Permanently attached piezoelectric sensors arranged in a spatially distributed array are under consideration for structural health monitoring systems. Ultrasonic signals transmitted and received between various array elements have been shown to be effective for localizing discrete sites of damage using algorithms based upon changes in signals compared to the undamaged state. Necessary to the success of the various imaging methods which have been proposed is a set of baseline signals recorded under the same conditions as the signals acquired after damage has occurred. Since many conditions other than structural damage can cause changes in ultrasonic signals, proposed here is an integrated strategy whereby damage is first detected and is localized only if the outcome of the detection step is positive. In this manner false alarms can be reduced since signal changes due to benign variations will not be localized and erroneously identified as damage. The detection strategy considers the long time behavior of the signals in the diffuse-like regime where distinct echoes can no longer be identified, whereas the localization strategy is to generate images of damage based upon the early time regime when discrete echoes from boundary reflections and scattering sites are meaningful. Results are shown for an aluminum plate subjected to a combination of temperature variations and introduction of artificial damage.

Fatigue crack growth during the service life of aging aircraft is a critical issue and monitoring of such cracks in structural hotspots is the goal of this research. This paper presents a procedure for classification and detection of cracks generated in bolted joints which are used at numerous locations in aircraft structures. Single lap bolted joints were equipped with surface mounted piezoelectric (pzt) sensors and actuators and were subjected to cyclic loading. Crack length measurements and sensor data were collected at different number of cycles and with different torque levels. A classification algorithm based on Support Vector Machines (SVMs) was used to compare signals from a healthy and damaged joint to classify fatigue damage at the bolts. The algorithm was also used to classify the amount of torque in the bolt of interest and determine if the level of torque affected the quantification and localization of the crack emanating from the bolt hole. The results show that it is easier to detect the completely loose bolt but certain changes in torque, combined with damage, can produce some non-unique classifier solutions.

Retirement criteria for many structural components and particularly landing gear structural parts, are generally based on analytical fatigue methods because the current means of detecting actual component damage cannot detect sufficiently small levels of damage such that safe operation for a useful interval can be confidently determined; limiting the capability to apply damage tolerance methods. The testing completed in these projects demonstrated that Induced Positron Analysis (IPA) technologies are sensitive to the tensile plastic strain damage induced in aerospace material specimens and components. The IPA process has shown that IPA methods can reliably detect and quantify plastic strain and plastic deformation under simulated and operational conditions. A preliminary functional relationship between total strain and the normalized IPA S parameter has been developed for several aerospace materials. The fatigue testing has demonstrated the IPA technologies have potential to detect fatigue damage induced in specimens and operational components when the loads are large enough to cause plastic deformation.

Piezoelectric films sprayed onto metal substrates together with interdigital transducer electrodes form the integrated Rayleigh surface acoustic wave (RAW) transducers to excite and detect RAW. Using integrated longitudinal (L) wave ultrasonic transducers (UTs) and mode conversion from L waves to shear waves symmetrical, anti-symmetrical and shear horizontal types of guided plate acoustic waves have been generated and received in aluminum alloy plates. These transducers can be operated in pulse-echo mode for in-situ non-destructive testing (NDT) and/or health monitoring purposes in a distance of hundreds of mini-meters at 150°C. Examples of using such waves for NDT of defects are also demonstrated.

A representative area of concern for fatigue crack growth in aircraft occurs in multi-layered metallic structures. Ultrasonic plate waves are currently being investigated by multiple initiatives to detect these types of flaws with a minimal number of sensors to enable Structural Health Monitoring (SHM). Previous work has focused on structures with one or two layers, coupled with modeling of the wave propagation within these representative samples. However, it is common for multi-layered structures to have more than two layers in many areas of interest. Therefore, this study investigates ultrasonic wave propagation and flaw detection in a multi-layered sample consisting of 2 to 4 total layers with fatigue cracks located in only one layer. The samples contain fastener holes configured as would be expected to find on typical aircraft structure. The flaws in this study are represented by electric discharge machined (EDM) notches. Preliminary measurements show that EDM notches can be detected by the guided ultrasonic waves, but that the sensitivity to EDM notch location is dependent on the boundary conditions of each layer. The boundary conditions are changed by applying various loads on the surface of each layer by tightening and loosening the fasteners that hold the sample together. This variation depicts representative conditions found of aircraft. The experimental results are supplemented by modeling of the guided wave propagation within the structure using the Finite Element Method. The primary parameter studied in the modeling effort is the effect of the changes in the boundary condition on the mode and amplitude of the guided wave. The results of this investigation establish some guidelines for the use of guided waves in multi-layered structures, plus challenges that exist for their use in SHM applications and strategies to address these challenges.

Structural health monitoring of composite materials will lead to a significant safety and economic impact on the aircraft and aerospace industries. Ultrasonic guided wave based methods are becoming popular because of an excellent compromise between coverage area and sensitivity for localized damage detection. The transducers currently used in composite health monitoring are designed mostly in an empirical manner. The work presented in this paper provides an analytical procedure to study the wave excitation phenomenon in composite laminates. A hybrid semi-analytical finite element method and global matrix method is used to obtained the guided wave modal solutions. A normal mode expansion technique is then used to simulate the guided waves excited from a surface mounted piezoelectric transducer with transient loading. Parametric studies are performed to obtain the guided wave mode tuning characteristics and to study the influence of piezoelectric wafer geometry on wave excitation. In an inverse problem, an appropriate loading pattern can be designed to achieve selective guided wave mode excitation for improved sensitivity and/or penetration power in the health monitoring of composites. A wave field reconstruction algorithm based on normal mode expansion is also introduced in this paper. This method is also very computationally efficient compared with the commonly used finite element method in wave field excitation simulation.

A new methodology of guided wave based nondestructive testing (NDT) is developed to detect crack damage in a thin metal structure without using prior baseline data or a predetermined decision boundary. In conventional guided wave based techniques, damage is often identified by comparing the "current" data obtained from a potentially damaged condition of a structure with the "past" baseline data collected at the pristine condition of the structure. However, it has been reported that this type of pattern comparison with the baseline data can lead to increased false alarms due to its susceptibility to varying operational and environmental conditions of the structure. To develop a more robust damage diagnosis technique, a new concept of NDT is conceived so that cracks can be detected even when the system being monitored is subjected to changing operational and environmental conditions. The proposed NDT technique utilizes the polarization characteristics of the piezoelectric wafers attached on the both sides of the thin metal structure. Crack formation creates Lamb wave mode conversion due to a sudden change in the thickness of the structure. Then, the proposed technique instantly detects the appearance of the crack by extracting this mode conversion from the measured Lamb waves, and the threshold value from damage classification is also obtained only from the current data set. Numerical and experimental results are presented to demonstrate the applicability of the proposed technique to instantaneous crack detection.

Deployable guided wave systems are commercially used for the inspection of long lengths of pipelines in non-destructive testing (NDT) applications. On this basis it might seem that guided waves could be used in a structural health monitoring system (SHM) that is able to detect damage anywhere in a structure with a relatively sparse array of permanently attached sensors. Furthermore, while guided wave NDT is limited to simple structures because of the problem of signal interpretation, reference signal subtraction can be applied to guided wave SHM hence apparently solving the problem of structural complexity. Despite this, and considerable international research effort, there have been no serious commercial applications of guided wave SHM. In this paper, the concept of guided wave propagation and reference signal subtraction are examined at a fundamental level to analytically estimate the sensitivity of the reference signal subtraction approach. It is argued that the limitation on sensitivity is the size of the residual signal left after baseline signal subtraction. The subtraction is never perfect due to environmental changes and results in imperfect cancellation of the signals from benign structural features, such as welds, edges, flanges etc. It is shown that the sensitivity decreases with propagation distance and therefore sensor spacing. Examples of the required sensor pitch to detect a 6mm hole in a 3mm thick aluminium plate subjected to a 1°C temperature change are given, and show the significant detrimental effect that even small temperature changes can have. It is shown that a significant improvement (typically 20 dB) is possible if signal envelopes rather than RF signals are subtracted but that this leads to the problem of sensitivity functions that vary non-monotonically and which may even include blind spots.

A critical aspect of existing Structural Health Monitoring (SHM) systems is the ability to compare current data obtained from a structure to a prerecorded baseline measurement taken for an undamaged case. Several Lamb wave-based SHM techniques have been successfully developed that use baseline measurements to identify damage in structures. The method developed in this study aims to instantaneously obtain baseline measurements in order to eliminate any complications associated with archiving baseline data and with the effects of varying environmental conditions on the baseline data. The proposed technique accomplishes instantaneous baseline measurements by deploying an array of piezoelectric sensors/actuators used for Lamb wave propagation-based SHM such that data recorded for equidistant sensor-actuator path lengths can be used to instantaneously identify several common features of undamaged paths. Once identified, data from these undamaged paths can be used as a baseline for near real-time damage detection. This method is made possible by utilizing sensor diagnostics, a recently developed technique which minimizes false damage identification and measurement distortion caused by faulty sensors. Several aspects of the instantaneous baseline damage detection method are detailed in this paper including determination of the features best used to identify damage, development of signal processing algorithms used to analyze data, and a comparison of two sensor/actuator deployment schemes.

This paper presents an impedance-based structural health monitoring (SHM) technique considering temperature effects. The temperature variation results in a significant impedance variation, particularly a frequency shift in the impedance, which may lead to erroneous diagnostic results of real structures such as civil, mechanical, and aerospace structures. A new damage detection strategy has been proposed based on the correlation coefficient (CC) between the reference impedance data and a concurrent impedance data with an effective frequency shift which is defined as the shift causing the maximum correlation. The proposed technique was applied to a lab-sized steel truss bridge member under the temperature varying environment. It has been found, however, the CC values are still suffering from the significant fluctuation due to the temperature variation. Therefore, an outlier analysis providing the optimal decision boundary has been carried out for damage detection. From an experimental study, it has been demonstrated that a narrow cut inflicted artificially to the steel structure was successfully detected using the proposed SHM strategy.

This paper reports on the status of ongoing collaborative studies between UCSD, University of Bologna and University of Pittsburgh aimed at developing a monitoring system for prestressing strands in post-tensioned structures based on guided ultrasonic waves (GUWs) and built-in sensors. A Semi-Analytical Finite Element (SAFE) method was first used to compute dispersion curves of a pretwisted waveguide representing a seven-wire strand. The strand embedded in grout and surrounded by a concrete media was subsequently modeled as an axisymmetric waveguide. The SAFE method allows to account for the material damping and can be used to discriminate low loss guided modes. Experimental tests targeted at the defect detection and prestress level monitoring were performed. Notch like defects, machined in a seven wire strand, were successfully detected using a reflection-based Damage Index (D.I.) vector. The D.I. vector was extracted from GUWs measurements which were processed using Discrete Wavelet Transform (DWT). A four dimensional Outlier analysis was performed to discriminate indications of flaws. In a parallel study, transmission measurements were collected to identify wave features sensitive to prestress level in strands embedded in post-tensioned concrete blocks. The most sensitive features are being investigated further to assess their reliability in a monitoring system whit sensors embedded in a real post-tensioned concrete structure.

Electro-mechanical (E/M) impedance is a powerful structural identification and health monitoring (SHM) technique that allows for inferring high-frequency structural dynamic characteristics directly by interrogating a network of embedded piezoelectric active sensors. In recent years, there has been a considerable interest in expanding range of applications of the electromechanical impedance technique, its synergistic integration into complementary SHM methodologies, and miniaturizing the associated impedance measurement circuitry. The present work is aimed at developing an E/M impedance modeling approach that explores analogies between electrical and mechanical systems and permits representation of the mechanical system elements in terms of equivalent electrical circuits. The advantage of such a representation is that analytical modeling is substantially simplified by considering a network of electrical elements, mechanical quantities are incorporated directly into the electrical model of a measurement unit, and modern circuit design, simulation and analysis software tools can be employed to improve the method performance. The electro-mechanical model of a piezoelectric impedance sensor is discussed and development of the electrical circuit representation of the sensor-structure interaction is presented. The proposed electrical and existing mechanical models are compared showing a good agreement. Applicability of the developed modeling approach is discussed and examples of numerical calculations are provided. It is suggested that describing a sensor-structure electro-mechanical system in terms of electro-mechanical analogies could simplify analytical modeling and improve instrumentation design.

Guided wave phased array systems have great potential in structural health monitoring (SHM), especially for aircraft applications due to its capability of steering the emitted guided wave beam to inspect a large area with the sensor array at just one accessible position. However, when the guided wave phased array is applied to composite panels of an aircraft component, the anisotropic behavior of the composite materials leads to a significant influence on the beam steering performance of the phased array. In this study, mode neighborhoods in dispersion curves where guided waves have quasi-isotropic behavior (i.e. constant or similar phase velocities in different wave propagation directions) are explored for unidirectional, cross-ply, and quasi-isotropic composite plates. It was demonstrated that the energy skewness of guided waves was well suppressed in these mode neighborhoods. Furthermore, by utilizing a modified delay-and-sum beam forming algorithm, the guided wave beam of a linear phased array can be steered quite well to the desired directions in a composite plate.

We introduce a simultaneous multipoint acousto-ultrasonic (AU) sensing system using a tunable laser and fiber wave Bragg grating (FWBG) sensors. Although the demodulation technique is same as the existing method for a fiber Bragg grating (FBG), the sensor head is changed to the FWBG sensor for which the FBG is installed in a strain-free configuration and detects the AU wave not directly but in the form of a fiber-guided wave. Therefore since the strain cannot make the FBG spectrum move, multiple FBGs with an identical spectrum can be connected with multiple optical paths realized by equal laser intensity dividers. Temperature difference among the multiple FWBG sensors is passively resolved by using a short grating, which provides a wider temperature-operating region. Consequently, we can solve the problem that the FBG spectrum is easily deviated from the lasing wavelength owing to the strain. Also, the simultaneous multipoint sensing capability based on the single laser improves cost-performance ratio, reduces inspection time, and enables in-situ monitoring of a real structure exposed to large and dynamic strain. The system feasibility is demonstrated in the health monitoring examples like acoustic source localization and ultrasonic waves detection burst by a piezoelectric transducer and a pulsed laser.

In the European project SAFE PIPES guided elastic waves in the frequency range between 100 and 250 kHz, generated and detected by appropriate transducer arrays, are used to monitor the structural integrity of industrial piping systems by comparing the actual state of the pipe with a predefined reference state. In the present paper, theoretical, numerical, and experimental investigations are combined to study guided wave propagation and wave interaction with relevant defects in detail. Based on these findings, a guided wave based multi-channel SHM system is designed and applied for monitoring of crack-like defects in steel pipes. The first results reveal that guided wave based SHM in the kHz frequency regime has great potential for online monitoring of piping systems. It is able to combine imaging techniques with long range detection capabilities and therefore closes the gap between high-frequency NDE on the one hand and low-frequency vibration analysis on the other hand.

Guided wave techniques have been used for pipeline inspection because of their long-range inspection capability. One of main concerns of these techniques is how ones decide axial interval of sensors. This question is related to the characteristics of attenuation of cylindrical guided waves. Parametric density concept is proposed for a long-range pipeline inspection. This concept is designed to obtain the attenuation of ultrasonic guided waves propagating in underwater pipeline without complicated calculation of attenuation dispersion curves. For this study, three pipe materials are considered, then different transporting fluids are assumed, and four different pipe geometries are adopted. It is shown that the attenuation values based on the parametric density concept reasonably match with the attenuation values obtained from the dispersion curves. However, it seems that the parametric concept is only applicable for fluid-filled underwater pipes. The limitations of the parametric density concept are also discussed.

The magnetostrictive effect is used to generate ultrasonic waves for a variety of health monitoring applications. Given the ductile nature of many ferromagnetic materials and the common geometrical configuration of magnetic inductance coils, magnetostrictive generation of ultrasound is especially suitable for long cylindrical waveguides such as thin wires. Furthermore, utilizing ultrasonic guided wave modes in such waveguides provides a robust tool for remote inspection of materials or environments over long distances. Through the use of different guided wave modes, structural health monitoring sensors could be tailored to suit individual applications. Guided wave modes offer a choice in displacement profile allowing sensors to be designed to be either sensitive or impervious to surface effects. The dispersivity of the guided wave velocity can also be optimized for applications involving time-of-flight measurements. Despite the advantages afforded by guided wave analysis, current magnetostrictive transducers, consisting of coil of wire and a bias magnet, can not perform at the frequencies necessary to excite higher order guided wave modes. In order to advance the capability of magnetostrictive transducers for ultrasonic guided waves in wires, the design parameters of inductance coils are examined. Using a Laser Doppler Vibrometer, ultrasonic displacements are measured over a range of excitation frequencies for different coil configurations and parameters to determine the feasibility of developing a higher mode magnetostrictive transducer.

Triangulation technique for impact point location works very well when the acoustic emission sensors are placed at a relatively large distance from the point of impact. In this situation the time of arrival measurement is not affected significantly by the small error that might arise from not being able to pinpoint the exact time of arrival of the acoustic signal. The conventional technique also requires that the wave speed in the medium is well-known and non-dispersive in the frequency range of interest. If the receiving wave is a P-wave or S-wave or a non-dispersive Rayleigh wave then the conventional triangulation technique is reliable. In this paper it is shown that the conventional triangulation technique is not very reliable for locating the impact point in a plate when the sensors are placed close to the striking point for two reasons - first, it is difficult to pin point the exact time of arrival of the signal and secondly the Lamb modes in a plate are dispersive. Dispersive signals attenuate differently at various frequencies and propagate with different speeds causing distortions in the received signals and thus introduce more error in the time of flight measurement. In this paper an alternative approach is proposed to locate the impact point more accurately. Experiments are carried out with an aluminum plate. The impact points predicted by the conventional triangulation technique and the proposed modified method are compared.

Guided Lamb waves can be excited in composite materials through piezoelectric wafer active sensors (PWAS) to detect damage. PWAS are small, light-weight, inexpensive, and can be attached or embedded in composite structures. The proposed paper will present a parallel effort on two analytical approaches for predicting Lamb wave propagation in composite structures with surface attached PWAS. The first approach implements a layerwise mechanics theory and finite element for laminated composite beams with transducers and delaminations. The second approach uses a transfer matrix methodology (TM) and normal mode expansion (NME) to predict PWAS-plate interaction. Wave propagation predictions are performed using 2-D layerwise beam theory approximating the in-plane displacement, the through-thickness displacements and the electrical field as a continuous assembly of linear layerwise fields through the thickness. The effect of delamination cracks can be predicted by the introduction of additional degrees of freedom. Prediction of symmetric, antisymmetric and shear horizontal Lamb wave dispersion curves is done for composite material structures using TM methodology developed by Nayfeh. NME technique is applied to predict the PWAS tuning curves on composite plates; theoretical and experimental results are compared. Prediction of sensor signals and local displacement curves through the thickness will be presented for composite structure.

Due to their high sensitivity, layered Surface Acoustic Wave (SAW) devices are ideal for various film characterization and sensor applications. Two prominent wave types realized in these devices are Rayleigh waves consisting of coupled Shear Vertical and Longitudinal displacements and Love waves consisting of Shear Horizontal displacements. Theoretical calculations of sensitivity of SAW devices to pertubations in wave propagation are limited to idealized scenarios. Derivations of sensitivity to mass change in an overlayer are often based on the effect of rigid body motion of the overlayer on the propagation of one of the aforementioned wave types. These devices often utilize polymer overlayers for enhanced sensitivity. The low moduli of such overlayers are not sufficiently stiff to accommodate the rigid body motion assumption. This work presents device modeling based on the Finite Element Method. A coupled-field model allows for a complete description of device operation including displacement profiles, frequency, wave velocity, and insertion loss through the inclusion of transmitting and receiving IDTs. Geometric rotations and coordinate transformations allow for the modeling of different crystal orientations in piezoelectric substrates. The generation of Rayleigh and Love Wave propagation was realized with this model by examining propagation in ST Quartz both normal to and in the direction of the X axis known to support Love Waves and Rayleigh Waves, respectively. Sensitivities of layered SAW devices to pertubations in mass, layer thickness, and mechanical property changes of a Polymethyl methacrylate (PMMA) and SU-8 overlayers were characterized and compared. Experimental validation of these models is presented.

Defects in underground pipes are detected by applying Gabor transforms on experimental guided wave signals and comparing the experimental group velocity plots with the theoretical group velocity dispersion curves. Gabor transform, which is a powerful signal processing tool, maps a signal into a two-dimensional space of time and frequency. Thus it provides information about both when and at what frequency a signal arrives. Focus of this paper is to study the applicability of cylindrical guided waves to detect defects in underground pipes using Gabor transform. Cylindrical guided waves are generated by piezo-electric transducers. Guided waves are propagated through pipes that are buried in the soil by placing transmitters on one end of the pipes and the receivers on the other end. The recorded signals are then processed using 2-D Gabor Transform or Short Time Fourier Transform (STFT). Gabor transform converts the time-amplitude signal into a time frequency signal which reveals the group velocities hidden in the signal. These experimentally obtained group velocities are then compared with the theoretical velocities for cylindrical pipes embedded in the soil. From the comparison of the theoretical and experimental group velocities, an effort has been made to identify which modes are propagating through the embedded defective pipes and which modes are having difficulty to propagate through the defective pipe wall. From this knowledge pipe wall defects can be detected.

Several nondestructive testing methods can be used to estimate the extent of damage in a concrete structure. Pulse-velocity and amplitude attenuation methods are very common in nondestructive ultrasonic evaluation. Velocity of propagation is not very sensitive to the degree of damage unless a great deal of micro-damages have evolved into localized macro-damages. The amplitude attenuation method is potentially more sensitive to damage than the pulse-velocity method. However, this method depends strongly on the coupling conditions between the transducers and the concrete and hence is unreliable. In a previous study, a new active modulation approach, Nonlinear Active Wave Modulation Spectroscopy, was developed and found promising for early detection of damage in concrete. In this procedure, a probe wave is passed through the system in a fashion similar to regular acoustic methods for inspection. Simultaneously, a second, low-frequency modulating wave is applied to the system to effectively change the size and stiffness of flaws microscopically and cyclically, thereby causing the frequency modulation to change cyclically as well. The resulting amplified modulations can be correlated to the extent of damage and quantification of small damage becomes possible. In this paper, we present the use of Hilbert-Huang transform to significantly enhance the damage detection sensitivity of this modulation method by performing time-frequency decomposition of nonlinear non-stationary time-domain responses.

In recent years Distributed Point Source Method (DPSM) is being used for modelling various ultrasonic, electrostatic and electromagnetic field modelling problems. In conventional DPSM several point sources are placed near the transducer face, interface and anomaly boundaries. The ultrasonic or the electromagnetic field at any point is computed by superimposing the contributions of different layers of point sources strategically placed. The conventional DPSM modelling technique is modified in this paper so that the contributions of the point sources in the shadow region can be removed from the calculations. For this purpose the conventional point sources that radiate in all directions are replaced by Controlled Space Radiation (CSR) sources. CSR sources can take care of the shadow region problem to some extent. Complete removal of the shadow region problem can be achieved by introducing artificial interfaces. Numerically synthesized fields obtained by the conventional DPSM technique that does not give any special consideration to the point sources in the shadow region and the proposed modified technique that nullifies the contributions of the point sources in the shadow region are compared. One application of this research can be found in the improved modelling of the real time ultrasonic non-destructive evaluation experiments.

The aim of this study is to use observed data from a shaking table test to verify experimentally an SVR-based (support vector regression) structural identification approach. The method has been developed in previous work and showed excellent performance for large-scale structural health monitoring in numerical simulations. SVR is a promising data processing method employing a novel &egr;-insensitive loss function and the 'Max-Margin' idea. Thus the SVR-based approach identifies structural parameters accurately and robustly. In this method, a sub-structure technique is used thus the SVR-based analysis is reduced in dimension. Experimental validation is necessary to verify the method's capability to identify structural status from real data. For this purpose, a five-floor shear-building shaking table test has been conducted and two cases, input excitations to the shaking table of the Kobe (NS 1995) earthquake and a Sine wave with constant frequency and amplitude are investigated.

Vibration-based damage detection has grown over the past decade with considerable attention paid towards monitoring of civil structures and machines. Much of the focus has been based on comparison of system properties 'before' and 'after' damage, with the premise that the system can be treated as linear in both states. This work uses a novel method for analyzing vibration signatures, aimed at monitoring structures and machines for incipient damage. This non-destructive method is based on a new technique, Empirical Mode Decomposition (EMD) and Hilbert-Huang Transform (HHT) for non-stationary and non-linear time series analysis. The technique essentially allows the decomposition of the time-domain signals into intrinsic oscillatory modes, providing a time-frequency distribution. Results from analysis of vibration signatures from anti-friction bearings will be presented. The data was obtained from experiments conducted on a lab test set-up specifically designed for this study. Analysis based on the time-frequency plots and Hilbert-Huang spectrum illustrate that this new approach may allow for the development of a reliable damage detection methodology for antifriction bearings.

Vibration-based damage identification is a useful tool for structural health monitoring. But, the damage detection results always have uncertainty because of the measurement noise, modeling error and environment changes. In this paper, information fusion based on D-S (Dempster-Shafer) evidence theory and Shannon entropy are employed for decreasing the uncertainty and improving accuracy of damage identification. Regarding that the multiple evidence from different information sources are different importance and not all the evidences are effective for the final decision. The different importance of the evidences is considered by assigning weighting coefficient. Shannon entropy is a measurement of uncertainty. In this paper it is employed to measure the uncertainty of damage identification results. The first step of the procedure is training several artificial neural networks with different input parameters to obtain the damage decisions respectively. Second, weighing coefficients are assigned to neural networks according to the reliability of the neural networks. The Genetic Algorithm is employed to optimize the weighing coefficients. Third, the weighted decisions are assigned to information fusion center. And in fusion center, a selective fusion method is proposed. Numerical studies on the Binzhou Yellow River Highway Bridge are carried out. The results indicate that the method proposed can improve the damage identification accuracy and increase the reliability of damage identification to compare with the method by neural networks alone.

We examined strain time series from fiber Bragg gratings sensors located in various positions on a composite material beam attached to a steel plate by a lap joint. The beam was vibrated using both broad-band chaotic signals (Lorenz system), and a narrow band signal conforming to the Pierson-Moskowitz frequency distribution for wave height (ambient excitation). The system was damaged by decreasing the torque on instrumented bolts in the lap joint from very tight all the way through to a joint with a gap and slippage. We analyzed the strain data by reconstructing the attractor of the system in the case of chaotic forcing and a pseudo-attractor in the case of sea-wave forcing. Using the highest torque case as an "undamaged" baseline, we calculated the continuity statistic between the baseline attractor and the attractors of the various damage levels for both forcing cases. We show where one can and cannot say that the functional relationship between the attractors changes and how those changes are related to damage levels.

Higher order spectral analysis techniques are often used to identify nonlinear interactions in modes of dynamical systems. More specifically, the auto and cross- bispectra have proven to be useful tools in testing for the presence of quadratic nonlinearities based on a system's stationary response. In this paper a class of mechanical system represented by a second-order nonlinear equation of motion subject to random forcing is considered. Analytical expressions for the second-order auto- and cross-spectra are determined using a Volterra functional approach and the presence and extent of nonlinear interactions between frequency components are identified. Numerical simulations accompany the analytical solutions to show how modes may interact nonlinearly producing intermodulation components at the sum and/or difference frequency of the fundamental modes of oscillation. A closed-form solution of the Bispectrum can be used to help identify the source of non-linearity due to interactions at specific frequencies. Possible applications include structural health monitoring where damage is often modeled as a nonlinearity. Advantages of using higher-order spectra techniques will be revealed and pertinent conclusions will be outlined.

Higher-order spectra (HOS) appear often in the analysis and identification of nonlinear systems. The auto-bispectrum is one example of a HOS and is frequently used in the analysis of stationary structural response data to detect the presence of certain types structural nonlinearities. In this work we use a closed-form expression for the auto-bispectrum, derived previously by the authors, to find the bispectral frequency most sensitive to the nonlinearity. We then explore the properties of nonlinearity detectors based on estimates of the magnitude of the auto-bispectrum at this frequency. We specifically consider the case where the bispectrum is estimated using the direct method based on the Fourier Transform. The performance of the detector is quantified using a Receiver Operator Characteristic (ROC) curve illustrating the trade-off between Type-I error and power of detection (1-Type-II error). Theoretically derived ROC curves are compared to those obtained via numerical simulation. Results are presented for different levels of nonlinearity. Possible consequences are discussed with regard to the detection of damage-induced nonlinearities in structures.

Fatigue tests on a stabilizer bar link of an automotive suspension system are used to initiate a crack and grow the crack size. During these tests, slow sine sweeps are used to extract narrowband restoring forces across the stabilizer bar link. The restoring forces are shown to characterize the nonlinear changes in component internal forces due to crack growth. Broadband frequency response domain techniques are used to analyze the durability response data. Nonlinear frequency domain models of the dynamic transmissibility across the cracked region are shown to change as a function of crack growth. Higher order spectra are used to show the increase in nonlinear coupling of response frequency components with the appearance and growth of the crack. It is shown that crack growth can be detected and characterized by the changes in nonlinear indicators.

Several data-driven features have recently proven to be successful at detecting damage in structures. Some of these features, developed within the context of their state space attractors, highlight dynamics-specific changes without relying on model-specific forms or assumptions such as linearity. Features such as generalized interdependence and state space prediction error can also be formulated such that they provide information about generalized correlations between time series. Therefore, in addition to damage indications, these features can also provide details about the location of damage in a structure by comparing dynamical differences between measurements. This work proposes a framework for establishing such an analysis procedure that can detect presence, extent, location, and/or type of damage in a structure from a single feature. This approach is validated on a multi-degree of freedom oscillator.

We have demonstrated that the parameters of a system of ordinary differential equations may be adjusted via an evolutionary algorithm to produce 'optimized' deterministic excitations that improve the sensitivity and noise robustness of state-space based damage detection in a supervised learning mode. Similarly, in this work we show that the same approach can select an 'optimum' bandwidth for a stochastic excitation to improve the detection capability of that same metric. This work demonstrates that an evolutionary algorithm can be used to shape or color noise in the frequency domain, such that improvement is seen in the sensitivity of the detection metric. Properties of the improved stochastic excitations are compared to their deterministic counterparts and used to draw inferences concerning a globally preferred excitation type for the model spring-mass system.

Flexible ultrasonic array transducers which can be attached to the desired structures or materials for nondestructive testing and structural health monitoring applications at room and elevated temperatures are developed. These flexible ultrasonic transducers (UTs) arrays consist of a thin polyimide membrane with a bottom electrode or stainless steel foil, a piezoelectric lead-zirconate-titanate (PZT) composite film and top electrodes. The flexibility is realized owing to the porosity of piezoelectric film and the thinness of substrate and electrodes. Top and bottom electrode materials are silver paste, silver paint or electroless plated nickel alloys. The UT array is configured by the several top electrodes. The flexible UT has been successfully tested at 150°C and also immersed into water as immersion ultrasonic probe operated in the pulse-echo mode with good signal to noise ratio.

In order to facilitate damage detection and structural health monitoring (SHM) research for composite unmanned aerial vehicles (UAV) a specialized test-bed has been developed. This test-bed consists of four 2.61 m all-composite test-pieces emulating composite UAV wings, a series of detailed finite element models of the test-pieces and their components, and a dynamic testing setup including a mount for simulating the cantilevered operation configuration of real wings. Two of the wings will have bondline damage built in; one undamaged and one damaged wing will also be fitted with a range of embedded and attached sensors-piezoelectric patches, fiber-optics, and accelerometers. These sensors will allow collection of realistic data; combined with further modal testing they will allow comparison of the physical impact of the sensors on the structure compared to the damage-induced variation, evaluation of the sensors for implementation in an operational structure, and damage detection algorithm validation. At the present time the pieces for four wings have been fabricated and modally tested and one wing has been fully assembled and re-tested in a cantilever configuration. The component part and assembled wing finite element models, created for MSC.Nastran, have been correlated to their respective structures using the modal information. This paper details the design and manufacturing of the test-pieces, the finite element model construction, and the dynamic testing setup. Measured natural frequencies and mode shapes for the assembled cantilevered wing are reported, along with finite element model undamaged modal response, and response with a small disbond at the root of the top main spar-skin bondline.

The objective of this study is to apply the concept of structural health monitoring to the detection of bolted joints loosening without human involvement. This paper proposes a method of bolt loosening detection by adopting a smart washer with sub-space state space identification (4SID) algorithm. The smart washer is the cantilevered plate type washer bonded piezoelectric material. The feature is the self-sensing and actuation function. The principle of how to detect the loosening of a bolt is the basis that the natural frequency of a smart washer system vary depending on a bolt tightening axial tension. The natural frequency of the smart washer was identified by using the sub-space state space identification method. For practical use of the smart washer, it is necessary to investigate the problem of repeatability and data quality depending on the influence of the ambient temperature characteristics, and to improve the sensitivity at the initial state of the bolt tightening axial tension decreasing. This paper describes the results of experimental and analytical about the effect on the sensitivity for the smart washer configuration, and the ambient temperature characteristics on the bolted joint. The experimental results indicate the influence of the temperature variation to the bolt tightening axial tension. In order to the sensitivity of the improve bolt loosening detection, vibration-modal analysis of the smart washer system is performed for the configuration of the smart washer. The design parameters of the smart washer was discussed on the results of the numerical simulation.

Coulomb excitation and detection of ultrasonic waves in piezoelectric crystals by spherical electrical probes is discussed in view of the opening angle of the cone of longitudinal waves coupling to such a probe. The electric field distribution in the piezoelectric crystal under the probe is modeled by means of finite elements in order to determine the effective size of the probe normalized to the sphere radius. The dynamic impedance of the probe is estimated, and it is shown that a probe of a size appropriate to illuminate or detect from the piezoelectric half space has a frequency-independent impedance of about 3 k&OHgr; under idealizing assumptions. Measurements of the directionality of ultrasound emission and detection at a frequency of about 100 MHz are presented for three probes with different tip radii, varying from about 30 &mgr;m to 2.5 mm. As expected, larger probes yield a higher directionality. A relatively large forward contribution is observed even for small spheres.

Previous work has led to the design, simulation, and development of a linear phased array transducer. The intention of the array is to be used as a non-destructive ultrasonic device to monitor and evaluate the health of a given specimen. The phased array has been manufactured and tested for the detection and characterization of defects on a target. The array was fabricated with a four-row "stepped" design with four wires to transfer data and one wire for grounding. The "stepped" design allows for the interrogation of a larger region using time delays and beam sweeping without the use of additional electrical channels. The array was designed to be utilized in a water immersion environment with about one inch between the array and the target specimen. An OmniScan MX system was used to operate the phased array and perform real-time linear and sectorial scans on a set of rectangular plates. S-scans allow for beam sweeping over an angle range as well as adjustments for time delays and a true-depth display. The array was operated with sixteen active elements and an angle range of 0 to 30 degrees. The phased array was tested with a variety of targets and was used to investigate and characterize different types of defects such as cracking, warping, and corrosion. The ability of the phased array to distinguish between defect types as well as resolve defect size was evaluated.

In this paper, we present a feasibility study of using wireless energy transmission systems to provide a required power for structural health monitoring (SHM) sensor nodes. The goal of this study is to develop SHM sensing systems which can be permanently embedded in the host structure and do not require an on-board power sources. With this approach, the energy will be periodically delivered as needed to operate the sensor node, as opposed to being harvested as in the conventional approaches. The wirelessly transmitted microwave energy is captured by a microstrip patch antenna, and then transformed into DC power by a rectifying circuit and stored in a storage medium to provide the required energy to the sensor and transmitter. Based on the fact that recent networked sensor systems require power on the order of fractions of a watt, it is quite possible to operate such sensing devices completely from the captured wirelessly delivered energy. The method of designing and optimizing a wireless energy transmission system is discussed. This paper also summarizes considerations needed to design such energy delivery systems, experimental procedures and results, and additional issues that can be used as guidelines for future investigations.

Method for viscosity measurement has not changed significantly over the past several decades. Most common techniques either require sample to be taken from the material to be measured or special installation of a side stream to be set up to monitor the viscosity. Here we present a compact fiber optic based viscometer based on damping measurement stem from interaction between fluid and the optical sensor. The fluid viscosity measurement is deduced from the fluid's frictional damping on the surface of the immersed vibrating fiber optic probe. This frictional damping, which becomes the dominant factor in the fluid damping under a small fiber's vibration, is a function of viscosity. Utilizing an intrinsic polarimetric technique, the fiber's vibration profile can be measured and thus damping characteristic due to viscosity on the probe can be derived. The uniqueness of the sensor is its compact size and potential application in an industrial environment without any additional modification to the existing sensor or the industrial setting. The sensor is also potentially can be made portable so that operators can take with them to the test site. Here theoretical and preliminary results will be presented.

The current work details the implementation of a meta-model based correlation technique on a composite UAV wing test piece and associated finite element (FE) model. This method involves training polynomial models to emulate the FE input-output behavior and then using numerical optimization to produce a set of correlated parameters which can be returned to the FE model. After discussions about the practical implementation, the technique is validated on a composite plate structure and then applied to the UAV wing structure, where it is furthermore compared to a more traditional Newton-Raphson technique which iteratively uses first-order Taylor-series sensitivity. The experimental testpiece wing comprises two graphite/epoxy prepreg and Nomex honeycomb co-cured skins and two prepreg spars bonded together in a secondary process. MSC.Nastran FE models of the four structural components are correlated independently, using modal frequencies as correlation features, before being joined together into the assembled structure and compared to experimentally measured frequencies from the assembled wing in a cantilever configuration. Results show that significant improvements can be made to the assembled model fidelity, with the meta-model procedure producing slightly superior results to Newton-Raphson iteration. Final evaluation of component correlation using the assembled wing comparison showed worse results for each correlation technique, with the meta-model technique worse overall. This can be most likely be attributed to difficultly in correlating the open-section spars; however, there is also some question about non-unique update variable combinations in the current configuration, which lead correlation away from physically probably values.

Although structural health monitoring and patient monitoring may benefit from the unique advantages of optical fiber sensors (OFS) such as electromagnetic interferences (EMI) immunity, sensor small size and long term reliability, both applications are facing different realities. This paper presents, with practical examples, several OFS technologies ranging from single-point to distributed sensors used to address the health monitoring challenges in medical and in civil engineering fields. OFS for medical applications are single-point, measuring mainly vital parameters such as pressure or temperature. In the intra-aortic balloon pumping (IABP) therapy, a miniature OFS can monitor in situ aortic blood pressure to trigger catheter balloon inflation/deflation in counter-pulsation with heartbeats. Similar sensors reliably monitor the intracranial pressure (ICP) of critical care patients, even during surgical interventions or examinations under medical resonance imaging (MRI). Temperature OFS are also the ideal monitoring solution for such harsh environments. Most of OFS for structural health monitoring are distributed or have long gage length, although quasi-distributed short gage sensors are also used. Those sensors measure mainly strain/load, temperature, pressure and elongation. SOFO type deformation sensors were used to monitor and secure the Bolshoi Moskvoretskiy Bridge in Moscow. Safety of Plavinu dam built on clay and sand in Latvia was increased by monitoring bitumen joints displacement and temperature changes using SMARTape and Temperature Sensitive Cable read with DiTeSt unit. A similar solution was used for monitoring a pipeline built in an unstable area near Rimini in Italy.

The physical deterioration of reinforced concrete reefs, which were fully immersed in Tongyeong waters of South Korea for 19, 21, 23, and 25 years, respectively, were investigated. Firstly, the marine environmental factors such as sea temperature, salinity, pH, dissolved oxygen, sea bottom materials, and water depth of target water sites were observed from 1997 to 2002. Secondly, four reinforced concrete reefs recovered from different sites in Tongyeong waters were tested through various nondestructive tools such as visual inspection, composition test, tensile strength test, compressive strength test, absorption rate and apparent density test, and pore volume test. Thirdly, those test results are analyzed to see the physical deteriorations. Based on the observations and test results, it is shown that, in global, the reinforced concrete reefs have sound physical properties and their originally estimated service life is secured enough for a further service period in the water depth of 28 to 32 m.

This paper presents an improved finite element (FE) model updating method for Binzhou Yellow River Highway Bridge and its associated uncertainties by utilizing measured dynamic response data. The dynamic characteristics of the bridge have been studied through both three dimensional finite element prediction and field vibration previously. A comprehensive sensitivity study to demonstrate the effects of structural parameters (including the connections and boundary conditions) on the modes concern is first performed, according with a set of structural parameters are then selected for adjustment. According to the eigenequation considering uncertainties, the proposed methodology transforms model updating problem for Binzhou Yellow River Highway Bridge into two deterministic constrained optimization problems regarding the predictable part and uncertainties of structural parameters. Both the predictable part and associated uncertainties of the structural parameters could be obtained in iterative fashions so as to minimize the difference between the predicted and the measured natural frequencies. The final updated model for Binzhou Yellow River Highway Bridge is able to produce natural frequencies and associated frequency uncertainties in good agreement with measured ones, and can be helpful for a more precise dynamic response prediction.

In this paper, a dynamic method will be developed to identify the surrounding bedding conditions of an undersea pipeline. The pipeline on the seabed is modeled as a simply supported beam on an elastic foundation. Two parameters are used to describe the scour or free span of the pipeline: they are the central location of the scour or span and the width of the scour or span. The study takes into account the dynamic interaction between the pipeline and the elastic foundation. The parameters are determined from natural frequencies of the pipeline. The effect of the number of natural frequencies and the measurement noise levels on the accuracy of the identification results of the pipeline bedding conditions is studied. Numerical simulation shows that the method is effective and reliable to assess the bedding conditions of the undersea pipeline.

Filament-wound rocket motor casings are being considered by the United States Army for use in future lightweight missile systems. As part of the design process, a real-time, minimal-sensing, quasi-active health-monitoring system is being investigated. The health-monitoring scheme is quasi-active because abnormal loads acting on the structure are identified passively, the input force is not measured directly, and the curve-fit estimate of the impact force is used to update the frequency response functions (FRFs) that are functions of the system properties. This task traditionally requires an active-interrogation technique for which the input force is known. The updated FRFs and the estimated impact force can then be used in model-based damage-quantification methods. The proposed quasi-active approach to health monitoring is validated both analytically with a lumped-parameter model and experimentally with a composite missile casing. Minimal sensing is used in both models in order to reduce the complexity and cost of the system, but the small number of measurement channels causes the system of equations used in the inverse problem for load identification to be under-determined. However, a novel algorithm locates and quantifies over 3000 impacts at various locations around the casing with over 98% success, and the FRF-correction process is successfully demonstrated.

The spectral data i.e. eigenvalues (natural-frequencies) and eigenvectors (mode-shapes), characterizes the dynamics of the system. The dynamic analysis of physical systems leads to certain direct and inverse eigenvalue problems. The direct eigenvalue problem deals in evaluating the spectral behavior of structures for given distributions of physical parameters such as mass, area, stiffness etc. whereas, the estimation of these physical parameters form the spectral data is known as inverse eigenvalue problem. The detection of minuscule (small) changes in the stiffness and mass of the structure, by solving certain inverse eigenvalue problems, is addressed here by considering a grooved axially vibrating rod. In solving direct problems, we have considered two types of eigenvalue problem: (i) traditional algebraic eigenvalue problems and (ii) transcendental eigenvalue problems associated with the continuous system. In conclusion, we have (a) obtained the eigenvalues of damaged rod, (b) analyzed the behavior of the spectral data due to minuscule change in the physical parameters, and (c) determined the different type of spectral data that are required for detecting damage parameters. Several numerical examples are solved here demonstrating the feasibility and accuracy of the identification technique by solving Transcendental Inverse Eigenvalue Problems.

Corrosion is detrimental to the structural integrity of many critical components, and ultrasonic methods are routinely used in the field to make thickness measurements at points of interest. However, is often difficult to assess the true extent of corrosion damage because of the likelihood of missing small corroded areas and the difficulty in mapping the extent of large corroded areas without an extensive number of time consuming measurements. Guided ultrasonic waves have the potential to both detect corrosion as early as possible and reduce the subsequent inspection time. This paper presents results from a study using Lamb waves to quantify the area extent of corrosion in an aluminum plate specimen. A sparse array of ultrasonic transducers was attached to an aluminum plate, and broadband excitation methods were used to generate both symmetric and anti-symmetric Lamb wave modes. As has been demonstrated in previous studies, the through transmission response recorded from each transmit-receive pair may be analyzed to determine if a defects exists and approximately determine its location. This paper presents a method to determine the exact location and quantify the extent of the corroded area using an acoustic wavefield imaging method. Lamb waves are generated using one of the permanently attached transducers as a source, and the acoustic wavefield is captured on the surface of the plate using an air-coupled transducer as a receiver. Full wavefield data are recorded as the receiver is scanned over the specimen surface, and wavefield images are processed to remove the strong incident wave and enhance the weaker scattered waves. The amplitude at the crest of the leading Lamb mode (S₀) is analyzed to produce spatial images of defective areas. Measured length and area results from these images compare very favorably with actual defect sizes. Results are also presented for scattering from a through hole with a simulated crack.

The quantitative evaluation of damage in woven composites using mode selective excitation of Lamb waves is reported in this paper. PVDF (polyvinylidene fluoride) comb sensors are used to generate and detect a single plate mode. The top electrode is a single set of equidistant fingers connected in parallel to the same potential while the bottom electrode is kept at ground. First, a pair of such sensors is used to generate and detect a single plate mode. Group velocity changes of a wave packet traveling through the damaged area are used for quantitative damage estimation. Second, a new electrode configuration is used in order to improve the receiver signal. The proposed configuration referred to as continuous sensors, is used in structural health monitoring (SHM) for detection of growing cracks. Theoretical and experimental results are presented. In addition, an analog circuitry to actuate the structure at high frequency (~1MHz) based on energy tapped from a vibrating cantilever beam (~20Hz) is developed, towards a high-frequency energy-harvested SHM.

Wind power is a fast-growing source of non-polluting, renewable energy with vast potential. However, current wind turbine technology must be improved before the potential of wind power can be fully realized. Wind turbine blades are one of the key components in improving this technology. Blade failure is very costly because it can damage other blades, the wind turbine itself, and possibly other wind turbines. A successful damage detection system incorporated into wind turbines could extend blade life and allow for less conservative designs. A damage detection method which has shown promise on a wide variety of structures is impedance-based structural health monitoring. The technique utilizes small piezoceramic (PZT) patches attached to a structure as self-sensing actuators to both excite the structure with high-frequency excitations, and monitor any changes in structural mechanical impedance. By monitoring the electrical impedance of the PZT, assessments can be made about the integrity of the mechanical structure. Recently, advances in hardware systems with onboard computing, including actuation and sensing, computational algorithms, and wireless telemetry, have improved the accessibility of the impedance method for in-field measurements. This paper investigates the feasibility of implementing such an onboard system inside of turbine blades as an in-field method of damage detection. Viability of onboard detection is accomplished by running a series of tests to verify the capability of the method on an actual wind turbine blade section from an experimental carbon/glass/balsa composite blade developed at Sandia National Laboratories.

As a key problem of the vibration-based damage detection, many damage indexes were developed in recent years, but a systematic and effective method to evaluate those damage indexes is not available till now. Therefore, a new assessment method by sensitivity from damage indexes to stiffness, adaptation to noise, ability of correct identification based on incomplete information and locality indicating locations of damage precisely is proposed in this paper to reflect various main problems in the damage detection and choose the proper damage index. The numerical example results show that conclusions drawn from proposed method as a foreordain way is consistent with common conclusions of previous study. The assessment method containing four indexes to qualify characteristic of indicators has bright prosperity in large structures for many important problems in practice are considered.

The paper describes the development of a mesh waveguide sensor capable of measuring pressure force at the plantar interface. The uniqueness of the system is in its batch fabrication process, which involves a microfabrication molding technique with poly(dimethylsiloxane)(PDMS) as the optical medium. The pressure sensor consists of an array of optical waveguides lying in perpendicular rows and columns separated by elastomeric pads. A map of normal stress was constructed based on observed macro bending which causes intensity attenuation from the physical deformation of two adjacent perpendicular waveguides. In this paper, optical and mechanical analysis of the bend loss will be presented. We will also present the results using a two-layer neural network system for force and image construction of fourteen different shape patterns and its corresponding four different applied forces.

Point source ultrasound holography has been applied to small bone samples using a phase sensitive scanning acoustic microscope (PSAM) in transmission at about 100 MHz. Conversion of the phase images into appropriate data matrices and subsequent data processing yielded the angle dependent ultrasound velocities for the observed space sector. The mathematical tools were derived from geometrical considerations and the basic properties of propagating acoustic waves. The results match conventional direction resolved measurements of the sound velocity in bone. However, the presented technique requires only two specimens. The demonstrated results are obtained for sample sizes of 5 × 5 × 0.5 mm³. No chemical or other treatment which could significantly influence the composition of the bone samples is required. The technique is illustrated and the results are demonstrated and discussed.

Narrowband excitation at 86 MHz with vector detection and wideband excitation in the range of 2 to 20 MHz have both been used for tomographic imaging in transmission. A line-shaped point spread function has been realized by temporal apodization selecting from a pulsed signal observed in transmission only the contribution traveling the path connecting the transducer foci. By this method a pair of scanned focusing transducers mounted in a defocused arrangement was employed for tomographic imaging. The technique relates to shadowing of a point source in transmission as used in X-ray tomography, but, in addition, variations of the time-of-flight are measured else by phase contrast or a cross-correlation procedure with high resolution. From these data an image with velocity contrast can be derived in addition to the conventional image representing the extinction in the samples under investigation. Examples presented include resolution test samples and biomedically relevant materials. It is also demonstrated that the coherent detection scheme can be used to enhance the resolution by the synthesis of an enlarged aperture. Respective procedures are implemented for image reconstruction.

A multi-layered optical bend loss sensor for pressure and shear sensing is presented. This design is based on the characteristic of optical bend loss. When external forces applied to the sensor, the optical fibers will bend and cause the light to escape from the fiber. The amount of light attenuation depends on the amount of bending occurred on the fiber. In our previous study, the sensor is composed of two layers of fiber optic mesh sensors that are molded into a thin polydimethyl siloxane (PDMS) substrate. Measuring changes of light intensity transmitted through the fiber provides information about the changes of the fiber's radius of curvature. The new design induces an elastomeric layer to separate the two optical fiber meshes. Pressure is measured based on the force induced light loss from the two affected crossing fibers. Shear was measured based on the relative position changes on these pressure points between the two fiber mesh layers. The additional elastomeric layer provides mobility in the lateral direction to improve the shear sensing. Preliminary testing on the new multi-layered sensor under normal and shear loading is encouraging. By adding the gel layer, when the applied force is 5N, the maximum attenuation is 30% at the top layer and 3% at the bottom layer. For the shear force detection, shifting of loading point at bottom layer was also observed from the experiment.

In this work, we discuss the design and implementation of a Bluetooth technology based infant monitoring system, which will enable the mother to monitor her baby's health condition remotely in real-time. The system will measure the heart rate, and temperature of the infant, and stream this data to the mother's Bluetooth based mobile unit, e.g. cell phone, PDA, etc. Existing infant monitors either require so many cables, or transmit only voice and/or video information, which is not enough for monitoring the health condition of an infant. With the proposed system, the mother will be warned against any abnormalities, which may be an indication of a disease, which in turn may result a sudden infant death. High temperature is a common symptom for several diseases, and heart rate is an essential sign of life, low or high heart rates are also essentials symptoms. Because of these reasons, the proposed system continously measures these two critical values. A 12 bits digital temperature sensor is used to measure infant's body temperature, and a piezo film sensor is used measure infant's heartbeat rate. These sensors, some simple analog circuitry, and a ToothPick unit are the main components of our embedded system. ToothPick unit is basically a Microchip 18LF6720 microcontroller, plus an RF circuitry with Bluetooth stack.

Biomechanical studies often involve measurements of the strains developed in tendons or ligaments in posture or locomotion. Fiber optic sensors present an attractive option for measurement of strains in tendons and ligaments due to their low cost, ease of implementation, and increased accuracy compared to other implantable transducers. A new displacement sensor based on fiber Bragg grating and shape memory alloy technology is proposed for the monitoring of tendon and ligament strains in different postures and in locomotion. After sensor calibration in the laboratory, a comparison test between the fiber sensors and traditional camera displacement sensors was carried out to evaluate the performance of the fiber sensor during application of tension to the Achilles tendon. Additional experiments were performed in cadaver knees to assess the suitability of these fiber sensors for measuring ligament deformation in a variety of simulated postures. The results demonstrate that the proposed fiber Bragg grating sensor is a high-accuracy, easily implantable, and minimally invasive method of measuring tendon and ligament displacement.

The detection and location of holes in an isotropic aluminium plate using fibre Bragg grating rosettes to detect ultrasound Lamb waves is described. This is followed by a description of the anisotropic properties of a carbon fibre plate and their effect on hole detection. Finally, the issues involved in attempting to locate holes in an anisotropic samples are discussed and the possibility of achieving this assessed

Changes in environmental conditions, and in particular temperature, limit the sensitivity of guided wave structural health monitoring (SHM) systems that use reference signal subtraction. The limitation on sensitivity is the size of the residual signal left after reference signal subtraction that arises from imperfect subtraction of the signals from benign structural features. The sensitivity can be improved by decreasing the spacing between sensors but the effect of temperature is so strong that it is doubtful whether the resulting SHM system is economically viable. This provides the motivation for searching for alternative strategies to improve sensitivity. One possibility is to record an ensemble of reference signals over a range of temperatures and then use the signal in the ensemble that best matches a subsequent signal for subtraction. Experimental results show that this provides an improvement in sensitivity of around 35 dB. It does however require a large database of signals and there is the potential concern that the subtraction of the best match signal may somehow also remove a genuine signal from damage. Another possibility is signal processing to improve sensitivity. A uniform temperature change to a structure results in a change in wave velocity and a dilation of the structure itself. The net effect is a dilation of the arrival times of each wave-packet in a guided wave signal. An obvious strategy to compensate for this effect is to apply the inverse dilation to the time-axis. However, this does not compensate for the effect exactly since the temperature change does not dilate individual wave-packets. An alternative and exact compensation scheme is presented and its practical application is discussed.

This paper is concerned with the detection and characterization of impact damage in stiffened composite structures using high frequency Lamb waves and low frequency modal vibrations. The geometric and material complexities of the structure present practical difficulties in the direct analysis of both wave propagation and modal vibration data using theoretical constructs. An improved test setup, consisting of high fidelity sensor arrays, laser scanning vibrometer, data acquisition boards, signal conditioning and dedicated software has been implemented. The conceptual structural health monitoring (SHM) system presented here involves a low level computational effort, has high reliability, and is able to treat the acquired data in real-time to identify the presence of existing as well as emerging damage in the structure. A statistical damage index algorithm is developed and automated by utilizing a diagnostic imaging tool to identify a defect right from its appearance, with high degree of confidence. The main advantage of the method is that it is relatively insensitive to environmental noise and structural complexities as it is based on the comparison between two adjacent dynamical states of the structure and the baseline for comparison is continuously updated to the previous state. The feasibility of developing a practical Intelligent Structural Health Monitoring (ISHM) System, based on the concept of "a structure requesting service when needed," is discussed.

In this study, a vibration-based method to simultaneously predict prestress-loss and flexural crack in PSC girder bridges is presented. Prestress-loss and flexural crack are two typical, but quite different in nature, types of damage which can be occurred in PSC girder bridges. The following approaches are implemented to achieve the objective. Firstly, two vibration-based damage detection techniques which can predict prestress-loss and flexural crack are described. The techniques are prestress-loss prediction model and mode-shape-based crack detection method. In order to verify the feasibility and practicality of the techniques, two different lab tests are performed. A free-free beam with external unbonded tendons is used to verify the feasibility of the prestress-loss prediction model. In additional, a PSC girder with an internal unbonded tendon is used to evaluate the practicality of the prestress-loss prediction model and the mode-shape- based crack detection method.

To develop a promising hybrid structural health monitoring (SHM) system, which enables to detect damage by the dynamic response of the entire structure and more accurately locate damage with denser sensor array, a combined use of structural vibration and electro-mechanical (EM) impedance is proposed. The hybrid SHM system is designed to use vibration characteristics as global index and EM impedance as local index. The proposed health-monitoring scheme is implemented into prestressed concrete (PSC) girder bridges for which a series of damage scenarios are designed to simulate various prestress-loss situations at which the target bridges can experience during their service life. The measured experimental results, modal parameters and electro-magnetic impedance signatures, are carefully analyzed to recognize the occurrence of damage and furthermore to indicate its location.

In practical structural health monitoring, it is essential to develop an efficient technique which can detect structural local damage utilizing only a limited number of measured acceleration responses of structures subject to unknown (unmeasured) excitations inputs. In this paper, a finite-element based time domain system identification method is proposed for this purpose. Structure state vectors are treated as implicit functions of structural dynamic parameters and excitations. The unknown structural dynamic parameters and excitation inputs are identified by an algorithm based on recursive least squares estimation with unknown excitations (RLSE-UI). Structural damage at element level is detected by the degrading of stiffness of damaged structural elements. Numerical simulation of a 3-story building demonstrates the proposed method can identify structural element stiffness parameters with good accuracy and structural damage at element level can be located from the degrading of element stiffness parameters.

This paper introduces an on-going research effort for integrating a wireless monitoring system to evaluate the long-term structural behavior of honeycomb fiber reinforced polymer (FRP) sandwich panels for bridge deck systems. The effort includes developing analytical models for evaluating the structural behavior of the panels and experimentally investigating the practicality and reliability of using wireless sensor systems for health monitoring. In the analytical part, three finite element models and one simplified I-beam model are to predict the structural behaviors of FRP sandwich panels. In the experimental part, a wireless sensor system is applied to measure structural response of FRP panels under static loading. The results of the analytical and experimental models are compared to evaluate the applicability of the wireless sensor system and validate the results of the analytical models. Conclusions are drawn from two aspects: first, preferable modeling methods are recommended in conducting structural analysis; second, the reliability and accuracy of the wireless sensor system is assessed.

Ubiquitous monitoring combining internet technologies and wireless communication is one of the most promising technologies of infrastructure health monitoring against the natural of man-made hazards. In this paper, an integrated framework of the ubiquitous monitoring is developed for real-time long term measurement in internet environment. This framework develops a wireless sensor system based on Bluetooth technology and sends measured acceleration data to the host computer through TCP/IP protocol. And it is also designed to respond to the request of web user on real time basis. In order to verify this system, real time monitoring tests are carried out on a prototype self-anchored suspension bridge. Also, wireless measurement system is analyzed to estimate its sensing capacity and evaluate its performance for monitoring purpose. Based on the evaluation, this paper proposes the effective strategies for integrated framework in order to detect structural deficiencies and to design an early warning system.

The engineering of human tissue represents a major technique in clinical medicine. Material evaluation of skin is important as preventive medicine. Decubitus originates in pressure and the rub. However, shearing in the skin has exerted the influences on the sore pressures most. This paper examines one demand of crucial importance, namely the real time in vivo monitoring of the shearing characteristics skin tissue. Rheometer is a technology developed to measure viscoelasticity of solid and liquid. To measure viscoelasticity of the skin in the noninvasive with this device, we remodeled it. It is ideal for the continuous monitoring of tissues in vivo.

Damage detection is the core technique of structure health monitoring systems. Mostly, the detection is based on comparison of initial signatures (frequency, mode shapes and so on) of intact structure with that of damaged structure. The techniques based on the analysis of vibration data of structures have received great attention in recent years. Generally, high-rise buildings have enough security under wind or some other natural conditions. Instances of damage caused by routine work can be rarely found. But under earthquake, high-rise buildings damages may occur on some weakness areas. In this paper, based on establishing the stiffness matrix of the columns and beams with joint damage, the finite element model of the damaged frame structure is set up. Calculating the modal date by the finite element model between the intact and damaged structure, simple and multi damages being imitated at the locations of the joints, the curvature mode shape method is used to identify the damage. The numerical example shows that the structural damage can be efficiency identified by using vibration characteristics of the building.