This PDF file contains the front matter associated with SPIE Proceedings Volume 6529, including the Title Page, Copyright information, Table of Contents, a list of NSF papers, Introduction, and the Conference and Symposium Committees listings.

This paper addresses examples of sensing and active mechanisms inherent in some biological species where both plants and animals cases are discussed: mechanosensors and actuators in Venus Fly Trap and cucumber tendrils, chemosensors in insects, two cases of interactions between different kingdoms, (i) cotton plant smart defense system and (ii) bird-of-paradise flower and hamming bird interaction. All these cases lead us to recognize how energy-efficient and flexible the biological sensors and actuators are. This review reveals the importance of integration of sensing and actuation functions into an autonomous system if we make biomimetic design of a set of new autonomous systems which can sense and actuate under a number of different stimuli and threats.

Measuring displacement response of large-scale structures is necessary to assess their performance and health condition. Current global position systems (GPS), with a significant cost, can provide point coordinate measurement with an accuracy of ±1cm horizontally and ±2cm vertically at a sampling frequency up to 20 Hz. Photogrammetry is a measurement technology in which the three-dimensional coordinates of points on an object are determined by measurements made with two or more photographic images taken from different positions. This technology is regaining its popularity in various engineering disciplines due to a recent remarkable evolution in the consumer digital cameras. The image resolution of these cameras has increased rapidly from below 1 million pixels a few years ago to over 10 million pixels today, with little increase or even decrease in cost. Image sequences recorded by these cameras contain both spatial and temporal information of the target object; hence can be used to extract the object's dynamic characteristics such as natural frequencies and mode shapes. Research indicates that accuracy in the order of as high as 1 part in 30,000 can be achieved when cameras are properly calibrated in the field and multiple high-resolution images are used. At this level of accuracy, point positions of a 30m object would be accurate to 1mm at 68% probability and responses of large-scale structures can be measured for further meaningful processing and interpretation. In this paper, several image-based sensing techniques that can be used for measuring response of large-scale structures are presented. These techniques are developed based on some methods from photogrammetry and computer vision such as the optical flow method and the egomotion estimation. Examples used to illustrate these techniques include response measurement of buildings and cable-stayed bridges. Results show that the image-based sensing techniques have a great potential for accurately measuring displacement responses of these large-scale structures.

This paper deals with a distributed acoustic emission sensing method, which is especially suitable for piezoelectric paint. Piezoelectric paint is a composite piezoelectric material that is comprised of tiny piezoelectric particles randomly dispersed within a polymer matrix phase. An overview of the distributed acoustic emission sensing method for defect monitoring is given in this paper. The use of piezoelectric materials for ultrasonic signal measurements is next discussed along with a series of ultrasonic tests performed to verify the ultrasonic sensing capability of piezoelectric paint. To examine the mechanism of the distributed acoustic emission sensing method for crack initiation detection, the results of a finite element simulation based study is presented in this paper. The finite element model used in the parametric study is calibrated with experimental data. The effect of sensor numbers included in the array has been studied using both simulation and experimental data. Based on the preliminary results of this study, piezoelectric paint sensor appears to hold a potential for use in on-line monitoring of cracks such as those caused by fatigue in metal structures although more work is still needed before successful practical application can be made.

In this study, the actuation displacement and blocking force of the LIPCA (Lightweight Piezo-Composite Actuator) under various combination of the external compressive load and prescribed voltage have been numerically and experimentally examined. For numerical analysis, the full three-dimensional model of the LIPCA including two end-tabs in the simply supported configuration was used and the measured nonlinear behavior of the bare piezoceramic wafer (3203HD, CTS) was implemented in the geometrically nonlinear finite element analysis. The central out-of-plane displacement of the LIPCA was measured while applying various electric fields and compressive loads at the same time. Dummy weights were added at the center of the LIPCA until the LIPCA cannot produce additional central actuation displacement for a given excitation voltage and the sum of the dummy weight was regarded as the blocking force. The numerical results acquired by geometrical/material nonlinear finite element analysis and the measured data showed a good agreement even for high electric field and compressive load. The investigation showed that the actuation displacement and blocking force of the LIPCA were significantly increased by pre-applied compressive load. At the same electric field, the actuation displacements of the LIPCA under nearly buckling load could be about two times larger than those without compressive load. The results also indicate that the positive voltage should be better applied to the actuator than the negative voltage. Therefore, the high negative electric field, which causes the polarization switching in the piezoceramic wafer, can be avoided in applications. At +150V, the blocking force of the compressed actuator under near buckling load was also increased around 26% higher than that of the actuator without compressive load.

In this paper, we present a robust quantitative decision-making methodology for structural damage detection using piezoelectric transducers and the Lamb wave approach with the consideration of environmental and operational variances. The features of wave propagation are extracted from multiple signals using an improved adaptive harmonic wavelet transform (AHWT), which are then denoised and highlighted by applying the principal component analysis (PCA) in the wavelet domain. After self-checking and updating the baseline dataset, the Hotelling's T² analysis provides a statistical indication of damage under a certain given confidence level. The detectability, sensitivity and robustness of the methodology are investigated using experimental as well as numerical studies. As the basis for the detection practice, the propagation of Lamb waves in an aluminum beam is systematically studied in this paper.

Despite various successful applications of Lead Zirconate Titanate (PZT) transducers in the electromechanical impedance (EMI) technique for structural health monitoring (SHM), fundamental research work on the sensitivity of the PZT transducers for damage detection is still in need. Conventionally, the root mean square deviation (RMSD) is utilized to statistically analyze the differences between the pre-damage and the post-damage electromechanical admittance signatures of a PZT transducer. Recently, another damage index method based on the structural impedance has been derived and successfully used for structural damage diagnosis. This paper presents a comparison of the sensitivity of these two methods to the damages in a concrete structure. An experimental test is carried out on a two-storey concrete frame subjected to base vibrations that simulate the earthquake and underground explosions. A number of PZT transducers are regularly arrayed and bonded to the concrete frame structure. After each phase of vibration loading, the PZT transducers are scanned to acquire the raw signatures of the PZT admittance. Subsequently, the damage indices based on both the raw signatures and the structural impedance extracted from the raw signatures are calculated. Results show that the PZT transducers with different distances away from the damage have different sensitivity to the structural damage. The relation between the damage index and the distance of the PZT transducer away from the damage is studied. Consequently, the sensitivity of the PZT transducers is discussed, and their sensing region in concrete is derived.

A pulse-echo ultrasonic guided wave approach that characterizes the setting and hardening of early age mortar during the first twenty-four hours of hydration is presented. The method invokes the fundamental torsional mode on the free end of a cylindrical steel rod partially embedded in mortar and monitors the reflected signals. Both the reflection from the end of the rod and the reflection from the point where the waveguide enters the mortar are monitored. The evolution of the mortar properties is related to both the energy leaked into the surrounding mortar and the energy reflected at the entry point. Results show that the technique is useful for monitoring the development of the mechanical properties of varying water-cement ratios (w/c = 0.40, 0.50, and 0.60). In addition, the effects of chemical (accelerant and retardant) and mineral (silica fume and fly ash) admixtures on the guided wave behavior were also studied. Time of setting and compressive strength measurements have been performed on the various mortar mixtures. The change in signal strength of the end- and entry-reflection of the guided wave appears to be correlated to the mortar setting times and compressive strength, respectively. The ability of this method to only require access to one side of the specimen makes it attractive for the development of a system that monitors in-situ cementitious materials.

Researchers at NASA-LaRC have developed a hybrid actuation system (HYBAS) that cooperatively employs an electroactive polymer and an electrostrictive single crystal. Experimental measurements and theoretical model predictions have been in good agreement thus far. To date, current research has only explored the usage of one electroactive polymer and one electrostrictive single crystal. A computational model was created based on this theoretical model. It implements the equations necessary to predict the actuator displacement profile and maximum displacement. Among the model variables are the actuator material properties. Changing the actuator materials has notable effects on actuator performance. As many viable materials as could be found were compiled into a database which can serve as a building block upon which a larger database can be built. Using these materials, a trade study was performed to determine which combination of materials demonstrates the best performance. As more electroactive materials are compiled, more extensive trade studies can be performed. Thus, the work in this paper will serve as a guideline for future HYBAS designs.

Large thermal variations can cause significant changes in guided-wave (GW) propagation and transduction for structural health monitoring (SHM). This work focuses on GW SHM using surface-bonded piezoelectric wafer transducers in metallic plates for the temperature range encountered in internal spacecraft structures (20°C to 150°C). First, studies done to determine a suitable bonding agent are documented. That was then used in controlled experiments to examine changes in GW propagation and transduction using PZT-5A piezoelectric wafers under quasi-statically varying temperature (also from 20°C to 150°C). Modeling efforts to explain the experimentally observed increase in time-of-flight and change in sensor response amplitude with increasing temperature are detailed. Finally, these results are used in detection and location of mild and moderate damage using the pulse-echo GW testing approach within the temperature range.

Laminated safety glass samples with different levels of adhesive bond strength were manufactured and tested using mechanical guided waves. The adhesive bond strength of the test samples was then also evaluated using the commonly used destructive testing method, i.e., the pummel test method. The imperfect interfaces between the plastic interface and the two adjacent glass plates were modeled using a bed of longitudinal and shear springs. The spring constants were estimated using fracture mechanics concepts in conjunction with surface analysis of the plastic interlayer and of the two adjacent glass plates using atomic force microscopy and profilometer measurements. In addition to mode shape analysis, the phase and energy velocities were calculated and discussed. The guided wave theoretical predictions of adhesion levels (obtained using this multilayered model) were validated using the pummel test results. Results show that this approach is useful in the nondestructive assessment of adhesive bond strength in laminated safety glass.

Array processing of seismic data provides a powerful tool for source location and identification. For this method to work to its fullest potential, accurate transduction of the unadulterated source mechanism is required. In our tests, controlled areas of normal-strength concrete specimens were exposed to a low relative humidity at an early age to induce cracking due to drying shrinkage. The specimens were continuously monitored with an array of broad-band, high-fidelity acoustic emission sensors contrived in our laboratory in order to study the location and temporal evolution of drying shrinkage cracking. The advantage of the broadband sensors (calibration NIST-traceable) compared to more traditional acoustic emission sensors is that the full frequency content of the signals are preserved. The frequency content of the signals provides information about the dispersion and scattering inherent to the concrete, and the full unadulterated waveforms provide insight into the micromechanisms which create acoustic emissions in concrete. We report on experimental and analytical methods, event location and source mechanisms, and possible physical causes of these microseisms.

This paper presents the microfabrication process of a MEMS piezoresistive shear stress sensor for direct, quantitative measurement of time-resolved, fluctuating wall shear stress. The sensor structure integrates shadow side-implanted diffused resistors into the sensor tethers for detecting in-plane deflection. Temperature compensation is achieved by integrating a fixed, dummy Wheatstone bridge adjacent to the active shear stress sensor. The device is fabricated from an SOI wafer using an 8-mask process. A phosphorus blanket implantation forms an n-well to ensure P/N junction isolation. Boron implantation forms a heavily doped Ohmic contact. The tethers and floating element are defined by patterning PECVD oxide via RIE and DRIE. The Si is etched vertically to 8 &mgr;m via DRIE to form the trench for the sidewall implant. The scallops formed on the sidewalls during DRIE are smoothed by hydrogen annealing. After a preamorphization implant, boron is implanted at an oblique angle of 54° to achieve a 5 &mgr;m shadow side-wall implantation. The structure is released from the backside using a combination of DRIE and RIE to etch the silicon, oxide, and nitride layers. Finally, the sensors are annealed in forming gas. Preliminary electrical testing indicates linear, junction-isolated resistors.

The search for existing or past life in the Universe is one of the most important objectives of NASA's mission. For this purpose, effective instruments that can sample and conduct in-situ astrobiology analysis are being developed. In support of this objective, a series of novel mechanisms that are driven by an Ultrasonic/Sonic actuator have been developed to probe and sample rocks, ice and soil. This mechanism is driven by an ultrasonic piezoelectric actuator that impacts a bit at sonic frequencies through the use of an intermediate free-mass. Ultrasonic/Sonic Driller/Corer (USDC) devices were made that can produce both core and powdered cuttings, operate as a sounder to emit elastic waves and serve as a platform for sensors. For planetary exploration, this mechanism has the important advantage of requiring low axial force, virtually no torque, and can be duty cycled for operation at low average power. The advantage of requiring low axial load allows overcoming a major limitation of planetary sampling in low gravity environments or when operating from lightweight robots and rovers. The ability to operate at duty cycling with low average power produces a minimum sample temperature rise allowing for control of the sample integrity and preventing damage to potential biological markers in the acquired sample. The development of the USDC is being pursued on various fronts ranging from analytical modeling to mechanisms improvements while considering a wide range of potential applications. While developing the analytical capability to predict and optimize its performance, efforts are made to enhance its capability to drill at higher power and high speed. Taking advantage of the fact that the bit does not require rotation, sensors (e.g., thermocouple and fiberoptics) were integrated into the bit to examine the borehole during drilling. The sounding effect of the drill was used to emit elastic waves in order to evaluate the surface characteristics of rocks. Since the USDC is driven by piezoelectric actuation mechanism it can designed to operate at extreme temperature environments from very cold as on Titan and Europa to very hot as on Venus. In this paper, a review of the latest development and applications of the USDC will be given.

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, although few problems, mainly related to the sensitivity and stability of the interferometric system, have to be better studied.

Rapid identification and detection of bacteria is an important issue in environmental and food science. We have developed an impedance-based method to simultaneously identify and detect bacteria in a derivatized microfluidic chamber with monoclonal antibodies. The presence of bacteria in the solution can be selectively recognized and fixed on the chamber wall and detected via impedance change in real time. The optimum reaction time between antibody and bacteria has been estimated using a simple model and evaluated experimentally. Various concentrations of cultured E. coli cells ranging from 10⁵ to 10⁸ CFU/ml were tested using the biosensor. By taking the advantage of a microfluidic system, the bacteria can be concentrated and accumulated on the chamber wall by continuously perfusing the chamber with bacterial suspension, therefore, enhancing the detection limit of the sensor. Using this approach, the biosensor was able to detect 10⁶ CFU/ml E. coli (BL21(DE3)) via five consecutive perfusions. The selectivity of the sensor is demonstrated by testing the antibody reaction for two bacteria stains, E. coli and M. catarrhalis. By derivatizing the chamber walls with specific antibodies, we can clearly identify the bacteria that are specific to the antibodies in the detection chamber. The simplicity of the technique also makes the device portable and ideal for clinical and field applications.

Piezoelectric wafer active sensors (PWAS) have been proven a valuable tool in structural health monitoring. Piezoelectric wafer active sensors are able to send and receive guided Lamb/Rayleigh waves that scan the structure and detect the presence of incipient cracks and structural damage. In-situ thin-film active sensor deposition can eliminate the bonding layer to improve the durability issue and reduce the acoustic impedance mismatch. Ferroelectric thin films have been shown to have piezoelectric properties that are close to those of single-crystal ferroelectrics but the fabrication of ferroelectric thin films on structural materials (steel, aluminum, titanium, etc.) has not been yet attempted. In this work, in-situ fabrication method of piezoelectric thin-film active sensors arrays was developed using the nano technology approach. Specification for the piezoelectric thin-film active sensors arrays was based on electro-mechanical-acoustical model. Ferroelectric BaTiO3 (BTO) thin films were successfully deposited on Ni tapes by pulsed laser deposition under the optimal synthesis conditions. Microstructural studies by X-ray diffractometer and transmission electron microscopy reveal that the as-grown BTO thin films have the nanopillar structures with an average size of approximately 80 nm in diameter and the good interface structures with no inter-diffusion or reaction. The dielectric and ferroelectric property measurements exhibit that the BTO films have a relatively large dielectric constant, a small dielectric loss, and an extremely large piezoelectric response with a symmetric hysteresis loop. The research objective is to develop the fabrication and optimum design of thin-film active sensor arrays for structural health monitoring applications. The short wavelengths of the micro phased arrays will permit the phased-array imaging of smaller parts and smaller damage than is currently not possible with existing technology.

Development of advanced lightweight solar arrays and small satellites requires deployment and release devices to be very small and lightweight. Achieving release requirements through a small size device will face more challenging design problems. The SMA (Shape Memory Alloys) devices designed so far have all been discrete point bolt release devices. When several release devices are used, it is very hard for present SMA devices to keep synchronous because of a long individual separation time. This paper will describe the advantages of a new type of space release device actuated with SMA wire, the design and experimental results to demonstrate its functions. The scheme is to take advantage of the ability of SMA to recover a parent shape when heated by an electrical current. A clever and simple structure design ensures small size and light weight of the device. To achieve high release reliability, Tanaka-Liang's constitutive model was selected to describe SMA wire's deformation and response characteristics. Ground test facilities were designed to validate numerical prediction. Tests results showed that the small release device actuated with SMA wires can response very quickly (within 0.1 seconds under satellite power supply of 28V). Synchronous deployment tests were also done when two release devices were installed at the same time, and also gained success. It is concluded that the developed SMA release device owning advantages of small size, lightweight, low shock, no contamination, easy reset and synchronization etc. will play an important role in developing future advanced lightweight solar arrays.

Pneumatic tires are critical components in mobile systems that are widely used in our lives for passenger and goods transportation. Wheel/ground interactions in these systems play an extremely important role for not only system design and efficiency but also safe operation. However, fully understanding wheel/ground interactions is challenging because of high complexity of such interactions and the lack of in situ sensors. In this paper, we present the development of a tire tread deformation sensor and energy harvester for real-time tire monitoring and control. Polyvinylidene fluoride (PVDF) based micro-sensor is designed and fabricated to embed inside the tire tread and to measure the tread deformation. We also present a cantilever array based energy harvester that takes advantages of the mechanical bandpass filter concept. The harvester design is able to have a natural frequency band that can be used to harvest energy from varying-frequency vibrational sources. The energy harvester is also built using with new single crystal relaxor ferroelectric material (1 - &Vkgr;)Pb(Mg_1/3Nb_2/3)O₃-&Vkgr;PbTiO₃ (PMN-PT) and interdigited (IDT) electrodes that can perform the energy conversion more efficiently. Some preliminary experiment results show that the performance of the sensor and the energy harvester is promising.

Ionomeric polymer transducers (IPTs) have recently received a great deal of attention. As actuators, IPT have the ability to generate large bending strain and moderate stress at low applied voltages. Although the actuation capabilities of IPTs have been studied extensively, the sensing performance of these transducers has not received much attention. The work presented herein aims to develop a wall shear stress sensor for aero/hydrodynamic and biomedical applications. Ionic polymers are generally created by an impregnation-reduction process in an ion exchange membrane, typically Nafion, and then coated with a flexible electrode. The traditional impregnation-reduction fabrication technique of IPTs has little control on the electrode thickness. However, the new Direct Assembly Process (DAP) for fabrication of IPTs allows for experimentation with varying conducting materials and direct control of electrode architecture. The thickness of the electrode is controlled by altering the amount of the ionomer/metal mix sprayed on the membrane. Transducers with varied electrode and membrane thicknesses are fabricated. The sensitivity of the transducer is characterized using two basic experiments. First, the electric impedance of the transducer is measured and its capacitive properties are computed. Earlier studies have demonstrated that capacitance has been strongly correlated to actuation performance in IPTs. Subsequently, the sensing capability of the IPTs in bending is measured using a fixed-pined cantilever configuration. Finally the shear stress sensing performance in fluid flow is quantified through a detailed calibration procedure. This is accomplished using two dynamic shear stress calibration apparatuses. In this study we demonstrate a strong correlation between the electrode thickness and the sensing performance of an IPT.

A miniature differential surface stress sensor consisting of two adjacent micromachined cantilevers (a sensing/reference pair) is developed for detection of chemical and biological species. Presence of analyte species is detected by measuring the differential surface stress associated with adsorption/absorption of chemical species on sensing cantilever. A novel interferometric technique is utilized to measure the differential surface stress induced bending of sensing cantilever with respect to reference cantilever. Sensor performance is characterized through measurement of surface stress associated with formation of alkanethiol self-assembled monolayers (SAMs) on gold coated sensing cantilever. Chemisorptions and self-assembly of alkanethiol molecules onto the gold-coated cantilever surface leads to development of compressive surface stress. Magnitude of measured surface stress compares well with data reported in literature.

Currently, much of the focus in the structural health monitoring community is shifting towards incorporating health monitoring technology into real world structures. Deployment of structural health monitoring systems for permanent damage detection is usually limited by the availability of sensor technology. Previously, we developed the first fully self-contained system that performs impedance-based structural health monitoring. This digital signal processor based system effectively replaces a traditional impedance analyzer and all of the manual analysis usually required for damage determination. The work described here will focus on improving this hardware. Efforts are made to reduce the overall power consumption of the prototype while at the same time improving the overall performance and efficiency. By introducing a new excitation method and implementing a new damage detection scheme, reliance on both analog-to-digital and digital-to-analog conversion are circumvented. These new actuation and sensing techniques, along with the underlying hardware, are described in detail. The reduction of power dissipation and improved performance are documented and compared with both traditional impedance techniques and the previous prototype.

A remotely-controlled model aircraft with morphing wings is built and its performance is evaluated. The aircraft relies in its operation on a network of distributed sensors that are embedded in the composite fabric of the wings to monitor the wing shape during morphing. The output of the sensor network is wirelessly transmitted to the ground command computer to simultaneously map the wing shape and the strain distribution of the aircraft during flight. The error between the actual wing shape and the desired shape corresponding to a specific aircraft mission is determined. The necessary control action is computed according to a selected control law and the resulting action is tele-metered from the ground computer to the modified servo-motors of the flying aircraft to compensate for the shape errors. The theory of operation of the sensor network and its interaction with the wing and aircraft dynamics are introduced. Comparisons between the desired and actual shapes of the morphing wings are also presented for different control law parameters. The developed theoretical and experimental techniques provide invaluable tools for the design and operation of other classes of remotely-controlled morphing aircraft. [Work is funded by NSF].

An approach based upon the employment of piezoelectric transducer rosettes is proposed for passive damage or impact location in anisotropic or geometrically-complex structures. The rosettes are comprised of rectangular Macro-Fiber Composite (MFC) transducers which exhibit a highly directive response to ultrasonic guided waves. The MFC response to flexural (A₀) motion is decomposed into axial and transverse sensitivity factors, which allow extraction of the direction of an incoming wave using rosette principles. The wave source location in a plane is then simply determined by intersecting the wave directions detected by two rosettes. The rosette approach is applicable to anisotropic or geometrically-complex structures where conventional time-of-flight source location is challenging due to the direction-dependent wave velocity. The performance of the rosettes for source location is validated through pencil-lead breaks performed on an aluminum plate, an anisotropic CFRP laminate, and a complex CFRP-honeycomb sandwich panel.

Lamb wave time reversal method is a new and tempting baseline-free damage detection technique for structural health monitoring. With this method, certain types of damage can be detected without baseline data. However, the application of this method to thin-wall structures is complicated by the existence of at least two Lamb wave modes at any given frequency, and by the dispersion nature of the Lamb wave modes existing in thin-wall structures. The theory of Lamb wave time reversal has not yet been fully studied. This paper addresses this problem by developing a theoretical model for the analysis of Lamb wave time reversal in thin-wall structures based on the exact solutions of the Rayleigh-Lamb wave equation. The theoretical model first used to predict the existence of single-mode Lamb waves. Then the time reversal behavior of single-mode and two-mode Lamb waves is studied numerically. The advantages of single-mode tuning in the application of time reversal damage detection are highlighted. The validity of the proposed theoretical model is verified through experimental studies. In addition, a similarity metric for judging time invariance of Lamb wave time reversal is presented. It is shown that, under certain condition, the use of PWAS-tuned single-mode Lamb waves can greatly improve the effectiveness of the time-reversal damage detection procedure.

Rock, soil, and ice penetration by coring, drilling or abrading is of great importance for a large number of space and earth applications. Proven techniques to sample Mars subsurface will be critical for future NASA astrobiology missions that will search for past and present life on the planet. The Ultrasonic/Sonic Drill/Corer (USDC) has been developed as an adaptable tool for many of these applications [Bar-Cohen et al., 2001]. The USDC uses a novel drive mechanism to transform the ultrasonic or sonic vibrations of the tip of a horn into a sonic hammering of a drill bit through an intermediate free-flying mass. For shallow drilling the cuttings travel outside the hole due to acoustic vibrations of the bit. Various methods to enhance the drilling/coring depth of this device have been considered including pneumatic [Badescu et al., 2006] and bit rotation [Chang et al., 2006]. The combination of bit rotation at low speed for cuttings removal and bit hammering at sonic frequencies are described in this paper. The theoretical background and testing results are presented.

Since their introduction in the mid seventies, a variety of fibre optic sensor configurations have been developed for the measurement of strain, deformation, temperature, vibration, pressure, etc. Variation of these parameters alters the refractive index and the geometric properties of the optical fibre, which in turn perturbs the intensity, phase, or polarization of the light wave propagating in the waveguide. Only in the past decade that Bragg grating-based fibre optic sensors emerged as the non-disputed champion in multiplexing and dual parameter sensing with increased potential for smart structure applications. Stringent requirements for single point discrete or distributed simultaneous strain and temperature measurements prompted this characterization study which has the objective of developing a detailed understanding of grating characteristics and response under external stimuli. Collocated and serially placed gratings were evaluated and tested for their effective sensitivity to strain and temperature and to coating materials variation such as polyamide and acrylite. Experimental sensitivity results correlated well with theoretical estimation for strain in single gratings. Whereas, significant wavelength differential is required for simultaneous temperature and strain measurement if collocated gratings are used.

Intelligent fault detection and diagnosis (FDD) depends on smart sensors which not only can render sensory information but also can make easy the subsequent detection and diagnosis. At the heart of every intelligent FDD system, there are sensors which work collaboratively with one another as well as the intelligent system. Miniaturized sensors present unique advantages in facilitating the installation of sensory devices for the purpose of diagnosis. In this paper, we present ongoing research on intelligent FDD and characterization using miniaturized sensor. With miniaturization, sensors can be readily made and integrated into intelligent diagnosis. Characterization and modeling of such innovative sensor designs are presented. Using new smart multi-function, telemetric, and integrated sensors as "intelligent nodes" in systems will provide necessary sensory information (for example, an integrated sensor which measures pressure, flow, and temperature--all in one module). The characterization and studies of miniaturized sensor are presented, with practical relevance to applications. The concept of intelligent nodes is further augmented with wireless sensors and system integration.

Piezoelectric transducers are commonly used to excite waves in elastic waveguides such as pipes, rock bolts and rails. While it is possible to simulate the operation of these transducers attached to the waveguide, in the time domain, using conventional finite element methods available in commercial software, these models tend to be very large. An alternative method is to use specially formulated waveguide finite elements (sometimes called Semi-Analytical Finite Elements). Models using these elements require only a two-dimensional finite element mesh of the cross-section of the waveguide. The waveguide finite element model was combined with a conventional 3-D finite element model of the piezoelectric transducer to compute the frequency response of the waveguide. However, it is difficult to experimentally verify such a frequency domain model. Experiments are usually conducted by exciting a transducer, attached to the waveguide, with a short time signal such as a tone-burst and measuring the response at a position along the waveguide before reflections from the ends of the waveguide are encountered. The measured signals are a combination of all the modes that are excited in the waveguide and separating the individual modes of wave propagation is difficult if there are numerous modes present. Instead of converting the measured signals to the frequency domain we transform the modeled frequency responses to time domain signals in order to verify the models against experiment. The frequency response was computed at many frequency points and multiplied by the frequency spectrum of the excitation signal, before an inverse Fourier transform was used to transform from the frequency domain to the time domain. The time response of a rail, excited by a rectangular piezoelectric ceramic patch, was computed and found to compare favorably with measurements performed using a laser vibrometer. By using this approach it is possible to determine which modes of propagation dominate the response and to predict the signals that would be obtained at large distances, which cannot be measured in the lab, and would be computationally infeasible using conventional finite element modeling.

Structural health monitoring (SHM) technologies, which use integrated sensing for damage detection, are expected to improve system reliability, availability, and operational cost. Guided waves can propagate great distances while experiencing low attenuation. They have been successfully used for damage detection in structures of relatively low geometric complexity such as plates and cylindrical pipes. The use of guided waves for this purpose becomes increasingly difficult as the geometric complexity of the structure increases. Aerospace structural components such as fuel tanks, wings, etc. often are comprised of substructures that consist of plates with integral stiffeners. This work reports on finite element simulations of guided waves in integrally stiffened plate structures. In these studies, the guided waves are generated by PZT wafer-type transducers mounted on the structure. Transient dynamic finite element simulations using PZFlex, in 2D and in 3D, were used to model both the structure and transducers. The interaction of the guided waves with cracks, simulated by notches of varying dimensions, is also modeled. This allows appraisal of the sensitivity of various modes for crack detection by providing insight into mode conversion and scattering resulting from the guided wave and crack interaction.

In this paper, the advantages of sensing rich approaches to the design of mechatronic systems are explored for the power transmission mechanism or drive train under servo control. The drive train is a fundamental element of any motion control system. Two cases of utilizing various sensing means for controls of drive trains are presented: 1) the use of vision cameras for real time generation of the reference inputs for robot joints for tracking of straight lines in the task space, and 2) the use of accelerometer for fine tuning of the parameters of servo controllers.

Silica-based optical fiber sensors are widely used in structural health monitoring systems for strain and deflection measurement. One drawback of silica-based optical fiber sensors is their low strain toughness. In general, silica-based optical fiber sensors can only reliably measure strains up to 2%. Recently, polymer optical fiber sensors have been employed to measure large strain and deflection. Due to their high optical losses, the length of the polymer optical fibers is limited to 100 meters. In this paper, we present a novel economical technique to fabricate hybrid silica/polymer optical fiber strain sensors for large strain measurement. First, stress analysis of a surface-mounted optical fiber sensor is performed to understand the load distribution between the host structure and the optical fiber in relation to their mechanical properties. Next, the procedure of fabricating a polymer sensing element between two optical fibers is explained. The experimental set-up and the components used in the fabrication process are described in details. Mechanical testing results of the fabricated silica/polymer optical fiber strain sensor are presented.

Optical fiber whitelight interferometers for distance measurement have attracted a lot of attention recently because they offer absolute measurement, ultrahigh accuracy, large dynamic range, and robustness. In this paper, the development of an in-fiber whitelight interferometric distance sensor based on the mode coupling effect of a long period fiber grating (LPFG) is presented. Unlike the Fabry-Perot interferometric (FPI) distance sensor that has a minimum requirement on the measurable distance, the LPFG-based distance sensor can measure a distance that is as small as several nanometers. Therefore, it can be applied for near-field surface profiling of micro/nano-sized components. The principle of operation of the LPFG-based distance sensor is first explained and an innovative micro-photolithographic technique to fabricate the sensor probe is described in detail. The performance of the distance sensors using two different types of LPFGs, laser-machined LPFG and mechanically induced LPFG, were evaluated and the experimental results are presented.

Piezoelectric materials (PZT) have shown the ability to convert mechanical forces into an electric field in response to the application of mechanical stresses or vice versus. This property of the materials has found extensive applications in a vast array of areas including sensors and actuators. The study presented in this paper targets the modeling of PZT bender for voltage and power generation by transforming ambient vibrations into electrical energy. This device can potentially replace the battery that supplies the power in a micro watt range necessary for operating sensors and data transmission. One of advantages is the maintenance free over a long time span. This paper focuses on the analytical approach based on Euler-Bernoulli beam theory and Timoshenko beam equations for the voltage and power generation, which is then compared with two previously described models in literature; Electrical equivalent circuit and Energy method. The three models are then implemented in Matlab/Simulink/Simpower environment and simulated with an AC/DC power conversion circuit. The results of the simulation and the experiment have been compared and discussed.

Growing concerns over the safety of the indoor environment have made the use of sensors ubiquitous. Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is more informed by intuition and experience rather by systematic design. To develop a sensor system design methodology, a proper indoor airflow modeling approach is needed. Various indoor airflow modeling techniques, from complicated computational fluid dynamics approaches to simplified multi-zone approaches, exist in the literature. In this study, the effects of two airflow modeling techniques, multi-zone modeling technique and zonal modeling technique, on indoor air protection sensor system design are discussed. Common building attack scenarios, using a typical CBW agent, are simulated. Both multi-zone and zonal models are used to predict airflows and contaminant dispersion. Genetic Algorithm is then applied to optimize the sensor location and quantity. Differences in the sensor system design resulting from the two airflow models are discussed for a typical office environment and a large hall environment.

An improved multi-channel MEMS chip for acoustic emission sensing has been designed and fabricated in 2006 to create a device that is smaller in size, superior in sensitivity, and more practical to manufacture than earlier designs. The device, fabricated in the MUMPS process, contains four resonant-type capacitive transducers in the frequency range between 100 kHz and 500 kHz on a chip with an area smaller than 2.5 sq. mm. The completed device, with its circuit board, electronics, housing, and connectors, possesses a square footprint measuring 25 mm x 25 mm. The small footprint is an important attribute for an acoustic emission sensor, because multiple sensors must typically be arrayed around a crack location. Superior sensitivity was achieved by a combination of four factors: the reduction of squeeze film damping, a resonant frequency approximating a rigid body mode rather than a bending mode, a ceramic package providing direct acoustic coupling to the structural medium, and high-gain amplifiers implemented on a small circuit board. Manufacture of the system is more practical because of higher yield (lower unit costs) in the MUMPS fabrication task and because of a printed circuit board matching the pin array of the MEMS chip ceramic package for easy assembly and compactness. The transducers on the MEMS chip incorporate two major mechanical improvements, one involving squeeze film damping and one involving the separation of resonance modes. For equal proportions of hole area to plate area, a triangular layout of etch holes reduces squeeze film damping as compared to the conventional square layout. The effect is modeled analytically, and is verified experimentally by characterization experiments on the new transducers. Structurally, the transducers are plates with spring supports; a rigid plate would be the most sensitive transducer, and bending decreases the sensitivity. In this chip, the structure was designed for an order-of-magnitude separation between the first and the second mode frequency, strongly approximating the desirable rigid plate limit. The effect is modeled analytically and is verified experimentally by measurement of the resonance frequencies in the new transducers. Another improvement arises from the use of a pin grid array ceramic package, in which the MEMS chip is acoustically coupled to the structure with only two interfaces, through a ceramic medium that is negligible in thickness when compared to wavelengths of interest. Like other acoustic emission sensors, those on the 2006 MEMS chip are sensitive only to displacements normal to the surface on which the device is mounted. To overcome that long-standing limitation, a new MEMS sensor sensitive to in-plane motion has been designed, featuring a different spring-mass mechanism and creating the signal by the change in capacitance between stationary and moving fingers. Predicted damping is much lower for the case of the in-plane sensor, and squeeze-film damping is used selectively to isolate the desired in-plane mechanical response from any unwanted out-of-plane response. The new spring-mass mechanism satisfies the design rules for the PolyMUMPS fabrication (foundry) process. A 3-D MEMS sensor system is presently being fabricated, collocating two in-plane sensors and one out-of-plane sensor at the mm scale, which is very short compared to the acoustic wavelength of interest for stress waves created by acoustic emission events.

A novel transducer for active or passive sensing has been developed and tested experimentally. It features a steel wire acting as a wave guide between a piezoceramic element and the structure under test. Some advantages of the wire-guided transducer include its applicability to structures operating at high temperature, which otherwise preclude the surface mounting of piezoceramics, its small contact area to the structure, which enables several such transducers to be deployed in an arc around a known crack location as an acoustic emission sensor array, and its low cost and ease of installation. Another potential advantage is simplified signal processing for source localization, which is developed in this paper and evaluated experimentally. The various steel wires used in our experiments to date are less than 1 mm in diameter and between 10 cm and 100 cm in length. The wire guides have been studied with active excitation under a pulse excitation as used in ultrasonic testing, at a relatively high frequency such as 1 MHz, and in the frequency range of 100 kHz to 500 kHz which is often of interest for Lamb wave generation in thin plates or for acoustic emission sensing. Our tests confirm that the wire acts as a cylindrical rod in which the fastest wave is the lowest longitudinal mode, displaying a sharp arrival, and in which the lowest flexural mode and lowest torsional mode are also excited; we report excellent agreement between measured and predicted wave speeds, as expected. We show experimental results in which a group of wire-guided transducers permit the localization of an impact on a thin plate and discuss the automation of this task for use in the field. We also show the ability of the wire-guided transducer to detect acoustic emission events simulated physically by pencil lead breaks.

Fatigue and overload of mechanical, civil and aerospace structures remains a major problem that can lead to costly repair and catastrophic failure. Long term monitoring of mechanical loading for these structures could reduce maintenance cost, improve longevity and enhance safety. However, the powering of these sensors during the lifetime of the monitored structure remains a major problem. In this paper we describe an implementation of a novel self-powered fatigue monitoring sensor. The sensor is based on the integration of piezoelectric transduction with floating gate avalanche injection. The miniaturized sensor enables self-powered continuous battery free monitoring and time-to-failure predictions of mechanical and civil structures. Measured results from a fabricated prototype in a 0.5&mgr;m CMOS process indicate that the device can compute cumulative statistics of electrical signals generated by the piezoelectric transducer, while consuming less that one microwatt of power. Furthermore, the sensor is capable of storing this information in non-volatile memory which makes it an attractive alternative when the converted electrical energy levels are low due to small mechanical force inputs. The current microchip is less than 2 square millimeters in area. The non volatile memory storage is coupled to a radio frequency (RF) identification microchip which allows the sensor to be interrogated asynchronously through a RF reader. We are currently developing a state vector machine (SVM), neural network based hardware to be included on the microchip. The SVM hardware will enable low-power processing and computation of the incoming mechanical loading cycle data.

Magneto-rheological fluid (MRF) was first developed in the late 1940s. MRF consists of iron or other ferrous particles, typically on the order of 1 - 10 μm characteristic dimension, dispersed in a host carrier fluid, usually oil or water. In the presence of a magnetic field, the alignment of the iron particles along field lines results in the effective rheological properties of the composite fluid to be modified. In the "off" state (no field applied), the fluid has similar viscous properties to the host fluid. In the "on" state (field applied), the viscosity and yield stress can be significantly modified. Recently, MRF has been of interest in a number of novel devices, for example, for variable damping such as in automotive shock absorbers. In the present work, we briefly describe our initial investigations into variable damping MRF/foam devices. Open-cell polymer foam blocks were infused with commercial MRF and subjected to magnetic fields of various strengths. Drop tests were conducted by dropping a small indenter from a fixed platform and observing the rebound height as a function of applied field strength. The difference in rebound height can be directly related to loss of energy through damping. In the tests conducted, the energy absorbed by the MRF/foam increased from about 60% in the off-state device to over 90% in the on-state device. One of the difficulties encountered in performing the drop tests and providing credible data interpretation was that the MRF/foam itself changed dimensions under applied field. The iron particles in the fluid were attracted to the magnet and thus caused constriction of the foam block. Peristalsis is the process of involuntary and successive wave-like muscular contractions by which food is moved through the digestive tract. The esophagus, stomach, and intestines all move and/or mix food and liquid by peristalsis. Peristalsis is also used to move lymph through the lymphatic system. Inspired by biological peristalsis, peristaltic pumps in industry are common for a variety of material handling applications, particularly involving the movement of sterile fluids (for example, blood). The peristaltic pump is usually circular in configuration, relying on external rollers to move fluid within a tube. Some linear configuration pumps have been proposed and developed, however they are complicated than their circular counterparts. In the remaining part of the present work, we discuss the development of a linear peristaltic actuator based upon the deformation of MRF/foam. The actuator consists of an open-cell polymer foam substrate infused with MRF. To one side of the foam substrate resides a translating magnet, such that a magnetic field can be propagated down its length. The linear peristaltic action is generated as the transversely propagating field shapes the MRF/foam substrate in a corresponding way. Experimental results are discussed, an outline of on-going theoretical modeling is presented, and conclusions are provided.

This paper is focused on the dynamic characterization of field-induced mechanical stiffness changes under varied bias magnetic fields in commercial-quality, single-crystal ferromagnetic shape memory Ni-Mn-Ga. Prior to the dynamic measurements, a specified variant configuration is created in a prismatic Ni-Mn-Ga sample through the application and subsequent removal of collinear or transverse bias magnetic fields. Base excitation is used to measure the acceleration transmissibility across the sample, from where the resonance frequency is directly identified. These measurements are repeated for various collinear and transverse bias magnetic fields ranging from 0 to 575 kA/m, which are applied by a solenoid and an electromagnet, respectively. A 1-DOF model for the Ni-Mn-Ga sample is used to calculate the mechanical stiffness from resonance frequency measurements. A resonance frequency increase of 21% and a stiffness increase of 52% are observed in the collinear field tests. In the transverse field tests, a resonance frequency decrease of -36% is observed along with a stiffness decrease of -61%. The damping exhibited by this material is low in all cases (≈ 0.03). The measured dynamic behaviors make Ni-Mn-Ga well suited for vibration absorbers with electrically-tunable stiffness.

The recent development of wireless sensors for structural health monitoring has revealed their strong dependency on portable, limited battery supplies. Unlike current wireless sensors, passive radio frequency identification (RFID) systems based on inductive coupling can wirelessly receive power from a portable reader while transmitting collected data back. In this paper, preliminary results of a novel inductively coupled strain and corrosion sensor based upon material fabrication techniques from the nanotechnology field are presented. By varying polyelectrolyte species during a layer-by-layer fabrication process, carbon nanotube-polyelectrolyte multilayer thin film sensors sensitive to different mechanical (e.g. strain) and chemical (e.g. pH) stimuli can be produced. Validation studies conducted with different carbon nanotube thin films designed as either strain or pH sensors reveal high sensitivity and linear performance. When coupled with a copper inductive coil antenna, resulting RFID-based sensors exhibit wirelessly readable changes in resonant frequency and bandwidth. Furthermore, a carbon nanotube-gold nanocomposite thin film is fabricated and patterned into a highly conductive coil structure to realize a novel thin film inductive antenna. Preliminary results indicate that nanotube-gold nanocomposites exhibit resonance conditions, holding great promise for future RFID applications.

The corrosion of steel reinforcing bars in concrete is a significant problem for the US infrastructure, and the need for effective corrosion sensing in structures clearly exists. This paper reviews recent developments in corrosion sensing. First the bases and applications of several different types of embedded corrosion sensors are discussed. We then present a new basis for corrosion sensing based on magnetic field measurement. Magnetic field measurement allows both the extent and rate of corrosion to be measured using active and passive sensing configurations respectively. These two sensing configurations are briefly described. Both active and passive approaches can be applied without excavation of the concrete, so either remote sensing at a surface or internal sensing with an embedded unit are possible. The feasibility of using recently-developed high sensitivity miniature GMR (Giant Magneto-Resistive) sensors in the magnetic sensing configuration is investigated. Initial tests with GMR sensors passive show promise for the passive sensing configuration.

High-frequency guided mechanical waves were used to ultrasonically monitor reinforced mortar specimens undergoing accelerated general corrosion damage. Waves were invoked, using both single-cycle and high-cycle tonebursts, at frequencies where the attenuation is at a local minimum. Results show that the high-frequency waves were sensitive to irregularities in the reinforcing rebar profile caused by corrosion. The sensitivity is thought to be due to scattering, reflections, and mode conversion at the irregularities. Certain frequencies show promise for being insensitive to the surrounding mortar, ingress of water, presence of additional rebar, stirrups, and rust product accumulation. This lack of sensitivity allows for changes in guided wave behavior from bar profile deterioration to be isolated from the effects of other surrounding interfaces.

This paper presents a semi-active flutter control strategy for a high-aspect-ratio (HAR) wing using multiple magnetorheological (MR) dampers. In this paper, the aeroelastic behavior of the system is first investigated by establishing the aeroelastic equations of a HAR wing-aileron system. The strip theory is employed for calculating the unsteady aerodynamic loads. Then the semi-active aeroelastic control system with multiple MR dampers is modeled. The clipped-optimal control algorithm is performed for controlling the MR dampers to suppressing the flutter of the aeroelastic system. A passive flutter control of the system is also performed for the purpose of comparison. Numerical simulation results show that the semi-active control strategy based on multiple MR dampers holds promise in suppressing the flutter of the HAR wing-aileron system.

Structural condition assessment of highway bridges is traditionally performed by visual inspections or nondestructive evaluation techniques, which are either slow, unreliable or detects only local flaws. Instrumentation of bridges with accelerometers and other sensors, however, can provide real-time data useful for monitoring the global structural conditions of the bridges due to ambient and forced excitations. Traditionally, videos are used for surveillance purposes and environmental monitoring of civil structures. In this paper the potential for the utilization of videos in an integrated structural health monitoring of highway bridges beyond the mentioned traditional applications are reported. Results obtained from the field tests, which were carried out on a short-span instrumented bridge, are presented. Videos of vehicles passing by, together with signals from laser beam sensors placed on the side of the bridge, were captured, and synchronized with data recordings from the accelerometers. For short-span highway bridges, vibration is predominantly due to traffic excitation. A stochastic model of traffic excitation on bridges is developed assuming that vehicles traversing a bridge (modeled as an elastic beam) form a sequence of Poisson process moving forces and that the contact force of a vehicle on the bridge deck can be converted to equivalent dynamic loads at the nodes of the beam elements. Basic information of vehicle types, arrival times and speeds are extracted from the video images to develop a physics-based simulation model of the traffic excitation. This modeling approach aims at circumventing a difficulty in the system identification of bridge structural parameters. Current practice of system identification of bridge parameters is often based on the measured response (or system output) only, and knowledge of the input (traffic excitation) is either unknown or assumed, making it difficult to obtain an accurate assessment of the state of the bridge structures. The effectiveness and viability of this video-assisted approach are demonstrated by the field results. Finally, a technique on how to integrate the weights of vehicles in the image processing algorithm is proposed.

Sensing technology and sensor development have received increased attention in the recent years, and a number of types of sensors have been developed for various applications for materials and structures. In this paper, we will discuss the concept of combining sensing of global vibration and local infrared imaging techniques. The global vibration-based techniques determine the health condition of structures by the changes in their dynamic properties or responses to external disturbs or excitations. Infrared Imaging is introduced here to detect local defects or problems so that to provide more direct and accurate assessment about the severity and extent of the damage. The progress on developing a hybrid structural health monitoring system is presented through the results on both the global sensing algorithm study and local infrared imaging investigation on a steel C channel.

The Structural Health Monitoring (SHM) systems monitor the condition of structures in order to promptly and quantitatively evaluate risks due to their deterioration or damage. The SHM systems require deployment of many sensors. However, it has been found that the management of the sensor network configuration and data transfer becomes extremely difficult when many kinds of sensors are used at once. In addition, for accurate diagnosis of a structure we need statistical information of similar and different structural systems. Thus we need standardized data structures for databases and the rules (protocols) for data transfer. Furthermore, using the databases, we can make the configuration control of sensor networks autonomous. For demonstrating the potential of the proposed database system, we selected the database system used XML. The metadata associated with acquired data and the sensor configuration are properly modeled and used for autonomous configuration control and data transfer.

We consider the problem of monitoring and scheduling a network of intelligent sensors and actuators in large flexible structures. A hybrid controller that activates a subset of the devices in the sensor and actuator network is proposed and whose objective is to effectively address the effects of spatiotemporally varying disturbances. It is assumed that the flexible structure is subjected to disturbances and the intelligent control policy attempts to activate the actuators that, over the duration of a time interval, have spatial authority against the spatiotemporally varying disturbances. The hybrid controller switches the relevant actuators on and deactivates the ones that are not used over a given time interval. The basic idea behind the proposed supervisory scheme is to show that using a switched controller, it is possible to simultaneously improve controller performance and reduce the power consumption in the actuator/sensor network. Both analytical and experimental results on a flexible aluminum plate with eight pairs of collocated actuator/sensor PZT pairs are presented.

Efficient inspection methods are strongly in need for rail track maintenance to improve safety and economy of railway operation. The possibility of utilization of ordinary service vehicles for rail track monitoring is studied in this paper. By using service vehicles, it is possible to cover the entire network with much higher density and frequency compared with the conventional inspection with designated personnel and vehicles. Monitoring system to measure floor vibration of the vehicles is developed so that installation can be made without modification of the vehicles, and to reduce cost for sensors and systems. Then the developed system is applied to an actual railway and measurements with different time instances are compared. By looking at the root mean square (RMS) acceleration responses, it is found that the responses at the same location are stable with repetitive measurements. It is also observed that repair and deterioration of track beds cause significant change in measurement.

Structural health monitoring and control have attracted much research interest in the last few decades. Traditional monitoring and control systems depend on the use of cables to transmit sensor data and actuation signals. With recent advances in wireless communication technology, wireless networks can potentially offer a low-cost alternative to traditional cable-based sensing and control systems. Another advantage of a wireless system is the ease of relocating sensors and controllers, thus providing a flexible and reconfigurable system architecture. However, compared to a cable-based system, wireless communication generally suffers more stringent limitations in terms of communication range, bandwidth, latency, and reliability. This paper describes the architectural design of a prototype wireless structural monitoring and control system. Although design criteria for sensing and control applications are different, state machine concepts prove to be effective in designing simple yet efficient communication protocols for wireless structural sensing and control networks. In wireless structural sensing applications, the design priority is to provide reliable data aggregation, while in wireless structural control applications, the design priority is to guarantee real-time characteristics of the system. The design methodologies have been implemented in a prototype wireless structural monitoring and control system, and validated through a series of laboratory and field experiments.

Image sequences recorded by high-resolution digital video cameras contain vast amount of spatial-temporal information of targeted objects. With the rapid increase of image resolution, these digital cameras can now be used to measure three-dimensional complex motion of structures with sufficient accuracy for the purpose of modal analysis or health monitoring applications. In this paper, a measurement technique based on image sequence analysis is proposed for extracting spatial-temporal responses of continuous structures. Two digital cameras are used to record two-dimensional (2D) image sequences of a three-dimensional (3D) structural vibration response. This structural vibration response is reconstructed using the two 2D image sequences through the epipolar geometry theory without the use of any pre-installed targets. The obtained displacement response provides a more direct way to quantify the modal properties of the structure. To demonstrate, a laboratory test was conducted to measure the free vibration of a cantilever steel rod. Results show that the proposed technique can obtain excellent results as compared to the analytical solution. The proposed technique provides a low-cost alternative to measure 3D vibration of low-frequency flexible structures such as bridge cables in a non-contact and non-target fashion.

Structural damage will change the dynamic characteristics, including natural frequencies, modal shapes, damping ratios and modal flexibility matrix of the structure. Modal flexibility matrix is a function of natural frequencies and mode shapes and can be used for structural damage detection and health monitoring. In this paper, experimental modal flexibility matrix is obtained from the first few lower measured natural frequencies and incomplete modal shapes. The optimization problem is then constructed by minimizing Frobenius norm of the change of flexibility matrix. Gauss- Newton method is used to solve the optimization problem, where the sensitivity of flexibility matrix with respect to structural parameters is calculated iteratively by only using the first few lower modes. The optimal solution corresponds to structural parameters which can be used to identify damage sites and extent. Numerical results show that flexibility-based method can be successfully applied to identify the damage elements and is robust to measurement noise.

The Hilbert-Huang transform (HHT) has been shown to be effective for characterizing a wide range of nonstationary signals in terms of elemental components through what has been called the empirical mode decomposition. The HHT has been utilized extensively despite the absence of a serious analytical foundation, as it provides a concise basis for the analysis of strongly nonlinear systems. In this paper, we attempt to provide the missing link, showing the relationship between the EMD and the slow-flow equations of the system. The slow-flow model is established by performing a partition between slow and fast dynamics using the complexification-averaging technique, and a dynamical system described by slowly-varying amplitudes and phases is obtained. These variables can also be extracted directly from the experimental measurements using the Hilbert transform coupled with the EMD. The comparison between the experimental and analytical results forms the basis of a nonlinear system identification method, termed the slow-flow model identification method, which is demonstrated using numerical examples.

Identification of damage in a structure, or structural change in general, has been a challenging problem for the researchers in Structural Health Monitoring (SHM) area. Over the last a few decades, a number of experimental and analytical techniques have been developed and used to solve such problem. It has been has been recently accepted in the literature that the process of damage identification problem is one where statistical pattern recognition techniques can be of use because of the inherent uncertainties of the problem. Time series analysis is one of the methods, which is implemented in statistical pattern recognition applications to SHM. In previous studies, Auto-Regressive (AR) models are highly utilized for this purpose. In this study, AR model coefficients are used with different outlier detection and clustering algorithms to detect the change in the boundary conditions of a steel beam. A number of different boundary conditions are realized by using different types and amounts of elastomeric pads. The advantages and the shortcomings of the methodology are discussed in detail based on the experimental results in terms of the ability of it to detect the structural changes and localize them.

The inconsistency in the data handling capacity of the components of an on-line SHM system has impeded its effective use. To address this problem, this paper presents a new concept for integrated SHM system with several special functional modules such as sensor data compression, interactive data retrieval and structural knowledge discovery. In such an integrated SHM system, streamlined data flow is used as a unifying thread to integrate the individual components of on-line SHM system. Adoption of this new concept will enable the design of on-line SHM system with more uniform data generation and data handling capacity for its subsystems. To examine this concept in the context of vibration-based SHM system, real sensor data from an on-line SHM system comprising a laboratory size steel bridge structure and an on-line data acquisition system with remote data access was used in this study. Vibration test results clearly demonstrated the prominent performance characteristics of integrated SHM system including rapid data access, interactive data retrieval and knowledge discovery of structural conditions on a global level.

The Bill Emerson Cable-stayed Bridge is a newly built 1206 meter long structure crossing the Mississippi River. Due to its criticality and proximity to the New Madrid Seismic Zone, a seismic monitoring system consisting of 84 accelerometers was established for the bridge and its adjacent area. This paper is focused on a three-step artificial neural network strategy that was developed to identify the stiff of the bridge structure using the field measured dynamic response time histories without performing any eigenvalue analysis. The first step is to develop and train an emulator neural network for accurate prediction of the responses of the Bill Emerson Cable-stayed Bridge model, which represents the healthy state of the structure. A finite element model of the cable-stayed bridge was established, which represents the as-built bridge and was calibrated with the measured earthquake data from the seismic monitoring system. The second step is to establish and train a parameter evaluator neural network for relating the stiff reduction in the model bridge to the response prediction error by the emulator neural network. The third and last step is to identify the location and degree of stiff reduction in the Bill Emerson Cable-stayed Bridge.

This study focuses on data-driven methods for structural health monitoring and introduces a Bivariate Regressive Adaptive INdex (BRAIN) for damage detection in a decentralized, wireless sensor network. BRAIN utilizes a dynamic damage sensitive feature (DSF) that automatically adapts to the data set, extracting the most damage sensitive model features, which vary with location, damage severity, loading condition and model type. This data-driven feature is key to providing the most flexible damage sensitive feature incorporating all available data for a given application to enhance reliability by including heterogeneous sensor arrays. This study will first evaluate several regressive-type models used for time-series damage detection, including common homogeneous formats and newly proposed heterogeneous descriptors and then demonstrate the performance of the newly proposed dynamic DSF against a comparable static DSF. Performance will be validated by documenting their damage success rates on repeated simulations of randomly-excited thin beams with minor levels of damage. It will be shown that BRAIN dramatically increases the detection capabilities over static, homogeneous damage detection frameworks.

Various identification methods are compared for full-scale nonlinear viscous dampers, including a parametric approach using a simplified design model (SDM), the non-parametric Restoring Force Method (RFM), and the non-parametric Artificial Neural Network (ANN) approach. Advantages and disadvantages of each method are discussed for monitoring purposes. In the comparison, it is shown that the RFM is superior to other methods in regard to the following aspects: (1) no assumption is needed on the nature of the monitored systems; (2) the method is applicable to a wide range of nonlinear system types; (3) the same identification model can be used for the unknown system changes, including the change of system type as well as the change of system parameter values; and (4) physical interpretation of system changes are possible, using the identified values of the series expansion coefficients. A set of experiments was also conducted using magneto-rheological (MR) dampers to validate the feasibility of system change detection. For small changes in the magnetic field strength, the corresponding changes in the dynamic characteristics of the MR damper were detected, using the identified RFM coefficients.

Determination of crack depth in field using the self-calibrating surface wave transmission measurement and the cutting frequency in the transmission function (TRF) is very difficult due to variations of the measurement conditions. In this study, it is proposed to use the measured full TRF as a feature for crack depth assessment. A principal component analysis (PCA) is employed to generate a basis of the measured TRFs for various crack cases. The measured TRFs are represented by their projections onto the most significant principal components. Then artificial neural network (ANN) using the PCA-compressed TRFs is applied to assess the crack in concrete. Experimental study is carried out for five different crack cases to investigate the effectiveness of the proposed method. Results reveal that the proposed method can be effectively used for the crack depth assessment of concrete structures.

This paper introduces a continuous effort towards the development of a heuristic initialization methodology for constructing multilayer feedforward neural networks to model nonlinear functions. In this and previous studies that this work is built upon, including the one presented at SPIE 2006, the authors do not presume to provide a universal method to approximate arbitrary functions, rather the focus is given to the development of a rational and unambiguous initialization procedure that applies to the approximation of nonlinear functions in the specific domain of engineering mechanics. The applications of this exploratory work can be numerous including those associated with potential correlation and interpretation of the inner workings of neural networks, such as damage detection. The goal of this study is fulfilled by utilizing the governing physics and mathematics of nonlinear functions and the strength of the sigmoidal basis function. A step-by-step graphical procedure utilizing a few neural network prototypes as "templates" to approximate commonly seen memoryless nonlinear functions of one or two variables is further developed in this study. Decomposition of complex nonlinear functions into a summation of some simpler nonlinear functions is utilized to exploit this prototype-based initialization methodology. Training examples are presented to demonstrate the rationality and effciency of the proposed methodology when compared with the popular Nguyen-Widrow initialization algorithm. Future work is also identfied.

The employment of hydrogen has shown a lot of promises as an alternative for conventional fuel sources. However, if not handled properly, hydrogen content as low as 4% can lead to a life-threatening catastrophe. Some sensors for hydrogen detection have already been built to address this safety issue. Unlike most of the traditional hydrogen sensors, the sensor developed in this study features high sensitivity, fast response, miniature size, and the ability to detect hydrogen under room temperature. The sensor template has a special nanoporous structure, coming from self assembled aluminum oxide after anodization process. Deposition of palladium particles into the nanopores brings superb hydrogen sensing ability by introducing a granular structure of sensing particles. The sensor prototype has been tested under controlled atmosphere with varying hydrogen concentrations.

Two parameter estimation approaches have been developed for system modeling and health monitoring of multi-story buildings based on structural vibration responses under seismic excitation and/or applied forces. In the first approach, parameter estimation is performed in a decentralized fashion, i.e. parameters are estimated for each story individually, while in the second approach, the parameters are estimated in a centralized manner for the entire structure. In order to reduce the effect of random noise, drift with D.C. off-set as well as low-frequency disturbances in the measured data, three kinds of filter (i.e., high-pass filter, moving average filter and Kalman filter) have been used for data preprocessing. Numerical simulations based on lumped parameter models and a finite element model of a realistic building have been conducted. The results show that, the performance of the decentralized approach is better than the centralized one in the cases studied.

We report on the application of wafer-type PZT transducers to the detection of flaws in steel plate girders. In these experiments one transducer is used to emit a pulse and the second receives the pulse and reflections from nearby boundaries, flaws, or discontinuities (pitch-catch mode). In this application there will typically be numerous reflections observed in the undamaged structure. A major challenge is to recognize new reflections caused by fatigue cracks in the presence of these background reflections. A laboratory specimen plate girder was fabricated at approximately half scale, 910 mm deep with an h/t ratio of 280 for the web and a b/t ratio of 16 for the flanges, and with transverse stiffeners fabricated with a web gap at the tension flange. Two wafer-type transducers were mounted on the web approximately 175 mm from the crack location, one on each side of the stiffener. The transducers were operated in pitch-catch mode, excited by a windowed sinusoid to create a narrowband transient excitation. The transducer location relative to the crack corresponded to a total included angle of roughly 30 degrees in the path reflecting from the crack. Cyclic loading was applied to develop a distortion-induced fatigue crack in the web at the web gap location. After appearance of the crack, ultrasonic measurements were performed at a range of center frequencies below the cutoff frequency of the A1 Lamb wave mode. Subsequently the crack was extended mechanically to simulate crack growth under primary longitudinal (bending) stress and the measurements were repeated. Direct differencing of the signals showed arrivals at times corresponding to reflection from the crack location, growing in amplitude as the crack was lengthened mechanically. These results demonstrate the utility of Lamb waves for crack detection even in the presence of numerous background reflections.

In recent years, unrestrained monitoring human posture and action is a field of increasing interest in the welfare of the elderly and the sport-biomechanics. The scope is this study is that we develop a wearable sensing clothes, which can detect entire body posture and motion using a hetero-core optic fiber sensor. This newly developed sensor can offers several advantages such as the simplicity of structure and fabrication, the stable single mode based operation, the temperature independent property, and the precise loss controllability on given macro bending. These properties are suitable for implementing unrestrained wearable clothes. In this paper, for monitoring flexion of joint without the disturbance of the rucks in the clothes, we proposed and fabricated the improved module structured in the joint ranging 0-90 degree. Additionally, in order to reduce the number of transmission line to be added due to monitoring the whole body posture and motion, we tested that two hetero-core sensors which are tandem placed in a single transmission line have been discriminated by the temporal differential of the optical loss. As a result, we have successfully demonstrated that the wearable sensing clothes could monitor arm motion and human walking without restraint to human daily behavior.

Structural health monitoring (SHM) technology may be applied to composite bonded repairs to enable the continuous through-life assessment of the repair efficacy. This paper describes an SHM technique for the detection of debonding in composite scarf repairs using fibre optic Bragg grating strain sensors. A typical composite sandwich structure with a scarf repair on one surface is examined in this paper. A finite element study was conducted which showed that the strain in the debonded region changed significantly compared to the undamaged state. A differential strain approach was used to facilitate the detection of debonds, where two sensors were strategically positioned so that their strain differential increased as the damage propagated. With the use of matching gratings, this technique greatly reduced the support equipment requirement by converting the spectral information into an intensity-modulated signal, thus allowing a compact photodetector to be used for sensor interrogation. An experimental investigation was conducted to validate the theoretically predicted results. The experimental measurements agreed well with the numerical findings qualitatively, indicating that the proposed scheme has great potential as a simple and effective monitoring technique for composite scarf repairs.

Recent work in the fabrication of self assembled quantum dot (QD) detectors on active structural fibers and for the implementation of optical fiber sensors is reported in this paper. The ability to develop the QD based devices and materials via the electrostatic self-assembly (ESA) process has been demonstrated by Hand and Kang in prior work. The QD precursor nanocluster materials involved in ESA have been designed and synthesized to proper size, stabilized in an aqueous-based solution, and functionalized to allow self-assembly. Optical fiber sensor instrumentation has been developed to monitor the reflected optical power with the buildup of the QD layers on the fiber endface during the ESA process. The results are confirmed by observing the effects of low-finesse QD Fabry-Perot interferometric cavities formed via such processes on the ends of optical fibers. The photocurrent-voltage characteristics show a diode-like behavior with linear photocurrent in the reverse bias and non-linearity in the forward bias. It is suggested that fast response times can be achieved due to the high carrier mobilities that arise in part due to structure of the materials formed via the solution-based ESA process. This paper reviews this prior work and shows examples of deposition of devices on both fiber endfaces and cladding surfaces.

This paper describes recent progress conducted towards the development of a miniature fiber Bragg grating sensor interrogator (FBG-Transceiver^TM) system based on multi-channel integrated optic sensor (InOSense^TM) microchip technology. The hybrid InOSense^TM microchip technology enables the integration of all of the functionalities, both passive and active, of conventional bench top FBG sensor interrogator systems, packaged in a miniaturized, low power operation, 2-cm x 5-cm package suitable for the long-term structural health monitoring in applications where size, weight, and power are critical for operation. The FBG-Transceiver system uses active optoelectronic components monolithically integrated to the InOSense^TM microchip, a microprocessor controlled signal processing electronics board capable of processing the FBG sensors signals related to stress-strain and temperature as well as vibration and acoustics. The FBG-Transceiver^TM system represents a new, reliable, highly robust technology that can be used to accurately monitor the status of an array of distributed fiber optic Bragg grating sensors installed in critical infrastructures. Its miniature package, low power operation, and state-of-the-art data communications architecture, all at a very affordable price makes it a very attractive solution for a large number of SHM/NDI applications in aerospace, naval and maritime industry, civil structures like bridges, buildings and dams, the oil and chemical industry, and for homeland security applications. The miniature, cost-efficient FBG-Transceiver^TM system is poised to revolutionize the field of structural health monitoring and nondestructive inspection market. The sponsor of this program is NAVAIR under a DOD SBIR contract.

Fiber optical components such as fiber gratings, fiber interferometers, and in-fiber Fabry-Perot filters are key components for optical sensing. Fiber optical sensors offer a number of advantages over other optical and electronic sensors including low manufacturing cost, immunity to electromagnetic fields, long lifetimes, multiplexing, and environmental ruggedness. Despite the advantages of purely passive optical components described above, fiber sensor performance and applications have been limited by their total passivity and solid-core/solid cladding structure configurations. Passive sensors can only gather limited information. Once deployed; set point, sensitivity, trigging time, responsivity, and dynamic range for each individual fiber sensor cannot be adjusted or reset to adapt to the changing environment for active sensing. Further, the fiber sensor sensitivity is also limited by the traditional solid core/solid cladding configuration. In this paper, we present a concept of active fiber sensor that can directly powered by in-fiber light. In contrast to a passive sensor, optical power delivered with sensing signal through the same fiber is used to power in-fiber fiber Bragg grating sensors. The optical characteristics of grating sensors can then be adjusted using the optical energy. When optical power is turned off, in-fiber components can serve as traditional passive sensor arrays for temperature and strain measurements. When optical power is turned on, the fiber sensor networks are capable of measuring a wide array of stimuli such as gas flow, wall shear stress, vacuum, chemical, and liquid levels in cryogenic, micro-gravity, and other hostile environments. In this paper, we demonstrate in-fiber light powered dual-function active FBG sensor for simultaneous vacuum, hydrogen fuel gas, and temperature measurement in a cryogenic environment.

In this study, the development and optimization of embedded fiber Bragg grating (FBG) sensor networks within composite materials was investigated. Various densities of optical fibers were embedded within composite laminates, and low-velocity impact damage responses were evaluated to determine the effects on the mechanical behavior of the laminates. The woven composites were subjected to multiple strikes at 2 m/s until perforation occurred, and the impactor position and acceleration were monitored throughout each event. From these measurements, we obtained dissipated energies and contact forces for specimens with and without embedded optical fibers. Embedded fibers were interrogated with light to determine the degree to which light could pass through them for each density and arrangement. Cross sectional optical micrographs of the specimens were used to determine the local effects of the embedded fibers on neighboring fibers and the surrounding matrix material, both before and after impact events. Currently FBG sensors are being calibrated and prepared for embedment in specifically chosen configurations within the composite. They will be serially multiplexed together to create a single fiber sensing network capable of monitoring damage over a large area. Real time strain information will be gathered as future embedded laminates are subjected to impact events, and the resulting data will be used to better monitor and predict damage in the composite system.

The field of nanotechnology is rapidly maturing into a fertile and interdisciplinary research area from which new sensor and actuator technologies can be conceived. The tools and processes derived from the nanotechnology field have offered engineers the opportunity to design materials in which sensing transduction mechanisms can be intentionally encoded. For example, single- and multi-walled carbon nanotubes embedded within polyelectrolyte thin films have been proposed for strain and pH sensing. While the electromechanical and electrochemical response of carbon nanotube composites can be experimentally characterized, there still lacks a fundamental understanding of how the conductivity of carbon nanotube composites is spatially distributed and how it depends on external stimuli. In this study, electrical impedance tomography is proposed for spatial characterization of the conductivity of carbon nanotube composite thin films. The method proves promising for both assessment of as-fabricated thin film quality as well as for two-dimensional sensing of thin film response to mechanical strain and exposure to pH environments.

A multifunctional structural nanoskin is being developed using Carbon Nanosphere Chains (CNSC) and a polymer. Three suites of properties are particularly important in developing the nanoskin; good elastic properties, good electrical properties, and good transducer properties. The CNSC material is first studied in the bulk form. Preliminary results show CNSC are well crystallized graphitic structures with spherical shape connected in chains. The CNSC are almost catalyst free, and are lightweight and hydrophobic. The CNSC morphology is between that of spheres and cylinders. Initial testing was done to characterize the CNSC and to determine if the nanosphere chains can be purified and then dispersed to reinforce an epoxy polymer. The testing involved evaluation of the mechanical properties and electrical conductivity of an epoxy nanocomposite material. A simple analysis of series and parallel fiber reinforcement of polymers was performed first and predicted that limited improvement in stiffness is possible using discontinuous fibers, while a large improvement is possible using continuous fibers. Epoxy nanocomposites were then formed by simultaneously mixing CNSC and epoxy using a shear mixer and ultrasonicator. The elastic properties of the cured nanocomposite showed small improvement with small percentages of the CNSC added to the polymer. On the other hand, compressed CNSC powder has high electrical conductivity. Therefore, a nanoskin material was designed by dispersing CNSC in a solvent, solution casting the solvent into a thin film in a mold, covering the film with epoxy, and closing the mold and curing under pressure. Evaluation of the material is still underway, but the nanoskin has electrical conductivity on one side and is electrically insulating on the other side. A major advantage of the CNSC material is that is can be produced in large quantities at reasonable cost for many potential applications.

Pre-existing cracks, introduced by a Vickers diamond hardness indenter in BM500 (Navy Type II) PZT, exhibit visible growth and thickening when subjected to low frequency electric fields with amplitudes above a threshold on the order of 1.66 E_c. Thickening, but no growth, of cracks is also observed after cycles of a field of 1.64 E_c. The threshold field is related to the ferroelectric, piezoelectric and elastic properties of the ceramic. At fields above the threshold, cracks grow to a limiting size after a relatively low number of cycles, and then increase in width, as opposed to length, when further electric cycles are applied. The maximum size to which field-induced cracks grow is of the order of the separation of the electrodes. Changes observed in the resonance peaks of impedance spectra may be used as a basis for non-destructive identification of defects in piezoelectrics.

This paper presents a theoretical model for anisotropic wave attenuation in composites. The model has been implemented in a software called FIBREWAVE in order to predict dispersion and attenuation of S₀, A₀ and SH₀ Lamb wave modes. The required input data are the complex stiffness matrix coefficients of the unidirectional plies of the laminate, which have been measured by a laser interferometry method. Complex stiffness data for an unidirectional CFRP laminates are moreover presented. Satisfactory agreement has been observed between predicted and experimental group velocities and wave attenuations.

This project investigates the magnetic structure and mechanical properties of iron-gallium nanowires to facilitate the modeling and design of sensor devices. Magnetic force microscopy (MFM) is employed to better understand the domain orientation and size along the cross-section of a close packed wire array. Mechanical properties are identified by conducting static tensile testing on individual nanowires using a manipulator stage designed for use within a scanning electron microscope (SEM). The Young's modulus of the nanowires is found to agree well with the value for the bulk material, but these structures do demonstrate a large increase in ultimate tensile strength. Other tests include resonance identification of nanowire beam bending via dynamic excitation.

This paper describes a new low-frequency seismic sensor for geophysical applications. The instrument is basically a monolithic tunable folded pendulum with an interferometric readout system, that can be configured as seismometer or as accelerometer. The monolithic mechanical design and the introduction of a laser interferometric technique for the readout implementation make it a very sensitive and compact instrument with a very good immunity to environmental noises. The theoretical sensitivity curve is calculated considering the brownian noise, the readout noise and the data acquisition noise. Preliminary tests on the mechanical performances of the monolithic structure and on the optical readout have been performed. Interesting result is the measured resonant frequency of the instrument of ≈ 150mHz obtained with a rough tuning, demonstrating the feasibility of a resonant frequency of the order of 5mHz with a more refined tuning. The transfer function of the folded pendulum in open loop configuration is calculated measuring the resonant frequency and the quality factor for several step responses. Then a PID controller is added to implement the closed loop configuration. The mechanics of the seismic sensor, the optical scheme of the readout system, the theoretical predictions and the preliminary experimental performances as accelerometer are discussed in detail, together with the foreseen further improvements.

Two micro-optomechanical accelerometers based on Multi-Mode Interference (MMI) couplers were designed and evaluated in this study. The optical components were optimized with the Parameter Scan Method. According to the photoelastic effect, the change in refractive index of a waveguide made of crystal materials is related to the mechanical strains in the waveguide. In this study, such change was calculated using the mechanical strains obtained from the Finite Element Analysis (FEA) results. Beam Propagation Method (BPM) was used to study the relationship between the input acceleration and the output optical power and thus the performance of the proposed accelerometers. The results show the two designs are suitable for different acceleration ranges.

A multifunctional optical MEMS sensor system that can be used for the simultaneous measurement of displacement, temperature, and pressure has been fabricated. The system is based on an array of micromachined Fabry-Perot devices suitable for high temperature and pressure operations. The central concept of the sensor system is that airflow force around the moving structure (air viscous damping) strongly affects the oscillating height of the microcavity and hence, the mechanical performance of the device. The major effect that the viscosity and the density of the air have on the damping provides the mechanism for the simultaneous detection of pressure and temperature in addition to displacement. Since the air is trapped by the viscous damping effects there is no need for a sealed cavity. In addition, the very simple configuration in the optical interferometric system can be considered for the integration in the sensor system package. A model to accurately predict the frequency response of the Fabry-Perot structure subjected to a mechanical excitation on the substrate at different pressures and temperatures is presented. The model shows that shifts of the order of 10.5°C and 7.46psi can be detected for temperatures and pressures around 536°C and 446psi respectively using 90μm long microcantilever beams vibrating at a frequency of 97.4 kHz. To the best of our knowledge, this sensor array is one of the few, if not the only MOEMS device in the literature capable of simultaneous measurement of displacement, temperature, and pressure in high temperature environments.

This paper presents the design, fabrication, and testing of a force sensor for integrated use with thermomechanical in-plane microactuators. The force sensor is designed to be integrated with the actuator and fabricated in the same batch fabrication process. This sensor uses the piezoresistive property of silicon as a sensing signal by directing the actuation force through two thin legs, producing a tensile stress. This tensile load produces a resistance change in the thin legs by the piezoresistive effect. The resistance change is linearly correlated with the applied force. The device presented was designed by considering both its piezoresistive sensitivity and out-of- plane torsional stability. A design trade-off exists between these two objectives in that longer legs are more sensitive yet less stable. Fabrication of the sensor design was done using the MUMPs process. This paper presents experimental results from this device and a basic model for comparison with previously attained piezoresistive data. The results validate the concept of integral sensing using the piezoresistive property of silicon.

This paper presents studies of seismic response control of a frame structure braced with SMA (Shape Memory Alloy) tendons through both numerical and experimental approaches. Based on the Brinson one-dimensional constitutive law for SMAs, a two-story frame structure braced diagonally with SMA tendons is used as an example to simulate numerically the vibration control process. By considering the temperature, different initial states and thermal properties of the SMA tendon, and the variable intensity and frequency of earthquake input, the parameters of the system were analyzed during the numerically simulation. The time histories of the displacement and hysteretic loops of the SMA tendons were simulated under earthquake ground motion by using finite element method (FEM). To validate the efficiency of the simulation, a shaking table test for the frame structure was conducted. Both numerical simulation and experimental results show that the actively controlled martensite SMA tendons can effectively suppress the vibration of the multi-story frame structure during an earthquake.

A conventional tuned liquid damper (TLD) generates a relatively small control force associated with low density of sloshing water. To overcome this main drawback, proposed in this study is a new TLD system composed of water and fine particles in a rectangular tank of sloping bottom. The effectiveness of the proposed mass-variable TLD system was demonstrated with shake table tests. In comparison with a conventional TLD, the mass-variable TLD can more effectively reduce structural responses particularly under large external excitations. The mass-variable TLD can also be effective in the earlier stage of an earthquake event due to the increasing mass nature as the excitation increases. This attribute makes the new TLD particularly attractive under impulsive loads such as near-field ground motions.

In this paper, a simple non-model based control strategy is developed to control stay cable vibration using MR dampers. The strategy is an integral plus double integral control based on the collocated accelerometer feedback. To experimentally study this control method, a model stay cable equipped with an Magneto-Rheological(MR) damper is used in this study. To demonstrate the effectiveness of the proposed controller, comparisons of the unimpeded stay cable, passive off, passive on and the proposed integral plus double integral control are conducted. For each case, the damping ratio of the stay cable vibration is calculated. Comparisons of the experimental results show that non-model based vibration control of the stay cable using the MR damper is most effective in reducing the stay cable vibration.

Water supply systems in Japan contribute significantly to improve public health. Unfortunately, there are many age-deteriorated pipes of various sizes and leaks frequently occur. Particularly devastating are hidden leaks occurring underground because when left undetected for years these leaks result in secondary damage. Thus, early detection and treatment of leaks is an important civil engineering challenge. At present the acoustic method is the most popular leak detection method. The purpose of this study is to propose an easy and stable leak detection method using the acoustic method assisted by pattern recognition techniques. In the proposed method we collect in the form of digital signals sound and pseudo-sound samples of underground leaking pipes. Principal component analysis (PCA) of the power spectrum of one leak sound is made, and a new coordinate system is constructed. We project the other sounds in the coordinate system, and evaluate if the sounds are similar to the sample sound or not by comparing the residual between the original and the projection. Next, we evaluate the DSF (Damage Sensitive Feature), which is a function of the first three AR model. At last, the feature vectors are created by combining the residuals, the DSF, and the damping ratio of the AR model, and a leak detection method is proposed using the Support Vector Machine (SVM) based upon them. In this study, it is shown that the residual and DSF are useful indices for leak detection. Furthermore, the proposed method shows high accuracy in recognizing leaks.

Despite the modernity of today's cities, all kinds of buildings are built without proper hedge strategies against the risk of large disasters such as earthquakes. In order to control such risks, new engineering and economic mechanisms should be developed. On the engineering front recently Structural Health Monitoring (SHM) systems using sensor networks have been proposed and even enacted in many variations. Fortunately, data taken from such systems serve as good candidates as risk indices for each building. The purpose of this study is to propose insurance derivatives to maintain and improve the safety of buildings and to provide a risk hedge instrument for owners. These derivatives should be able to take advantage of information gained from SHM sensor networks. In this study, hazard information offered by J-SHIS (Japanese Seismic Hazard Information Station), and Weibull distributions associated with Is-WF (Seismic index based on seismic diagnosis), proposed by Okada and Takai as Damage Index Functions, were used for the quantification of risk. This simply defined quantification was used to evaluate the proposed earthquake derivatives. Results showed that the proposed derivative is better than the functions currently used for earthquake insurance, and that it has potential to be used as incentive for seismic strengthening.

Artificial neural networks (ANNs) have been increasingly utilized for structural health monitoring (SHM) due to the advantage that it needs only a few training data to detect damage in structures. In this study, a new damage monitoring method using a set of parallel ANNs and acceleration signals is developed for alarming locations of damage in PSC girder bridges. First, theoretical backgrounds are described. The problem addressed in this paper is defined as the stochastic process. In addition, a parallel ANN-algorithm using output-only acceleration responses is newly designed for damage detection in real time. The cross-covariance of two acceleration-signals measured at two different locations is selected as the feature representing the structural condition. Neural networks are trained for potential loading patterns and damage scenarios of the target structure for which its actual loadings are unknown. The feasibility of the proposed method is evaluated from numerical model tests on PSC beams for which accelerations were acquired before and after several damage cases.

Developed to study long, regularly sampled streams of data, time series analysis methods are being increasingly investigated for the use of Structural Health Monitoring. In this research, Autoregressive (AR) models are used in conjunction with Artificial Neural Networks (ANNs) for damage detection, localisation and severity assessment. In the first reported experimental exercise, AR models were used offline to fit the acceleration time histories of a 3-storey test structure in undamaged and various damaged states when excited by earthquake motion simulated on a shake table. Damage was introduced into the structure by replacing the columns with those of a thinner thickness. Analytical models of the structure in both damaged and undamaged states were also developed and updated using experimental data in order to determine structural stiffness. The coefficients of AR models were used as damage sensitive features and input into an ANN to build a relationship between them and the remaining structural stiffness. In the second, analytical exercise, a system with gradually progressing damage was numerically simulated and acceleration AR models with exogenous inputs were identified recursively. A trained ANN was then required to trace the structural stiffness online. The results for the offline and online approach showed the efficiency of using AR coefficient as damage sensitive features and good performance of the ANNs for damage detection, localization and quantification.

Damage indicator for building structures using artificial neural networks (ANN) requiring only acceleration response is proposed. The ANN emulator used for emulating the structural response is tuned to properly model the hysteretic nature of building response. To facilitate the most realistic monitoring system using accelerometers, the acceleration streams at the same location but at different time steps were utilized. The prediction accuracy could be raised by the increment of number of acceleration streams at different time steps. In our proposed approach, damage occurrence alarm could be obtained practically and economically only using readily available acceleration time histories. Based on the numerical simulation for a 5-story shear structure, the adaptability, generality and appropriate parameter of the neural network were studied in. The damage is quantified by using relative root mean square (RRMS) error. Variant ground motions were used to certify the generality of this approach. The appropriate parameter of the neural network was suggested according to variant values of damage index corresponding to the different parameters.

It is difficult to obtain dynamic response measurement of a whole structure in reality, development of structural parametric identification methodologies using spatially incomplete dynamic response measurement is critical for performance evaluation and the realization of infrastructure sustainability. A general structural parametric identification methodology by the direct use of free vibration acceleration time histories without any eigenvalue extraction process that is required in many inverse analysis algorithms is proposed. An acceleration-based neural network (ANN) and a parametric evaluation neural network (PENN) are constructed to identify structural inter-storey stiffness and damping coefficients using an evaluation index called root mean square of prediction difference vector (RMSPDV). The performance of the proposed methodology using spatially incomplete acceleration measurements is examined by numerical simulations with a multi-degree-of-freedom (MDOF) shear structure involving all stiffness and damping coefficient values unknown. Numerical simulation results show that the proposed methodology is a practical method for near real-time identification and damage detection when several seconds of spatially incomplete dynamic responses measurements are available.

A challenging problem in structural damage detection based on vibration data is the requirement of a large number of sensors and the numerical difficulty in obtaining reasonably accurate results when the system is large. To address this issue, the substructure identification approach may be used. Due to practical limitations, the response data are not available at all degrees of freedom of the structure and the external excitations may not be measured (or available). In this paper, an adaptive damage tracking technique, referred to as the sequential nonlinear least-square estimation with unknown inputs and unknown outputs (SNLSE-UI-UO) along with the sub-structure approach will be used to identify damages at critical locations (hot spots) of the complex structure. In our approach, only a limited number of response data are needed and the external excitations may not be measured, thus significantly reducing the number of sensors required and computational efforts. The accuracy of the proposed approach is illustrated using a long-span truss with finite-element formulation. Simulation results demonstrate that the proposed approach is capable of tracking the local damages and it is suitable for local structural health monitoring.

The detection of structural damage is an important objective of structural health monitoring systems. Analysis techniques for the damage detection of structures, based on vibration data measured from sensors, have been studied without experimental verifications. In this paper, a newly proposed data analysis method for structural damage identifications, referred to as the adaptive quadratic sum squares error (AQSSE), will be verified experimentally. A series of experimental tests using a scaled 3-story building model have been conducted recently. In the experimental tests, white noise excitations were applied to the top floor of the model, and different damage scenarios were simulated and tested. These experimental data will be used to verify the capability of the AQSSE approach in tracking the structural damage. The tracking results for the stiffness of all stories, based on the AQSSE approach, are compared with the stiffness predicted by the finite-element method. Experimental results demonstrate that the AQSSE approach is capable of tracking the structural damage with reasonable accuracy.

Both piezoresistive and piezoelectric materials are commonly used to detect strain caused by structural vibrations in macro-scale structures. With the increasing complexity and miniaturization of modern mechanical systems such as hard disk drive suspensions, it is imperative to explore the performance of these strain sensors when their dimensions must shrink along with those of the host structures. The miniaturized strain sensors must remain as small as possible so as to minimum their effect on structure dynamics, yet still have acceptable sensing resolution. The performances of two types of novel micro-scale strain gage for installation on stainless steel parts are compared in this paper. Micro-fabrication processes have been developed to build polycrystalline silicon piezoresistive strain sensors on a silicon substrate, which are later bonded to a steel substrate for testing. Piezoresistor geometries are optimized to effectively increase the gage factor of piezoresistive sensors while reducing sensor size. The advantage and disadvantage of these piezoresistors are compared to those of piezoelectric sensors. Experimental results reveal that the MEMS piezoelectric sensors are able to achieve a better resolution than piezoresistors, while piezoresistors can be built in much smaller areas. Both types of the MEMS strain sensors are capable of high sensitivity measurements, subject to differing constraints.

This paper is a continuation of the authors' previous effort (presented at SPIE 2006) of developing a "Smart Dust" (Mica2 Motes)-based wireless sensor network to detect hazardous roadway surface conditions. New developments reported herein focus on a series of investigations into the performance of "Smart Dust" wireless network. A series of pseudo-outdoor and road tests are conducted in this study. The network is fairly small with a large transmitting range between each Mote, compared with the published work on applying the same product. Surge Time Synchronization is explored in the specific application to allow each Mote to "wake up" periodically at a predefined time interval. In addition, a fairly simplistic pattern classification algorithm is embedded into the Motes to create the smart wireless sensing application. Many performance metrics of the adopted "Smart Dust" wireless sensor network with a small size and large transmitting range are revealed in this study through a series of data processing efforts. Results are presented to examine (1) network connectivity, (2) packet delivery performance, (3) initial connection time, (4) error rate, (5) battery life, and (6) other network routing properties such as the parent time histories for each Mote. These results and analysis form a database for future efforts to better understand the performance of and the collected results from "Smart Dust".

The demand for real-time or in situ structural health monitoring has stimulated efforts to integrate self and environmental sensing capabilities into structural composite materials. Essential to the application of smart composites is the issue of the mechanical coupling of the sensor to the host material. In this study various methods of embedding sensors within the host composite material are examined. 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 or suitable simulated sensors. The sensors that are examined include simulated sensors in the form of chip resistors with the original packaging geometry and thin film sensors (PVDF). The sensors are integrated into the composite either by placement between the layers of prepreg or by placement within precision punched cut-outs of the prepreg material. Thus, through these tests we determine the technique that optimizes the mechanical properties of the host composite material.

This paper presents a damage assessment method using the measurement data of restoring force from a sub-structural system. A normalized hysteretic energy (NHE) for bi-linear model is developed as a function structural period and system ductility, which serves as a reference-based model for damage assessment. The stiffness degradation, strength deterioration and pinching effect in the inelastic hysteretic model are then determined from a series of nonlinear time history analysis of an inelastic SDOF system. Next, modification factors on the NHE for sensitivities of the inelastic model parameters are developed. Based on the identified model parameters by measuring the inelastic hysteretic behavior of the restoring force incorporated with the reference-based NHE model and the modification factor, the percentage of structural damage in relating to strength and stiffness degradation can be evaluated. Verification of the proposed method by simulation and experimental data of the cyclic loading and shaking table tests of the RC frame are conducted.

In order to measure three-axis force, two four-part tactile sensing systems based on piezoelectricity and optics were designed and fabricated. The feasibility and reliability of the two systems were evaluated both numerically and experimentally. A general formula between the applied three-axis force and the four-part tactile sensing signals was developed. It is expected that this formula should benefit the design and fabrication of new tactile sensing systems.

The purpose of this paper is to present experimental testing results obtained by using a novel polymer high strain sensor, Metal Rubber^TM. Dynamic, quasi-static tensile and quasi-static bending tests are performed to study the sensor's change in resistance as a result of the application of various mechanical loads. The strain signal generated by the Metal Rubber^TM sensor is also compared to the strain measured by a set of optical imaging cameras during a high strain tensile test of a nylon fabric. The results of the aforementioned experiments indicate that the Metal Rubber^TM sensor exhibits non-linearity and hysteresis as compared to a conventional metal foil strain gage. In addition, time varying, stress hardening was observed in the sensor. Results of the dynamic tests demonstrated that the sensor could be used to determine the resonant frequencies of a cantilever beam, when compared to using an accelerometer or a metal foil strain gage.

We present an intrinsic Fabry-Perot interferometric fiber sensor for high density quasi-distributed temperature and strain measurement. The two internal partial reflection mirrors in such a sensor are formed by a pair of ultra-short fiber Bragg gratings. We experimentally demonstrate the multiplexing of 56 such sensors in a single fiber using a frequency-division multiplexing scheme. We show that theoretically as many as 500 sensors can be multiplexed. We demonstrated the experimental results of the multiplexed sensors for quasi-distributed temperature and strain measurement and the temperature compensation of strain sensors.

It is well known that vibration-based damage detection methods lack sensitivity in modal frequencies to small changes in mass, stiffness, and damping parameters induced by damage. To circumvent this deficiency, in this paper a scheme through feedback control together with coherence method is first employed to enhance sensitivity the occurrence and location of damage through few of the lower natural frequencies. This sensitivity enhancement is based on pole placement from a single-point feedback control to compute the control gains. Relying on a priori knowledge of how certain damage scenarios affect modal properties, a coherence method correlates measured and predicted modal frequency shifts for a given set of damage scenarios to locate the damage. Numerical results show that the method with closed-loop control increases both the accuracy of locating damage and the ability to tolerate environmental noise. Subsequent to the fine sensitivity to locating the damage position, restoration to original dynamic structural performance in terms of few of the lower natural frequencies of the damaged structure is conducted by the feedback control using distributed actuation surrounding the damage area (multi-point control). Simulation results show that the dynamic characteristics of damaged structures can be successfully restored by applying distributed actuation that can be induced from the voltage by the distributed piezoelectric actuators.

Sonic infrared (IR) Imaging employs a short ultrasonic pulse excitation and Infrared Imaging to detect defects in materials and structures. The ultrasound pulse, typically a fraction of a second, causes heating in the defects, which results in the change of IR radiation from the target. This change can be detected by infrared sensors, thus, defects can be identified. One key objective in developing this technology is to optimize the IR signal with minimum ultrasound excitation energy being applied to the target. We have learned that the ultrasonic frequency, coupling medium between the ultrasonic transducer and the target, the pressure from the transducer to the target, the characteristics of the target itself, etc. are all factors that affect the IR signals. In a previous paper at this conference, we presented the thermal energy computing tools developed for analyzing IR data. In this paper, we present the results of our study on the effect of different coupling materials on IR signal levels for different types of materials.

Compliant piezoresistive MEMS sensors exhibit great promise for improved on-chip sensing. As compliant sensors may experience complex loads, their design and implementation require a greater understanding of the piezoresistive effect of polysilicon in bending and combined loads. This paper presents experimental results showing the piezoresistive effect for these complex loads. Several n-type polysilicon test structures were tested. Results show that, while tensile stresses cause a linear decrease in resistance, bending stresses induce a nonlinear rise in resistance contrary to the effect predicted by available models. The experimental data illustrate the inability of published piezoresistance models to predict the piezoresistive trends of polysilicon in bending and combined loads, indicating the need for more complete models appropriate for these loading conditions and more complete understanding of the piezoresistive effect.

Widely used 1-D guided wave phased arrays can only scan within 0°~180° range due to the intrinsic structural limitation. To overcome this limitation, multiple installations are unavoidable. However, by using 2-D configuration phased arrays, large structural interrogation can be conducted from a single location with a single scanning covering the entire 0°~360° range through omnidirectional beamforming. Based on the developed generic PWAS Lamb wave phased array beamforming formula, this paper aims to bring up the practical implementation of an 8x8 PWAS array and present analytical and experimental results concerning the omnidirectional damage detection ability. The theoretical beamforming of 2-D rectangular PWAS configuration will be presented at first based on the generic PWAS phased array beamforming formulation. Then, an 8x8 rectangular PWAS array is installed on the target aluminum specimen. Laboratory experiment is set up next and conducted various crack damage detection. Specimens include: (1) a single crack positioned at 90°; (2) a single crack positioned at 270°; (3) a single hole positioned at 180°; 4) a crack at 90° and a hole at 180°, respectively. The experiments will demonstrate the 360° damage finding ability of the 2-D PWAS array and the multiple damage detection ability as well. We finally end up with discussions on the practical application and come up with plans for future work on various 2-D array developments.

A new coupled vibration control system is proposed for a group of slender buildings constructed closely in urban areas. The connection dampers which can move in vertical, not in lateral are set between the adjacent buildings. Also, to concentrate the earthquake input energy to the connection dampers, a rocking structural system is applied to each connected building. This proposed system can introduce a kind of 'smart' self-centering system for target buildings. To verify the earthquake reduction effects of the proposed system, some numerical analyses are executed to real scale building frame models. In the analyses, two buildings are connected by the vertical dampers. That is the simplest application of the coupled vibration control system. Their responses are compared with those of a single fixed base frame model and a single rocking frame model. The analysis results successfully demonstrated that the new coupled vibration control system has high performance for seismic response reduction of target slender buildings.

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 singlemode 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. 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.

A project targeted at developing a low-cost fiber optic interrogator system for fiber Bragg grating (FBG) sensors has been completed, and has resulted in a stand-alone system that can be used in multiple applications. The interrogator system, tailored as a potential solution for embedded strain sensing in composite wind turbine blades, was recently tested and its performance validated at the Infrastructure Assurance & Non-Destructive Inspection (NDI) department at Sandia National Laboratories (SNL). The test specimen used to test the system consisted of a single fiber optic cable with six FBG sensors embedded in a 36-ply fiberglass composite specimen. The FBG sensors were installed around a series of known engineered flaws. Six foil type resistive strain gauges were bonded to the composite specimen surface and co-located with the six embedded FBG sensors. The fiber optic interrogator was used to sample the FBG sensors and an independent data acquisition system was used to sample the foil strain gauges. The test specimen was subjected to a series of static loads and the results from both the foil strain gauges and the FBG sensors were compared. Results from the analysis show a good correlation between the embedded FBG sensors and the foil strain gauges.

A possible approach to meet the increasing performance requirements of lightweight structures in various engineering fields is the application of smart structures. One of the functions, which are required, is the observation of the structures' shape. During operation, however, the monitoring of displacement fields is difficult. This paper discusses the displacement field estimation of a dynamically excited plate using fiber Bragg grating strain sensors. Using a modal approach, it is possible to derive a transformation matrix to estimate the displacement field using only a few strain measurements. To reduce systematic estimation errors due to residual modes, a parameter study was performed and the sensor location optimized using the condition number of the transformation matrix as an objective function. An experiment with an optimized sensor configuration including 16 fiber Bragg grating strain sensors was performed to verify the method and the simulation results.

A total of 72 long-gage (2m long) optical fiber deformation sensors, along with 36 thermocouples were installed into one span of the five span high performance prestressed concrete I-10 Bridge over University in Las Cruces, NM. The sensors were installed along the bottom and top flanges, at mid-span and quarter spans. Pairs of crossed sensors in a rosette configuration were embedded in the webs at the supports. The embedded sensors measured temperature and deformations at the supports, quarter spans, and mid-span. Data was collected from beam fabrication, thru bridge construction and service. Collected data was analyzed to evaluate in-situ material properties, prestress losses and cambers in the girders. Actual losses and camber were compared to the losses and camber predicted using available code methods. The project was funded by the New Mexico DOT and the FHWA under the Innovative Bridge Research and Construction Program.

FRP-OFBG smart rebar is the smart structure material, which is the integration of good mechanical property and sensing performance. And FRP-OFBG rebar can be widely used in civil engineering health monitoring. But in the smart rebar application procedure, there is large residual strain exiting in FBG in smart rebar, and multiple-peaked to FBG reflection spectrum, which affect the sensing performance of smart rebar. In this paper, it's theoretically analyzed using FBG to measure the residual strain in FRP after fabrication; In smart rebar pultrusion fabrication processing, the strain and temperature were monitored by two connecting FBGs. It's analyzed FRP fabrication processing through monitoring data; To the multiple-peaked smart rebar, which caused by nonuniform residual strain distributing along FBG length, post thermal treatment was done. The result proved that thermal treatment can improve the spectrum of smart rebar and remove the multiple-peaked phenomenon of smart rebar. But the thermal treatment can't relief the residual strain, and further research about how long will the residual strain recovery at room temperature must be done.

One of the advantages of fiber optics with respect to traditional electrical gauges is they can act both as sensors and as a pathway for signals produced by other sensors. This feature allows adoption of a simple sensor system architecture, even when arrays of many sensors are needed. In this paper, we present the development and laboratory validation of in-line multiplexing for the low-coherence interferometric SOFO standard deformation sensor. A standard SOFO, as developed, produced and commercialized by Smartec SA, employs total reflectors at the end of the measurement and the reference fibers, allowing measurement of the strain over a single field. In the solution presented, broadband Fiber Bragg Gratings (FBGs) are employed as partial reflectors to obtain in-line multiplexing. These FBGs, presenting a 5% reflectivity in their reflection spectra, are produced using a chirped phase mask. An experiment was carried out on a 3-field sensor, to investigate effectiveness, resolution and temperature sensitivity. Outcomes show clear fringe visibility for each pair of gratings and a resolution of about 2.5 &mgr;m RMS, of the same order as the single field sensor. Issues regarding the maximum number of measurement fields on a single line and deformation range limits are discussed.

The development of smart sensors for structural health monitoring and damage detection has been advanced remarkably in recent years. Nowadays fiber optic sensors, especially fiber Bragg grating (FBG) sensors, have attracted many researchers' interest for their attractive features, such as multiplexing capability, durability, lightweight and electromagnetic interference immunity. In this paper, two damage detection approaches by dynamic strain measurements using FBG sensors are presented. They are the modal strain-flexibility and the modal strain energy methods. An experimental study was conducted to investigate the feasibility of the methods for damage detection and localization. It has been found that the strain-based approaches using dynamic strain measurements from FBG sensors can successfully detect and localize multiple small damages near the sensors. However, the damage detection range of the present short-gage FBG sensors seems rather narrow. Long-gage FBG sensors would be a possible solution.

A laser based fiber-optic sensor was proposed in our previous work. The sensor developed was based on the principle of scattering of light and the sensitivity directional property of optical fibers. A beam of light is incident on a surface or an edge, the scattered light is received by a linear array of optical fibers. The lateral position of the web edge is determined based on the intensity of light received by each fiber in the fiber array. Static experiments were conducted to show the feasibility of the sensing strategy. In this work, the performance of the sensor is evaluated on an actual web handling platform. The analysis of static and dynamic (with non-zero web transport velocity) experimental data of the sensor under various realistic operating conditions and disturbances is conducted. A direct comparison of the fiber optic sensor and two existing industrial sensors is presented. The experimental data from the sensors are compared using different web materials and under different operating conditions. The new fiber optic sensor is more accurate and the measurements are less noisy. Further, the new sensor overcomes some of the key limitations of existing sensors. The problem of determining the actual position of the web when it is completely outside the sensing window or when it completely covers the sensing windows is resolved; the solution consists of a new configuration. The new configuration also improves the precision of the sensor.

In this paper a new low cost, wireless unpowered sensor will be discussed that is designed to monitor the conductivity of concrete, which may provide information on the ingress of chloride ions during the life of the structure. A method of extracting temperature information from a previously developed corrosion sensor will also be presented. During a recent test, both a wireless corrosion sensor and a wireless conductivity sensor were placed in concrete and monitored throughout the duration of the curing process. Analysis of the data shows it is possible to determine temperature information based on the corrosion sensor response, allowing wireless in-situ temperature monitoring of the concrete during the cure. Monitoring curing temperature using the same sensor which would later be used for long-term corrosion detection would help reduce the cost of such a monitoring system.

The long-term reliability of a prototype, threshold corrosion sensor is demonstrated using data collected during an eighteen-month accelerated corrosion test. The sensors were embedded in reinforced concrete slabs, subjected to alternating wet/dry cycles, and interrogated periodically during the test. The frequency signature of the sensor changes after the steel sensing wire corrodes, providing a convenient and noninvasive technique for determining when a threshold amount of corrosion has occurred. The results indicate that the sensor data are reliable, but that some variability of readings should be expected due to the close tie between the presence of cracks in the concrete and the chloride levels, as the locations of the cracks are not known at the time that the sensors are embedded in the concrete.

The evaluation, health monitoring and response prediction of soil and soil-structure systems during construction and due to extreme hazard conditions are on the verge of a significant paradigm shift. New and less expensive sensing technologies have enabled the development of innovative instrumentation and advanced interactive modeling tools. These tools, combined with recent advances in information technology including wireless sensor networking, data mining, visualization and system identification, promise significant improvements in real time monitoring during construction, sensor-assisted design and early warning of impending failure. This paper presents the newly developed Wireless Shape-Acceleration Array (WSAA) sensor that measures multi-dimensional acceleration and deformation profiles and constitutes a major step toward autonomous monitoring technology for soil and soil-structure systems. The Wireless Shape-Acceleration Array (WSAA) sensor employs micro-machined electromechanical sensors (MEMS), which have enabled gravity-based shape calculation along a sensorized substrate. The method is an extension of technologies that use fiber optic orientation sensing to calculate 3D polylines representing the shape of a sensor array. WSAA uses MEMS accelerometers in a pre-calibrated, geometrically constrained array to provide long-term stability previously unattainable with fiber optic methods. This sensor array is capable of measuring 2D soil acceleration and 3D permanent ground deformations to a depth of one hundred meters. Each sensor array is connected to a wireless earth station to enable real time monitoring of a wide range of soil and soil-structure systems as well as remote sensor configuration. This paper presents the evolving design of this new sensor array as well as lessons learned from two field installations of this sensor.

This work addresses the development of a new four-noded rectangular Mindlin plate bending element (MP4C) with a crack which consists of three degrees of freedom at each corner node. The crack in the element is assumed to be not closed and non-propagating. The crack affects the elastic strain energy and the flexibility matrix of the element, whereas the mass matrix remains unchanged. The complete element stiffness matrix is constructed as the inverse of the combined flexibility matrix of both non-cracked and cracked elements. To evaluate the behavior of the proposed cracked Mindlin plate element, numerical examples are provided. They are based on developing user subroutines in the commercial finite element software ABAQUS. The finite element analysis results using the developed plate element are in excellent agreement with those reported in previous work. The cracked plate element developed in this paper provides a simple and robust approach to model the real service conditions in plate-like structures.

Crack detection with piezoelectric wafer active sensors (PWAS) is emerging as an effective and powerful technique in structural health monitoring (SHM). Modeling and simulation of PWAS and host structure play an important role in the SHM applications with PWAS. For decades finite element method has been extensively applied in the analysis of piezoelectric materials and structures. The advantage of finite element analysis over analytical solutions is that stress and electrical field measurements of complex geometries, and their variations throughout the device, are more readily calculated. FEM allows calculation of the stress and electric field distributions under static loads and under any applied electrical frequency, and so the effect of device geometry can be assessed and optimized without the need to manufacture and test numerous devices. Coupled field analysis taking both mechanical motions and electrical characteristics into account should all be employed to provide a systemic overview of the piezoelectric sensors/actuators (even arrays of them) and the host structures. This use of PWAS for SHM has followed two main paths: (a). Wave propagation (b). Electromechanical impedance; Previous research has shown that PWAS can detect damage using wave reflections, changes in wave signature, or changes in the electromechanical (E/M) impedance spectrum. The primary goal of this paper is to investigate the use of finite element method (FEM) to simulate various SHM methods with PWAS. For the simulation of Electro-mechanical (E/M) impedance technique, simple models, like free PWAS of different shapes and 1-dimmension beam with PWAS are investigated and the simulated structural E/M impedance was presented. For the wave propagation SHM technique, a long beam with several PWAS installed was studied. One PWAS is excited by tone burst signals and elastic wave will propagate along the beam. The existence of a crack will affect the structure integrity and the echo reflected by crack can be observed through the simulations. By using the coupled field elements, direct simulation of electro-mechanical interaction of the PWAS and the host structure was made possible. The electrical potential generated on the PWAS surface by the stimulation of elastic wave can be examined in our FEM analysis. The simulation results are then compared to analytical calculation and experimental data.

Cable-stayed bridges can exhibit large amplitude irregular stay cable oscillations under certain conditions of combined traffic flow and rain-wind loads that can pose severe risks to structural integrity. To investigate the mechanisms causing this behavior, a high fidelity nonlinear finite element model of a typical cable-stayed bridge has been developed using LS-DYNA based on the design of the Bill Emerson Memorial Bridge at Cape Girardeau, MO. The model uses over 540,000 finite elements representing 1254 bridge components to fully describe the detailed real geometry of the bridge tower, deck, stay cables, edge girders and floor-beam support girders. Traffic loads on the bridge deck are simulated by a Poisson Distributed Pulse (PDP) stochastic process model involving multi-lane traffic flows of more than 300 vehicles of various axle loads with varying arrival rates. The response data sets generated by the LS-DYNA simulations were then analyzed for chaotic behavior with the software CTBR. This extracts the nonlinear system invariants, the Lyapunov exponents, to identify the chaotic behavior from the dynamics of the structural system. The simulations showed positive Lyapunov exponents at various locations of the bridge deck and the bridge stay cable network. The analysis of these results revealed that even in the absence of strong rain-wind excitations the bridge deck vibration exhibits significant chaotic behavior that could excite the stay cables into a stronger chaotic regime, especially at the upper portion of the networked stay cables. This illustrates a phenomenon often ignored or unable to be captured by conventional linear dynamics analysis. Analysis of actual data sets collected from a monitoring network on the bridge also confirmed this chaotic behavior.

Long term structural health monitoring has become recognized as an important tool for ensuring the structural performance of our nation's cable-stayed bridges. However, this depends upon the establishment of a reliable base-line of structural condition at the early stage of the bridge's service life. The recent completion of the Bill Emerson Memorial Bridge at Cape Girardeau, MO, which included the installation of a network of seismic motion sensors, provides an opportunity to investigate the issues of creating such a base-line. Moreover, the availability of such a monitoring data set enables the evaluation of the possibility of inherent chaotic behavior in cable-stayed structures. This study analyzed the time series data sets collected from various locations along the bridge deck and tower of the Bill Emerson Bridge using CTBR, a Windows-based software application developed by Turner-Fairbank Highway Research Center of FHWA. This software automates the process of extracting the Lyapunov exponents, which are used to characterize the nonlinear dynamics of a structure. The analysis found one or more positive Lyapunov exponents, the signature of chaotic behavior, at various locations on the bridge deck. This phenomenon, resulting from ambient traffic loading rather than from wind and rain loading on the stays themselves, illustrates a mechanism that has been implicated in chaotic behavior of other cable stayed bridges. The analysis has thus revealed a previously unknown effect of chaotic deck motions that could couple into the stay cables. This research demonstrates that once the base-line chaotic systems have been identified it will be possible to track the values of the Lyapunov exponents over time to monitor the structural health of the bridge.

Luminescent photoelasticity is a new approach to measure mechanically induced strain 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. These characteristics can facilitate determining the principle strains and directions on complex geometries, without additional experimental or analytical techniques, by exploiting the angle dependent emission from multiple camera and/or illumination orientations. This paper presents a brief overview of the technique and a newly initiated research program sponsored by the NSF. Resulting advancements of the research are expected to integrate luminescence sensing for strain measurement into time-demanding product design cycles, validate complimentary computational methods, and provide a foundation to expand into critical need areas such as structural health monitoring in civil, automotive and aerodynamic applications.

Researchers at UCSD, with the initial support of NSF and the current support of the Federal Railroad Administration (FRA), have been working on a flaw detection prototype for rails that uses non-contact ultrasonic probing and robust data processing algorithms to provide high speed and high reliability defect detection in these structures. Besides the obvious advantages of non-contact probing, the prototype uses ultrasonic guided waves able to detect and quantify transverse cracks in the rail head, notoriously the most dangerous of all rail track defects. This paper will report on the first field test which was conducted in Gettysburg, PA in March 2006 with the technical support of ENSCO, Inc. Good results were obtained for the detection of both surface-breaking and internal cracks ranging in size from 2% cross-sectional head area (H.A.) reduction to 80% H.A. reduction.

The application of sensitivity vector fields (SVF) for tip-sample interactions in the context of multimode dynamics of atomic-force-microscopes (AFM) is presented. Analyzing sensitivity vector fields is a novel approach to determine simultaneous parameter variations of the system very accurately by exploiting the geometric features of observed chaotic dynamics. In certain operating condition, higher modes change the system dynamics significantly. Hence, higher order modes cannot be neglected. The paper demonstrates the accuracy of the SVF approach as applied to a multimode AFM model where mode shapes vary due to multiple variations of parameters.

This work describes the thermomechanical characterization and FEA modeling of commercial jet engine chevrons incorporating active Shape Memory Alloy (SMA) beam components. The reduction of community noise at airports generated during aircraft take-off has become a major research goal. Serrated aerodynamic devices along the trailing edge of a jet engine primary and secondary exhaust nozzle, known as chevrons, have been shown to greatly reduce jet noise by encouraging advantageous mixing of the streams. To achieve the noise reduction, the secondary exhaust nozzle chevrons are typically immersed into the fan flow which results in drag, or thrust losses during cruise. SMA materials have been applied to this problem of jet engine noise. Active chevrons, utilizing SMA components, have been developed and tested to create maximum deflection during takeoff and landing while minimizing deflection into the flow during the remainder of flight, increasing efficiency. Boeing has flight tested one Variable Geometry Chevron (VGC) system which includes active SMA beams encased in a composite structure with a complex 3-D configuration. The SMA beams, when activated, induce the necessary bending forces on the chevron structure to deflect it into the fan flow and reduce noise. The SMA composition chosen for the fabrication of these beams is a Ni60Ti40 (wt%) alloy. In order to calibrate the material parameters of the constitutive SMA model, various thermomechanical experiments are performed on trained (stabilized) standard SMA tensile specimens. Primary among these tests are thermal cycles at various constant stress levels. Material properties for the shape memory alloy components are derived from this tensile experimentation. Using this data, a 3-D FEA implementation of a phenomenological SMA model is calibrated and used to analyze the response of the chevron. The primary focus of this work is the full 3-D modeling of the active chevron system behavior by considering the SMA beams as fastened to the elastic chevron structure. Experimental and numerical results are compared. Discussion is focused on actuation properties such as tip deflection and chevron bending profile. The model proves to be an accurate tool for predicting the mechanical response of such a system subject to defined thermal inputs.

There are numerous engineering applications where there is a need to transfer power and communication data thru the walls of a structure. A piezoelectric acoustic-electric power feedthru system was developed in this reported study allowing for wireless transfer of electric power through a metallic wall using elastic waves. The technology is applicable to the transfer of power for actuation, sensing and other tasks inside sealed containers and vacuum/pressure vessels. A network equivalent circuit including material damping loss was developed to analyze the performance of the devices. Experimental test devices were constructed and tested. The power transfer capability and the transfer efficiency were measured. A 100W feed though capability with 38 mm diameter device and 88% transmission efficiency were demonstrated. Both analytical and experimental results are presented and discussed in this paper.

A new class of vibrational energy harvester based on Magnetostrictive material (MsM) Metglas 2605SC is deigned, developed, and tested in building practical energy harvesting wireless sensor networks. Compared to piezoelectric material, Metglas 2605SC offers advantages including ultra-high energy conversion efficiency, high power density, longer life cycles without depolarization issue, and flexibility to operate in strong ambient vibrations. To enhance the energy conversion efficiency and shrink the size of the harvester, Metglas is annealed in the direction normal to the axial strain direction without the need of electromagnet for applying bias (static) magnetic field. To seamlessly integrate with a newly developed wireless sensor at NC State¹, a prototype design for the MsM harvester is proposed. An analytical model is developed for the harvesting using an equivalent electromechanical circuit. The model resulting in achievable output performances of the harvester powering a resistive load and charging a capacitive energy storage device, respectively, is quantitatively derived. An energy harvesting module, which powers a wireless sensor, stores excess energy in an ultracapacitor is designed on a printed circuit board (PCB) with dimension 25mm x 35mm. The main functionalities of the circuit include a voltage quadrupler, a 3F ultracapacitor, and a smart regulator. The output DC voltage from the PCB can be adjusted within 2.0~5.5V. In experiments, the maximum output power and power density on the resistor can reach 200 &mgr;W and 900 &mgr;W/cm³, respectively. For a working prototype, the average power and power density during charging the ultracapacitor can achieve 576 &mgr;W and 606 &mgr;W/cm³ respectively, which are much higher than those of most piezo-based harvesters.

Piezoelectric acoustic-electric power feedthru devices that are able to transfer electric power through metallic/ferromagnetic wall are investigated. Electric energy is converted to acoustic energy by piezoelectric transducer at one side of the wall. The acoustic wave propagates through the wall and, then, it is converted back to electric energy by another transducer on the other side. For high efficient transmission, it is critical that all the energy loss should be minimized. In addition to the electrical, mechanical and electromechanical loss in the transducers and the thickness of the wall, Lamb (plate) waves are excited by the transducers in the wall and they also result in energy losses. In this study, the energy loss caused by the Lamb waves are analyzed analytically and by finite element simulations. The results and the methods to reduce the loss are presented and discussed in this presentation.

The computational and wireless communication capabilities of smart sensors densely distributed over structures can provide rich information for structural monitoring. While smart sensor technology has seen substantial advances during recent years, interdisciplinary efforts to address issues in sensors, networks, and application specific algorithms are needed to realize their potential. This paper first discusses each of these issues, and then reports on research that combines the results to develop a structural health monitoring (SHM) system suitable for implementation on a network of smart sensors. Experimental verification is provided using Intel's Imote2 smart sensors installed on a threedimensional truss structure. The Imote2 is employed herein because it has the high computational and wireless communication performance required for advanced SHM applications. This SHM system is then investigated from sensing, network, and SHM algorithm perspectives.

This study examines the potential use of wireless communication and embedded computing technologies within realtime structural control applications. Based on the implementation of the prototype WiSSCon system in a three story steel test structure with significant eccentricity, the centralized control architecture is implemented to mitigate the lateral and torsional response of the test structure using two MR dampers installed in the first story. During the test, a large earthquake time history is applied (El Centro earthquake) at the structure base using a shaking table. Three major performance attributes of the wireless control system were examined: (1) validation of the reliability of wireless communications for real-time structural control applications, (2) validation of a modified exponential damper model embedded in the wireless sensors to operate the MR dampers, and (3) exploration of control effectiveness when using WiSSCon in a centralized architectural configuration.