Long span bridges are today conceived and designed in such a way that a control system assists their performance under extreme loading and/or exceptional conditions. Long span bridges see the hardware of such a control system made by sensors, control devices and controllers. In the control system architecture, it can be located in stations along the bridge. The problem is how to allow these stations to communicate each with the other. Classical wired links are quite inappropriate for both installation and maintenance drawbacks. This paper discusses the architecture and the implementation of a wireless link between two of these control stations.

In this paper, we make a brief study of some of the important requirements of a structural monitoring system for civil infrastructures and explain the key issues that are faced in the design of a suitable wireless monitoring strategy. Two-tiered wireless sensor network architecture is proposed as a solution to these issues and the protocol used for the communication in this network is described. The power saving strategies at various levels, from the network architecture, to communication protocol, to the sensor unit architecture are explained. A detailed analysis of the network is done and the implementation of this network in a laboratory setting is described.

SRI International is developing a wireless sensor for monitoring the level of chloride ingress into concrete bridge decks. We call this device a Smart Pebble since it has roughly the size and weight of a typical piece of the rock aggregate that is used in such structures. It is "smart" in that it contains a chloride sensor and a radio-frequency identification (RFID) chip that can be queried remotely both to identify it and to indicate chloride concentration levels. The Smart Pebble is also powered remotely, thus precluding the need for any lifetime-limiting batteries. It is designed to be inserted in the bridge deck either during the initial construction (or during refurbishment) or in a back-filled core hole. This paper will discuss the Smart Pebble design, operation, and status.

Various nondestructive evaluation (NDE) techniques have been studied to locate steel rebars or dowel, and to detect invisible damage such as voids and cracks inside concrete and debonding between rebars and concrete caused by corrosions and earthquakes. In this study, the authors developed 3-dimensional (3D) electromagnetic (EM) imaging technology to detect such damage and to identify exact location of steel rebars or dowel. The authors have developed sub-surface two-dimensional (2D) imaging technique using tomographic antenna array in previous works. In this study, extending the earlier analytical and experimental works on 2D image reconstruction, a 3D microwave imaging system using tomographic antenna array was developed, and multi-frequency technique was applied to improve quality of the reconstructed image and to reduce background noises. This paper presents the analytical expressions of numerical focusing procedures for 3D image reconstruction and numerical simulation to study the resolution of the system and the effectiveness of multi-frequency technique. Also, the design of 4x4 antenna array with switching devices is introduced as a preliminary study for the final design of whole array.

A protype of Remote Intelligent Monitoring System (RIMS) was developed for intelligent bridge and infrastructure maintenance. It consists of MEMS sensor, micro-controller with buffer memory and Ethernet controller. Each component is carefully chosen. In the software, TCP/IP and http are adopted in the communication part. The RIMS prototype is a small and relatively inexpensive. It was installed to measure the acceleration of a light pole and its effectiveness was demonstrated.

The effect of embedding MEMS strain gages in composite materials is investigated. In a preliminary phase, silicon MEMS devices are modeled as prismatic objects embedded in the composite continuum. Variations in the dimensions and mechanical properties of the composite structure and the device are considered to identify factors that affect most the structural integrity of the composite structure. A maximum size of the microsensor is determined that will allow the composite structure to tolerate 2% strain without exceeding its failure strength. A critical ratio of the microsensor device to composite structure dimension is determined.

Electrically conductive fiber-reinforced composites have been designed in order to develop self-diagnosis materials with the ability to memorize damage histories. Irreversible resistance changes dependent on the strain histories of the composites were utilized to achieve this ability. Conductive fiber-reinforced plastics for memorizing maximum strain were prepared by adding carbon fibers or particles into the composites. Pre-tensile stresses in composites containing carbon fibers were found to effectively enhance their residual resistance and to significantly improve the limit of smallest detectable strains. The residual resistances of composites containing carbon particles connected by a percolation structure were found to depend strongly on the volume fractions of carbon particles; composites with high volume fractions of carbon displayed remarkable residual resistance without application of a pre-tensile stress. In order to memorize cumulative damage, composites consisting of a brittle titanium nitride ceramic wire laminated with glass fiber reinforced plastics were prepared. These composites were found to exhibit remarkable residual resistances that increased in proportion to the logarithm of the number of tensile cycles. These results suggest that a simple and low cost monitoring technique without real-time measurement system will be available in wide range of applications using these composites.

Acoustic emission testing is an important technology for evaluating structural materials, and especially for detecting damage in structural members. Significant new capabilities may be gained by developing MEMS transducers for acoustic emission testing, including permanent bonding or embedment for superior coupling, greater density of transducer placement, and a bundle of transducers on each device tuned to different frequencies. Additional advantages include capabilities for maintenance of signal histories and coordination between multiple transducers. We designed a MEMS device for acoustic emission testing that features two different mechanical types, a hexagonal plate design and a spring-mass design, with multiple detectors of each type at ten different frequencies in the range of 100 kHz to 1 MHz. The devices were fabricated in the multi-user polysilicon surface micromachining (MUMPs) process and we have conducted electrical characterization experiments and initial experiments on acoustic emission detection. We first report on C(V) measurements and perform a comparison between predicted (design) and measured response. We next report on admittance measurements conducted at pressures varying from vacuum to atmospheric, identifying the resonant frequencies and again providing a comparison with predicted performance. We then describe initial calibration experiments that compare the performance of the detectors to other acoustic emission transducers, and we discuss the overall performance of the device as a sensor suite, as contrasted to the single-channel performance of most commercial transducers.

Steel rods in the form of rebar or strands are widely used in civil engineering. The first part of this paper discusses the application of an ultrasonic technique for the measurement of applied loads in steel rods. Ultrasonic wave velocity depends on stress and temperature. The stress dependence of the velocity, known as the acoustoelastic effect, can be used to monitor the applied or residual stress. An acoustoelastic constant is defined in terms of relative variation of ultrasonic group velocity. Theoretical considerations suggest that the acoustoelastic effect is more pronounced for certain wave frequencies. The effect of the excitation frequency on the acoustoelastic response of circular steel rods and strands was investigated experimentally. A frequency-dependence of the acoustoelastic constant was found and the role of cross sectional mode shapes was considered in this context. In the second portion of the work, laser ultrasonic techniques were used for a basic investigation of dispersive wave propagation in strands. The tests used a joint time-frequency analysis based on the Gabor wavelet transform. Dispersion and frequency-dependent attenuation were studied. Those ultrasonic frequencies propagating with minimum attenuation were identified as the most suitable for field use to probe long length of the member at once.

This research examines the propagation of guided Lamb waves in bonded components, establishing the effectiveness of combining laser ultrasonic techniques with a time-frequency representation (TFR) to experimentally measure the dispersion curves of a layered medium. The specific layered medium examined is a fiber-reinforced polymer (FRP) plate bonded (with an adhesive layer) to concrete. A TFR is used to operate on experimentally measured, guided Lamb waves to resolve individual Lamb wave modes and to generate the system's dispersion curves. The objective of this research is to demonstrate that it is possible to develop the dispersion curves of FRP bonded components from a single, experimentally measured guided wave signal. The experimental results show that, by examining the characteristics of the system's dispersion curves, the stiffer the bond, the more deviation from the behavior of a free plate case, and the less modes that are present.

A non-destructive method for early detection of reinforcement steel bars (re-bar) delamination in concrete structures has been developed. This method, termed modal analysis, has been shown effective in both laboratory and field experiments. In modal analysis, an audio speaker is used to generate flexural resonant modes in the re-bar in reinforced concrete structures. Vibrations associated with these modes are coupled to the surrounding concrete and propagate to the surface where they are detected using a laser vibrometer and/or accelerometer. Monitoring both the frequency and amplitude of these vibrations provides information on the bonding state of the embedded re-bar. Laboratory measurements were performed on several specially prepared concrete blocks with re-bar of varying degrees of simulated corrosion. Field measurements were performed on an old bridge about to be torn down in Howard County, Maryland and the results compared with those obtained using destructive analysis of the bridge after demolition. Both laboratory and field test results show this technique to be sensitive to re-bar delamination.

The use of dynamic response to identify damage location and extent of civil engineering structures has been an increasing research focus in recent years. Most of the vibration-based damage assessment methods developed till now require modal properties that are obtained via the traditional Fourier transform. Unfortunately, these Fourier-based modal properties, such as natural frequencies, mode shapes, etc., have been reported to be insensitive to structural damage and hence are not regarded as good damage indicators. In this paper, a novel structural condition index, wavelet packet signature (WPS), is proposed for locating and quantifying structure damage. After extracting the WPS from the response measured at various locations, the spatial distribution curvature of the WPS is used for locating damage. A numerical study on a simply supported beam shows that, according to the difference of the spatial WPS distribution curvature, the damage position can be accurately located and the damage severity can be qualitatively assessed. One special advantage of the proposed method is it does not require an accurate analytical model of the structure been monitored and is very suitable for practical application.

This paper is concerned with robust strategies to perform a model-based damage detection of multistory buildings effectively. Theoretically, the model-based damage detection can be reasonably carried out through vibration monitoring and system identification. The change in modal properties due to damage is identified accurately by time series model if structural vibrations are measured appropriately. Then, the reduction of local stiffness is estimated correctly from the change in modal properties by using sensitivity equations. However, in practice, it is not an easy task to pinpoint the location and extent of local damage because of noise contamination, system nonlinearity, estimation error, model uncertainty and so on. To overcome these problems, several robust strategies are presented in the model-based damage detection of multistory buildings. The basic idea consists of decreasing the number of physical parameters to be estimated, increasing the number of modal properties with good accuracy, enhancing sensitivity to damage and reducing noise and nonlinear effects. The effectiveness and limitations of these strategies are discussed through a series of shaking table tests of two small-scaled test structures.

A method using the support vector machine (SVM) to detect local damages in a building structure with the limited number of sensors is proposed. The SVM is a powerful pattern recognition tool applicable to complicated classification problems. The method is verified to have capability to identify not only the location of damage but also the magnitude of damage with satisfactory accuracy. In our proposed method, feature vectors derived from the modal frequency patterns are used after proper normalization. The feature vectors contain the information on the location and magnitude of damages. As the method does not require modal shapes, typically only two vibration sensors are enough for detecting input and output signals to obtain the modal frequencies. The support vector machines trained for single damage is also effective for detecting damage in multiple stories.

A non-destructive evaluation technique using piezoceramic (PZT) as an actuator-sensor has an ability to efficiently detect structural damage. In this technique, a PZT actuator-sensor patch is bonded on a structure. Through the measurement of its electrical impedance, which is related to mechanical impedance of the structure being bonded, the change in structure properties due to damage can be detected. This paper presents the use of PZT in structural health monitoring to quantitatively detect damage of bolted joints. The structure used in this study consists of two aluminum beams connected by a bolted joint. The damage is simulated by loosening of the bolts. To quantitatively monitor the damage, a numerical model of the structure is formulated. Spectral element method (SEM) based on wave propagation approach is used to model the structure. A bonded-PZT beam and a bolted joint element are developed by using SEM. The equations of motion are derived by using Hamilton's principle subsequently, the spectral element matrices are formulated. Experimental results show the ability of this method to detect the damage. By using the proposed model, the loosening of bolts can be quantitatively identified as the change in stiffness and damping at the bolted joint. Therefore, this method has high potential to quantitatively monitor damage of bolted joints.

At Los Alamos National Laboratory (LANL), various algorithms for structural health monitoring problems have been explored in the last 5 to 6 years. The original DIAMOND (Damage Identification And MOdal aNalysis of Data) software was developed as a package of modal analysis tools with some frequency domain damage identification algorithms included. Since the conception of DIAMOND, the Structural Health Monitoring (SHM) paradigm at LANL has been cast in the framework of statistical pattern recognition, promoting data driven damage detection approaches. To reflect this shift and to allow user-friendly analyses of data, a new piece of software, DIAMOND II is under development. The Graphical User Interface (GUI) of the DIAMOND II software is based on the idea of GLASS (Graphical Linking and Assembly of Syntax Structure) technology, which is currently being implemented at LANL. GLASS is a Java based GUI that allows drag and drop construction of algorithms from various categories of existing functions. In the platform of the underlying GLASS technology, DIAMOND II is simply a module specifically targeting damage identification applications. Users can assemble various routines, building their own algorithms or benchmark testing different damage identification approaches without writing a single line of code.

In this study, the applicability of an auto-regressive model with exogenous inputs (ARX) in the frequency domain to structural health monitoring (SHM) is explored. Damage sensitive features that explicitly consider the nonlinear system input/output relationships produced by damage are extracted from the ARX model. Furthermore, because of the non-Gaussian nature of the extracted features, Extreme Value Statistics (EVS) is employed to develop a robust damage classifier. EVS is useful in this case because the data of interest are in the tails (extremes) of the damage sensitive feature distribution. The suitability of the ARX model, combined with EVS, to nonlinear damage detection is demonstrated using vibration data obtained from a laboratory experiment of a three-story building model. It is found that the current method, while able to discern when damage is present in the structure, is unable to localize the damage to a particular joint. An impedance-based method using piezoelectric (PZT) material as both an actuator and a sensor is then proposed as a possible solution to the problem of damage localization.

Continuously operating instrumented structural health monitoring (SHM) systems are becoming a practical alternative to replace visual inspection for assessment of condition and soundness of civil infrastructure. However, converting large amount of data from an SHM system into usable information is a great challenge to which special signal processing techniques must be applied. This study is devoted to identification of abrupt, anomalous and potentially onerous events in the time histories of static, hourly sampled strains recorded by a multi-sensor SHM system installed in a major bridge structure in Singapore and operating continuously for a long time. Such events may result, among other causes, from sudden settlement of foundation, ground movement, excessive traffic load or failure of post-tensioning cables. A method of outlier detection in multivariate data has been applied to the problem of finding and localizing sudden events in the strain data. For sharp discrimination of abrupt strain changes from slowly varying ones wavelet transform has been used. The proposed method has been successfully tested using known events recorded during construction of the bridge, and later effectively used for detection of anomalous post-construction events.

A seismic-resistant member with a shape memory alloy (SMA) rod was used in an exposed-type column base as a passive damper for building structures. Horizontal and vertical loading tests on the column base with SMA anchorage were done with increasing drift amplitude to investigate the restoring force characteristics of the column base. The results showed that (1) use of an SMA rod prevents deterioration of the restoring force characteristics, (2) use of an appropriate SMA material and a moderate-size rod can yield large deformation capacity and good restoring force characteristics, and (3) after a large drift in the building frame, SMA anchorage enables the original shape and resisting performance to recover with unloading.

Shape Memory Alloys (SMA) exhibit stable superelasticity between a reverse transformation finish temperature (A_f) and approximately 30°C above A_f, and therefore can sufficiently work as a superelastic material for structural use in building under the temperature in a construction environment. In order to verify the potential self-restoration capacity of mortar beams containing superelastic SMA reinforcements, static loading tests were conducted, and the results were then compared with those for a beam containing steel wires. The comparison indicates that (1) after maximum deflection, the mortar beam with SMA can return to an about one-tenth deflection compared with the maximum, (2) the range of deflection of the mortar beam with SMA is more than seven times that of the beam with steel, and (3) wide single crack can occur at the critical section due to a weaker bond force between SMA and mortar.

This study evaluates the properties of superelastic shape memory alloys under cyclical loading to asses their potential for applications in seismic resistant design and retrofit of civil engineering structures. Shape memory alloy bars are tested to evaluate the effect of bar size (diameter) and loading history on the strength, equivalent viscous damping, and recentering properties of the shape memory alloys in superelastic form. The bars are tested under both quasi-static and dynamic loading. The results show nearly ideal superelastic properties can be obtained in large diameter shape memory alloy bars. However, comparing these results to previous studies, the more common wire form of the shape memory alloys show higher strength and damping properties compared with the large bars. The recentering capabilities (based on residual strains) are not affected by the section size of the bar. Overall, the damping potential of superelastic shape memory alloys is low for large diameter bars, typically less than 7% equivalent viscous damping. Degradation of the superelastic properties of the shape memory alloys occurs for cyclical strain greater than 6%, leading to increased residual strains and reduction in energy dissipated. Finally, strain rate effects are evaluated by subjecting the shape memory alloys to loading rates representative of typical seismic loadings. The results show that increased loading rates lead to slight decreases in the equivalent damping, but have negligible effect on the recentering of the shape memory alloys.

Characteristics of piezoelectric dampers built with piezoelectric materials were investigated as part of a smart structural system for buildings. Piezoelectric materials can be applied not only to the sensors and the actuators, but also to the dampers. Here, first the damping mechanism and the complex stiffness for a piezoelectric damper were derived from the piezoelectric equations. Then, based on the complex stiffness and Biggs's formula, an equation used to evaluate the damping performance for building structures with piezoelectric dampers was derived. Finally, to determine the applicability and availability of piezoelectric dampers, the habitability of a building with piezoelectric dampers to strong wind was investigated for a high-rise steel apartment building. The results show that piezoelectric dampers enable high-rise apartments of practical dimensions to satisfy H-2 grade habitability.

In this paper, a previously designed and fabricated friction damper with four piezoelectric actuators was installed on the first story of a ¼ scale, 3-story steel structure. The performance of the damper and a simple control strategy was evaluated both numerically and experimentally under four modified earthquake ground motion records of various amplitudes. The seismic effectiveness and adaptability of the algorithm as well as the effect of damper saturation on structural responses were investigated. Numerical simulations of the structure agreed well with the experimental results. The proposed control strategy can not only effectively reduce the structural responses but also adapt to the varying excitations from both weak and strong earthquakes. Experimental results also indicated that a piezoelectric friction damper slightly saturated could be advantageous to the seismic mitigation of buildings. Over saturation will, however, degrade the performance of the semi-active control strategy.

As the world's first time implementation of MR-based smart damping technique in bridge structures, a total of 312 semi-active magneto-rheological (MR) dampers have recently been installed on the cable-stayed Dongting Lake Bridge for wind-rain-induced cable vibration control. Prior to the full implementation, a comprehensive field vibration test, has been conducted on the longest cable of 150 m to identify and compare damping performance of the cable-damper system under different damper installation setups and under a wide spectrum of voltage inputs to the MR dampers. Forced vibration experiments were carried out for the cable without damper, with single-damper setup, and with twin-damper setup, respectively. One purpose of this in-situ experimental investigation is to determine the optimal input voltage which achieves maximum system damping for the aim of designing a multi-switch control strategy. Due to geometric nonlinearity of cables and hysteretic nonlinearity of MR dampers, the equivalent modal properties of the cable-damper system are deemed to be amplitude-dependent. Keeping this in mind, a Hilbert transform based method is deployed in the present study to identify the amplitude-dependent natural frequencies and modal damping from the sinusoidal-decay response data. The experimental and identification results show that the equivalent modal damping ratios of the system are noticeably dependent on vibration amplitude and the relevance of the natural frequencies to vibration amplitude is negligible. The single-damper setup is competitive with the twin-damper setup in suppressing in-plane vibration of the cables. However, when mitigation of cable out-of-plane vibration is also required, the twin-damper setup performs much better. For both setups, the value of optimal voltage is found to be mode-dependent and amplitude-dependent.

This paper addresses the problem of formulating a feedback control law for the semiactive control of a class of two-span bridge, which is equipped with controllable friction devices at the joints between the columns and the deck. A finite element model is available to represent the essential dynamical features of the bridge. Based on this model, a Lyapunov-based robust semiactive control law is designed, which uses feedback from the nodes where the devices are located. Two sources of uncertainties are considered in the design: a first order actuator dynamics and a seismic excitation at the column supports. After the formulation of the control law, numerical tests are performed to assess the efficiency of the control scheme to reduce the response of the bridge.

The development of implementable control strategies that can fully utilize the capabilities of semi-active control devices is a challenging task due to the intrinsically nonlinear characteristics of the problem. In this study, a multivariable adaptive fuzzy controller is derived for a multiple-input and multiple-output nonlinear system, and a multivariable adaptive fuzzy control strategy is proposed accordingly for the use of magnetorheological (MR) dampers to protect buildings against dynamic hazards, such as severe earthquakes and strong winds. The proposed control strategy involves the design of fuzzy controllers and adaptation laws. The control objective is set to minimize the difference between some desirable response and the response of the combined system by adaptively adjusting MR dampers. The use of the adaptation law eliminates the needs for acquiring characteristics of the combined system in advance. The combination of the fuzzy controller and the adaptation law provides a robust control mechanism that can be used to protect nonlinear or uncertain structures subjected to random loads. Numerical and analytical results are presented to illustrate the application of the proposed control strategy.

A sizeable number of efforts have sought to instrument bridges for the purpose of structural monitoring and assessment. The outcomes of these efforts, as gaged by advances in the understanding of the definition of structural damage and their role in sensor selection as well as in the design of cost and data-effective monitoring systems, has itself been difficult to assess. The authors' experience with the design, construction, and operation of a monitoring system for the south-bound Kishwaukee Bridge has provided several lessons that bear upon these concerns. In this paper we describe certain aspects of the design of our Unix-based monitoring system. The system, patterned after similar systems developed for kick detection and well-control in the oil industry, has performed well in providing a continuous, low-cost monitoring platform for bridge engineers with immediately relevant information.

This paper presents a remote state monitoring system designed for and installed on the Hongcaofang Crossroad Bridge in Chongqing, China. In this system, three kinds of sensor, one of which is new, are installed in the bridge to periodically collect strain and deflection information. To control the operation of the sensors, a local computer is integrated in the pier of the bridge. The local computer processes the data from sensors, records processed results, and sends the state information to a host computer through the local Public Service Telephone Network (PSTN) using an ordinary modem. At the other terminus, the host computer receives and analyzes the data, stores the history information, queries the health state, and extracts abnormity information regarding the bridge. With the interconnect technology available through the PSTN, real time state information can be obtained on command in the monitoring room far from the bridge. This on-line monitoring system operated on the Hongcaofang Bridge for over two years. This paper reviews some of the more important results regarding both the strain and the two-dimensional deflection of the bridge, and discusses the experience gained thus far.

This paper briefly describes a health monitoring system designed for use on the Dafosi Bridge, the largest cable-stayed bridge across the Yangtze River in western China. The system can be divided into two major components, one for measurement, and one for control and data processing. The measurement system itself includes four sensing subsystems relating to: 1) fiber optic strain sensing, 2) displacement sensing, 3) temperature sensing, and 4) dynamic measurements. The control and data processing system consists of three subsystems: 1) a local computer, 2) a communication subsystem, and 3) a host computer. Sensor outputs are pre-processed locally and sent to the host computer at the management center via the Internet. The system design and implementation are reviewed, and the results of data from two sensing subsystems are presented.

A state-of-art design of a wireless sensing unit, which serves as the fundamental building block of wireless modular monitoring systems (WiMMS), has been optimized for structural monitoring sensing applications. Employing wireless communications as a primary means of data transfer, the high-cost but fragile cables of traditional tethered monitoring systems is eradicated resulting in a low-cost yet flexible monitoring infrastructure. An additional innovation is the inclusion of advanced embedded microcontrollers to accommodate the computational tasks of engineering and decision support analysis. To quantify the performance of the wireless sensing unit, field validation upon a full-scale benchmark structure is undertaken. The Alamosa Canyon Bridge in New Mexico is instrumented with wireless sensing units and a traditional cable-based monitoring system in parallel. Forced vibrations are applied to the bridge and monitored using both (wireless and tethered) data acquisition systems. Recorded time-history measurements are used to identify the modal properties of the structural system. The performance of the wireless sensing units is compared to that of the commercial wire-based monitoring system.

Stockholm consists of several islands connected by a number of bridges. Many of these bridges need to be repaired or replaced because of their age. Replacing and repairing existing bridges are of economic concern for many local authorities and governments. In order to minimize the costs for reparation and maintenance and to ensure the safety of civil infrastructures, there is an increasing need in our society for health monitoring of bridges. Monitoring helps us to understand the real behavior of the structure and lets us verify the design uncertainties. It is clear that monitoring will have a major role in the design of the future structures, and suitable monitoring systems will be designed together with the structures. The new Årsta Railway Bridge, which is under construction in Stockholm, is an optimized and very complex ten-span pre-stressed concrete structure. Each span has a length of 78 meters. The Swedish National Railway Administration (Banverket) has initiated a measuring campaign in order to study and understand the dynamic and static behavior of the bridge. The main objectives are: firstly, to monitor the bridge during the first 10 years including construction and testing period, and secondly, for the static study, to compare traditional measuring technique using strain transducers developed at Royal Institute of Technology, KTH, Sweden, with the fiber optic sensors developed by SMARTEC, Switzerland. After a short overview of the existing measurement systems and technique for measuring civil infrastructures, the paper illustrates the installation of KTH's and SMARTEC's monitoring systems. In addition, some very early results are included.

From the point of view of structural health monitoring, it is extremely important to discriminate alteration in structural behavior/response attribute due to damage from that due to environmental and operational fluctuation. In this paper, the correlation between natural frequencies and temperature is investigated for the cable-stayed Ting Kau Bridge by using measurement data from a long-term monitoring system installed on this bridge. One-year continuously acquired data from 45 accelerometers (a total of 67 channels) and 83 temperature sensors are used for this study. The data from 20 temperature sensors at the locations susceptible to temperature are first selected for the correlation analysis. Natural frequencies of the first 10 modes are identified by spectral analysis of the acceleration data at one-hour intervals. In order to ensure the identification accuracy, the natural frequency for a specific mode is determined using only the data from the accelerometers which produce large spectral peaks at that mode. The identified natural frequencies for each hour are used to correlate with the one-hour average temperatures measured from the 20 sensors during the same time. Based on the one-year measurement data which cover a full cycle of varying environmental and operational conditions, a four-layer perceptron neural network with 20 input nodes and 1 output node is trained for each mode to represent the relation between the measured temperatures (input) and the corresponding natural frequency (output). The configured neural networks for the 10 modes show excellent capabilities for mapping between the temperatures and natural frequencies for all the one-year measurement data.

Wireless health monitoring schemes are innovative techniques, which effectively remove the disadvantages associated with current wire-based sensing systems, i.e., high installation and upkeep costs. However, recorded data sets may have relative time-delays due to the blockage of sensors or inherent internal clock errors. In this paper, two algorithms are proposed for the synchronization of the recorded asynchronous data measured from sensing units of a wireless monitoring system. In the first algorithm, the input signal to a structure is measured. Time-delay between an output measurement and the input is identified based on the minimization of errors of the ARX (auto-regressive model with exogenous input) models for the input-output pair recordings. The second algorithm is applicable when a structure is subject to ambient excitation and only output measurements are available. ARMAV (auto-regressive moving average vector) models are constructed from two output signals and the time-delay between them is evaluated based on the minimization of errors of the ARMAV models. The proposed algorithms are verified by simulation data and recorded seismic response data from multi-story buildings.

An automatic modal identification program is developed for continuous extraction of modal parameters of three cable-supported bridges in Hong Kong which are instrumented with a long-term monitoring system. The program employs the Complex Modal Indication Function (CMIF) algorithm to identify modal properties from continuous ambient vibration measurements in an on-line manner. By using the LabVIEW graphical programming language, the software realizes the algorithm in Virtual Instrument (VI) style. The applicability and implementation issues of the developed software are demonstrated by using one-year measurement data acquired from 67 channels of accelerometers deployed on the cable-stayed Ting Kau Bridge. With the continuously identified results, normal variability of modal vectors caused by varying environmental and operational conditions is observed. Such observation is very helpful for selection of appropriate measured modal vectors for structural health monitoring applications.

A new method for identifying dynamic parameters of a structure by measuring its first several frequencies and mode shapes is presented in this paper. Accurate estimates of the dynamic characteristics of a structure using limited measurement data are necessary for applications such as damage localization and finite element model verification. This method is developed from the unconstrained simplex method by introducing some pratical constraint conditions. The approach is not limited by either the minimum order of required eigenvalue and eigenvector pairs or the completeness of each order, for instance, even only a subset of frequencies or mode shapes are sufficient for a given order to yield acceptable identification results. Two numerical examples for identifying the stiffness distribution of a ten-story shear building under different health conditions are provided. The identified stiffness agrees with the physical model quite well. It is shown that this method has the advantages of good accuracy in calculation and great potentiality for most applications in similar structures or areas due to the fact that it is not only very robust but also not so strict with measurement methods and the amount of required information in field tests.

A "smart" structure has many functions, including monitoring, repairing, shape formation, and learning. Recently, interest in applying a monitoring system to a structure for quality assurance and for evaluating seismic risk has been strong. Monitoring system is useful to diagnose the structural condition and detect structural damage and degradation. In this study, we developed a monitoring system to assess the structural integrity of a structure. This system includes a diagnostic system for structural damage and degradation based on mode parameters and wave propagation. The damage detection strategy is to first detect the damage sites globally by using an improved MDLAC (Multiple Damage Location Assurance Criterion) method, and then to evaluate the damage sites locally by using wave propagation. As a result, it is pointed out that there is a possibility to confirm the diagnostic system by utilizing these two methods.

It has been the goal of railroad track inspectors and researchers alike to constantly strive to improve the methods being used for rail inspection. This paper proposes a method to analyze long-range rail test data with the continuous wavelet transform in order to extract reflection coefficients which may then be used to classify defects. The feasibility of using three different dynamic rail tests for defect classification of four sizes of transverse head defects was investigated. Optimum frequencies to be used for maximum sensitivity to the defects were identified.

This paper summarizes the ongoing work at the University of Texas to develop wireless sensors to monitor the condition of civil engineering structures. The state sensors will be attached to or embedded in the structures during construction and will be interrogated during routine inspections of the structure. Each sensor comprises two components: a switch to detect the damage within the structure and a resonant circuit to transmit the information to the inspector. Prototype sensors have been developed to detect the presence of cracks in welded steel construction and corrosion in reinforced concrete construction.

Resident sensors are envisioned for civil infrastructure applications, but providing long-term power for such devices remains a design challenge. An ideal solution would be to scavenge energy from structural strains and make the scavenging component a part of the sensor package. In principle, piezoelectric materials are suited to that role, and studies by others have demonstrated the feasibility of energy scavenging from flexible PZT devices operated at large strains and high strain rates. We have conducted experiments to collect electrical energy from PZT ceramics. We summarize the governing piezoelectric equations and outline the most convenient forms to use for the energy scavenging problem, illustrated by tracing one complete loading cycle. We review the material properties for the three PZT ceramics used in our experiments. We show experimental results recording voltage and charge in the cases of open-circuit, resistive loads, and capacitive loads, showing good agreement with analytical predictions. However, the greatest challenge is the approach to energy storage. In theory, capacitors can store energy but at varying voltage and with non-negligible leakage, whereas a battery can store energy at constant voltage with little leakage. We conducted experiments on both approaches, and we discuss our findings of the feasibility and efficiency of battery recharging at the scale of our devices, which have nominal dimensions of 10x10x1 mm.

The authors have developed an electrically conductive fiber reinforced composite that its electrical resistance changes almost in proportion to strain. This material was tested for its tensile and bond behaviors. As a result, it was discovered that this material applied for the strengthening of concrete structures is highly effective to diagnose cracks in the concrete.

Once every generation, Switzerland treats itself to a National Exhibition commissioned by the Swiss Confederation. Expo 02 was spread out in five "Arteplage" over a whole region: the land of the three lakes, on the shores of the lakes of Biel, Murten and Neuchatel, which are located in the northwest of Switzerland. Each "Arteplage" relates to a theme, which is reflected in its architectures and exhibitions. The "Arteplage" of Neuchatel was related to "Nature and Artificiality;" A big steel-wood whale eating a village represents the fairy tale named "Pinocchio" from the Italian writer Collodi. The "Piazza Pinocchio" was built together with other exposition buildings on one large artificial peninsula. The belly of the whale holds the exposition dedicated to robotic and artificial intelligence, while the rest of the village was developed on two floors with steel piles/beams and wood walls and floors. A fiber optic sensor system was commissioned to monitor the visitor's loads over the whole "Piazza Pinocchio." The main requirements were: real-time computer-screen figure-form results of the live loads during 18 hours a day, automatic thermal-induced strain compensation, real-time warnings and pre-warnings for each single pile, automatic phone call advises when reaching warning thresholds and remote monitoring for complete management of the monitoring sytem. The SOFO system based on low coherence fiber optic deformation sensors was selected to carry out the requirements. The aim of this paper is to present an overview of the project, the installation solution, the results, and data analysis of the installed monitoring system.

An example of structural health monitoring system using FBG-based optical fiber sensors for the damage tolerant building structure is presented. The damage tolerant building is equipped with several passive dampers for absorbing earthquake input energy, and the structural health monitoring system is focused to monitor performance of these dampers. FBG-based optical fiber sensor modules are developed to apply in structural health monitoring system for damage tolerant building structures. The system is verified on static measurement and dynamic measurement in earthquake.

In recent years, innovative vibro-modulation technique has been introduced for detection of contact-type interfaces such as cracks, debondings, and delaminations. The technique utilizes the effect of nonlinear interaction of ultrasound and vibrations at the interface of the defect. Vibration varies on the contact area of the interface modulating passing through ultrasonic wave. The modulation manifests itself as additional side-band spectral components with the combination frequencies in the spectrum of the received signal. The presence of these components allows for detection and differentiation of the contact-type defects from other structural and material inhomogeneities. Vibro-modulation technique has been implemented in N-SCAN damage detection system. The system consists of a digital synthesizer, high and low frequency amplifiers, a magnetostrictive shaker, ultrasonic transducers and a PC-based data acquisition/processing station with N-SCAN software. The ability of the system to detect contact-type defects was experimentally verified using specimens of simple and complex geometries made of steel, aluminum, composites and other structural materials. N-SCAN proved to be very effective for nondestructive testing of full-scale structures ranging from 24 foot-long gun barrels to stainless steel pipes used in nuclear power plants. Among advantages of the system are applicability for the wide range of structural materials and for structures with complex geometries, real time data processing, convenient interface for system operation, simplicity of interpretation of results, no need for sensor scanning along structure, onsite inspection of large structures at a fraction of time as compared with conventional techniques. This paper describes the basic principles of nonlinear vibro-modulation NDE technique, some theoretical background for nonlinear interaction and justification of signal processing algorithm. It is also presents examples of practical implementation and application of the technique.

This study was aimed at developing and validating a new type of coaxial cable sensors that can be used to detect cracks or measure strains in reinforced concrete (RC) structures. The new sensors were designed based on the change in outer conductor configuration under strain effects in contrast to the geometry-based design in conventional coaxial cable sensors. Both numerical simulations and calibration tests with strain gauges of a specific design of the proposed cables were conducted to study the cables' sensitivity. Four designs of the proposed type of sensors were then respectively mounted near the surface of six 3-foot-long RC beams. They were tested in bending to further validate the cables' sensitivity in concrete members. The calibration test results generally agree with the numerical simulations. They showed that the proposed sensors are over 10~50 times more sensitive than conventional cable sensors. The test results of the beams not only validate the sensitivity of the new sensors but also indicate a good correlation with the measured crack width.

Breaks often occur to urban water distribution systems under severely cold weather, or due to corrosion of pipes, deformation of ground, etc., and the breaks cannot easily be located, especially immediately after the events. This paper develops a methodology to locate a break in a water distribution system by monitoring water pressure online at some nodes in the water distribution system. For the purpose of online monitoring, supervisory control and data acquisition (SCADA) technology can well be used. A neural network-based inverse analysis method is constructed for locating the break based on the variation of water pressure. The neural network is trained by using analytically simulated data from the water distribution system, and validated by using a set of data that have never been used in the training. It is found that the methodology provides a quick, effective, and practical way in which a break in a water distribution system can be located.

In earlier work we developed a MEMS phased array transducer, fabricated in the MUMPs process, and we reported on initial experimental studies in which the device was affixed into contact with solids. We demonstrated the successful detection of signals from a conventional ultrasonic source, and the successful localization of the source in an off-axis geometry using phased array signal processing. We now describe the predicted transmission and coupling characteristics for such devices in contact with solids, demonstrating reasonable agreement with experimental behavior. We then describe the results of flaw detection experiments, as well as results for fluid-coupled detectors.

Elastic and Electromagnetic waves provide important information about the soil mass in the near-surface. In order to facilitate the application of geophysical technique to soil characterization, experiments are performed for each wave. The first application is related to characterization of unsaturated particulate materials using shear wave. The small strain stiffness is continuously measured on specimens subjected to drying. Experimental results show that changes in stiffness are related to changes in interparticle forces such as capillarity, bonding due to ion sharing, buttress effect due to fine migration, cementation due to salt precipitation. Several phenomena associated with the evolution of capillary forces during drying are identified as well. The second application is relevant to the electromagnetic wave. A needle-size probe is developed to assess the spatial distribution of void ratio and other properties in laboratory specimens. Experimental results show that the spatial variability of void ratio affects shear strength so that not only mean void ratio but its variation should be considered in design analysis.

Magnetic measurements were performed on steel cables subjected to a magnetic field and the response measured without contact using Faraday's law, to estimate the effect of temperature and corrosion on magnetic properties of structural steel. Magnetic measurements were compared with electrochemical measurements to correlate corrosion quantitatively in terms of mass loss. The results obtained from the present work are helpful in bounding the achievable sensitivity for conventional magnetoelastic corrosion sensing and for suggesting the need for alternate techniques.

Blue Road Research and the University of California have been collaborating over the past three years to develop a system employing fiber Bragg grating strain sensors and modal analysis to provide real-time, quantitative information on the structure's response to a dynamic input (such as a seismic event), and a fast prediction of the structure's integrity. This research, being funded by the National Science Foundation, has several publications showing its strong progress. This year marks a significant step forward in this effort, with the successful completion of a full-scale test performed on a longitudinal carbon shell girder being tested as part of the planned I-5/Gilman Advanced technology Bridge in California, USA.

Composite materials based on glass, carbon and aramid fibers have many advantages such as fast application, lightweight and corrosion resistance, and are widely diffused for manufacturing of tanks, pipings and for restoration, upgrade and seismic retrofit of structures and historical heritage. As several questions regarding long term durability of composite strengthenings remains still unsolved, monitoring of strain and temperature is strongly recommended, respectively to assess proper load transfer and no glass phase transition of the polymeric matrix. In this research work strain and temperature distributed sensing trough Brillouin scattering in single-mode optical fibers was used in different tests in order to understand the influence of different fiber coatings and embedding techniques. Pressure tests were performed on a GFRP piping with inhomogeneous strengthening layout and Brillouin strain data were compared with conventional strain gages. A smart CFRP material has been also developed and evaluated in a seismic retrofit application on an historical building dated 1500 that was seriously damaged in the earthquake of 1997. The developed embedding technique has been demonstrated successful to obtain fiber-optic smart composites with low optical losses, and the data comparison between Brillouin and resistive strain gauges confirms Brillouin technique is very effective for composite monitoring.

In order to do continuous health monitoring of large structures, it is necessary that the distributed sensing of strain and temperature of the structures are to be measured. So, we present the strain and temperature measurement distributed on a beam using fiber optic BOTDA(Brillouin Optical Time Domain Analysis) sensor. Fiber optic BOTDA sensor has good performance of strain measurement. However, the signal of fiber optic BOTDA sensor is influenced by strain and temperature. Therefore, we applied an optical fiber on the beam as follows: one part of the fiber, which is sensitive the strain and the temperature, is bonded on the surface of the beam and another part of the fiber, which is only sensitive to the temperature, is located at the same position of the strain sensing fiber. Therefore, the strains can be determined from the strain sensing fiber with compensating the temperature from the temperature sensing fiber. These measured strains were compared with the strains from electrical strain gages. After temperature compensation, it was concluded that the strains from fiber optic BOTDA sensor had good agreements with those values of the conventional strain gages.

A number of reports have been published on investigation of damage to pile foundation of buildings due to the 1995 Hyogoken-Nambu earthquake. The result of these investigations indicates the urgent need for development of techniques to enable quick and accurate assessment of damage to piles following major earthquakes. Authors have been conducting a series of researches on the development of monitoring techniques to detect damage to concrete piles due to the earthquakes. The sensor using carbon fiber has already been proposed, and its applicability has been investigated by various kinds of experiments on carbon fiber and the sensor. In this paper, performance of the sensor evaluated by experimental analysis is discussed in detail. Then, the examples of installation of the sensor to actual structures are described to show the applicability to practical purpose.

Fiber Optic Polarimetric Sensors (FOPS) can be used for static and dynamic integrated deformation/strain measurement. It has also been shown to capture natural and excited frequency response spectra for structural health assessment. This is achieved by relating vibrational frequency changes to structural stiffness variations caused by damage. The deployment of the FOPS for this purpose is a relatively new endeavor and many factors pertaining to its use have yet to be investigated in detail -- including the parameters affecting its signal acquisition and the subsequent interpretation of acquired signals. Using a military mobile bridge as the test specimen, it is found that the FOPS yields a unique frequency spectrum containing information on damage severity and location for each specimen. The reliability of this signature frequency spectrum depends primarily on empirical parameters such as mounting location, method of bonding, type of structural supports used, strength of excitation impact and location of impact. Further, owing to the FOPS' unique global sensing nature, a new damage quantification system has to be used, which is also dependent on the consistency of the signal acquisition process for accuracy. Both finite element and experimental modal analyses were used in the development of an optimal FOPS configuration for signal reliability.

A powerful Volterra/Wiener Neural Network (VWNN) is designed to reflect the underlying dynamics of hysteretic systems. The nonlinear response of multi-degree-of-freedom systems subjected to force excitation can be tracked using this neural network. More importantly, the inner-workings of the network, such as the design parameters as well as the weights and biases, can be loosely related to physical properties of dynamic systems. This effort differs markedly from what is typically done for neural networks as well as the original version of the VWNN in Ref. 1. An adaptive training algorithm and improved formulation of high-order nodes are adopted to enable fast training and stable convergence. A training example is provided to demonstrate that the VWNN is able to yield a unique set of solutions (i.e., the weights) when the values of the controlling design parameters are fixed a priori. The selection of these design parameters in practical applications is discussed. The advantages of the VWNN illustrate the potential of applying highly flexible nonparametric identification techniques in a parametric fashion to suit the needs of structural health monitoring and damage detections.