A model based analysis of the interaction of high intensity focused ultrasound with biological materials is carried out in an effort to predict the path of the sound waves and the temperature field in the focal region. A finite element based general purpose code called PZFlex is used to determine the effects of nonlinearity and geometrical complexity of biological structures. It was found that at frequencies of interest in therapeutic applications, the nonlinear effects are usually negligible and the geometrical complexities can be handled through a sub-structuring procedure. An approximate analytical method is developed as an alternative to the purely numerical approach used in PZFlex. The mechanical and thermal effects in two-layered fluid material systems induced by high-frequency focused ultrasound are calculated through this analytical method. The analytical method is shown to be computationally much more efficient than the numerical method and to yield results with acceptable accuracy for clinical applications.

Ultrasonic atomic force microscopy (U-AFM) was used to image the elastic properties of hamster kidney (BHK) cells. Force-distance curves and finite element analysis were also used in this work assist in the description of the U-AFM images. These tools helped explain the differences in contrast seen from the center to the edge of the cell. The explanation of the U-AFM image contrast will lead to more analytical tools to investigate both nonviable and viable materials. Improvement of our system for living cell (in a culture) imaging is also discussed.

A decisive problem in biomedical or biomaterial research of the post-genomic era is the determination of protein structure and function. Common techniques that can give full structural information do not permit in-vivo measurements. Vibrational Proteomics, an innovative combination of biochemical techniques and infrared or Raman spectroscopy, can provide information which will help substantially to fill this gap. Infrared and Raman spectroscopy are well established as methods for qualitative and quantitative analysis of protein secondary structure, in solution and even when adsorbed to implant surfaces. Their singular advantage over other techniques is that spectra can be obtained for proteins in a wide range of environments, in solutions and on surfaces including polymers, metals and bioceramics. Here we report on structural changes in fibrinogen from the dissolved to the adsorbed state on implant material of different hydrophobicity. FTIR imaging permits the identification of coagulation spots on the implant.

Acoustic techniques are widely employed in health monitoring and nondestructive evaluation of materials. Phase micrographs obtained by phase-sensitive acoustic techniques often contain useful information complementary to the information acquirable from amplitude micrographs alone. Most of this information remains relatively unexploited due to the difficulties encountered in unwrapping and processing of the raw phase data. In this work, a review of the derivable information from the phase images of a scanning acoustic microscope with phase contrast (PSAM) is presented. Different perspectives and insights on sample structural and biological mesocale systems are discussed, predicated on phase information obtained by simulations and three-dimensional imaging.

A flexible high-resolution sensor capable of measuring the distribution of both shear and pressure at the plantar interface are needed to study the actual distribution of this force during daily activities, and the role that shear plays in causing plantar ulceration. We have previously developed a novel means of transducing plantar shear and pressure stress via a new microfabricated optical system. However, a force image algorithm is needed to handle the complexity of construction of two-dimensional planar pressure and shear images. Here we have developed a force image algorithm for a micromachined optical bend loss sensor. A neural network is introduced to help identify different load shapes. According to the experimental result, we can conclude that once the neural network has been well trained, it can correctly identify the loading shape. With the neural network, our micromachined optical bend loss Sensor is able to construction the two-dimensional planar force images.

Among the methods for the determination of mechanical properties of living cells acoustic microscopy provides some extraordinary advantages. It is relatively fast, of excellent spatial resolution and of minimal invasiveness. Sound velocity is a measure of the stiffness of the cell. Attenuation of cytoplasm is a measure of supramolecular interactions. These parameters are of crucial interest for studies of cell motility, volume regulations and to establish the functional role of the various elements of the cytoskeleton. Using a phase and amplitude sensitive scanning acoustic microscope, longitudinal wave speed, attenuation and thickness profile of a biological cell have been measured earlier by Kundu, Bereiter-Hahn and Karl (2000) from the voltage versus frequency or V(f) curves in the frequency range 980-1100 MHz. Two limitations of that study are overcome in this paper. In that study it was assumed that the cell properties did not change through the cell thickness and could vary only in the lateral direction. Secondly, the acoustic microscope generated ultrasonic signal was modeled in that study as a plane wave striking the cell and the substrate at normal incidence. Such assumption ignores the contribution of the surface skimming Rayleigh waves. Improved and more generalized analysis that is presented here avoids such restrictive assumptions. For the first time, in this paper the cell is modeled as a multi-layered material with different properties for nucleus and surrounding cell material. The inverse problem is solved to study the effect of drugs on living cells.

Microbubbles, are produced inside the human body by several mechanisms which may cause many serious health problems or even death. The ability of a gas bubble to scatter ultrasound waves has led to the testing of various ultrasonic devices to monitor microbubble formation in the blood stream. These have included pulsed echo, acoustic-optical imaging, Doppler technique and the through-transmission technique. In this work, a pulse through transmission method for measuring ultrasound velocity in bubbly gel phantoms was used. The bubble size has been assessed by measurement of the pulse-wave velocity. A specially designed pressure chamber ensured the measured velocity was directly related to the volume of microbubble by Boyle's law. This velocity is an average indicator of the bubble size between transmitting and receiving transducers. The average bubble radius was 0.1 mm. For best results the measurement were carried out around 1-3 MHz frequency range. It is shown that a large change in velocity of ultrasound occurs as a result of small changes in the volume of microbubble. When the fraction by volume of gas in gel is changed from 0.6 percent to 0.8 percent the velocity changed from 1500 to 500 m/s respectively. This large change in velocity should provide a good base for detecting and more importantly, sizing microbubbles in the blood stream. The measured results were compared with theoretical prediction with good agreement between theory and experiment. This technique can be used as a simple real time method to monitor and measure the volume of the microbubles in the blood stream. This technique has many application in medical field such as; open heart surgery, blood dialysis and deep sea diving (decompression sickness).

In this study, a new wireless sensing unit for operation within an automated Structural Health Monitoring (SHM) system is proposed, designed and validated. The design of the wireless sensing unit emphasizes minimization of its power consumption characteristics to ensure it is suited for long-term field deployment in civil structures. The wireless modem integrated with the unit has a long communication range that permits wireless sensors to be spaced over 100m apart. A multi-channel high-resolution analog-to-digital converter is included within each sensing unit to provide flexibility for high-fidelity data collection. A key feature of the wireless sensing unit design is the inclusion of a sophisticated computing core that is capable of locally executing engineering algorithms in real-time. As part of the embedded software, a novel communication protocol is written that can accomplish low-latency communications for accurate time synchronization between spatially distributed wireless sensors. To illustrate the capabilities of the wireless monitoring platform, including the execution of extensive computational tasks, a prototype system is fabricated and tested in the laboratory and field. As part of validating the system performance in the field, the vertical acceleration response of the Geumdang Bridge under traffic loading is measured by 14 wireless sensing unit prototypes.

Emerging wireless sensor technology presents a tremendous opportunity for developing low-cost monitoring systems for civil infrastructure. A set of wireless MICA2 mote accelerometers were deployed on a reinforced concrete bridge column to collect data during a shaking table earthquake simulation test. The data from the test were ingested into a data and metadata system for testing the usability of the metadata description for data mining and visualization. The metadata system used the NEESgrid metadata services interface for backend storage. The results of the data acquisition and ingestion were used to determine the feasibility of using a comprehensive sensor, data storage, and data retrieval system for health monitoring.

Concrete bridge piers are a common structural element employed in the design of bridges and elevated roadways. In order to ensure adequate behavior under earthquake-induced displacements, extensive reinforcement detailing in the form of closely spaced ties or spirals is necessary, leading to congestion problems and difficulties during concrete casting. Further, costly repairs are often necessary in bridge piers after a major earthquake which in some cases involve the total or partial shutdown of the bridge. In order to increase the damage tolerance while relaxing the transverse reinforcement requirements of bridge piers, the use of high-performance fiber reinforced cementitious composites (HPFRCC) in earthquake-resistant bridge piers is explored. HPFRCCs are a relatively new class of cementitious material for civil structures with tensile strain-hardening behavior and high damage tolerance. To monitor the behavior of this new class of material in the field, low-cost wireless monitoring technologies will be adopted to provide HPFRCC structural elements the capability to accurately monitor their performance and health. In particular, the computational core of a wireless sensing unit can be harnessed to screen HPFRCC components for damage in real-time. A seismic damage index initially proposed for flexure dominated reinforced concrete elements is modified to serve as an algorithmic tool for the rapid assessment of damage (due to flexure and shear) in HPFRCC bridge piers subjected to large shear reversals. Traditional and non-traditional sensor strategies of an HPFRCC bridge pier are proposed to optimize the correlation between the proposed damage index model and the damage observed in a circular pier test specimen. Damage index models are shown to be a sufficiently accurate rough measure of the degree of local-area damage that can then be wirelessly communicated to bridge officials.

Changes in diffuse ultrasonic signals recorded from permanently mounted sensors can be correlated to initiation and growth of structural damage, offering hope that sparse sensor arrays can be utilized for monitoring large areas. It is well-known that benign environmental changes also have significant effects on diffuse ultrasonic signals that are of comparable magnitude to the effects of damage. Several methodologies are investigated for quantifying differences in diffuse ultrasonic signals by computing parameters that can be used to discriminate damage from environmental changes. The methodologies considered are waveform differencing, spectrogram differencing, change in local temporal coherence, and temperature compensated differencing. For all four methods, a set of baseline waveforms are first recorded from the undamaged specimen at a range of temperatures, and subsequently recorded waveforms are compared to those of the baseline set. Experimental data from aluminum plate specimens with artificial defects are analyzed. Results show that the local coherence method is the most effective for discriminating damage from temperature changes whereas waveform differencing is the least effective. Both the spectrogram differencing method and the temperature compensated differencing method offer intermediate performance. As expected, the efficacy of all four methods improves as the number of waveforms in the baseline set increases.

This paper presents recent developments and approaches (using GPS technology and real-time double-integration) to obtain displacements and, in turn, drift ratios, in real-time or near real-time to meet the needs of the engineering and user community in seismic monitoring and assessing the functionality and damage condition of structures. Drift ratios computed in near real-time allow technical assessment of the damage condition of a building. Relevant parameters, such as the type of connections and story structural characteristics (including geometry) are used in computing drifts corresponding to several pre-selected threshold stages of damage. Thus, drift ratios determined from real-time monitoring can be compared to pre-computed threshold drift ratios. The approaches described herein can be used for performance evaluation of structures and can be considered as building health-monitoring applications.

This paper presents the preliminary findings of a study on data and system identification results (derived from collected data) in a wireless sensing environment. The goal of this study is to understand how various hardware design choices and operational conditions affect the quality of the data and accuracy of the identified results; the focus of this paper is packet and data loss. A series of experimental investigations are carried out using a laboratory shaking table instrumented with off-the-shelf Micro-Electro-Mechanical Systems (MEMS) accelerometers. A wireless sensing unit is developed to interface with these wired analog accelerometers to enable wireless data transmission. To reduce the overall design variance and aid convenient application in civil infrastructure health monitoring, this wireless unit is built with off-the-shelf microcontroller and radio development boards. The anti-aliasing filter and analog-to-digital convectors (ADC) are the only customized components in the hardware. By varying critical hardware configurations, including using analog accelerometers of different commercial brands, taking various designs for the anti-aliasing filter, and adopting ADCs with different resolutions, shaking table tests are repeated, the collected data are processed, and the results are compared. Operational conditions such as sampling rate and wireless data transmitting range are also altered separately in the repeated testing. In all of the cases tested, data is also collected using a wire-based data acquisition system to serve as a performance baseline for evaluation of the wireless data transmission performance. Based on this study, the challenges in the hardware design of wireless sensing units and data processing are identified.

It is estimated that 70% of all mechanical failures are related to fastener failure. One important mode of fastener failure is self-loosening of bolted joints. Self-loosening is especially problematic when the bolted joint is in an inaccessible location, a hostile environment, or a part of a machine whose shutdown would be costly. In this study, a piezoelectric (PZT) active-sensing device was used to detect the self-loosening mode in bolted joint connections. PZT enhanced washers were used to continuously monitor the condition of the joint by monitoring its dynamic characteristics. The mechanical impedance matching between the PZT enhanced devices and the joint connections was used as a key feature to monitor the preload changes and prevent further failure. The dynamic response was readily measured using electromechanical coupling property of the PZT patch, in which its electrical impedance is coupled with the mechanical impedance of the structure. This paper summarizes experimental results, the considerations needed in experimental procedures and design and several issues that can be used as a guideline for future investigation.

Damage prognosis of structures and systems can be significantly improved by developing intelligent sensors with adaptive sensitivity to the ambient signals via self-tuned criticality. Active amplification of weak signals using an inherent dynamical sensory mechanism which is maintained at the threshold of an oscillatory instability is proposed in this paper as a general framework for designing and developing sensors for damage detection and prognosis for civil and mechanical systems. This idea is inspired by the sensing mechanism of mammalian cochlea to develop a new sensing system paradigm. A numerical feasibility study of such a sensor system is conducted and presented as a building block for more general design and future implementation.

The thermal protection system is an essential part of any launch vehicle. Standoff metallic thermal protection system (TPS) panels protect the vehicle from the hostile environment on the panel exterior; consequently, the panels are exposed to a variety of loads including high temperature thermal stresses, thermal shock, acoustic pressure, and foreign object impact. These loads can cause degradation in the health of mechanically attached metallic TPS panels in the form of, for example, face sheet buckling, deformation/cracking of standoff bolts and standoffs or wrinkling to thermal seals. In this work, two sets of experiments were performed. The first experiment aimed to partially recreate the acoustic environment that the TPS experiences during service by subjecting the panel to broadband noise broadcast from a loudspeaker. In this set of experiments, "damage" was introduced into the TPS by loosening standoff fasteners to represent cracked or warped bolts and a transmissibility-based damage index was implemented to detect and locate damage. The second experiment was designed to examine the variation in damage indices when the panel is subjected to combined thermo-acoustic loading. In this set of experiments, the panel was not subjected to any "damage"; instead, the exterior of the panel was heated with an infrared heat lamp while being excited by acoustic noise. It is demonstrated that the transmissibility-based damage indicator is a viable method for detecting and locating damage in the TPS panel. It is also shown that damage present in the panel may become more or less identifiable while the system is subjected to thermal loading. This paper was approved for unlimited public release on February 18, 2005; LA-UR-05-1192.

The fusion of data from Edge of Light(EOL) and eddy current inspections of aircraft lap joints is investigated in this study. The pillowing deformation caused by corrosion products is estimated by the EOL technique first. Eddy current (ET) techniques, e.g. multi-frequency eddy current testing (MF-ET) and pulsed eddy current testing (P-ET), can provide depth-sensitive inspections of fuselage joints. The objective of this study is to investigate how the testing results obtained from the two different methods correlate to each other and what kind of complementary information is available in each result. This work contains two steps. First, the EOL inspection is quantified through a calibration process where a laser displacement sensor is used to provide the reference. The EOL estimation is for the total material loss while the eddy current or pulsed eddy current testing is employed to provide the complementary information on the remaining thickness. Second, the ET data are fused with the principle component analysis method and the results are calibrated by a calibration experiment. Finally, the bottom layer corrosion is estimated through the subtraction of EOL and ET results. The preliminary results are presented in this paper.

Most of the multi-layered aircraft structures including composite structures are still inspected primarily through various visual methods that require removal of multiple structural components to detect flaws in the internal layers of the structure. Some aircraft operators utilize for the multi-layered inspections more advanced NDI techniques such as X-ray. However, application of the X-ray technique still requires access to the bottom layers of the multi-layered structures for proper positioning of films or digital sensors. Additional time is also needed to comply with the safety rules for the X-ray inspection procedures. Hence, current inspection procedures for the multi-layered aircraft structures are fairly cumbersome, time-consuming and costly. Application of the dry-coupled ultrasonic modules makes it possible to detect and characterize defects in the internal layers from outside aircraft skin without disassembly. The inspection technique is easy to use, and, at the same time, is sensitive enough to identify critical structural degradation caused by the defects. The dry-coupled inspection technique is also sufficiently rapid so that aircraft downtime is minimized. The modules are also suitable for concurrent flaw detection and sealant quality monitoring in the multi-layer aircraft structures. The concept of the dry-coupled transducer modules has already been tested on the DC-10 horizontal stabilizer (crack detection around fasteners). Several current inspection procedures for aircraft multi-layered composite structures were reviewed to identify the areas for effective implementation of the dry-coupled ultrasonic techniques. Ultrasonic inspection techniques are being developed including flaw detection and characterization protocols for internal defects in various layers of the multi-layered structures. Modular dry-coupled ultrasonic transducers with exchangeable elements and digital encoding systems are being modified for applications on the multi-layered composite structures.

In recent work at Northwestern University, we have shown that near-field scattering of ultrasound generated by a Scanning Laser Source (SLS) can be used to effectively identify surface flaws in macroscale structures. In past work, the laser ultrasound source was in the near-field of a scatterer and a piezoelectric detector was used to measure the ultrasound in the far field. It was observed that distinct variations are observed in the far-field signals as the SLS scans past surface-breaking flaws. These changes were attributed to the near-field scatterer redirecting parts of the ultrasonic beam (which might otherwise have gone into the bulk of the object) towards the far-field detector. We now propose an extension of the SLS approach to map defects in microdevices by bringing both the generator and the receiver to the near-field scattering region of the defects. For the purpose of near-field ultrasound measurement, the receiving transducer has to be made very small as well. To facilitate this, silicon microcantilever probes are fabricated and their acoustical characteristics are first investigated. Silicon cantilevers with tip and chip body are fabricated using isotropic reactive ion etching and anisotropic KOH etching. To characterize the free cantilever vibration, the chip body with the microcantilever is excited by an ultrasonic transducer and a Michelson interferometer is used to monitor the cantilever motion. The fundamental frequency of the microcantilever is measured and compared with analytically calculated fundamental frequency assuming the cross sections of the cantilevers are rectangular. Next, the performance of the fabricated microcantilevers as ultrasound detectors is investigated. The microcantilever is used essentially as a profilometer by contacting it to the specimen surface. Surface and bulk acoustic waves are generated with specific narrowband frequencies and the surface ultrasonic displacements are detected using the microcantilever probe. Next, broadband ultrasound is generated by a laser source and the resulting surface acoustic displacements are monitored using the microcantilever probe in the near-field of the source. Finally, both the laser-generated ultrasonic source and the microcantilever probe are used to monitor near-field scattering by a surface-breaking defect.

Magneto-Optical Imagers (MOI) appear to be good alternatives to conventional eddy current sensors for defect detection in large metallic structures. Indeed, they allow short time inspection of large structures such as airplanes fuselage or wings, thanks to the visualization of "real time" images relative to the presence of defects [1]. The basic principle of the MOI is to combine a magnetic inductor, used to induce the circulation of eddy currents into the structure under test, with an optical set-up used to image the resultant magnetic field, thanks to the Faraday effect occurring in a magneto-optical garnet. The MOI designed by G. L. Fitzpatrick and Physical Research Instrumentation provides two-level images relative to the presence of defects, with an adjustable detection threshold. These so-called qualitative images, although highly contrasted, are rather poor and limited in terms of defect characterization possibilities. In, this paper, the authors present a new kind of MOI, called Quantitative Magneto-Optical Imager (Q-MOI), based on the use of a dedicated "linear" magneto-optical garnet associated with a specific instrumentation. The Q-MOI should considerably reduce the inspection time and allow to fully characterize the encountered defects. First images obtained with a demonstration prototype are shown for surface and buried flaws and further enhancements of the device are proposed.

Acoustic Micro Imaging (AMI) has long been established as a method of NDT of the wafer-to-wafer bonding quality in directly bonded wafers. In conventional imaging systems a C-Mode Scanning Acoustic Microscope operating in reflection is utilized. In this paper a non-confocally adjusted Phase Sensitive Acoustic Microscope (PSAM) operating in transmission at a frequency of 85 MHz is employed for imaging. This mode of operation results in a time-dependent point spread function, which together with full-transient data acquisition allows for its optimization in terms of resolution in the post-processing stage. Furthermore, the information contained in the images produced by varying time-dependent PSF is used for identification of bonding defects in directly bonded wafers. Both completely disbanded and weak bond regions in the wafer-to-wafer interface are identified. These latter areas are present, e.g. at the rim of the entirely disbanded regions as an intermediate interface condition between fully bonded and completely disbanded states. Mode conversion of the ultrasound waves at the solid-solid and solid-liquid wafer boundaries has been exploited to excite shear waves that are sensitive to weak bonds. A short burst transducer excitation and time-selective post-processing of the acquired data is employed to prevent overlap with the direct transmission signal or its echo sequences and in this way making visible the amplitude variation induced by the interface bond degradation.

An electromagnetic method allowing to localize and characterize main damages inside composites such as CFRP and GFRP, has been developed. This method is based on the local measurement of the induced electric field, by electric excitation (GFRP) or magnetic induction (CFRP). All damages inducing a local variation of electric conductivity and/or dielectric permittivity, one can detect and characterize damages inside composites materials by analysis of these two parameters. On the other hand, this technique allows detecting some damages having non mechanical origin such as liquid ingress (e.g. water oil, fuel...) or small burns generated by electric sparks (e.g. short circuits, lightning impacts), these kinds of damages being quasi non detectable by more classical methods such as ultrasonic analysis.

One paradigm within the structural health monitoring field involves analyzing the vibration response of structures as a method of detecting damage. Recent work has focused on extracting damage-sensitive features from the state-space representation of the structural response. Some of these features involve constructing a baseline attractor and an attractor at some later time and using the baseline to predict the evolution of the future attractor. An inability to accurately predict said evolution can be construed as possible damage to the structure. Such attractor-based methods are sensitive to a number of parameters related to reconstruction of the attractor, prediction techniques, and statistical accuracy. This work couples various input excitations with experimental data in an attempt to optimize these parameters for maximum sensitivity to damage.

Detection of the change in the vibration response of a structure as a means of damage detection has long been explored in the structural health monitoring field. Recently, damage detection metrics based on state-space attractor comparisons have been presented in the literature. This work compares various state-space attractor methods within an experimental context in an effort to determine the sensitivity of the methods to induced damage. The various methods are judged according to damage discrimination capability and computational effort.

Recent research has shown that chaotic structural excitation and state space reconstruction may be used beneficially in structural health monitoring (SHM). The focus of this study is to apply a chaotic waveform to a piezoelectric (PZT) patch that is bonded to a test structure. The use of high frequency chaotic excitation (~80 kHz) combined with PZT active sensing allows the location of incipient damage in the structure to be easily identified. The generation of high frequency chaos from a low frequency process necessitates bandwidth up-conversion that has been shown to be dimension preserving. We investigate the use of this method in conjunction with a novel prediction error algorithm to determine the damage state of a frame structure.

Structural system identification, historically, has largely consisted of seeking linear relationships among vibration time series data, e.g., auto/cross-correlations, modal analysis, ARMA models, etc. This work considers how dynamical relationships may be viewed in terms of 'information flow' between different points on a structure. Information or interdependence metrics (e.g., time-delayed mutual information) are able to capture both linear and nonlinear aspects of the dynamics, including higher-order correlations. This work computes information-based metrics on a frame experiment where nonlinearity is introduced by the loosening of a bolt. Both linear and nonlinear measures of dynamical interdependence are then used to assess the degree of degradation to the joint. Results indicate clear differences in the way linear and nonlinear measures quantify the bolt loosening.

Recent train accidents and associated direct and indirect repair costs have reaffirmed the need for developing rail defect detection systems more effective than those used today. The group at the UCSD NDE & Structural Health Monitoring Laboratory, in collaboration with the US Federal Railroad Administration, is conducting a study that aims at developing an inspection strategy for rails based on guided ultrasonic waves. This paper illustrates a guided-wave inspection system that is targeted to the detection of transverse-type cracks in the rail head, that are among the most dangerous flaws in rails. The methodology is based on a hybrid non-contact system that uses a pulsed laser for generating waves and multiple air-coupled sensors for detecting waves. The remote sensors are positioned as far away as 76 mm (3”) from the top of rail head. Signal processing based on the Continuous Wavelet Transform is used to characterize the time-frequency content of the propagating waves. Features extracted after Discrete Wavelet processing of the wave signals result in a damage index that is robust with respect to noise and is related to the crack depth; the method allows for fast inspection with the potential for quantifying the extent of the flaw. It is demonstrated that the adopted setup allows for the detection of small cracks, as shallow as 1 mm in depth. It is also shown that the ultrasonic wave features considered in this study are directly related to the reduction of the rail head cross-sectional area caused by a transverse crack.

From various studies by different investigators it has been now well established that a number of cylindrical guided wave modes are sensitive to the pipe wall defects. Several investigations by these authors and other researchers showed that the strengths of the guided waves propagating through a pipe that is placed in air are reduced when the pipe wall defects are encountered. This reduction is expected because the pipe wall defects (gouge, dent, removed metal due to corrosion etc.) alter the pipe geometry, hampering the free propagation of guided wave modes. When water flows through the pipes, the guided wave technique becomes more challenging because the flowing water absorbs part of the propagating acoustic energy. Flowing water may also induce some standing modes. The propagating cylindrical guided wave modes become leaky modes in presence of the flowing water, in other words energy leaks into water. Therefore, the energy detected by a receiver, placed at a large distance from the transmitter, is reduced even for a defect free pipe. Further reduction in the signal strength occurs in presence of defects.

This paper is concerned with the detection of low velocity impact and the associated internal damage in composite structures using Lamb waves. Impact tests are carried out on a cross ply graphite epoxy plate using an instrumented impact testing system. The contact force and the surface motion caused by the impact load are recorded at several points on the plate surface away from the impact location and are analyzed based on theoretical simulations. The Lamb waves generated by the impact load and internal damage to the plate caused by it are shown to be highly effective tools for damage detection in laboratory specimens. Ultrasonic and impact tests are also conducted on a stiffened, woven composite panel in an effort to examine the propagation characteristics of ultrasonic waves in realistic composite structural components. Preliminary analysis of the recorded waveforms indicates that Lamb waves can be used to interrogate relatively large composite structures.

This research proposes a technique to decompose a transient, multi-mode, Lamb wave, time-domain signal into its individual Lamb wave modes. The technique is derived for a Lamb wave signal consisting of two Lamb wave modes (double-mode Lamb wave signal). The extension to the general multi-mode signal is straightforward, but requires additional computations. The proposed technique assumes knowledge of the dispersion characteristics of Lamb waves, which can be theoretically calculated or obtained by other signal processing techniques. The proposed technique is verified for simulated (by eigen-expansion) signals to demonstrate the method's accuracy in a well-controlled environment. The use of eigen-expansion signals for the simulation allows for the calculation of the total response, as a combination of responses due to all existing Lamb modes. The comparison between the decomposed and simulated signals shows good agreement and demonstrates the validity of the proposed technique. The paper concludes with a discussion of the extension of this technique to the more general multimode, Lamb wave signal in leaky conditions, and its use in attenuation calculations.

We describe and compare two novel methods of detecting ultrasonic Lamb waves used for damage detection and location, and then go on to compare their characteristics with those of more conventional PZT transducers. The two methods are measurements of the change in polarization state of the light in an optical fibre and the changes in reflected power from a fibre Bragg grating. Since different transducers measure different properties of Lamb waves by different methods, their relative sensitivities to the S₀ and A₀ modes can also vary. This can be of interest because, for instance, the A₀ mode is more sensitive to the presence of delaminations in a sheet due to the larger shear strain component that this mode contains. We also describe the directional properties of the sensors and demonstrate the ways in which these can be used to advantage in the detection and location of damage.

Analysis of Wave propagation in plates with sinusoidal boundaries has been considered in this paper. Guided elastic wave in a two-dimensional periodically corrugated plate is studied analytically. The plate material is considered as homogeneous, isotropic and linearly elastic. In a periodically corrugated wave-guide all possible spectral order of wave numbers are considered. The dispersion equation is obtained by applying the traction free boundary conditions. Solution of the dispersion equation includes both symmetric and anti-symmetric mode. Non-propagating 'stop bands' and propagating 'pass bands' are investigated.

Three dimensional wave propagation characteristics in laminated plates are studied considering the anisotropic and viscoelastic properties of fiber reinforced composite material. A Rayleigh-Ritz based stiffness method is used to discretize the plate in the vertical direction to determine propagation characteristics (wave number, phase velocity, group velocity) and mode shapes for a plane wave front. For 3-dimesional cases, wave propagation problem is decomposed into a series of two-dimensional plane wave problems with three displacements coupled. Double Fourier transform integral transformations are used to get the governing equation in a transformed wave number domain. Steady state elastodynamic Green's functions for the laminated composite plates are constructed through summing the contribution of all two-dimensional problems and the application of modal summation technique. Numerical integration of double infinite integrals is performed by summations over a finite range. The wave propagation characteristics for a 16-layer unidirectional fibre reinforced laminated composite plate show the orthotropic nature of the plate reflected in its 3-D wave propagation characteristics. It is also seen that the Green's functions for 3D waves are very different from those for plane strain 2D waves. Furthermore, the direction of propagation has a significant effect on the Green's function for surface displacements.

In this paper we will be describing noise reduction techniques for new type of wireless sensor for use in monitoring strain in civil structures. This strain sensor is a passive sensor that can be embedded and then interrogated through an attached antenna and hence has the advantage that is requires no permanent electrical or optical connection. The sensor is a metal coaxial cylindrical cavity embedded or attached to the object in which strain is to be measured. As the structure changes dimension in response to applied forces the electromagnetic cavity also changes dimension and hence its resonant frequency also changes. The sensor can then be interrogated via the antenna and the resonant frequency of the electromagnetic cavity determined. Once the resonance frequency is determined it can be used to calculate the strain in the structure. We will present results on the use of time domain gating to reduce environmental and instrumental noise. We will also present results using peak fitting techniques that make optimum use of signals to locate the resonance. These noise reduction techniques make the use of this type of sensor applicable in a wider range of environments. We have demonstrated a strain resolution of 8 microstrain in a noisy environment by using peak fitting techniques. These techniques were much less sensitive to environmental sources of noise than FM modulation and phase sensitive detection.

The dynamic response of offshore oil platform under seismic excitation is the coupling response of liquid and solid vibration. In recent years, the computation of dynamic responses and design of offshore platform have attracted the attention of many researchers. This paper presents a shaking table test of offshore oil platform model scaled down an actual one. Fiber Bragg grating is a new measurement technology with its superior ability of explosion proof, immunity to electromagnetic interference and high accuracy. In this paper, FBG sensors are used to monitor the dynamic response of offshore oil platform model on line. Ten FBG sensors are installed, one of which is temperature sensor, two of which are acceleration sensors and the others of which are strain sensors. One FBG accelerometer is placed on the surface of the shaking table; and another one is placed on the top surface of the offshore oil platform model. FBG strain sensors are placed on the key parts of the platform model. Some traditional strain gauges are installed in parallel with FBG strain sensors. In this experiment, electromagnetic interference of strain gauge is very big, while the FBG strain sensor has not this phenomenon. Based on the experiments results, it can be concluded that FBG sensor is superior to strain gauge.

A modified technique to measure acoustic nonlinearity in fatigued components is proposed in this paper. As opposed to the conventional technique to measure acoustic nonlinearity, the proposed technique eliminates the couplant effects between the transducers and the specimen. The proposed technique is compared with the conventional technique by performing nonlinearity measurements on a fatigued aluminum alloy specimen and calculating the coefficient of variation (COV) of the nonlinearity parameter. Preliminary results show that the COV of the nonlinearity parameter obtained using the modified technique is approximately half of that obtained using conventional technique. It is therefore felt that the proposed technique will help to reduce the variability in the nonlinearity measurements in fatigued components.

An information-theoretic approach is described for detecting damage-induced nonlinearities in structures. Both the time-delayed mutual information and time-delayed transfer entropy are presented as methods for computing the amount of information transported between points on a structure. By comparing these measures to "linearized" surrogate data sets, the presence and degree of nonlinearity in a system may be deduced. For a linear, five-degree-of-freedom system both mutual information and transfer entropy are derived. An algorithm is then described for computing both quantities from time-series data and is shown to be in agreement with theory. The approach successfully deduces the amount of damage to the structure even in the presence of simulated temperature fluctuations. We then demonstrate the approach to be effective in detecting varying levels of impact damage in a thick composite plate structure.

Prognosis integrates physics based models of damage, noninvasive real time interrogation techniques and data/signature analysis to predict future performance. One of the significant capabilities essential for the prognosis methodology to work is to develop analysis methods for multiple and interacting damage and failure mechanisms. In this paper the proposed methodology has been demonstrated with the help of a nonlinear multi-degree-of-freedom system which exhibits multiple phenomenological damage phenomenon. It is shown that the participation factors for the bifurcating damage modes can be used to characterize the damage mechanism.

A novel method of structural damage detection, aimed at monitoring the state of a structure based on measured time series data, is presented for the analysis and interpretation of underwater explosion (UNDEX) test data. This method extracts sets of simple basis function components, known as Intrinsic Mode Functions, and tracks structural damage based on a fundamental relationship connecting the instantaneous phases of measured structural waveforms to the structural mass and stiffness parameters. The data were obtained during a recently conducted test series in which shock isolators, mounted on an adjustable deck fixture, are used to mitigate the shock impact for equipment cabinets. The state of the isolation system is then evaluated, and possible structural damage is identified based on instantaneous attributes such as the frequency of structural response and the phase of structural waveforms. The studies presented here show that this method, intrinsically suited to non-linear systems and non-stationary processes, produces valuable insight into the state of a structure during an extreme loading event. It can be used to assess structural conditions directly from recorded UNDEX data.

Non-linear nondestructive testing is different from linear acoustic in that it correlates the presence and characteristics of a defect with acoustical signals whose frequencies differ from the frequencies of the emitted probe signal. The difference in frequencies between the probe signal and the resulting frequencies is due to a nonlinear transformation of the probe signal as it passes through a defect. Under acoustic interrogation due to longitudinal waves, as the compression phase passes the defect the two sides of the interface are in direct contact and the contact area increases. Similarly, the tensile phase passes through the defect, the two sides separate and the contact area decreases, thereby modulating the signal amplitude. The contact area depends on the roughness of the surface and on the magnitude of the cohesive forces that arise from the small crack openings. Such cohesive forces may be attributed to aggregate interlock (in plain concrete), fiber bridging (in fiber reinforced concrete) or both. In this paper, the frequency shifts of the probe elastic wave will be analytically related to the roughness and varying cohesive forces of the crack-like defect.

The embedded ultrasonic structural radar (EUSR) algorithm was developed by using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. EUSR has been verified to be effective for detecting a single crack either at a broadside or at an offside position. In this research, advanced signal processing techniques were included to enhance inspection image quality and detect multiple damage. The signal processing methods include discrete wavelet transform for signal denoising, short-time Fourier transform and continuous wavelet transform for time-frequency analysis, continuous wavelet transform for frequency filtering, and Hilbert transform for envelope extraction. All these signal processing modules were implemented by developing a graphical user-friendly interface program in LabVIEW. The paper starts with an introduction of embedded ultrasonic structural radar algorithm, followed with the theoretical aspect of the phased array signal processing method. Then, the mathematical algorithms for advanced signal processing are introduced. In the end, laboratory experimental results are presented to show how efficiently the improved EUSR works. The results are analyzed and EUSR is concluded to have been improved by using the advanced signal processing techniques. The improvements include: 1) EUSR is able to provide better image of the specimen under monitoring; 2) it is able to detect multi-damage such as several cracks; 3) it is able to identify different damage types.

This paper presents recent development and current capabilities of a dynamics-based Boundary Effect Evaluation Method (BEEM) for damage inspection of large structures. Damage introduces new boundaries to a structure, and influences of boundaries on steady-state high-frequency dynamic response are localized effects. The BEEM is a signal processing method that takes advantage of these localized effects to perform area-by-area extraction of damage-induced boundary effects from steady-state Operational Deflection Shapes (ODSs) to reveal damage locations. Steady-state ODSs of a structure can be measured using any full-field measurement tool, and the BEEM decomposes an ODS into central and boundary solutions using a sliding-window least-squares data-fitting technique. Numerical and experimental results show that boundary solutions are excellent damage indicators because of Gibbs' phenomenon, and the central solutions can be used to easily identify actual structural boundary conditions. Except experimental ODSs of the damaged structure under inspection the method requires no model or historical data for comparison. Experimental results of many one- and two-dimensional structures validates the capabilities of BEEM in detecting and estimating multiple small defects in large structures.

Automatic magnetic particle inspection based vision system using CCD camera is a new development of magnetic particle inspection. A vision system using linear CCD cameras in semiautomatic fluorescent magnetic particle inspection of axles of railway wheelsets is presented in this paper. The system includes four linear CCD cameras, a PCI data acquisition & logic control card, and an industrial computer. The unique characteristic of striation induced by UV light flicker in scanning image acquired by linear CCD camera are investigated, and some digital image processing methods for images of magnetic particle indications are designed to identify the cracks, including image pre-processing using wavelet, edge detection based connected region using Candy operator and double thresholds. The experimental results show that the system can detect the article cracks effectively, and may improve inspection quality highly and increase productivity practically.

In this study, the detection of delamination flaws in laminated composite plates is carried out using artificial neural networks (ANN) in a two-level cascading manner. The three damage parameters detected using ANN are the size of the delamination, its vertical location (across the plate thickness) and horizontal location (along the plate surface). The numerical data in the form of frequency domain Green's function for the displacement response on the surface of the plate containing the delamination flaw is generated first using an available numerical method. Pseudo-experimental data is generated adding artificial random noise into the numerical data. At the first level, a counterpropagation neural network (CPN) is trained for qualitatively classifying the damage parameters using the numerical data generated above. Next, a second level back-propagation network (BPN) is used for each subclass to quantify the damage parameters. An overlapping data set is used for the training of each class of the second level network. As a result, any pattern misclassified by the CPN due to its closeness to the boundary of any two classes is still quantified correctly. By feeding pseudo-experimental data to the trained networks, it is seen that the classification success rate and noise tolerance level of CPN is excellent. The quantification of damage by the second level BPN is also good. It is possible to stop after the first level if only a qualitative assessment of the damage and its approximate location is required. These cascaded networks show promise in providing a successful delamination damage detection tool.

A structural health monitoring system is developed for continuous online monitoring of delamination initiation and growth in composite structures. Structural health monitoring problems are often cast in the context of a statistical pattern recognition paradigm, in which a damage state of the system is inferred by comparing test data with baseline data. However, subtle signal changes due to damage can often be masked by larger ambient variation of the operational and environmental conditions of an in-service structure. Therefore, it is critical for the development of a robust monitoring system to minimize false-positive indications of damage caused by the undesired operational and environmental variation of the system. The issue of minimizing damage misclassification has been addressed in this paper by developing an instantaneous damage detection system that does not rely on any prior baseline data. The development of the proposed instantaneous damage diagnosis system is based on the concepts of time reversal acoustics and consecutive outlier analysis, and the proposed damage diagnosis system has been tested for detecting delamination in composite plates.

Presented here is the optical characterization and 2D scanning capabilities of an SU-8 based waveguide scanner. Transducing a resonant microcantilever in both the vertical and horizontal direction provides a raster motion useful for imaging when in combination with light source and detector. An application of this design can be in the area of endoscopy where noninvasive instrumentation is desired. MEMS fabricated polymeric devices will allow reduction of the overall size of the system while maintaining the resolution and field-of-view (FOV) of current endoscopes. Our design provides the initial phases for the realization of this system. A waveguide scanner has been fabricated with a 50x100mm cross section and beam length of 2mm. Mode coupling from input to output of the structural design has been determined to be 71.4%. Total power output measured experimentally to be 20%. Preliminary tests have shown 2D imaging with digital processed reconstruction.

In design of partial discharge (PD) diagnostic systems, finding a set of features corresponding to an optimal classification performance (accuracy and reliability) is critical. A diagnostic system designer typically does not have much difficulty to obtain a decent number of features by applying different feature extraction methods on PD measurements. However, the designer often faces challenges in finding a set of features that give optimal classification performance for the given PD diagnosis problem. The primary reasons for that are: a) features cannot be evaluated individually since feature interaction affects classification performance more significantly than features themselves; and b) optimal features cannot be obtained by simply combining all features from different feature extraction methods since there exist redundant and irrelevant features. This paper attempts to address the challenge by introducing feature selection to PD diagnosis. Through an example this paper demonstrates that feature selection can be an effective and efficient approach for systematically finding a small set of features that correspond to an optimal classification performance of PD diagnostic systems.