This PDF file contains the front matter associated with SPIE Proceedings Volume 6932, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

Decentralized computing is required to harvest the rich information that a dense array of smart sensors can make available for structural health monitoring (SHM). Though smart sensor technology has seen substantial advances during recent years, implementation of smart sensors on full-scale structures has been limited. Direct replacement of wired sensing systems with wireless sensor networks is not straight-forward as off-the-shelf wireless systems are unlikely to provide the data users expect. Sensor component characteristics limit the quality of data collected due to packet loss during communication, time synchronization errors, and slow communication speeds. This paper describes a scalable, decentralized approach to SHM using smart sensors, including the middleware services which address these issues common to smart sensor applications for structural health monitoring. In addition, the results of experimental validation are given. Finally, ongoing research addressing other factors critical to successful implementation of a full-scale smart sensor network for SHM are discussed.

Curved concrete bridge girders have very complex internal forces, stress and strain distribution. As a consequence of their shape, not only the usual bending moments and shear forces are generated, but also important torsion moments are created. These moments "rotate" the axes of principal tensional stresses increasing the risk of cracking. Post-tensioning can prevent the cracks, but the added compression forces introduced in different directions increase the complexity of stress and strain fields. Therefore, the curved post-tensioned concrete girders must be particularly designed and carefully constructed. However, the real structural behavior should be verified, and risks and uncertainties related to structural design and quality of construction minimized. Structural health monitoring is a natural solution for these issues. Structural health monitoring method, based on the use of fiber optic interferometric technology including long-gage sensors and inclinometers, is presented in this paper. A 36 meters long curved post-tensioned bridge box girder is equipped with so-called parallel and so-called crossed sensor topologies, and inclinometers, in order to monitor axial strain, both horizontal and vertical curvature changes, torsion, average shear strain and rotations in both vertical plans. Important parts of structure life such as construction, post-tensioning and first years of service are registered, analyzed and presented.

The integrity and safety of metallic structures can be jeopardized by structural damage (e.g., yielding, cracking, impact, corrosion) that can occur during operation or service. While a variety of sensors have been proposed and validated for structural health monitoring, most sensors only provide data regarding a discrete point on the structure, thereby requiring densely-distributed sensors; however, such an approach may be infeasible for many structures due to geometrical and economic constraints. In this study, a nanoengineered carbon nanotube-polyelectrolyte sensing skin is proposed for monitoring strain, impact, and corrosion of metallic structures. Experimental validation studies have verified that these conformable films exhibit highly sensitive electromechanical and electrochemical responses to applied strain and corrosion processes, respectively. Here, the proposed nanocomposite is coupled with an electrical impedance tomographic (EIT) conductivity imaging technique. Unlike traditional point-based sensing transducers, EIT reconstructs two-dimensional skin conductivity distributions for damage identification of large structural components. Since EIT relies solely on boundary electrical measurements, one does not need to physically probe each structural location for data acquisition. Instead, any structural damage that affects the nanocomposite coating will produce localized changes in film conductivity detectable via EIT and boundary electrical measurements.

Piezoelectric ceramic transducers were made and embedded in concrete structures in this paper in order to monitor cracks under static load. In the experiment, the component was made in concrete with rebars. The transducers were used as sensors according to the direct piezoelectric effect and actuators according to the indirect piezoelectric effect. During the experiment, sine pulse signals are applied on the transducer to generate elastic wave to scan the area between the transducers. As being electronic device, signal of piezoelectric material will be disturbed by electromagnetic wave in environment. Wavelet analysis with its good ability both in time and frequency domain was adopted in filtering the interfering signal. Then damage index was established based on continuous wavelet analysis. From the change of the damage index, the information of crack occurring and developing in the concrete component has been acquired. And the trend of the damage index also has a good correlation with that of the strain gauges used in the experiment. The results have shown that this method has the advantages that do not require sensors placed on the point of damage occurring and can protect sensors from damage. Thus it can be used in the monitoring of civil structure.

Nearly 90% of the bridges in California are post-tensioned box-girders. Prestressing (PS) tendons are the main load-carrying components of these and other post-tensioned structures. Despite their criticality, much research is needed to develop and deploy techniques able to provide real-time information on the level of prestress and on the presence of structural defects (e.g. corrosion and broken wires) in the PS tendons. In collaboration with Caltrans, UCSD is investigating the combination of ultrasonic guided waves and embedded sensors as an approach to provide both prestress level monitoring and defect detection capabilities in concrete-embedded PS tendons. This paper will focus on the prestress level monitoring by first discussing the behavior of ultrasonic guided waves propagating in seven-wire, 0.6-in diameter twisted strands typically used in post-tensioned concrete structures. A semi-analytical finite element analysis is used to predict modal and forced wave solutions as a function of the applied prestress level. This analysis accounts for the changing inter-wire contact as a function of applied loads. A feature shown sensitive to load levels is the inter-wire energy leakage. In order to monitor such feature, the method uses low-profile piezoelectric sensors able to probe the individual, 0.2-in wires comprising the strand. Results of load monitoring in free and embedded strands during laboratory tests will be presented.

A wavelength interrogation system based on an arrayed-waveguide-grating (AWG) is evaluated. The transmission wavelengths are capable of shifting by thermally scanning the AWG. By employing this AWG wavelength tunability scheme, the center wavelength of a long-period-grating (LPG) sensor is precisely interrogated. The theoretical principle and the experimental result are presented in this paper. An interrogated wavelength resolution of 0.5 pm is achieved by introducing this technique. Furthermore, a palm-size LPG sensor interrogator based on a chip integrated with an AWG demultiplexer, a photodiode, a signal processing module and an electronic controlling module is proposed.

Whatever may be the material used to build the engineering structures, they are bound to undergo damage at some point in their lifetime. The damage could develop because of continuous usage, degradation, environmental factors, earthquakes or man-made disasters. Structural health monitoring (SHM) has emerged as an important area that has attracted intensive research attention in the recent time. Smart materials like piezoceramics (e.g. lead zirconate titanate or PZT) and fibre optical sensors (FOSs) based effective SHM tools are rapidly developing. Especially, the FOSs offer great potential as monitoring sensors due to their small size, immunity to electromagnetic interference, robustness and survivability in harsh environment. Conventional FOSs use phase modulation techniques for sensing. In spite of the above advantages, they are dependent heavily on source intensity fluctuations and coupling loses. However the fibre Bragg grating (FBG) sensors developed from FOSs are immune to source intensity fluctuations, thus addressing some potential problems of the conventional FOSs. This paper presents a review on the current development of FBG based monitoring techniques and their applications.

Complex stress monitoring test of big scale offshore platform T-shape tubular joint is designed and accomplished. To assist this study, a finite element model of the T-shape tubular joint is established to predict the complex strain distribution in the hot spot of the joint. Installation principle and scheme of FBG sensors are proposed. The right angle FBG strain rosette is developed to measure the principle strain, along with the strain distribution of the hot point, in comparison with results from strain gauges. The results show that FBG rosette can monitor the principle strain precisely, and single FBG sensor is acceptable for the hot point strain monitoring. A method is proposed to correct the FBG sensor measurement for its relatively long sensing gauge. Further experimental results show that a single FBG sensor with data correction can monitor the hot spot strain of the model. Static test using FBG sensors and strain gauges were designed and conducted, respectively. Results show that FBG sensors can precisely measure the axial force, the hot spot strain, and the local strain of the tubular joint model.

In Japan's rapidly aging society, the number of elderly people living alone increases every year. Theses elderly people require more and more to maintain as independent a life as possible in their own homes. It is necessary to make living spaces that assist in providing safe and comfortable lives. "Biofication of Living Spaces" is proposed with the concept of creating save and pleasant living environments. It implies learning from biological systems, and applying to living spaces features such as high adaptability and excellent tolerance to environmental changes. As a first step towards realizing "Biofied Spaces", a system for acquisition and storing information must be developed. This system is similar to the five human senses. The information acquired includes environmental information such as temperature, human behavior, psychological state and location of furniture. This study addresses human behavior as it is the most important factor in design of a living space. In the present study, pyroelectric infrared sensors were chosen for human behavior recognition. The pyroelectric infrared sensor is advantageous in that it has no limitation on the number of sensors put in a single space because sensors do not interfere with each other. Wavelet analysis was applied to the output time histories of the pyroelectric infrared sensors. The system successfully classified walking patterns with 99.5% accuracy of walking direction (from right or left) and 85.7% accuracy of distance for 440 patterns pre-learned and an accuracy of over 80% accuracy of walking direction for 720 non-learned patterns.

The paper is concerned with a geometrically nonlinear finite element formulation to analyze piezoelectric shell structures. The classical shell assumptions are extended to the electromechanical coupled problem. The consideration of geometrical nonlinearity includes the analysis of stability problems and other nonlinear effects. The formulation is based on the mixed field functional of Hu-Washizu. The independent fields are displacements, electric potential, strains, electric field, stresses and dielectric displacements. The mixed formulation allows an interpolation of the strains and the electric field through the shell thickness, which is an essential advantage when using nonlinear 3D material laws. With respect to the numerical approximation an arbitrary reference surface of the shell is modeled with a four node element. Each node possesses six mechanical and one electrical degree of freedom. Some simulations demonstrate the applicability of the present piezoelectric shell element.

Current control and performance requirements for large-aperture deployable structures call for precise displacement control, with some tolerances approaching micron levels. Given that strain gages are one of the most economically-deployed sensor architectures, we explored two methods for reconstructing displacement from a distributed strain sensing array. One method linearly maps displacement fields to local strains in a supervised learning mode. After loading the system with sufficient cases, a matrix can be established to approach the approximate displacement-strain relationship. The other method is based on linear regression of generalized basis function projections, typically mode shapes. Results of these two approaches are compared for accuracy, robustness, training time, and real-time feasibility. The second method has higher accuracy due to natural modal behaviors, while the first method is feasible if large amount of training cases and measuring points are available.

According to the characters of smart piezoelectric concrete structures, the structure health monitoring strategy was researched in the paper in details including three basic contents. Firstly, it was proposed that the placement of piezoelectric transducers in the form of an array. The problem of the distance between adjacent transducers was also discussed. Secondly, several forms of detecting signals, frequency band and modes of the transmitting signals were pointed out in the paper. At last, a feasible damage identification method was proposed. The method combined the wavelet packet analysis with the root-mean-square deviation to evaluate the damage level. Especially, when analyzing the damage location, a concept of a transducer array resolution was proposed and used in the damage identification. The transducer array divided the structure into many sub-regions where the damage locations were approximately determined. The accuracy of the damage location will be better and finer with the increasing of the transducer array resolution.

This paper describes a mechanical monolithic sensor for geophysical applications developed at the University of Salerno. The instrument is basically a monolithic tunable folded pendulum, shaped with precision machining and electric-discharge-machining, that can be used both as seismometer and, in a force-feedback configuration, as accelerometer. The monolithic mechanical design and the introduction of laser interferometric techniques for the readout implementation make it a very compact instrument, very sensitive in the low-frequency seismic noise band, with a very good immunity to environmental noises. Many changes have been produced since last version (2007), mainly aimed to the improvement of the mechanics and of the optical readout of the instrument. In fact, we have developed and tested a prototype with elliptical hinges and mechanical tuning of the resonance frequency together with a laser optical lever and a new laser interferometer readout system. The theoretical sensitivity curve both for both laser optical lever and laser interferometric readouts, evaluated on the basis of suitable theoretical models, shows a very good agreement with the experimental measurements. Very interesting scientific result, for example, is that the measured natural resonance frequency of the instrument is 70 mHz with a Q = 140 in air without thermal stabilization, demonstrating the feasibility of a monolithic FP sensor with a natural resonance frequency of the order of mHz with a more refined mechanical tuning. Results on the readout system based on polarimetric homodyne Michelson interferometer is discussed.

Laser interferometry is one of the most sensitive methods for small displacement measurement for scientific and industrial applications, whose wide diffusion in very different fields is due not only to the high sensitivity and reliability of laser interferometric techniques, but also to the availability of not expensive optical components and high quality low-cost laser sources. Interferometric techniques have been already successfully applied also to the design and implementation of very sensitive sensors for geophysical applications. In this paper we describe the architecture and the expected theoretical performances of a laser interferometric velocimeter for seismic waves measurement. We analyze and discuss the experimental performances of the interferometric system, comparing the experimental results with the theoretical predictions and with the performances of a state-of the art commercial accelerometer. The results obtained are very encouraging, so that we are upgrading the system in order to measure the local acceleration of the mirrors and beam splitter of the velocimeter using an ad hoc designed monolithic accelerometers for low frequency direct measurement of the seismic noise.

A new sensor for web flutter measurement is proposed in this paper. The sensor is based on the principle of scattering of light and directional properties of optical fibers. A collimated beam of light is incident on the web edge and scattered light from the web edge is collected using a linear array of optical fibers. As the web flutters the point of scattering moves. Due to the directional property of the optical fibers, each fiber collects scattered light that is incident on it at certain angles. The motion of the scattering point as the web flutters is directly related to which fibers are being illuminated within the fiber array. The other end of the fiber array is terminated onto a linear array of photodiodes (pixels). Based on which fibers in the array are receiving scattered light and the amount of light received, the transverse displacement (web flutter) of the web can be determined. This paper describes the construction and working of the new sensor for web flutter measurement. Experiments conducted on a web platform show that the sensor is capable of accurately measuring web flutter. The frequency response of the sensor is limited only by the scanning rate of the pixel array and not by the flutter measurement method. A dedicated signal processing circuit can be used to obtain a desired scanning rate, thus, a desired frequency response.

We have presented our preliminary results on studying the effect of two different coupling materials in Sonic Infrared (IR) Imaging, which is a hybrid ultrasonic/infrared NDE technology and can detect defects in materials and structures by detecting the changes of IR radiation of defective objects through sensors during an ultrasound excitation pulse (can be a fraction of a second), in the Smart Structures and NDE in San Diego in March 2007. Those two coupling materials produced different results in the sense of producing different IR signal levels. We have been further investigating the non-linear phenomena of different coupling materials in Sonic IR Imaging because this non-linear effect appears to play a very important role in Sonic IR Imaging technology. We focus our study on the effect of the level of coupling mechanical energy from the ultrasound transducer to the target, and the level of infrared signals produced around the defects. We present our results from those aspects in this paper.

This study experimentally investigates the capabilities of iron-gallium nanowire arrays as artificial cilia transducers. The experiments are conducted with a custom manipulator device incorporated into the stage of a scanning electron microscope (SEM) for observation. Individual nanowires of varying size and composition are mechanically tested statically and dynamically to determine the elastic properties and failure modes. Entire arrays of close packed wires are mounted onto giant magnetoresistive (GMR) sensors to measure the coupled magnetic induction response resulting from bending the array. This data is compared with empirical and simulated results from previous macroscale research.

Radio Frequency IDentification (RFID) tag is a promising device for the management of products at a very low cost. Huge number of such low-cost sensors can be installed to the structure beforehand, after a disaster we can access to these sensors wirelessly and very easily. In this system, an electrically conductive paint or printed sheet is applied to a part of structure in which crack will occur. Copper wire is connected to the attachment on the structure and a RFID tag. When a crack occurs, the paint or printed sheet is broken, resulting in an increase in resistance. Crack width can be estimated by the ability of an RFID transmitter to communicate with the tag. By bending tests of concrete specimens, the relationships between concrete crack width and conductivity of the materials are examined. It is shown that the level of concrete crack width can be related to the ability of the paint or printed sheet to conduct electricity or not. This printed sheet is also applied for steel crack. By fatigue test of steel specimen with a notch, very small steel crack can be detected by this sensor.

Smart dampers with on-demand controllable damping curves are key components for semi-active vibration control of structures. Smart dampers utilize friction or viscosity to dissipate mechanical energy by heat. The potential thermal problems are their major drawbacks. Novel colloidal dampers are recently developed with low-heat generation and high damping efficient, they are, however, passive and with no on-demand controllable damping capability. In this paper, we propose a smart colloidal damper by employing water-based ferrofluids in damping media. We find that the corresponding damping hysteresis loops can be affected by applied magnetic fields significantly and rapidly. We further retrieve the instant stiffness and damping coefficient of the smart colloidal dampers from the measured hysteresis loops. It is shown that the negative stiffness and the negative damping coefficient may occur during the operation of the smart colloidal dampers.

Magnetorheological (MR) dampers are one of the most advantageous control devices for civil engineering applications to natural hazard mitigation due to many good features such as small power requirement, reliability, and low price to manufacture. To reduce the responses of a structural system by using MR dampers, a control system including a power supply, control algorithm, and sensors is needed. The control system becomes complex, however, when a lot of MR dampers are applied to large-scale civil structures, such as cable-stayed bridges and high-rise buildings. Thus, it is difficult to install and/or maintain the MR damper-based control system. To overcome the above difficulties, a smart passive system was proposed, which is based on an MR damper system. The smart passive system consists of an MR damper and an electromagnetic induction (EMI) system that uses a permanent magnet and a coil. According to the Faraday law of induction, the EMI system that is attached to the MR damper can produce electric energy and the produced energy is applied to the MR damper to vary the damping characteristics of the damper. Thus, the smart passive system does not require any power at all. Besides the output of electric energy is proportional to input loads such as earthquakes, which means the smart passive system has adaptability by itself without any controller or sensors. In this paper, the integrated design method of a large-scale MR damper and Electromagnetic Induction (EMI) system is presented. Since the force of an MR damper is controllable by altering the input current generated from an EMI part, it is necessary to design an MR damper and an EMI part simultaneously. To do this, design parameters of an EMI part consisting of permanent magnet and coil as well as those of an MR damper consisting of a hydraulic-type cylinder and a magnetic circuit that controls the magnetic flux density in a fluid-flow path are considered in the integrated design procedure. As an example, a smart passive control system for reducing stay cable responses is considered in this investigation and it will be fabricated and tested through experiment in the future.

The smart passive system consisting of a magnetorheological (MR) damper and an electromagnetic induction (EMI) part has been recently proposed. An EMI part can generate the input current for an MR damper from vibration of a structure according to Faraday's law of electromagnetic induction. The control performance of the smart passive system has been demonstrated mainly by numerical simulations. It was verified from the numerical results that the system could be effective to reduce the structural responses in the cases of civil engineering structures such as buildings and bridges. On the other hand, the experimental validation of the system is not sufficiently conducted yet. In this paper, the feasibility of the smart passive system to real-scale structures is investigated. To do this, the large-scale smart passive system is designed, manufactured, and tested. The system consists of the large-capacity MR damper, which has a maximum force level of approximately ±10,000N, a maximum stroke level of ±35mm and the maximum current level of 3 A, and the large-scale EMI part, which is designed to generate sufficient induced current for the damper. The applicability of the smart passive system to large real-scale structures is examined through a series of shaking table tests. The magnitudes of the induced current of the EMI part with various sinusoidal excitation inputs are measured. According to the test results, the large-scale EMI part shows the possibility that it could generate the sufficient current or power for changing the damping characteristics of the large-capacity MR damper.

This paper presents the performance evaluation of a semi-active controlled floor isolation system for earthquake reduction. The floor isolation system consists of a rolling pendulum system and a semi-active controlled MR damper. The modified Bouc-Wen model is used to represent the behavior of the MR damper. A serious of performance test of the MR damper is made and been used for system identification. Two contrasting control methods including LQR with continuous-optimal control and Fuzzy Logic control are experimentally investigated as potential algorithms and comparisons are made from the results. Unlike the clipped-optimal control, LQR with continuous-optimal control can output the continuous command voltage to control the MR damper, and get smoother control effect. A three-story steel structure with the floor isolation system on the 2nd floor is tested on the shake table. Scaled historical near- and far-field seismic records are employed to examine controller performance with respect to frequency content and PGA level. Experimental results show that both control algorithms can suppress the acceleration of the isolated floor during small and large PGA levels, and alleviate both displacement and acceleration simultaneously in larger, near-field events. Both control algorithms are adaptive and robust to various intensity of excitation. This investigation demonstrates the feasibility and capabilities of a smart semi-active controlled floor-isolation system.

This paper presents the structural control results of shaking table tests for a steel frame structure in order to evaluate the performance of a number of proposed semi-active control algorithms using multiple magnetorheological (MR) dampers. The test structure is a six-story steel frame equipped with MR-dampers. Four different cases of damper arrangement in the structure are selected for the control study. In experimental tests, an EL Centro earthquake, a Kobe earthquake and a Chi-Chi earthquake (station TCU067) are used as ground excitations. Various control algorithms are used for this semi-active control studies, including the Decentralized Sliding Mode Control (DSMC), LQR control and passive-on and passive-off control. Each algorithm is formulated specifically for the use of MR-dampers. Additionally, each algorithm uses measurements of the absolute acceleration and the device velocity for the determination of the control action to ensure that the algorithm can be implemented on a physical structure. The performance of each algorithm is evaluated based on the results of shaking table tests, and the advantages of each algorithm is compared and discussed. The reduction of the story drift and acceleration throughout the structure is examined.

Critical non-structural equipment, including life-saving equipment in hospitals, circuit breakers, computers, high technology instrumentations, etc., are venerable tostrong earthquakes, and the failure of these equipments may result in a heavy economic loss. In this connection, innovative control systems and strategies are needed for their seismic protections. This paper presents the performance evaluation of passive and semi-active control in the equipment isolation system for earthquake protection. Through shaking table tests of a 3-story steel frame with equipment on the 1^nd floor, a MR-damper together with a sliding friction pendulum isolation system is placed between the equipment and floor to reduce the vibration of the equipment. Various control algorithms are used for this semi-active control studies, including the decentralized sliding mode control (DSMC) and LQR control. The passive-on and passive-off control of MR damper is used as a reference for the discussion on the control effectiveness.

Magnetorheological fluid damper (MR damper) has been expected to control the response of civil and building structures in recent years, because of its large force capacity and variable force characteristics. At first, a series of real-time hybrid tests was conducted. The important objective of this paper is to verify the validity of real-time hybrid tests by comparison with the test results of shaking table tests by using the same MR damper. The maximum damping force of the MR damper is 10 (kN), the stroke is 600(p-p) (mm), and the maximum piston velocity is 1(m/s). To determine the control force of the MR damper, optimal control theory and skyhook control were employed. The capability of the MR damper to control the response displacements and accelerations of base isolation system was verified by both shaking table tests and real-time hybrid tests.

This paper is concerned about the basic properties of deployment for shape memory polymer composite (SMPC) and its application in deployable hinge for space structure. Shape-memory polymers (SMP) are an emerging class of active polymers that have dual-shape capability. One of another advantage, compared with other traditional material hinge, the SMPC carpenter type hinge is that it will not produce a large shock when it spring into the deployed position. There are several kinds of shape memory polymer composite (fiber reinforced, powder reinforced, etc,). Epoxy SMPs, carbon fibre fabric reinforced SMPC was introduced in this work. In order to investigate the basic performances of SMPC hinge, the experimental methods are used as follows: dynamic mechanical analysis (DMA), three point bending test and the radio of shape recovery. In the end, the structure of the carpenter type hinge is introduced. The carpenter type hinge is one mechanism that has the advantage of high-reliability of the deployment; light weighted, and low cost. This SMPC carpenter type hinge performs good deployment performances during numerous thermomechanical cycles. So the potential applications for such materials as active medical devices are highlighted.

Cornerstone Research Group Inc. has developed reflexive composites achieving increased vehicle survivability through integrated structural awareness and responsiveness to damage. Reflexive composites can sense damage through integrated piezoelectric sensing networks and respond to damage by heating discrete locations to activate the healable polymer matrix in areas of damage. The polymer matrix is a modified thermoset shape memory polymer that heals based on phenomena known as reptation. In theory, the reptation healing phenomena should occur in microseconds; however, during experimentation, it has been observed that to maximize healing and restore up to 85 % of mechanical properties a healing cycle of at least three minutes is required. This paper will focus on work conducted to determine the healing mechanisms at work in CRG's reflexive composites, the optimal healing cycles, and an explanation of the difference between the reptation model and actual healing times.

Durability and damage tolerance criteria drives the design of most composite structures. Those criteria could be altered by developing structure that repairs itself from impact damage. This is a technology for increasing damage tolerance for impact damage. Repaired damage would enable continued function and prevent further degradation to catastrophic failure in the case of an aircraft application. Further, repaired damage would enable applications to be utilized without reduction in performance due to impacts. Self repairing structures are designed to incorporate hollow fibers, which will release a repairing agent when the structure is impacted, so that the repairing agent will fill delaminations, voids and cracks in les than one minute, thus healing matrix voids. The intent is to modify the durability and damage tolerance criteria by incorporation of self-healing technologies to reduce overall weight: The structure will actually remain lighter than current conventional design procedures allow. Research objective(s) were: Prove that damage can be repaired to within 80-90% of original flexural strength in less than one minute, in laminates that are processed at 300-350F typical for aircraft composites. These were successfully met. The main focus was on testing of elements in compression after impact and a larger component in shear at Natural Process Design, Inc. Based on these results the advantages purposes are assessed. The results show potential; with self repairing composites, compressive strength is maintained sufficiently so that less material can be used as per durability and damage tolerance, yielding a lighter structure.

This paper is concerned about the drive of shape memory styrene copolymer through an infrared optical fiber carrying infrared laser. The infrared laser was chosen to drive the SMP through the optical fiber embedded into the SMP. The working frequency of infrared laser was installed in 3-4μm, the working band of optical fiber was 1-6μm. An optical fiber was embedded into the SMP for delivery of 3-4μm laser light for activation. The surface of the optical fiber was etched by the aqueous solution of sodium-hydroxide in order to increase transmission efficiency of the optical fiber. We synthesized thermoset SMP based on styrene copolymer, and measured Tg of SMP is the 53.7oC by the DMA. The thermally activated SMP is possible to initiate an originally shape by a touchless and highly selective infrared laser stimulus. The infrared laser-activated SMP could be recovered its original shape by less temperature than Tg, it was proved this driving method of SMP is more effective than conventional external heaters. Therefore infrared laser-activated method was advantageous for using in the low temperature condition. The increase in temperature of SMP which was embedded treated optical fiber indicated that the infrared laser irradiated into the SMP from here and heated the SMP. The optical fiber was treated by the aqueous solution of sodium-hydroxide, transmission efficiency of the optical fiber increased, and the total contact area between SMP and the optical fiber. The infrared laser stimulation of SMP was interest for actuator systems as well as medical applications.

Results from our efforts to improve the performance of low-cost, unpowered, wireless, resistance based Electronic Structural Surveillance tags (ESS) will be presented. The ESS tags use an unpowered embedded sensor read by an external reader using an inductively coupled impedance measurement. Read range of coupled tags is largely dependent on the strength of inductive coupling which is influenced by the relative shape and size of the coils. Reader coil geometries can be optimized to increase read range. Additionally, an enhanced circuit model, for data extraction, is developed and tested with the corrosion sensor. The model provides increased information about the sensor and its surroundings. Better coil design and circuit model based data extraction methods can improve the reliability in reading the sensor. Recommendations for design and analysis resulting from this study can be extended to optimize other electronic structural surveillance tag sensors.

In this study, a smart sensor node is developed for hybrid health monitoring of PSC girder bridges. Hybrid health monitoring of those structures is to alarm damage occurrence, to classify damage-types, and to identify damage locations and severities by measuring accelerations and impedance signals. In order to achieve the objective, the following approaches are implemented. Firstly, a smart sensor node with wireless sensing capacity and embedded monitoring algorithms is developed for measuring acceleration. Secondly, we design a hybrid damage monitoring scheme that combines acceleration-based and impedance-based methods for PSC girder bridges. Finally, the performance of the smart sensor node is evaluated using a laboratory-scale PSC girder bridge model for which acceleration and impedance signals were measured for prestress-loss and stiffness-loss cases.

Large Scale Heavy Derrick Lay Barge is very important for sea work. Under intense wind and wave load, the hook on the Barge will vibrate so large that in some cases it can not work. Through installing the Tuned Mass Damper(TMD) on the hook, the vibration will be reduced to a certain range to meet the demand on sea work, which is also important for increasing the efficiency of sea work. To design the suitable TMD for the hook, the dynamical parameters should be specified beforehand. Generally, the related dynamical parameters such as inclinometer and acceleration are measured by wire sensors. But due to the restriction of the actual condition, the wire sensors are very hard to implement. Recently, the wireless sensors have been presented to overcome the shortcomings of wire ones. It is more suitable and also convenient to utilize wireless sensors to acquire the useful data of large scale heavy derrick lay barge. In this paper, the hook reducing swing movement control module is designed for large scale heavy derrick lay barge. Secondly, wireless inclinometer sensor system is integrated using the technique of MEMS, sensing and wireless communication. Finally, the hook reducing swing movement control module is validated by the developed wireless inclinometer data acquisition system. The wireless inclinometer sensor can be used not only in swing monitoring for large scale heavy derrick lay barge's Hook, but also in vibration monitoring for TV tower, large crane. In general, it has great application foreground.

This paper describes an autonomous embedded system for remote monitoring of bridges. Salient features of the system include ultra-low power consumption, wireless communication of data and alerts, and incorporation of embedded sensors that monitor various indicators of the structural health of a bridge, while capturing the state of its surrounding environment. Examples include water level, temperature, vibration, and acoustic emissions. Ease of installation, physical robustness, remote maintenance and calibration, and autonomous data communication make the device a self-contained solution for remote monitoring of structural health. The system addresses shortcomings present in centralized structural health monitoring systems, particularly their reliance on a laptop or handheld computer. The system has been field-tested to verify the accuracy of the collected data and dependability of communication. The sheer volume of data collected, and the regularity of its collection can enable accurate and precise assessment of the health of a bridge, guiding maintenance efforts and providing early warning of potentially dangerous events. In this paper, we present a detailed breakdown of the system's power requirements and the results of the initial field test.

The objective of this research is to develop and verify the wireless micro-electro-mechanical system (MEMS) monitoring system for the health monitoring of high rise buildings. The MEMS accelerometer has advantages of small size, low-cost and low power consumption, and thereby is suitable for wireless monitoring. Consequently, the use of MEMS and wireless communication can reduce system cost and simplify the installation for the structural health monitoring. To assess the applicability, the wireless MEMS monitoring system is applied to a full-scale building structure with hybrid mass damper (HMD) system. The building is a 5-story steel building and the HMD is mounted on the 4th floor to vibrate the building. The field evaluation results indicate that the wireless MEMS monitoring system is reliable and robust for the health monitoring of buildings.

From a traffic safety point-of-view, there is an urgent need for intelligent tires as a warning system for road conditions, for optimized braking control on poor road surfaces and as a tire fault detection system. Intelligent tires, equipped with sensors for monitoring applied strain, are effective in improving reliability and control systems such as anti-lock braking systems (ABSs). In previous studies, we developed a direct tire deformation or strain measurement system with sufficiently low stiffness and high elongation for practical use, and a wireless communication system between tires and vehicle that operates without a battery. The present study investigates the application of strain data for an optimized braking control and road condition warning system. The relationships between strain sensor outputs and tire mechanical parameters, including braking torque, effective radius and contact patch length, are calculated using finite element analysis. Finally, we suggested the possibility of optimized braking control and road condition warning systems. Optimized braking control can be achieved by keeping the slip ratio constant. The road condition warning would be actuated if the recorded friction coefficient at a certain slip ratio is lower than a 'safe' reference value.

In this study, we investigated a promising method for measuring three-axis force based on an optical tactile sensing system. Such system consists of a waveguide, an array of tactile cell, a light source and an image sensor (a CCD camera). When the tactile cells are subjected to external forces, the condition for total internal reflection of the attached waveguide is spoiled. The original symmetrical planar waveguide then changes to an asymmetrical one, leading to light leakage in the transverse direction, which is used as the sensing mechanism for the applied forces. A numerical study involving three-dimensional finite element analysis was carried out to study the deformation of tactile cells due to contact forces. A linear relationship between the applied three-axis force and the spot sizes of the image of the leaked light was obtained and validated by experiments.

Machinery maintenance accounts for a large proportion of plant operating costs. Compared with the conventional scheduled maintenance strategy which is to stop the machine at pre-determined intervals, modern condition-based maintenance strategy stops the machine only when there is evidence of impending failure. It is now possible to use multi-modal sensor input to monitor machine condition in a collaborative and distributed manner. In this paper, three categories of methods for condition monitoring are reviewed - 1. knowledge based, 2. model based 3. data based methods. Knowledge-based systems are derivations from expert systems that use rules and inference engines to determine failures and their causes. Data-driven methods use machine fault data, typically derived during experiments to train a monitoring system. Pattern recognition algorithms then attempt to classify actual sensor data using the results of the training phase. However it is often impractical to obtain data for every type of fault. Model-based techniques on the other hand use mathematical models to predict machine performance. We propose to combine the model based and data based method for machine condition monitoring. The data is used to train the model and derive its parameters. The various fault modes are then identified and simulated. The output is then input to the classification schemes that can be then used to identify and classify real-time data. We apply the technique to condition monitoring of electrical motors.

A pulse-echo ultrasonic guided wave approach that monitors the development of early age mortar during the initial stages of setting and hardening is presented. The method transmits the fundamental torsional wave mode on one end of a cylindrical steel rod partially embedded in mortar and then monitors the reflected signals. Both the reflection from the end of the rod and the reflection from the point where the waveguide enters the material are monitored. The development of the material's mechanical properties is related to the change in signal strength of the reflections. The reflection at the location where the waveguide pierces the material is essentially a surface measurement. It is known that the material properties of concrete vary with depth; specifically, the material in the surface layer possess different material properties than the core material of the specimen. Finite element analysis was used to analyze these differences and to provide a clearer understanding of the entry-reflection. The analysis shows that at early stages, it takes more time for the surface layer to achieve the same properties as that of the core of the specimen. However, after the mortar has achieved measurable strength (e.g. 12-14 hours), the material properties of the surface layer can reasonably approximate those of the core of the specimen.

High-frequency guided longitudinal waves have been used in a through-transmission arrangement to monitor reinforced mortar specimens undergoing both accelerated uniform and localized corrosion. High-frequency guided longitudinal waves were chosen because they have the fastest propagation velocity and lowest theoretical attenuation for the rebar/mortar system. This makes the modes easily discernible and gives them the ability to travel over long distances. The energy of the high-frequency longitudinal waves is located primarily in the center of the rebar, leading to less leakage into the surrounding mortar. The results indicate that the guided mechanical waves are sensitive to both forms of corrosion attack in the form of attenuation, with less sensitivity at higher frequencies. Also promising is the ability to discern uniform corrosion from localized corrosion in a through-transmission arrangement by examination of the frequency domain.

This study focuses on a structural health monitoring (SHM) using case-based reasoning (CBR). Structural condition is diagnosed using propagation patterns of ultra-sonic waves. Firstly, emitted pseudo-AE waves are measured in pencil lead fracture experiments. Then, the AE signals are classified into 90 types according to location, magnitude and structural condition. Secondly, pattern identification is conducted using feature parameters extracted from the signals for damage pattern recognition. Finally, feasibility of the method to real structures using CBR is studied. Results showed that the damage patterns could be determined with 82% accuracy. If only the damage location is needed, of the accuracy was higher with 95%. The proposed method using ultra-sonic waves and CBR is thus feasible for practical applications.

In earlier work we developed inductive coupling for surface-mounted Lamb wave transducers operating at relatively low frequencies, such as 300 kHz. We now report on similar inductively-coupled transducers at higher (multiple MHz) frequencies. Our investigation was motivated by a particular application, to examine a box girder top flange, using transducers mounted along the flange edge. We employ a pair of transducers in pitch-catch mode, offset to create a diagonal path, and show that a shadow is detected when the path is intercepted by a through-thickness crack. We compare results obtained using conventionally wired transducers and using inductively-coupled transducers, showing that effective performance can be achieved with wireless (inductively-coupled) operation. Superior performance is obtained if plexiglas wedges are used to direct the beam along the diagonal path. Reflection from the crack is evident, as is the shadow effect along the direct diagonal path.

We discuss waves created in relatively thick plates by edge excitation at frequency-thickness (fd) products that correspond, in principle, to multiple Lamb wave modes. For relatively low values of the fd product it is clear that Lamb wave modes will be generated, while at large values of the fd product we observe a bulk (longitudinal wave) in the solid, but influenced by reflections from the plate surfaces. We show that for a range of intermediate fd products a train of regularly spaced nearly-longitudinal waves is generated. The development of a lead pulse and trailing pulses, all traveling at the longitudinal (bulk) wave speed, is well known and has been explained in the literature. In this paper we describe the transition from Lamb wave generation to the formation of nearly-longitudinal waves with their trailing pulses. We report experimental results and theoretical results, with good correspondence between them. We also examine the transfer of energy from leading to trailing pulses, which means that such nearly-longitudinal waves will not propagate indefinitely; however, we show that they retain ample energy for flaw detection at distances of several meters. Most importantly, we study the interaction of these trailing pulses with cracks, again showing experimental results and theoretical predictions that are consistent with one another. The results suggest that these nearly-longitudinal waves are an attractive option for flaw detection because of their shorter wavelength (as compared to Lamb waves at low fd products) and because they preserve their pulse train characteristics after scattering.

Miniature and light weight thick piezoelectric films (>40μm) integrated ultrasonic transducers (IUTs) for bulk longitudinal (L) and shear (S) and plate acoustic waves (PAW) propagation are presented. The unique and distinct advantages of these IUTs are that they can be fabricated, using sol-gel based technique, directly onto sample with complex structures including curved surfaces and require no couplant for operation. Using novel mode conversion methods, the L wave generated by IUTs can be converted to S, symmetric, anti-symmetric and shear-horizontal (SH) PAW. The experimental results agreed well with those obtained by a finite difference based method which solves the 3D visco-elastic wave equations. These IUTs can operate at temperatures at least up to 150°C, at center frequencies ranging from 1 to 20 MHz, and provide damage detection range of tens of centimeters in metallic structures. An inductive coupled technique is used to achieve non-contact measurements with these IUTs.

Linear sensor arrays made from small molecule/carbon black composite chemiresistors placed in a low headspace volume chamber, with vapor delivered at low flow rates, allowed for the extraction of chemical information that significantly increased the ability of the sensor arrays to identify vapor mixture components and to quantify their concentrations. Each sensor sorbed vapors from the gas stream to various degrees. Similar to gas chromatography, species having high vapor pressures were separated from species having low vapor pressures. Instead of producing typical sensor responses representative of thermodynamic equilibrium between each sensor and an unchanging vapor phase, sensor responses varied depending on the position of the sensor in the chamber and the time from the beginning of the analyte exposure. This spatiotemporal (ST) array response provided information that was a function of time as well as of the position of the sensor in the chamber. The responses to pure analytes and to multi-component analyte mixtures comprised of hexane, decane, ethyl acetate, chlorobenzene, ethanol, and/or butanol, were recorded along each of the sensor arrays. Use of a non-negative least squares (NNLS) method for analysis of the ST data enabled the correct identification and quantification of the composition of 2-, 3-, 4- and 5-component mixtures from arrays using only 4 chemically different sorbent films and sensor training on pure vapors only. In contrast, when traditional time- and position-independent sensor response information was used, significant errors in mixture identification were observed. The ability to correctly identify and quantify constituent components of vapor mixtures through the use of such ST information significantly expands the capabilities of such broadly cross-reactive arrays of sensors.

An investigation was performed to develop a flexible sensor network that can be stretched and expanded to cover structures with an order of magnitude larger than its original unexpanded size. The increasing need to cover large areas with a high number of sensors, networks, and electronic devices for structural health monitoring leads to this study. In this paper a flexible polymer with ultra- high stretching capability (linear expansions larger than 1000% the original length) is designed, fabricated and tested for sensor network applications. The stretchability of the polymer is achieved by engineering thousands of micronodes, which house the sensors and electronics, interconnected by extendable and flexible polymer microwires. The extendable microwires are the key element to perform uniform expansions of the network in all directions, to allow precise location of the nodes, to maximize the polymer expansion per unit area and to allow translation only of the nodes. With the proposed microwire design, a linear elongation wider than 1000% was achieved for a 256 nodes network, avoiding failure of the microwires and micronodes during fabrication and extension. It is believed that the proposed flexible, expandable polymer design is a cost-effective approach to integrate networks of thousands of sensors, actuators and electronic devices into large structures.

Compact sensing schemes are desirable for feedback control of ionic polymer-metal composite (IPMC) actuators in their targeted bio, micro, and nano applications. In this paper, a novel integrated sensory actuator with both position and force feedback is designed by combining IPMC with polyvinylidene fluoride (PVDF) films. The design adopts differential configurations for both the sensor-actuator structure and the sensing circuit, and thus eliminates capacitive coupling between IPMC and PVDF, minimizes the internal stress at bonding interfaces, and enables excellent immunity to thermal and electromagnetic noises. Closed-loop position control of the IPMC output is demonstrated together with simultaneous tip force measurement, based upon the integrated PVDF position and force sensors.

We present four new findings pertaining to MEMS sensors for acoustic emission detection. Our sensors are resonant-type capacitive transducers, operating with a frequency between 100 kHz and 500 kHz, fabricated in the PolyMUMPS process. The sensitivity of a resonant transducer is related to the sharpness of its resonance, measured by the quality factor Q, and operating in a coarse vacuum will increase Q. We describe a practical laboratory method for sealing and evacuating our MEMS sensor, and present measurements showing Q in the evacuated packages to be 2.4 to 3.6 times greater than under atmospheric pressure. We also describe our theoretical analysis of noise sources in the electromechanical behavior of a resonant, capacitive-type transducer sensitive to out-of-plane motion, with particular interest in noise resulting from mechanical excitation of the moving plate by air molecule impact. We report on a new transducer design to sense out-of-plane motion featuring a moving plate constructed as an open grill rather than as a plate perforated by etch holes. Characterization measurements show the open grill design to have a higher Q than a comparable perforated plate transducer. Finally, we report on another novel transducer designed to sense in-plane motion. The sensor is a comb finger capacitive transducer, and theoretical predications predict the in-plane sensor to have a much higher Q than the out-of-plane sensors. We show experimental measurements confirming these design characteristics, and we show results from pencil lead break experiments.

The development of an in-fiber whitelight interferometric distance sensor based on the mode coupling effect of a Long Period Fiber Grating (LPFG) for absolute distance measurement has been investigated. Unlike the Fabry-Perot interferometric distance sensor that uses a regular single mode fiber as the sensor probe, the LPFG-based distance sensor employs a single mode fiber whose cladding region is coated with a reflective film and having a LPFG located at a distance from the cleaved fiber end. The LPFG serves as a beam splitter that separates the light into a core mode and a cladding mode and recombines the two light waves to generate interference, from which the absolute distance can be deducted. Because the optical path difference of the LPFG-based interferometric distance sensor is contributed by both the free-space cavity distance and the distance between the LPFG and the fiber end, it does not impose a limit on the minimum measurable distance. In this paper, the experimental setup for mechanically inducing LPFG in the optical fiber is first described. It is demonstrated that the transmission characteristics of the LPFG can be easily controlled by adjusting the grating period and the applied pressure. The implementation and data analysis of an LPFG-based whitelight interferometric distance sensor are then discussed in detail. Experimental results verified that the distance sensor is capable of measuring small distances that can not be measured by a Fabry-Perot interferometric distance sensor.

Existing strain gages are mostly point sensors that measure local strains from a few discrete locations, while TDR sensor can interrogate distributed changes along the entire length of the sensor line. The present study investigates feasible applications of a new technique using TDR as a distributed strain sensor for structural health monitoring. First, a specially designed TDR sensor laid out on a substrate successfully measured distributed strains and detected a failure location when the substrate was under an increasing tensile load. Second, a TDR sensor spirally wound around a cylindrical tank measured a circumferential strain and detected a failure location on the tank surface when the tank was increasingly pressurized. The developed TDR monitoring technique shows great potential for real-time health monitoring of various critical structures such as bridge, aircraft, and aerospace applications.

An analytical investigation of the transverse shear wave mode tuning with a resonator mass (packing mass) on a Lead Zirconium Titanate (PZT) crystal bonded together with a host plate and its equivalent electric circuit parameters are presented. The energy transfer into the structure for this type of wave modes are much higher in this new design. The novelty of the approach here is the tuning of a single wave mode in the thickness direction using a resonator mass. First, a one-dimensional constitutive model assuming the strain induced only in the thickness direction is considered. As the input voltage is applied to the PZT crystal in the thickness direction, the transverse normal stress distribution induced into the plate is assumed to have parabolic distribution, which is presumed as a function of the geometries of the PZT crystal, packing mass, substrate and the wave penetration depth of the generated wave. For the PZT crystal, the harmonic wave guide solution is assumed for the mechanical displacement and electric fields, while for the packing mass, the former is solved using the boundary conditions. The electromechanical characteristics in terms of the stress transfer, mechanical impedance, electrical displacement, velocity and electric field are analyzed. The analytical solutions for the aforementioned entities are presented on the basis of varying the thickness of the PZT crystal and the packing mass. The results show that for a 25% increase in the thickness of the PZT crystal, there is ~38% decrease in the first resonant frequency, while for the same change in the thickness of the packing mass, the decrease in the resonant frequency is observed as ~35%. Most importantly the tuning of the generated wave can be accomplished with the packing mass at lower frequencies easily. To the end, an equivalent electric circuit, for tuning the transverse shear wave mode is analyzed.

It is widely known that materials exposed to the severe low earth orbit (LEO) environment undergo degradations. For the evaluation of fiber Bragg grating (FBG) sensors in the LEO environment, the reflective spectrum change and the Bragg wavelength shift of FBG sensor were measured during aging cycles simulating the LEO environment. The LEO environment was simulated by high vacuum (~10^-5 Torr), ultraviolet (UV) radiation (<200nm wavelength), temperature cycling (-30°C~100°C), and atomic oxygen atmosphere (AO flux of 9.12×10¹⁴ atoms/cm²/s and kinetic energy of ~0.04 eV). FBG sensor arrays were embedded into the graphite/epoxy composite material. Through the aging cycles simulated for the LEO environment, the change in the reflective spectrums and the Bragg wavelengths from FBG sensors were investigated.

Recently, a damage detection technique has been developed based on the polarization characteristics of the piezoceramic (PZT) transducers attached on the both sides of a thin and uniform metal plate. Damage is identified using instantaneously measured Lamb wave signals without using previously obtained baseline data. If the propagating waves along a thin plate encounter a discontinuity point such as a crack, mode conversion occurs and this mode conversion is extracted using the proposed technique. So for, the proposed technique is demonstrated for specimens with a uniform thickness although many structural systems have more complex structural features such as stiffeners, holes and bolts. In this study, the effect of through-the-thickness holes on the proposed technique is investigated. An array of holes creates multiple reflections and refractions of Lamb waves, and these multiple reflections and refractions may cause difficulties in analyzing responses of Lamb waves. Because the through-the-thickness holes do not produce mode conversion, it is expected that these holes do not affect the performance of the proposed technique. This study experimentally investigates whether a crack damage can be still identified even in the presence of the holes using the proposed technique.

The amount and magnitude of absorption and scattering of stress waves in concrete, mainly due to internal friction and aggregate inclusions, may be different when the concrete mix proportion varies. In this study, the surface wave spectral energy transmission method is proposed for the estimation of crack depth in concrete structures, in which the effect of the concrete mix proportion on measurements of self-compensated surface wave transmission functions (TRFs) and surface wave spectral energy transmission ratios (SETRs) is investigated and a relationship between the crack depth and the SETR has been determined from experimental data on various concrete specimens with different mix proportions and different crack depths using a regression analysis. In the results, it is found that the self-compensated surface wave TRFs are very sensitive to both concrete mix proportions and crack depths. However, SETR is not much affected by the concrete mix proportion but very sensitive to the crack depth. Therefore, the spectral energy transmission method can be effectively used for crack depth estimation in concrete structures regardless of their material mix proportions.

A glulam beam retired from the field and without visible indications of wood decay was used. Towards detection and assessing wood decay, X-ray computer tomography and ultrasonic measurements were carried out. It was observed that decrease in mass density with increasing levels of wood decay affects x-rays attenuation and allows radioscopy to detect and assess wood decay. Furthermore, it was also observed that the decrease in mass density and stiffness caused by wood decay affects ultrasonics measurements. It was observed that ultrasonic velocity and stress wave features such as time of arrival, area under the power spectral density curve, energy, and frequency of maximum amplitude allows detection and assessment of wood decay. Results show that results from both X-ray computer tomography and ultrasonic measurements are consistent with each other and can be used to detect and assess wood decay in structural lumber.

This paper presents the development of the theoretical basis for the design of sensor networks for determining the 2-dimensioal shape of morphing structures by monitoring simultaneously the bending and twist deflections. The proposed development is based on the non-linear theory of finite elements to extract the transverse linear and angular deflections of a plate-like structure. The sensors outputs are wirelessly transmitted to the command unit to simultaneously compute maps of the linear and angular deflections and maps of the strain distribution of the entire structure. The deflection and shape information are required to ascertain that the structure is properly deployed and that its surfaces are operating wrinkle-free. The strain map ensures that the structure is not loaded excessively to adversely affect its service life. The developed theoretical model is validated experimentally using a prototype of a variable cambered span morphing structure provided with a network of distributed sensors. The structure/sensor network system is tested under various static conditions to determine the response characteristics of the proposed sensor network as compared to other conventional sensor systems. The presented theoretical and experimental techniques can have a great impact on the safe deployment and effective operation of a wide variety of morphing and inflatable structures such as morphing aircraft, solar sails, inflatable wings, and large antennas.

This work seeks to extend the functionality of the composite material beyond that of simply load-bearing and to enable in situ sensing, without compromising the structural integrity of the host composite material. Essential to the application of smart composites is the issue of the mechanical coupling of the sensor to the host material. Here we present various methods of embedding sensors within the host composite material. In this study, quasi-static three-point bending (short beam) and fatigue three-point bending (short beam) tests are conducted in order to characterize the effects of introducing the sensors into the host composite material. The sensors that are examined include three types of polyvinylidene fluoride (PVDF) thin film sensors: silver ink with a protective coating of urethane, silver ink without a protective coating, and nickel-copper alloy without a protective coating. The methods of sensor integration include placement at the midplane between the layers of prepreg material as well as a sandwich configuration in which a PVDF thin film sensor is placed between the first and second and nineteenth and twentieth layers of prepreg. Each PVDF sensor is continuous and occupies the entire layer, lying in the plane normal to the thickness direction in laminated composites. The work described here is part of an ongoing effort to understand the structural effects of integrating microsensor networks into a host composite material.

For the deflection measurement of a bridge, sensor inaccessibility due to the reference point (fixed point) may cause lots of inconvenience and increase of installation cost and time. Therefore, an alternative indirect deflection estimation method is proposed utilizing the FE model updating with measured acceleration data from an ambient vibration test. For the fast and stable optimization during the model updating, two step model updating approach is additionally proposed. To investigate the effects of used modal quantities and their weighting factors, extensive model updating was carried out by applying several kinds of data sets: using only natural frequencies, using only mode shapes, and using both of them, By simulating the load test on each of the updated model, deflections were estimated and compared with the real measured deflection data in the load test.

This paper presents results from a thermal sensitivity study of a luminescent photoelastic coating. The investigation is part of larger research program to integrate luminescence sensing for strain measurement and health monitoring in civil, automotive and aerodynamic applications. Luminescent photoelasticity is a new approach to measure mechanically induced stress and/or strain, and corresponding principal directions on structural components. The technique incorporates a luminescent dye that partially preserves the stress-modified polarization state within a birefringent coating and provides high emission signal strength at oblique surface orientations. The optical strain response of the coating is a nonlinear function of the maximum shear strain in the plane perpendicular to the propagation of light. Several parameters may affect the strain response including luminescent polarization efficiency, optical sensitivity, coating absorptivity and effective excitation-emission wavelength. The temperature dependency of these parameters is important to characterize if the technique is extended to high-temperature or cyclic-temperature environments. A small thermal chamber was constructed with open optical access to test coated cantilevered specimens under a linearly varying bending stress. Results show that the optical strain response decreases as temperature increases. Over a temperature range spanning from 24 °C to 92 °C, the optical strain response decreased by 77%. Most of the percentage drop occurred between 35 °C and 80 °C, with relatively constant response for temperatures lower and higher. The primary source of the temperature dependency is the coating sensitivity coefficient which is a function of the modulus of elasticity. Higher strains tended to delay the transition, indicating strain-temperature coupling in the optical sensitivity coefficient.

An identification method for estimating the time varying excitation force acting on a structural system based on its response measurement is presented in this study. The method employs the simple Kalman filter to establish a regression model between the residual innovation and the input excitation forces. Based on the regression model, a recursive least-squares estimator is proposed to identify the input excitation forces incorporating with the measurement noise and the modeling error. In applying the method, the ambient vibration measurement of a structural system was used first. The stochastic subspace identification is applied to estimate the system matrix "A" and the measurement matrix "C". Then the Kalman filter with a recursive estimator is applied to determine the input excitation forces. The dynamic excitation forces are estimated from the measured structural responses by an inverse algorithm while least-square method with a recursive estimator is employed to update the estimation in the sense of real-time computation. Verification of the method with numerical simulation through MIMO system is conducted first. Identification of soil forces during the shaking table test of soil-pile interaction is also demonstrated.

Electro-mechanical impedance (EMI) method utilizing smart piezoelectric sensors has emerged as a promising technology for structural health monitoring in civil, mechanical and aerospace engineering. However, two major limiting factors have prevented field deployment of this method in real life. First, smart piezoelectric sensors, such as Lead Zirconate Titanate (PZT) patches, are highly sensitive to environmental changes such as temperature, humidity, and vibration. Secondly, bulky and expensive equipment is needed for performing impedance measurement. This paper proposes a feedback-enhanced electro-mechanical impedance (FEMI) technique for improving robustness against environmental variations and a design of a low-power EMI sensor with built-in measurement circuitries based on this new technique. The proposed FEMI technique employs a feedback scheme to amplify the peaking characteristics of the natural resonance frequencies in the EMI frequency response. The feedback loop includes a phase-locked loop (PLL) and a transimpedance amplifier (TIA). An analog EMI measurement circuit is developed to replace bulky EMI measurement instruments. To keep the power consumption low, the proposed system does not require any analog-to-digital conversion or DSP circuit blocks, but uses a simple analog mixer to multiply input and output waveforms of the PZT sensor, and then extract the EMI amplitude by passing the mixer output through a low-pass filter (LPF). The performance of the proposed FEMI sensor is verified by simulations using MATLAB. Simulated natural frequency peaks in the EMI spectrum are noticeably sharper with the feedback scheme than the one without feedback. As a result, the natural frequency shift due to any structural change can be more easily detected. To quantify the shift of these natural frequency peaks, the root mean square deviation (RMSD) of the difference between cases with and without damage is calculated. The simulation results show that the RMSD with feedback is greater than the RMSD without feedback by a factor of 3.2, when the damage is emulated by a 30% decrease in stiffness. This result confirms that the FEMI technique with the proposed EMI measurement circuits can detect structural damage with higher sensitivity compared to existing methods. Our future goal is to build a prototype for the FEMI sensors and integrate all the circuitries in a single CMOS chip.

Damage identification of structures is an important task of a health monitoring system. The ability to detect damages on-line or almost on-line will ensure the reliability and safety of structures. Analysis methodologies for structural damage identification based on measured vibration data have received considerable attention, including the least-square estimation (LSE), extended Kalman filter (EKF), etc. Recently, new analysis methods, referred to as the sequential non-linear least-square estimation (SNLSE) and quadratic sum-squares error (QSSE), have been proposed for the damage tracking of structures. In this paper, these newly proposed analysis methods will be compared with the LSE and EKF approaches, in terms of accuracy, convergence and efficiency, for damage identification of structures based on experimental data. A series of experimental tests using a small-scale 3-story building model have been conducted. In these experimental tests, white noise excitations were applied to the model, and different damage scenarios were simulated and tested. Here, the capability of the adaptive LSE, EKF, SNLSE and QSSE approaches in tracking the structural damage are demonstrated using experimental data. The tracking results for the stiffness of all stories, based on each approach, are compared with the stiffness predicted by the finite-element method. The advantages and drawbacks for each damage tracking approach will be evaluated in terms of the accuracy, efficiency and practicality.

The damage locating vector (DLV) method based on dynamic response is (a) modified for structural damage detection using normalized cumulative energy (instead of stress) indicator, (b) applied to the case where the number of sensors used is small compared to the structural degrees of freedom, and (c) employed to identify multiple damaged elements of an existing structure. From the measured structural dynamic response at the reference and damaged states, the change in flexibility matrix at sensor locations is formulated based on which the DLV is calculated. The DLV is a set of static load vector which has the property that when applied to the structure at its reference state, no energy is induced in the damaged elements providing the basis to identify damaged elements. The efficiency and robustness of the proposed method are examined using both simulated and experimental data.

This paper present a new displacement reconstruction scheme using only acceleration measured from a structure. For a given set of acceleration data, the reconstruction problem is formulated as a boundary value problem in which the acceleration is approximated by the second-order central finite difference of displacement. The displacement is reconstructed by minimizing the least squared errors between measured and approximated acceleration within a finite time interval referred to as a time window. An overlapping time window is introduced to improve the accuracy of the reconstructed displacement. The displacement reconstruction problem becomes ill-posed because the boundary conditions at both ends of each time window are not known a priori. Furthermore, random noise in measured acceleration causes physically inadmissible errors in the reconstructed displacement similar to the conventional time integration schemes. A Tikhonov regularization scheme is adopted to alleviate the ill-posedness. The validity of the proposed method is demonstrated through two laboratory experiments.

The ability of an early detection of possible damage in a structure especially when subjected to severe external loadings is a very important research topic. Damage in a structure usually comes with nonlinear and time-varying characteristics, such as hysteresis, that lead to time-varying structural parameters. Identification of time-varying structural parameters is necessary for assessing the safety of these damaged structures. A time-varying system identification technique using wavelet multi-resolution analysis is proposed in this paper. Wavelet is well known for its ability to approximate and represent arbitrary temporal functions. By expressing the time-varying parameters in a hysteretic structure using wavelet multi-resolution models, the problem of identification of these time-varying parameters is transformed to a time-invariant problem that depends on solving constant wavelet coefficients. An orthogonal forward regression algorithm is then adopted to prune insignificant wavelet coefficients while estimating those significant ones. Examples of single- and multi-degree-of-freedom hysteretic structures with different time-varying properties are given to demonstrate the applicability and accuracy of the proposed approach.

This paper investigates the use of filtering techniques such as the Low-pass and Kalman filter in combination with the quasi-static strain-displacement transformation in order to estimate dynamic structural displacement based on noisy strain measurements. Numerical simulations and vibration experiments were performed on simple beam structures under various dynamic loading cases to determine the sensitivity of estimation procedures against model errors and noise disturbance. In the experimental setup the multiplexing ability of fiber Bragg grating (FBG) sensors was used to obtain strain data with high accuracy and low noise level. Estimated displacements in the experiment were verified against laser displacement readings. Depending on the load case the noise-sensitive, quasi-static shape estimation results could be highly improved by applying recursive filtering methods which allow an application of the simple approach even for complex, vibrating structures.

This paper proposes a warranty system based on a seismic performance agreement, and investigates its feasibility. Specifically, we focus on making clear to building users the relationship between seismic force and seismic damage or loss, and propose a warranty agreement in which accountability of seismic loss is defined in terms of ground motion parameters obtained by a seismic sensor. This study uses the Japan Meteorological Agency seismic intensity scale (I-jma) because of its general acceptance and recognition. A portfolio of buildings in 10 suburbs of the Kanto region is chosen for seismic portfolio analysis. The following conclusions were derived: 1. For a portfolio of 10 base-isolated buildings, the builder's seismic expected loss was found to be approximately 0.01%. 2. In regards to feasibility of risk finance by seismic derivatives, this study found that it is possible to transfer most of builder's risk through a 0.01% premium rate. 3. Builder risk reduction was verified by use of a seismometer. 4. A new contract warranty agreement for seismic loss insurance for users was proposed, and it can reduce the premium to 1/15 of the current seismic insurance schemes.

Among many damage types, prestress-loss in tendon is the major one that should be monitored in its early stage in order to secure the safety of PSC girder bridges. This damage-type obviously change vibration characteristics, but with apparent difference depending on sensing mechanism as well as information analysis. Recently, there have been research efforts to develop wireless smart sensor nodes embedded damage monitoring algorithms for various sensing mechanisms. In this study, vibration-based damage monitoring algorithms which are appropriate for the smart sensor nodes to alarm the occurrence of prestress-loss in PSC girder bridges are presented. Firstly, two sensing mechanisms are considered for vibration characteristics: one is acceleration and the other is electro-mechanical impedance. Also, four acceleration-based algorithms and three impedance-based algorithms are selected to extract features from those signals. Secondly, the performances of those selected methods are evaluated using a large-scaled PSC girder for which a set of acceleration-impedance tests were measured for several prestress-loss scenarios by using both commercial instruments and a wireless smart sensor node.

Water supply systems are essential for public health, ease of living, and industrial activity; basic to any modern city. But water leakage is a serious problem as it leads to deficient water supplies, roads caving in, leakage in buildings, and secondary disasters. Today, the most common leakage detection method is based on human expertise. An expert, using a microphone and headset, listens to the sound of water flowing in pipes and relies on their experience to determine if and where a leak exists. The purpose of this study is to propose an easy and stable automatic leak detection method using acoustics. In the present study, 10 leakage sounds, and 10 pseudo-sounds were used to train a Support Vector Machine (SVM) which was then tested using 69 sounds. Three features were used in the SVM: average Itakura Distance, maximum Itakura Distance and the largest eigenvalue as derived from Principal Component Analysis. This paper focuses on the Itakura Distance, which is a measure of the difference between AR models fitted to two data sets, and is found using the identified AR model parameters. In this study, 10 leakage sounds are used as a standard reference set of data. The average Itakura Distance is the average difference between a test datum and the 10 reference data. The maximum Itakura Distance is the maximum difference between a test datum and the 10 reference data. Using these measures and the PCA eigenvalues as features for our SVM, classification accuracy of 97.1% was obtained.

We have developed a novel damage monitoring system that can monitor the integrity of composite structures in aircrafts. In this system, fiber Bragg grating (FBG) sensors are used as sensors and piezoelectric transducers (PZT) are used as the generators of elastic waves that propagate in the structure to be inspected. The damage monitoring system can detect the structural integrity by the change in elastic waves that are detected by the FBG sensor and arrayed waveguide grating (AWG)-type filter. We confirmed that the structure health monitoring (SHM) system was able to monitor the damage initiation and propagation by a change in the waveform of the elastic waves in coupon specimens and structural element specimens. In this study, we demonstrate the detectability of the damage monitoring system by using a subcomponent test specimen that simulates an actual aircraft wing box structure composed of carbon fiber reinforced plastics (CFRPs). The FBG sensors and PZTs are bonded to the surfaces of hat-shaped stringers by an adhesive. Damages such as de-bonding and delamination are introduced in the bonded sections of the skin and stringers by impact. Damage monitoring and diagnosis are carried out by the SHM system under ambient conditions. We successfully verify the detectability of our system.

This paper presents modeling, fabrication, and testing results for a high flow-rate and high frequency Nitinol MEMS valve. ANSYS^(R) is used to evaluate several Nitinol MEMS valve structural designs with the conclusion that a pentagonal flap with five legs produces higher frequencies and higher strengths without the inherent rotation problem present in standard designs. The Nitinol penta-leg design was fabricated using a novel bi-layer lift-off method. A PMGI polymer layer is initially used as an underlayer while a chromium layer is used as a top layer to produce a non-rotational ortho-planar Nitinol MEMS valve array. This array consists of 65 microvalves with dimensions of 1mm in circumference, 50 μm in leg width, and 8.2 μm in Nitinol thickness. Each microvalve covers an orifice of 220 μm in diameter and 500 μm in length and is capable of producing a 150 μm vertical deflection. This Nitinol MEMS valve array was tested for flow-rates in a hydraulic system as a function of applied pressure with a maximum water flow-rate of 16.44 cc/s.

Health monitoring systems require a means for detecting and quantifying abnormalities from measured signals. In this paper, a new method for detecting abnormalities in a human gait is proposed for an improved gait monitoring system for patients with walking problems. In the previous work, we introduced a fuzzy logic algorithm for detecting phases in a human gait based on four foot pressure sensors for each of the right and left foot. The fuzzy logic algorithm detects the gait phases smoothly and continuously, and retains all information obtained from sensors. In this paper, a higher level algorithm for detecting abnormalities in the gait phases obtained from the fuzzy logic is discussed. In the proposed algorithm, two major abnormalities are detected 1) when the sensors measure improper foot pressure patterns, and 2) when the human does not follow a natural sequence of gait phases. For mathematical realization of the algorithm, the gait phases are dealt with by a vector analysis method. The proposed detection algorithm is verified by experiments on abnormal gaits as well as normal gaits. The experiment makes use of the Smart Shoes that embeds four bladders filled with air, the pressure changes in which are detected by pressure transducers.

As an emerging technology for in-situ damage detection and nondestructive evaluation, structural health monitoring with active sensors (active SHM) plays as a promising candidate for the pipeline inspection and diagnosis. Piezoelectric wafer active sensor (PWAS), as an active sensing device, can be permanently attached to the structure to interrogate it at will and can operate in propagating wave mode or electromechanical impedance mode. Its small size and low cost (about ~$10 each) make itself a potential and unique technology for in-situ SHM application. The objective of the research in this paper is to develop a permanently installed in-situ "multi-mode" sensing system for the corrosion monitoring and prediction of critical pipeline systems. Such a system is used during in-service period, recording and monitoring the changes of the pipelines over time, such as corrosion, wall thickness, etc. Having the real-time data available, maintenance strategies based on these data can then be developed to ensure a safe and less expensive operation of the pipeline systems. After a detailed review of PWAS SHM methods, including ultrasonic, impedance, and thickness measurement, we introduce the concept of PWAS-based multi-mode sensing approach for corrosion detection in pipelines. Particularly, we investigate the potential for using PWAS waves for in thickness mode experimentally. Finally, experiments are conducted to verify the corrosion detection ability of the PWAS network in both metallic plate and pipe in a laboratory setting. Results show successful corrosion localization in both tests.

The reflective spectrum of fiber Bragg grating (FBG) sensor under axial uniform stresses has a single peak with narrow bandwidth and high reflectivity. But, if the impact-induced damage is generated around FBG sensor attached on the sandwich panel, peak splits can occur due to strain gradient and transverse loading. The detection of the impact-induced damage is very important for structural safety, because this damage can degrade the flexural properties of sandwich panels. From the experiments, the impact-induced damages were detected by using the reflective spectrum change of FBG sensors. Bending stiffness, among the key flexural properties of sandwich panels were measured by 4-point bending test. By matching these results at each experiment, the flexural property degradation of sandwich panels can be estimated after impacts at different energy levels. The survivability of FBG sensors after impact was found to be acceptable, as 11 out of 17 FBG sensors remained intact after the impact test.

Radiation detector capable of discriminating between different species of high energy ions is of great demand by aerospace and high energy physics communities. We propose the optical fiber-based real time ion detector and discriminator, which can have long lifetime in radiation environment, can be compact and low production cost. The basis of detector's principle of operation is the strong dependence of the pattern of energy dissipation with ion penetration depth in the matter on the type of the ion. Another key phenomenon enabling our fiber optic based detector is the refractive index change in optical fiber in the vicinity of particle track due to the dissipated energy. These two effects provide the opportunity to measure the energy dissipation versus penetration depth as well as total energy released simultaneously in real time with a single detector. Thus, different types of ions can be distinguished by measuring total energy dissipated and energy dissipation versus distance. To discriminate between ions species we propose to use measurement of the Bragg peak position. Total energy dissipated by the particle in the detector material and determination of the Bragg peak position gives the full information on the kind of the incident ion as confirmed via simulations.

Recent work by our research group on the dynamic demodulation of strain-induced wavelength shifts in fiber Bragg grating (FBG) sensors show that these sensors are suitable for the detection of high frequency ultrasonic waves produced by impact loading. A FBG sensor is incorporated into an optical detection system that uses a broadband tunable laser source in the C-band, a two wave-mixing photorefractive interferometer, and a high-speed photodetector. When an ultrasonic wave interacts with the FBG sensor, the wavelength of the reflected light in the fiber is dynamically shifted due to strain-induced perturbation of the index of refraction and/or the period of the grating in the fiber. The wavelength shift is converted into an intensity change by splitting the light into signal and pump beams and interfering the beams in an InP:Fe photorefractive crystal (PRC). The resulting intensity change is measured by a photodetector. The two-wave mixing (TWM) photorefractive interferometer allows for several FBG sensors to be wavelength multiplexed in one PRC and it also actively compensates for low frequency signal drifts associated with unwanted room vibrations and temperature excursions. In this work, we present preliminary experimental results on the detection of impact signals using a low power (1 mW) TWM PRC based demodulation system. The response time of the PRC is optimized by focusing the signal and pump beams into the crystal allowing for adaptivity of the demodulation system to quasi-static strains or temperature drifts. The TWM intensity gain of the system is optimized for efficient wavelength demodulation through resonant enhancement of the space charge electric field formed in the PRC. The low power demodulation system would facilitate significant reduction in the overall cost of the system.

This paper introduces a concept of smart structural elements for the real-time condition monitoring of bridges. These are prefabricated reinforced concrete elements embedding a permanent sensing system and capable of self-diagnosis when in operation. The real-time assessment is automatically controlled by a numerical algorithm founded on Bayesian logic: the method assigns a probability to each possible damage scenario, and estimates the statistical distribution of the damage parameters involved (such as location and extent). To verify the effectiveness of the technology, we produced and tested in the laboratory a reduced-scale smart beam prototype. The specimen is 3.8 m long and has cross-section 0.3 by 0.5m, and has been prestressed using a Dywidag bar, in such a way as to control the preload level. The sensor system includes a multiplexed version of SOFO interferometric sensors mounted on a composite bar, along with a number of traditional metal-foil strain gauges. The method allowed clear recognition of increasing fault states, simulated on the beam by gradually reducing the prestress level.

The strain and temperature sensing performance of FBG are studied in the temperature range of 123K to 273K by the experiment. The temperature sensitive, strain coefficient and cross-sensitivity coefficient of the sensors are derived analytically and verified by experiments. It is found that they are nonlinear. Cross sensitivity increase with lower temperature. At a constant temperature, the Bragg wavelength shift is linear with the longitudinal strain within the range of 5000 micro strains.

A parametric study of guided mechanical wave propagation in laminated safety glass (windshields) is presented. Laminated safety glass is considered a three layered structure modeled as a viscoelastic layer bonded by two elastic layers, i.e., glass plates. The interface between each of the two bonded layers is modeled as a bed of longitudinal and shear linear springs. The spring constants are estimated using surface analysis in conjunction with atomic force microscopy and profilometer analysis. Attenuation due to material absorption of the viscoelastic interlayer is considered while calculating the dispersion curves for the system. The dependence of phase and energy velocities, attenuation, and resonance frequencies, upon variations of material properties (e.g., modulus of elasticity, Poisson's ratio, and longitudinal and shear ultrasonic material attenuation) is discussed. The relative physical dimensions (i.e., layer thickness variation of each layer) influence upon guided wave behavior is also presented and discussed. Results are applicable to any similar three-layer laminated structure.

This research proposes the shape reconstruction algorithm for the deformation monitoring of composite structures using the high-resolution distributed strain data, which is obtained by the embedded optical fiber network. The accurate shape monitoring system is expected to be useful for full-scaled structural monitoring of larger composite structures. Once the optical fiber network is installed in the structure, such global shape monitoring system will provide an excellent tool for many monitoring applications in their life time. In this paper, we constructed the reconstruction algorithm for the deflection in the bending deformation of composite laminates. The high-resolution distributed strain data was obtained by one of the optical fiber sensing systems, pulse-pre-pump Brillouin optical time domain analysis (PPP-BOTDA) system. We fabricated a composite laminate specimen with an embedded optical fiber network, and the cantilever bending test was carried out. Using obtained distributed data, the deflection of the specimen was predicted using the constructed algorithm. The deflections were successfully reconstructed with a few percents of the prediction error. From the result, it was shown that the deformation of composite structures was able to be reconstructed with high estimation accuracy using our algorithm, which uses distributed strain data obtained by the embedded optical fiber network.

This paper reports the development of a low-cost inductively coupled passive wireless strain sensor which can be easily embedded within composite prepreg layers for structural health monitoring application. The sensor response shows great linearity, low hysteresis and drift, and sufficient sensing range for wireless interrogation. The sensor sensitivity is found to be relatively low, but with some modifications on the sensor pattern design approximately three-fold increase in sensitivity is obtained. The investigation on both sensor array and sensor directivity verifies its potential to be developed as wireless rosette strain sensor. In addition, mechanical tests are performed. Among the tested mechanical properties, the interlaminar shear strength of composite specimens degrades the most upon sensor embedment. Finally, an analytical model is developed. Its normalized resonant frequency shift due to strain change agrees well with the experimental result.

The use of piezoceramic materials for structural sensing and actuation is a fairly well developed practice that has found use in a wide variety of applications. However, just as advanced composites offer numerous benefits over traditional engineering materials for structural design, actuators that utilize the active properties of piezoelectric fibers can improve upon many of the limitations encountered when using monolithic piezoceramic devices. Several new piezoelectric fiber composites have been developed, however almost all studies have implemented these devices such that they are surface-bonded patches used for sensing or actuation. This paper will introduce a novel active piezoelectric structural fiber that can be laid up in a composite material to perform sensing and actuation, in addition to providing load bearing functionality. The sensing and actuation aspects of this multifunctional material will allow composites to be designed with numerous embedded functions including, structural health monitoring, power generation, vibration sensing and control, damping, and shape control through anisotropic actuation. A one dimensional micromechanics model of the piezoelectric fiber will be developed to characterize the feasibility of constructing structural composite lamina with high piezoelectric coupling. The theoretical model will be validated through finite element (FE) modeling in ABAQUS. The results will show that the electromechanical coupling of a fiber reinforced polymer composite incorporating the active structural fiber (ASF) could be more than 70% of the active constituent.

This paper presents a numerical study on a vibration control of a cantilever flexible beam using PZT patches. The PZT patches used as both actuators and sensors were adopted in the forms of surface-bond devices on the flexible aluminum beam to control actively the vibration responses. The beam was actuated electrically by the PZT actuator to generate the vibration and the feedback signals were collected by the PZT sensors during the numerical analysis and experimental validation. A finite element method (FEM) in which the materials of the beam and PZTs were coupled was used numerically to analyze the vibration and structural control. A compare study between the numerical simulation and experiment results was finished. The results of the FEM simulation showed that it was effective to use PZT patches to control the responses of flexible structure and the proposed numerical method was also successful in analyzing the vibration responses of the coupled material structures.

In this paper, an intelligent control methodology is proposed to mitigate earthquake vibrations in a building. The structure object of study is a 10-story building whose base is isolated by means of a passive actuator and an MR damper. The system has uncertain parameters and nonmeasurable variables that must be accounted for in order to gain good control performance. Besides, the system is subject to unknown perturbations (incoming earthquakes). An adaptive backstepping controller is designed to generate the actuator control signal based on the base velocity and displacement measurements as well as on the dynamics of the base isolation system. Uncertainty in structure stiffness and damping coefficients are compensated by parameter adaptation. The MR damper can be modeled by the well known Bouc-Wen model. However, this model contains an unmeasurable variable, z, that describes the hysteretic behavior, so it must be estimated. A neural network approximator is proposed to estimate the unmeasurable variable. This way, the hysteresis effect is modeled by the neural network. The control performance is verified by simulations performed in MATLAB/Simulink using common earthquakes such as those of El Centro and Taft.

An embeddable sensor mote for structural monitoring is described. The Missouri University of Science and Technology (MST) F1 mote is designed to provide a general platform for sensing, networking, and data processing. The platform consists of an 8051 variant processor, two 802.15.4 variant radio platform options, micro Smart Digital (SD^TM) flash storage, USB connectivity, RS-232 connectivity, and various sensor capabilities. Sensor capabilities include, but are not limited to, strain gauges, a three-axis multi-range accelerometer, thermocouples, and interface options for other digital and analog sensors via a screw terminal block. In its default configuration the strain conditioning channel is appropriate for structural monitoring, but through reconfiguration it can be used with other resistive bridge transducers for pressure, force, displacement, etc. The F1 mote provides capabilities for strain, temperature, and vibration sensing in a small package. The mote is used at MST for networked monitoring of structures and networked robotic vehicles. In this paper an overview of the F1 mote will be given that emphasizes its operating architecture and potential applications. Applications include infrastructure monitoring for structures such as bridges, levees, and buildings as well as robotics, machine monitoring, and sensor networks. The described platform provides novelty in that it has the ability to be a dedicated structural monitoring system, however can be also used in development of other systems. The F1 platform was designed to combine features of available dedicated platforms and available development kits. The F1 provides a novel combination of sensing, processing, and application possibilities for the targeted application areas.

Sensors and actuators based on piezoelectric plates have shown increasing demand in the field of smart structures, including the development of actuators for cooling and fluid pumping applications and transducers for novel energy harvesting devices. This project involves the development of a finite element and topology optimization software to design piezoelectric sensors, actuators and energy harvesting devices by distributing piezoelectric material over a metallic plate in order to achieve a desired dynamic behavior with specified vibration frequencies. The finite element employs a general formulation capable of representing both direct and converse piezoelectric effects. It is based on the MITC formulation, which is reliable, efficient and avoids the shear locking problem. The topology optimization formulation is based on the PEMAP-P model (Piezoelectric Material with Penalization and Polarization), where the design variables are the pseudo-densities that describe the amount of piezoelectric material at each finite element. The optimization problem has a multi-objective function, which can be subdivided into three distinct problems: maximization of mean transduction, minimization of mean compliance and optimization of Eigenvalues. The first one is responsible for maximizing the amount of electric energy converted into elastic energy, the second one guarantees that the structure does not become excessively flexible and the third one tunes the structure for a given frequency. This paper presents the implementation of the finite element and optimization software and shows preliminary results achieved.

Transduction of electrical signals to mechanical signals and vice-versa in piezoelectric materials is controlled by the material coupling coefficient. In general in a loss-less material the ratio of energy conversion per cycle is proportional to the square of the coupling coefficient. In practical transduction however the impedance mismatch between the piezoelectric material and the electrical drive circuitry or the mechanical structure can have a significant impact on the power transfer. In this paper a novel method of matching the acoustic impedance of structures to the piezoelectric material are described and discussed in relation to the objective of increasing power transmission and efficiency. In typical methods the density and acoustic velocity of the matching layer is adjusted to give "ideal" matching between the transducer and the load. The approach discussed in this paper utilizes solid micro horn arrays in the matching layer which channel the stress and increase the strain in the layer. This approach is found to have potential applications in energy harvesting, medical ultrasound and in liquid and gas coupled transducers.

In this article, the design of a biology-inspired miniature directional microphone is presented. This microphone consists of two clamped circular diaphragms, which are mechanically coupled by a connecting bridge that is pivoted at its center. A theoretical model is constructed to determine the microphone response to sound incident from an arbitrary direction. Both the simulation and preliminary experimental results show that the proposed microphone provides a remarkable amplification of the time delay associated with the sound induced diaphragm responses. This study should be relevant to various sound source localization applications.

The purpose of this study is to develop a novel thermokinetically-driven actuator technology based on the physics of metal hydrides (MH's). A metal hydride absorbs and desorbs hydrogen due to the imposed temperature swing(s). The MH can also work as an effective thermally-driven hydrogen compressor producing more than 5,000 psia net pressure swing. The MH actuation system can be built in a simple structure, exhibits high power, produces soft actuating, and is essentially noiseless. Moreover, it is much more powerful and compact than conventional pneumatic systems that require bulky auxiliary systems. It is our belief that the MH actuators are useful for many emerging industrial, biorobotic, and civil structural applications. In this paper, we report the recent preliminary experimental results for a laboratory-prototyped MH actuation system. In particular, the dynamic response characteristics, enhanced controllability, thermodynamic performances, and reliability of the metal hydride actuator were studied in order to estimate the actuation capability of the MH actuator. A unique design of the MH actuator was created. It encases a so-called "porous metal hydride (PMH)" in the reactor to effectively achieve desirable performance by improving overall thermal conductance.

A nanostructured sensing element based on anodic aluminum oxide (AAO) nanowells was fabricate and assessed for hydrogen gas sensing. AAO nanowells with an average diameter of 73 nm and depth proportional to the anodization time were immersed in a surfactant solution and coated with an 8 nm film of palladium nanoparticles. The electrical resistance change of the nanostructure with hydrogen gas exposure was used as the sensing parameter. The AAO nanowells-Pd nanostructures were characterized using atomic force microscopy (AFM), field-emission scanning electron microscopy (FESEM), and contact angle test. Hydrogen concentrations as low as 0.05 vol% (500 ppm) can be detected at room temperature. Response times as fast as 1.15 seconds were obtained. Compared to current devices and nanostructures in development, the AAO nanowell-Pd nanostructure is found to be considerably fast without compromising sensitivity and selectivity.

This paper presents a new approach, based on H₂ optimal control theory, for the maximization of power generation in energy harvesting systems. The theory determines the optimal harvested power attainable through the use of power electronics to effect linear feedback control of transducer current. In contrast to most of the prior work in this area, which has assumed harmonic response, the theory proposed here applies to stochastically-excited systems in broadband response, and can be used to harvest power simultaneously from multiple significant vibratory modes. It is also applicable to coupled networks of many transducers. The theory accounts for the impact of energy harvesting on the dynamics of the vibrating system in which the transducers are embedded. It also accounts for resistive and semiconductor dissipation in the power-electronic network interfacing the transducers with energy storage. Thus, losses in the electronics are addressed in the formulation of the optimal control law. Finally, the H₂-optimal control formulation of the problem naturally allows for harvested power to be systematically balanced against other response objectives. Here, this is illustrated by showing how the harvesting objective can be maximized, subject to the constraint that the transducer voltages be maintained below that of the power-electronic bus; a condition which is required for the power-electronic control system to be fully operational. Although the theory is applicable across a broad range of applications, it is presented in the context of a piezoelectric bimorph example.

Piezoelectric materials have received considerable attention from the smart structure community because of their potential use as sensors, actuators and power harvesters. In particular, polyvinylidene fluoride (PVDF) has been proposed in recent years as an enabling material for a variety of sensing and energy harvesting applications. In this study, carbon nanotubes (CNT) are included within a PVDF matrix to enhance the properties of PVDF. The CNT-PVDF composite is fabricated by solvent evaporation and melt pressing. The inclusion of CNT allows the dielectric properties of the PVDF material to be adjusted such that lower poling voltages can be used to induce a permanent piezoelectric effect in the composite. To compare the piezoelectric characteristics of the CNT-PVDF composite proposed, scanning electron microscope (SEM) images were analyzed and ferroelectric experiments were conducted. Finally, the aforementioned composites were mounted upon the surface of a cantilevered beam to compare the voltage generation of the CNT-PVDF composite against homogeneous PVDF thin films.

The declining state of civil infrastructure has motivated researchers to seek effective methods for real-time structural health monitoring (SHM). Decentralized computing and data aggregation employing smart sensors allow the deployment of a dense array of sensors throughout a structure. The Imote2, developed by Intel, provides enhanced computation and communication resources that allow demanding sensor network applications, such as SHM of civil infrastructure, to be supported. This study explores the development of a versatile Imote2 sensor board with onboard signal processing specifically designed for the demands of SHM applications. The components of the accelerometer board have been carefully selected to allow for the low-noise and high resolution data acquisition that is necessary to successfully implement SHM algorithms.

Triggering instrumentation for autonomous monitoring of load-induced strain is described for economical, fast bridge inspection. The development addresses one aspect for the management of transportation infrastructure - bridge monitoring and inspection. The objectives are to provide quantitative performance information from a load test, to minimize the setup time at the bridge, and to minimize the closure time to traffic. Multiple or networked measurements can be made for a prescribed loading sequence. The proposed smart system consists of in-situ strain sensors, an embedded data acquisition module, and a measurement triggering system. A companion control unit is mounted on the truck serving as the load. As the truck moves to the proper position, the desired measurement is automatically relayed back to the control unit. In this work, the testing protocol is developed and the performance parameters for the triggering and data acquisition are measured. The test system uses a dedicated wireless sensor mote and an infrared positioning system. The electronic procedure offers improvements in available information and economics.

Recent disease surveys on some cable-supported bridges show that cable corrosion is one of the main dangers for bridge safety, serviceability and durability. Since cables are the main supporting components for these bridges, this type of damage must be detected at the earliest possible stage for further maintenance. Acoustic monitoring technique shows an efficient way for this purpose. This paper presents such a research on modeling and wavelet analyzing the acoustic emission signal in seven-wire strands for damage diagnosis. In order to demonstrate the accuracy of the proposed technique, the propagation of the guided waves in a cylindrical bar is examined firstly. These modeling results are compared to some analytical results. The comparisons clearly illustrate the effectiveness of the guided wave propagation modeling technique and verify the potential of the modeling technique on solving those problems whose analytical solution is not available due to the complexity of the component geometry. The modeling technique is then used to generate the wave samples for two damage conditions of the seven-wire strands and a wavelet based pattern extraction technique is adopted to extract the baseline time-frequency characteristics of the wave.

This paper presents the design, theory, characterisation and application of a novel fibre optic acoustic emission (AE) sensor. The sensor consists of a pair of optical fibres that are heated, fused and drawn to create a fused-tapered region that is sensitive to acoustic perturbations. The sensor is housed in a silica V-groove. The modelling of this fibre optic AE sensor is presented with a finite element analysis on the strain field based on the effect of the geometry within the sensing region. The characterisation of the sensor was carried out using a glass block with 160mm thickness as an acoustic medium. The applications of this sensor were demonstrated in three experiments. Firstly, the sensor was surface-mounted in carbon fibre reinforced composite samples and tested to failure under tensile loading. In the second experiment, the sensor was surface-mounted on double-cantilever Mode-I test specimens. The AE response from the sensor was correlated to the inferred modes of failure during the Mode-I test. In the third experiment, the sensor was surface-mounted onto the composite "blow-off" test samples. The feasibility of using the sensor to detect damage development in real-time was demonstrated.

Acoustic emission techniques (AET) have a lot of potential in structural health monitoring for example to detect cracks or wire breaks. However, the number of actual applications of conventional wired AET on structures is limited due to the expensive and time consuming installation process. Wires are also vulnerable to damage and vandalisms. Wireless systems instead are easy to be attached to structures, scalable and cost efficient. A hybrid sensor network system is presented being able to use any kind of commercial available AE sensor controlled by a sensor node. In addition micro-electro-mechanical systems (MEMS) can be used as sensors measuring for example temperature, humidity or strain. The network combines multi-hop data transmission techniques with efficient data pre-processing in the nodes. The data processing of different sensor data prior to energy consuming radio transmission is an important feature to enable wireless networking. Moreover, clusters of sensor nodes are formed within the network to compare the pre-processed data. In this way it is possible to limit the data transfer through the network and to the sink as well as the amount of data to be reviewed by the owner. In particular, this paper deals with the optimization of the network to record different type of data including AE data. The basic principles of a wireless monitoring system equipped with MEMS sensors is presented along with a first prototype able to record temperature, moisture, strain and other data continuously. The extraction of relevant information out of the recorded AE data in terms of array data processing is presented in a second paper by McLaskey et al. in these proceedings. Using these two techniques, monitoring of large structures in civil engineering becomes very efficient.

As civil infrastructure ages, the early detection of damage in a structure becomes increasingly important for both life safety and economic reasons. This paper describes the analysis procedures used for beamforming acoustic emission techniques as well as the promising results of preliminary experimental tests on a concrete bridge deck. The method of acoustic emission offers a tool for detecting damage, such as cracking, as it occurs on or in a structure. In order to gain meaningful information from acoustic emission analyses, the damage must be localized. Current acoustic emission systems with localization capabilities are very costly and difficult to install. Sensors must be placed throughout the structure to ensure that the damage is encompassed by the array. Beamforming offers a promising solution to these problems and permits the use of wireless sensor networks for acoustic emission analyses. Using the beamforming technique, the azmuthal direction of the location of the damage may be estimated by the stress waves impinging upon a small diameter array (e.g. 30mm) of acoustic emission sensors. Additional signal discrimination may be gained via array processing techniques such as the VESPA process. The beamforming approach requires no arrival time information and is based on very simple delay and sum beamforming algorithms which can be easily implemented on a wireless sensor or mote.

Acoustic emission (AE) has emerged as a powerful nondestructive tool to detect preexisting defects or to characterize failure mechanisms. Recently, this technique or this kind of principle, that is an in-situ monitoring of inside damages of materials or structures, becomes increasingly popular for monitoring the integrity of large structures. Concrete is one of the most widely used materials for constructing civil structures. In the nondestructive evaluation point of view, a lot of AE signals are generated in concrete structures under loading whether the crack development is active or not. Also, it was required to find a symptom of damage propagation before catastrophic failure through a continuous monitoring. Therefore we have done a practical study in this work to fabricate compact wireless AE sensor and to develop diagnosis system. First, this study aims to identify the differences of AE event patterns caused by both real damage sources and the other normal sources. Secondly, it was focused to develop acoustic emission diagnosis system for assessing the deterioration of concrete structures such as a bridge, dame, building slab, tunnel etc. Thirdly, the wireless acoustic emission system was developed for the application of monitoring concrete structures. From the previous laboratory study such as AE event patterns analysis under various loading conditions, we confirmed that AE analysis provided a promising approach for estimating the condition of damage and distress in concrete structures. In this work, the algorithm for determining the damage status of concrete structures was developed and typical criteria for decision making was also suggested. For the future application of wireless monitoring, a low energy consumable, compact, and robust wireless acoustic emission sensor module was developed and applied to the concrete beam for performance test. Finally, based on the self-developed diagnosis algorithm and compact wireless AE sensor, new AE system for practical AE diagnosis was demonstrated for assessing the conditions of damage and distress in concrete structures.

Concrete structures have been used widely in civil infrastructural systems especially in bridges. Due to the complex nature of its microstructure, nondestructive testing (NDT) of concrete inherently imposes many challenges, which can cause severe limitations to both the resolution and sensitivity of the observed signals. In this study, surface wave propagation in concrete is examined and simulated by using a surface bonded active piezoelectric actuators/sensors system experimentally and numerically, especially at high frequency. First, different experimental tests are conducted to evaluate effects of the loading frequency upon the resulting surface wave propagation. Secondly, the numerical results are compared with experimental data. The very good agreement shows the great feasibility and potential of surface wave signals by using piezoelectric actuators/sensors to locate and characteristics of surface damages.

Predicted time-history responses from a finite-element (FE) model provide a baseline map where damage locations are clustered and classified by extracted damage-sensitive wavelet coefficients such as vertical energy threshold (VET) positions having large silhouette statistics. Likewise, the measured data from damaged structure are also decomposed and rearranged according to the most dominant positions of wavelet coefficients. Having projected the coefficients to the baseline map, the true localization of damage can be identified by investigating the level of closeness between the measurement and predictions. The statistical confidence of baseline map improves as the number of prediction cases increases. The simulation results of damage detection in a truss structure show that the approach proposed in this study can be successfully applied for locating structural damage even in the presence of a considerable amount of process and measurement noise.

The frequency-shift based damage detection method entertains advantages such as the global detection capability and the easy implementation, but also suffers from drawbacks that include low detection sensitivity and the difficulty in identifying damage using a small number of measurable frequencies. Meanwhile, the damage detection performance is inevitably affected by the uncertainty/variations in the baseline model. In this research, we investigate an enhanced statistical damage identification method using the tunable piezoelectric circuitry. The tunable piezoelectric circuitry can lead to much enriched information of frequency-shift (before and after damage occurrence). The circuitry elements, meanwhile, can be directly and accurately measured and thus can be considered uncertainty-free. A statistical damage identification algorithm is formulated which can provide both the mean and variance of the elemental property changes. Our analysis indicates that the integration of the tunable piezoelectric circuitry can significantly enhance the robustness in damage identification under uncertainty and noise.

The basic idea of the impedance-based damage detection is that the electrical impedance of the piezoelectric transducer is directly related to the mechanical impedance of the host structure. Therefore, damage effect is reflected in the change of the piezoelectric impedance curves before and after damage occurrence. Previous studies in this area mainly focus on declaring damage occurrence. In this research, we develop a model-based identification method that can identify both the damage location and the severity of the damage. The model is built upon the spectral element method, which has high accuracy and numerical efficiency in the high frequency range. Using the difference between the measured and healthy impedance curves as input, an inverse identification procedure is developed to extract directly the property change of the elements. Extensive numerical and experimental studies are carried out to demonstrate the effectiveness of the proposed method.

This paper reports on the development of an optical fibre sensor comprising an array of uniformly distributed Bragg gratings that are configured to allow for the detection and modal decomposition of structural plate waves. Aspects of the design, fabrication and validation of the sensor are discussed. Laser vibrometry (LV) and advanced numerical modeling are used to demonstrate the fidelity of dynamic strain measurements furnished by a fibre Bragg grating. The sensor is applied in an experimental study involving a metal plate where it is shown that mode conversion of Lamb waves caused by a structural inhomogeneity is robustly measured.

Ionic Polymer Metal Composite (IPMC) is a nano-scale metal deposited ionic polymer and may be used as soft actuator and sensor. Numerous researches have been conducted to study IPMC as actuator. Many other applications like energy harvesting, impact sensing and velocity sensing use IPMC as a sensor, thus making it necessary to understand sensing nature of IPMC. It has been demonstrated that production of charge under the influence of mechanical deformation in IPMC, is a combined effect of chemical, mechanical and electrical response which may be affected by nature of existing cation and, conductivity and morphology of electrodes. This paper presents a comparison between the sensing behavior of IPMC under the influence of different cations like Li⁺, Na⁺ and H⁺. In addition, experiments were also performed to study the effect of nano-to-micro scale surface cracks in IPMC. It was also discovered that inducing nano-to-micro scale surface cracks in IPMC improves the sensing characteristics of IPMC. Experiments were also performed to compare the effect of electrode surface morphology and conductivity on sensing performance of IPMC. These effects were also compared for energy harvesting applications of IPMC.

This paper presents some preliminary results of an ongoing project. A pattern classification algorithm is being developed and embedded into a Field-Programmable Gate Array (FPGA) and microprocessor-based data processing core in this project. The goal is to enable and optimize the functionality of onboard data processing of nonlinear, nonstationary data for smart wireless sensing in structural health monitoring. Compared with traditional microprocessor-based systems, fast growing FPGA technology offers a more powerful, efficient, and flexible hardware platform including on-site (field-programmable) reconfiguration capability of hardware. An existing nonlinear identification algorithm is used as the baseline in this study. The implementation within a hardware-based system is presented in this paper, detailing the design requirements, validation, tradeoffs, optimization, and challenges in embedding this algorithm. An off-the-shelf high-level abstraction tool along with the Matlab/Simulink environment is utilized to program the FPGA, rather than coding the hardware description language (HDL) manually. The implementation is validated by comparing the simulation results with those from Matlab. In particular, the Hilbert Transform is embedded into the FPGA hardware and applied to the baseline algorithm as the centerpiece in processing nonlinear time histories and extracting instantaneous features of nonstationary dynamic data. The selection of proper numerical methods for the hardware execution of the selected identification algorithm and consideration of the fixed-point representation are elaborated. Other challenges include the issues of the timing in the hardware execution cycle of the design, resource consumption, approximation accuracy, and user flexibility of input data types limited by the simplicity of this preliminary design. Future work includes making an FPGA and microprocessor operate together to embed a further developed algorithm that yields better computational and power efficiency.

A continuous structure has several response characteristics that make it a candidate for a sensor used to locate an acoustic source. One of primary goals in developing such a sensor is to ensure that the response is rich enough to provide information about the impinging acoustic wave and its direction of travel without being too sensitive to background noise. As such, there are several factors that must be examined with regard to sensor configuration and measurement requirements. The research described here includes the initial study that examines various configuration requirements for such a sensor. Some of the parameters of interest include the size and aperture of the structure, boundary conditions, material properties, and thickness. Since it is expected that an inverse formulation will be used to reconstruct the transient acoustic pressure wave propagating across the structure's surface, the requirements for the inverse approach may also impact the structure's configuration. The initial results presented here include the impact of these factors on the response of a beam-like sensor structure. The response of the structure to transient sinusoidal wave excitations is examined numerically. To gain insight into the dynamic information contained within the response, methods like the wavenumber spectrum are utilized to assess the behavior. The tools presented here will be extended to alternative configurations prior to prototype development and testing. Supported by NSF Sensor Innovation and Systems.

In this paper the design and static analysis of a novel artificial muscle system are presented. The proposed design is based on exponential strain amplification applied to PZT stack actuators. Exponential strain amplification is achieved by means of a nested cellular architecture. The primary limitation of the nested strain amplification mechanisms is the loss of blocking force due to structural compliance. Therefore, to quantify and improve the performance of the design, analytical expressions are obtained for the blocking force and free displacement of two separate amplification mechanisms using Castigliano's strain energy and displacement theorem. Measured values for blocking force and free displacement validate the static behavior predicted by the solid mechanics. Design implications for the amplification mechanisms are then enumerated based on the theoretical modeling.

After the evolution over the last decade, the wireless sensor network (WSN) technology is successfully adopted into applications such as remote medical care, health monitoring, smart houses and vehicle electron fields. Rapid advancement of many technologies such as IC design, sensor technology, circuits/firmware development, communication protocol design, and network programming was incorporated into modern WSN technology and was recognized as one of the most important emerging technology. In order to further expand the application arena of WSN technology, a team of researchers from different fields, funded by Nation Science Council (NSC), Taiwan are now working together to push the technology forward and focus on a low cost WSN platform which may enable the application of WSN technology in general households or say smart living space. The first objective of the group was to establish a new wireless sensor network development platform with very low cost sensor nodes and also free software. With the new platform, the deployment cost of WSN technology will be minimized, and thus the application of the technology on different new areas can be explored especially the application of smart living space. This paper will detail the Super Node and Simple Node low-cost sensor code designed in this project, and also the software development platform, packet routing, data collection will be further introduced. The modulus design concept of both a Simple Node and Super Node for further integration with other application circuits in order to facilitate the prototype design for different applications will also be detailed.

Wireless sensors are becoming extremely popular for their ability to be employed in hostile and inaccessible locations to monitor various parameters of importance, and vibration energy harvesting shows great potential in powering these sensor networks. For efficient operation the device should operate in resonance at the environmental excitation frequency and hence requires a frequency tuning mechanism. Recently efforts have been attempted to broaden the frequency range of energy harvesting devices, but in terms of power density an efficient design methodology is lacking. In this work, a tunable energy harvesting device with high efficiency and power density is presented. The technique involves two single DOF's cantilever beams which are coupled in a novel fashion by means of magnetic force for resonance frequency tuning. Here the magnetic force acts as a variable stiffness coupling the two cantilever beams, allowing one to alter the corresponding resonance frequencies of the cantilever beams. Magnetic force of attraction and repulsion can be used to achieve the magnetic coupling and can increase the overall stiffness of either of the cantilever beams while decreasing the others. The total power output of the device is found to be between 180 μW to 320 μW.

One of the most sensitive problems regarding the application of SHM (Structural Health Monitoring) is found in the aeronautical segment. This field presents the necessity of monitoring small structural changes representing damage, due both to economic aspects and safety. In this contribution two helicopter blade structures (pertaining to a civil and a military helicopter) are studied. In both cases, two types of damage are inserted, namely holes and cracks. Through the impedance-based structural health monitoring method, an identification procedure using cluster analysis techniques was performed aiming at distinguishing these two types of damage. Then, a meta-model based on a probabilistic neural network was built for fault position identification.

In this paper we present a prototype of an Adaptive Optics system for the control of geometrical fluctuations in a laser beam in air based on the interferometric detection of the beam phase front. We show that this technique is of particular interest when high sensitivity and high band-pass are required for correction of small perturbations. The main technique adopted for the control is based on the interferometric detection of phase-front fluctuations: the beam is made to interfere with a reference beam, properly obtained, and the phase difference is read by means of a pixellated photodiode. The signals are then sampled by a fast automatic control system, which computes also the correction signals, and sent to the deformable mirror. In the paper we show and discuss some experimental results of the technique, discussing the most important limits and estimating the possibility of future developments and improvements.

A long period grating-based pH sensor has been designed in order to measure the pH in the ocean. The pH-sensitive hydrogel, which is made through the thermal crosslink of poly vinyl alcohol and poly acrylic acid, can swell or contract in response to the pH change in the surrounding environment. The sensor is designed in a single mode-multimode-single mode (SMS) fiber structure. The long period grating is written into the multimode fiber of the SMS structure using a focused CO₂ laser at the critical period (1 mm) of this particular multimode fiber. The hydrogel is glued underneath the SMS structure and will physically stretch or compress the long period grating hence change the phase matching condition in the SMS structure. Because of the different core sizes of the single mode fiber and the multimode fiber, only energy coupled in and out of the fundamental mode in the multimode fiber will be detected directly. The SMS structure has a higher sensitivity than using just the multimode sensing fiber. This sensor has been utilized in the seawater pH sensing in the range of 6 ~ 8. Experiments show that the sensor has a pH resolution of 0.0042.

Damage detection is the core technique of bridge health monitoring systems. Mostly, the detection is based on comparison of initial signatures (frequency, mode shapes and so on) of intact bridge with that of damaged bridge. The damage identification technique for bridge structure by vibration mode analysis is based on the precision of modal experiment. In order to identify the damage in time, the problem of sensor placement is very important. The number of the sensors and their settled locations determine the accuracy of test results. So how to distribute sensors reasonably to get the appropriate information about the changes of structure state of the bridge is the key for the health monitoring to large span bridges. Taking an actual long span Bridge as an example and calculating the modal date by the finite element model, a method based on the eigenvector sensitivity, the EI (Effective Independence) method and MAC (Modal Assurance Criterion) method are used to optimize the placement procedure of the sensors in this paper. The numerical example shows that the eigenvector sensitivity based method is an effective method for optimal sensor placement to identify vibration characteristics of the bridges.

The rapid growth in the smart sensor technology (SST) has enabled easier and more economic construction of the structural health monitoring system (SHM). Nevertheless, there is no distributed damage detection algorithm for efficient usage of the computation power of the SST. Therefore, this study aims at developing a new distributed damage detection algorithm suitable for the smart sensor system for the SHM. The algorithm suggested in this study utilizes the damping ratio of a structure, using the structure's energy dissipation ratio. In other words, each smart sensor installed to the structure analyzes the response signals from the structure into a damping ratio, which in turn is computed into an energy dissipation ratio, using the smart sensor's ability to handle data. Thus, this method detects the damages and locations of the damages in a structure using the changes in the energy dissipation ratio it has calculated. In this study proves the usefulness of the developed energy dissipation ratio by numerical simulation.

This paper explores the advantages of sensing rich approaches to the design and operation of the power transmission mechanism or drive train under servo control. The drive train is a fundamental element of any motion control system. Three specific cases are presented: 1) vision-based online trajectory generation for contour following for a two link manipulator, 2) the use of vision image and other sensors such as accelerometers and gyros for end-effector sensing, and 3) sensor-based controller tuning of indirect drive train using accelerometers on the load side. For each of the three cases, the advantages are demonstrated by experiments.

In this paper, we describe the development and realization of a sensing system using a high-resolution temperature and strain sensor with fiber Bragg grating (FBG) technology and a simple and low-cost long-period grating (LPG) sensor for the water level measurement in pavement structures. The FBG sensor consists of a reference fiber grating and a grating pair scheme that could offer the potential of simultaneous measurement of strain and temperature for monitoring pavement structures. For FBG sensor, experimental results have shown that measurement errors of 6 micro strains and 0.13 Celsius for strain and temperature could be achieved, respectively. The LPG sensor was extremely sensitive to the refractive index of the medium surrounding the cladding surface of the sensing grating, thus allowing it to be used as an ambient index sensor. A LPG-type water level sensor with a resolution was of ~5 mm was demonstrated to distinguish between in the air and under water. This integrated FBG and LPG sensing system is expected to benefit the health monitoring of multi-layer pavement structures especially for the evaluation and application of new materials, mix design procedures or construction technology.

Generally, the management criteria by monitoring items applied to the bridge management is decided through the intuition of the based on the empirical data without any professional and systematic background. In this study, the span deflection is selected among the bridge monitoring items and verify the appropriate management criteria in the case of deflection by the laboratory test. Test specimens are the small-sizing bridge specimens which are made by reinforced concrete. Those are classified by variation of span length and stiffness of section. As a result of test, the relationship between the span center deflection and the safety level of bridge is suggested.

This paper presents intrinsic polymer fiber (POF) sensors for high-strain applications such as the performance-based assessment and health monitoring of civil infrastructure systems subjected to earthquake loading or morphing aircraft. POFs provide a potential maximum strain range of 6-12%, are more flexible that silica optical fibers, and are more durable in harsh chemical or environmental conditions. Recent advances in the fabrication of single mode POFs have made it possible to extend POFs to interferometric sensor capabilities. Furthermore, the interferometric nature of intrinsic sensors permits high accuracy for such measurements. Measurements of the mechanical response of the sensor at various strain rates are presented. Several cleaving methods were also tested in order to appropriately cleave POFs for coupling purposes. In addition, the design of a time-of-flight interferometer for phase measurements over the large strain range required is discussed. Finally the bond strength between the embedded POF and various structural materials is investigated and a methodology demonstrated for embedment of the sensors into a reinforced concrete structural component.

Wireless sensors capable of sensing, processing, and wireless communication have been adopted for monitoring purposes in a variety of contexts, many of which feature challenging radio propagation characteristics. Fast rotating structures are commonly found in mechanical, transportation and energy systems, and the challenges of using wireless sensors on such structures have not been adequately addressed. For wireless sensors on rotating structures, it has been found there is an eminent dependency of packet error rates on rotation speeds, bursty bit errors, periodic variation in received signal strengths, and dominance of multipath effects. Previously, a reliable data transmission approach was developed to recover transmission errors, and it was found that transmission errors have mostly occurred in certain high-error regions. The objective of this study is to utilize the transmission approach to infer the transmission error pattern of such regions. The paper presents a sliding window algorithm for estimating the error region width, and a transmission simulator for studying dependencies among error burst statistics, error region distribution and widths, and accuracy of the rotation speeds. It is concluded that i) the number, width, and distribution of error regions can be inferred from normalized error burst distance distributions, ii) the error burst distance distributions depend sensitively on accuracy of the rotation speed, and iii) the error in speed can be inferred from the error burst distance distributions. The conclusions directly guide future work on transmission error modeling, on-line error pattern inference, and error-avoidant transmission methods for radios on rotating structures.

We are developing a three-dimensional sensing system that enables the tracking of localized material movement by recording displacement and rotation of passive radar targets within materials of interest. Ultimately, the development of this system will provide a highly reliable, cost-efficient set of tools for basic and applied granular materials research. However, the size and material density of the passive radar targets will be inevitably different than the material in which they are embedded, and particles of different sizes and densities tend to segregate when jostled, sheared, or otherwise disturbed. In other words, neighboring particles of different sizes and/or densities will likely not have identical movements. Therefore, effective use of the passive radar targets to predict movement of the bulk material will require a systematic understanding of how segregation depends on relative size and density of the tracer particles. We study segregation in two different systems to isolate different segregation driving mechanisms in densely sheared granular mixtures. In this paper, we discuss the results from these experiments and demonstrate how this can be used to relate sensor particle movement with bulk granular materials movement.

Fault is a undesirable factor in any mechanical/pneumatic system. It affects the efficiency of system operation and reduces economic benefit in industry. The early detection and diagnosis of faults in a mechanical system becomes important for preventing failure of equipment and loss of productivity and profits. In this paper, we present our ongoing research results on intelligent fault detections and diagnosis (FDD) on mechanical/ pneumatic systems. Using data from sensors and sensor network in an integrated industrial system, our proposed FDD methodology provides the analysis of necessary sensory information (for example, flow rates and pressure, as well as other digital sensor data) for the detection and diagnosis of system fault. In this experimental study, the leakage of pneumatic cylinder was the "fault." It was shown that the FDD analysis was able to make diagnosis of leakage both in location and size of the fault. In addition, the systematic fault and localized faults can be detected separately. The proposed wavelet method gives rise to the fingerprint analysis to recognize the patterns of the flow rate and pressure data - a very useful tool in intelligent fault detection and diagnosis.