Carbon fiber reinforced cement (CFRC), which mainly composed of hardened cement and short cut carbon fibers, possesses piezoresistive effect, and could be used to produce new type of compressive stress sensors. As having character of low cost, good compatibility with concrete and high durability, CFRC sensor extraordinary adapt to be used in the field of long time health monitoring of concrete structures. Based on large quantity of duplicate tests, the influence of temperature and humidity on electrical specific resistance of CFRC was studied. The function of volume content of carbon fiber or silica fume on above influence is also discussed. Results show that specific resistance of CFRC will decrease with increase of temperature or relative humidity, and above changing have no relationship with carbon fiber or silica fume volume content.

Structural health monitoring (SHM) is important for reducing maintenance costs while increasing safety and reliability. Piezoelectric wafer active sensors (PWAS) used in SHM applications are able to detect structural damage using Lamb waves. PWAS are small, lightweight, unobtrusive, and inexpensive. PWAS achieve direct transduction between electric and elastic wave energies. PWAS are essential elements in the Lamb-wave SHM with pitch-catch, pulse-echo, and electromechanical impedance methods. Traditionally, structural integrity tests required attachment of sensors to the material surface. This is often a burdensome and time-consuming task, especially considering the size and magnitude of the surfaces measured (such as aircraft, bridges, structural supports, etc.). In addition, there are critical applications where the rigid piezoceramic wafers cannot conform to curved surfaces. Existing ceramic PWAS, while fairly accurate when attached correctly to the substance, may not provide the long term durability required for SHM. The bonded interface between the PWAS and the structure is often the durability weak link. Better durability may be obtained from a built-in sensor that is incorporated into the material. An in-situ fabricated smart sensor may offer better durability. This paper gives a review of the state of the art on the in-situ fabrication of PWAS using different approaches, such as piezoelectric composite approach; polyvinylidene fluoride (PVDF) approach. It will present the principal fabrication methods and results existing to date. Flexible PVDF PWAS have been studied. They were mounted on a cantilever beam and subjected to free vibration testing. The experimental results of the composite PWAS and PVDF PWAS have been compared with the conventional piezoceramic PWAS. The theoretical and experimental results in this study gave the basic demonstration of the piezoelectricity of composite PWAS and PVDF PWAS.

The objective of this paper is to advance the state-of-art of frequency-shift-based damage identification method using tunable piezoelectric transducer circuitry. More specifically, we aim at improving the current methodology [1] by developing a more accurate and efficient approach. The basic principle of this new approach is to include the high order terms in the eigensolution perturbation formulation, and use an iterative procedure in conjunction with a constrained optimization scheme. In addition, guidelines on how to tune the inductance in the circuit to best capture the damage features are proposed based on a detailed analysis of eigenvalue loci veering and variation of eigenvalue changes with respect to the changing inductance. Results show that more information of the structural damage features can be included in the vector of eigenvalue changes and sensitivity matrices if we tune the inductance inside the eigenvalue veering ranges. Numerical results on identifying single and multiple damages in a cantilever beam example are provided to demonstrate the accuracy of the improved method for structural damage identification.

For a novel method of characterize stress of concrete structure by measuring embedded ceramic disc, we establish a model of a piezoelectric ceramic disc under the situation mentioned above, and then the relationships between the complex coefficients and the equivalent circuit parameters are obtained. Derived from the piezoelectric equations with complex coefficients, the dissipation factors are related to the equivalent circuit parameters. Experimental results show that there are linear relationships between most of the equivalent parameters and the loadings applied on the concrete structure. The mechanisms of the results are discussed by use of the theory of moving domain walls and point defects. The results also support the method of estimating the stress by measuring the value of equivalent circuit parameters of piezoelectric ceramic.

Closed-loop control of electrostatic MEMS requires sensing to provide a feedback signal. We present an integrated sensor for charge and position that negligibly affects the open-loop dynamics, does not increase the device footprint, and may be easily fabricated. Numerical finite-element simulation, incorporating a realistic electrostatic field model, and experimental results validate the functionality of the sensor. Simulations show how the sensor may be used in conjunction with nonlinear control to provide full gap operation and improved transient performance. Nonlinear control is often considered too complex for convenient implementation, however the controller presented may be implemented using on-chip, local, integrated circuit components.

Accelerometer and displacement transducer are two common sensors used for structural displacement measurement. Due to their incapability of measuring static deflection of a structure, Global Positioning System (GPS) is developed as a novel sensor for measuring and monitoring both static and dynamic displacement responses of large civil engineering structures under gust winds. However, the accuracy of dynamic displacement measurement with GPS at the sub-centimeter to millimeter level depends on many factors such as required data update rate, satellite coverage, atmospheric effect, multi-path effect, and GPS data processing methods. Therefore, this paper focuses on the assessment of dynamic displacement measurement accuracy of GPS in two orthogonal directions. A 2-D motion simulation table is first developed as a test bed simulating various types of two perpendicular translational motions of tall buildings. The 2-D motion simulation table was then used to assess the performance of GPS through a series of field measurements in an open area. A band-pass filtering scheme is finally designed and applied to the table motion data recorded by the GPS. The comparison of the table motion recorded by the GPS with the original motion generated by the table shows that the GPS can measure sinusoidal or circular dynamic displacements accurately within certain amplitude and frequency ranges. The comparative results also demonstrate that the GPS can trace wind-induced dynamic responses of tall buildings satisfactorily.

A novel piezoelectric/fiber-optic system is developed for long-term health monitoring of aerospace vehicles and structures. The hybrid diagnostic system uses the piezoelectric actuators to input a controlled excitation to the structure and the fiber optic sensors to capture the corresponding structural response. The aim of the system is to detect changes in structures such as those found in aerospace applications (damage, cracks, aging, etc.). This system involves the use of fiber Bragg gratings, which may be either bonded to the surface of the material or embedded within it in order to detect the linear strain component produced by the excitation waves generate by an arbitrary waveform generator. Interrogation of the Bragg gratings is carried out using a high speed fiber grating demodulation unit and a high speed data acquisition card to provide actuation input. With data collection and information processing; is able to determine the condition of the structure. The demands on a system suitable for detecting ultrasonic acoustic waves are different than for the more common strain and temperature systems. On the one hand, the frequency is much higher, with typical values for ultrasonic frequencies used in non-destructive testing ranging from 100 kHz up to several MHz. On the other hand, the related strain levels are much lower, normally in the μstrain range. Fiber-optic solutions for this problem do exist and are particularly attractive for ultrasonic sensing as the sensors offer broadband detection capability.

Concrete-filled steel pipes are usually exposed in hostile environments such as seawater and deicing materials. The outside corrosion of the steel pipe can reduce the wall thickness and the corrosion-induced delamination of internal concrete can increase internal volume or pressure. In addition, the void that can possibly exist in the pipe reduces the bending resistance. To avoid structural failure due to this type of deterioration, appropriate inspection and repair techniques are to be developed. Guided wave techniques have strong potentials for this kind of inspection because of long-distance inspection capability. Among different transducer-coupling mechanism, electro-magnetic acoustic transducers (EMATs) give relatively consistent results in comparison to piezoelectric transducers since they do not need any couplant. In this study EMATs are used for transmitting and receiving cylindrical guided waves through concrete-filled steel pipes. Through time history curves and wavelet transform, it is shown that EMAT-generated cylindrical guided wave techniques have good potential for the interface inspection of concrete-filled steel pipes.

The performance of many multi-sensor systems can be significantly improved by using a priori environmental information and sensor data to plan the movements of sensor platforms that are later deployed with the purpose of improving the quality of the final detection and classification results. However, existing path planning algorithms and ad-hoc data processing (e.g., fusion) techniques do not allow for the systematic treatment of multiple and heterogeneous sensors and their platforms. This paper presents a method that combines Bayesian network inference with probabilistic roadmap (PRM) planners to utilize the information obtained by different sensors and their level of uncertainty. The uncertainty of prior sensed information is represented by entropy values obtained from the Bayesian network (BN) models of the respective sensor measurement processes. The PRM algorithm is modified to utilize the entropy distribution in optimizing the path of posterior sensor platforms that have the following objectives: (1) improve the quality of the sensed information, i.e., through fusion, (2) minimize the distance traveled by the platforms, and (3) avoid obstacles. This so-called Probabilistic Deployment (PD) method is applied to a demining system comprised of ground-penetrating radars (GPR), electromagnetic (EMI), and infrared sensors (IR) installed on ground platforms, to detect and classify buried mines. Numerical simulations show that PD is more efficient than path planning techniques that do not utilize a priori information, such as complete coverage, random coverage method, or PRM methods that do not utilize Bayesian inference.

With the discovery in plants of the proteinaceous forisome crystalloid (Knoblauch et al. 2003), a novel nastic non-living, ATP-independent biological material became available to the designer of smart materials for advanced actuating and sensing. The in vitro studies of Knoblauch et al. show that forisomes (1-3 micron wide and 10-30 micron long) can be repeatedly stimulated to contract and expand anisotropically by shifting either the ambient pH or the ambient calcium ion concentration. In a device, the energy required for the transformations would be provided electrochemically by mini-electrodes inducing pH variation. Because of their unique abilities to develop and reverse strains greater than 20% in time periods less than 1s , forisomes have the potential to outperform current smart materials (such as ATP-dependent actuators or synthetic hydrogels/polymers) as advanced, biomimetic, multi-functional, smart sensors or valves or actuators. To date, studies have been limited to questions of protein engineering explored by Knaublach et al. Probing forisome material properties is therefore an immediate need to lay the foundation for synthesizing forisome-based smart materials for health monitoring of structural integrity in civil infrastructure and aerospace hardware. Here, we use microfluidics to study the surface interaction between forisome and substrate and the conformational dynamics of forisomes within a confined geometry to lay the foundation for forisome-based smart materials synthesis with controlled and repeatable environment.

Health monitoring for reinforced concrete bridges and other large-scale civil infrastructure has received considerable attention in recent years. Traditional inspection methods (x-ray, C-scan etc.) are expensive and sometimes ineffective for large-scale structures. Piezoceramic transducers have emerged as new tools to health monitoring of large size structures due to the advantages of active sensing, low cost, quick response, availability in different shapes, and simplicity for implementation. In this research, piezoceramic transducers in the form of patches are used to detect internal cracks of a 6.1-meter long reinforced concrete bridge bent-cap. Piezoceramic patches are embedded in the concrete structure at pre-determined spatial locations prior to casting. This research can be considered as a continuation of an early work, where four piezoceramic patches were embedded in planar locations near one end of the bent-cap. This research involves ten piezoceramic patches embedded at spatial locations in four different cross-sections. To induce cracks in the bent-cap, the structure is subjected to loads from four hydraulic actuators with capacities of 80-ton and 100-ton. In addition to the piezoceramic sensors, strain gages, LVDTs, and microscopes are used in the experiment. During the experiment, one embedded piezoceramic patch is used as an actuator to generate sweep sinusoidal waves, and the other piezoceramic patches are used as sensors to detect the propagating waves. With the increase of number of and severity of cracks, the magnitude of the sensor output decreases. Wavelet packet analysis is used to analyze the recorded sensor signals. A damage index is formed on the basis of the wavelet packet analysis. The experimental results show that the proposed methods using piezoceramic transducers along with the damage index based on wavelet packet analysis is effective in identifying the existence and severity of cracks inside the concrete structure. The experimental results also show that the proposed method has the ability to predict the failure of concrete as verified by results from conventional microscopes (MS) and LVDTs.

A variation of dielectric response with deformation, called dielectrostriction, provides a new approach for in-line monitoring properties and structure of materials. The dielectrostriction effect resembles a well-known birefringence phenomenon which has been widely used for NDE of transparent materials. While birefringence is described by the stress-optic rule, the stress-dielectric rule applies to dielectrostriction. However, dielectrostriction measurements can be applied to both transparent and opaque dielectric materials, require a much simpler measurement technique, are capable of measuring local stresses/strains and can be implemented for material processing and health monitoring of structures. Planar capacitor sensor setup is implemented to detect the dielectrostriction effect in both liquid and solid polymers. Dielectrostriction effect and the stress-dielectric relationship are studied for solid polycarbonate subjected to uniaxial tensile load. Similar results are obtained for liquid polymers in oscillatory shear flow.

Smart structure technology has become a key technology in the design of modern, so-called intelligent, civil, mechanical and aerospace (CMA) systems. One key aspect for a successful design is the communication between structure and controller, for which sensors and actuators are responsible. In continuous CMA systems a crucial point is the distribution of sensors to obtain proper information and the distribution of actuators to influence the behavior of the structure properly. Finding these distributions is the topic of this paper. A common strategy for the modeling of continuous CMA systems is based on the linearized theory of elasticity; within this paper we consider a three-dimensional linear elastic background body with sources of self-stress. These self-stresses can be produced by smart materials, which exhibit the well known strain induced actuation mechanism; as many of the modern smart materials have both, actuation and sensing properties, we assume the sensing be based on the same mechanism. We show that a suitable distribution of sensors results into a sensor signal proportional to kinematical entities (e.g. displacement), whereas a suitable distribution of the actuation results in actuators that act like dynamical entities (e.g. force). Our design strategy automatically results into collocated sensor/actuator pairs; this design is highly suitable from a control point of view, because it allows the application of common control strategies in a straightforward manner; e.g. a simple PD-controller ensures stability of the closed loop system.

We describe Sonic Infrared Imaging NDE for materials and structures. In this imaging technique, a short ultrasonic pulse is applied to the structure/material to cause heating of the defects, while an infrared camera images the time evolution of the heating effect to identify the defective areas in the target. The heating effect is astonishing. In this paper, we'll include our study of Sonic IR imaging NDE on aircraft structure specimens, automotive specimens, etc. for metals, composites, ceramics, addressing fatigue cracks, and delaminations/disbonds. Some fundamental issues related to Sonic IR imaging NDE are discussed in this paper as well.

In an urban highway network system such as Tokyo Metropolitan Expressway, to detect conditions of road pavement and expansion joints is a very important issue. Although accurate surface condition can be captured by using a road profiler system, the operating cost is expensive and development of a simpler and more inexpensive system is really needed to reduce monitoring cost. "Vehicle Intelligent Monitoring System (VIMS)" developed for this purpose is described in this paper. An accelerometer and GPS are installed to an ordinary road patrol car. GPS together with a PC computer are used to measure the road surface condition and to identify the location of the vehicle, respectively. Dynamic response of the vehicle is used as a measure of the road pavements surface condition as well as the expansion joints. A prototype of VIMS is installed to a motor car and measurement is made at the actual roads. Accuracy of measuring result and effectiveness of this system are demonstrated; the outline of the system and some of the measurement results are reported herein.

In recent years, structural health monitoring (SHM) has been an important research area for designing and evaluating reliability of civil engineering structures. With the development of the technologies in sensing, wireless communication, and micro electro mechanical systems (MEMS), wireless sensing technique has been caused much more attentions and used gradually in the SHM. The wireless sensors and network has low capital and installation costs as well as ensures more reliability in the communication of sensor measurements, but there exists a key problem of the finite energy and this is a primary design constraint. Therefore, some measures must be adopted to make wireless sensor work more effectively. In this paper, a kind of wireless sensor with 3 variables, temperature- acceleration- strain, is proposed. Such several modules as sensing unit, micro-processing unit, power unit and wireless transceiver are constructed using commercially available parts, and integrated into a complete wireless sensor. The fusion arithmetic of the temperature-acceleration is embedded in the wireless sensor so that the measured acceleration values are more accurate. Measures are also adopted to reduce the energy consumption. Experimental results show that, the wireless sensor can monitor the temperature-acceleration-strain of the structures at real time and precisely, and pre-process and pack the measured data to reduce the data volume to be transmitted and save energy.

This paper presents a Bond graph approach to analyzing the energy efficiency of a self-powered wireless pressure sensor for pressure measurement in an injection mold. The sensor is located within the mold cavity and consists of an energy converter, an energy modulator, and a signal transmitter. Pressure variation in the mold cavity is extracted by the energy converter and transmitted through the mold steel in the form of ultrasound pulses to a signal receiver located outside of the mold. Through Bond graph models, the energy efficiency of the sensing system is characterized as a function of the configuration of the piezoceramic stack within the energy converter, and the pulsing cycle of the energy modulator. The obtained energy model is then used to identify the minimum level of signal intensity required to ensure successful detection of the ultrasound signals by the signal receiver. The Bond graph models established can be further used to optimize the design of the sensing system and its constituent components.

Conventional wireless sensors for structural health monitoring do not accommodate the need of high frequency data acquisition. Lack of development of this type of wireless smart sensors will without doubt hinder the applications of active diagnostic methods, normally used in local damage interrogation. In this paper, a novel wireless smart sensor design, using FPGA as co-controller with ultra sensing capability, is presented. The development and some outstanding issues of the sensor are discussed in detail, and a preliminary experimental result is given to verify the effectiveness of this wireless smart sensor design.

In recent years, the importance of Structural Health Monitoring has been recognized but an SHM system still confronts serious problems related to complexity and cost in practical use. To solve these problems, the authors have developed the simple and smart SHM system by integrating self-diagnosis material and a wireless data measurement device. By installing this SHM system, it is possible to detect damage to structures easily even after a large earthquake or other disaster and also to inspect possible deterioration of a structure in a short time. As a practical matter this SHM system is expected to be very reliable, and when it is mass-produced it should have a low cost. To confirm the utility of the damage detection of a building after a large earthquake, the pre-production system was installed in a specimen simulating the beam-to-column connection part in a mid-size conventional reinforced concrete building, and a loading test was performed on the specimen. The effectiveness of the proposed system is demonstrated by the test results.

This paper presents the preliminary results of an investigation on the application of Field Programmable Gate Arrays (FPGAs) to civil infrastructure health monitoring. An off-the-shelf FPGA development board available at a comparable price to microprocessor development boards is adopted in this study. Advantages, disadvantages, feasibility and design concerns when using such a reconfigurable hardware architecture for implementing algorithms for structural health monitoring in a wireless sensor unit are studied in a showcase of implementing Fast Fourier Transform (FFT) in a wireless data transmitting setting.

Health Monitoring is very important for large structures like suspension- and cable-stayed bridges, offshore platforms, tall buildings and so on. Due to recent developments in new sensor systems, wireless communication systems, Internet-based data sharing and monitoring, advanced technologies for structure health monitoring (SHM) have been caused much more attentions, in which the wireless sensor network is recently received special interests. Wireless sensor networks (WSNs) consist of large populations of wirelessly connected nodes, capable of computation, communication, and sensing. In this paper, a wireless sensor networks based health monitoring system for tall buildings has been explored integrated with wireless sensing communication, computation, data management and data remote access via Internet. Firstly, a laboratory prototype was designed and developed to demonstrate the feasibility and validity of the proposed system. Wireless sensor nodes were deployed on a test structure, the data being sensed by the sensor nodes in the network is eventually transmitted to a base station, where the information can be accessed. Through a Wireless Local Area Network (WLAN, IEEE802.11b), the simulated data was transferred among personal computers and wireless sensor nodes peripherals without cables. And then, a Wireless Sensor Network (WSN) includes eight sensor nodes and one base station was installed on Di Wang Tower to verify the performance of the present system in-depth. Finally, comparisons between WSN and cable-based monitoring analytical acceleration responses of field measurement have been performed. The proposed system is shown to be effective for structural health monitoring.

This paper describes a damage identification method for structures mainly subject to bending load, considering the applicability in a decentralized computing environment of wireless sensor networks. A modal flexibility-based damage indices that have simple and intuitive physical interpretation is presented. Since the proposed damage indices are computed using angular mode shapes of the lowest several modes, MEMS gyroscopes are adopted as the sensing device. The damage evaluation algorithm is then modified to a decentralized form, which is to be implemented as the local computation of mode separation at each sensor unit and the global computation of the damage index at the central monitoring station. Experiments using a bolted beam are conducted to show the applicability of the proposed algorithm to the detection of loose bolt failures.

Efficiently utilizing the power available to increase service life of sensors is one of the key challenges in the design and operation of a wireless sensor network for system health monitoring. This paper addresses energy-efficient computation on the sensor node level by presenting an in-network data processing scheme. The scheme is motivated by the concept of Dynamic Voltage Scheduling (DVS), which minimizes energy consumption through dynamically adjusting the voltage supply and clock frequency of the individual sensors. Unlike the traditional approach where a uniform data processing speed is employed for all the sensors, the proposed scheme adjusts the speed of each sensor individually to utilize the processor idle time for prolonged computation latency. The advantage of such a scheme becomes increasingly evident when a large amount of raw data needs to be processed locally at each sensor to reduce the amount of overall data communication. An application model using vibration-base sensory nodes for machine health monitoring was constructed to test the new data processing scheme. Simulation has shown that energy saving of up to 29% could be achieved.

A novel approach to determine very accurately multiple parametric variations by analyzing sensitivity vector fields is proposed. These sensitivity vector fields describe changes in the state space attractor of the dynamics and system behavior when parametric variations occur. The parametric changes are reconstructed by analyzing the deformation of the attractor in state space (characterized by means of the sensitivity vector fields). An optimal set of basis functions in the vector space formed by the sensitivity fields is obtained and used to successfully identify test cases involving multiple simultaneous parametric variations. The method presented is shown to be robust over a wide range of parametric variations and to perform well in the presence of noise. The main application and the emphasis of the proposed technique is on detecting multiple simultaneous damages in vibration-based structural health monitoring.

In this paper, we design a sensor network system with a host computer and a sensor terminal, which has local data processing by using off-the-shelf hardware. If all data, which are obtained by many sensors, are transmitted to the host computer and data processing is centralized at the host computer, the task of the host computer becomes large. Therefore, we consider that tasks of the host computer are decreased by making each sensor unit to share data processing locally and transmit results to the host computer. The sensor terminal consists of an accelerometer, an analog-to-digital (A/D) converter and the T-Engine (M32104) has capacity of data acquisition, processing and transmission in real time. We use the wavelet transform as an algorithm of data processing. The host computer can receive the result of the wavelet transform by sending the request to the sensor terminal. However, The host computer and the sensor terminal are connected by LAN cables. Next version of the prototype has wireless LAN. We demonstrate the performance of the sensor network system by applying this system to a structural model and make the sensor terminal execute locally the wavelet transform.

Wireless networks allow monitoring systems to be made non-invasive. This is required when solving the problem of monitoring cultural heritage and is also very convenient on other civil structures such as bridges and buildings. This paper reflects the authors' efforts toward the optimization of the architecture of a wireless sensor network for civil engineering applications.

Piezoelectric wafer active sensors (PWAS) are small, inexpensive, unobtrusive devices capable of generating and detecting Lamb waves in thin-wall structures. PWAS are directly attached to the surface of a metallic structure or inserted between the layers of a composite structure. PWAS interact with the structure through surface shear stresses that couple the in-plane motion of the PWAS with the in-plane motion of the structure undergoing Lamb wave motion. The paper will present a simulation of the Lamb wave interaction between PWAS and host structure using analytical solutions in axisymmetric formulation. The Bessel function solutions are used to model the Lamb waves emanating from the PWAS. The time domain Fourier transform is used to process the excitation signal into its frequency components. The frequency domain excitation is used to modulate the Fourier transform of the Bessel function solution in the frequency domain. Inverse Fourier transform is used to return from the frequency domain in to the time domain. Simulations will be presented for symmetric and antisymmetric Lamb-wave modes at various frequencies and mode numbers. The influence of the mode number and frequencies upon the efficiency of the Lamb wave interaction between PWAS and host structure is studied and exemplified with numerical solutions and visualizations. Experiments on different kind PWAS and plate material, thickness, and dimension, will be illustrated and compared with the simulations. The aim of the paper will be then to evidence that the illustrated method is able to predict the Lamb-wave tuning with PWAS transducers in different structures.

Electro-mechanical impedance method is emerging as an important and powerful technique for structural health monitoring. The E/M impedance method utilizes as its main apparatus an impedance analyzer that reads the in-situ E/M impedance of the piezoelectric wafer active sensors (PWAS) attached to the monitored structure. Present-day impedance analyzer equipments (e.g. HP4194) are bulky, heavy and expensive laboratory equipment that cannot be carried into the field for on-site structural health monitoring. To address this issue, several investigators have explored means of miniaturizing the impedance analyzer making the impedance analyzer more compact and field-portable. In this paper we present an improved algorithm for efficient measurement of the E/M impedance using PWAS transducers. Instead of using a sine wave as the excitation signal to the PWAS and slowly changing its frequency, our method utilizes a chirp signal which is abundant in frequency components. By applying Fast Fourier Transform (FFT) to both the input and response signals, the impedance spectrum of the PWAS is acquired. The algorithm was implemented and tested in a real-time system, which consists of excitation signal generation module, voltage and current measurement module and digital signal acquisition module. The size and the implementation of the overall system using either a laptop or a digital signal processor (DSP) are also discussed. Finally, practical results are presented and comparatively examined.

Lamb waves at ultrasonic frequencies travel with little attenuation in thin elastic plates, and we demonstrate their use in pulse-echo behavior to monitor plate integrity. We envision using a single PZT wafer-type transducer to generate waves and to receive reflections from distant flaw or boundary locations. However, Lamb waves generally have multiple modes, each of them highly dispersive, and in consequence pulse dispersion can become pronounced and can make difficult or impossible the interpretation of pulse-echo responses. We show that selective generation of the S0 wave will overcome those difficulties; therefore, selection of transducer dimensions and pulse characteristics to achieve selective generation should be considered mandatory for most intended applications. We first review the work of others identifying a basic relationship between transducer dimension and excitation frequency for selective generation of the S0 wave. We then summarize our extensive experimental studies of wafer-type transducers with particular attention to S0 and A0 mode behavior, both in transmission and reception. We next report our two-dimensional finite element simulation of the same problem performed in FEMLAB, requiring transient simulation of the coupled electromechanical problem. We simulate the piezoelectric response of the wafer-type transducer coupled to the elastic plate, both as transmitter and receiver, as well as the development of Lamb waves within the source region and their subsequent propagation along the plate. Simulations illustrate the development and separation of the S0 and A0 modes and reproduce the expected group velocities and dispersion behavior. We show good agreement between our experiments and our simulations regarding S0 mode behavior, and we summarize the results to guide a designer in choosing transducer dimensions. In particular, good selectivity between the S0 and A0 mode generation can be obtained with appropriate choice of transducer size and center frequency. We show the results of experiments on an aluminum plate in which excitation of a single PZT wafer-type transducer at 6.5 V (peak-to-peak) produces reflected signals of ample strength (tens of mV) from distant boundaries and from partial thickness flaws.

Structural Health Monitoring technologies have the potential to reduce life-cycle costs and improve reliability for aircraft. Previous research conducted by the Metis Design Corporation has demonstrated the ability of Lamb wave methods to provide reliable information regarding the presence, location and type of damage in coupon-level specimens. Several critical system components have been developed during the course of this research, including circuitry and packaging, and integrated into the Monitoring & Evaluation Technology Integration (M.E.T.I.) Disk. In order to demonstrate the validity of M.E.T.I.-Disks for aircraft applications, a testbed has been fabricated by dividing a 1/8" plate of aircraft-grade aluminum into four equal quadrants with several c-channels. M.E.T.I.-Disk nodes were then placed in the center of each quadrant, and data was collected and interpreted by the METISv2.10 software package. The results produced by this software validated the M.E.T.I.-Disk by using a single undamaged cell to calibrate the system, and then correctly identify that there was no damage present in the remaining quadrants. Next, representative damage was introduced into several combinations of the quadrants, and the software was executed again to query the structure. The resulting data revealed the presence and location of damage, while still identifying the two undamaged regions.

Piezoelectric materials have been widely used in ultrasonic nondestructive testing (NDT). PZT ceramics can be used to receive and generate surface acoustic waves. It is a common application to attach PZT transducers to the surface of structures for detecting cracks in nondestructive testing. However, not until recently have piezoelectric polymers attracted more and more attention to be the material for interdigitated (IDT) surface and guided-wave transducers. In this paper, an interdigitated gold-on-polyvinyldine fluoride (PVDF) transducer for actuating and sensing Lamb waves has been introduced. A specific etching technology is employed for making the surface electrodes into a certain finger pattern, the spacings of which yield different single mode responses of Lamb waves. Experiments have been performed on steel plates. Results from PVDF IDT sensors have been compared with those from PZT transducers for verification.

This work addresses the 3-D elasticity modeling of the guided wave (GW) fields excited by piezoelectric actuators in various configurations for isotropic structures. First, a general derivation for the GW field excited by an arbitrary shape, finite dimension, and surface-bonded piezo actuator in isotropic plates is presented. This is then used to generate solutions for the specific cases of ring-shaped and rectangular piezo actuators and rectangular Macro Fiber Composite actuators. An expression for the response of a piezo-sensor in a GW field is developed. Experimental verification supporting the model is provided. Excellent correlation is found between theoretical and experimental results.

In this paper, a wavelet-based built-in damage detection and identification algorithm for carbon fiber reinforced polymer (CFRP) laminates is proposed. Lamb waves propagating in laminates are first modeled analytically using higher-order plate theory and compared them with experimental results in terms of group velocity. Distributed piezoelectric transducers are used to generate and monitor the fundamental ultrasonic Lamb waves in the laminates with narrowband frequencies. A signal processing scheme based on wavelet analysis is applied on the sensor signals to extract the group velocity of the wave propagating in the laminates. Combined with the theoretically computed wave velocity, a genetic algorithms (GA) optimization technique is employed to identify the location and size of the damage. The applicability of this proposed method to detect and size the damage is demonstrated by experimental studies on a composite plate with simulated delamination damages.

Finite element model updating of structures usually results in a nonlinear optimization problem. Finding an optimization technique with high efficiency is one of the key issues for model updating. A hybrid optimization technique is proposed in this paper, which draws together the global searching capability of the chaos-based optimization technique and high searching efficiency of the trust-region optimization method. The hybrid approach is demonstrated to be more efficient and prone to obtain a global minimum as compared to conventional methods using a two dimensional test function. Then this hybrid method is employed to update a 14-bay frame model. An optimization problem for model updating using modal frequencies and modal shapes is formulated. Studies using numerically simulated data and experimental data show that the proposed hybrid optimization technique is very promising for structural model updating.

This study investigates the possibility of injecting parametric features into nonparametric identification techniques like neural networks in modeling nonlinear dynamic restoring forces. This affords the potential of creating relationships between model parameters in data-driven techniques and phenomenological behaviors in physics-based modeling, which is prompted by the needs in structural health monitoring and damage detections. Here a linear sum of sigmoidal basis functions is used in modeling nonlinear hysteretic restoring forces of single-degree-of-freedom oscillators under the force-state mapping formulation to showcase this idea. A constructive approach is proposed to guide the neural network initial design, where the number of hidden layers and hidden nodes as well as the initial values of the weights and biases are decided upon the characteristics of the nonlinear restoring force to be modeled rather than through indiscriminate numerical initialization schemes. Numerical simulations are presented to demonstrate the efficiency and engineered feature of this approach. A training example is provided to show that this approach enables neural networks to carry either physical or phenomenological "meaning" while remaining adaptive and thus powerful in system identification.

A new strategy for structural control systems using viscous dampers is proposed. When we use some energy absorption devices, such as viscous dampers, in a building structure, the devices are uniformly distributed over the building so that the input energy should not concentrate in a specific story. However, this design strategy is not always the optimum one. A unique strategy that does not utilize the uniform distribution of dampers is presented here. Many advantages exist in the system that does not have uniformly distributed dampers. First, in the stories which do not require dampers, more freedom for using the floor space is possible. In addition, this fact results in lowering the cost as well by allocating the dampers to limited stories. By simplifying the flow of energy absorption, the structural reliability is significantly improved. The simplified energy flow in the structure will enhance the feasibility of the structural health monitoring system. In this paper, it is also shown that by softening appropriately the stiffness of the story to which dampers are installed, it is possible to raise the energy absorption efficiency without causing concentration of the drift. We define the modal concentration ratio using complex modal vectors to obtain optimal story stiffness and the capacity of viscous dampers for achieving the desired damping ratio. The performances of the systems were carefully evaluated by conducting nonlinear dynamic response analyses subject to several large earthquakes. The analysis models for the structures were the lumped mass models considering shear deformation. The dampers attached to the structure were modeled as Maxwell models to incorporate the stiffness of the supporting members.

This paper presents a non-destructive evaluation (NDE) technique for detecting damages on a jointed steel plate on the basis of the time of flight and wavelet coefficient, obtained from wavelet transforms of Lamb wave signals. Probabilistic neural networks (PNNs) and support vector machines (SVMs), which are tools for pattern classification problems, were applied to the damage estimation. Two kinds of damages were artificially introduced by loosening bolts located in the path of the Lamb waves and those out of the path. The damage cases were used for the establishment of the optimal decision boundaries which divide each damage class’s region from the intact class. In this study, the applicability of the PNNs and SVMs was investigated for the damages in and out of the Lamb wave path. It has been found that the present methods are very efficient in detecting the damages simulated by loose bolts on the jointed steel plate.

This paper addresses a novel type of hybrid carbon fiber-reinforced polymer (HCFRP) sensors suitable for the structural health monitoring (SHM) of civil engineering structures. The HCFRP sensors are composed of different types of carbon tows, which are active materials due to their electrical conductivity, piezoresistivity, excellent mechanical properties and resistance to corrosion. The HCFRP sensors are designed to comprise three types of carbon tows-high strength (HS), high modulus (HM) and middle modulus (MM), in order to realize a distributed and broad-based sensing function. Two types of HCFRP sensors, with and without pretreatment, are fabricated and investigated. The HCFRP sensors are bonded with epoxy resins on the bottom concrete surface of RC beam specimens to monitor the average strain, the initiation and propagation of cracks. The experimental results indicate that such kinds of sensors are characterized with broad-based and distributed sensing feasibilities. As a result, the structural health of the RC beams can be monitored and evaluated through characterizing the relationships between the change in electrical resistance of the HCFRP sensors, the average strain and the crack width of the RC beams. In addition, it is also revealed that the damages can also be located by properly adding the number of electrodes.

The Terra-Scope system is an affordable 4-D down-hole seismic monitoring system based on independent, microprocessor-controlled sensor Pods. The pods are nominally 50 mm in diameter, and about 120 mm long. They are expected to cost approximately $6000 each. An internal 16-bit, extremely low power MCU controls all aspects of instrumentation, eight programmable gain amplifiers, and local signal storage. Each pod measures 3-D acceleration, tilt, azimuth, temperature, and other parametric variables such as pore water pressure and pH. The following parameters are independently controllable at each pod: pre-trigger length, post-trigger length, trigger time stamp, sampling rate, trigger level, trigger parameters, non-volatile storage, and calibration and self-evaluation. Each Pod communicates over a standard digital bus (e.g. RS-485) through a complete web-based GUI interface, and has a power consumption of less than 400mW. Three-dimensional acceleration is measured by pure digital force-balance MEMS-based accelerometers. These accelerometers have a dynamic range of more than 115 dB and a frequency response from DC to 1000 Hz. The accelerometer chip uses a 5th order delta-sigma feedback loop to yield a noise floor of less than 30 ngrms/√Hz. Accelerations above 0.2 g are measured by a second set of MEMS-based accelerometers, giving a full 160 dB dynamic range. The prototype of the device is currently undergoing evaluation. The first array will be installed in the fall of 2005.

In this paper, the calibration and workability of magnetoelastic (ME or EM) stress sensors for large steel cables used in Qiangjiang 4th bridge in China are discussed. As an engineering application of magnetoelasticity, EM sensors make non-contact stress monitoring possible for steel hangers and post-tensioned cables on suspension and cable-stayed bridges, and other ferromagnetic structures. By quantifying the correlation of tension with magnetic properties represented by the relative permeability of the steel structure itself, the EM sensor inspects the loading level of the steel structure. The tension dependence of the relative permeability and the temperature influence was calibrated. The results revealed that the magnetoelasticity of the multi-wire hangers is consistent with one another, while the post-tensioned cables are similar to single wires. Cable stress monitoring on Qiangjiang (Qj) 4th bridge demonstrated the reliability of the EM sensors in safety evaluation of bridge.

New type of distributed coaxial cable sensors for health monitoring of large-scale civil infrastructure was recently proposed and developed by the authors. This paper shows the results and performance of such sensors mounted on near surface of two flexural beams and a large scale reinforced concrete box girder that was subjected to twenty cycles of combined shear and torsion. The main objectives of this health monitoring study was to correlate the sensor's response to strain in the member, and show that magnitude of the signal's reflection coefficient is related to increases in applied load, repeated cycles, cracking, crack mapping, and yielding. The effect of multiple adjacent cracks, and signal loss was also investigated.

In recent years, a new class of cementitious composite has been proposed for the design and construction of durable civil structures. Termed engineered cementitious composites (ECC), ECC utilizes a low volume fraction of short fibers (polymer, steel, carbon) within a cementitious matrix resulting in a composite that strain hardens when loaded in tension. By refining the mechanical properties of the fiber-cement interface, the material exhibits high tolerance to damage. This study explores the electrical properties of ECC materials to monitor their performance and health when employed in the construction of civil structures. In particular, the conductivity of ECC changes in proportion to strain indicating that the material is piezoresistive. In this paper, the piezoresistive properties of various ECC composites are thoroughly explored. To measure the electrical resistance of ECC structures in the field, a low-cost wireless active sensing unit is proposed. The wireless active sensing unit is capable of applying DC and AC voltage signals to ECC elements while simultaneously measuring their corresponding voltages away from the signal input. By locally processing the corresponding input-output electrical signals recorded by the wireless active sensing units, the magnitude of strain in ECC elements can be calculated. In addition to measuring strain, the study seeks to correlate changes in ECC electrical properties to the magnitude of crack damage witnessed in tested specimens. A large number of ECC specimens are tested in the laboratory including a large-scale ECC bridge pier laterally loaded under cyclically repeated drift reversals. The novel self-sensing properties of ECC exploited by a wireless monitoring system hold tremendous promise for the advancement of structural health monitoring of ECC structures.

A research effort has been launched at the University of Trento, aimed at developing an innovative distributed construction system based on smart prefabricated concrete elements allowing for real-time condition assessment of civil infrastructures. So far, two reduced-scale prototypes have been produced, each consisting of a 0.2 by 0.3 by 5.6m RC beam specifically designed for permanent instrumentation with 8 long-gauge Fiber Optics Sensors (FOS) at the lower edge. The sensors employed are Fiber Bragg Grating (FBG) -based and can measure finite displacements both in statics and dynamics. The acquisition module uses a single commercial interrogation unit and a software-controlled optical switch, allowing acquisition of dynamic multi-channel signals from FBG-FOS, with a sample frequency of 625 Hz per channel. The performance of the system underwent validation I n the laboratory. The scope of the experiment was to correlate changes in the dynamic response of the beams with different damage scenarios, using a direct modal strain approach. Each specimen was dynamically characterized in the undamaged state and in various damage conditions, simulating different cracking levels and recurrent deterioration scenarios, including concrete cover spalling and partial corrosion of the reinforcement. The location and the extent of damage are evaluated by calculating damage indices which take account of changes in frequency and in strain-mode-shapes. This paper presents in detail the results of the experiment and demonstrates how the damage distribution detected by the system is fully compatible with the damage extent appraised by inspection.

An innovative smart shape memory alloy (SMA) -based damper/displacement transducer, which had comprehensive energy dissipation and strain self-sensing abilities (i.e. electric resistance vs. applied strain relationship) simultaneously, was proposed in this paper. This smart SMA-based damper/displacement transducer had three characteristics: 1) SMA wires in the damper/transducer were always elongated during the entire excitation; 2) SMA wires dissipated energy with re-centering ability due to pseudoelasticity; 3) SMA damper/transducer could simultaneously play the role of displacement transducer due to the strain self-sensing property of SMA wires in the damper. Such smart SMA-based damper/displacement transducer, incorporated into a building or a bridge, provided the potential to rapidly assess post-earthquake safety of structures. A large number of tests were conducted firstly, on the hysteresis stress-strain-electric resistance relationship of NiTi SMA wires (diameter 1.2mm). These tests were carried out under sinusoidal excitations with different loading frequencies at room temperature. The experimental results indicated that the pseudoelastic hysteresis loops of the SMA wires were dependent on loading frequency. In addition, the sensitivity coefficient of electric resistance vs. applied strain of the NiTi wires was identified to be 6.466 from the test results, which was independent of the loading frequency. Finally, shake table tests for a scaled 5-story steel frame, with the said smart SMA dampers/displacement transducers at the first story, subjected to various earthquake excitations, were conducted. The results of the shake table tests indicated that not only could the smart SMA damper/displacement transducers suppress structural seismic response effectively, but also it could monitor structural interstory drifts accurately.

We describe the design, fabrication, testing and application (in structural experiments) of our 2004 (second generation) MEMS device, designed for acoustic emission sensing based upon experiments with our 2002 (first generation) device. Both devices feature a suite of resonant-type transducers in the frequency range between 100 kHz and 1 MHz. The 2002 device was designed to operate in an evacuated housing because of high squeeze film damping, as confirmed in our earlier experiments. In additional studies involving the 2002 device, experimental simulation of acoustic emissions in a steel plate, using pencil lead break or ball impact loading, showed that the transducers in the frequency range of 100 kHz-500 kHz presented clearer output signals than the transducers with frequencies higher than 500 kHz. Using the knowledge gained from the 2002 device, we designed and fabricated our second generation device in 2004 using the multi-user polysilicon surface micromachining (MUMPs) process. The 2004 device has 7 independent capacitive type transducers, compared to 18 independent transducers in the 2002 device, including 6 piston type transducers in the frequency range of 100 kHz to 500 kHz and 1 piston type transducer at 1 MHz to capture high frequency information. Piston type transducers developed in our research have two uncoupled modes so that twofold information can be acquired from a single transducer. In addition, the piston shape helps to reduce residual stress effect of surface micromachining process. The center to center distance between etch holes in the vibrating plate was reduced from 30 μm to 13 μm, in order to reduce squeeze film damping. As a result, the Q factor under atmospheric pressure for the 100 kHz transducer was increased to 2.37 from 0.18, and therefore the vacuum housing has been eliminated from the 2004 device. Sensitivities of transducers were also increased, by enlarging transducer area, in order to capture significant small amplitude acoustic emission events. The average individual transducer area in the 2004 device was increased to 6.97 mm² as compared to 2.51 mm² in the 2002 device. In this paper, we report the new experimental results on the characterization of the 2004 device and compare them with analytical results. We show improvements in sensitivity as measured by capacitance and as measured by pencil lead break experiments. Improvement in damping is also evaluated by admittance measurement in atmosphere. Pencil lead break experiments also show that transducers can operate in atmospheric pressure. Finally, we apply the device to acoustic emission experiments on crack propagation in a steel beam specimen, precracked in fatigue, in a four-point bending test.

Health monitoring is becoming an increasingly valuable tool for assessment of aging infrastructure in urban zones. For such applications, Global Positioning Systems (GPS) present a promising monitoring technique-one that is able to capture the total displacements of a structure. However, due to the relative infancy of this technology, there are still issues to be resolved, including the characterization and removal of multipath effects. This paper discusses the manifestation and removal of multipath errors by examining the full-scale response of a tall building to demonstrate the accuracy of high precision GPS in comparison with traditional sensors like accelerometers.

We describe the design of a system for wildfire monitoring incorporating wireless sensors, and report results from field testing during prescribed test burns near San Francisco, California. The system is composed of environmental sensors collecting temperature, relative humidity and barometric pressure with an on-board GPS unit attached to a wireless, networked mote. The motes communicate with a base station, which communicates the collected data to software running on a database server. The data can be accessed using a browser-based web application or any other application capable of communicating with the database server. Performance of the monitoring system during two prescribed burns at Pinole Point Regional Park (Contra Costa County, California, near San Francisco) is promising. Sensors within the burn zone recorded the passage of the flame front before being scorched, with temperature increasing, and barometric pressure and humidity decreasing as the flame front advanced. Temperature gradients up to 5 C per second were recorded. The data also show that the temperature slightly decreases and the relative humidity slightly increases from ambient values immediately preceding the flame front, indicating that locally significant weather conditions develop even during relatively cool, slow moving grass fires. The maximum temperature recorded was 95 C, the minimum relative humidity 9%, and barometric pressure dropped by as much as 25 mbar.

Honeywell International has developed and flight-tested a Corrosion and Corrosivity Monitoring System (C2MS). The C2MS detects galvanic corrosion in the main gearbox feet fasteners of helicopters. In addition, it monitors the environmental conditions inside the main floorboard compartment to determine the need for structural maintenance. The C2MS sensor on a main gearbox feet fastener sends a small electrical signal through the fastener and housing to measure the conductivity of the assembly. The measured conductivity value is used to determine if galvanic corrosion is present in the fastener assembly. The floorboard compartment sensors use a surrogate metal coupon to measure the corrosivity of the environment. The information from this sensor is used to recommend an extension to the calendar-based maintenance schedule. Fleet-wide information can be gathered by the system. The C2MS uses two Data Collection Units (DCUs) to store the corrosion data: one for the main gearbox feet fasteners and one for the main floorboard compartment. The DCU design addresses the issues of long battery life for the C2MS (greater than 2 years) and compactness. The data from the DCUs is collected by a personal digital assistant and downloaded to a personal computer where the corrosion algorithms reside. The personal computer display provides the location(s) of galvanic corrosion in the main gearbox feet fasteners as well as the recommended date for floorboard compartment maintenance. This paper discusses the methodology used to develop the C2MS software and hardware, presents the principles of the galvanic corrosion detection algorithm, and gives the laboratory and flight test results that document system performance in detecting galvanic corrosion (detection and false alarm rate). The paper also discusses the benefits of environmental sensors for providing a maintenance scheduling date.

The prototype sensors provide a low-cost method to detect the onset of corrosion in concrete structures using a noninvasive approach. The embedded sensors are wirelessly powered by inductive coupling and do not require batteries. Unlike traditional techniques for detecting corrosion which require an electrical connection to the embedded reinforcement, the sensors are self-contained and provide information about the environmental conditions within the concrete in the vicinity of the sensor. The sensors were originally envisioned to provide binary information about the onset of corrosion based on the characteristic frequency of the impedance response. However, more complicated signal processing is required to determine the state of the sensor. The viability of the corrosion sensors is being evaluated through a comprehensive series of laboratory tests using small-scale concrete prisms and large-scale reinforced concrete members.

Corrosion is a major problem for airframe operators. For the aircraft industry in general, the direct costs of corrosion are estimated at $2.2 billion. As part of their strategy to control corrosion, airframe operators constantly seek to improve their ability to anticipate, manage and identify corrosion activity. Motivated by the need for an on-line real-time corrosion-monitoring tool for industry and aircraft a prototype system and analysis approach is presented. The tool employs ultrasonic Lamb waves along with a dispersion compensated synthetic aperture focusing technique (SAFT) to detect emerging pitting damage. In order to develop an automated detection approach the noise sources of the SAFT processed defect maps were examined and modeled. The random noise was found to be neither stationary nor normally distributed. Locally varying Weibull distribution parameters are used to characterize the image noise. An algorithm is developed to quantify the uncertainty in the corrosion detection and to allow assignment of a constant false alarm probability to any region of the monitored area.

In this paper, comparisons are made between the performances of two kinds of distributed sensors, Electric Time Domain Reflectometry (ETDR) cable sensor that is based on the propagation of electromagnetic waves in an electrical cable and Brillouin Optical Time Domain Reflectometry (BOTDR) optical sensor that is based on the propagation of optic pulses and Brillouin scattering that occurs when light is transmitted through the optic fiber. A cable sensor was mounted near the surface of the 80% scale beam-column reinforced concrete assembly that was loaded cyclically until the shear failure occurred. The embedded depth was 0.5 inches. At the same time, a fiber optic sensor was mounted on the surface of the assembly with two installation procedures called Point Fixation (PF) Method and Overall Bonding (OB) Method to measure the strain distribution. Both BOTDR and ETDR sensors were subjected to tension and compression in one loading cycle. Strain distributions obtained from the ETDR and BOTDR sensing systems under different cycle loadings were compared with each other. They were also compared with those measured from the traditional strain gauge.

This paper is concerned with the design concepts, modelling and implementation of various fibre optic sensor protection systems for development in concrete structures. The design concepts of fibre optic sensor protection system and on-site requirements for surface-mounted and embedded optical fibre sensor in concrete structures have been addressed. The aspects of finite element (FE) modelling of selected sensor protection systems in terms of strain-transfer efficiency from the structure to the sensing region also been focused in this paper. Finally, the experimental validations of specified sensor protection system in concrete structures have been performed successfully. Protected Extrinsic Fabry-Perot Interferometric (EFPI) and Fibre Bragg Grating (FBG) sensors have been used to monitor the structural health status of plain and composite wrapped concrete cylinders. Results obtained indicate that the protection system for the sensors performs adequately in concrete environment and there is very good correlation between results obtained by the protected fibre optic sensors and conventional electrical resistance strain gauges.

In this study, measurements from low-impact velocity experiments and embedded and surface mounted optical fiber Bragg grating (FBG) sensors were used to obtain detailed information pertaining to damage progression in two-dimensional laminate woven composites. The woven composites were subjected to multiple strikes at 2m/s until perforation occurred, and the impactor position and acceleration were monitored throughout each event. From these measurements, we obtained dissipated energies and contact forces. The FBG sensors were embedded and surface mounted at different critical locations near penetration-induced damaged regions. These FBG sensors were used to obtain initial residual strains and axial and transverse strains that correspond to matrix cracking and delamination. The transmission and the reflection spectra were continuously monitored throughout the loading cycles. They were used, in combination with the peak contact forces, to delineate repeatable sensor responses corresponding to material failure. From the FBG spectra, fiber and matrix damage were separated by an analysis based on signal intensity, the presence of cladding modes, and the behavior of individual Bragg peaks as a function of evolving and repeated impact loads. This provided an independent feedback on the integrity of the Bragg gratings. A comparison by number of strikes and dissipated energies corresponding to material perforation indicates that embedding these sensors did not affect the integrity of the woven systems and that these measurements can provide accurate failure strains.

A three element, 15.3 cm, fiber Bragg grating array (FBGA) operating at 1550 nm wavelength is fabricated using a single mode photosensitive fiber. The FBGA is initially simulated using in-house developed software based on the Transfer Matrix Method, then fabricated using a double frequency Argon laser and a phase mask technique, and interrogated using Optical Frequency Domain Reflectometry. A single fiber Bragg grating (FBG) is accurately strain calibrated using a Fabry-Perot interferometer and piezoelectric actuation. The piezoelectric is linearly ramped, and the shifts in the Bragg wavelength along with the fringe count from the Fabry-Perot interferometer are recorded. The fringe count is then used to determine the strain on the FBG and compared to changes in the Bragg wavelength in-order to calculate the strain gage factor. This result is used to calibrate the FBGA for strain measurements. The FBGA is then bonded to a cantilever beam with three electric strain gages attached next to each FBG in the array. The axial strain results obtained from the electric strain gages and FBGA are compared for various displacements of the cantilever beam. The Fabry-Perot interferometer and piezoelectric calibration method is a non-destructive process that eliminates the need to bond the FBG to an external support during the calibration process, and can also be used to calibrate electric strain gages.

To monitor structural behavior of large-scale civil infrastructures such as long-span bridges, it requires direct and accurate measurement of "macroscopic" strains which are more representative of the deformation of entire structural element. On the other hand, quasi-distributed measurements are also supposed to serve the purpose to catch the characters of whole structure. In this regard, a novel packaging method for practical adaptation of long-gage FBG strain sensor in civil structures is proposed. After a series of tests including uniaxial tension and compression, bending, free-vibration and shaking table tests, the ability of the packaged FBG sensors fixed on different specimen for macro-strain measurements has been characterized by comparing with conventional foil strain gauges in both static and dynamic cases. Combined with the parametric identification method based on macro-stains, the applicability of quasi-distributed long-gage FBG sensors in structural parameter estimation and damage detection is discussed.

Binzhou yellow river Highway Bridge with 300 meter span and 768 meter length is located in the Shandong province of China and is the first cable stayed bridge with three towers along the yellow river, one of the biggest rivers in China. In order to monitoring the strain and temperature of the bridge and evaluate the health condition, one fiber Bragg grating sensing network consists of about one hundred and thirty FBG sensors mounted in 31 monitoring sections respectively, had been built during three years time. Signal cables of sensors were led to central control room located near the main tower. One four-channel FBG interrogator was used to read the wavelengths from all the sensors, associated with four computer-controlled optic switches connected to each channel. One program was written to control the interrogator and optic switches simultaneously, and ensure signal input precisely. The progress of the monitoring can be controlled through the internet. The sensors embedded were mainly used to monitor the strain and temperature of the steel cable and reinforced concrete beam. PE jacket opening embedding technique of steel cable had been developed to embed FBG sensors safely, and ensure the reliability of the steel cable opened at the same time. Data obtained during the load test can show the strain and temperature status of elements were in good condition. The data obtained via internet since the bridge's opening to traffic shown the bridge under various load such as traffic load, wind load were in good condition.

In this paper, a Fiber Bragg Grating (FBG) sensor system for smart structures is described. FBGs are well-suited for long term and extremely severe experiments, where traditional strain gauges fail. In the system, a reflect wave-length measurement method which employs a tunable light source to find out the center wave-length of FBG sensor is used. The real field test was performed to verify the behaviors of fiber Bragg grating (FBG) sensors attached to the containment structure in Uljin nuclear power plant as a part of structural integrity test which demonstrates that the structural response of the non-prototype primary containment structures within predicted limits plus tolerances when pressurized to 115% of containment design pressure, and that the containment does not sustain any structural damage. The system works very well and it is expected that it can be used for a real-time strain, temperature and vibration detector of smart structure.

Two goals are pursued in this paper. The first goal consists of comparing the performance of the innovative SOFO dynamic system, which uses long-gauge fiber-optic sensors, with the traditional monitoring method based on accelerometers. For this purpose, a dynamic laboratory test was carried out, and measurements were taken from a single-storey three-dimensional steel frame model excited at the base by a shaking table. The SOFO dynamic system was installed on one column of the frame structure, while two accelerometers were mounted on the base and on the frame storey, respectively, for comparison. The use of fiber-optic sensors allows to overcome the difficulties associated with the traditional dynamic measurement methods, such as the limitations in the number and in the locations of the monitoring devices. Furthermore, the long-gauge fiber-optic strain sensors show a very high sensitivity and extend the frequency range (1mHz-1KHz). The second goal is to investigate the sensitivity to local damage of a recently proposed method for damage detection and localization. Indeed, the use of better performing long-gauge strain sensors allows the detection of local damage that is hardly visible in the global response of the structure. Damages of increasing intensities are therefore gradually introduced in the structure, and the measurements acquisition is repeated for each of the damaged cases. The SHM-RSM method, which is based on the idea of using a response surface model to approximate the relationship between the measurements collected by different sensors during the same test, is finally applied to the collected data to detect and locate the damages of different intensities.

Strain and temperature sensing obtained through frequency shift evaluation of Brillouin scattered light is a technology that seems extremely promising for Structural Health Monitoring (SHM). Due to the intrinsic distributed sensing capability, Brillouin can measure the deformation of any individual segment of huge lengths of inexpensive single-mode fiber. In addition, Brillouin retains other typical advantages of Fiber Optic Sensors (FOS), such as harsh environment durability and interference rejection. Despite these advantages, the diffusion of Brillouin for SHM is constrained by different factors, such as the high equipment cost, the commercial unavailability of specific SHM oriented fiber products and even some prejudices on the required sensitivity performances. In the present work, a complete SHM pilot application was developed, installed and successfully operated during a diagnostic load test on the High Performance Steel (HPS) bridge A6358 located at the Lake of the Ozarks (Miller County, MO, USA). Four out of five girders were extensively instrumented with a "smart" Glass Fiber Reinforced Polymer (GFRP) tape having embedded fibers for strain sensing and thermal compensation. Data collected during a diagnostic load test were elaborated through a specific post-processing software, and the strain profiles retrieved were compared to traditional strain gauges and theoretical results based on the AASHTO LRFD Bridge Design Specifications for structural assessment purposes. The excellent results obtained confirm the effectiveness of Brillouin SHM systems for the monitoring of real applications.

Brillouin fiber optic sensing is a promising technology for Structural Health Monitoring (SHM) whose diffusion is however at present reduced by the unavailability of proper sensor products and established installation techniques specifically aimed at the building industry. Due to its intrinsic distributed sensing capability, Brillouin systems can individually measure the deformation of any single segment of considerable lengths of single-mode fiber. In addition, Brillouin retains all the other typical advantages of Fiber Optic Sensors (FOS), such as harsh environment durability and electro-magnetic interference rejection. These advantages, especially considering that the required sensors are really low cost, make the system particularly attractive for periodical ("discontinuous") strain monitoring of unattended infrastructures that might be exposed to ageing and vandalism damages. Despite the high equipment cost, the technique can become economically convenient when the same initial investment can be amortized over a number of applications that can be monitored periodically using the same device. This work presents a comparison between two different Brillouin sensor installation techniques: Near-to-Surface Fiber (NSF) embedding and smart-FRP sensor bonding. Both systems have been experimented in the field on small Reinforced Concrete (RC) bridges subject to a diagnostic load test. The obtained results clearly highlight the advantages of the smart-FRP system, in terms of performance enhancements, installation cost, and time reduction.

Structural health monitoring systems are being recognized as effective tools to minimize maintenance costs for civil infrastructures. Recently, many damage evaluation methods for the systems have been proposed. For example, natural frequencies were used for global monitoring, and strain measurement for local monitoring. In this study, a novel monitoring system that measures two physical values simultaneously, acceleration and strain, by a single sensor is proposed. At first, a hybrid FBG sensor for monitoring strain and acceleration is proposed. The sensor consists of an FBG element and a mass to form a vibration system. Then, a monitoring system using the hybrid FBG sensor and support vector machines is proposed. Many damage scenarios for a moment-resistant frame were tested. The results show that the sensitivities of strain and natural frequency are significantly different. It is confirmed that combined use of acceleration and strain measurement enhances the performance of the system.

Monitoring the movement of existing tunnels when new tunnel construction or other construction activities occur in close proximity is important to the tunnel owners. Existing manual monitoring systems, although considered most reliable, require access to the tunnel outside of passenger traffic hours and thus only provide measurements during a limited time of the day and under non-operational conditions. Remote monitoring systems, enabling 24 hour monitoring, are currently available based on electrolevels and automatic motorised theodolites. However, it is hoped that the proposed optical fibre sensor system will be more versatile and economic to install and operate. The underlying concept is based on a fibreglass rod containing optical fibres, with Fibre Bragg Gratings (FBG) written into them, which is fixed at discrete points to the tunnel lining. The movement of the tunnel induces a deformation of the rod, and hence strains the FBGs positioned at different points along the optical fibres. The FBGs work by reflecting narrow bands of light propagating along the optical fibres, the wavelength of the reflected light being a function of the strain at the position of the grating. This paper will discuss one experimental arrangement designed to explore the challenges of installing the monitoring system and interpreting the results. Results from tests are presented and discussed together with the sensitivity and accuracy achievable with the proposed system. Further, one method of interpreting the strain measurements and hence determining the displacement of the structure will be presented.

Grid structures are the structures made of the trusses consisting of simple ribs. Especially, the structure which uses carbon fiber reinforced plastic (CFRP) unidirectional composites as ribs is called advanced grid structures (AGS). Highly Reliable Advanced Grid Structure (HRAGS) is one of the AGS in which fiber Bragg grating (FBG) sensors are embedded in the longitudinal direction of the ribs in order to detect various damages that appear in the composite grid structures. In this research, the authors tried to identify the damage location in AGS from the structural strain distribution measured by FBG sensors embedded in all ribs. When some damages appear in the AGS, the structural strain distribution in the AGS changes accordingly. Considering the tendency of change, the damage location was identified. At first, FBG sensors were embedded into AGS and three point bending test was examined. The result showed that these embedded sensors could detect the strains applied to the corresponding ribs. Then, low velocity impact test was carried out, which revealed that only fiber breakage was appeared in the AGS. Moreover, three types of models for finite element analysis (FEA) were proposed and compared with the experimental result. According to the comparison, the authors selected beam element model (BEM) for damage-location identification in this research. Furthermore, strain distributions in the structure including damages were calculated with this model. The result proved that the identification of damage location could be realized.

This paper describes the design of an extrinsic optical fibre sensors based on poly(methamethycrylate) for structural health monitoring applications. This polymer-based optical fiber sensor relies on the modulation of light intensity and is capable of monitoring the response of the host structure subjected to either static or dynamic load types. A series of mechanical tests have been conducted to assess the response of the plastic optical fiber (POF) sensor. The readings of the sensors attached to an aluminium bar were found to compare well to electrical strain gauge response. The POF sensors were also attached to rebar concrete beams and exhibited encouraging response under flexural loading. Static and cyclic loading tests were also performed and the sensor was shown to exhibit excellent strain linearity and repeatability. Free vibration tests on a cantilever beam set-up in which the POF sensor was surface-bonded to a composite beam were also conducted. The results obtained highlight the capability of the sensor to accurately monitor the dynamic response of the beam. Impulse-type dynamic response of the sensor was also conducted and the POF sensor demonstrated potential for detecting the various modal frequencies of the host structure. POF sensors were also attached to a series of impacted composite beams with varying degree of damage to assess their potential to detect and quantify the damage in the host structure. The results demonstrated the feasibility of using the sensor for structural health monitoring applications.

It is still a practical problem how to effectively install FBG sensors on bridge cabes. In this paper, a simple and effective solution is introduced to develop smart bridge cables using FRP-OFBG bars developed in HIT (Harbin Institute of Technology). Here, the FRP-OFBG bar acts as one component of the cable and shows force resistance and well-protected sensors in service. The installation techniques and the sensing properties of FBGs in three kinds of cables, FRP cables, common steel-wire cable and extruded-anchor cable, are introduced and tested under dead load. Moreover, the preliminary introduction of a practical field application based on this solution has been also given. The experimental results show that the deformability of FRP-OFBG bars in the smart cables can reach the terminal and show wonderful accuracy, which shows that such kind of smart cable is practical in field application.

A mathematical model based on the complex modal theory is formulated to evaluate the damping ratio of cables incorporating smart magneto-rheological (MR) dampers in open-loop control mode, taking into account the damper coefficient, damper stiffness, damper mass, stiffness of the damper support, nonlinearity of the damper, as well as the cable sag and inclination. Based on asymptotic solution of the developed mathematical model, a 'generalized universal formula' is proposed to facilitate the damper design. Comprehensive parametric studies are carried out to analyze the effects on the maximum attainable damping ratio and the corresponding optimal damper coefficient. Making use of the 'generalized universal formula' and results from the parametric studies, design guidelines/procedures for open-loop cable vibration control using MR dampers are developed, for both single-mode optimal control and multi-mode suboptimal control. The guidelines/procedures facilitate the engineering application of MR dampers in mitigating the rain-wind-induced cable vibration on cable-stayed bridges.

A parameter-adaptive three-element model is first developed for a full-scale MR damper based on laboratory tests. The parameters of the model are represented by a set of empirical formulae in terms of displacement amplitude, voltage input, and excitation frequency. The model is then incorporated into the governing equation of cable-damper system for investigation of open-loop vibration control of stay cables in a cable-stayed bridge, by installing the dampers in single- and twin-damper setups respectively. The concept of optimal voltage/current input achieving the maximum damping for the system is put forward and verified. Multi-mode and multi-switch open-loop control methods in single- and twin-damper setups are then developed and a procedure for determining optimal geometric configuration of the twin-damper setup is proposed. The developed analytical formulations and design methods contribute to consummating the design specifications/guidelines for open-loop cable vibration control using MR dampers.

The implementation of smart structures technology in the design, construction and maintenance of civil and mechanical systems have been shown beneficial to the performance enhancement, operating efficiency and reliability of structural systems. However, most of today's engineering students are unaware of the remarkable properties of smart sensors and many applications of smart structures technology. It is thus desirable to prepare the future engineers of the society for the cutting-edge technologies in smart structures, for which they may see broad application in their generation. Pioneering work in incorporating smart structures technologies into civil engineering curriculum has been done by the writer at Lehigh University and is described in this paper. In particular, a graduate-level course entitled "Smart Structural Systems" has been taught in the Spring Semester of Year 2004 at Lehigh University. To better convey the course material to students, a smart structures test-bed, which is used not only to showcase various technological aspects of a smart structural system but also offer students an opportunity to gain hands-on experience by doing experiments has been under development at Lehigh University. The hands-on experience that could be developed with the smart structures test-bed is believed being essential for students to have a good understanding and mastering of the smart structures technologies.

The most common choice of importance density is the transition prior density function for particle filter (it is also known as SIR filter, Monte Carlo filter, Bayesian bootstrap filter, condensation, etc.), since it is intuitive and simple to implement, but using the prior as the importance density suffers from drawback of without any knowledge of the observations, and hence the state space is explored without direct knowledge of the observations, maybe lead to poor performance for the particle filtering. To accomplish this, it is necessary to incorporate the current observation in the importance density. In this paper, we propose an auxiliary particle filter (APF) method to identify a non-stationary dynamic system with abrupt change of system parameters. In the APF, the importance density is proposed as a mixture density that depends upon the past state and the most recent observations, and hence which has a good time tracking ability is more suitable for tracking the non-stationary system than the conventional particle filters. The numerical simulations confirm effectiveness of the proposed method for the structural system identification.

Structural identification based on the vibration data is still a challenging topic especially when the input and output (I/O) measurements are corrupted by high-level noise. In this paper, we propose a new structural parameter identification method based on the Support Vector Regression (SVR) which has been found working very well in many fields as an exclusively data based non-linear modeling method. Machine learning technologies such as Neural Networks has been applied widely in the field of health monitoring field. However, most papers just obtain the 'block-box' model of the studied structures from Neural Network training but the structural parameters are not identified actually. In our work, we not only generate the 'block-box' model but also identify the structural parameters by combining ARMA model together with SVR. Due to the “max-margin” idea used, SVR showed powerful properties in ARMA and structural identification under different kinds and amplitude noise. Furthermore, how to choose the parameters of SVR is also studied in this paper. Finally, numerical examples are given to demonstrate that the proposed method based on SVR is effective and powerful for identifying ARMA time series and structural models.

An early detection of structural damage is an important goal of any structural health monitoring system. In particular, the ability to detect damages on-line, based on vibration data measured from sensors, will ensure the reliability and safety of the structures. Innovative data analysis techniques for the on-line damage detection of structures have received considerable attentions recently. The problem is quite challenging, in particular when the structure is nonlinear. In this paper, we proposed a new data analysis method, referred to as the sequential nonlinear least square estimation (SNLSE), for the on-line identification of nonlinear structural parameters. This new approach has significant advantages over the extended Kalman filter (EKF) approach in terms of the stability and convergence of the solution as well as the computational efforts involved. Further, an adaptive tracking technique recently proposed has been implemented in the proposed SNLSE to identify on-line the time-varying system parameters of nonlinear structures. The accuracy and effectiveness of the proposed approach has been demonstrated using a nonlinear elastic structure and nonlinear hysteretic structures. Simulation results indicate that the proposed approach is capable of tracking on-line the changes of structural parameters leading to the identification of structural damages.

The purpose of this study is to provide a system identification tool to obtain dynamic structural properties of buildings when closed-loop control devices are in operation so that we will be able to detect possible damages or changes in the building structures without suspending the control devices. The difficulty associated with closed-loop systems, where noise, input and output signals are correlated, can be resolved using the output over-sampling approach. Using the approach, we were able to successfully obtain the open-loop properties of the building structures even when the control device is operated. Until now, it has been a common practice to temporarily suspend the closed-loop control circuits to measure the properties of the building without the influence of the control device. The control device is used as an exciter for the building structure with no feedback to the device. However, the true dynamic properties of the building when subject to control forces generated by the control devices that are operated as closed-loop systems may be different from those neglecting the control force. Thus, the output over-sampling approach was employed to overcome these difficulties. The employed approach was indeed able to estimate the properties of the building when the AMD, that is a typical vibration control device, is in operation under the condition that the control system can hold its control signal for the sampling period T.

Bridges and other civil structures can exhibit nonlinear and/or chaotic behavior under ambient traffic or wind loadings. The probability density function (pdf) of the observed structural responses thus plays an important role for long-term structural health monitoring, LRFR and fatigue life analysis. However, the actual pdf of such structural response data often has a very complicated shape due to its fractal nature. Various conventional methods to approximate it can often lead to biased estimates. This paper presents recent research progress at the Turner-Fairbank Highway Research Center of the FHWA in applying a novel probabilistic scaling scheme for enhanced maximum entropy evaluation to find the most unbiased pdf. The maximum entropy method is applied with a fractal interpolation formulation based on contraction mappings through an iterated function system (IFS). Based on a fractal dimension determined from the entire response data set by an algorithm involving the information dimension, a characteristic uncertainty parameter, called the probabilistic scaling factor, can be introduced. This allows significantly enhanced maximum entropy evaluation through the added inferences about the fine scale fluctuations in the response data. Case studies using the dynamic response data sets collected from a real world bridge (Commodore Barry Bridge, PA) and from the simulation of a classical nonlinear chaotic system (the Lorenz system) are presented in this paper. The results illustrate the advantages of the probabilistic scaling method over conventional approaches for finding the unbiased pdf especially in the critical tail region that contains the larger structural responses.

Unmanned Aerial Vehicles (UAVs) are being increasingly used in military as well as civil applications. A critical part of the structure is the adhesive bond between the wing skin and the supporting spar. If not detected early, bond defects originating during manufacturing or in service flight can lead to inefficient flight performance and eventual global failure. This paper will present results from a bond inspection system based on attached piezoelectric disks probing the skin-to-spar bondline with ultrasonic guided waves in the hundreds of kilohertz range. The test components were CFRP composite panels of two different fiber layups bonded to a CFRP composite tube using epoxy adhesive. Three types of bond conditions were simulated, namely regions of poor cohesive strength, regions with localized disbonds and well bonded regions. The root mean square and variance of the received time-domain signals and their discrete wavelet decompositions were computed for the dominant modes propagating through the various bond regions in two different inspection configurations. Semi-analytical finite element analysis of the bonded multilayer joint was also carried out to identify and predict the sensitivity of the predominant carrier modes to the different bond defects. Emphasis of this research is based upon designing a built-in system for monitoring the structural integrity of bonded joints in UAVs and other aerospace structures.

The integrity of thermal protection systems (TPS) is crucial to ensure a successful mission of space exploration vehicles. In this paper, an attenuation-based built-in diagnostic technique is demonstrated through a carbon-carbon (C-C) panel for the detection of bolt loosening under extreme environments. The proposed technique is based on the attenuation properties of propagating waves, which depend on the torque level and contact material at the bolted-joint interface. A smart washer was developed with an embedded piezoelectric element used as an actuator to generate the propagating waves as well as a sensor to receive the diagnostic waves. The washers were installed in each bolt on the TPS panel. During the course of the investigation, a complete diagnostic system including smart washers, diagnostic algorithms, and electronic hardware was developed to verify the proposed attenuation technique. Experiments which simulate the acoustic environments during the re-entry process were conducted using a shaker in the AFRL to verify the technique. The test results revealed that the proposed system successfully identify the bolt loosening and failure. More tests are being considered to include temperature effect.

We present efforts to develop structural composite materials which include networks of embedded sensors with decision-making capabilities that extend the functionality of the composite materials to be information-aware. The next generation of structural systems will include the capability to acquire, process, and if necessary respond to structural or other types of information. We present work related to the development of embedded arrays of miniature electronic-based microsensors within a structural composite materials, such as GFRP. Although the scale and power consumption of such devices continues to decrease while increasing the functionality, the size of these devices remain large relative the typical scale of the reinforcing fibers and the interlayer spacing. Therefore, the question of the impact of those devices on the various mechanical properties is relevant and important. We present work on characterizing some of those effects in specific systems where sensors, or suitable dummy sensors, are arrayed with ~1 cm spacing between elements. The typical size of the microelectronic sensing element is ~1 mm, and here is orthorhombic. Of particular importance are the effects of inclusion of such devices on strength or fatigue properties of the base composite. Our work seeks to characterize these effects for 1 and 2 dimensional arrays lying in planes normal to the thickness direction in laminated composites. We also seek to isolate the effects due to the sensing elements and the required interconnections that represent the power-carrying and data communications capabilities of the embedded network.

This paper presents the design, analysis, and experimental verification of a piezoelectric device that extracts energy from low-level vibrations. Such a device may be configured as a new source of power supply to operate wireless sensor networks. A millimeter-sized, non-uniformly shaped beam consisting of two piezoelectric layers is proposed as the key component of the device. An analytical model of the beam is established and used to predict the dynamic response of the beam and subsequently, its power output, when it is subject to vibration inputs. Through a coupled-field analysis, the coupling between the mechanical and electrical domains of the energy extraction device is analyzed. Simulations and experiments on a vibration shaker have shown that, compared with the rectangular beam design that has been traditionally used, the new design has increased the energy extraction capability of the beam by as much as 70%. In addition to beam design, issues related to device packaging are also addressed in the paper.

This paper presents an adaptive filtering technique for the health diagnosis of mechanical systems, based on the generalized harmonic wavelet transformation. Through selection of two wavelet level parameters, a series of sub-frequency band wavelet coefficients corresponding to equi-bandwidth vibration signals measured from a machine were constructed. The energy and entropy associated with each sub-frequency band were then calculated, and the band with the maximum energy-to-entropy ratio was chosen to form a band-limited filter for the vibration signals. Experimental studies using rolling bearings that contain structural defects have confirmed that, the developed new technique enables high signal-to-noise ratio for effective machine failure detection and health diagnosis.

This paper studies damage detection using structural frequency response functions (FRFs). In practice, one major difficulty of using FRFs for damage detection is that the vibration signatures are inevitably contaminated by noise. Sensitivity to detect damage is severely impaired as abnormality information caused by the damage could be covered up by the relatively high measurement noise. To tackle this issue and to develop a robust damage detection protocol, a feature extraction/de-noising methodology based on principal component analysis (PCA) is implemented. We first establish a feature space of the intact structure by using multiple measurements with noise. Abnormal signature that is different from the baseline signature can then be identified and magnified after signal reconstruction using intact structure features. Essentially, the directionality between an inspected signal and the baseline signal in the feature space is used as index of damage occurrence. Numerical examples demonstrate that, in all cases considered, the new methodology has good accuracy and high sensitivity for structural damage detection. The relation between detectability, damage severity, noise level, and the number of data sets of the intact structure is examined.

This paper presents an active noise cancellation technique for recovering wearable biosensor signals corrupted by bodily motion. A finger mounted photoplethysmograph (PPG) ring sensor with a collocated MEMS accelerometer is considered. The system by which finger acceleration disturbs PPG output is identified and a means of modeling this relationship is prescribed using either FIR or Laguerre models. This means of modeling motivates the use of a recursive least squares active noise cancellation technique using the MEMS accelerometer reading as an input for a FIR or Laguerre model. The model parameters are identified and tuned in real time to minimize the power of the recovered PPG signal. Experiments show that the active noise cancellation method can recover pulse information from PPG signals corrupted with up to 2G of acceleration with 85% improvement in mean squared error.

The detection of cracks in beams and plates using piezo-actuated Lamb waves has been presented in the last SPIE Symposium. This paper is an extension of the technique to pipes. It has been shown that for a thin-walled pipe, the assumption of Lamb wave propagation is valid. Such waves can be efficiently excited using piezoceramic transducers (PZT) with good control on the pulse characteristics to assess the health of structural components, such as the presence of cracks. In this paper, a systematic methodology to detect and locate cracks in homogenous cylinder/pipe based on the time-of-flight and strength analysis of propagating Lamb wave is proposed. By observing the attenuation in strength of the direct wave incidence at the sensor, the presence of a crack along the propagation path can be determined. At least four actuation positions, two on each end of the pipe segment of interest, are needed to exhaustively interrogate for the presence of cracks. The detailed procedure for locating and tracing the geometry of the crack(s) is described. It is shown experimentally that the detection using circular PZT actuator and sensor, with dimensions of 5.0 mm diameter and 0.5 mm thick, is possible for an aluminum pipe segment of up to at least 4.0 m in length. The proposed methodology is also explored for the aluminum pipe under more practical situations, such as burying it in sand with only the actuator and sensor positions exposed. Experimental results obtained showed the feasibility of detecting the 'concealed' crack on the pipe buried in sand.

Using control area network (CAN) technique and open connectivity (OPC) method, a sensor fieldbus is developed to acquire and preprocess the data came from structure for monitoring the damage. The OPC interface is added in sensor bus for information sharing. The algorithm of distance of storing-strategy data is embedded in the sensor fieldbus. A system of data acquisition and preprocessing based on the sensor fieldbus is presented and simulated it on the offshore platform. The result shows that the speed and efficiency of sensor fieldbus are reliable and robust when the gigantic data stream into the monitoring system.

Truss and tower systems are widely used in variety of applications ranging from industrial structures to space stations. Such systems are normally designed for specified loads and by using respective codes. But in certain cases, they may be subjected to loads over the design values due to earthquakes of higher intensity, cyclones or even man-made disasters like terrorist attacks. Then a need arises to protect these systems, if they serve lifeline activities, through some inherent means; and this paper focuses attention on one such aspect. The objective is to provide a "smart control", which comes into effect only when the specified loads are exceeded by certain margins.[3] To demonstrate the introduction of smartness, a three-dimensional, three-panel tower system is chosen. Actuators, which activate corrective control to externally applied forces at the nodes of the truss, are provided on the members of the truss. The control forces within an active control system are typically generated through actuators based on feedback information from the measured response of the structure. The measured responses are monitored by sensors, which based on a pre-determined control algorithm, apply appropriate control signal for operation of the actuators. The generation of control forces requires external power leading to an active control system. Such a self correcting structure can be termed as smart or adaptive structure. This paper focuses on providing in-built smartness to handle both force and deformation when unanticipated loads up to 100 percent increase over a short duration act on these systems. Analysis is made for loads at the rate of 1.25,1.5,1.75 and 2 times the design load on the tower. For each of these loads, the example highlights how suitable control forces are generated and how the system under combined action of unanticipated and control forces balance in such a manner as to keep the structural integrity during short duration unanticipated loads.

One of the most promising NDT technologies is the guided ultrasonic wave technology. The most useful guided ultrasonic wave is Lamb waves. Damage detection and (or) nondestructive evaluation of structures using Lamb waves may be completed by the comparison between the analytic and the experimental dispersion diagram of Lamb waves. In order to construct the experimental dispersion diagram, the estimation of group velocities of each Lamb modes is necessary. Time of arrival information is needed to calculate the group velocity of each Lamb mode, and frequency information is needed to tell the Lamb modes from receiving signals because at least two modes are present at same frequency. Current research for detection of the time of arrival and the frequency is either in time domain or in frequency domain. However, these methods were not designed to give simultaneous information of the time and the frequency. Furthermore the scattering of waves and the background noise often mask the signal, leading difficulties in its estimation of the time of arrival and the frequency of the reflected and transmitted of dispersive Lamb waves. In this study, the authors introduce a detection method to estimate the time of arrival and the frequency simultaneously via time-frequency representation and to resolve the noise problem based on statistical signal detection theory. Numerical experiments were conducted to verify and validate the capability of the proposed method. The results of experiments demonstrate the utility of the proposed method.

Wires, bars, multi-wire strands made of steel or composite materials are widely used in civil infrastructures as tensioning members in cable-stayed bridges, suspension bridges and prestressed concrete. The health monitoring of these components is a long-standing challenge in the NDE community. In the last few years, the authors have been conducting a study on the application of ultrasonic guided waves for the structural health monitoring of bars and multi-wire strands. This paper presents an application of a signal processing technique based on the Discrete Wavelet Transform (DWT) for the detection and the quantification of damage (in the form of small notches) in loaded seven-wire steel strands. The DWT is applied to ultrasonic signals generated and detected via magnetostrictive transducers. The detection and the quantification of damage in the strands are accomplished by constructing and computing a damage index based on the variance and the root mean square of the wavelet coefficient vector of the ultrasonic damage signatures. It is shown that the logarithmic value of the damage index is linearly dependent on the damage size. In the last portion of the paper an eight-dimensional damage index is constructed and it is fed to an artificial neural network that classifies the size and the location of the notch.

Most structural responses can be considered as the superposition of some monotonic components. These monotonic components contain modal information that can be used for structural damage detection and health monitoring. This paper presents a comparative study of three techniques for signal decomposition and analysis. These techniques are the wavelet transform (WT) technique, the empirical mode decomposition (EMD) technique, and the principle component analysis (PCA) technique. These techniques are all capable of decomposing multi-component signals into a summation of mono-components without resorting to the traditional frequency-domain approach. All three techniques can estimate natural frequencies, damping ratios and mode shapes of a structure from its time-domain vibration responses and hence can be used to monitor structural condition. A numerical study on a three-story shear-beam building frame is performed and presented to show the accuracy of these techniques.

The Empirical Mode Decomposition (EMD), which combines with the Hilbert transform (HT), has been used successfully to identify the dynamic characteristics of linear multi-degree-of-freedom structures. In this study, the EMD method is applied to the identification of nonlinear normal modes (NNMs) of nonlinear multi-degree-of-freedom (MDOF) structures. It is shown that the intrinsic mode functions (IMFs), which are obtained by applying the EMD method to the structural response, agree quite well with the nonlinear modal responses obtained from the invariant manifold approach. A two-degree-of-freedom building model with nonlinear stiffness is used for illustration. The EMD method is applied to decompose the measured response of the building model. The resulting IMFs are compared with the corresponding nonlinear modal responses, including their instantaneous frequencies and time-dependent amplitudes from the HT method. The comparison indicates that the resulting IMFs from the EMD method can reveal the nonlinear modal responses. It is seen that this EMD-based technique is fairly accurate to determine the nonlinear stiffness characteristics of the building model. The result suggests that the IMFs can be used to determine the physical dynamic properties of nonlinear structures.

Artificial Neural Networks (ANNs) have been applied in structural damage detection as a classifier, but generally a capable ANNs has to be trained with a certain amount of samples. When both damage locations and damage extents are to be identified, the amount of training samples is tremendous because of the combinations of damage locations and extents. By wavelet transform of the structure free motion equations, the Residual Wavelet Coefficient Vector (RWCV) is deduced. A damage feature parameter is defined as the ratio between RWCVs in two different frequency bands. This parameter has a unique property that it's sensitive only to damage locations, and is independent of damage extents. The damage feature parameters are then fed to the neural network for damage localization. After the damage sites are detected, the damage extent is further identified by another neural network with RWCVs as inputs. This two-phase approach for damage localization and extent identification can simply the neural network and reduce the training samples tremendously. Finally a numerical example is given for damage detection of a 10 DOFs system using the proposed approach.

A modern bridge is such a complicated system that is difficult to analyze by conventional mathematic tools. A rational bridge monitoring requires a good knowledge of the actual condition of various structural components. Fatigue analysis of concrete bridges is one of the most important problems. Concrete bridges are often undergoing a fatigue deterioration, starting with cracking and ending with large holes through the web. There is a need for the development of efficient health assessment system for fatigue evaluation and prediction of the remaining life. This information has clear economical consequences, as deficient bridges must be repaired or closed. The goal of this research is to provide a practical expert system in bridge health evaluation and improve the understanding of bridge behavior during their service. Efforts to develop a functional bridge monitoring system have mainly been concentrated upon successful implementation of experienced-based machine learning. The reliability of the techniques adopted for damage assessment is also important for bridge monitoring systems. By applying the system to an in-service PC bridge, it has been verified that this fuzzy logic expert system is effective and reliable for the bridge health evaluation.

Vibration-based damage detection methods use changes in modal parameters to diagnose structural degradation or damage. Structures in reality are subject to varying environmental effects which also cause changes in modal parameters. The well-defined nature of the environmental effects on modal properties is essential for reliable damage diagnosis based on vibration measurement. In this paper, the performance of artificial neural networks (ANNs) for simulation and prediction of temperature-caused variability of modal frequencies is investigated. Making use of one-year measurement data of modal frequencies and temperatures from an instrumented cable-stayed bridge, three- layer back-propagation (BP) neural networks are configured to model the correlation between the temperatures and frequencies. Two approaches are adopted in defining the training samples to train the neural networks and the testing samples to verify the prediction capability of the neural networks. It is shown that when using appropriate training data covering a wide range of temperature variations, the trained neural networks exhibit satisfactory performance in both reproduction (simulation) and prediction (generalization). A good mapping between the temperatures and frequencies is obtained by the neural network models for all measured modes.

A damage detection method utilizing Support Vector Machine (SVM) for bending structures is proposed. The SVM was recently proposed as a new technique for pattern recognition. The SVM is a powerful pattern recognition tool applicable to complicated classification problems and is effectively utilized in the method. Based on the modal frequency changes, the damage location and its severity are defined by the SVM. In our previous studies, it was shown that our proposed method worked very well for structures modeled by shear frames. However, this modeling is only appropriate for low-rise building structures and is not appropriate for tall buildings. Therefore, it is our purpose here to extend the method to bending frames that are appropriate models for tall buildings. In the analytical evaluation, we constructed the finite element models to represent bending structures. Then, we conducted a series of experiments for verification. We could show that the damage detection method using SVM was also possible and effective for bending structures.

This work is part of an effort to develop smart composite materials that monitor their own health using embedded micro-sensors and local network communication nodes. Here we address the issue of data management through the development of localized processing algorithms. We demonstrate that the two-dimensional Fast Fourier Transform (FFT) is a useful algorithm due to its hierarchical structure and ability to determine the relative magnitudes of different spatial wavelengths in a material. We investigate different algorithms for implementing the distributed FFT and compare them in terms of computational requirements within a low-power, low-bandwidth network of microprocessors.

The past few years have seen unprecedented technological advancement in commercial digital cameras. The image resolution of these cameras has increased from below 1 million pixels a few years ago to over 10 million pixels today, with little increase in cost. These low cost high-resolution digital cameras have opened up new areas of application for various engineering disciplines, including civil engineering. The objective of this study is to investigate the application of videogrammetric principle for measuring structural response. A general videogrammetric framework for high precision measurement of three-dimensional structural response is proposed using two commercial digital cameras. Some important issues such as camera calibration, feature point detection and 3D point reconstruction are discussed. In order to evaluate the performance of the technique, three experiments involving capturing the trajectories of different types of motion are performed. The test results indicate that the videogrammetric technique can provide sub-pixel measurement accuracy and can be used to measure both static and dynamic responses of structures in laboratory.

A framework has been defined for storing and retrieving civil infrastructure monitoring data over a network. The framework consists of two primary components: metadata and network communications. The metadata component provides the descriptions and data definitions necessary for cataloging and searching monitoring data. The communications component provides Java classes for remotely accessing the data. Packages of Enterprise JavaBeans and data handling utility classes are written to use the underlying metadata information to build real-time monitoring applications. The utility of the framework was evaluated using wireless accelerometers on a shaking table earthquake simulation test of a reinforced concrete bridge column. The NEESgrid data and metadata repository services were used as a backend storage implementation. A web interface was created to demonstrate the utility of the data model and provides an example health monitoring application.

The University Of Connecticut, with support and assistance from the Connecticut Department of Transportation, has been involved in the design and implementation of long-term monitoring systems on a network of bridges critical to the State of Connecticut's highway infrastructure. This paper presents a report on the development, implementation and evaluation of the monitoring of a steel box-girder bridge. The bridge is a multi-span, continuous, box girder bridge made up of two steel box-sections that are composite with the deck slab. The bridge is supported on a series of tall concrete columns, one per support. Field investigations have shown that the columns have been subject to cracks that are thought to be due to torsion. Two spans in a three-span continuous segment are currently being monitored using 8 accelerometers, 8 temperature sensors and 6 tilt meters. An extensive analysis has been conducted to evaluate the test data. There have been large temperature gradients due to both annual climate changes and due to the position of the sun with respect to the bridge. The data has also been used to develop a basis for long-term nondestructive evaluation. This is based primarily on the development of a vibration signature. The field data has also been compared with results from an extensive finite element analysis. The longterm goal of this project has been to characterize the bridge behavior and then to use this in the nondestructive evaluation of the performance over multi-year periods.

Two-step identification approach for effective bridge health monitoring is proposed to alleviate the issues associated with many unknown parameters faced in the real structures and to improve the accuracy in the estimate results. It is suitable for on-line monitoring scheme, since the rigorous damage assessment is not always needed to be performed whereas the alarming for potential damage occurrence is to be continuously carried out. In this study, two-step identification approach is incorporated. In the first step for screening potential damaged members, three different methods were utilized: (1) Damage Indicator Method based on the Modal Strain Energy (DIM-MSE), (2) Probabilistic Neural Networks (PNNs), and (3) Neural Networks using Grouping technique (NNs-Gr). Then, in the second step, the conventional neural networks technique is utilized for damage assessment on the screened members. The proposed methods are verified through a field test on the northern-most span of old Hannam Grand Bridge over Han River in Seoul, Korea. The issues on measurement noise, modeling errors and multiple damages are addressed.

This paper outlines the design of an instrumentation system for durability monitoring of the world's longest cable-stayed bridge: the Sutong Bridge with a central span of 1088 m. As part of the Structural Health Monitoring And Safety Evaluation System (SHMASES) for the Sutong Bridge, the durability monitoring system is designed to monitor the corrosion in reinforced concrete structures. The sensors for durability monitoring include two categories. The first category refers to the sensors to monitor the causes leading to corrosion, such as temperature and relative humidity. The second category is electrode assemblies which are used to monitor the end results of corrosion. Data from the sensory system are then periodically collected using a portable or remotely computerized data acquisition system. The collected data from this system will provide useful information on maintenance and repair of concrete structures, and are envisaged to be incorporated into the reliability-based safety evaluation system developed for the Sutong Bridge

Intelligent health monitoring systems are becoming attractive topics in civil engineering because they not only ensure the safety of infrastructures; but also provide a method to research the evolving of damage and performance deterioration of infrastructures. However, its full implementation is very limited so far. Last year, two health monitoring systems were installed on two cable-stayed bridges for monitoring their health and assessing their safety in long-term service in mainland China, i.e. Shandong Binzhou Yellow River Highway Bridge and Harbin Songhua River Cable-stayed Bridge. The health monitoring system for Shandong Binzhou Yellow River Highway Bridge successively measures data and evaluates the safety on-line. The monitoring system for Harbin Songhua River Cable-stayed Bridge measures data periodically every year and evaluates the safety off-line. In this paper, two health monitoring systems for the above two cable-stayed bridges are introduced and partial data collected when the bridges subjected to vehicle loads and ambient condition during the static and dynamic tests are presented.

Even significant damage may cause very small changes in structural characteristics, particularly for large structures. Furthermore, these changes may go undetected due to changes in environmental and operational conditions. In this paper, the temperature-driven variability on a combined structural health monitoring (SHM) system is examined in a model plate-girder bridge. The combined SHM system consists of global vibration-based technique and local electro-mechanical impedance (EMI) based technique. First, dynamic modal parameters of the test structure are measured before and after the occurrence of flexural cracks at various temperatures. Also, EMI signatures are sensed before and after the changes in support systems at various temperatures. Next, the risk of damage-occurrence in the structure is alarmed by statistical pattern recognition of the signals. Damage-induced changes in the signals are distinguished from temperature-driven uncertainty. The effect of temperature variability is also assessed to estimate the accuracy of damage detection.

This paper presents a research on the development of a bridge structural health monitoring and information management system (BSHM&IMS) by utilizing geographic information system (GIS) and other related technologies. Based on the dynamic monitored information from various sensors on a bridge, the status of its structural health can be monitored. One of the major issues in this monitoring process is to handle a huge amount of data-both real time and accumulated historical data. The traditional data processes and management methods cannot fully meet the requirements on data process and management for bridge structural health monitoring. Besides the attribute information, the monitored information of a bridge structural health status is highly related to geospatial location. That is, the monitored information can be referenced to a spatial location, for examples, geospatial locations of bridges, geospatial layouts of various sensors on bridges, three-dimensional models of bridges, and fault points of sensors on maps. GIS technology is therefore applied to manage the information in bridge structural health monitoring. The general framework of BSHM&IMS, which is based on an integration of several information technologies, including GIS, database management system, network and others, will be introduced firstly in this paper. For the implementation of the general design, a prototype of BSHM&IMS has been developed and the major solutions will then be described in details. These functions include design of geospatial database structure for bridges, information processing from various sensors, management of a huge amount of monitored data, visualization of bridge information, illustration of warning information of fault points of sensors on three-dimensional models of bridges, and backup and output of important data according to users’ querying conditions. The experimental results demonstrate that the BSHM&IMS is capable to manage huge amounts of monitored data of bridge structural health, including real time and accumulated historical data, effectively.

Economic and effective evaluation of the actual condition of a bridge is an important issue for bridge maintenance and preservation. The current condition of the bridge is usually far more different from the construction design and also with the bridge being in service for few years, a quantitative evaluation is essential. Assimilating reviews and comparisons of traditional inspection and evaluation methods, this paper promotes the concept of application of wireless sensors developed at the Bridge Research Center for rapid installation and low power requirements for in-service real-time bridge inspection. The concept focuses on obtaining useful data such as strain, displacement, frequency for estimating the actual characteristics of the bridge while in service, thus avoid closing the traffic as compared to traditional load test which needs traffic closure causing inconvenience to public and indirectly affecting economy. Plans and procedures of the field inspection are detailed as well as the data processing and the analysis results are presented. The effectiveness and feasibility of the proposed real-time inspection based on wireless sensors approach are illustrated via the practical inspection of a deck beam bridge.

System identification and damage detection for structural dynamic systems have received more and more attention in recent years. One of the time domain methodologies, the extended Kalman filter (EKF), has been widely applied in identifying the states and parameters of dynamic systems simultaneously. In EKF algorithm, the original dynamic systems have been transformed into nonlinear state-space system models. Therefore, the observability problem of the nonlinear state-space systems is required to be investigated before the application of EKF algorithm. In this paper, the definitions and the rank criterion of nonlinear observability for continuous-time systems are presented, which are only discussed in a few areas involved nonlinear systems previously. The analysis on the nonlinear observability of SISO and SIMO state-space structure-systems show that the rank criterion presented can provide sufficient conditions for the observability of the nonlinear systems to be identified. In practice, this criterion gives out a theoretical guideline for the selection of appropriate sensor types and locations before putting up the system identification, which is quite important but neglected in most of the EKF-identification literature thus far.

The magnetorheological (MR) damper is on of the smart controllers used widely in civil engineering structures. These kinds of dampers are applied in the paper in the elevated highway bridge (EHB) with rubber bearing support piers to mitigate damages of the bridge during the severe earthquake ground motion. The dynamic calculating model and equation of motion for the EHB system are set up theoretically and the LQR semi-active control algorithm of seismic response for the EHB system is developed to reduce effectively the responses of the structure. The non-linear calculation model of the piers that rigid degradation is considered and numerical simulative calculation are carried out by Matlab program. The number and location as well as the maximum control forces of the MR dampers, which are the most important parameters for the controlled system, are determined and the rubber bearing and connection forms of the damper play also important rule in the control efficiency. A real EHB structure that is located in Anshan city, Liaoning province in China is used as an example to be calculated under different earthquake records. The results of the calculation show that it is effective to reduce seismic responses of the EHB system by combining the rubber bearing isolation with semi-active MR control technique under the earthquake ground motion. The locations of MR dampers and structural parameters will influence seriously to the effects of structural vibration control.

As strain-sensing elements in the structural health monitoring, the research and application of the Fiber-optic Bragg Grating sensor (FBG) has been widely accepted. Although there are some significant achievements on the interface transferring mechanism and error modification of FBG, the theoretical research on the creep behavior of FBG sensors is rarely taken into account. Because the optical fiber and adhesive is macromolecular polymer, when loaded in long term or high temperature, the creep characteristic of these material is emerging which influences the accuracy of FBG sensors. This paper presents the theoretical part on creep behavior of FBG sensors. Firstly, based on the linear viscoelastic constitutive relations, the general expression of multiplayer interface strain transferring mechanism is derived, and the error modified equation of FBG sensors is obtained. Secondly, the transient and steady-state responses of FBG sensors are presented. Finally, the elasticity-viscoelasticity corresponding principle is proposed, which is used for solving a class of interface strain transferring linear viscoelastic problem.

The reinforcement strength of porous concrete and its applicability as a recycled aggregate was measured. Changes in physical and mechanical properties, subsequent to the mixing of carbon fiber and silica fume, were examined, and the effect of recycled aggregate depending on their mixing rate was evaluated. The applicability of planting to concrete material was also assessed. The results showed that there were not any remarkable change in the porosity and strength characteristics although its proportion of recycled aggregate increased. Also, the mixture of 10% of silica was found to be most effective for strength enforcement. In case of carbon fiber, the highest flexural strength was obtained with its mixing rate being 3%. It was also noticed that PAN-derived carbon fiber was superior to Pitch-derived ones in view of strength. The evaluation of its use for vegetation proved that the growth of plants was directly affected by the existence of covering soil, in case of having the similar size of aggregate and void.

The relationship between the strains measured by a fiber Bragg grating sensor and the actual structural strains is deduced, then the average strain transfer rate computed by the formulation developed in this paper is compared with available experimental data. The critical adherence length of an optical fiber sensor is determined by a strain lag parameter, which contains both the effects of the geometry and the relative stiffness of the structural components. The analyses shows that the critical adherence length of a fiber sensing segment is the minimum length with which the fiber has to be tightly glued to a structure for adequate sensing. The strain transfer rate of an optical fiber sensor embedded in a multi-layered structure is developed in a similar way, and the factors that influence the efficiency of optical fiber sensor strain transferring are discussed. It is concluded that the strains, sensed by a fiber Bragg grating, have to be magnified by a factor (strain transfer rate) to equal exactly to the actual structural strains.

Sensors, which collect data for further information processing, are core component of any viable structural health monitoring system. Continuous on-line structural health monitoring can be achieved through the use of advanced sensors developed for real-time structural health monitoring applications. To overcome the problems associated with traditional piezoelectric ceramics, a polymer-based piezoelectric paint material has been developed and recently used for sensors. The piezoelectric paint is composed of tiny piezoelectric particles mixed within polymer matrix and therefore belongs to "0-3" piezoelectric composite. Because of the electro-mechanical coupling properties of piezoelectric paint, the dynamic responses of host structures can be monitored by measuring the output voltage signals from the piezoelectric paint sensor. Piezoelectric paint sensors hold a great potential for dynamic strain sensing applications due to the ease with which their mechanical properties can be adjusted, low fabrication cost, ease of implementation, and conformability to curved surface Additionally, a novel surface crack detection technique has been conceived and validated experimentally, in which cracks of the host structure is detected by observing the measured signals from an piezoelectric paint sensor with multi-electrode configuration. This paper presents this piezoelectric paint-based crack monitoring method as well as validation test data. The piezoelectric paint sensor is ideal for surface crack detection in locations with complex geometry, such as welded joints, which conventional sensors are ill equipped to do.

Battery-free sensor systems would benefit from the availability of a stress or strain sensor that exhibits a large enough property change to allow simplification and power reductions in sensor interface and data transmission circuitry. A new sensor has been developed specifically for this purpose, which uses the large stress induced impedance changes exhibited by ribbons of amorphous magnetic alloy. In comparison to semiconductor strain gauges, which show a change in resistance of 15% when strained to their maximum recommended stress level, the amorphous alloy sensor demonstrates a change in inductance of 315%, when strained to its maximum working level. Although, amorphous magnetic alloys are inherently sensitive to external magnetic fields, a simple, biasing technique renders the stress-sensing device insensitive to modest field strengths. The amorphous magnetic alloys are produced in large volumes and realize an extremely low cost sensor. A low cost and low power analogue electrical circuit has been designed that, in combination with the amorphous alloy sensor, functions as a battery-free sensor 'tag'. The sensor tag can transmit stress data to a transceiver system via an inductive link, negating the need for battery power or a hardwire connection. The system’s range is directly related to the transceiver and tag antenna dimensions; however a system with 20cm diameter antennas has been demonstrated operating over a range of up to 60cm. This range is achieved through the extremely low power demands of the sensor tag (<1mW). A demonstration unit has been developed for vehicle tyre pressure monitoring applications.