This PDF file contains the front matter associated with SPIE Proceedings Volume 7647, including the Title Page, Copyright information, Table of Contents, the Conference Committee listing and introduction.

This paper examines the feasibility of embedding wireless sensors into concrete for structural health monitoring. Wireless sensors (motes) with temperature and humidity measurement capabilities were designed with onboard communication using the 433 MHz ISM band and embedded into concrete. A package was designed to protect the sensor from the aggressive environment within concrete. The effect of the package on the response time and accuracy of the sensor was quantified in a humidity chamber. Testing was carried out on the sensors which replicated on site conditions, to determine what the effect of the concrete itself, the steel reinforcement, and steel backed formwork had on the transmission of data. The transmission distance and reliability of receiving data was quantified. Test results suggest that it is possible to deploy an embedded sensor system and transmit live data from the embedded sensor to a data acquisition system located outside the concrete. Preliminary results show that steel backed formwork reduces the transmission distance of the sensors to 3.5m which extended to 7.5m when the formwork was removed. A temperature and moisture sensor applied to the mote gave an indication of the ability of the sensor to transfer live data from within the concrete. It was found that the temperature sensor accurately followed the temperature profile of the concrete when compared to a thermocouple.

State-of-the-art wireless smart sensor technology enables a dense array of sensors to be distributed through a structure to provide an abundance of structural information. However, the relatively low resolution of the MEMS sensors that are generally adopted for wireless smart sensors limits the network's ability to measure lowlevel vibration often found in the ambient vibration response of building structures. To address this problem, development of a high-sensitivity acceleration board for the Imote2 platform using a low-noise accelerometer is presented. The performance of this new sensor board is validated through extensive laboratory testing. In addition, the use of the high-sensitivity accelerometer board as a reference sensor to improve the capability to capture structural behavior in the smart sensor network is discussed.

This paper presents a structural health monitoring (SHM) system using a dense array of scalable smart wireless sensor network on a cable-stayed bridge (Jindo Bridge) in Korea. The hardware and software for the SHM system and its components are developed for low-cost, efficient, and autonomous monitoring of the bridge. 70 sensors and two base station computers have been deployed to monitor the bridge using an autonomous SHM application with consideration of harsh outdoor surroundings. The performance of the system has been evaluated in terms of hardware durability, software reliability, and power consumption. 3-D modal properties were extracted from the measured 3-axis vibration data using output-only modal identification methods. Tension forces of 4 different lengths of stay-cables were derived from the ambient vibration data on the cables. For the integrity assessment of the structure, multi-scale subspace system identification method is now under development using a neural network technique based on the local mode shapes and the cable tensions.

Research was conducted using simulated civil infrastructure system conditions to evaluate issues pertaining to signal strength. This research evaluated the performance of the wireless MICA2 sensor motes developed by Crossbow Technology, Inc. The data collected is intended to demonstrate how the motes would perform in a typical civil infrastructure application when placed in a large network of sensors. Specific to signal strength, the strength, quality, and reliability of the signal originating from remote sensor was assessed as a function of its distance from the Gateway Sensor. These experiments encompassed several factors that relate to signal strength and distance such as single motes, multiple motes, single hop, and multi-hop. Experimentation was also performed to evaluate the mote performance for buried applications. The results of the experimentation show that in all cases the quality, reliability and strength of the transmitting signal is a function the distance of the Gateway Sensor from the obstruction and the amount of signal scattering caused by the material surrounding the mote.

Recently, an adaptive extended Kalman filter (AEKF) approach has been proposed for the damage identification and tracking of structures. Simulation and experimental studies have demonstrated that this AEKF approach is capable of tracking the damages for linear structures. In this paper, an experimental study is conducted and presented to verify the capability of the adaptive extended Kalman filter (AEKF) approach for identifying and tracking the damages in nonlinear structures. A base-isolated building model, consisting of a scaled building model mounted on a rubber-bearing isolation system, has been tested experimentally in the laboratory. The non-linear behavior of the base isolators is modeled by the Bouc-Wen model. To simulate the structural damages during the test, an innovative device, referred to as the stiffness element device (SED), is proposed to reduce the stiffness of either the upper story of the structure or the base isolator. Two earthquake excitations have been used to drive the test model, including the El Centro and Kobe earthquakes. Various damage scenarios have been simulated and tested. Measured acceleration response data and the AEKF approach are used to track the variation of the stiffness during the test. The tracking results for the stiffness variations correlate well with that of the referenced values. It is concluded that the AEKF approach is capable of tracking the variation of structural parameters leading to the detection of structural damages.

An objective of the structural health monitoring system is to identify the state of the structure and to detect the damage when it occurs. Analysis techniques for the damage identification of structures, based on vibration data measured from sensors, have received considerable attention. Recently, a new damage tracking technique, referred to as the adaptive quadratic sum-square error (AQSSE) technique, has been proposed, and simulation studies demonstrated that the AQSSE technique is quite effective in identifying structural damages. In this paper, the adaptive quadratic sumsquare error (AQSSE) along with the reduced-order finite-element method is proposed to identify the damages of complex structures. Experimental tests were conducted to verify the capability of the proposed damage detection approach. A series of experimental tests were performed using a scaled cantilever beam subject to the white noise and sinusoidal excitations. The capability of the proposed reduced-order finite-element based adaptive quadratic sum-square error (AQSSE) method in detecting the structural damage is demonstrated by the experimental results.

Impedance-based damage detection using the magnetic transducer, which is referred to as the magnetic impedance approach, is recently under investigation. In an earlier work we have demonstrated that integrating a synthetic, tunable negative resistance and a tunable capacitor with the magnetic transducer can amplify both the admittance measurement magnitude and the damaged-induced admittance anomaly, and thus have much higher signal-to-noise ratio and higher detection sensitivity than the conventional approach. In this research, we investigate further enhancing the magnetic impedance approach with circuitry integration by systematically studying how the design parameters of the transducer affect the magneto-mechanical coupling. It is demonstrated the magneto-mechanical coupling parameter, which is developed excluding the circuitry parameters and structural properties, is capable of quantifying the dynamic coupling effect under various transducer design parameters, leading to the guidelines for the optimal design and configuration of the new sensing scheme. Extensive numerical and experimental studies are carried out to analyze the parametric influences.

We conducted the delamination detect test for composites plate using the Brillouin optical correlation domain analysis (BOCDA) method. Firstly, a hole-assisted-fiber was chosen for embedding optical fiber sensor in order to avoid the increase of optical transmission loss induced by embedded into composite plate. The hole-assisted-fiber is functional better than comparing with the telecommunication optical fibers when optical fiber sensor was embedded into composite. Secondly, a delamination propagating was detected by the BOCDA from Brillouin peak frequency distribution and Brillouin gain spectrum shape changes.

Varying loading conditions of aircraft structures result in stress concentration at fastener holes, where multi layer components are connected, possibly leading to the development of fatigue cracks. Guided ultrasonic waves propagating along a structure allow in principle for the efficient non-destructive testing of large plate-like structures, such as aircraft wings. This contribution presents a study of the detection and monitoring of fatigue crack growth using both low frequency and higher frequency guided ultrasonic wave modes. Two types of structures were used, single layer aluminum tensile specimens, and multi layer structures consisting of two adhesively bonded aluminum plate-strips. Fatigue experiments were carried out and it was shown that fatigue crack detection and growth monitoring at a fastener hole during cyclic loading using both guided wave types is possible. The sensitivity and repeatability of the measurements were ascertained, having the potential for fatigue crack detection at critical and difficult to access fastener locations. Good agreement was observed between the experimental results and predictions from full three-dimensional numerical simulations of the scattering of the low frequency guided ultrasonic wave at the fastener hole and crack. The robustness of the methodology for practical in-situ ultrasonic monitoring of fatigue crack growth is discussed.

Compared with traditional microprocessor-based systems, rapidly advancing field-programmable gate array (FPGA) technology offers a more powerful, efficient and flexible hardware platform. An FPGA and microprocessor (i.e., hardware and software) co-design is developed to classify three types of nonlinearities (including linear, hardening and softening) of a single-degree-of-freedom (SDOF) system subjected to free vibration. This significantly advances the team's previous work on using FPGAs for wireless structural health monitoring. The classification is achieved by embedding two important algorithms - empirical mode decomposition (EMD) and backbone curve analysis. Design considerations to embed EMD in FPGA and microprocessor are discussed. In particular, the implementation of cubic spline fitting and the challenges encountered using both hardware and software environments are discussed. The backbone curve technique is fully implemented within the FPGA hardware and used to extract instantaneous characteristics from the uniformly distributed data sets produced by the EMD algorithm as presented in a previous SPIE conference by the team. An off-the-shelf high-level abstraction tool along with the MATLAB/Simulink environment is utilized to manage the overall FPGA and microprocessor co-design. Given the limited computational resources of an embedded system, we strive for a balance between the maximization of computational efficiency and minimization of resource utilization. The value of this study lies well beyond merely programming existing algorithms in hardware and software. Among others, extensive and intensive judgment is exercised involving experiences and insights with these algorithms, which renders processed instantaneous characteristics of the signals that are well-suited for wireless transmission.

The load transfer and shaft capacities of civil infrastructure foundations (e.g., axially-loaded piles) depend on the soilstructure interface's shear and friction interactions. However, cyclic loading (e.g., ground motion) can dramatically deteriorate the shaft resistance of these foundations leading to catastrophic structural failure, thereby motivating research in understanding mechanics, soil-structure interactions, and interface responses. While tethered sensing systems have been adopted for gaining insight on soil-structure interfaces, the cables that interconnect sensors with the data acquisition system can interfere with measurement of true soil-structure response. Thus, the objective of this study is to develop a passive wireless sensor that is capable of measuring absolute displacement of soil particles at the soil-structure interface. Wireless communications and power transmission to the sensor is accomplished via electromagnetic coupling between a portable reader and sensor tag. Here, the reader is simply a coil antenna connected to an impedance analyzer, and the sensor circuitry comprises of a resistor, inductor (i.e., coil antenna), and capacitor connected in a series configuration. The displacement of the embedded sensor can be easily measured by correlating reader impedance changes with the reader-to-sensor's line-of-sight distances. Preliminary experimental results of the passive wireless sensor's displacement measurement capabilities are presented.

The objective of this paper is to upgrade a wireless sensing unit which can meet the following requirements: 1) Improvement of system powering and analog signal processing 2) Enhancement of signal resolution and provide reliable wireless communication data, 3) Enhance capability for continuous long-term monitoring. Based on the prototype of the wireless sensing unit developed by Prof. Lynch at the Stanford University, the following upgrading steps are summarized: 1. Reduce system noise by using SMD passive elements and preventing the coupling digital and analog circuits, and increasing the capacity of power. 2. Improve the ADC sampling resolution and accuracy with a higher resolution Analog-to-Digital Converter (ADC): a 24bits ADC with programmable gain amplifier. 3. Improve wireless communication by using the wireless radio 9XTend which supported by the router (Digi MESH) communication function using 900MHz frequency band. Based on the upgrade wireless sensing unit, verification of the new wireless sensing unit was conducted from the ambient vibration survey of a base-isolated building. This new upgrade wireless sensing unit can provide more reliable data for continuous structural health monitoring. Incorporated with the identification software (modified stochastic subspace identification method) the smart sensing system for SHM is developed.

Guided waves based nondestructive testing (NDT) techniques have attracted many researchers' attentions for structural health monitoring due to their relative long sensing range. These guided waves in a structure can be generated and sensed by a variety of techniques. This study proposes a new wireless scheme for PZT excitation and sensing, where power as well as measured data can be transmitted via laser. First, a generated waveform modulated by a laser is wirelessly transmitted to a photodiode connected to a PZT on the structures. Then, the photodiode converts the light into an electrical signal and excites the PZT and the structure. The reflected response signal received at the same PZT is reconverted into a laser, which is transmitted back to another photodiode located at the data acquisition unit for diagnosis. The feasibility of the proposed power transmission scheme has been experimentally demonstrated at a laboratory setup. The wireless data transmission aspect is under verification. Since there is no need for a power supply and a signal generator at the PZT transducer node, a self-sufficient PZT transducer unit can be realized with little additional electronic components.

Application of wireless sensor network (WSN) for structural health monitoring (SHM), is becoming widespread due to its implementation ease and economic advantage over traditional sensor networks. Beside advantages that have made wireless network preferable, there are some concerns regarding their performance in some applications. In long-span Bridge monitoring the need to transfer data over long distance causes some challenges in design of WSN platforms. Due to the geometry of bridge structures, using multi-hop data transfer between remote nodes and base station is essential. This paper focuses on the performances of pipelining algorithms. We summarize several prevent pipelining approaches, discuss their performances, and propose a new pipelining algorithm, which gives consideration to both boosting of channel usage and the simplicity in deployment.

The continued development of renewable energy resources is for the nation to limit its carbon footprint and to enjoy independence in energy production. Key to that effort are reliable generators of renewable energy sources that are economically competitive with legacy sources. In the area of wind energy, a major contributor to the cost of implementation is large uncertainty regarding the condition of wind turbines in the field due to lack of information about loading, dynamic response, and fatigue life of the structure expended. Under favorable circumstances, this uncertainty leads to overly conservative designs and maintenance schedules. Under unfavorable circumstances, it leads to inadequate maintenance schedules, damage to electrical systems, or even structural failure. Low-cost wireless sensors can provide more certainty for stakeholders by measuring the dynamic response of the structure to loading, estimating the fatigue state of the structure, and extracting loading information from the structural response without the need of an upwind instrumentation tower. This study presents a method for using wireless sensor networks to estimate the spectral properties of a wind turbine tower loading based on its measured response and some rudimentary knowledge of its structure. Structural parameters are estimated via model-updating in the frequency domain to produce an identification of the system. The updated structural model and the measured output spectra are then used to estimate the input spectra. Laboratory results are presented indicating accurate load characterization.

Motivated by the preservation of an artistic treasure, the fresco of the "Cycle of the Months" on the second floor in an historic tower, Torre Aquila, a wireless sensor network (WSN) has been developed and installed for permanent health monitoring. The monitoring scheme covers both static and dynamic evaluation of the tower structural integrity from local to global scale and consists of 17 nodes, including 2 long length fiber optic sensors (FOS), 3 accelerometers and 12 environmental nodes. The system has been working for 1.5 years and has been debugged and updated both as to hardware and software. This paper focuses mainly on the ambient vibration analysis used to investigate the performance of the sensor nodes and structural properties of the tower. Initial ambient vibration monitoring shows that cyclic environmental factors, such as traffic flow, are not the dominant cause of tower vibration; and the vibration levels of the tower in different axes are not large enough to be a critical issue calling for attention under current conditions. It proves that the WSN is an effective tool, capable of providing information relevant to safety assessment of the tower.

Conventionally, rehabilitation treatments for gait disorders are performed by physical therapists in a clinical setting. Although an array of equipment, such as motion capture devices and multi-directional force plates, has been devised to provide the physical therapists with more objective diagnostic data, restriction of the time and space limits the effective use of such devices. To overcome this limitation various wearable sensors for patients to directly monitor their health conditions anywhere at anytime have been studied in recent years. In this paper, a mobile gait monitoring system (MGMS) is introduced, which integrates Smart Shoes and the monitoring algorithms in a mobile microprocessor with a touch screen display. The mobility of the MGMS allows patients to take advantage of the gait monitoring device in their daily lives. The monitoring algorithms embedded in the MGMS observe various physical quantities useful for objective gait diagnoses, such as the ground contact forces (GCFs) and the center of ground contact forces (CoGCF). Also it calculates the gait abnormality which shows how far the GCFs are from the normal GCF patterns. By the visual feedback information displayed on the MGMS, the patients can self correct their walking patterns. The preliminary results of clinical verification are also given.

Modal analysis is a well developed field with many applications. The multi-output approaches in particular are well suited for system identification and online damage detection because they use the natural excitations the system undergoes in its normal operation. In this work two multi-output approaches are analyzed, compared, and improved upon. The first method is smooth orthogonal decomposition (SOD). SOD was originally developed as a tool for detecting features of chaotic dynamical systems. Recently, it has been used as a time-based multioutput modal analysis approach. SOD has been demonstrated effectively for the free vibration case and for random excitations. The second method is direct system parameter identification (DSPI). DSPI was developed as a time-based multi-input multi-output modal analysis approach. When the inputs are not measured DSPI can handle the free vibration case and random excitations like SOD. If the inputs are measured then DSPI works with arbitrary excitations. In addition to comparing SOD and DSPI, novel filtering algorithms are introduced to improve each method's performance when working with noisy data. Numerical simulations are carried out to compare the two methods and demonstrate the effectiveness of the filtering algorithms in improving frequency and mode shape extraction.

In this work we consider the effects of noise on system behavior during parameter sweeps through bifurcations that induce sharp jumps in response amplitudes. These problems arise in a variety of applications, including the use of bifurcation amplification in micro-sensors. Due to inherent system noise, the observed bifurcation events are stochastic in nature and one must estimate parameter values from a distribution. A stochastic dynamical systems analysis allows one to distill the problem to a one-dimensional, one-parameter Fokker-Planck equation, where the parameter is the ratio of the noise intensity to sweep rate. Approximate closed form solutions for the distributions are obtained in the limits of slow and fast parameter sweep rates, and a numeric solution captures the intermediate sweep range that bridges these two approximations. These results are essential for quantifying errors in bifurcation amplifiers and for optimizing bifurcation detection schemes, as used in sensing applications. Preliminary experimental results for a parametrically excited microdevice show good qualitative agreement with the theory.

When using microphone array for sound source localization, the most fundamental step is to estimate the time difference of arrival (TDOA) between different microphones. Since TDOA is proportional to the microphone separation, the localization performance degrades with decreasing size relative to the sound wavelength. To address the size constraint of conventional directional microphones, a new approach is sought by utilizing the mechanical coupling mechanism found in the superacute ears of the parasitic fly Ormia ochracea. Previously, we have presented a novel bio-inspired directional microphone consisting of two circular clamped membranes structurally coupled by a center pivoted bridge, and demonstrated both theoretically and experimentally that the fly ear mechanism is replicable in a man-made structure. The emphasis of this article is on theoretical analysis of the thermal noise floor of the bio-inspired directional microphones. Using an equivalent two degrees-of-freedom model, the mechanical-thermal noise limit of the structurally coupled microphone is estimated and compared with those obtained for a single omni-directional microphone and a conventional microphone pair. Parametric studies are also conducted to investigate the effects of key normalized parameters on the noise floor and the signal-to-noise ratio (SNR).

This contribution is concerned with adaptive damping of plate-like structures equipped with a piezoelectric patch. Damping of mechanical modes can be accomplished by connecting simple electrical impedances at the terminals of the piezoelectric patch. For reason of miniaturization and robustness with respect to a shift in eigenfrequencies of the mechanical structure, the authors propose the algorithmic implementation of the electrical behavior of the impedance on a microcontroller. The digital approach enables real time updating of parameters associated with the artificial electrical impedance. The problem of finding optimal parameters is addressed and an update law for online tuning of parameters is introduced. The performance of the algorithm is evaluated on the mathematical model of a Kirchhoff plate equipped with a piezoelectric patch shunted by a resistor.

Structural health monitoring (SHM) techniques based on guided waves have been of great interests to many researchers. Among various SHM devices used for guided wave generation and sensing, lead zirconate titanate (PZT) transducers and fiber Bragg grating (FBG) sensors have been widely used because of their light weight, non-intrusive nature and compactness. To best take advantage of their merits, combination of PZT-based guided wave excitation and FBG-based sensing has been attempted by a few researchers. However, the PZT-based actuation and the FBG-based sensing are basically two independent systems in the past studies. This study proposes an integrated PZT/FBG system using a single laser source. Since power and data delivery is based on optical fibers, it may alleviate problems associated with conventional wire cables such as electromagnetic interference (EMI) and power/data attenuation. The experimental procedure for the proposed system is as follows. First, a tunable laser is used as the common power source for guided wave generation and sensing. The tunable laser beam is modulated and amplified to contain an arbitrary waveform. Then, it is transmitted to the PZT transducer node through an optical fiber for guided wave actuation. The transmitted laser beam is also used with the FBG sensor to measure high-speed strain changes induced by guided waves. Feasibility of the proposed technique has been experimentally demonstrated using aluminum plates. The results show that the proposed system could properly generate and sense the guided waves compared to the conventional methods.

This paper describes the generation and propagation of highly nonlinear solitary waves (HNSWs) in a chain of steel beads excited by means of laser pulses. Ablative generation of mechanical stress was induced on the bead at one end of the chain in order to enhance the amplitude of the stress waves generated. Compared to the use of a mechanical striker, the laser-based generation of stress waves is fully non-contact and allows for the broadest energy spectrum. In this study the amplitude, duration, and velocity of the solitary waves propagating along the chain of beads as a function of the laser pulse energy is investigated. Moreover the application of HNSW as a pulse generator for the NDE of bulk structures is shown.

The use of magnetic nanparticles in microfluidic systems is emerging and is receiving growing attention due to the synergistic advantages of microfluidics and magnetic nanoparticles. Biomagnetic separation techniques based on magnetic nanoparticles are becoming increasingly important with a wide range of possible applications. However, the separation products are difficult to be detected by general method due to the small size of MNPs. Here, we demonstrate magnetic nanoparticles can greatly enhance the signal of surface plasmon resonance spectroscopy (SPR). Features of MNPs-aptamer conjugates as a powerful amplification reagent for ultrasensitive immunoassay are explored for the first time. Our results confirm that MNPs is a powerful sandwich element and an excellent amplification reagent for SPR based sandwich immunoassay and SPR has a great potential for the detection of magnetic nanoparticles-based separation products.

This paper summarizes our recent research progresses in developing optical fiber harsh environment sensors for various high temperature harsh environment sensing applications such as monitoring of the operating conditions in a coal-fired power plant and in-situ detection of key gas components in coal-derived syngas. The sensors described in this paper include a miniaturized inline fiber Fabry-Perot interferometer (FPI) fabricated by one-step fs laser micromachining, a long period fiber grating (LPFG) and a fiber inline core-cladding mode interferometer (CMMI) fabricated by controlled CO₂ laser irradiations. Their operating principles, fabrication methods, and applications for measurement of various physical and chemical parameters in a high temperature and high pressure coexisting harsh environment are presented.

Micro-sensors are highly desired for on-line temperature/pressure monitoring in turbine engines to improve their efficiency and reduce pollution. The biggest challenge for developing this type of sensors is that the sensors have to sustain at extreme environments in turbine engine environments, such as high-temperatures (>800 °C), fluctuated pressure and oxidation/corrosion surroundings. In this paper, we describe a class of sensors made of polymer-derived ceramics (PDCs) for such applications. PDCs have the following advantages over conventional ceramics, making them particularly suitable for these applications: (i) micromachining capability, (ii) tunable electric properties, and (iii) hightemperature capability. Here, we will discuss the materials and their properties in terms of their applications for hightemperature micro-sensors, and microfabrication technologies. In addition, we will also discuss the design of a heat-flux sensor based on polymer-derived ceramics.

Galfenol is an iron-gallium alloy that exhibits magnetostrictive behavior up to approximately 350 ppm. It has been shown that Galfenol exhibits a linear response in strain that follows commercially available strain gauges when a magnetic bias field is placed near the Galfenol patch in a bending test. In this study we extend these results to use of a Galfenol patch for measuring torque. The benefits of Galfenol-based torque sensors over existing strain sensors for measuring torque are (1) the potential for use of stray magnetic fields for non-contact torque measurement; (2) ease of integration and/or retrofit of the proposed torque measuring capability into existing hardware; and (3) an inexpensive yet mechanically robust alternative to torque sensors that require slip rings or wireless signal transmission. This research will show that when placed on a circular shaft at ± 45o relative to the shaft axis, Galfenol will exhibit a linear response to shear strain produced when a torque is applied to the shaft. By showing that measurement of shear strain is possible it is evident that the torque on the shaft can also be determined. A Hall Effect sensor will be rigidly attached to a non-rotating component of the measurement frame supporting the shaft, and used to determine the change in the magnetic field above the patch. While the shaft is rotating the response from the Hall Effect sensor is monitored to determine the torque load on the shaft.

The aging infrastructure requires a proactive strategy to ensure their functionality and performance. Innovative sensors are needed to develop infrastructures that are intelligent and adaptive. A power supply strategy is among the crucial components to reduce the instrument cost and to ensure the long term function of these embedded sensors. This paper introduces the results of a preliminary study on using thermo-electricity generation to power sensors. This presents an innovative strategy for long term monitoring of pavement performance.

A new kind of smart fiber reinforced polymer (FRP)-concrete composite bridge superstructure, which consists of two bridge decks and each bridge deck is comprised of four FRP box sections combined with a thin layer of concrete in the compression zone, was developed by using eight embedded FBG sensors in the top and bottom flanges of the FRP box sections at mid-span section of one bridge deck along longitudinal direction, respectively. The flexural behavior of the proposed smart composite bridge superstructure was experimentally studied in four-point loading. The longitudinal strains of the composite bridge superstructure were recorded using the embedded FBG sensors as well as the surfacebonded electric resistance strain gauges. Test results indicate that the FBG sensors can faithfully record the longitudinal strain of the composite bridge superstructure in tension at bottom flange of the FRP box sections or in compression at top flange over the entire loading range, as compared with the surface-bonded strain gauges. The proposed smart FRPconcrete composite bridge superstructure can monitor its longitudinal strains in serviceability limit state as well as in strength limit state, and will has wide applications for long-term monitoring in civil engineering.

A study was carried out to assess the possibility of monitoring of joint angles, foot posture and foot motion through the use of conductive polymer sensors. The sensors are composed of a carbon polymer coating on an elastic fabric and they behave like strain gauges. A mechanically driven hinge was used to simulate joint motion by generating an angle change between its wings. A sensor strip was clamped longitudinally across the hinge in order for it to stretch when the angle between the wings increases. An electrogoniometer was used to monitor the angle spanned by the two wings of the hinge. Series of simultaneous measurements of angle and resistance were conducted at different speeds. Results indicate that a unique rate of change of voltage can be assigned to a specific angular velocity. This idea allows the tabulation of a database of voltages and time derivatives of voltages with corresponding angles and angular velocities. Angular velocity information was obtained by computing the derivatives of sensor output voltages in real time and comparing both voltage and their time derivatives to values in the database, with linear interpolation used as necessary. Angular displacement was then obtained by numerically integrating velocity information. Three carbon sensors were then applied on socks and were placed on different locations of maximum strain on the foot. Wireless data transmission was added in order to enable unhindered foot motion for future applications.

In order to take full advantages of composites and enable future composite structures to operate at their physical limits rather than limits predetermined from computational design assumptions and safety factors, there is a need to develop an embeddable sensing system to allow a structure to "feel" and "think" its structural state. In this paper, the concept of multi-modal sensing capabilities using a network of multifunctional sensors integrated with a structure has been developed. Utilizing this revolutionary concept, future structures can be designed and manufactured to provide multiple modes of information that when synthesized together can provide capabilities for intelligent sensing, environmental adaptation and multi-functionality. To demonstrate the feasibility of multi-modal sensing capabilities with built-in sensor network, one single type of piezoelectric sensor was selected to perform the measurements of dynamic strain, temperature, damage detection and impact monitoring. The uniqueness of the sensing system includes (1) Flexible, multifunctional sensor networks for integration with any type of composite structural component, (2) Scalable sensor network for monitoring of a large composite structure, (3) Reduced number of connecting wires for sensors, (4) Hybrid diagnostics with multiple sensing capabilities, (5) Sensor network self-diagnostics and self-repair for damaged sensor system.

In this paper application of integrated Optical Fiber Sensors for strain state monitoring of composite high pressure vessels is presented. The composite tanks find broad application in areas such as: automotive industry, aeronautics, rescue services, etc. In automotive application they are mainly used for gaseous fuels storage (like CNG or compressed Hydrogen). In comparison with standard steel vessels, composite ones have many advantages (i.e. high mechanical strength, significant weight reduction, etc). In the present work a novel technique of vessel manufacturing, according to this construction, was applied. It is called braiding technique, and can be used as an alternative to the winding method. During braiding process, between GFRC layers, two types of optical fiber sensors were installed: point sensors in the form of FBGs as well as interferometric sensors with long measuring arms (SOFO®). Integrated optical fiber sensors create the nervous system of the pressure vessel and are used for its structural health monitoring. OFS register deformation areas and detect construction damages in their early stage (ensure a high safety level for users). Applied sensor system also ensured a possibility of strain state monitoring even during the vessel manufacturing process. However the main application of OFS based monitoring system is to detect defects in the composite structure. An idea of such a SMART vessel with integrated sensor system as well as an algorithm of defect detection was presented.

Mass deposition changes resonance frequencies of structures. Resonator sensitivity, defined as a fraction of change in frequency per unit deposited mass, is found for microcantilever sensors electrostatically actuated to include fringe and Casimir effects. These actuation forces produce nonlinear parametric oscillations. Constant thickness mass deposition on all four lateral surfaces of the cantilever of rectangular cross-section was assumed. The Euler-Bernoulli theory was used under the assumption that the beams are slender. Mass deposition on the free end surface of the cantilever was neglected. The deposition thickness was considered uniform and very small compared to any beam dimension. The deposited mass had no contribution to the stiffness, only to the mass. Analytical expression of the sensitivity of electrostatically actuated uniform microcantilever resonators sensor near natural frequency is determined.

A new rotational magnetomechanical transducer network model for a magnetostrictive unimorph is presented. Often these laminated structures define an operating point about which the mechanical, magnetic and electrical quantities show only small variations and the behavior can be decribed by a linear model. It is shown how the magnetomechanical transduction coefficient in actuation direction, which is obtained via classical laminated plate theory, holds also for the sensing relation. The magnetomechanical model is combined with electromagnetic coil models. The electromagnetic and the magnetomechanical transducer are connected by a magnetic voltage divider which takes demagnetization or the planar coil field distribution into account. The presented models can be used for a fast analysis of existing systems and also for the optimization of new designs. The resulting circuit description can be simplified, e.g. to a single impedance, by transforming network elements into other domains.

Piezoceramic based transducers are widely researched and used for structural health monitoring (SHM) systems due to the piezoceramic material's inherent advantage of dual sensing and actuation. Wireless sensor network (WSN) technology benefits from advances made in piezoceramic based structural health monitoring systems, allowing easy and flexible installation, low system cost, and increased robustness over wired system. However, piezoceramic wireless SHM systems still faces some drawbacks, one of these is that the piezoceramic based SHM systems require relatively high computational capabilities to calculate damage information, however, battery powered WSN sensor nodes have strict power consumption limitation and hence limited computational power. On the other hand, commonly used centralized processing networks require wireless sensors to transmit all data back to the network coordinator for analysis. This signal processing procedure can be problematic for piezoceramic based SHM applications as it is neither energy efficient nor robust. In this paper, we aim to solve these problems with a distributed wireless sensor network for piezoceramic base structural health monitoring systems. Three important issues: power system, waking up from sleep impact detection, and local data processing, are addressed to reach optimized energy efficiency. Instead of sweep sine excitation that was used in the early research, several sine frequencies were used in sequence to excite the concrete structure. The wireless sensors record the sine excitations and compute the time domain energy for each sine frequency locally to detect the energy change. By comparing the data of the damaged concrete frame with the healthy data, we are able to find out the damage information of the concrete frame. A relative powerful wireless microcontroller was used to carry out the sampling and distributed data processing in real-time. The distributed wireless network dramatically reduced the data transmission between wireless sensor and the wireless coordinator, which in turn reduced the power consumption of the overall system.

Wireless smart sensors equipped with computational and wireless communication capabilities are expected to provide rich information for structural health monitoring (SHM); inexpensive nature of sensors nodes and wireless communication allow dense sensor instrumentation over structures. While dense measurement is advantageous with regard to spatially characterizing structural dynamic behaviors, limited sensing accuracy of inexpensive wireless sensor nodes possibly bounds applications. For example, small ambient vibration may not be captured by smart sensor nodes. This paper proposes a combined use of low-cost smart sensors and high accuracy sensors for dynamic measurement of bridges to alleviate the influence of this limitation.

This paper describes a new software package, SHMTools, for prototyping algorithms for various structural health monitoring (SHM) applications. The software includes a set of standardized MATLAB routines covering three main stages of SHM: data acquisition, feature extraction, and feature classification for damage identification. A subset of the software in SHMTools is embeddable, which consists of Matlab functions that can be cross-compiled into generic "C" programs to be run on a target hardware. The software is designed to accommodate multiple sensing modalities, including piezoelectric active-sensing, which have become widely used in SHM practice. The software package, standardized datasets, and detailed documentation are publicly available for use by the SHM community. The details of this software will be discussed, along with several example processes to demonstrate its utility.

Smart sensors have been recognized as a promising technology with the potential to overcome many of the inherent difficulties and limitations associated with traditional wired structural health monitoring (SHM) systems. The unique features offered by smart sensors, including wireless communication, on-board computation, and cost effectiveness, enable deployment of the dense array of sensors that are needed for monitoring of large-scale civil infrastructure. Despite the many advances in smart sensor technologies, power consumption is still considered as one of the most important challenges that should be addressed for the smart sensors to be more widely adopted in SHM applications. Data communication, the most significant source of the power consumption, can be reduced by appropriately selecting data processing schemes and the related network topology. This paper presents a new decentralized data aggregation approach for system identification based on the Random Decrement Technique (RDT). Following a brief overview of the RDT, which is an output-only system identification approach, a decentralized hierarchical approach is described and shown to be suitable for implementation in the intrinsically distributed computing environment found in wireless smart sensor networks (WSSNs). RDT-based decentralized data aggregation is then implemented on the Imote2 smart sensor platform based on the Illinois Structural Health Monitoring Project (ISHMP) Services Toolsuite. Finally, the efficacy of the RDT method is demonstrated experimentally in terms of the required data communication and the accuracy of identified dynamic properties.

There has been a rapid advancement in wireless sensor network (WSN) technology in the past decade and its application in structural monitoring has been the focus of several research projects. The evaluation of the newly developed hardware platform and software system is an important aspect of such research efforts. Although much of this evaluation is done in the laboratories and using generic signal processing techniques, it is important to validate the system for its intended application as well. In this paper the performance of a newly developed accelerometer sensor board is evaluated by using the data from a beam-column connection specimen with a local damage detection algorithm. The sensor board is a part of a wireless node that consists of the Imote2 control/communication unit and an advanced antenna for improved connectivity. A scaled specimen of a steel beam-column connection is constructed in ATLSS center at Lehigh University and densely instrumented by synchronized networked systems of both traditional piezoelectric and wireless sensors. The column ends of the test specimen have fixed connections, and the beam cantilevers from the centerline of the column. The specimen is subjected to harmonic excitations in several test runs and its acceleration response is collected by both systems. The collected data is then used to estimate two sets of system influence coefficients with the wired one as the reference baseline. The performance of the WSN is evaluated by comparing the quality of the influence coefficients and the rate of convergence of the estimated parameters.

In many in-situ instruments information about the mass of the sample could aid in the interpretation of the data and portioning instruments might require an accurate sizing of the sample mass before dispensing the sample. In addition, on potential sample return missions a method to directly assess the captured sample size would be required to determine if the sampler could return or needs to continue attempting to acquire sample. In an effort to meet these requirements piezoelectric balances were developed using flextensional actuators which are capable of monitoring the mass using two methods. A piezoelectric balance could be used to measure mass directly by monitoring the voltage developed across the piezoelectric which is linear with force, or it could be used in resonance to produce a frequency change proportional to the mass change. In the case of the latter, the piezoelectric actuator/balance would be swept in frequency through its fundamental resonance. If a mass is added to the balance the resonance frequency would shift down proportionally to the mass. By monitoring the frequency shift the mass could be determined. This design would allow for two independent measurements of the mass. In microgravity environments spacecraft thrusters could be used to provide acceleration in order to produce the required force for the first technique or to bring the mass into contact with the balance in the second approach. In addition, the measuring actuators, if driven at higher voltages, could be used to fluidize the powder to aid sample movement. In this paper, we outline some of our design considerations and present the results of a few prototype balances that we have developed.

We use a new design of high-fidelity nanoseismic sensors to detect the stress waves produced at the initiation of sliding during stick-slip friction. The piezoelectric sensors can detect radiated waves just a few pm in amplitude in the frequency range of 10 kHz to over 2 MHz. The reported experiments are designed to provide insights that may be applicable to both fault scales and micro contact junctions. The sensors used are packaged in a hardened steel case to facilitate their use in the field. The transducer's small size (14 mm threaded body, 30 mm long) permits a dense population of sensors to be installed on laboratory-sized samples, or surrounding localized centers of damage on structural applications. The closely spaced sensor array facilitates the localization of individual load releases from tiny asperities on a cm-scale frictional interface. At the same time, the broadband response of the conical piezoelectric sensors makes possible the study of source dynamics using theory developed for the study of earthquake source mechanisms via radiated seismic waves.

The flow fields and boundary erosion that are associated with scour at bridge piers are very complex. Direct measurement of the boundary shear stress and boundary pressure fluctuations in experimental scour research has always been a challenge and high spatial resolution and fidelity have been almost impossible. Most researchers have applied an indirect process to determine shear stress using precise measured velocity profiles. Laser Doppler Anemometry and Particle Image Velocimetry are common techniques used to accurately measure velocity profiles. These methods are based on theoretical assumptions to estimate boundary shear stress. In addition, available turbulence models cannot very well account for the effect of bed roughness which is fundamentally important for any CFD simulation. The authors have taken on the challenge to advance the magnitude level to which direct measurements of the shear stress in water flow can be performed. This paper covered the challenges and the efforts to develop a higher accuracy and small spatial resolution sensor. Also, preliminary sensor designs and test results are presented.

Health degradation by corrosion of steel in civil engineering, especially in rough environment, is a persistent problem. Structural health monitoring (SHM) techniques can lead to improved estimates of structural safety and serviceability. A novel all solid state-current confined corrosion sensor has been developed to provide the platform for corrosion monitoring of the steel bar in concrete beam by electrochemical method. Finite element method has been used to certify the current confined effect of the sensor. The sensors have been used in concrete beams to monitor the corrosion of the steel bar. Also, half-cell potential of the beam has obtained. The results shows that the corrosion sensor can effectively confine the current in the fixed area which is 45mm×π×Dsteel bar and the monitoring results of the corrosion sensor are accurate.

In this study, a technique using wireless impedance sensor node and interface washer is proposed to monitor prestressforce in PSC girder bridges. In order to achieve the goal, the following approaches are implemented. Firstly, a wireless impedance sensor node is designed for automated and cost-efficient prestress-force monitoring. Secondly, an impedance-based algorithm is embedded in the wireless impedance sensor node for autonomous prestress-force monitoring. Thirdly, a prestress-force monitoring technique using an interface washer is proposed to overcome limitations of the wireless impedance sensor node such as measureable frequency ranges with narrow band. Finally, the feasibility and applicability of the proposed technique are evaluated in a lab-scaled PSC girder model for which several prestress-loss scenarios are experimentally monitored by the wireless impedance sensor node.

In this paper, the self-sensing and mechanical properties of concrete structures strengthened with a novel type of smart basalt fiber reinforced polymer (BFRP) bars were experimentally studied, wherein the sensing element is Brillouin scattering-based distributed optical fiber sensing technique. First, one of the smart bars was applied to strengthen a 2m concrete beam under a 4-points static loading manner in the laboratory. During the experiment, the bar can measure the inner strain changes and monitor the randomly distributed cracks well. With the distributed strain information along the bar, the distributed deformation of the beam can be calculated, and the structural health can be monitored and evaluated as well. Then, two smart bars with a length of about 70m were embedded into a concrete airfield pavement reinforced by long BFRP bars. In the field test, all the optical fiber sensors in the smart bars survived the whole concrete casting process and worked well. From the measured data, the concrete cracks along the pavement length can be easily monitored. The experimental results also confirmed that the bars can strengthen the structures especially after the yielding of steel bars. All the results confirm that this new type of smart BFRP bars show not only good sensing performance but also mechanical performance in the concrete structures.

Self-repairing structural systems can potentially improve performance ranges and lifetimes compared to those of conventional systems without self-healing capability. Self-healing materials have been used in automotive and aeronautical applications for over a century. The bulk of these systems operate by using the damage to directly initiate the repair response without any supervisory coordination. Integrating sensing and supervisory control technologies with self-healing may improve the safety and reliability of critical components and structures. This project used laboratory scale test beds to illustrate the benefit of an integrated sensing, control and self-healing system. A thermal healing polymer embedded with resistive heating wires acted as the sensing-healing material. Sensing duties were performed using an impedance, capacitance, and resistance testing device and a PC acted as the controller. As damage occurs to the polymer it is detected, located, and characterized. Based on the sensor signal, a decision is made as to whether to execute a repair and then to subsequently monitor the repair process to ensure completeness. The second demonstration was a self-sealing pressure vessel with integrated sensing and healing capability. These proof-of-concept prototypes can likely be expanded and improved with alternative sensor options, sensing-healing materials, and system architecture.

A glulam beam retired from the field and without visible indications of wood decay was used. Towards detection and assessing wood decay, X-ray computer tomography and ultrasonic measurements were carried out. It was observed that decrease in mass density with increasing levels of wood decay affects x-rays attenuation and allows radioscopy to detect and assess wood decay. To detect and assess decay when only one lateral side of the beam is available, a modified impulse-echo is presented. The modified impulse-echo approach is based on observing the dynamic response of each lamina in the glulam beam to the drop of a steel sphere onto a steel plate coupled to the glulam beam lamina and upon a decay rate analysis of the corresponding time domain signal in a frequency band of interest. The selection of the frequency band of interest only requires knowledge of the nominal transverse dimensions of each lamina in the beam and of the corresponding wood species. It was observed that decay rate analysis allows detection and assessment of wood decay. The decay rate approach leads to an overall rate of false calls of 7.2%. Considering the variability that exists in wood including the presence of splits, orientation and thickness of growth rings, etc., this relative low rate of false calls makes this approach very attractive. Results show that results from both X-ray computer tomography and impulse-echo decay-rated based measurements are consistent with each other and can be used to detect and assess wood decay in structural lumber.

Fiber loop ringdown (FLRD), a uniform time-domain sensing scheme, has potential to help address the three key issues: Power losses, light intensity fluctuations, and high terminal equipment costs, in the development of fiber optic sensor networks for simultaneously sensing multiple quantities, including pressure, temperature, strain, chemical species, etc. with fast response, high sensitivity, and significantly reduced costs. Performance and design of a cluster of individual FLRD-based fiber optic sensors are presented. Multiplexing those individual FLRD sensor units into a large scale sensor system for multi-function sensing is proposed. System configuration, operation, and advantages are discussed.

In this article, localization of a static source by using a mobile sensor platform is studied. With appropriate assumptions on the system dynamics, the noise robustness of a previously proposed localization algorithm1 is examined. By using Lyapunov analysis, it is demonstrated that if the noise uncertainty is constant and bounded, the adaptive localization algorithm results in bounded localization errors. The analytical results are validated through numerical simulations.

An approach to identify and classify objects in real time by multispectral imaging, wavelets based fusion, and Haar classification is presented. The specific object of interest is a cardboard box placed on the roadside. The proposed approach involves capturing a scene in the visible and infra red spectrum. Fusing the spectra is performed by using the wavelet transform. Further, Haar training is performed using sample positives and negatives prior to classification. The presented approach is tested to work in real time with very good accuracy. If successful, the method will be applied to the detection of a variety of anomalous objects placed at the roadside.

This paper gives a general view on some aspects of the influence of uncertainty in model-based monitoring of loadcarrying structures. The advantages and relevance of monitoring for the prediction of reliability will be clarified and the difference between uncertainty and reliability is discussed. Solving inverse Problems is a particular challenge in monitoring systems. Therefore, different categories of inverse problems are discussed. A generally valid extended difference equation, which describes the transfer behavior of the structure, will be derived as the basis for digital signal processing of model-based monitoring. This equation also considers changes in the structures dynamic properties, e.g due to damage or temperature. With this equation, the influence of uncertainty due to measurement noise to the functionability of monitoring is discussed and some possibilities are shown to control this uncertainty when determining ideal sensor-positions for monitoring.

Singular Spectrum Analysis (SSA) is a novel non-parametric technique based on principle of multivariate statistics. The original time series is decomposed into a number of additive time series, each of which can be easily identified as being part of the modulated signals, or as being part of the random noise. It shows that the embedding dimension m of a dynamical time series can be conducted by the Singular Value Decomposition (SVD) experiments. This SVD scheme was used to detect low-dimensionally dynamic signals and the residuals. It provides trend extraction involves a decomposition of a time series into low-frequency trends and high-frequency variability. In this study, first, SSA is used to decompose the nonlinear seismic responses of reinforced concrete frames and to elucidate permanent deformation. Then, damage feature extraction is conducted using the high-frequency variability of SSA to identify the occurrence of damage. Comparison the results with the Holder exponent and the Level-1 detail of the discrete wavelet component to detect the damage occurrence was made. Finally, using SSA to estimate the permanent deformation using recorded acceleration data was also discussed. In this study, four reinforced concrete frame test data collected in response to various degrees of seismic excitation are used to demonstrate the application of SSA in damage detection.

This paper applies support vector machine (SVM) to the field of structural health monitoring. SVM is a data processing technique that performs binary classification. The machine in its name indicates its association with machine learning, a category of algorithms that are able to solve classification problems by learning from example data given in a training process. This paper uses SVM for abnormality detection on data from a cable-stayed bridge's health monitoring system. The goal is to investigate whether the east end expansion joint is constraining the longitudinal motion of the bridge's main girder, which is suspected due to the results of a finite element updating procedure. Regarding the training process, distinct examples of the normal and abnormal expansion joint are unavailable from the health monitoring system. For this reason training examples are obtained from a finite element model. Accordingly, since SVM accuracy is highly dependent on the similarity between the training data and data being classified, the finite element modeling is a primary challenge of the paper's approach. The contributions of this paper include an application of SVM to an in-service structure, as well as a discussion on its performance and some limitations that affect its accuracy.

The Kalman filter is commonly employed to fuse the measured information from displacement and acceleration responses. This fusion technique can mitigate the noise effect and produce more accurate response estimates. The fusion performance however significantly depends on the accuracy of noise estimation. The noise variances are generally estimated empirically a priori and assumed to be fixed throughout the calculation. Hence some estimation error might occur when the noise characteristics are time-varying. In this study, an adaptive subspace-based technique is developed to identify the noise variances. The approach is based on the principal component analysis which decomposes noisecontaminated signals into the signal subspace and the noise subspace. The variances of the noise and signals can then be estimated independently. To track the time variations of the noise and signal variances in an on-line fashion, a projection approximation subspace tracking technique is employed. The proposed technique can be incorporated into an adaptive Kalman filter and provide a more accurate estimation for data fusion.

Human state in human-machine systems highly affects the system performance, and should be monitored. Physiological cues are more suitable for monitoring the human state in human-machine system. This study was focused on developing a new sensing system, i.e. NANO-Skin, to non-intrusively measure physiological cues from human-machine contact surfaces for human state recognition. The first part was to analyze the relation between human state and physiological cues. Generally, heart rate, skin conductance, skin temperature, operating force, blood alcohol concentration, sweat rate, and electromyography have close relation with human state, and can be measured from human skin. The second part was to compare common sensors, MEMS sensors, and NANO sensors. It was found that MEMS sensors and NANO sensors can offer unique contributions to the development of NANO-Skin. The third part was to discuss the design and manufacture of NANO-Skin. The NANO-Skin involves five components, the flexible substrate, sensors, special integrated circuit, interconnection between sensors and special integrated circuit, and protection layer. Experiments were performed to verify the measurement accuracy of NANO-Skin. It is feasible to use NANO-Skins to non-intrusively measure physiological cues from human-machine contact surfaces for human state recognition.

Single-walled carbon nanotubes (SWNTs) with their large surface area, high aspect ratio are one of the novel materials which have numerous attractive features amenable for high sensitivity sensors. Several nanotube based sensors including, gas, chemical and biosensors have been demonstrated. Moreover, most of these sensors require off chip components to detect the variations in the signals making them complicated and hard to commercialize. Here we present a novel complementary metal oxide semiconductor (CMOS) integrated carbon nanotube sensors for portable high sensitivity chemical sensing applications. Multiple zincation steps have been developed to ascertain proper electrical connectivity between the carbon nanotubes and the foundry made CMOS circuitry. The SWNTs have been integrated onto (CMOS) circuitry as the feedback resistor of a Miller compensated operational amplifier utilizing low temperature Dielectrophoretic (DEP) assembly process which has been tailored to be compatible with the post-CMOS integration at the die level. Building nanotube sensors directly on commercial CMOS circuitry allows single chip solutions eliminating the need for long parasitic lines and numerous wire bonds. The carbon nanotube sensors realized on CMOS circuitry show strong response to various vapors including Dimethyl methylphosphonate and Dinitrotoluene. The remarkable set of attributes of the SWNTs realized on CMOS electronic chips provides an attractive platform for high sensitivity portable nanotube based bio and chemical sensors.

Research into operational aspects of mini (<5kg) unmanned aerial vehicles (UAV) and structural health monitoring systems (SHM) is being conducted at the Defence Science and Technology Organisation and La Trobe University. A fundamental area of interest is investigating the problems associated with robustness of the control and health monitoring sensors for such systems. While many technologies for UAV and SHM systems can be, and have been, adapted from those currently available in large manned aircraft; cost, weight, and size constraints have prevented mini UAVs from including many of the robust mechanisms common to larger aircraft. Moreover, the ubiquitous nature of the sensing requirements for SHM systems has limited their uptake, due mainly to the same issues of cost, weight and size. This paper details the design of a reconfigurable multivariable MEMS (Micro Electro Mechanical System) array to address these issues. This array is composed of multiple instances of identical sensors, which can be dynamically reconfigured to achieve the desired measurand(s) with tradeoffs against accuracy. The available measurands include such items as; accelerations, rotational rates, magnetic fields (X, Y and Z directions), temperature and pressure. The paper presents the design of a reconfigurable multivariable MEMS sensor array together with simulation results.

Piezoelectric wafer active sensors (PWAS) are well known for its dual capabilities in structural health monitoring, acting as either actuators or sensors. Due to the variety of deterioration sources and locations of bridge defects, there is currently no single method that can detect and address the potential sources globally. In our research, our use of the PWAS based sensing has the novelty of implementing both passive (as acoustic emission) and active (as ultrasonic transducers) sensing with a single PWAS network. The combined schematic is using acoustic emission to detect the presence of fatigue cracks in steel bridges in their early stage since methods such as ultrasonics are unable to quantify the initial condition of crack growth since most of the fatigue life for these details is consumed while the fatigue crack is too small to be detected. Hence, combing acoustic emission with ultrasonic active sensing will strengthen the damage detection process. The integration of passive acoustic emission detection with active sensing will be a technological leap forward from the current practice of periodic and subjective visual inspection, and bridge management based primarily on history of past performance. In this study, extensive laboratory investigation is performed supported by theoretical modeling analysis. A demonstration system will be presented to show how piezoelectric wafer active sensor is used for acoustic emission. Specimens representing complex structures are tested. The results will also be compared with traditional acoustic emission transducers to identify the application barriers.

This paper describes the use of embedded and surface bonded piezoelectric transducers (PZTs) to monitor concrete by means of the electromechanical impedance (EMI) method. The main objective of the present study is the design and utilization of a rugged and embeddable sensing system capable to monitor curing, stress and damage in concrete structures. Three concrete cylinders with in-house designed sensors were cast and tested. Surface bonded PZT were also used to compare the response of conventional PZT patch to the response of the embedded system. After the conventional 28-days curing, two cylinders were subjected to a compression test and the third cylinder was subjected to induced damage. The EM signatures were processed using a statistical index and a slope gradient. The results show that the sensing system and the EMI method are suitable to monitor curing progression and to detect applied stress, damage onset, and damage propagation.

An impedance-based monitoring technique is used to detect the gradual bonding between steel reinforcing bar and fresh concrete. The method, which has made significant progress in the fields of structural health monitoring (SHM) and non-destructive evaluation (NDE), is essentially based on the application of piezoelectric transducers as collocated sensors and actuators utilizing their direct and converse piezoelectric effects simultaneously. In this study, a piezoelectric ceramic (PZT) transducer bonded to a steel rebar was embedded in concrete and the changes in the conductance signature of the transducer were monitored by exciting it at high frequencies. The monitoring was carried out up to 72 hours to investigate the influence of setting and initial hardening of concrete.

Fatigue induced damage is often progressive and gradual in nature. Structures subjected to large number of fatigue load cycles will encounter the process of progressive crack initiation, propagation and finally fracture. Monitoring of structural health, especially for the critical components, is therefore essential for early detection of potential harmful crack. Recent advent of smart materials such as piezo-impedance transducer adopting the electromechanical impedance (EMI) technique and wave propagation technique are well proven to be effective in incipient damage detection and characterization. Exceptional advantages such as autonomous, real-time and online, remote monitoring may provide a cost-effective alternative to the conventional structural health monitoring (SHM) techniques. In this study, the main focus is to investigate the feasibility of characterizing a propagating fatigue crack in a structure using the EMI technique as well as estimating its remaining fatigue life using the linear elastic fracture mechanics (LEFM) approach. Uniaxial cyclic tensile load is applied on a lab-sized aluminum beam up to failure. Progressive shift in admittance signatures measured by the piezo-impedance transducer (PZT patch) corresponding to increase of loading cycles reflects effectiveness of the EMI technique in tracing the process of fatigue damage progression. With the use of LEFM, prediction of the remaining life of the structure at different cycles of loading is possible.

The purpose of this research is to develop the structural health monitoring system for composite airframe structures by strain mapping through their life cycles. We apply FBG sensor networks to CFRP pressure bulkheads and monitor the strain through their life cycles: molding, processing, assembly, operation and maintenance. Damages, defects and deformations which occurred in each stage are detected using the strain distribution. At first, we monitored the strain of CFRP laminates during molding and processing with FBG sensors. As a result, not only the thermal strain on curing process but also strain change due to demolding was measured precisely. In addition, we analyzed the change in strain distribution due to damages of CFRP pressure bulkhead such as stringer debonding and impact damage of skin under operational load in flight. On the basis of these results, the location of FBG sensors suitable for the detection of damages was determined.

A new sensor concept for fatigue crack growth monitoring in technical structures is presented. It allows the in-situ determination of the position of the crack tip as well as the fracture mechanical quantities. The required data are obtained from a piezoelectric polymer film, which is attached to the surface of the monitored structure. The stress intensity factors and the crack tip position are calculated from electrical potentials obtained from a sensor array by solving the non-linear inverse problem.

Continuous strip transducers are investigated to generate ultrasonic guided waves for structural health monitoring of plate and shell structures. A theoretically driven approach, based on the application of wave mechanics principles, will be used to research and design a network of strip transducers. The initial transducer concept is that the strips will function like comb transducers and generate planar Lamb waves that travel normal to the longitudinal axis of the strip. Fibrous piezoelectric composites are considered for the comb elements, expanding the design space of these elements to include fiber orientation and volume fraction in addition to size, configuration, and location of the electrodes. This paper presents results from wave propagation studies of continuous strip actuators. As intended, the strip transducer excites Lamb waves that are reasonably planar with little interaction with the energy that propagates in the direction of the strip. Micromechanical modeling results for overall material properties of piezoelectric fiber composites are presented and demonstrate the wide design space for these types of devices.

The demands of aging infrastructure require effective methods for structural monitoring and maintenance. Wireless smart sensor networks offer the ability to enhance structural health monitoring (SHM) practices through the utilization of onboard computation to achieve distributed data management. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While smart sensor technology is not new, the number of full-scale SHM applications has been limited. This slow progress is due, in part, to the complex network management issues that arise when moving from a laboratory setting to a full-scale monitoring implementation. This paper presents flexible network management software that enables continuous and autonomous operation of wireless smart sensor networks for full-scale SHM applications. The software components combine sleep/wake cycling for enhanced power management with threshold detection for triggering network wide tasks, such as synchronized sensing or decentralized modal analysis, during periods of critical structural response.

This paper presents an immune network-based emergent pattern recognition method. The artificial immune network provides more flexible learning tools than neural networks and clustering technologies. With a neural network, a network structure has to be defined first. The immune network allows their components to change and learn patterns by changing the strength of connections between individual components. The presented computational model achieves emergent pattern recognition by dynamically constructing a network of feature vectors to represent the internal image of input data patterns. The immune network-based emergent pattern recognition approach has tested using a benchmark civil structure. The test result shows the feasibility of using the presented method for the emergent structural damage pattern recognition.

This study presents the development of a multi-functional wireless sensor node for the impedance-based SHM. The bottom line is to provide multifunctional wireless sensor nodes for low cost and low power excitation/sensing, structural damage detection/sensor self-diagnosis using embedded algorithms, temperature/power monitoring, and energy scavenging. A miniaturized impedance measuring chip is utilized for low cost and low power structural excitation/selfsensing. Then, structural damage detection/sensor self-diagnosis are executed on the on-board microcontroller. Moreover, it can use the harvested power from solar energy to measure and analyze the impedance data. Simultaneously it can monitor temperature and power consumption. In order to validate the feasibility of this multi-functional wireless impedance sensor node, a series of experimental studies have been carried out for detecting loose bolts and crack damages on a lab-scale steel structure as well as on real steel bridge/building structures. As a result, it has been found that the proposed wireless impedance sensor nodes can be effectively used for local health monitoring of structural components and for constructing a low-cost and low-power but multifunctional SHM system as "place and forget" sensors.

Structural health monitoring (SHM) and damage detection have attracted great interest in recent decades, in meeting the challenges of assessing the safety condition of large-scale civil structures. By wiring remote sensors directly to a centralized data acquisition system, traditional structural health monitoring systems are usually costly and the installation is time-consuming. Recent advances in wireless sensing technology have made it feasible for structural health monitoring; furthermore, the computational core in a wireless sensing unit offers onboard data interrogation. In addition to wireless sensing, the authors have recently developed a mobile sensing system for providing high spatial resolution and flexible sensor deployment in structural health monitoring. In this study, transmissibility function analysis is embedded in the mobile sensing node to perform onboard and in-network structural damage detection. The system implementation is validated using a laboratory 2D steel portal frame. Simulated damage is applied to the frame structure, and the damage is successfully identified by two mobile sensing nodes that autonomously navigate through the structure.

Recent advances in wireless sensing technology have made it possible to deploy dense networks of sensing transducers within large structural systems. Because these networks leverage the embedded computing power and agent-based abilities integral to many wireless sensing devices, it is possible to analyze sensor data autonomously and in-network. In this study, market-based techniques are used to autonomously estimate mode shapes within a network of agent-based wireless sensors. Specifically, recent work in both decentralized Frequency Domain Decomposition and market-based resource allocation is leveraged to create a mode shape estimation algorithm derived from free-market principles. This algorithm allows an agent-based wireless sensor network to autonomously shift emphasis between improving mode shape accuracy and limiting the consumption of certain scarce network resources: processing time, storage capacity, and power consumption. The developed algorithm is validated by successfully estimating mode shapes using a network of wireless sensor prototypes deployed on the mezzanine balcony of Hill Auditorium, located on the University of Michigan campus.

A new type of adaptive structure is presented that relies on pressurized honeycomb cells that extent a significant length with respect to the plane of the hexagons. By varying the pressure inside each of the cells, the stiffness can be altered. A variable stiffness in combination with an externally applied force field results in a fully embedded pressure adaptive actuator that can yield strains well beyond the state-of-the-art in adaptive materials. The stiffness change as a function of the pressure is modeled by assigning an equivalent material stiffness to the honeycomb walls that accounts for both the inherent material stiffness as the pressure-induced stiffness. A finite element analysis of a beam structure that relies on this model is shown to correlate well to experimental results of a three-point bend test. To demonstrate the concept of embedded pressure adaptive honeycomb, an wind tunnel test article with adaptive flap has been constructed and tested in a low speed wind tunnel. It has been proven that by varying the cell pressure the flap changed its geometry and subsequently altered the lift coefficient.

The β-phase of polyvinylidene fluoride (PVDF) is well known for its piezoelectric properties. PVDF films have been developed using solvent cast method. The films thus produced are in β-phase . The β-phase films are transformed to piezoelectric β-phase , when films are hot-stretched at different temperature, and with different stretching factors. Films are characterized for structural, tensile and surface morphological changes during the transformation from α- to β-phase by using X-ray diffraction, differential scanning calorimeter, Raman spectra, Infrared spectra, tensile testing, and scanning electron microscopy. The films showed increased crystallinity with stretching up to 80oC. The optimum conditions to achieve β-phase have been discussed in detail. The fabricated PVDF sensors have been tested for free vibration and impact on plate structure, and its response is compared with conventional piezoelectric wafer type sensor. The resonant and anti-resonant peaks in the frequency response of PVDF sensor match well with that of PZT.

The unusual properties of shape memory alloys (SMAs) are due to solid-to-solid martensitic phase transformations (MPTs) which correspond to a lattice level instability of the crystal structure. The high temperature phase is usually a high symmetry structure and is called the austenite phase whereas the low temperature phase has a low symmetry and is called the martensite phase. Currently, there exists a shortage of material models of MPTs based on the material's atomic composition and crystal structure that would lead to computational discovery of new improved SMAs. The present work develops a lattice dynamics model using a first-order self-consistent approach based on statistical perturbation theory that aims to capture the qualitative and ultimately quantitative behavior of MPTs. In particular, the atomic interactions are modeled using Morse pair potentials. The effects of atomic vibrations on the material properties are captured by renormalizing the frequencies of atomic vibration using self-consistent equations. These renormalized frequencies are dependent on both configuration and temperature. The model is applied for the case of a one dimensional bi-atomic chain. The constant Morse pair potential parameters are chosen to demonstrate the usefulness of the current model. The resulting model is evaluated by generating stress-free equilibrium paths with temperature as the loading parameter. These plots are generated using branch-following and bifurcation techniques. A second-order phase transformation (PT) is predicted which involves transformation from a high symmetry phase to a low symmetry phase as the temperature is decreased. Thus, the current model is able to capture the important aspect in MPTs, i.e., transformation from high symmetry phase to low symmetry phase as temperature is decreased. We believe that this model applied to three dimensional structures will be able to capture first-order MPTs that occur in SMAs. This qualitative prediction of a temperature-induced PT indicates the likely hood that the current model can be used for the computational discovery of new shape memory alloys. Such an undertaking would involve, first, determining the potential parameters of new alloys from first-principles calculations and, second, using these parameter values with the current self-consistent model to evaluate the shape memory behavior of the new previously unstudied materials.

High specific surface area structures are used in a variety of applications including production of highly sensitive biosensors, fabrication of separation membranes, manufacturing of high throughput catalytic microreactors, and development of efficient electrodes for batteries and fuel cells. In many electrochemical applications (i.e. sensors and batteries) it's also critical to have good conductive properties of the fabricated high surface area structures. For energy harvesting technologies such as batteries and fuel cells, careful design of surface-to-volume ratio of the electrode surface is important, because while high specific surface area facilitates electrochemical reaction rates, it also increases overall electrode resistance. Thus, it is desirable to construct electrodes with a range of hierarchical features (for example with fractal structures). We invented a novel fabrication technology for creating three-dimensional conductive high surface area structures based on the deposition and subsequent processing of the electroactive polymers (EAP). The proposed fabrication technique is capable of fast and inexpensive production of high surface area structures with the designed geometry, porosity, and conductivity.

Fiber optic sensor system, which is not corrosible semi-permanent, no influence by electromagnetic waves, and able to multiplex, can be expect to take an important part to assess the safety and residual estimate the life span of the highway pavement structure. In this research, as in situ monitoring of roughness of pavement, we propose the vibration monitoring method using fiber optic sensors. We designed and produced prototype fiber optic vibration sensor packages. Laboratory impact tests with the sensors were performed. The sensors showed very good responsibility to the impact and nice damping shape like other ordinary accelerometers. Actual road tests with the prototype vibration sensor were also performed. The ambient vibration by the vehicles was used for the experiment.

BOTDR is one of the strain measurement technologies that is suitable for smart monitoring of civil engineering infrastructures. While the technology has the advantage of supplying spatially distributed data, it is currently limited to a spatial resolution of about 1m. This infers that the technology may lack the ability to identify the exact type and source of damage; that is, different geometrical configurations of cracking within a concrete beam may lead to similar BOTDR readings, and hence the exact nature of cracking might not be resolved by the BOTDR. This study suggests different crack indicators, and examines, both analytically and experimentally, their correlation with BOTDR readings of damaged reinforced concrete beams. The analytical part entails statistical analysis of hundreds of cracking cases in fractured reinforced concrete beams and their effect on the simulated BOTDR readings. The analysis is conducted within COMSOL-Multiphysics, and is aimed to understand the correlation between different crack indicators and the beam curvature as would be obtained by the BOTDR. The experimental part consists of a controlled load test of a reinforced beam instrumented by BOTDR fibers, and is aimed to support the analytical findings.

For the understanding of the bearing behavior of a loaded ground anchor, the measuring and monitoring of the stress distribution in the anchor tendon is essential. This paper proposes a novel monitoring ground anchor using embedded optical fibers for the continuous strain assessment along the anchor tendon. In a first step, optical sensors have been integrated into short tendons using different methods and laboratory strain testing was performed on these instrumented tendons. The evaluation of the laboratory testing enabled the design and development of an 8m long monitoring ground anchor for field application. In 2009, this anchor has been placed into a wall supporting an excavation pit and subsequently, anchor pullout test was carried out. The anchor was loaded stepwise up to 470kN, almost reaching its ultimate bearing capacity. Optical measurements were taken successfully at each load step. Comparison of the optical data with data acquired using conventional methods indicated good consistency of the results. To a geotechnical engineer, this proposed monitoring anchor provides a powerful tool for the measuring of the pullout load, the anchor head displacement and the load distribution in the anchor tendon.

In this paper, based on the distributed optical fiber strain sensing technology of pulse-pre-pump Brillouin Optical Time Domain Analysis (PPP-BOTDA), the creep properties of two types of optical fiber sensors, i.e. single mode optical fiber with jacket (Type-A) and optical fiber with UV resin coating (Type-B), were studied at different load (60g~600g) amplitudes. Experimental results show that there exists some creep for both types in initial loading period and tend to level off with time. But for Type-B, the strain variation is 5% of initial strain, and the stabilization time is about 48h, both of which are obviously smaller than those of Type-A. As a result, it is revealed that Type-B is characterized by a smaller creep, suitable for the long-term monitoring of infrastructures.

This paper presents a top-down design methodology for a behavioral modeling System, based on smart sensors for aerospace structures monitoring, implemented on a MATLAB/Simulink environment. The modeled acquisition platform in this aeronautic health monitoring systems (AHMS) is built using the following specific sensors: humidity, pressure, temperature, stress and acceleration. For this application it has been implemented frequency acquisition techniques ensuring optimum noise immunity, particularly: a signal acquisition technique based on voltage to frequency converter, capacitance to frequency and frequency to code converters (VtoF-cC, CtoF-cC). The Simulink model presents a high accuracy level in signal acquisition and conditioning compared to the electrical system simulation behavior.

We suggest a method for the mathematical modeling of the response of a thin structure with integrated piezoelectric sensors and actuators under mechanical and electrical loads. The plate with attached piezoelectric patches is considered as a two-dimensional material surface with mechanical and electrical degrees of freedom of particles. The model is complemented with an asymptotic analysis of the three-dimensional problem. For the equations of a layered piezoelectric plate, we seek those terms in the solution, which dominate as the thickness tends to zero. The results serve as a basis for the analysis of geometrically nonlinear shell structures as well as for model-based monitoring and optimal sensor and actuator placement.

This paper presents a systematic investigation of power and energy transduction in piezoelectric wafer active sensors (PWAS) for structural health monitoring (SHM). After a literature review of the state of the art, the paper develops a simplified pitch-catch model of power and energy transduction of PWAS attached to structure. The model assumptions include: (a) 1-D axial and flexural wave propagation; (b) ideal bonding (pin-force) connection between PWAS and structure; (c) ideal excitation source at the transmitter PWAS and fully-resistive external load at the receiver PWAS. Frequency response functions are developed for voltage, current, complex power, active power, etc. First, we examined PWAS transmitter and determined the active power, reactive power, power rating of electrical requirement under harmonic voltage excitation. It was found that the reactive power is dominant and defines the power requirement for power supply / amplifier for PWAS applications. The electrical and mechanical power analysis at the PWAS structure interface indicates all the active electrical power provides the mechanical power at the interface. This provides the power and energy for the axial and flexural waves power and energy that propagate into the structure. The sum of forward and backward wave power equals the mechanical power PWAS applied to the structure. The parametric study of PWAS transmitter size shows the proper size and excitation frequency selection based on the tuning effects. Second, we studied the PWAS receiver structural interface acoustic and electrical energy transduction. The parametric study of receiver size, receiver impedance and external electrical load gives the PWAS design guideline for PWAS sensing and power harvesting applications. Finally we considered the power flow for a complete pitch-catch setup. In pitch-catch mode, the power flows from electrical source into piezoelectric power at the transmitter; the piezoelectric conduction converts the electrical power into the mechanical interface power at the transmitter PWAS and then into the acoustic wave power travelling in the structure. The wave power arrives at the receiver PWAS and is captured at the mechanical interface between the receiver PWAS and the structure; the captured mechanical power is converted back into electrical power at the receiver PWAS and measured by the receiver electrical instrument. Our numerical simulation and graphical chart show the trends in the power and energy flow behavior with remarkable peaks and valleys that can be exploited for optimum design.

Piezoelectric wafer active sensors (PWAS) have been used as actuators in structural health monitoring system of beams, plates, and truss elements. This paper presents a shear lag solution for the transfer of stress and strain between a structurally attached piezoelectric wafer active sensor and the support structure. We will derive a shear lag solution not limited to the low frequency approximation, i.e., a generic solution. Both the low frequency approximation and the generic solution will be applied to the computation of PWAS-structure tuning curves.

A magnetostrictive bending sensor with rectangular planar coil is investigated. Its purpose is to measure contactlessly mechanical quantities of non-vibrating structures using an alternating magnetic field. The coil turns are electrodeposited by pattern plating on top of a magnetostrictive Galfenol layer and a thin isolation layer. The coil turns investigated in this paper were manufactured with a constant height of 10 μm and gap of 20 μm but variable width. The sensor is operated near its electrical self-resonance between 5 and 40 MHz and requires a high quality factor. FEMsimulations show that the quality factor of circular planar coils is almost independent on the conductor width under the given design restrictions when skin and proximity effects are included. Analytical calculations of rectangular coil parameters with three different turn numbers and conductor widths depending on the turn number predict an almost constant self-resonance quality factor in the DC case. Measured self-resonance quality factors are up to 59 % lower. The main reason for the disagreement is the current crowding by the proximity effect since analytical calculation show a significant influence of the skin effect only at higher frequencies with respect to the investigated self-resonance frequencies. Compared to the results of an FEM analysis obtained for circular coils the proximity effect is much smaller as well as the achievable low frequency quality factor.

Electromechanical network models are used in this paper to analyze a prototype micro-gyro sensor that employs the magnetostrictive alloy GalFeNOL for transduction of Coriolis induced forces into an electrical output at a given angular velocity. The sensor is designed as a tuning fork structure which reacts with vibration of the prongs in tangential direction due to an excited vibration in radial direction. A GalFeNOL patch attached to the axial-radial-surface changes its permeability depending on the bending. When it is surrounded by a solenoid coil and a magnet creates a bias magnetic field in the sensor patch, then this field fluctuates with the prong vibration. The induced voltage in the sensor coil is used as sensor output. A sinusoidal angular velocity being effective on the tuning fork structure causes an amplitude modulation of the excitation frequency which is the carrier frequency. A circuit representation of the electromechanical system is derived where the prongs are modeled as dynamic bending beams. The network model enables an understanding and explanation of the behavior of this system involving different physical domains, as well as fast analytical and numerical calculations, e.g. with pSpice. Experiments confirm the predicted sidebands of the sinusoidal rotation.

The development of sensor technologies for in situ, real time monitoring the high temperature/high pressure (HTP) chemical processes used in clean energy technologies is a tough challenge, due to the HTP, high dust and corrosive chemical environment of the reaction systems. A silica optical fiber is corrosive resistance, and can work in HTP conditions. This paper presents our effort in developing fiber optic sensors for in situ, real time monitoring the concentration of trace ammonia and hydrogen in high temperature gas samples. Preliminary test results illustrate the feasibility of using fiber optic sensor technologies for monitoring HTP processes for next generation energy industry.

Various energy harvesting technologies have been employed to extend the lifetime of wireless sensor networks. However, the network lifetime is still limited by the cycle life of rechargeable batteries (RBs) for the traditional RB-only storage system. Alternatively, supercapacitors (SCs) have extremely long cycle life-on the order of millions of cycles. A hybrid storage system combining RB and SC can leverage the complementary strengths of RB and SC and therefore significantly extend the lifetime of wireless sensors. This paper presents a generalized model of energy harvesting and hybrid storage system in order to evaluate the performance of hybrid energy storage systems (HESS) with different energy source and consumer profiles. Since high energy conversion efficiency is desired for most energy harvesting systems in addition to the lifetime, the system performance is analyzed in terms of two metrics: wireless sensor lifetime and energy conversion efficiency. A tradeoff is usually observed between the two performance metrics. However, under certain circumstances some specific HESS configurations can outperform the RB-only storage system in terms of both metrics. The results also suggest that an adaptive HESS that dynamically configures the storage devices based on the energy source and consumer profiles may have better performance comparing with a fixed HESS configuration.

Microbial Fuel cells (MFCs) are batteries driven by bacteria. MFCs have the potential of powering small sensors in remote areas and disposing of organic waste safely as they harvest the energy stored in the waste products. From previous research in this field, a few important factors for MFC performance have been identified. These include the internal resistance of MFC, the surface area of anode with catalyst for the biofilm development, the type and number of bacteria, and the abundance of nutritional supplies to the bacteria. With internal resistance as the focus of this MFC research, this experiment uses previous discoveries to develop and optimize the single chambered fuel cell for large-scale applications. A variety of methods were applied to improve MFC efficiency. Mainly, the researchers employed design techniques to increase the surface area of the electrodes, so that more of the generated electrons could be transported to the anode. In addition to that, several other measures were implemented to reduce the internal resistance, namely, adding ionic content, as well as introducing conductive particles such as carbon powder. These resulted in findings crucial to MFC technology.

This paper describes a version of the mechanical horizontal monolithic sensor for geophysical applications developed at the University of Salerno. The instrument is basically a monolithic tunable folded pendulum, shaped with precision machining and electric-discharge-machining, that can be used both as seismometer and, in a forcefeedback configuration, as accelerometer. It is a very compact instrument, very sensitive in the low-frequency seismic noise band, with a very good immunity to environmental noises, whose main characteristics are the tunability of the resonance frequency, a high mechanical quality factor and a very sensitive interferometric readout. In this paper we describe the results of the first tests performed on this new instrument, comparing the results with a previous version of the instrument.

World events have called for a need for fast, reliable, and more deployable methods of detection of improvised explosive devices (IEDs) than trained canines and visible detection by X-ray screening technologies. Anodized Aluminum Oxides (AAOs) are ideal substrates for chemical sensor developments. The nanoporous structure provides small pore-to-pore distance and large surface areas. These unique qualities allow optical interference in the visible spectrum when the thin film thickness is in the proper range. By coating the nanowells of the oxide surface first with a thin film of a noble metal followed by a monolayer of a target-specific chemical, detection of trace amounts of explosive materials becomes possible. Research has shown that the carboxyl group of 6-mercaptopyridine-3-carboxylic acid (6-MNA) has an attraction to the nitro groups of 2,4,6-trinitrotoluene (TNT) while the thiol group of 6-MNA creates a self-assembled monolayer on the substrate. By utilizing these chemical properties together, UV-vis spectrometry can detect a shift in the visible spectrum on the coated AAO substrate as the 6-MNA structure attracts trace amounts of TNT particles.

In this study, a multi-phase model update approach for system identification of real railway bridge using vibration test results is present. First, a multi-phase system identification scheme designed on the basis of eigenvalue sensitivity concept is proposed. Next, the proposed multi-phase approach is evaluated from field vibration tests on Wondongcheon bridge which is a steel girder railway bridge located in Yangsan, South Korea. On the bridge, a few natural frequencies and mode shapes are experimentally measured under the excitation of trains, ambient vibration and free vibration. The corresponding modal parameters are numerically calculated from a three-dimensional finite element (FE) model which is established for the target bridge. Eigenvalue sensitivities are analyzed for potential model-updating parameters of the FE model. Then, structural subsystems are identified phase-by-phase using the proposed model update procedure. Based on model update results, a baseline model of the Wondongcheon railway bridge is identified.

Identification of the changes in the properties of a structure are a potential indication of damage in that structure. In nonlinear systems, hysteretic models are often used to represent structural deterioration as well. Thus, the updating of such nonlinear hysteretic models using measured responses from a monitoring system is one approach to identify structural properties and thus damage. Nonlinear observer theory provides the tools to update such models, potentially online and in real-time. This paper examines several nonlinear observers that can be applied as online hysteretic model updating tools, and compares the results by using a Bouc-Wen model updating case. The online updating feature also demonstrates the potential application in providing state feedback to nonlinear structural control.

The detection of structural damages, either on-line or almost on-line, based on vibration data measured from sensors, is essential for the structural health monitoring system. The problem is quite challenging, in particular when the external excitations are not completely measured and when the structural system is complex. In practical applications, external excitations (inputs), such as seismic excitations, wind loads, traffic loads, etc., may not be measured or may not be measurable, and the structure may not always be shear-beam type which can be easily represented as spring-mass system. In this paper, a newly proposed damage detection method, referred to as the adaptive quadratic sum-squares error with unknown inputs (AQSSE-UI), is used for the detection of structural damages of a plane steel truss with finite element model. In this approach, external excitations and some structural responses may not be measured. Analytical recursive solution for the proposed AQSSE-UI method will be presented. The accuracy and effectiveness of the proposed approach will be demonstrated by numerical simulations where the structure is excited by different external loads. The simulation results indicate that the proposed approach is a viable damage detection technique capable of: (i) identifying structural parameters, (ii) tracking the changes of parameters leading to the detection of structural damages, and (iii) identifying the unknown external excitations.

Recent reports show that modal macro-strain vector (MMSV) obtained by using distributed long-gage FBG sensors is an effective indicator for damage detection. However, in previous researches, MMSV was always obtained under impulsive load such as hammer impact. In structural health monitoring of real large-scale structures, however, it is often very difficult to apply such impulsive load. This paper therefore introduces a new method to abstract MMSV under ambient excitation. Theoretical deduction reveals that MMSV can be uniquely determined by auto-spectrum of dynamic macro-strain responses under ambient excitation. Both numerical simulation and experiment were conducted to verify the proposed methods. Simulation results showed that that the identified frequencies and MMSV vectors under random excitation are in good agreement with those obtained from theoretical analysis, while experimental results showed the identified frequencies and MMSV agreed well with those obtained using point impulsive excitation.

Quality, amplitude and frequency of the interaction forces between a human and an actuator are essential traits for haptic applications. A variety of Electro-Active Polymer (EAP) based actuators can provide these characteristics simultaneously with quiet operation, low weight, high power density and fast response. This paper demonstrates a rolled Dielectric Elastomer Actuator (DEA) being used as a telepresence device in a heart beat measurement application. In the this testing, heart signals were acquired from a remote location using a wireless heart rate sensor, sent through a network and DEA was used to haptically reproduce the heart beats at the medical expert's location. A series of preliminary human subject tests were conducted that demonstrated that a) DE based haptic feeling can be used in heart beat measurement tests and b) through subjective testing the stiffness and actuator properties of the EAP can be tuned for a variety of applications.

Spacecrafts require a variety of separation and release devices to accommodate separation from the launch vehicle or deployment of heat radiation panels, solar arrays and other appendages. In order to overcome drawbacks of the current release devices, this paper proposes a design scheme of release device with a form of segmented nut and actuated with SMA (Shape Memory Alloy) wire. In order to validate the release device's function and performance, ground tests including single device response time tests, synchronous tests of two devices, fatigue life tests were carried out. Tests results show that the innovative space release device developed in this paper owning the advantages of small size, quick response, long fatigue life, high simultaneity and auto-reset has a potential use in space engineering.

Venus is one of the many significant scientific targets for NASA. New rock sampling tools with the ability to be operated at high temperatures of the order of 460°C are required for surface in-situ sampling/analysis missions. Piezoelectric materials such as LiNbO3 crystals and Bismuth Titanate are potentially operational at the temperature range found on the surface of Venus. A study of the feasibility of producing piezoelectric drills for a temperature up to 500°C was conducted. The study includes investigation of the high temperature properties of piezoelectric crystals and ceramics with different formulas and doping. Several prototypes of Ultrasonic/Sonic Drill/Corers (USDC) driven by transducers using the high temperate piezoelectric ceramics and single LiNbO3 crystal were fabricated. The transducers were analyzed by scanning the impedance at room temperature and 500°C under both low and high voltages. The drilling performances were tested at temperature up to 500°C. Preliminary results were previously reported [Bao et al, 2009]. In this paper, the progress is presented and the future works for performance improvements are discussed.

Cornerstone Research Group Inc. (CRG) is developing low-cost, lightweight, shape memory polymer (SMP) actuators for use in the deployment of rigid aeroshells. The SMP actuator technology has been selected for use because of its ability to store energy, within a very small volume, and release that energy on demand with little requirement for power. During the Phase I SBIR effort, CRG demonstrated the feasibility of using a thermally activated SMP actuator for the deployment of a subscale, rigid, deployable aeroshell. The follow-on Phase II effort improved upon the Phase I actuator technology through the application of finite element analysis and testing. This work resulted in the fabrication of a full-scale actuator (0.127m long, 0.102m diameter) that was able to develop more than 40 ft-lb of torque during actuation. A conformal cartridge heater (CCH) was developed in parallel to solve the problem of efficiently transferring heat stimulus into the SMP materials. The CCH maintains surface contact with the walls of the SMP actuator throughout the actuator's range of motion to optimize the heat transfer between the heating surface and the SMP material surface. The SMP actuator also has the potential of moving or deploying mechanisms simply through environmental stimulus. Since CRG is able to custom tailor the material properties of the SMP, broad application of this technology is possible.

A high speed, portable, multi-function WIM sensing system based on Fiber Bragg Grating (FBG) technology is reported in this paper. This system is developed to measure the total weight, the distribution of weight of vehicle in motion, the distance of wheel axles and the distance between left and right wheels. In this system, a temperature control system and a real-time compensation system are employed to eliminate the drifts of optical fiber Fabry-Pérot tunable filter. Carbon Fiber Laminated Composites are used in the sensor heads to obtain high reliability and sensitivity. The speed of tested vehicles is up to 20 mph, the full scope of measurement is 4000 lbs, and the static resolution of sensor head is 20 lbs. The demodulator has high speed (500 Hz) data collection, and high stability. The demodulator and the light source are packed into a 17'' rack style enclosure. The prototype has been tested respectively at Stevens' campus and Army base. Some experiences of avoiding the pitfalls in developing this system are also presented in this paper.

Because of the higher attenuation of AE signal in composite materials, it is required to develop a damage assessment technique less affected by the signal intensity in order to use AE signals for damage detection. In this research, we investigated impact induced AE signals using FBG sensors on carbon epoxy composite panel. The frequency characteristics of impact AE signals were examined with wavelet decomposition focused on the leading wave. Consequently, we established a damage assessment technique using the sharing percentage of the wavelet detail components of AE signal, and conducted a low-velocity impact test on composite laminates to confirm the feasibility of the damage assessment method with FBG sensors.

Some dynamic topics have become of increasing concern for the large bridges' safety. However, precise dynamic characteristics of the bridges are the foundation to solve these topics. In addition, the numerical model can be updated by exact parameters to serve as the baseline model for the following health monitoring and damage detection. This paper describes the experimental and theoretical modal analysis performed on the Sutong Bridge in China, which is the firstbuilt thousand-meter scale cable-stayed bridge in the world. Ambient vibration tests are carried out with dense sensor arrays and the acceleration responses of the deck and the two towers are obtained for processing. Some global vibration modes of the bridge are identified in the frequency range lower than 1.0Hz using both the FFT-based method and the random decrement technique combined with Ibrahim time domain method. The scattering ranges of the extracted modal damping ratios of all modes are narrow and the results contribute to the following research. Theoretical analysis is conducted on the three-dimentional finite element model developed from the design drawings combined with some measured material properties. A good correlation is achieved between the theoretical and the experimental analysis. So the main assumptions adopted in the FE model for dynamic analysis are assessed and summarized. Based on the study, some useful guidelines for dynamic analysis are presented.

Current bridge visual inspections are time-consuming, subjective, and rely heavily on personal experiences. The resulting ratings may be inconsistent. This paper discusses using remote-sensing technologies for bridge assessment, specifically, the use of high-resolution aerial imagery. The Small-Format Aerial Photography (SFAP) is a low-cost solution for bridge surface imaging. Providing top-down views, the airplanes flying at 1000 ft, can allow visualization of sub-inch (< 0.5 inch) cracks and joint openings on bridge decks or highway pavements. However, the site lighting may influence the quality of the images; surrounding tree shades and the highway wear surface reflectivity. Several examples of bridge evaluation using SFAP aerial photography are presented to demonstrate the capability of remote sensing as an effective tool for bridge construction monitoring and condition assessment. Several imaging issues are raised about analytical techniques that are necessary to ensure proper quantification of bridge problems, which include crack detection, movement determination, heavy trucking assessment, debris detection, channel width determination and environment assessment.

Along with the incessant advancement in optics, electronics and computer technologies during the last three decades, commercial digital video cameras have experienced a remarkable evolution, and can now be employed to measure complex motions of objects with sufficient accuracy, which render great assistance to structural displacement measurement in civil engineering. This paper proposes a computer vision-based approach for dynamic measurement of structures. One digital camera is used to capture image sequences of planar targets mounted on vibrating structures. The mathematical relationship between image plane and real space is established based on computer vision theory. Then, the structural dynamic displacement at the target locations can be quantified using point reconstruction rules. Compared with other tradition displacement measurement methods using sensors, such as accelerometers, linear-variable-differential-transducers (LVDTs) and global position system (GPS), the proposed approach gives the main advantages of great flexibility, a non-contact working mode and ease of increasing measurement points. To validate, four tests of sinusoidal motion of a point, free vibration of a cantilever beam, wind tunnel test of a cross-section bridge model, and field test of bridge displacement measurement, are performed. Results show that the proposed approach can attain excellent accuracy compared with the analytical ones or the measurements using conventional transducers, and proves to deliver an innovative and low cost solution to structural displacement measurement.

Wireless Smart Sensor Networks (WSSN) facilitates a new paradigm to structural health monitoring (SHM) for civil infrastructure. Conventionally, SHM systems employing wired sensors and central data acquisition have been used to characterize the state of a structure; however, wide-spread implementation has been limited due to difficulties in cabling, high equipment cost, and long setup time. WSSNs offer a unique opportunity to overcome such difficulties. Recent advances in sensor technology have realized low-cost, smart sensors with on-board computation and wireless communication capabilities, making deployment of a dense array of sensors on large civil structures both feasible and economical. Wireless smart sensors have shown their tremendous potential for SHM in recent full-scale bridge monitoring examples. However, structural damage identification in WSSNs, a primary objective of SHM, has yet to reach its full potential. This paper presents an implementation of the stochastic dynamic damage locating vector (SDDLV) method on the Imote2 sensor platform and experimental validation in a laboratory environment. The WSSN application is developed based on the Illinois SHM Project (ISHMP) Services Toolsuite (http://shm.cs.uiuc.edu), combining decentralized data aggregation, system identification, receptance-based damage detection, and global damage assessment. The laboratory experiment uses a three-dimensional truss structure with a network of Imote2 sensors for decentralized damage identification. Future efforts to deploy a long-term structural health monitoring system for a fullscale steel truss bridge are also described.

This paper presents an interim report on an international collaborative research project between the United States and Korea that fundamentally addresses the challenges associated with integrating structural health monitoring (SHM) system components into a comprehensive system for bridges. The objective of the project is to integrate and validate cutting-edge sensors and SHM methods under development for monitoring the long-term performance and structural integrity of highway bridges. A variety of new sensor and monitoring technologies have been selected for integration including wireless sensors, EM stress sensors and piezoelectric active sensors. Using these sensors as building blocks, the first phase of the study focuses on the design of a comprehensive SHM system that is deployed upon a series of highway bridges in Korea. With permanently installed SHM systems in place, the second phase of the study provides open access to the bridges and response data continuously collected as an internal test-bed for SHM. Currently, basic facilities including Internet lines have been constructed on the test-beds, and the participants carried out tests on bridges on the test road section owned by the Korea Expressway Corporation (KEC) with their own measurement and monitoring systems in the local area network environment. The participants were able to access and control their measurement systems by using Remote Desktop in Windows XP through Internet. Researchers interested in this test-bed are encouraged to join in the collaborative research.

The luminescent photoelastic coating (LPC) technique is an optical technique to measure the full-field strain on three-dimensional (3D) structural components. A luminescent dye within a photoelastic binder is excited with circular polarized light, and the corresponding coating emission intensity is detected via a digital camera for loaded and unloaded states of the specimen to which the coating is applied. Images are processed to find the relative change in emission with respect to camera analyzer position, and, subsequently, analyzed to determine maximum in-plane shear strain and the principal strain directions. For 3D structures with moderate movement or deflection in the field-of-view, especially when implementing an oblique excitation approach to separate the principal strains while accounting for non-strain related polarization changes due to surface inclination, the image analysis is preferably performed on a 3D grid. This study describes such an approach and discusses the analysis procedures to separate the principal strains and to obtain full-field strain distribution. The theoretical results are compared to experimental data from a 3D test specimen.