System identification is especially important for structural health monitoring and vibration control. It is one of the critical factors to control structural vibration with high quality and evaluate whether control method can be applied or not. In this paper, a kind of multi-branch BPNN model is proposed to identify structural dynamic system. In this model, the primary factors that affect structure's dynamic response, namely structure state variables and seismic inputs, are separately treated as the branches of the model, which is expected to enhance prediction precision. The aim of identification is to make the trained model be able to accurately predict structure's future dynamic response. When the model is established, it can be trained with collected dynamic response and seismic wave data. The vibration law of the structure is deposited in the weights of the trained multi-branch BPNN model. Then the model can be used to predict structure's future dynamic response. In this paper, a numerical example is given. The analytic result turns out that the proposed identification model can accurately predict structure's future dynamic response after being trained.

The identification of damage in structural systems, including characterization of damage location and severity, is of extreme interest to the structural engineering profession. To date, many damage detection methods have been proposed that utilize global structural response measurements in the time and frequency domains to hypothesize the existence of structural damage. The accuracy and robustness of current damage detection methodologies could be improved through the use of active sensors. Active sensors, such as piezoelectric pads, impart low-energy acoustic excitations into structural elements and can record the corresponding system behavior. In this study, a novel methodology utilizing the input-output behavior of actively sensed structural elements is proposed. The poles of ARX time-series models describing modal frequencies and damping ratios are plotted upon the discrete-time complex plane and Perceptron linear classifiers employed to determine if poles of the structural element in an unknown state (damaged or undamaged) can be separated with those of the undamaged structure. If poles of the unknown state are separable from those of the undamaged state, the system is diagnosed as damaged. A simple cantilevered aluminum plate damaged by hack saw cuts is actively sensed by piezoelectric pads to show the efficacy of the proposed damage detection methodology. Furthermore, the number of misclassified poles and the final value of the Perceptron criterion function can be shown to be correlated to the severity of the damage.

A structural health monitoring (SHM) system for the purpose of maintenance cost reduction or performance guarantee of civil, mechanical and aerospace systems is proposed. The proposed system utilizes an active sensing diagnostic technique to predict the location of structure damage with a limited number of PZT elements and some vibrators if necessary. As PZT elements are inexpensive, small in size, and function as sensors and actuators, it is possible to integrate them into a structural component without reducing structural performance. In this study, an active sensing diagnostic technique using PZT elements is proposed to characterize damage in plates. Built-in PZTs working as Lamb wave emitters and receivers are used to predict damage by comparing differences of Lamb wave signals recorded before and after damage. Such differences are due to the change of the physical parameters relevant to damage in the structure. Amplitude modulation is used in this paper by actuating PZTs with different driving signals to effectively extract damage features. Modulated signals are processed to form feature vectors for support vector machines to estimate damage automatically.

In this paper Jiles-Atherton model, a phenomenological model, is proposed to model physical properties of structural steel and magnetite(corrosion product). The Jiles-Atherton model parameters based on mean field approximation were optimized to simulate the curves obtained from magnetic measurements using conventional quasi-static method. Results from hot rolled steel, a low carbon steel, were simulated using Jiles model to understand and correlate the measured and simulated curves. Hysteresis curves for magnetite, one of the most prevalent corrosion product and the only ferromagnetic component, are obtained to simulate the effect of corrosion products on the magnetic measurements of corroded structural steel. Since corrosion is initially a surface phenomenon, high frequency measurements were suggested from the simulations obtained to reduce the skin depth estimates and increase the accuracy of corrosion measurement.

In this paper, we present a damage monitoring method to detect and track the evolution of structural damages based on the measurements acquired by vibratory gyroscopes. We propose a modal flexibility-based damage index that quantifies the local bending flexibility of the beam structures by conducting virtual local loading tests. We use vibratory gyroscopes to measure the angular mode shapes which are necessary to assess the proposed damage index. A time-frequency analysis-based simple scheme is developed to identify the time-varying mode shapes to detect and track the evolution of the damage index. Experimental results show that the proposed monitoring method is capable to indicate the location of the damages as well as the time when they occur.

Blue Road Research and the University of California at San Diego have been collaborating over the past four years to develop a system employing fiber Bragg grating strain sensors and modal analysis to provide real-time, quantitative information on a bridge’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. In the latter part of 2004, this system will be installed on the Broadway Bridge in downtown Portland, Oregon, USA. In preparation for this deployment, the system is undergoing testing from the sensors through the readout unit and bridge modeling to ensure its performance once installed. The steps of preparation and testing are discussed here.

Permanent damage in various materials and constructions often causes high-energy high-frequency acoustic waves. To detect those so called ‘acoustic emission (AE) events’, in most cases ultrasonic transducers are embedded in the structure or attached to its surface. However, for many applications where event localization is less important, an embedded low-cost multimode optical fiber sensor configured for event counting may be a better alternative due to its corrosion resistance, immunity to electromagnetic interference and light-weight. The sensing part of this intensity-modulated sensor consists of a multimode optical fiber. The sensing principle now relies on refractive index variations, microbending and mode-mode interferences by the action of the acoustic pressure wave. A photodiode is used to monitor the intensity of the optical signal and transient signal detection techniques (filtering, frame-to-frame analysis, recursive noise estimation, power detector estimator) on the photodiode output are applied to detect the events. In this work, the acoustic emission monitoring capabilities of the multimode optical fiber sensor are demonstrated with the fiber sensor embedded in the liner of a Power Data Transmission (PDT) coil to detect damage (delamination, matrix cracking and fiber breaking) while bending the coil. With the Hankel Total Least Square (HTLS) technique, it is shown that both the acoustic emission signal and optical signal can be modeled with a sum of exponentially damped complex sinusoids with common poles.

In order to address application problem of fiber optic sensor in concrete, characteristics of concrete was analyzed deeply. Mechanical and metrological characteristics of both bare and packed fiber Fabry-Perot strain sensor were also analyzed in details. Modulus requirement and dimensional requirement of fiber strain sensor for concrete was deduced. A special measure of sleeve was proposed to get rid of drawback of packed fiber Fabry-Perot strain sensor in concrete. Corresponding procedures was also proposed to ensure survivability of the sensors when embedding fiber sensor into a concrete structure. An application example of fiber Fabry-Perot strain sensor network system in the Dafosi Bridge of Yangtze River at Chongqing has been presented to demonstrate the validity of this technique. With help of presented technique, 45 fiber Fabry-Perot strain sensors had been successfully embedded in 5 segments of gird during 9 months construction. The system was put into operation automatically from January 2003. Some typical results recorded by the system were presented. Constructing progress, tardo distortion trend, and temperature dependent fluctuation of gird was revealed in the result.

This paper discusses of the monitoring of the temperature distribution by an optical fiber Bragg grating sensor system. The sensors are embedded in a pipe underground. Ground-source heat pump system utilizes the thermal energy of the underground soil to heat or cool a building. Optical fiber Bragg grating sensors are used to measure the temperature distribution of the soil and the thermal difference of the circulating water system. The sensors were designed and packaged delicately to eliminate the influence of strain as well as to improve the thermal sensitivity. Three Bragg grating sensors were placed at intervals of five meters in a deep well with a length of 25 meters. Data were collected immediately after the installation of the water pipes using a commercial FBG interrogation system. The ultimate purposes of these tests are to measure the water temperature fluctuation along the pipe at the places where the sensors were installed during the operation of the ground source heat pump system, and evaluate the reliability of FBG sensor system for a long period.

Optical fiber sensors show superior potential for structural health monitoring of civil structures to ensure their structural integrity, durability and reliability. Apparent advantages of applying fiber optic sensors to a marine structure include fiber optic sensors’ immunity of electromagnetic interference and electrical hazard when used near metallic elements over a long distance. The strains and accelerations of the newly proposed model of a single post jacket offshore platform were monitored by fiber Bragg grating (FBG) sensors. These FBG sensors were attached to the legs and the top of the platform model in parallel with electric strain gauges or traditional piezoelectric accelerometers, respectively. Experiments were conducted under a variety of loading conditions, including underwater base earthquake simulation dynamic tests and static loading tests. Underwater seismic shaking table was utilized to provide the appropriate excitations. The natural frequencies measured by the FBG accelerometer agree well with those measured by piezo-electrical accelerometers. The monitoring network shows the availability of applying different fiber optic sensors in long-distance structural health monitoring with frequency multiplexing technology. Finally, the existing problems of packaging, strain transferring ratio between the bare fiber and the host structure on which the fiber embedded, and installation and protection of fiber optic sensors are emphasized.

The long-term goal of this project is the development of embedded, optimally distributed, multi-scale sensing methodologies that can be integrated into material systems for failure identification in structural systems. The coupling of sensor data fusion with a three-dimensional predictive framework will provide insight and understanding of events that are difficult, if not impossible, in any experimental study, such as subsurface damage and crack nucleation in structural systems. The current work presents an experimental study of the survivability and degradation behavior of an optical fiber Bragg grating sensor, surface mounted on a woven fiber composite material system during multiple low velocity impacts. The results reveal that as sensor degradation occurs, additional coupling phenomena other than Bragg reflection are observed in the grating sensor. From these additional modes, information on the sensor/host bond and fiber degradation is obtained.

Health monitoring of defective flat plates is achieved through the use of a distributed network of sensors that can map the deflection profile of these plates. The mapped deflection profiles are then used to extract the structural power flow as an effective criterion for identifying the exact location of the defects. In this paper, emphasis is placed on developing the theoretical equations governing monitoring the deflection and localizing the defects using the theory of finite elements. The predictions of the developed theoretical models are validated experimentally using a scanning laser vibrometer as means for monitoring the structural power flow over defective plates. The accuracy and effectiveness of the power flow maps in localizing the defects are demonstrated and compared with conventional modal parameter identification methods that fail to identify small defects. The presented concepts can be easily employed in health monitoring of more complex and critical structures such as aircraft fuselages and bridges where small defects can be detrimental to their safe operation and their locations can not be easily identified by conventional modal identification methods.

As in-situ structural integrity monitoring disciplines mature, there is a growing need to process sensor/actuator data efficiently in real time. Although smaller, faster embedded processors will contribute to this, it is also important to develop straightforward, robust methods to reduce the overall computational burden for practical applications of interest. This paper addresses the use of equivalent circuit modeling techniques for inferring structure attributes monitored using impedance perturbation spectroscopy. In pioneering work about ten years ago significant progress was associated with the development of simple impedance models derived from the piezoelectric equations. Using mathematical modeling tools currently available from research in ultrasonics and impedance spectroscopy is expected to provide additional synergistic benefits. For purposes of structural health monitoring the objective is to use impedance spectroscopy data to infer the physical condition of structures to which small piezoelectric actuators are bonded. Features of interest include stiffness changes, mass loading, and damping or mechanical losses. Equivalent circuit models are typically simple enough to facilitate the development of practical analytical models of the actuator-structure interaction. This type of parametric structure model allows raw impedance/admittance data to be interpreted optimally using standard multiple, nonlinear regression analysis. One potential long-term outcome is the possibility of cataloging measured viscoelastic properties of the mechanical subsystems of interest as simple lists of attributes and their statistical uncertainties, whose evolution can be followed in time. Equivalent circuit models are well suited for addressing calibration and self-consistency issues such as temperature corrections, Poisson mode coupling, and distributed relaxation processes.

A semi-analytic method is presented for analyzing the behavior of layered, circular piezoelectric cylinders under axisymmetric mechanical and electric loads. Discretization occurs in the radial direction so that any number of layers with distinct material properties and thickness can be accommodated. Axial and circumferential behaviors are obtained analytically. Mechanical loads include axial force, torque, longitudinal and circumferential surface shears, and arbitrary pressure distributions. Electric loads include voltage and charge distributions along the axis of the cylinder that may be applied on any layer’s surface. In the present approach, all loads are represented by power series in the axial coordinate. There are several advantages provided by the semi-analytic method. First, as part of the solution is analytic, it is more accurate than any fully discrete (e.g., finite element) method. It is also computationally more efficient than discrete methods as the dimension of the problem is reduced, essentially, by one order. Second, the method is more accurate than technical (beam, plate, shell) theories as the deformation of the cross-section is not constrained by any simplifying kinematic hypothesis. Third, it provides solutions for complex geometry and material distributions for which there are no analytic solutions. The method may be extended to general, nonhomogeneous cross-sectional geometries. Veracity of our implementation is demonstrated by comparing the results for various problems with those obtained via three-dimensional finite element methods. We also provide the analysis of a bimodal actuator to demonstrate the utility of the present technique for evaluating designs of smart structures with layered, axisymmetric geometries.

One of the most important aspects of detecting damage in the work-frame of structural health monitoring is increasing the sensitivity of the monitored feature to the presence, location, and extent of damage. Distinct from previous techniques of obtaining information about the monitored structure - such as measuring frequency response functions - the approach proposed herein is based on an active interrogation of the system. This interrogation approach allows for the embedding of the monitored system within a larger system by means of a nonlinear feedback excitation. The dynamics of the larger system is then analyzed in state space, and the shape of the attractor of its dynamics is used as a complex geometric feature which is very sensitive to damage. The proposed approach is implemented for monitoring the structural integrity of a panel forced by transverse loads and undergoing limit cycle oscillations and chaos. The nonlinear von Karman plate theory is used to obtain a model for the panel combined with a nonlinear feedback excitation. The presence of damage is modeled as a loss of stiffness in a portion of the plate. The sensitivity of the proposed approach to parametric changes is shown to be an effective tool in detecting damages.

Diagnostics capability of combat systems shall be compatible with the Army Diagnostic Improvement Program. Present systems are capable of performing health monitoring and health checks using internal embedded resources. They employ standard sensors and data busses that monitor data signals and built-in test (BIT). These devices provide a comprehensive source of data to accomplish an accurate system level diagnostics and fault isolation at line replaceable unit (LRU) level. Prognostics routines provide capability to identify the cause of predicted failure and corrective action to prevent unscheduled maintenance action. Combat system’s health status and prognostic information are displayed to operator, crew, and maintenance personnel. Present systems use common data/information interchange network in accordance with standards defined in the Joint Technical Architecture (JTA) to provide access to vehicle’s health data. The technologies utilized in present systems include embedded diagnostics, combat maintainer, schematic viewer, etc. Implementation of these technologies significantly reduced maintenance hours of combat systems. Health monitoring, diagnostics and prognostics of future systems will utilize federated software and probes approach. Gauges will determine if the system operates within acceptable performance bands by monitoring data provided by the probes. Health monitoring system will use models of missions to make intelligent choices considering tasks criticality.

Whatever specific methods come to be preferred in the field of structural health/integrity monitoring, the associated raw data will eventually have to provide inputs for appropriate damage accumulation models and decision making protocols. The status of hardware under investigation eventually will be inferred from the evolution in time of the characteristics of this kind of functional figure of merit. Irrespective of the specific character of raw and processed data, it is desirable to develop simple, practical procedures to support damage accumulation modeling, status discrimination, and operational decision making in real time. This paper addresses these concerns and presents an auto-adaptive procedure developed to process data output from an array of many dozens of correlated sensors. These represent a full complement of information channels associated with typical structural health monitoring applications. What the algorithm does is learn in statistical terms the normal behavior patterns of the system, and against that backdrop, is configured to recognize and flag departures from expected behavior. This is accomplished using standard statistical methods, with certain proprietary enhancements employed to address issues of ill conditioning that may arise. Examples have been selected to illustrate how the procedure performs in practice. These are drawn from the fields of nondestructive testing, infrastructure management, and underwater acoustics. The demonstrations presented include the evaluation of historical electric power utilization data for a major facility, and a quantitative assessment of the performance benefits of net-centric, auto-adaptive computational procedures as a function of scale.

Structural sensing systems that employ adaptive strategies have the potential to achieve superior performance over nonadaptive counterparts. Adaptation is a means that many systems use to improve performance to compensate for varying and uncertain circumstances. Structural sensing systems can use several different adaptive sensing techniques including adaptive signal processing, adaptive data acquisition protocols, rapidly deployable sensors and mobile sensors. Adaptive signal processing is where the processing that is applied to a given set of data is modified according to the information content in the data or external circumstances. Adaptive data acquisition can be implemented through modifying the acquisition parameters and through the modification of sensor location and spatial sensitivity. The adaptive deployment of sensors requires mobile sensors and mechanisms, such as robots, to move the sensors into more advantageous positions. While the enabling technologies of adaptive sensing systems are readily emerging, optimal and effective adaptive strategies remain largely unexplored. This paper will also discuss some of the issues related to developing effective adaptation strategies for sensing systems and present example applications of adaptive signal processing and mobile robotic sensing applications.

Increasingly, the demand to monitor structures in service is driving technology in new directions. Advances in many areas including novel sensor technologies afford new opportunities in structural health monitoring. 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. This work brings together many important developments over the last few years in several areas: developments in composites and the emergence of multifunctional composites, the emergence of a broad range of new sensors, smaller and lower power microelectronics with increased and multiple integrated functionality, and the emergence of algorithms that extract important structural health information from large data sets. This work seeks to leverage these individual advances by solving the challenges needed to integrate these into an information-aware composite structure. We present details of efforts to integrate and entrap connectorized microelectronic components within fiber/conductor braided bundles to minimize their impact as composite crack initiation centers. The bundles include conductors to transmit electric signals for power and communications. They are suitable for inclusion in woven composite fabrics or directly in the composite lay-up. The low-power electronic devices can operate on a multi-drop and point-to-point networks. Future directions include implementing in-network local processing, adding a greater range of sensors, and developing the composite processing techniques that allow sensor network integration.

The authors have developed such sensors which can be applied to steel structures for health monitoring. The sensor is manufactured by placing copper foils (electrodes) on polymer film and splaying the electrically conductive material on the surface. The electrically conductive material is composed of resin and carbon particles. Carbon particles form a continuous link each other. The strain due to the deformation of the steel members influences the electrical resistance. We can evaluate the strain of the steel members by measuring changing rate of the electric resistance, and then estimate the damages of the steel members. A strain monitoring system with this sensor enables low cost, because it does not need special equipment except for an electrical resistance meter. The authors carried out experimental tests on steel structure specimens with the film sensor attached. The specimens were beam-to-column connections of steel structures buildings subjected to alternative cyclic deformation correspond to input by severe earthquakes. Based on the tests, we investigated the performance and applicability of the sensor for the members of steel structures. As the test results, it turned out that the sensor is able to be used for strain detecting of steel structures.

A novel approach for NDE of polymeric materials utilizing the dielectrostriction effect is presented. Any dielectric material exhibits dielectrostriction effect which is defined as variation of dielectric properties of the material with deformation. This phenomenon resembles well known photoelastic effect which has been widely used for NDE of transparent materials. The major difference is that dielectrostriction measurements can be conducted using a lower frequency than optical range of electromagnetic field. Thus, the dielectrostriction measurements can be administered to any, even non-transparent, material for in-line monitoring of strains and stresses. In addition, no mechanical contact is required for dielectrostriction measurements. Therefore, there is no problem with interface and attachment of the sensing element to the monitored part. A potential of dielectrostriction phenomenon for NDE is not completely explored at this time and would be the subject of future extensive studies. We will show its feasibility for monitoring undesirable features such as fatigue, cracks and residual stresses in dielectric materials. In this paper, we will present theoretical background and experimental data for dielectrostriction study of polymeric parts manufactured under various processing conditions.

Structural Health Monitoring (SHM) technologies have the potential to realize economic benefits in a broad range of commercial and defense markets. Previous research conducted by Metis Design and MIT has demonstrated the ability of Lamb waves methods to provide reliable information regarding the presence, location and type of damage in composite specimens. The present NSF funded program was aimed to study manufacturing, packaging and interface concepts for critical SHM components. The intention is to be able to cheaply manufacture robust actuating/sensing devices, and isolate them from harsh operating environments including natural, mechanical, or electrical extremes. Currently the issues related to SHM system durability have remained undressed. During the course of this research several sets of test devices were fabricated and packaged to protect the piezoelectric component assemblies for robust operation. These assemblies were then tested in hot and wet conditions, as well as in electrically noisy environments. Future work will aim to package the other supporting components such as the battery and wireless chip, as well as integrating all of these components together for operation. SHM technology will enable the reduction or complete elimination of scheduled inspections, and will allow condition-based maintenance for increased reliability and reduced overall life-cycle costs.

MEMS ultrasonic transducers for flaw detection have heretofore been built as capacitive diaphragm-type devices. A diaphragm forms a moveable electrode, placed at a short gap from a stationary electrode, and diaphragm movement has been detected by capacitance change. Although several research teams have successfully demonstrated that technology, the detection of capacitance change is adversely affected by stray and parasitic capacitances, limiting the sensitivity of such transducers and typically requiring relatively large diaphragm areas. We describe the design and fabrication of what to our knowledge is the first CMOS-MEMS ultrasonic phased array transducer using piezoresistive strain sensing. Piezoresistors have been patterned within the diaphragms, and diaphragm movement creates bending strain which is detected by a bridge circuit, for which conductor losses will be less significant. The prospective advantage of such piezoresistive transducers is that sufficient sensitivity may be achieved with very small diaphragms. We compare transducer response under fluid-coupled ultrasonic excitation and report the experimental gauge factor for the piezoresistors. We also discuss the phased array performance of the transducer in sensing the direction of an incoming wave.

Acoustic emission testing is a passive nondestructive testing technique used to identify the onset and characteristics of damage through the detection and analysis of transient stress waves. Successful detection and implementation of acoustic emission requires good coupling, high transducer sensitivity and ability to discriminate noise from real signals. We report here detection of simulated acoustic emission signals using a MEMS chip fabricated in the multi-user polysilicon surface micromachining (MUMPs) process. The chip includes 18 different transducers with 10 different resonant frequencies in the range of 100 kHz to 1 MHz. It was excited by two different source simulation techniques; pencil lead break and impact loading. The former simulation was accomplished by breaking 0.5 mm lead on the ceramic package. Four transducer outputs were collected simultaneously using a multi-channel oscilloscope. The impact loading was repeated for five different diameter ball bearings. Traditional acoustic emission waveform analysis methods were applied to both data sets to illustrate the identification of different source mechanisms. In addition, a sliding window Fourier transform was performed to differentiate frequencies in time-frequency-amplitude domain. The arrival and energy contents of each resonant frequency were investigated in time-magnitude plots. The advantages of the simultaneous excitation of resonant transducers on one chip are discussed and compared with broadband acoustic emission transducers.

The concept of the Picostrain sensor technology is based on a standard, commercially available, electrical cable assembly embedded in pavement or structural members. The concept has been developed through the 1990s and patented by the Idaho Transportation Department (ITD) in 2003. The objective of this new technology is to build an inexpensive, easily installed and maintained sensor system for the purposes of vehicle classification (VC), vehicle identification (VI), weigh-in-motion (WIM), and vehicle tracking (VT) applications along with real-time monitoring and evaluation of structural performance under static and dynamic traffic loading. It is intended, in the future, that these sensors will be further developed to replace curently utilized expensive embedded pavement and structural sensors for ultimate improvement of transportation decision-making and planning. This will also help to document the movement of people and goods along with the evironmental, social, economic and financial parameters with an emphasis on tracking movements in social life for security based upon the use of this durable and reliable transducers. Approximately, 400 sensors have been installed on and in the reinforced concrete structural members of the West Park Center River Crossing Bridge (Bridge) and the Micron Engineering Center (MEC) building (Building) at Boise State University (BSU) in Boise, Idaho, USA, since 1998. These sensors were installed: in bridge pile caps, piers, girders and decks; bridge abutment embankments; building footings, columns, beams, floor slabs; and, have been linked to instrument cabinets on site. These sensors installed structures may now be called "smart" structures since they contain a resident sensing system capable of maintaining a constant watch over the integrity of the structure. These sensing systems will be able to evaluate the applied loads, as well as the static and dynamic response of the structure. This paper introduces and describes the new concept of Picostrain sensors and their installation, including the description of the proposed data acquisition system design and electronics for real-time monitoring of structural performance, WIM, VT, VC, VI, soil-structure interaction, and soil pressure and deformation due to moving traffic loads. The data and its interpretation will be made available to researchers and other interested organizations elsewhere upon completion of the data acquisition system (DAS) and collection and evaluation of the data.

Health monitoring of aircraft structures with optical fiber sensors requires that the fibers remain functional for the lifetime of these structures as repairs are generally very costly and time consuming. Thus, the feasibility of using optical fibers in various aircraft structures depends heavily on the durability of these fibers under adverse loading conditions. It is well known that silica optical fibers are vulnerable to applied mechanical and thermal loads that make flaws grow rapidly and eventually lead to fiber failure. In this paper, we investigate theoretically and experimentally the combined effect of the mechanical, thermal, and moisture loading on the aging process of fiber optic cables in an attempt to assess the expected lifetime of these cables in a naval aviation environment. It is also important to note that there is a pressing need for such an investigation, as all the studies available in the literature address the individual rather than the combined effects of these parameters on the lifetime of the cables.

This paper presents a technique for enhancing the temperature sensitivity of fiber sensors. The method is based on the peculiar shape and doping characteristics of a reduced cladding index fiber. A portion of the core of the fiber is removed and replaced with a material having a larger change in index with temperature than the core material it replaces. A perturbation of the sensing material results in a change in the polarization of the light at the output of the fiber. This change is detected as a change in intensity through the use of polarizers. A temperature sensitive device is presented as an example of this type of sensing device. Initial experimental results indicate that replacing the core with polymer enhances the temperature sensitivity by at least a factor of 4. The new technique is promising as a means for incorporating a variety of sensing materials into the path of a beam traveling in an optical fiber.

A distributed Brillouin scattering sensor with high special precision has been developed for the measurement of small damages/cracks of 1.5 cm. The out-layer damaged regions in an optical ground wire (OPGW) cable have been identified successfully by measuring the strain distributions every 5 cm using this technology. The stress increased to 127 kN which corresponds to more than 7500 micro-strain in the fibers. The locations of structural indentations comprising repaired and undamaged regions are found and distinguished using their corresponding strain data. The elongation of repaired region increases with time on 127 kN. These results are quantified in terms of the fiber orientation, stress, and behavior relative to undamaged sections.

The strain and temperature dependence of the Brillouin gain/loss spectrum has been studied in terms of Brillouin frequency, power and bandwidth for panda, bow-tie and tiger polarization maintaining (PM) fibers using our Brillouin gain/loss based distributed sensor system for the first time. The PM fibers are stressed at various temperature to measure the power, bandwidth and Brillouin frequency coefficients at the spatial resolution of 20 cm. Using our measured coefficients with various combinations Brillouin power and bandwidth and Brillouin frequency, we realized three groups of simultaneous temperature and strain sensing, for Brillouin frequency combined with bandwidth, strain/temperature resolutions are 39με/2°C (panda), 126με/3°C (bow-tie), 598με/16°C (tiger); for the Brillouin frequency combined with power, strain/temperature resolutions are 153με/8°C (panda), 237με/4°C (bow-tie); for the bandwidth combined with power, strain/temperature resolutions are 135με/38°C (panda), 195με/38°C (bow-tie).

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 examines a viable architecture for a wireless sensor network and shows the results of some tests carried out on a wireless fuzzy control system at the authors’ laboratory.

Guided wave ultrasound is a very powerful and reliable nondestructive testing technique. The emerging smart structure health monitoring strategies demand a wireless sensor for most applications. Passive sensor interfacing with wireless technology is advanced due mainly to the mW power requirements of such sensors. Guided wave sensors, on the other hand, are active sensors that require orders of magnitude more power than the typical passive sensor. Consequently, the design of the sensor, embedded electronics, and adjacent power source become more complicated. Sensor accessories can be minimized by locating zones on the phase dispersion curves where modes are efficiently generated. In this paper, this concept formulated via the source influence phenomenon. Experimentation focuses on quantifying the activation power requirements in different zone of the dispersion curves.

A self-powered wireless sensing module for the condition monitoring of mechanical systems and high energy manufacturing processes is described, with injection molding as a special application. The design and analysis of three constituent components in such a sensing module: an energy converter consisting of a piezoceramic stack, an energy regulator based on a pair of bipolar transistors, and a piezoelectric transmitter that transmits ultrasound signals proportional to the pressure within the injection mold, are presented in this paper. The energy extraction mechanism is investigated based on the interactions between the mechanical strain and the electric field developed within the piezoceramic stack. Analytical models for the energy modulator and signal transmitter are also established. Quantitative results are obtained that describe the energy flow among the three components and guide the parametric design of the three constituent components. Simulations and experimental studies have validated the functionality of each component. The models established can be used to subsequently optimize the design of the entire sensor module in terms of minimizing the energy requirement for the sensor and identifying the minimum level of signal intensity required to ensure successful detection of the signal by the signal receiver on the outside of the injection mold. The proposed self-powered sensing technique enables a new generation of sensors that can be employed for the condition monitoring and health diagnosis of a wide range of mechanical and civil systems that are characterized by high energy contents.

Civil engineering structures are large and their damage mechanism is complex requiring a large number of inexpensive, spatially distributed and wirelessly powered embedded sensing devices that support frequent and on-demand acquisition of real-time information about their state. Microelectromechanical Systems (MEMS) seem to have the necessary characteristics to meet these requirements. MEMS technology, such as, sensors, actuators and other engineered components can be embedded into concrete structures to provide sensing and interaction capabilities. By embedding active electronics with MEMS, the ability of the concrete structure to interpret its environment is improved. However, many challenges must be met in order to develop a mature MEMS technology for structural health monitoring (SHM). These challenges are primarily technical in nature and need to be addressed before this emerging technology can be implemented in different civil engineering structures. The objective of this paper is to study the feasibility of embedding MEMS devices into concrete material for conditioning and health monitoring of civil infrastructure. A research program was conducted to evaluate the durability and sensing capability of different embedded MEMS devices, and the findings are presented here.

This paper presents two case histories of the use of wireless sensor Mote technologies. These are devices that incorporate communications, processing, sensors, sensor fusion, and power source into a package currently about two cubic inches in size -- networked autonomous sensor nodes. The first case discussed is the November, 2001, instrumentation of a blast-induced liquefaction test in Tokachi Port, Japan. The second case discussed is the dense-pak instrumentation of the seismic shaking test of a full-scale wood-frame building on the UCB Richmond shake table. The utility of dense instumentation is shown, and how it allows location of damage globally unseen. A methodology of interpreting structural seismic respose by Bayesian updating and extended Kalman filtering is presented. It is shown that dense, inexpensive instrumentation is needed to identify structural damage and prognosticate future behavior. The case studies show that the current families of Motes are very useful, but the hardware still has difficulties in terms of reliability and consistancy. It is apparent that the TinyOS is a wonderful tool for computer science education but is not an industrual quality instrumentation system. These are, of course, growing pains of the first incarnations of the Berkeley Smart Dust ideal. We expect the dream of easy to use, inexpensive, smart, wireless, sensor networks to become a reality in the next couple of years.

A remotely-powered wireless temperature sensor to monitor a bearing health has been developed. The device employs a pair of miniaturized temperature sensitive capacitors in a simple inductor-capacitor (L-C) oscillator configuration. The bearing temperature is encoded in the frequency of the oscillator’s signal. The signal is wirelessly monitored by a receiver, which is connected to a PC for further analysis. Energy for the sensor circuit’s operation is supplied by a second electromagnetic radio signal, produced by an exciter coil. Thus, no wires or batteries are attached to the sensor circuit. The devices are fabricated on Dupont Kapton thick film substrates using surface mount components, and can be integrated onto bearing cages during fabrication. The circuits are designed to have small size, low power consumption, wide dynamic range and very low cost. After a brief introduction, this article describes the circuits employed. Calibration results are then presented.

For long-term bridge health monitoring, structural dynamic properties are usually obtained by system identification based only on the system output (bridge vibration responses), because the system input (traffic excitation) is difficult to measure. To facilitate such identification the excitation is commonly assumed as spatially uncorrelated white noise. However, when physically modeling it as a stationary stream of moving forces traversing the bridge, whose arrivals at the bridge are in accordance with a Poisson process, the traffic excitation is found to be spatially correlated. In this paper a procedure for formulating the traffic excitation model based on its physics is proposed, which involves first converting the moving forces into equivalent nodal excitation time-histories by the dynamic nodal loading approach, and then applying the Campbell’s theorem for the filtered Poisson processes. By this procedure, a non-diagonal frequency-variant excitation spectrum density matrix (SDM) is obtained. This does not conform to the conventional white noise excitation model. One of the output-only identification techniques based on the conventional excitation model, the frequency domain decomposition technique is implemented to demonstrate that direct application of the technique to traffic-induced vibrations can lead to misleading results. The proposed procedure for formulating the traffic excitation SDM provides a way to describe primary knowledge of the traffic excitation in frequency domain even for complicated bridges, which will potentially enable improvement in output-only identification techniques with unknown but spatially correlated excitation.

An important objective of health monitoring systems for civil infrastructures is to identify the state of the structure and to detect the damage when it occurs. System identification and damage detection based on measured vibration data have received considerable attention recently. Frequently, the damage of a structure may be reflected by a change of some system parameters, such as a degradation of the stiffness. In this paper, we propose an adaptive tracking technique, based on the extended Kalman filter approach, to identify the structural parameters and their changes. The proposed technique is capable of tracking the abrupt change of system parameters from which the event and severity of structural damages can be detected. Our adaptive filtering technique is based on the current measured data to determine the parametric variation so that the residual error of the estimated parameters is contributed only by noises. The proposed technique is applicable to linear and nonlinear structures. Simulation results for tracking the parametric changes of linear and nonlinear hysteretic structures are presented to demonstrate the application and effectiveness of the proposed technique in detecting the structural damages using vibration data from the health monitoring system.

The variation of modal properties caused by temperature effects is assessed to correct modal data used for damage detection in plate-girder bridges. First, experiments on model plate-girder bridges are described. Next, the relationship between temperature and natural frequencies is estimated and a set of empirical frequency-correction formula are analyzed for the test structure. Finally, a frequency-based method is used to locate and estimate severity of damage in the test structure using experimental modal data which are adjusted by the frequency-correction formula. Here, local damage in beam-type structures is detected by using measured frequencies and analytical mode shapes.

In this paper, we develop a damage identification method for beam structures based on the measurement of propagating waves excited by ambient loads. First, the ambient vibration data acquired by arrayed sensors are separated into the forward-going and the backward-going wave components utilizing the dispersion relation in the frequency domain. Then, the transfer function between an in-coming and out-going pair of the wave components is identified, whose inverse Fourier transform represents the out-going wave packet from a particular region of the structure in response to an impulsive incident. If there exists a crack at a certain location, additional echoes are observed in the identified impulse response, and the arrival time of the echoes would indicate the location of the crack. Experiments show that the proposed method is capable to detect the existence and the position of a crack only using a couple of sensors.

Among the various schemes being considered for Structural Health Monitoring (SHM), Lamb-wave testing has shown great promise. While Lamb-wave testing using hand-held transducers for Non Destructive Evaluation (NDE) is a well-established technology, Lamb-wave testing for SHM using surface-bonded/embedded piezos is a relatively new field. Little effort has been made towards a precise characterization of Lamb-wave excitation using piezos and often the various parameters involved are chosen without mathematical foundation. In this work, modeling of transient plane and circular-crested Lamb-wave generation and sensing using surface-bonded piezos in isotropic plates based on the 3-D linear elasticity equations is explored. Equations for the output voltage response of surface-bonded piezo-sensors in Lamb-wave fields are presented and optimization of the actuator/sensor geometry and materials is done based on those. Finally, numerical and experimental results to examine the validity of these models are discussed.

This paper presents a systematic investigation of the effect of sensor placement on the measurement data quality and subsequently, on the effectiveness of machine system health monitoring. First, signal propagation process from the defect location to the sensor was analyzed. Numerical simulations using finite element modeling was then conducted to determine the signal strength at several representative sensor locations. The analytical and numerical results showed that placing sensors closer to the component being monitored resulted in higher signal-to-noise ratio, thus improving the data quality. Using meso-sized piezoceramic chips, the obtained results were then experimentally evaluated. Comparisons with a set of commercial vibration sensors verified the developed sensor placement strategy. The presented study quantitatively justified why placing sensors closer to the machine being monitored is of critical importance to ensuring high quality data, and confirmed that the customized shock wave sensing approach can achieve comparable result for vibration measurement, but with a much less space requirement.

Since damage usually reduces stiffness, frequency responses of a structure can be used to detect damage where the variation/decrease in natural frequencies is used as indicator. Although frequency responses are easy to measure with a small number of sensors, they are global reflections of the system dynamic property and one single FRF oftentimes lacks the sensitivity for local damage detection. In addition, locating damage is difficult as it normally requires a large number of measured natural frequency shifts. In this paper we propose a new frequency response based approach by integrating piezoelectric transducer with variable inductance to the host mechanical structure. A piezoelectric shunt circuit could significantly change the system dynamic responses. While frequency responses can be easily measured for such system (for example, by applying voltage to the piezoelectric actuators), varying the inductance can lead to a family of frequency responses. By doing so, one can get much more complete “scanned” reflection of the possible damage within the mechanical structure. The family of frequency responses provides a much larger dataset for more accurate and reliable damage detection. In this paper, an inverse sensitivity based detection algorithm is formulated and the performance improvement due to the integration of variable inductive piezoelectric shunt is demonstrated.

The study proposes an improved Gabor order tracking (GOT) technique to cope with crossing orders that cannot be effectively separated using the original GOT scheme. The improvement aids both the reconstruction and interpretation of two crossing orders such as a transmission-element-regarding order component and a structural resonant component. In the paper, the influence of the dual function to Gabor expansion coefficients is investigated, which can affect the precision of the tracked order component. Additionally, using the GOT scheme in noise conditions is demonstrated as well. For applying the improved GOT in real tasks, separation and extraction of close-order components of vibration signals measured from a transmission-element test bench is illustrated using both the GOT and Vold-Kalman filtering (VKF) OT schemes. Finally, comprehensive comparisons between the improved GOT and VKF_OT schemes are made from processing results.

Rails maintenance is becoming a critical issue because of the increase of the traffic and the train speed, which amplify the risk of catastrophic failures. A methodology, based on wave propagation theory, aimed at detecting damage in rails is presented in this paper. The damage detection algorithm is based on the assumption that the rails behave as a wave guides and stress waves may travel alongside the rail length without being reflected unless they meet discontinuities (damages). The Wave Propagation Based Damage Detection (WPBDD) algorithm proposed is a two steps technique. In the first step the travel time of a perturbation wave, generated by a train passage, from its arrival to the sensor locations to the discontinuity and back to the sensor, is measured by a Time Correlation Function (TCF) evaluated using the wavelet transform. The second algorithm locates the damage sites using a Ray-Tracing (RT) algorithm. The WPDDD algorithm has been designed to use indifferently either body waves (P and S waves) or surface waves (Rayleigh waves). The technique proposed aimed at the identification of single and multi-site rolling contact fatigue damages was tested on a numerical test case.

Embedded ultrasonic structural radar (EUSR) algorithm is developed for using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. Signal processing techniques are used to extract the time of flight of the wave packages, and thereby to determine the location of the defects with the EUSR algorithm. In our research, the transient tone-burst wave propagation signals are generated and collected by the embedded PWAS. Then, with signal processing, the frequency contents of the signals and the time of flight of individual frequencies are determined. This paper starts with an introduction of embedded ultrasonic structural radar algorithm. Then we will describe the signal processing methods used to extract the time of flight of the wave packages. The signal processing methods being used include the wavelet denoising, the cross correlation, and Hilbert transform. Though hardware device can provide averaging function to eliminate the noise coming from the signal collection process, wavelet denoising is included to ensure better signal quality for the application in real severe environment. For better recognition of time of flight, cross correlation method is used. Hilbert transform is applied to the signals after cross correlation in order to extract the envelope of the signals. Signal processing and EUSR are both implemented by developing a graphical user-friendly interface program in LabView. We conclude with a description of our vision for applying EUSR signal analysis to structural health monitoring and embedded nondestructive evaluation. To this end, we envisage an automatic damage detection application utilizing embedded PWAS, EUSR, and advanced signal processing.

In this study, a technique that integrates the wavelet transform with a covariance-driven modal analysis scheme, is proposed to address the output-only modal analysis problem. Under the assumption that the ambient excitation can be modeled as a white-noise process, the output covariance is computed firstly to separate the effect of random excitation from the response measurement. The wavelet transform is then employed to convert the covariance vector in the time domain to the power scalogram in the time-scale plane. The wavelet coefficients along the energy concentrated curve are extracted and the structural modal parameters including the resonant frequency, modal damping and mode shape vector can then be estimated based on the amplitude and the phase of the extracted wavelet coefficients. As the wavelet transform has a capacity to capture both stationary and transient information from the original measurement, the proposed technique provides a promising approach for identifying modal properties of both linear and nonlinear structures. Both numerical and experimental studies are performed to demonstrate the proposed technique and verify its accuracy. The results show the proposed method works very well in identifying modal parameters of structures with multiple degrees of freedom.

This paper presents a new approach to on-line health diagnosis of mechanical systems, based on the wavelet packet transform. Specifically, signals acquired from vibration sensors are decomposed into sub-bands by means of the discrete harmonic wavelet packet transform (DHWPT). Based on the Fisher linear discriminant criterion, features in the selected sub-bands are then used as inputs to three classifiers (Nearest Neighbor rule-based and two Neural Network-based), for system health condition assessment. Experimental results have confirmed that, comparing to the conventional approach where statistical parameters from raw signals are used, the presented approach enabled higher signal-to-noise ratio for more effective and intelligent use of the sensory information, thus leading to more accurate system health diagnosis.

Multi-wire steel strands are used in civil structures as pre-stressing tendons in prestressed concrete and as stay-cables in cable-stayed and suspension bridges. Monitoring the structural performance of these components is important to ensure the proper functioning and safety of the entire structure. Among the various NDE techniques that are under investigation for monitoring tendons and cables, the use of ultrasonic guided waves shows good promises. The main advantage of this approach is the possibility for the simultaneous monitoring of loads and detection of defects, such as corrosion and broken wires, by using the same ultrasonic setup. Load monitoring is achieved by measuring the travel time of the wave across a given length of the cable. Defect detection is achieved by measuring the reflections of the wave from the geometrical discontinuities. The new contributions of the current paper are two-fold. First, the study identifies those ultrasonic frequencies propagating with low attenuation for long-range defect detection. Second, the technique is substantially improved by implementing the Discrete Wavelet Transform (DWT) as a data post-processing tool. The data de-noising and data compression abilities of the DWT allow for greater sensitivity, larger ranges and higher monitoring speed. It is shown that the implementation of the DWT in the ultrasonic guided-wave technique becomes necessary for monitoring tendons and cables in the field.

In this paper, an approach based on "energy-damage" theory for structural damage diagnosis is presented by use of wavelet packet analysis and improved BP neural network. The damage characteristics of the time domain response signals are more obvious after being transformed by the wavelet. Using the node energy in different frequency bands as the sample of tbe ANN can quite well reflect the damage features. As a numerical example, the benchmark structure given by the ASCE is used for describing the process of the damage detection presented here.

Fuzzy logic control (FLC) and genetic algorithms (GA) are integrated into a new approach for the semi-active control of structures installed with MR dampers against severe dynamic loadings such as earthquakes. The interactive relationship between the structural response and the input voltage of MR dampers is established by using a fuzzy controller rather than the traditional way by introducing an ideal active control force. GA is employed as an adaptive method for optimization of parameters and for selection of fuzzy rules of the fuzzy control system, respectively. The maximum structural displacement is selected and used as the objective function to be minimized. The objective function is then converted to a fitness function to form the basis of genetic operations, i.e. selection, crossover, and mutation. The proposed integrated architecture is expected to generate an effective and reliable fuzzy control system by GA’s powerful searching and self-learning adaptive capability.

In the previous study, authors developed a probabilistic algorithm for active control of structures. In the probabilistic control algorithm, the control force is determined by the probability that the structural energy exceeds a specified target critical energy, and the direction of a control force is determined by Lyapunov controller design method. In this paper, an experimental verification of the proposed probabilistic control algorithm is presented. A three-story test structure equipped with an active mass driver (AMD) was used. The effectiveness of the control algorithm was examined exciting the test structure using a sinusoidal signal, a scaled E-Centro earthquake and a broadband Gaussian white noise. Specially, experiments on control had been performed under a different condition to that of system identification in order to prove the stability and robustness of the proposed control algorithm. Experimental results indicate that the probabilistic control algorithm can achieve a significant response reduction under various types of ground excitations even when the modeling error exists.

A semi-active Tri-D algorithm combining Coulomb, Reid and viscous damping mechanisms has recently been developed by the authors to drive piezoelectric friction dampers. The objective of this study is to analytically compare its performance with those of bang-bang control, clipped-optimal control, modulated homogeneous control, and a modified clipped-optimal control. Two far-field and two near-field historical earthquake records with various intensities and dominant frequencies were used in this study. All algorithms were evaluated with a ¼ scale 3-story frame structure in terms of reductions in peak inter-story drift ratio and peak floor acceleration. A piezoelectric friction damper was considered to be installed between a bracing support and the first floor of the frame structure. Both advantages and disadvantages of each control algorithm were discussed with numerical simulations. At near resonance, both bang-bang and clipped-optimal algorithms are more effective in drift reduction, and the modified clipped-optimal algorithm is more effective in acceleration reduction than both Tri-D and modulated homogeneous algorithms. But the latter requires less control force on the average. For a non-resonant case, the Tri-D and modulated homogeneous algorithms are more effective in acceleration reduction than others even with less control force required. Overall, the Tri-D and modulated homogeneous controls are effective in response reduction, adaptive, and robust to earthquake characteristics.

This paper summarizes the ongoing work at the University of Texas to develop a class of passive, wireless sensors to detect corrosion in reinforced concrete structures. Two prototype sensors have been developed that are designed to be attached to the reinforcing cage before the concrete is placed. The basic and improved sensors are inexpensive to fabricate, sufficiently durable to survive the construction process, can be interrogated through concrete, and provide reliable information about the initiation of corrosion in the adjacent reinforcement. Because the sensors do not contain an internal battery, the expected life of the sensors is expected to be essentially the same as the design life of the structure in which they are embedded.

Smart Health Monitoring System (SHMS) is a set of integrated system of hardware and software designed to automatically collect and analyze the data from a faraway bridge. The real-time data can be preprocessed in the sub-workstation on the bridge then transferred to the main server with a wired or wireless internet access. SHMS is based on the statistical analysis of the static and dynamic characteristics of structures. In order to automate the procedure of processing and analyzing all the raw data, a rule-based expert system was developed for the monitoring system with Bootstrap Method. In general, the estimation of parameters from measurement always contains systematic perturbations and random fluctuations. The systematic perturbations mainly come from periodic environmental factors, especially temperature. Random fluctuations result from irregular disturbance including instrumentation sources and numerical processing algorithms. The former can be identified and characterized. Based on the historical data, a set of correction models have been built to remove the influence from systematic perturbations. Random fluctuations are difficult to be characterized by traditional statistical methods. But with Bootstrap Method, we can minimize the random error.

The authors have been continuously conducting a series of research works on the development of the fiber reinforced composites as self-diagnosis materials. The function to detect damage is based on the property of carbon materials as a conductor of electricity. The conductive fiber reinforced composite, which is the glass fiber reinforced plastics added carbon particles for electrical conductivity, has been confirmed to possess excellent sensitivity as a self-diagnosis materials. In this study, a self-diagnosis material with the ability to memorize damage history has been applied. Irreversible resistance changes dependent on the strain histories of the composites were utilized to achieve this ability. The authors have also developed an electrically conductive film sensor bonded on the concrete surface to detect cracks and measure crack width. The specimens of the reinforced concrete bridge pier columns were tested under quasi-static cyclic lateral loading. The performance of the proposed self-diagnosis materials to detect damage to concrete structures is evaluated through confirmation of the relationship between the extent of damage and the variation of electrical conductivity of self-diagnosis materials. On the basis of the obtained experimental results, the applicability of self-diagnosis materials to structural health monitoring for concrete structures are discussed in detail, and the practical monitoring techniques for structures are proposed.

The Kishwaukee bridge (circa 1979) is a five-span pre-cast post-tensioned segmental concrete box girder bridge. The structure has been under increasingly stringent inspection since extensive cracking adjacent to the piers in the webs was observed. There is limited observational evidence that continued propagation of the cracks has been occurring, and static load testing of the structure in 2000 provided direct indications of locally excessive stresses in the shear reinforcement. Since that time, the authors have developed instrumentation which continuously monitors the bridge. Our previous thermal analyses and modeling based upon the data collected demonstrates that thermal equilibrium is rare for this structure, a situation that undoubtably applies to most bridges of this type. Partly due to this constant disequilibrium, basing alarm criteria on real time measurements is untenable. In this paper we develop a two-step monitoring strategy which can be applied to both global and local deformation data. The strategy is based on preliminary modeling to identify the thermomechanical influences, followed by a second step using a bootstrap comparator.

For the identification of linear time-varying system, this study aims at a critical comparison and assessment of several recursive SISO (single-input single-output) parametric time-domain methods for the identification of seismic response of building structure. The methods are: • RLS method with constant trace, • RLS with variable forgetting, • Changing Spectrum Method, • RLS with selective forgetting, • wavelet analysis. For nonlinear system identification, this study aims at a critical assessment of the estimation of nonlinear restoring force. This study used the simulation seismic response data of a time-varying SDOF system and the full-scale pseudo-dynamic test data of a frame structure to discuss the characteristics of each method. Concise summaries of the methods, highlighting their principles and realizations, are provided.

An important way of increasing the payload in a reusable launch vehicle (RLV) is to replace heavy metallic materials by lightweight composite laminates. Engineers and scientists have studied many metallic materials thoroughly, due to the long history of practical usage in many aerospace and aeronautical structures. Compared to metallic materials, composite laminates are a relatively new material and therefore require more attention to ensure the safety and reliability. Among various parts and systems of the RLV, this study focuses on tanks containing cryogenic fuel. Historically, aluminum alloys have been used as the materials to construct fuel tanks for launch vehicles. To replace aluminum alloys with composite laminates or honeycomb materials, engineers have to make sure that the composites are free of defects before, during, and after launch. In addition to robust design and manufacturing procedures, the performance of the composite structures needs to be evaluated constantly. In recent years, the impedance-based health monitoring technique has shown its promise in many applications. This technique makes use of the special properties of smart piezoelectric materials to identify the change of material properties due to the nucleation and progression of damage. A major advantage of this technique is that the procedure is nondestructive in nature and does not perturb the properties and performance of the materials and structures. This paper reports the results of applying the impedance-based nondestructive testing technique to the damage identification of composite laminates at cryogenic temperature. These materials have potential application for fuel tanks in future RLV’s.

Correct sensing provides the availability of information for health monitoring interests, including those associated with unit health, stress, diagnostics and prognostics. Data is presented from measurement projects employing a 'highly linear,' wideband (0 to hundreds of kilohertz), large dynamic range (over 180 dB demonstrated in both displacement and acceleration), non-contact, vibration and Acoustic Emissions (AE) measurement capability. The measurement capability is currently embodied in an Epoch Engineering, Inc. Research and Development (R&D) Robust Laser Interferometer (RLI). Existing data from previous measurement projects is assessed in terms of its potential to provide meaningful information for health monitoring needs in situations involving civil, mechanical and aerospace infrastructure elements. In addition to performance considerations, implementation alternatives, integration benefits, cost considerations and remaining work that would need to be accomplished for commercializing the RLI capability is presented.

Measurement of the moisture and corrosion rate within occluded regions is difficult because of their inherent restricted access. The objective of this work was to simultaneously measure in situ the ingress and egress of water and the corrosion activity within simulated aircraft lap joints. Fiber optic moisture sensors monitored the presence of the aggressive aqueous environment within pristine and corroded joints whereas the relative corrosion rate inside the joint was monitored using a SQUID magnetometer, which measures the magnetic fields associated with the small electrical currents produced from the corrosion reactions. Water ingress was very rapid (~ 1 mm/min) whereas egress was much slower (< 0.01 mm/min) and spatially non-uniform. Corroded joints dried slower than pristine joints due to the finely porous, hydroscopic nature of the corrosion products. Corrosion activity correlated with moisture in a complex manner. Wetting caused a substantial increase in corrosion activity within the joint in comparison to the dry baseline condition. During drying, a transient increase prior to cessation in corrosion activity occurred due to concentration and increase in aggressiveness of the solution within the joint. This work highlights the efficacy of simultaneously monitoring moisture and the corrosion activity within occluded regions by employing small profile fiber optic sensors and SQUID technique.

Many researchers have made efforts to develop structural health monitoring methods to detect damages, cracks, corrosion and bolt loosening using modal characteristics of structures. However, modal characteristics are affected by not only damages but also boundary conditions and loading conditions etc. In fact, local damages induce very slight change of modal parameter. Therefore, it will be difficult to apply most of these conventional methods to actual structures. In this paper, we propose a new structural health monitoring method to detect bolt loosening using the characteristics of local vibration modes of a thin plate sensor sandwiched between a bolt, a nut and washers in main structures. This sensor consists of a thin plate and some piezoelectric elements. In local mode vibration of the thin plate sensor, the bolt’s axial tension determines its boundary condition. Bolt loosening changes the boundary condition and natural frequencies of the sensor. However, main structure’s characteristics don’t affect sensor’s modal characteristics. Since our method attempts using local vibration modes it is important to distinguish the local vibration modes of interest from the global ones related to structures. We propose a technique to distinguish local modes using finite element method. Finally, we confirm the validity of the thin plate sensor experimentally.

One of the most common modes of premature failure of asphalt pavements is water damage. Moisture damage in hot-mix asphalt (HMA) pavements occurs when water infiltrates the pavement system, causing premature failure of hot-mix asphalt pavements, primarily through loss of adhesion between the asphalt binder and the aggregates. Loss of adhesion can lead to stripping of the asphalt film from the aggregate and raveling, where aggregates are dislodged from the pavement. The laboratory testing procedures currently available for testing HMA moisture susceptibility were primarily developed to determine the degree of resistance to moisture damage by a particular combination of asphalt and aggregate as well as compare mixes composed of different types and quantities of aggregate. These methods are all based on destructive testing. There is currently a need for innovative nondestructive testing technologies that can be used to identify and isolate the effects of water damage in mixtures. As a first step in the development of a non-destructive method to test HMA pavements, modal hammer tests were conducted on several test specimens of fine and coarse grained granite-based mixes commonly used by the Florida Department of Transportation (FDOT). The results of the testing indicate that there is a large frequency shift in the transfer function measurements for the damaged samples compared to the undamaged samples. The results imply that modal hammer testing may be used as a method to characterize the health of HMA pavements.

As new technologies are increasingly applied to civil infrastructure, the need for structural monitoring systems becomes more critical. Serviceability, or deflection, is very important in monitoring the health of not only a structural system, but also in analyzing the affects of a new technology applied in the field. Traditionally, Linear Variable Displacement Transducers (LVDT’s) are used to measure deflection in many filed load tests. In the field, access can easily become an issue with this instrumentation system that is truly designed for laboratory use. LVDT instrumentation for load testing typically requires several labor intensive hours to prepare for a load test in the field; the system is accompanied by wiring and expensive electronics that may not only become a safety issue but is also very sensitive to the elements. Set up is especially difficult, if not impossible, on tall bridge spans and bridge spans over water. A recent research project required serviceability monitoring through a series of load tests for several retrofitted bridges in Missouri. For these tests, surveying equipment was employed in attempt to make serviceability measurement more practicable. Until recently, surveying equipment would not have produced the accuracy required for structural monitoring use; however, manufacturers of this equipment have developed new technologies to increase the accuracy of the instrumentation. The major component used, the total station, can measure deflection accurate to 0.2 millimeters (0.0079 in.). This monitoring system is much easier to set up and use, reducing labor and time requirements. The system has almost no site restrictions. This paper will compare and contrast the total station to traditional load testing monitoring equipment (LVDT).

We carry out shaking table test using a three-story large-scale steel structure with cementitious devices to detect and estimate damages. The test frame floor height is 1.8m, total height is 5.4m, floor plan is 4mx3m. Shaking table test is carried out at large-scale earthquake simulator facility of the National Research Institute for Earth Science and Disaster Prevention. Cementitious devices are installed in the center frame of tested structure and devices are actually damaged during the shaking. Two types of identification are tried. One is identification using the data under excitation and the other is identification using the data of before and after of the excitation. In both cases, we use identification method by ARX model. From identified results, natural frequency decreases, damping ratio increases and story stiffness decreases as experienced amplitude increases or input amplitude increases. A model using stick-slip elements is proposed. Natural frequency, damping ratio and story stiffness described by this model are consistent with experimental results. The fitting of the experimental result based on this model is carried out, and skeleton curve got from structural design and fitting result are corresponded well. Damage evaluation method using this fitting results and skeleton curve is proposed.

The objective of this study is to investigate the feasibility of an impedance-based damage detection technique using piezoelectric (PZT) transducers for civil infrastructures such as steel bridges. The basic concept of the technique is to monitor the changes in the electrical impedance to detect structural damages. Those changes in the electrical impedance are due to the electro-mechanical coupling property of piezoelectric materials. The smart PZT transducers which act as both actuators and sensors in a self-analyzing manner are emerging to be effective in non-parametric health monitoring of structural systems. This health monitoring technique can be easily adapted to existing structures, since only a small number of PZT patches are needed for continuous monitoring of their structural integrity. This impedance-based method operates at high frequencies (above 100 kHz), which enables it to detect incipient-type damage. It is not interfered by normal operating conditions, vibrations of the host structure, and changes in the host external body. The results of the experimental study on three kinds of structural members indicate that cracks or loosened bolts/nuts near the PZT sensors may be effectively detected by monitoring the shifts of the resonant frequencies of the impedance functions.

It is shown that water distribution systems can be damaged by earthquakes, and the seismic damages cannot easily be located, especially immediately after the events. Earthquake experiences show that accurate and quick location of seismic damage is critical to emergency response of water distribution systems. This paper develops a methodology to locate seismic damage -- multiple breaks in a water distribution system by monitoring water pressure online at limited positions 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 seismic damage 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 an effective and practical way in which seismic damage in a water distribution system can be accurately and quickly located.

The supervisory control and data acquisition (SCADA) technology has been used in water distribution systems in recently years, in which, waterhead at some nodes and/or flowrate in some links in the water distribution systems are monitored by radio or internet, and the waterhead and flowrate monitoring stations are usually determined by experience or simply evenly distributed. For the purpose of more efficient monitoring, optimal monitoring of waterhead in a water distribution system was developed by the authors, and as the second part of the study, this paper has proposed a method for optimal monitoring of flowrate in a water distribution system. A perturbation analysis is conducted to determine the sensitivity matrix, and the sensitivity equation is solved by a least square method, and the optimal monitoring of flowrate is then decided. The optimal monitoring solution is compared with the evenly distributed case, and it is found the optimal monitoring provides a more efficient and practical scheme if the number of monitoring stations is specified.

Dafosi Yangtze River Bridge, completed in August 2001, 1,176 meters long, with the longest main span of 450 meters in Asia in its design period, is one of the key projects of Yu-Qian Expressway and Out-Circle Ring and Round City Highway in Chongqing City. So it is significative to monitor the health of Dafosi Yangtze River Bridge after its completion. A remote health monitoring system is designed for Dafosi Yangtze River Bridge and implemented in the end of 2002. This system includes three subsystems, namely, sensing subsystem, local monitoring subsystem and remote monitoring subsystem. The sensing subsystem can gain the state information of the bridge via sensors, which installed in the key parts of the bridge, such as the fiber-optic strain sensors, the opto-electronic deflection sensors and the temperature sensors. Local sub-system can control all the sensors to collect health information periodically, store and transmit the health data to the remote subsystem via fiber cable. The remote subsystem can analyze and evaluate the health state of this bridge. In this paper, the whole system is introduced, and some monitoring results are presented.

Fiber-optic based sensors and sensor networks are being increasingly used for a variety of sensing applications in composite structures. In this paper, we propose a multifunctional fiber optic network configuration where the fiber-optic network can serve a dual role -- as a communications network and as a health monitoring system. This can be made possible through wavelength division multiplexing, which allows multiplexing of multiple wavelengths into a single fiber. For example, multi-axis fiber Bragg gratings operating at 1550 nm can be used to sense strain, temperature, humidity etc, while allowing use of 1310 nm wavelength for communications. The goal is to develop a smart network that can interrogate the state of the structure on demand using fiber-optic gratings and also use the same fiber-optic network for communication as a data bus integrated in the structure. Such architectures are desirable for applications such as next generation lightweight systems for military as well as commercial composites industry, where real-time monitoring and cross functionality are required of structural materials. A composite laminate was fabricated with an embedded fiber Bragg grating and subjected to a 3-point bending test, while being connected to a computer network. Network traffic in the composite and strain under 3-point bending were monitored simultaneously. Results show no network performance deterioration up to composite failure, thus allowing the same fiber to serve both as a data bus and a sensor system.

We report on the use of a high-speed wavelength division multiplexing (WDM) technique for multiplexing Fiber Bragg Grating (FBG) sensors applied to structural Vibration Control for the measurement of strain, permitting many sensing devices along a single optical fiber at different locations collecting samples at 5000 Hz with microstrain resolution. In this demonstration, a cantilevered flexible aluminum beam is used as the object for vibration control. A piezoceramic patch surface-bonded to the cantilevered end of the beam is used as an actuator to suppress the beam vibration. Various active vibration controllers such as positive position feedback (PPF), strain rate feedback (SRF), proportional plus derivative (PD), pole placement, and sliding mode based robust control are tested by using the fiber optical sensor for feedback purpose. Experiments successfully demonstrate that the signals from the fiber optic sensor can be used for active feedback control of the beam vibration.

With recent advances in digital circuitry, wireless communications, and Micro-Electro-Mechanical Systems (MEMS) technology have led to the emergence of Wireless Sensor Networks (WSNs) as a novel class of networked embedded systems. Many projects and diverse applications for these systems are currently being explored. The determination of location and extent of structural damage known as Structural Health Monitoring (SHM) is significant importance to civil infrastructures such as bridges, dams, offshore platform large buildings. For applying WSN to real-world civil infrastructures monitoring, sensor network architecture is proposed in this paper. The system development includes hardware and software design of the wireless sensor nodes, the design of the sensor network, and the capabilities for remote data access and management. With the ready availability of MEMS sensors, RISC micro-controller and RF unit, a wireless sensor node is designed and fabricated. The data being sensed by the sensor nodes in the network is eventually transmitted to a base station, where the information can be accessed. Via the Internet, multiple users with a proper access authorization to the URL site may simultaneously acquire, display data and monitor real-time performance of the structures remotely using a Web browser. In order to support hardware and SHM algorithm development, primitive software architecture is developed using commercially software systems. To demonstrate the feasibility and validity of the proposed WSN, the performance test is done in the laboratory.

A new smart semi-active device, called magneto-rheological -- tuned liquid column damper (MR-TLCD) has recently been devised by the authors for wind-induced vibration control of tall building structures. The damping performance of this device can be continuously changed and is controllable by altering magnetic filed applied on the MR fluid at the bottom of a U-tube container. Numerical simulations have been conducted to demonstrate its effectiveness in both open-loop and closed-loop control modes, and MR-TLCD prototypes using different solvents in magneto-rheological fluid (MRF) have been manufactured in laboratory. This paper presents an experimental study of an MR-TLCD using one kind of synthetic hydrocarbon -- poly-alpha-olefin (PAO) as solvent of MRF. The prototype is fabricated using a U-tube container with PAO-based MRF, of which the viscosity can be altered in milliseconds by exerting voltage to the electro-magnetic coils at the bottom of the tube. It was tested on a hanging shaking table by positioning it on the top of a structural model which was subjected to ground excitation. Open-loop control tests were carried out with a spectrum of voltage inputs to the MR-TLCD under sweeping sine excitation. The tests show that the smart MR-TLCD can effectively mitigate structural vibration response and a maximum response reduction can be achieved when an optimal voltage input to the damper is exerted, validating the findings of theoretical and simulation studies.

This paper presents theoretical and in-situ experimental studies on semi-active vibration control of bridge cables using magneto-rheological (MR) dampers. The feedback control is accomplished using only one MR damper and one accelerometer collocated near the lower end of the cable. A new control strategy, state-derivative feedback control, is formulated within the framework of reciprocal state space (RSS). This state-derivative feedback control strategy is novel in the sense that it directly uses acceleration information for feedback and state estimation, which is usually the only measurand available in practical cable vibration control implementation. More importantly, the control force commanded by this strategy with an appropriate energy weighting tends to be dissipative and therefore implementable by semi-active MR dampers without clipping. Numerical simulations of state-derivative feedback control for a 115m long stay cable in the cable-stayed Dongting Lake Bridge are conducted under different excitation conditions, and then experimental validation of the prototype cable is carried out in the bridge site with the help of the real-time control system dSPACE. Good agreement is observed between the simulation and experimental results.

Hybrid control platform is investigated in this paper for mitigating microvibration of a batch of high tech equipment installed in a high tech facility (building) subject to nearby road vehicle-induced horizontal and vertical ground motions. Hybrid control platform, on which high tech equipment is installed, is mounted on the building floor through a series of passive mounts and controlled by hydraulic actuators in both horizontal and vertical directions. The hybrid control platform is taken as an elastic body with significant bending modes of vibration, and a sub-optimal control algorithm is used to manipulate the hydraulic actuators with the actuator dynamics included. The governing equations of motion of the coupled platform-building system are established in the absolute coordinate to facilitate the feedback control and performance evaluation of the platform. The horizontal and vertical ground motions at the base of the building induced by nearby moving road vehicles are assumed to be random and statistically stationary processes. A typical three-story high tech building is selected as a case study. The case study shows that the ground motion and vibration of the high tech building are higher in the vertical direction than in the horizontal direction. The use of hybrid control platform can effectively reduce both horizontal and vertical microvibrations of a vast quantity of high tech equipment to the level satisfying the most stringent microscale velocity requirement specified in the BBN criteria.

Mitigating seismic responses of adjacent buildings by using control devices linked the two buildings has been recognized as a feasible alternative control scheme in past decade. A numbers of research studies have been undertaken in revealing and comparing the control capability among passive, active and semi-active control strategies employed in the coupled building system. The general interest and intention for the coupling control approach are mainly placed on the adjacent high-rise structures, and the LQ control algorithm relying on feedback with multiple measurement points is also the major design preference. This paper will focus on evaluating the effectiveness of controllable friction dampers as coupling devices that are implemented with semi-active control strategy based on local response feedback for a coupled podium structure and medium-rise building system. The effect of the height, mass and stiffness of two semi-actively controlled structures is one of the investigations. A comparison on control performance by a proposed semi-active control strategy with passive and clipped optimal control strategy is also presented. It is shown that control strategy with local response feedback can provide increased control performance over the passive strategy, and it is also of similar efficiency compared to the clipped optimal control strategy.

Many approaches on modeling of cracks in structural members have been reported in the literatures. However, most of them are explicitly developed for the purpose of studying the changes in static and dynamic responses of the structure due to the crack damage, which is a forward problem mathematically. Thereby the use of these models is inconvenient or even impossible for detecting damage in structures from vibration measurements, which is usually an inverse problem. An anisotropic damage model is proposed in this paper for detecting edge-parallel cracks in a rectangular thin plate. The cracked plate element is represented by an equivalent plate element with orthotropic anisotropic material expressed in terms of the virgin material stiffness and a tensor of damage variables. A non-model-based damage identification approach is developed incorporating the proposed anisotropic model and the estimated uniform load surface curvature (ULSC) of the plate from vibration measurements. The actual length of the crack is then predicted from the identified variables based on conservation law of potential energy for crack growth. The validity of the methodology is demonstrated by numerical examples and experiment results with comparison with results from existing crack identification theory.

The purpose of this study is to search for an efficient flexibility-based method for locating damage in plate structures. Although a large number of methods exist for detecting damage in a structure using measured modal parameters, many of them require a correlated finite element model. In this paper several damage localization methods based on changes in the modal flexibility, Uniform Load Surface (ULS), and their curvatures will be discussed. These methods require frequencies and mode shapes from the lower modes of the plate before and after damage, or only the eigen-pairs from the damaged state if the gapped-smoothing technique is applied. The method based on flexibility changes or flexibility curvature was originally proposed to localize damage in one-dimensional beam-like structures. In this paper this technique is generalized to two-dimensional plate structures using Chebyshev polynomial approximation, and incorporated with ULS, the derivative of modal flexibility, and its curvature for detecting damage in plates. Numerical examples considering measurement noise, mode truncation, and sensor sparsity are studied to evaluate and compare the effectiveness of the proposed methods. It is found that the ULS curvature is the most sensitive index for locating damage, especially for truncated and noisy measurements.

Electromechanical (E/M) impedance method is emerging as an effective 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 piezoelectric wafer active sensors (PWAS) attached to the monitored structure. Laboratory-type impedance analyzers (e.g. HP4194) are bulky, heavy, and expensive. They cannot be easily carried into the field for on-site structural health monitoring. To address this issue, means of to reduce the size of the impedance analyzer making the impedance analyzer more compact and field-portable are explored. In this paper, we present a systematic approach to the development of a field-portable small-size impedance analyzer for structural health monitoring using the electromechanical impedance technique. Our approach consists of several developmental stages. First, we perform a simulation of the E/M Impedance technique and develop the software tools for analyzing the signal in a fast and efficient way while maintaining the desired accuracy. The objective of this signal processing part is to obtain the complex impedance, Z_R+iZ_I)=|Z| angle arg Z, at a number of frequencies in a predetermined range. Several signal processing methods were explored such as: (a) integration method; (b) correlation method; (c) Discrete Fourier transform (DFT) method. Second, we discuss the hardware issues associated with the implementation of this approach. The hardware system architecture consists of several blocks: (a) reference signal generation; (b) voltage and current measurements; and (c) digital signal acquisition and processing. Practical results obtained during proof-of-concept experiments are presented and comparatively examined.

Our society depends heavily on a network of buildings, bridges and roadways. In order to properly maintain this civil infrastructure and avoid damage and costly repairs due to structural failure, it is necessary to monitor the health of these structures. Sensors must frequently be placed in inaccessible locations under harsh conditions and should ideally last the lifetime of the structure the sensors are monitoring. This paper presents the development of a low cost, passive, un-powered wireless analog resistance sensor. The sensor was originally designed for monitoring corrosion in concrete, but there are many other potential applications including remote temperature monitoring, embedded accelerometers, and embedded strain gauges. The passive wireless nature makes the sensor ideally suited for embedding in inaccessible locations under harsh conditions. The sensor consists of a resonant inductor-capacitor circuit containing a resistive transducer. The sensor is interrogated by measuring the impedance through a remote, magnetically coupled reader loop. The width of the resonance is directly related to the resistance of the transducer. The sensor has been simulated under a variety of conditions using a circuit model and compared to actual test sensors built and evaluated in the laboratory.

Configuration-based coaxial cable sensors have recently been developed to detect cracks in reinforced concrete (RC) structures. These sensors have shown a high sensitivity when applied to several short RC flexural members. However, the signal losses resulting from a long cable sensor may distort the initial waveform of the electromagnetic wave propagating along the cable, thereby compromising the spatial resolution and sensitivity of this sensor. The signal losses consist of the contributions from the skin effect of conductors, energy absorption in the dielectric material, and impedance mismatch loss due to multiple signal reflections resulting from discontinuities caused by the separation between the adjacent spirals, which acts as the outer conductor of a cable sensor. This paper summarizes the basic physics of signal losses in cable sensors, and investigates the impact of the signal losses on the spatial resolution and sensitivity of a cable sensor over distance. Several methods are proposed to simulate and quantify various factors affecting the signal losses.

A newly developed smart sensor node that can monitor the safety of temporary structures such as scaffolds at construction sites is detailed in this paper. The design methodology and its trade-offs, as well as its influence on the optimization of sensor networks, is examined. The potential impact on civil engineering construction sites, environmental and natural disaster pre-warning issues, etc., all of which are foundations of smart sensor nodes and corresponding smart sensor networks, is also presented. To minimize the power requirements in order to achieve a true wireless system both in terms of signal and power, a sensor node was designed by adopting an 8051-based micro-controller, an ISM band RF transceiver, and an auto-balanced strain gage signal conditioner. With the built-in RF transceiver, all measurement data can be transmitted to a local control center for data integrity, security, central monitoring, and full-scale analysis. As a battery is the only well-established power source and there is a strong desire to eliminate the need to install bulky power lines, this system designed includes a battery-powered core with optimal power efficiency. To further extend the service life of the built-in power source, a power control algorithm has been embedded in the microcontroller of each sensor node. The entire system has been verified by experimental tests on full-scale scaffold monitoring. The results show that this system provides a practical method to monitor the structure safety in real time and possesses the potential of reducing maintenance costs significantly. The design of the sensor node, central control station, and the integration of several kinds of wireless communication protocol, all of which are successfully integrated to demonstrate the capabilities of this newly developed system, are detailed. Potential impact to the network topology is briefly examined as well.

This study conducts an investigation on flaw cogged V-belts, galling roller-chains, and imbalancing rotors through a constructed transmission-component test bench. Nine channels of noise and vibration data are acquired and processed to extract features that exhibit the faulty condition of components in specific states. Two artificial neural network schemes, i.e., the backward propagation and self-organization mapping algorithms, are employed as pattern recognition tools. Additionally, the classification of condition patterns of machine components is further illustrated using a discrimination-space technique. Thus, the mechanism of pattern recognition of artificial neural networks can be clearly realized, but not only considered as an inaccessible processing black box.

The paper describes new concepts of flexible polyurethane auxetic (negative Poisson’s ratio) foams with embedded carbonyl dispersions. Compared to conventional flexible PU foams, this type of cellular solid exhibit higher compliance under impact loading and increased dielectric loss factors in the X-band between 12 and 18 GHz. Results from mechanical tensile tests and rectangular wave guide experiments are shown and discussed in view of possible applications on sandwich structures typical of Salisbury screens or microwave absorbers.