reduce maintenance cost. The K-SVD algorithm was originally developed in information theory for sparse signal representation. This algorithm creates an optimal over-complete set of bases, referred to as a dictionary, using singular value decomposition (SVD) and represents the data as sparse linear combinations of these bases using the orthogonal matching pursuit (OMP) algorithm. Since ambient vibration data are stationary, we can segment them and represent each segment sparsely. Then only the dictionary and the sparse vectors of the coefficients need to be transmitted wirelessly for restoration of the original data. We applied this method to ambient vibration data measured from a four-story steel moment resisting frame. The results show that the method can compress the data efficiently and restore the data with very little error.

This paper proposes a new control method for active mass dampers using a Central Pattern Generator in vibration mitigation. The active mass dampers (or active dynamic absorbers) have been applied to structural vibration control of high-rise buildings, bridges and so on. In this case, the mass of the active mass damper must oscillate in an appropriate phase in relation to the control object, and generally, the damper has been designed by linear control theory as pole placement method, optimal control method or H infinity control method, and all the rest. On the other hand, on walking of animate beings like mammals or insects, both side feet have appropriate phase relations; moreover, it is possible to keep moving on irregular ground. That is, algorithms for the walking would be embedded into the animate beings to control the complicated and redundant bodies with ease and robustness. In biological study, the Central Pattern Generators in bodies playing a significant role in the walking have been learned over the last few decades, and some studies said that some animate beings are able to control their feet by using the generators without their brains in the walking. Moreover, mathematical models of the pattern generators have been proposed, and some researchers have been studying to realize walking of biped-robots using the pattern generators embedded in a computer. In this study, the algorithm is installed into a controller for the active mass damper; furthermore, validation of the controller is performed by numerical simulation.

In this paper we describe the scientific data recorded mechanical monolithic horizontal sensor prototypes located in the Gran Sasso Laboratory of the INFN. The mechanical monolithic sensors, developed at the University of Salerno, are placed, in thermally insulating enclosures, onto concrete slabs connected to the bedrock. The main goal of this experiment is to characterize seismically the sites in the frequency band 10^-4 ÷ 10Hz and to get all the necessary information to optimize the sensor.

Recently, Structural health monitoring (SHM) algorithms based on the modal flexibility matrix has drawn significant attention. These algorithms have been shown to be more effective in damage localization than other methods such as using natural frequencies or mode shapes alone. However, not many of these algorithms are directly applicable for inservice highway bridges. Some studies that are done on highway bridges use SHM algorithms that require known excitations. Other studies require the use of a finite element model to implement the flexibility-based approach. In this paper, a model-free modal flexibility based SHM algorithm is used to identify structural damage while compensating for variations in modal properties due to temperature fluctuations. The algorithm is first validated using a laboratory scale girder bridge under constant temperature. The modal flexibility of different damage scenarios is compared to a baseline undamaged state. Finally, the efficacy of the SHM algorithm is verified using data collected under ambient loading conditions on an in-service highway bridge.

In this paper, the material property assessment and crack identification of concrete using embedded smart cement modules are presented. Both the concrete samples with recycled aggregates (RA) and natural aggregates (NA) were prepared. The smart cement modules were fabricated and embedded in concrete beams to serve as either the actuators or sensors, and the elastic wave propagation-based technique was developed to detect the damage (crack) in the recycled aggregate concrete (RAC) beams and monitor the material degradation of RAC beams due to the freeze/thaw (F/T) conditioning cycles. The damage detection results and elastic modulus reduction monitoring data demonstrate that the proposed smart cement modules and associated damage detection and monitoring techniques are capable of identifying crack-type damage and monitoring material degradation of the RAC beams. Both the RAC and natural aggregate concrete (NAC) beams degrade with the increased F/T conditioning cycles. Though the RAC shows a lower reduction percentage of the modulus of elasticity from both the dynamic modulus and wave propagation tests at the given maximum F/T conditioning cycle (i.e., 300 in this study), the RAC tends to degrade faster after the 180 F/T cycles. As observed in this study, the material properties and degradation rate of RAC are comparable to those of NAC, thus making the RAC suitable for transportation construction. The findings in development of damage detection and health monitoring techniques using embedded smart cement modules resulted from this study promote the widespread application of recycled concrete in transportation construction and provide viable and effective health monitoring techniques for concrete structures in general.

Wireless Smart Sensor Networks (WSSN) facilitates a new paradigm to structural health monitoring (SHM) for civil infrastructure. Conventionally, SHM systems employing wired sensors and central data acquisition have been used to characterize the state of a structure; however, wide-spread implementation has been limited due to difficulties in cabling and data management, high equipment cost, and long setup time. WSSNs offer a unique opportunity to overcome such difficulties. Recent advances in sensor technology have realized low-cost, smart sensors with on-board computation and wireless communication capabilities, making deployment of a dense array of sensors on large civil structures both feasible and economical. Wireless smart sensors have shown their tremendous potential for SHM in recent full-scale bridge monitoring examples. However, structural damage identification in WSSNs, a primary objective of SHM, has yet to reach its full potential. This paper presents a full-scale validation of the decentralized damage identification application on the Imote2 sensor platform on a historic steel truss bridge. The SHM application for WSSN developed in the previous research is further combined with continuous and autonomous monitoring application. In total, 144 sensor channels and one base station have been deployed on the bridge for damage localization. The efficacy of the developed application has been demonstrated to compare the damage identification results with the traditional centralized processing.

This paper proposes a continuous real-time structural health monitoring (SHM) and damage detection system. Wavelet packet decomposition (WPD) with a likelihood ratio was used for the damage sensitive indicator (DSI). A benchmark model updating structure instrumented with acceleration sensors was used for demonstration tests. A real-time reference-free damage detection algorithm is successfully implemented and verified using the benchmark test structure. The DSI based on WPD with a likelihood ratio algorithm showed consistency with two different damage scenarios. Furthermore, the application was web-published on a remote collaboratory site for remote access to a real-time structural health monitoring system.

In this paper, we present a new stochastic model updating methodology to identify spatially varying material properties based on experimental data. This data is typically obtained from ambient or forced vibration measurements. For this purpose, a linear elastic property is modeled as a random field. Stochastic properties of the random field are quantified using an exponential covariance kernel. In order to combine the stochasticity with a Galerkin numerical model of a structure, the covariance kernel is discretized using the Karhunen-Loeve (KL) expansion. In the KL expansion, the covariance kernel is decomposed in the spectral domain by numerically solving a homogeneous Fredholm integral equation. For model updating, stochastic parameters are updated so that the Galerkin model provides dynamic properties matching with realizations that have been identified in experiments. In this paper, Gaussian realizations for varying properties have been employed for the corresponding reference model. This proposed method demonstrates its ability to identify the updating stochastic properties.

Piezoelectric lead zirconate titanate (PZT) transducers have been used for health monitoring of various structures over the last two decades. There are three methods to install the PZT transducers to structures, namely, surface bonded, reusable setup and embedded PZTs. The embedded PZTs and reusable PZT setups can be used for concrete structures during construction. On the other hand, the surface bonded PZTs can be installed on the existing structures. In this study, the applicability and limitations of each installation method are experimentally studied. A real size concrete structure is cast, where the surface bonded, reusable setup and embedded PZTs are installed. Monitoring of concrete hydration and structural damage is conducted by the electromechanical impedance (EMI), wave propagation and wave transmission techniques. It is observed that embedded PZTs are suitable for monitoring the hydration of concrete by using both the EMI and the wave transmission techniques. For damage detection in concrete structures, the embedded PZTs can be employed using the wave transmission technique, but they are not suitable for the EMI technique. It is also found that the surface bonded PZTs are sensitive to damage when using both the EMI and wave propagation techniques. The reusable PZT setups are able to monitor the hydration of concrete. However they are less sensitive in damage detection in comparison to the surface bonded PZTs.

In this study, a micro-pump for Bio-MEMS by using a new bio-compatible piezoelectric thin film is newly developed, which could be built in DDS and HMS. At first, we carried out the performance assessment of our piezoelectric thin film pump of a newly designed micro-fluid system by using the finite element method, which can consider the interaction between the piezoelectric solid and the fluid. The results of numerical analyses show a enough transportation ability of our micro-pump system. Then, we generate multilayer MgSiO₃ thin film on Cu/Ti/Si(100) substrate by using RFmagnetron sputtering method. We measured the crystallographic orientation and piezoelectric property and confirmed that MgSiO₃(101) crystal has grown well. The strain constant d₃₃ was calculated by using the displacement-voltage curve, such as 179.4pm/V. Further, the deflection and frequency of the monomorph-actuator, which fabricated by using the micro-machining process, were measured by the laser doppler vibrometer. It showed that the deflection linearly increased with applied voltage, and it was 82.6nm with the applied voltage of 15V. We evaluated the flow rate of micropump using the luminance difference measurement method. The results showed that the maximum flow rate was 7.1nl/s at the applied voltage of 15V. It shows the possibility of Bio-MEMS device by using our newly developed micro-pump with a new bio-compatible piezoelectric material MgSiO₃.

This study presents vibration-based structural health monitoring method in foundation-structure interface of harbor caisson structure. In order to achieve the objective, the following approaches are implemented. Firstly, vibration-based response analysis method is selected and structural health monitoring (SHM) technique is designed for harbor caisson structure. Secondly, the performance of designed SHM technique for harbor structure is examined by FE analysis. Finally, the applicability of designed SHM technique for harbor structure is evaluated by dynamic tests on a lab-scaled caisson structure.

The paper describes the application of a monolithic folded pendulum (FP) as a tiltmeter for geophysical applications, developed at the University of Salerno. Both the theoretical model and the experimental results of a tunable mechanical monolithic FP tiltmeter prototype are presented and discussed. Some of the most important characteristics, like the possibility of tuning its resonance frequency to values as low as 70mHz and its measured resolution of ≈ 0.1 nrad at 100mHz, are detailed. Among the scientific results, earth tilt tides have been already observed with a monolithic FP tiltmeter prototype.

In this paper we present the control system we implemented for test the control of a suspended mass using monolithic tunable folded pendulum sensors in the band 0.01 - 100 Hz. The main goal of this experiment is to test the performances of monolithic sensors as main acceleration sensors for application in inertial damping control systems. The main advantages of these sensors with respect to the others are the sensitivity (better than 10^-11 m/s²/√(Hz) in the band 0.1 ÷ 10Hz), the large band (0.01 ÷ 100Hz), the tuneability of the resonance frequency (necessary to match the sensors to the suspension mechanics) and the high sensitive integrated laser optical readout, consisting of an optical lever and an interferometer, and a very good immunity to environmental noises. Preliminary results are presented and discussed in this paper together with the planned further developments and improvements of monolithic sensors.

This thesis proposes a newly developed tilt-meter by means of optical fiber hetero-core structured sensor. An optical fiber has advantages such as resistance to corrosion and electromagnetic interference. Additionally, the hetero-core optical fiber is sensitive to bending action only on the sensor portion and the fiber transmission line is unaffected to external disturbances such as temperature fluctuation because of its single-mode stable propagation scheme. Therefore, a hetero-core fiber sensor enables to monitoring harsh environment in a long time usage and is suited for landslide detection in various situations. The proposed tilt-meter consists of an aluminum balk, a pendulum with a weight and a bearing. The tilt can be converted into bending by a clamper at the pendulum and an aluminum board in the tilt-meter. The proposed tilt-meter has indicated a dynamic range of 4.57 dB for ±15 deg., which is needed to check landslide, and accuracy of ±1.5 deg. On the other hand, it was proposed that flat springs added in the tilt-meter so as to decrease hysteresis effect. As a result, the loss for full-scale was decreased to be 2.45 dB, however, the precision was improved to be ±0.2 deg.

South Carolina is one of the most seismically active states in the eastern U.S. Due to this high level of seismic activity, structural health monitoring is important to ensure a high level of confidence in the state's infrastructure. The University of South Carolina (U.SC) is currently studying the behavior of prestressed pile to bent-cap connections that are typical of construction used in the state. Bent caps are generally constructed with multiple piles. In these tests single pile specimens were created for both interior and exterior piles. Interior specimens were subjected to a constant compressive load while exterior specimens experienced both compressive and tensile loads. Acoustic Emission (AE) sensing was utilized on fullscale test specimens to investigate the feasibility of detecting and characterizing damage in these connections during a seismic event. Seven full-scale prestressed concrete piles have been embedded into cast-in-place (CIP) reinforced concrete bent caps and tested under reverse cyclic loading. AE data has been gathered with eight strategically placed AE sensors. Preliminary analysis of the data indicates that AE is promising method with respect to the detection of damage prior to detection by visual observation. AE activity is used to detect both the onset and location of cracking and to characterize the extent of damage at later stages of degradation. One focus of the work is to minimize the amount of AE data recorded for the development of wireless systems having low power consumption.

In order to identify damage of civil engineering structures precisely and efficiently, an approach for damage identification by employing Adaptive Immune Clonal Selection Algorithm (AICSA) is proposed. By utilizing secondary response, adaptive mutation regulation and vaccination operator, AICSA achieves the dynamic control of evolution process, which realizes global optimal computing combined with the local searching. Compared with basic clonal selection algorithm, AICSA improves convergence rate and global optimum searching ability. The experimental results show that AICSA can efficiently and precisely identify single and multiple damages of civil engineering structures respect to different damage location, extent and measurement noise.

In the present paper, we suggest an algorithm for a sensor agent robot with a laser range finder to recognize the flows of residents in the living spaces in order to achieve flow recognition in the living spaces, recognition of the number of people in spaces, and the classification of the flows. House reform is or will be demanded to prolong the lifetime of the home. Adaption for the individuals is needed for our aging society which is growing at a rapid pace. Home autonomous mobile robots will become popular in the future for aged people to assist them in various situations. Therefore we have to collect various type of information of human and living spaces. However, a penetration in personal privacy must be avoided. It is essential to recognize flows in everyday life in order to assist house reforms and aging societies in terms of adaption for the individuals. With background subtraction, extra noise removal, and the clustering based k-means method, we got an average accuracy of more than 90% from the behavior from 1 to 3 persons, and also confirmed the reliability of our system no matter the position of the sensor. Our system can take advantages from autonomous mobile robots and protect the personal privacy. It hints at a generalization of flow recognition methods in the living spaces.

Safer, more comfortable and energy-efficient living spaces are always demanded. However, most buildings are designed based on prescribed scenarios so that they do not act on abrupt changes of environments. We propose "Biofication of Living Spaces" that has functions of learning occupants' lifestyles and taking actions based on collected information. By doing so, we can incorporate the high adaptability to the building. Our goal is to make living spaces more "comfortable". However, human beings have emotion that implies the meaning of "comfortable" depends on each individual. Therefore our study focuses on recognition of human emotion. We suggest using robots as sensor agents. By using robots equipped with various sensors, they can interact with occupants and environment. We use a sensor agent robot called "e-bio". In this research, we construct a human tracking system and identified emotions of residents using their walking information. We focus on the influences of illuminance and sound. We classified emotions by calculating the distance of the mapped points in comfortable and uncomfortable spaces with parametric eigen space method, in which parameters are determined by a mapping of tracks in the space. As a method of pattern recognition, a weighted k-nearest neighbor is used. Experiments considering illuminance and sound environments, illustrates good correlation between emotion and environments.

Soil compaction monitoring is critical to earthwork projects, including roadways, earth dams, and levees. Current methods require a halt of production, and provide at best sparse coverage. A system is proposed for static pad foot soil compaction to provide real-time feedback at higher spatial resolutions through machine integrated sensors. The system is composed of pad sensors that measure total normal force and contact stress distribution (CSD), laser sensors that measure soil deflection, and GPS to spatially reference measurements. By combining these measurements, soil stiffness and potentially modulus can be determined. This paper discusses the development of the force and CSD sensing pad. The concept is to instrument individual pads with strain gages to determine loading conditions. Modeling is used to inform strain gage positioning through pad strain behavior analysis of different simulated soil conditions. The finite element analysis (FEA) of a Caterpillar pad is discussed, including formulation and rationale for the various model parameters. The loading parameters are explained, including the range of force magnitudes experienced throughout compaction and the CSD elicited by various soils. The results of this analysis are presented, and show that pad strain is sensitive to both force magnitude and CSD. Specific strain trends are identified in the sidewall and bottom face of the pad which are particularly sensitive to the loading variables. Strain gage placements are proposed that capture the identified trends, thereby providing definitive information on total normal force and CSD.

A decentralized damage detection method for structure was applied to a shake table experiment which was carried out by Building Research Institute as part of U.S.-Japan cooperative research efforts. This method requires only three sensors to identify localized damage in any story of a structure building. A substructure method was used in this method to divide a complete structure into several substructures. Each substructure has a considerably smaller number of degrees of freedom (DOFs) which makes fewer requirements on the computing power of the data processing system. Moreover the damage detection process can be independently conducted on each substructure. Thus, this method is very attractive especially when smart sensors that have the embedded computing power are used.

Pacific Northwest National Laboratory (PNNL) has developed the Captive Carry Health Monitor Unit (HMU) and the Humidity Indicator HMU. Each of these devices provides end users information that can be used to ensure the proper maintenance and performance of the missile. These two efforts have led to the ongoing development and evolution of the next generation Captive Carry HMU and the next generation Humidity Indicator HMU. These next generation efforts are in turn, leading to the future of HMUs. This evolutionary development process inherently allows for direct and indirect impact toward new HMU functionality, operability and performance characteristics by influencing their requirements, testing, communications, data archival, and user interaction. Current designs allow systems to operate in environments outside the limits of typical consumer electronics for up to or exceeding 10 years. These designs are battery powered and typically provided in custom mechanical packages that employ sensors for temperature, shock/vibration, and humidity measurements. The data taken from these sensors is then analyzed onboard using unique algorithms. The algorithms are developed from test data and fielded prototypes. Onboard data analysis provides field users with a simple indication of missile exposure. The HMU provides missile readiness information to the user based on storage and use conditions observed. To continually advance current designs PNNL evaluates the potential for enhancing sensor capabilities by improving performance or power saving features, increasing algorithm and processing abilities, and adding new features. Future work at PNNL includes the utilization of power harvesting, using a defined wireless protocol, and defining a data/information structure. These efforts will lead to improved performance allowing the HMUs to benefit users with direct access to HMUs in the field as well as benefiting those with the ability to make strategic and high-level supply and inventory decisions in real-time.

This paper discusses the eigenvalue problem of a nonlinear differential equation that governs the stability of a shear bending column under extremely large deformation. What is taken into consideration is the geometrical nonlinearity while the material is supposed to be linear. The reason of a superbly stable buckling behavior of a slender rubber bearing is physically explained by pointing out the analogy that is similar to the nonlinear wave propagation expressed in KdV equation. The nonlinear boundary condition and the nonlinear term of the differential equation cancel each other and make the associated eigenvalue rather constant. In other words, as far as the material is supposed to be linear, the column does not buckle no matter how large the deformation is. This theoretical prediction is experimentally verified and successfully applied to a base isolation system of a lightweight structure.

The authors have explored the use of morphing control surfaces to replace traditional servo-actuated control surfaces in UAV applications. The morphing actuation is accomplished using Macro Fiber Composite (MFC) piezoelectric actuators in a bimorph configuration to deflect the aft section of a control surface cross section. The resulting camber change produces forces and moments for vehicle control. The flexible piezoelectric actuators are damage tolerant and provide excellent bandwidth. The large amplitude morphing deflections attained in bench-top experiments demonstrate the potential for excellent control authority. Aerodynamic performance calculations using experimentally measured morphed geometries indicate changes in sectional lift coefficients that are superior to a servo-actuated hinged flap airfoil. This morphing flight control actuation technology could eliminate the need for servos and mechanical linkages in small UAVs and thereby increase reliability and reduce drag.

An investigation regarding de-icing of wing leading edges through the use of smart structures is performed. Piezoelectric actuators are used to excite the structures at their natural frequencies. This vibration excites shear stresses at the surface, which lead to the shedding off of ice. For optimal excitation of the structure, the frequency and the placement of piezo elements are determined, in order to maximize the shear stress. First, experimental investigations on a clamped aluminum plate are carried out. With these findings, the transition to an aluminum sample of a wing leading edge is performed. Practical experiments have been carried out on a sample of an aluminum wing leading edge. First, the structural behavior is determined by a modal analysis so that the natural frequencies and the eigenmodes can be calculated. By FE simulation all parameter combinations can be calculated, so the practical tests can be adapted accordingly. Practical experiments have been carried out under realistic conditions in terms of ice formation in an icing research tunnel. Different types of ice have been considered, which require a different level of shear stresses for the de-icing. Further investigations will concern the determination of the suitable frequency and furthermore an ongoing monitoring of the process to take up account on different icing conditions. The studies point to a further possibility of energy efficient de-icing.

At present time a variety of Structural Health Monitoring (SHM) technologies for monolithic and sandwich composite structures exist. In general, all these technologies have in common that None-Destructive-Testing (NDT) sensing systems - comprising sensor, cabling and connector - are being combined with structural elements. These combinations of systems with structures lead to multi-variables optimisation problems and resulting conflicts. In order to develop a globally optimised solution for the integration of a sensing system in a structure for a given SHM use case, the S³ logic considers the aspects of sensor, structure and process. Therefore, the S³ logic enables a multi-disciplinary system development in a pragmatic way. This paper focuses on the application of the S³ logic during manufacturing.

With the concept and application of the Underground Wireless Signal Networks (UWSNs), the global subsurface monitoring in real-time can be achieved. The wireless signal networks use the signal strength variation of wireless sensor nodes in the host medium (i.e., soil in this case) as the main indicator of an underground event or a physical change in soil properties. However, the deployment of underground signal/sensor networks has more constraint than aboveground deployment, because installation and management of sensors are more difficult and the radio signal attenuation is much higher than above ground communication. This paper summarizes practical potential applications of underground wireless signal networks and challenges and possible solutions on underground signal network deployment. The two representative applications of underground wireless signal networks are experimentally evaluated by laboratory simulations.

The metal oxide semiconductor thin film gas sensors have been successfully fabricated on a nanospiked silicon surface formed with femtosecond laser irradiations. The sensors show significant response to CO gas at room temperature. It is well-known that the C-O is polarized with positive charges on oxygen atom and negative charges on carbon atom. When the currents pass through the semiconductor sensitive layer, some electrons may accumulate on the tips of the nanospikes to maintain the same electric potential on the surface, which results in strong local electrical fields near the tips of the nanospikes. Then more CO molecules will be pulled onto the tips of the nanospikes and this will enhance the sensitivity of the sensor. A gate bias enhancement has been studied on silicon/oxide layer/semiconductor architecture with the underlying silicon substrate as the back gate. The bias voltage applied on the gate can further enhance the sensitivities of the gas sensors by alternating the electron (or hole) concentration on the surfaces of the metal oxide semiconductor thin film.

The paper presents the project team's advanced sensor-computer sphere technology for real-time and continuous monitoring of wastewater runoff at the sewer discharge outfalls along the receiving water. This research significantly enhances and extends the previously proposed novel sensor-computer technology. This advanced technology offers new computation models for an innovative use of the sensor-computer sphere comprising accelerometer, programmable in-situ computer, solar power, and wireless communication for real-time and online monitoring of runoff quantity. This innovation can enable more effective planning and decision-making in civil infrastructure, natural environment protection, and water pollution related emergencies. The paper presents the following: (i) the sensor-computer sphere technology; (ii) a significant enhancement to the previously proposed discrete runoff quantity model of this technology; (iii) a new continuous runoff quantity model. Our comparative study on the two distinct models is presented. Based on this study, the paper further investigates the following: (1) energy-, memory-, and communication-efficient use of the technology for runoff monitoring; (2) possible sensor extensions for runoff quality monitoring.

Over the past few years, the luminescent photoelastic coating technique has been extended to acquire principal strain measurements on static, three-dimensional structural components under load. The approach uses oblique incident excitation and digital imaging of the luminescence; subsequent analysis is performed on a three-dimension grid compatible with finite element analysis. This paper discusses the initial efforts to extend the technique for dynamically loaded specimens in which the excitation is strobed in synchronization with the load application cycle.