Hidden damage caused by foreign object impact in a composite structure, if left undetected, can grow and lead to a catastrophic failure of the structure. Detection of impact events and characterization of the degree of damage caused by them, preferably in real time, would be extremely helpful in safe continued operation of composite structures. In this paper, low velocity impact experiments are carried out on AS4/3501-6 [0/90]8S cross-ply graphite epoxy composite plates. An instrumented impact testing system is used to record the contact force and the surface motion at locations away from the impact point. The response of the plate due to localized sources is calculated using a modified laminate theory providing detailed information on the relationship between the impact load and the signals generated by the load. For thin plates, the far-field response is dominated by plate guided Lamb waves. It is shown that the occurrence of an impact loading can be easily detected from the recorded signals. Delamination damage, if any, can also be determined through careful analysis of the recorded waveforms. Practical applications of the technique in structural health monitoring will require careful investigation and elimination of environmental noise.

A recently developed Green's function and Hybrid method to analyze wave scattering problem in laminated composite plate have been employed and extended to include material damping and calculate the time domain response beyond the crack zone. Analysis has been carried out for through depth vertical crack only. Attention has been focused on plane-strain motion. Arbitrary values of damping factor have been introduced for numerical analysis to check the decaying phenomenon of the Lamb wave modes in layered composite plate. Experimental verification of the applicability of the simulation with the numerical analysis has also been carried out. It has been found that numerical analysis results are in good agreement with the experimental results.

The health state of a structure depends on both the degradation of its mechanical properties during its life cycle (ageing) and to the presence of localised defects such as corrosion, cracks, or delaminations. We already described1-3 a method enabling the recovery of both kinds of information, and based upon a piezoelectric disk attached to the plate-like composite structure. The element dimensions are chosen in order to uncouple the frequency ranges of its thickness and radial vibration modes. The thickness mode is then exploited to monitor the homogeneous ageing of the structure through electrical impedance measurement. Whereas the radial vibrations, are used to launch and detect Lamb waves, which are known to propagate over long distances. The present work focuses more particularly on the reliability of the technique. The definition of a very simple "damage index" computed from the experimental data is proposed and its high sensitivity is discussed. A finite element model of real and hence complex damages is used in order to understand the interaction of the selected Lamb waves with the defects. A good agreement between the experimental observations and the simulations is found. The sensitivity of a given guided mode to a given type of damage can then be understood and then a predictive implementation of the experimental device can be envisaged.

Advanced fiber-reinforced polymer composite (FRP) has been increasingly used in bridge deck to replace concrete or steel. A FRP bridge deck can be designed to meet AASHTO HS-25 load requirements. FRP decks have many advantages over the conventional reinforced concrete or steel decks owing to their lightweight, high strength and corrosion resistance. However, such new deck system requires extensive monitoring to ensure its designed performance before its widespread acceptance by the bridge community. For inspection and evaluation purpose, a proper monitoring system consisting of various kinds of sensors installed in the FRP deck is critical. This paper provides a framework for designing an efficient monitoring system. The strategic sensor locations are identified based on the stress analysis of the FRP deck.

The behavior of the wave field produced in a thin unidirectional graphite/epoxy composite plate by a dynamic point load is studied using an approximate shear deformation plate theory (S.D.P.T) and a finite element analysis (F.E.A). Comparisons are made for propagation at 0°, 45°, and 90° directions relative to the fibers showing excellent agreement between the two model approaches. The approximate method is then used to calculate the response of a composite plate as well as of an aluminum plate to a uniform dynamic surface load distributed in a circular region. A periodic reversal in the phase of the signal with propagation distance is observed. It is found that this is caused by the strong dispersion of the first antisymmetric waves at low frequencies. For clarification, the steepest descent method is applied to obtain a closed form analytical expression for the far field response in the aluminum plate for a Dirac delta source. It is shown that the waveform carries a singularity that reverses its phase at regular intervals. The present work should be helpful in understanding the nature of waveform signals produced by impact loads and in the detection and characterization of impact damage in composite structures.

This paper describes a Lamb-wave scanning method for the detection of notches simulating cracks at rivet holes in thin plates. The approach requires the generation of an ultrasonic S_o-Mode Lamb wave using an incident transmitter excited with a tone burst centered at a near non-dispersive frequency. Area scans are performed on a plate with a hole with a notch to generate times series information which is used to create animations illustrating the wave propagation characteristics. The time series are subject to a sifting process to obtain intrinsic mode functions which contain narrow frequency banded information of the signals. The Hilbert-Huang transform is applied to the intrinsic mode functions which permit the computation of the signal energy as a function of time, proportional to the square of the amplitude of the analytical signal. Animations of the propagation of the Lamb-wave energy illustrate that a potential scanning approach is to acquire time series along a line between the transmitter and the hole, capturing wave scattering from the hole and reflections from the notches. The times of flight and amplitudes of the notch-reflected energy are used to calculate coordinates of the source of the reflections by a geometric approach. The identified coordinates of the reflections outline the extent of the notch at the rivet hole. Results of experiments conducted on thin square plates with a single hole with notches of various sizes compare favorably with the actual notches.

A new method (patent pending) was developed at Varian Medical Systems and OHT Inc. for non-destructive evaluation of printed circuit boards (PCB’s). The electrostatic imager uses a TFT array, where each pixel has a small storage capacitor connected to it and a separate top electrode. An insulator layer covers these top electrodes. When we place a PCB on top of this insulator layer and activate a trace of the PCB by an electrical pulse, that trace induces charges in all of the underlying pixels. By reading out the image of the charges with electronics, similar to ones used for digital x-ray imaging, we can reconstruct the image of the electrical trace. Using the above technique we can test and detect defects in PCB’s such as shorted traces, broken traces, etc. This method is also applicable to test other electrical and electronic circuits and components with electrical pulses. The paper gives a detailed descripton of this new imaging technique illustrated by real applications.

Dry-coupled inspection techniques are very important for applications on components with non-uniform surfaces and for inspections of advanced materials or coatings that are porous or otherwise sensitive to the application of water, gel, or some other ultrasonic couplants. To overcome the problems associated with the liquid coupling medium, a number of polymer films have been developed to transmit the ultrasound through a dry interface. These materials are very flexible so even low pressure loading is sufficient to adapt the films to the irregular inspection surfaces. Several polymer films have been evaluated to develop dry-coupled substrates for transducer modules. The modules will be utilized to detect and characterize fatigue cracks and corrosion spots in the aircraft structures. Ultrasonic properties of the polymer films were measured and compared with the properties of plastic or rubber-like materials commonly used for ultrasonic applications. Experiments have been carried out to analyze propagation of longitudinal and shear waves in the films. Two different types of the ultrasonic modules with the flexible polymer substrates are being developed. The influence of the surface condition on the module performance was evaluated for both types of the modules.

We previously reported on 2"x 2" and 4" x 4" size imagers, direct digital radiography X-ray detectors, based on photoconductive polycrystalline mercuric iodide deposited on a flat panel thin film transistor (TFT) array, as having great potential for use in medical imaging, NDE, and security applications. Recently we successfully upgraded our mercuric iodide deposition technique to 20 cm x 25 cm size, the size required in common NDE and security imaging applications. A TFT array with a pixel pitch of 127 microns was used for this imager. The mercuric iodide direct conversion layers were vacuum deposited onto TFT array by Physical Vapor Deposition (PVD). In addition to successful imager scale up, more sophisticated, non-TFT based detectors were developed in order to improve analysis methods of the mercuric iodide photoconductor. Measurements on mercuric iodide photoconductor were performed using a 36 x 6 electrode array on a 10cm x 10cm substrate (total of 216 measurement points). The array is formed by 36 palladium stripes on the glass substrate, upon which the mercuric iodide is deposited, and 6 palladium stripes that are deposited on top of the mercuric iodide layer. These two sets of electrodes are oriented at 90 degrees to each other to create the measurement matrix. These detectors were evaluated in radiographic mode, continuous fluoroscopic mode and pulsed fluoroscopic mode. Mercuric iodide coatings with thickness ranging between 140 microns and 300 microns were tested using beams with energies between 40 kVp and 100 kVp utilizing exposure ranges typical for both fluoroscopic and radiographic imaging. Diagnostic quality radiographic and fluroscopic images at up to 15 pulses per second were demonstrated. We evaluated the dark current, sensitivity and MTF characteristics. The MTF is determined primarily by the aperture and pitch of the TFT array with Nyquist frequency of ~3.93 mm^-1 (127 micron pixel pitch). The MTF curve of a good quality HgI2 imager is very close to the theoretical sinc function. Image lag characteristics of mercuric iodide appear adequate for fluoroscopic rates.

Recent research on reusable launchers indicates that those vehicles require a more complex design and higher technology performance levels than actual expendable launchers. The need for an advanced Health Monitoring System (HMS) appears then to be unavoidable to assure the concept of reusability at an affordable cost without affecting the overall mission risk. After a brief reminder on mission risk management aspects and then possible ways to reduce the risks inherent to any system operation, the sensor specifications of this advanced integrated HMS are fully deduced from the environmental and operational requirements, according to the NDE sensing technique in review and the corresponding final detection objectives. Some short examples are given all the way long to show what has already been developed and where the most difficult problems remain (including also remote controlled systems like space probe, deep-see submarine,etc.). With the help of an advanced integrated multi-sensor network (hardware) and the use of an expert system (software), damage detection, monitoring and prognosis are performed to deduce the safety state of any subsystem or associated operation. Then the information is used to modify accordingly the mission scenario if imposed to maintain an acceptable level of risk.

The detection of structural damage from the high-frequency local impedance spectra is addressed with a spectral classification approach consisting of features extraction followed by probabilistic neural network pattern recognition. The paper starts with a review of the neural network principles, followed by a presentation of the state of the art in the use of pattern recognition methods for damage detection. The construction and experimentation of a controlled experiment for determining benchmark spectral data with know amounts of damage and inherent statistical variation is presented. Spectra were collected in the 10-40 kHz, 10-150 kHz, and 300-450 kHz for 5 damage situations, each situation containing 5 members, "identical", but slightly different. A features extraction algorithm was used to determine the resonance frequencies and amplitudes contained in these high-frequency spectra. The feature vectors were used as input to a probabilistic neural network. The training was attained using one randomly selected member from each of the 5 damage classes, while the validation was performed on all the remaining members. When features vector had a small size, some misclassifications were observed. Upon increasing the size of the features vector, excellent classification was attained in all cases. Directions for further studies include the study of other frequency bands and different neural network algorithms.

Vehicle system health diagnostics is an area where major improvements have been identified for potential implementation into the design of new reusable launch vehicles in order to reduce life-cycle costs, to increase safety margins, and to improve mission reliability. NASA Ames is leading the effort to advance inspection and health management technologies for thermal protection systems. This paper summarizes a joint effort by NASA Ames and Korteks to develop active "wireless" sensors that can be embedded in the thermal protection system to monitor subsurface temperature histories. These devices are thermocouples integrated with radio-frequency identification circuits to enable non-contact communication of temperature data through aerospace thermal protection materials. Two generations of prototype sensors are discussed. The advanced prototype collects data from three type-k thermocouples attached to a 25-mm square integrated circuit and can communicate through 7 to 10 cm thickness of thermal protection materials.

A new concept of Structural Health Monitoring System for composite materials, (CFRP and GFRP) using electromagnetic properties of the material, has been developed at ONERA (Office National d’Etudes et de Recherches Aerospatiales, France). This concept, based on the detection of local electric conductivity variations and/or local dielectric permittivity variations, has allowed to design a demonstrator having a great sensitivity to detect main defects such as delaminations, fiber breaking, burning and liquid ingress. However, this technique at the present state, does not presently allow to perform quantitative measurements of electric conductivity and dielectric permittivity. In order to remedy to this disadvantage, a numerical simulation with an original method developed at ENS-Cachan (Ecole Normale Superieure de Cachan, France) by D. Placko and N. Liebeaux, has been performed. Various results obtained by simulation are presented discussed and compared with experimental measurements.

Several techniques are known for non-destructive testing of aerospace structures, such as pulse echo, Eddy current, magnetic resonance, etc. Each of these techniques detects some faults but misses others, so it is desirable to combine (fuse) the results of these techniques. Several methods of data fusion are known. To improve the quality of fault detection, we modified the straightforward statistical method as follows: (1) we computed mean and variance iteratively: detected faults are excluded form the computation on the next iteration; (2) we treated the plate's edge and the inside separately; (3) we dismissed measurements in which only one technique detects a fault as possibly erroneous. The resulting method indeed leads to a much better fault detection.

Two health monitoring systems for damage detection in composite structures have been developed. First, a magnetic probe measures the magnetic field reflection during a frequency exploration. The local electrical conductivity of the structure is deduced from the cut-off frequency of the transfer function. Secondly, a probe with piezoelectric elements analyzes the local visco-elastic response of the structure produced at the moment of touching and stressing it. The same piezoceramic elements induces the mechanical solicitation and senses the response signal. The probes are compared in the analysis of damages induced in a coupon of quasi isotropic Carbon-epoxy material by various aggressions: 4 J- and 2 J-impacts inducing delaminations, a local burning by contact with a hot body and a simulated lightning impact by electric spark. Both probes show sensitivities to these various types of damage. For the piezoelectric probe, a "real-time" strategy, based on the processing of spectral power densities of the sensor signals, leads to an automatic measuring system classifying the damages. A software, based on fuzzy logic and implemented on a dedicated micro controller, elaborates the input data in order to realize the material damages classification. Combination the two techniques in a hybrid probe and use of the fuzzy logic procedure to the full signals to classify the structure response in a more subtle and extended way is the starting point of the design of a multisensor tactile probe able to recognize damages for a given material (NDE) or several classes of materials (robotized examinations in hostile environments).

Boeing is currently conducting evaluation testing of the Comparative Vacuum Monitoring (CVMTM) system offered by Structural Monitoring Systems, Ltd (SMS). Initial testing has been conducted by SMS, with further test lab validations to be performed at Boeing in Seattle. Testing has been conducted on dog bone type specimens that have been cut at the center line. A notch was cut at one of the bolt holes and a CVM sensor installed on both sides of the plate. The doublers were added and a single line of 4 bolts along the longitudinal center line were used to attach the doubler plates to the dog bone type specimen. In this way, a high load transfer situation exists between the two halves of the dog bone specimen and the doubler plates. The CVM sensors are slightly over 0.004" (0.1mm) in thickness and are installed directly upon the faying surface of the dog bone specimen. Testing was conducted on an Instron 8501 Servohydraulic testing machine at the Department of Mechanical and Materials Engineering, University of Western Australia. The standard laboratory equipment offered by Structural Monitoring Systems, Ltd was used for crack detection. This equipment included the Kvac (vacuum supply) and the Sim8 (flow meter). The Sim8 was electrically connected to the Instron machine so that as soon as a crack was detected, fatigue loading was halted. The aim of the experiment was for CVM to detect a crack on the faying surface of the specimens at a length of 0.050" ± 0.010". This was accomplished successfully. CVM has been developed on the principle that a small volume maintained at a low vacuum is extremely sensitive to any ingress of air. In addition to the load bearing sensors described above, self-adhesive, elastomeric sensors with fine channels on the adhesive face have been developed. When the sensors have been adhered to the structure under test, these fine channels, and the structure itself, form a manifold of galleries alternately at low vacuum and atmospheric pressure. When a crack develops, it forms a leakage path between the atmospheric and vacuum galleries, producing a measurable change in the vacuum level. The sensors have several advantages over standard test methodologies. As the structure under test effectively becomes part of the sensor, the system measures the physical crack; there can be no false negatives. The elastomeric nature of the sensors allows them to conform to complex curves, and individual sensors can cover relatively large areas. The sensors are transparent; allowing visual inspection to occur without removal. Independent testing by a SMS client has confirmed that eddy current testing can be conducted through CVM sensors of 1mm thickness. The sensitivity of the sensor is governed by the gallery spacing and may be as low as 0.010" (250 μm). Finally, the sensors are also able to detect surface corrosion of aluminium structure. US Navy are monitoring crack growth on an H-53 helicopter with the portable CVM system offered by SMS.

A recently developed semi-analytical technique called DPSM (Distributed Point Source Method) is improved and used to model the ultrasonic field in a fluid generated by an ultrasonic transducer and scattered by a solid plate of finite dimension. Earlier works on the ultrasonic field modeling by the DPSM technique have been limited to homogeneous fluids or nonhomogeneous media with infinite interfaces. This is the first attempt to model the complete ultrasonic field consisting of incident, reflected, transmitted and diffracted fields by a finite scatterer of any shape or size. No closed form analytical solution exists for ultrasonic field computation in presence of a scatterer and an ultrasonic transducer, both of which can have finite dimensions and any shape. Finite element solution for wave propagation analysis is very time consuming; hence, the semi analytical technique used here appears to be the method of choice for solving such practical problems. The paper shows how the scattered field varies as the acoustic properties and dimensions of the scatterer change.

A three dimensional numerical model for elastic wave propagation in multilayered structures is the subject of this paper. The model is based on the Transmission Line Matrix method (TLM) and has a three dimensional acoustic node as a key element. A full description of the numerical method implementation is provided. The numerical analysis was applied to structures with a relatively complicated geometry, similar to the geometries used in non-destructive testing and in medical imaging. The comparison between the experimental and numerical frequency response for a multi-layered cylindrical piece validates the proposed numerical model. An acoustic impedance profile similar to biological tissue was numerically modeled. The comparison between real and numerically generated signals shows good agreement between experiment and numerical analysis.

Recently, a new approach in vibration-based structural health monitoring has been developed utilizing features extracted from concepts in nonlinear dynamics systems theory. The structure is excited with a low-dimensional chaotic input, and the steady-state structural response attractor is reconstructed using a false nearest neighbors algorithm. Certain features have been computed from the attractor such as average local "neighborhood" variance, and these features have been shown in previous works to exceed the damage resolving capability of traditional modal-based features in several computational and experimental studies. In this work, we adopt a similar attractor approach, but we present a feature based on nonlinear predictive models of evolving attractor geometry. This feature has an advantage over previous attractor-based features in that the input excitation need not be monitored. We apply this overall approach to a steel frame model of a multi-story building, where damage is incurred by the loosening of bolted connections between model members.

Development of efficient tools to successfully localize and characterize hidden damage in critical structural components is an important task in the design and construction of structural health monitoring systems in aging as well as new structures. In this paper two methodologies for damage identification and localization will be presented. The first is an automatic numerical scheme using a state space system identification approach and the second is based on certain damage correlation indices associated with changes in the frequency response of the structure in presence of flaws. In each case, the structure is to be instrumented with an array of sensors to record its dynamic response including vibration and wave propagation effects. To determine the type and location of an unknown defect, the sensor data detected is used to identify a new system, which then is compared to a database of state-space models to find the nearest match. The second method deals with the definition of a set of damage correlation indices obtained from the frequency response analysis of the structure. Two types of indices have been considered. The first uses the correlation between the responses of the defect free and damaged structure at the same point, and the second uses correlation at two different points. The potential application of the general approach in developing health monitoring systems in defects-critical structures is discussed.

Vibration analysis for non-destructive evaluation of large-scale civil engineering structures often rely on ambient vibrations as excitation sources. In this case, the input force is typically not available for establishing the transfer functions for vibration analyses. Conventional technologies dealing with random vibration signals, such as correlation analysis and/or random decrement method, may yield less accurate results when the signal-to-noise ratio of the response measurement is not sufficiently high. In this paper, a method called lag-superposition is introduced that provides a better response spectrum and more accurate results with reasonable computation speed. Formulations of Single-Degree-of-Freedom (SDOF) and Multi-Degree-of-Freedom (MDOF) approaches are presented and verified by experimental tests and numerical examples. Comparisons with other methods are also made.

In this paper, study on a new 0-3 type cement-based PZT (Lead Zirconate Titanate) composities is presented. Using a normal mixing and compacting method, up to 50vol% PZT ceramic powder could be incorporated into cement-based composites. The behaviors of the composites under different polarizing conditions are investigated. And the piezoelectric properties of cement-based PZT composites are evaluated both theoretically and experimentally. Moreoever, the impedence spectrum of composites is studied to approve the electromechanical coupling behavior. It shows that cement-based PZT composities have some advantage to the polyer-based PZT composites. There is good potential for application of 0-3 type cement-based piezoelectric composites in civil engineering.

Internet technologies are increasingly facilitating real-time monitoring of Bridges and Highways. The advances in wireless communications for instance, are allowing practical deployments for large extended systems. Sensor data, including video signals, can be used for long-term condition assessment, traffic-load regulation, emergency response, and seismic safety applications. Computer-based automated signal-analysis algorithms routinely process the incoming data and determine anomalies based on pre-defined response thresholds and more involved signal analysis techniques. Upon authentication, appropriate action may be authorized for maintenance, early warning, and/or emergency response. In such a strategy, data from thousands of sensors can be analyzed with near real-time and long-term assessment and decision-making implications. Addressing the above, a flexible and scalable (e.g., for an entire Highway system, or portfolio of Networked Civil Infrastructure) software architecture/framework is being developed and implemented. This framework will network and integrate real-time heterogeneous sensor data, database and archiving systems, computer vision, data analysis and interpretation, physics-based numerical simulation of complex structural systems, visualization, reliability & risk analysis, and rational statistical decision-making procedures. Thus, within this framework, data is converted into information, information into knowledge, and knowledge into decision at the end of the pipeline. Such a decision-support system contributes to the vitality of our economy, as rehabilitation, renewal, replacement, and/or maintenance of this infrastructure are estimated to require expenditures in the Trillion-dollar range nationwide, including issues of Homeland security and natural disaster mitigation. A pilot website (http://bridge.ucsd.edu/compositedeck.html) currently depicts some basic elements of the envisioned integrated health monitoring analysis framework.

Experimental work performed on several full-scale stay-cable models as well as on RAMA IX Bridge in Bangkok has confirmed that the application of magnetic flux leakage (MFL) methods is a viable approach to the non-destructive evaluation of large diameter steel cables. Such method allows for a high sensitivity and high-resolution detection of fractured wires in stay cable systems. So far, the information obtained from the recorded data (intensity of the MFL on the surface of a cable) was limited to the accurate position of detected flaws along the axis of the cable and a qualitative indication of the position of the flaws within the cross-section. The ability to accurately determine the position of flawed wires within the cross-section of a cable is especially useful in the case of multi-strand systems, in which individual strands can be replaced if damaged. Such information can be obtained by computation with finite element models or sophisticated dipole approximations. An alternative to such computing intensive approach, based on a simple mathematical model of the MFL function is proposed in this work. The function is used for a non-linear fit of the measured data. The method has been tested successfully on simulated and measured data.

A structural parametric identification strategy based on neural networks algorithms using dynamic macro-strain measurements in time domain from a long-gage strain sensor by fiber optic sensing technique such as Fiber Bragg Grating (FBG) sensor is developed. An array of long-gage sensors is bounded on the structure to measure reliably and accurately macro-strains. By the proposed methodology, the structural parameter of stiffness can be identified. A beam model with known mass distribution is considered as an object structure. Without any eigenvalue analysis or optimization computation, the structural parameter of stiffness can be identified. First an emulator neural network is presented to identify the beam structure in current state. Free vibration macro-strain responses of the beam structure are used to train the emulator neural network. The trained emulator neural network can be used to forecast the free vibration macro-strain response of the beam structure with enough precision and decide the difference between the free vibration macro-strain responses of other assumed structure with different structural parameters and those of the original beam structure. The root mean square (RMS) error vector is presented to evaluate the difference. Subsequently, corresponding to each assumed structure with different structural parameters, the RMS error vector can be calculated. By using the training data set composed of the structural parameters and RMS error vector, a parametric evaluation neural network is trained. A beam structure is considered as an existing structure, based on the trained parametric evaluation neural network, the stiffness of the beam structure can be forecast. It is shown that the parametric identification strategy using macro-strain measurement from long-gage sensors has the potential of being a practical tool for a health monitoring methodology applied to civil engineering structures.

The committee technique for neural networks has been widely used for pattern recognitions in speech and vision studies. In this study, the committee technique is applied to damage estimation of structures for the purpose of structural health monitoring. The input to the neural networks consists of the modal parameters, and the output is composed of the element-level damage indices. Multiple neural networks are constructed and each individual neural networks is trained independently with different initial synaptic weights. Then, the estimated damage indices from different neural networks are averaged. Several committee methods were investigated and used to estimate the element-level damage locations and severities. The validity of the committee technique for damage estimation was examined on a frame structure through numerical simulation. Then experiments were carried out on a bridge model with a composite cross section subjected to vehicle loadings. It has been found that the estimated damage indices improve significantly by employing the committee technique.

Lower limb complications associated with diabetes include the development of plantar ulcers that can lead to infection and subsequent amputation. While it is known from force plate analyses that there are medial/lateral and anterior/posterior shear components of the ground reaction force, there is little known about the actual distribution of this force during daily activities, nor about the role that shear plays in causing plantar ulceration. Furthermore, one critical reason why these data have not been obtained previously is the lack of a validated, widely used, commercially available shear sensor, in part because of the various technical issues associated with shear measurement. Here we have developed novel means of tranducing plantar shear and pressure stress via a new microfabricated optical system. The pressure/shear sensor consists of an array of optical waveguides lying in perpendicular rows and columns separated by elastomeric pads. A map of pressure and shear stress is constructed based on observed macro bending through the intensity attenuation from the physical deformation of two adjacent perpendicular optical waveguides. The uniqueness of the sensor is in its batch fabrication process, which involves injection molding and embossing techniques with Polydimethylsiloxane (PDMS) as the optical medium. Here we present the preliminary results of the prototype. The sensor has been shown to have low noise and responds linearly to applied loads. The smallest detectable force on each sensor element based on the current setup is ~0.1 N. The smallest area we have resolved in our mesh sensor is currently 950x950μm²

The interaction between ultrasound and biological tissues has been the subject of a number of investigators for nearly half a century and the number of applications of high intensity, focused ultrasound for therapeutic purposes continues to grow. This paper is motivated by possible medical applications of focused ultrasound in minimally invasive treatment of a variety of musculoskeletal disorders that are responsive to thermal treatment. The mechanical and thermal effects in a subject’s body induced by high-frequency ultrasound are simulated using PZFlex, a finite element based program. The FEM model described in this report is of a transverse section of the body at the level of the second lumbar vertebra (L2) extracted from a CT image. In order to protect the nerves inside the spinal canal as well as to obtain an effective heating result at the focal region within the intervertebral disk, a suitable orientation of axis of the focused ultrasound lens have to be determined in advance. The pressure, energy loss distribution and temperature distribution are investigated in this paper with the different orientations of the axis and different transverse diameter of the spherical ultrasound lens. Since nonlinear effects are expected to be important in the therapeutic application in some literatures, this paper also demonstrates the effects of nonlinearities on the pressure and temperature distribution induced by focused ultrasound in a two dimensional model. Finally, a comparison of the results between linear and nonlinear cases is reported.

It has been reported that a mechanical scanning reflection acoustic microscope (hereinafter called simply "SAM"), using high frequency ultrasonic tone-burst waves, can form a horizontal cross-sectional image (i.e., c-scan image) showing a highly resolved cellular structure of biological tissue. However, the tissue prepared for the SAM has been mostly a thinly sectioned specimen. In this study, the SAM images of specimens thickly sectioned from the tissue were analyzed. Optical and scanning acoustic microscopies were used to evaluate tissues of human small intestine and esophagus. For preparing thin specimens, the tissue was embedded in paraffin, and substantially sectioned at 5-10μm by the microtome. For optical microscopy, the tissue was stained with hematoxylin and eosin, and affixed onto glass substrates. For scanning acoustic microscopy, two types of specimens were prepared: thinly sectioned specimens affixed on the glass substrate, wherein the specimens were deparaffinized in xylene, but not stained, and thickely sectioned specimens. Images of the thick specimens obtained with frequency at 200 MHz revealed cellular structures. The morphology was very similar to that seen in the thinly sectioned specimens with optical and scanning acoustic microscopy. In addition, scanning electron microscopy was used to compare the images of biological tissue. An acoustic lens with frequency at 200 MHz permitted the imaging of surface and/or subsurface of microstructures in the thick sections of small intestine and esophagus.

Flexible medical endoscopes currently used in medicine have many problems and a fundamental tradeoffs. Either resolution or field of view is sacrificed when the scope diameter is less than 3mm, since the minimum pixel size is usually at least 4 microns in a pixel-array such as a camera or fiber bundle. Previous work has shown the design of a micromachined cantilever beam able to realize a 100μm wide, one dimension scanning pattern. First mode resonances of the cantilever scanner are found between 16-52 kHz with response amplitudes ranging from 62.5 to 420 μm. Since cantilever waveguides with resonant frequencies above 20 kHz are potentially suitable for video rate scanning, these devices may be used for image acquisition and display. Described in this work is an alternative method of design for a micro-optical scanning endoscope. The endoscope consists of an optical waveguide microfabricated using SU-8 photoresist. SU-8 is a high contrast, negative tone, chemically amplified, epoxy based photoresist chosen for its high aspect ratio (~15:1) for imaging near vertical sidewalls. With the use of SU-8, we were able to fabricate a much larger waveguide (~85 μm) as compared to the previous silicon oxide method (~3 μm) An overall larger device makes coupling a fiber into the waveguide much easier and increases the amount of light coupled into the cantilever beams. The neagactively toned epoxy resin based SU-8 also increases the device durability and simplifies the fabrication process.

Noninvasive diagnosis in medicine has shown considerable attention in recent years. Several methods are already available for imaging the biological tissue like X-ray computerized tomography, magentic resonance imaging and ultrasound imaging et c. But each of these methods has its own disadvantages. Optical tomography which uses NIR light is one of the emerging methods in teh field of medical imaging because it is non-invasive in nature. The only problem that occurs in using light for imaging the tissue is that it is highly scattered inside tissue, so the propagation of light in tissue is not confined to straight lines as is the case with X-ray tomography. Therefore the need arises to understand the behaviour of propagation of light in tissue. There are several methods for light interaction with tissue. Monte Carlo method is one of these methods which is a simple technique for simulation of light through tissue. The only problem faced with Monte Carlo simulation is its high computational time. Once the data is obtained using Monte Carlo simulation, it need to be inverted to obtain the reconstruction of tissue image. There are standard methods of reconstruction like algebraic reconstruction method, filtered backprojection method etc. But these methods can not be used as such in the case when light is used as probing radiations because it is highly scattered inside the tissue. The standard filtered backprojection method has been modified so that the zigzag path of photons is taken into consideration while back projecting the data. This is achieved by dividing the tissue domain in a square grid and storing the average path traversed in each grid element. It has been observed that the reconstruction obtained using this modification is much better than the result in case of standard filtered backprojection method.

In the current work, an algorithm based on wavelet transformations is used to detect damage prior to the degradation of structural parameters of plates. Plates are of interest because they are basic building blocks for many structures, such as naval ships. Damage to the connecting joints and in the form of through thickness cracks, along with material and temperature variations are included in the analysis. Dynamic loading conditions consisting of impulse and chaotic oscillations are examined. The wavelet algorithm is applied to sensor data in the form of time histories (e.g. strain). These histories are either measured experimentally or generated via finite element analysis. Sensitivity, robustness, and potential uses of this wavelet algorithm for damage detection are discussed.

This paper describes results from an investigation into weld line unzipping. The experiments use a series of steel plates (762 x 408 x 3.17 mm) instrumented with five fiber Bragg grating strain gauges. We rely on tuned chaotic excitation using a Lorenz oscillator to maintain a low dimension system suitable for chaotic attractor property analysis. Weld unzipping is simulated by leaving gaps in a weld line which start at one edge of the plate and extend for 34 or 74 mm (8 or 18% of the plate width). Two speeds of the Lorenz oscillator are used for excitation. These correspond to positive Lyapunov exponents of 5 and 10 and provide insight into our ability to control the dimensionality of the system. Strain data from the sensors are cast into attractors and analyzed for changes using a feature called nonlinear prediction error. The nonlinear prediction error results demonstrate that the LE=5 excitation barely excites any structure dynamics while the LE=10 excitation clearly excites the first LE of the structure. At the 95% confidence limit with LE=10 excitation three of the five sensors can distinguish all three damage cases with the other two sensors able to separate damaged from undamaged. At the 95% confidence limit with LE= 5, only one sensor was able to distinguish damaged from undamaged and no sensors could distinguish the two damage cases.

In past work, we have presented a methodology for vibration based damage detection derived from the characterization of changes in the geometric properties of the time domain response of a structure. In brief, input forcing signals and output response signals can be transformed into state space geometrical representations. When allowed to evolve to a steady state, the geometric object is called an attractor. Certain properties of the attractor, such as the local variance of neighborhoods of points or prediction errors between attractors, have been shown to correlate directly with damage. While most inputs will generate some type of attracting geometric object, prescribing a low dimensional input forcing signal helps to maintain a low dimensional output signal which in turn simplifies the calculation of attractor properties. Work to date has incorporated the use of a chaotic input forcing signal based on its low dimensionality yet useful frequency content. In this work we evaluate various forms of shaped noise as alternative effectively low dimensional inputs. We assess whether the intrinsic properties of the chaotic input leads to better damage detection capabilities than various shaped noise inputs. The experimental structure considered is a thin plate with weld line damage.

Previous studies suggest that optimal port wine stain (PWS) laser treatment parameters require knowledge of skin characteristics such as blood vessel size, depth, and distribution. Effective and rapid imaging modalities are not widely available. In the present study, photothermal tomography (PTT) images of an in vivo hamster window model and human PWS skin were obtained and analyzed. Subtherapeutic laser light pulses at 585 and 600 nm were applied to skin surface and image sequences acquired with an infrared camera. A nonnegatively constrained conjugate gradient algorithm was used to reconstruct a PTT image of the initial temperature distribution immediately following pulsed laser irradiation. Vessel dimensions determined from PTT images of hamster window model skin compared well with those measured directly using video microscopy. PTT images of human PWS skin contained vessels with estimated diameters of 200-250 μm over a 250-320 μm depth range. Use of dual wavelength excitation (DWE) analysis allowed for imaging of shallow vessels.

Infrared (IR) optical fiber have aroused great interest in recent years because of their potential in in-vivo spectroscopy. This potential includes the ability to be flexible, small and to guide IR light in a very large range of wavelengths. Two types - silver halide and chalcogenide - infrared transmitting fibers are investigated in the detection of a malignant tumor. As a test sample for all types of fibers we used a thin section of an entire rat brain with glioblastoma. The fibers were connected with a common infrared microscope. Maps across the whole tissue section with more than 200 spectra were recorded by moving the sample with an XY stage. Data evaluation was performed using fuzzy c-means cluster analysis (FCM). The silver halide fibers provided excellent results. The tumor was clearly discernible from healthy tissue. Chalcogenide fibers are not suitable to distinguish tumor from normal tissue because the fiber has a very low transmittance in the important fingerprint region.

IR spectroscopy provides a new diagnostic tool due to its sensitivity to molecular composition and structure in cells, which accompany transformation from healthy to diseased state. The IR spectrum of a sample is, therefore, a biochemical fingerprint. It has been found that the most significant changes occur in the mid-IR spectral range 3-25 mm. Encouraging results have been reported in the literature on various types of cancers, such as human breast, lung, colon, cervical, and leukemia using FT-IR microspectroscopy. Much progress has also been made by several groups on IR spectral maps and IR imaging with good agreement between the data and the histopathological information. In an attempt to characterize healthy and diseased tissues, infrared microspectroscopy of cervical and colon human tissues was studied using an infrared microscopy. The comparative qualitative and quantitative changes detected using FTIR microspectroscopy are discussed.

Tissue infrared microscopy has been applied in dermatopatholoical assessment of common benign, premalignant, and malignant skin lesions in order to observe processes from benign to malignant transformation and compare them to normal. Various approaches how to develop computerised data processing and to sort out useful information within grouped lesion categories against huge inter- and intra-sample variability included spectral and multivariate data treatment. Spectral data processing was carried out to assign spectral bands in the measured spectra using the classical group frequency approach. A multivariate technique, principal component analysis (PCA), was performed to identify and to confirm the wavenumber values that contributed to most of the variance within 1661 points of the spectrum, to evaluate and maximise the differences in the spectra by reducing the number of variables characterising each patient, pathology category and skin component (epidermis, dermis, the lesion and its adjacent area). The results suggest that there is a common tendancy for the observed spectral features in benign, premalignant and malignant lesions directly related to protein conformations and nucleic acid bases in the 800-1750 cm^-1 region, that was possible to distinguish from normal against a huge background of inter- and intra-sample variability.

Many civil and infrastructures continue to be used despite aging and the associated potential for damage accumulation. Therefore, the ability to monitor the health of these systems is becoming increasingly important. The purpose of this paper is to propose a real-time health monitoring system of cable-stayed bridge and building, based-on non-destructive measurement. And also this paper focuses on the safety assessment for bridge from health monitoring system to accomplish this safety assessment. Using the proposed health monitoring system, it helps structure maintenance and reduces the economic cost of a life-cycle costs. Also it give important data to develop the design and analysis method for cable-stayed bridges and buildings.

A neural networks based modeling of structural parametric identification strategy with the direct use of dynamic measurements in time domain is developed. Without any eigenvalue analysis, the structural parameter of stiffness and Rayleigh damping coefficients can be identified simultaneously. A shear frame structural model with known mass distribution is considered as an object structure. First a reference structure with assumed structural parameters is chosen. The assumed reference structure has the same degree of freedoms and topology with the object structure. An emulator neural network is constructed and trained to identify the reference structure by the use of dynamic measurements under dynamic excitation. The trained emulator neural network can be used to forecast dynamic measurements of the reference structure with enough precision and decide the difference between the dynamic measurements of other assumed structure with different structural parameters and those of the reference structure. The root mean square (RMS) error vector is presented to evaluate the difference. Subsequently, corresponding to each assumed structure with different structural parameters, the RMS error vector can be calculated. By using the training data sets composed of the structural parameters and the corresponding RMS error vector, a parametric evaluation neural network is trained for the purpose of forecasting the structural stiffness and the Rayleigh damping coefficients.

Ion channels are promising biomolecules for sensor applications. They combine high sensitivity with excellent selectivity. Presently the main problem consists in the integration of such ion channels into synthetic matrices but keeping them operative. In this study we report on the development of a microstructured polymer layer as matrix for an ion channel sensor array and an optical method for parallel detection. A thin PMMA layer was prepared by spin coating a gold surface. Small pores with diameter in the range of few micrometers were made by e-beam lithography. FTIR imaging spectroscopy and SPR imaging were used to characterize the quality of microstructured arrays.