This paper is concerned with the detection and characterization of hidden defects in advanced structures before they grow to a critical size. A methodology for automatic damage identification and localization is developed using a combination of vibration and wave propagation data. The structure is assumed to be instrumented with an array of actuators and sensors to excite and record its dynamic response, including vibration and wave propagation effects. A damage index, calculated from the measured dynamical response of the structure in a reference state and the current state, is introduced as a determinant of structural damage. The indices are used to identify low velocity impact damages in composite as well as aluminium plates for different arrangements of the source and the receivers. The potential applications of the approach in developing health monitoring systems in defects-critical structures is discussed.

Since today's aging fleet is intended to far exceed their proposed design life, monitoring the structural integrity of those aircraft has become a priority issue for today's Air Force. One of the most critical structural problems is corrosion. In fact the KC-135 now costs $1.2 billion a year to repair corrosion. In this paper, we plan to show the use of Lamb waves to detect material loss in thin plates representative of aircraft skins. To do this we will use embedded transducers called Piezoelectric Wafer Active Sensor (PWAS) in a pitch-catch configuration. The sensors were placed on a grid pattern. Material loss through corrosion was simulated by removing the material mechanically with an abrasive tool. Thus, simulated corrosion pits of various depths and area coverage were made. Three-count tone burst wave packets were used. The Lamb wave packets were sent in a pitch-catch mode from one transmitter PWAS to the other PWAS in the grid acting as receivers. The Lamb wave mode used in these experiments was A₁, since this was found to be more sensitive to changes due to material loss. At the frequencies considered in our experiments, the A₁ waves are highly dispersive. It was found that, as the Lamb wave travels through simulated corrosion damage, the signal changes. The observed changes were in the signal wavelength (due to change in the dispersive properties of the medium) and in signal amplitude (due to redistribution of energy in the wave packet). This change in signal can be correlated to the magnitude of damage. To achieve this, we have used several approaches: (a) direct correlation between the sent and the received signals; (b) wavelet transform of the signal followed by correlation of the wavelet coefficients time-frequency maps; (c) Hilbert transform of the signal to produce the signal envelope and comparison of the resulting envelope signals (d) neural network correlation between the sent and received signals. It was found that these methods work well together in a complementary way.

This paper summarizes a spin test of an IN100 minidisk that demonstrated advanced fatigue crack growth predictive tools under dwell fatigue and the ability to infer the damage state from state-awareness sensed data. The test was performed at elevated temperature in a partial vacuum and was a major success. The advantages of employing 3D fracture mechanics tools were clearly demonstrated when the prediction using the advanced analysis technique produced a crack growth lifetime 10 times greater than the standard 2D tools and well within a factor of two of the test result. However, when the effect of the partial vacuum was also taken into account, the predictions more closely resembled the test results. Another success was demonstrated when the "blade-tip" time-of-arrival sensors detected deflections of 50 microns and greater at temperature. Using the 3D analysis tools, a transfer function was created that related blade-tip deflection to crack size. The crack size was tracked in near real time for the final 150 cycles. This test represented significant demonstrations of both 3D fracture mechanics tools and state-awareness sensing. Both are advanced technologies that will eventually impact the life management of turbine engines.

This research uses a combination of laser ultrasonics, signal processing and analytical modeling techniques to examine the propagation of transient Lamb waves in absorbing plates -- in particular an isotropic plate with a lossless fluid on one side. The motivation is to develop a non-contact, point source-receiver technique capable of measuring attenuation of Lamb waves in lossy situations in general. The theoretical model enables an understanding of loss mechanisms and enables prediction of attenuation. The laser ultrasonic techniques enable broadband, point source-receiver idealization. The proposed signal processing technique, the short-time Fourier transform, resolves a signal into the time-frequency domain and enables Lamb mode separation and calculation of energy distribution at specific frequency-velocity points on the dispersion curves. The experimental procedure uses a stress-free plate as a reference for system variation and other loss mechanisms. Then, a plate with fluid on one side is tested to validate the signal processing algorithm. There is satisfactory agreement between the attenuation measured and predicted in the frequency range of interest.

In this paper, an efficient and accurate semi-analytical method based on the wavenumber integral representation of the elastodynamic field is described to calculate the surface responses produced by localized dynamic loads in a relatively thick composite plate. Two types of loads are considered: a pencil lead break source located on the surface and a localized shear delamination within the interior of the plate. In the case of the pencil lead break source, the calculated results for the surface motion are compared with those obtained in laboratory experiments on a 4.4 mm thick 32 layered cross-ply graphite/epoxy using high-fidelity broad band transducers. The waveforms consist of both flexural and extensional modes; the amplitude variations of these modes are found to be strongly dependent on their propagation direction. For the delamination source at the mid plane, the results from the exact calculation are compared with those from an approximate laminate theory with shear correction factor and “moment tensor” representation of the source. The results obtained by the two methods are shown to have excellent agreement in the low frequency ranges. Although, the motion due to the delamination is dominated by flexural waves of lower frequency in both thin and thick plates, the presence of extensional waves are observed in thicker laminates. The acoustic emission waveforms from the initiation of a shear delamination source at various interfaces are also calculated. It is found that the amplitude of the flexural modes decreases and that of the extensional modes increases as the source moves farther away from the mid plane.

This paper illustrates an integrated approach for identifying structural damage in an aluminum plate. Piezoelectric (PZT) materials are used to actuate/sense the dynamic response of the structure. Two damage identification techniques are integrated in this study, including Lamb wave propagations and impedance methods. In Lamb wave propagations, one PZT launches an elastic wave through the structure, and responses are measured by an array of PZT sensors. The changes in both wave attenuation and reflection are used to detect and locate the damage. The impedance method monitors the variations in structural mechanical impedance, which is coupled with the electrical impedance of the PZT. Both methods operate in high frequency ranges at which there are measurable changes in structural responses even for incipient damage such as small cracks or loose connections. This paper summarizes two methods used for damage identification, experimental procedures, and additional issues that can be used as a guideline for future investigations.

Adhesively bonded joints between metallic and composite plates are gaining increasing acceptance in safety critical applications such as automotive and aerospace structures. Lamb wave methods have considerable potential for the inspection of adhesive joints and assemblies for two reasons: they do not require direct access to the bond region, and they are much more amenable to rapid scanning than are compression wave techniques. Lamb waves can be excited in one plate of a bonded assembly, propagated across the joint region, and received in the second plate of the assembly. The paper will present a study of the use of guided Lamb waves for disbond detection in adhesively bonded layered media using piezoelectric wafer active sensors (PWAS). The focus is on developing and compare methods for damage and disbond detection in adhesively bonded structures. For far-field detection, propagating Lamb waves will be used in pitch-catch and pulse-echo modes. The pitch-catch method will send Lamb waves across the adhesive joint, while the pulse-echo method will send Lamb waves along the joint line. For near-field detection, high-frequency standing Lamb waves will be used to evaluate the presence of disbond from the changes in the mechanical impedance of the bonded joint. The standing wave approach is achieved with the self-sensing electromechanical impedance method. Both, the propagating and the standing Lamb waves are generated with the same PWAS installation. The combination of far-field and near-field damage detection in the same sensor installation is a unique feature of our work.

This paper deals with the propagation of ultrasonic guided waves in adhesively-bonded lap-shear joints. The topic is relevant to ultrasonic bond inspection in aerospace components. Specifically, the propagation of the lowest-order, antisymmetric a₀ mode through the joint is examined. This mode can be easily generated and detected in the field due to the predominant out-of-plane displacements at the surface of the test piece. An important aspect is the mode conversion at the boundaries between the single-plate adherends and the multilayer overlap. The a₀ strength of transmission is studied for three different bond states in aluminum joints, namely a fully cured adhesive bond, a poorly cured adhesive bond, and a slip bond. Theoretical predictions based on the Global Matrix Method indicate that the dispersive behavior of the guided waves in the multilayer overlap is highly dependent on bond state. Experimental tests of the joints are conducted by a hybrid, broadband laser/air-coupled ultrasonic setup in a through-transmission configuration. This system does not require any wet coupling and it can be moved flexibly across the test piece. The Gabor Wavelet transform is employed to extract energy transmission coefficients in the 100 kHz - 1.4 MHz range for the three different bond states examined. The cross-sectional mode shapes of the guided waves are shown to have a substantial role in the energy transfer through the joint. A rationale for the selection of the a₀ excitation frequencies highly sensitive to bond state will be given.

Wave propagation in structures with irregular boundaries is studied by transforming the plates with irregular surfaces to sinusoidal wave-guides. 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. The analysis is carried out in the wave-number domain for symmetric modes. Non-propagating 'stop bands' and propagating 'pass bands' are investigated.

Many of the structures responsible for the launch, ground turnaround and support operations of the space shuttle are still being used well past their design life. This has led to an increased interest in monitoring these structures in order to decrease the risk of breakdowns or structural failure. One monitoring method which has shown promising results for such applications is the impedance-based structural health monitoring technique. This paper presents results from proof-of-concept tests on the launch pad's orbiter access arm bolted connection, solid rocket booster support post, mobile launch platform heat shield and crawler transporter bearing. These tests showed that the impedance method can provide a permanent structural health monitoring solution to NASA's ground structures. In addition several positive and negative aspects of the impedance method were discovered or highlighted. Modifications for future tests are suggested.

Health monitoring systems set up to assure the safe operation of structures require linking sensors with computational tools able to interpret sensor data in terms of structural performance. Although intensive development continues on innovative sensor systems, there is still considerable uncertainty in deciding on the number of sensors required and their location in order to obtain adequate information on structural behavior. This paper considers the problem of locating sensors on a bridge structure with the aim of maximizing the data information so that structural dynamic behavior can be fully characterised. Four different optimal sensor placement techniques, two based on the maximisation of the Fisher Information Matrix and two on energetic approaches, have been investigated. Mode shape displacements are taken as the measured data set and two comparison criteria were employed. The first was based on the mean square error between the FE model and the cubic spline interpolated mode shapes. The second criterion measured the information content of each sensor location to investigate on the strength of the acquired signals and their ability to withstand the noise pollution keeping intact the information relative to the structure properties. The results highlight that the Effective Independence Driving-Point Residue (EFI-DPR) method provides an effective method for optimal sensor placement to identify vibration characteristics of the studied bridge.

Runway roughness affects primarily ride quality and dynamic wheel loads. The forces applied onto the airport pavement by aircraft vary instantaneously above and blow the static weight, which in turn increase the runway roughness. One method to effectively assess the ride quality of the airport runway is to measure its longitudinal profile and numerical simulate aircraft response performing a takeoff, landing or taxiing on that profile data. In this study the aircraft responses excited as the aircraft accelerates or moves at a constant speed on the runway during takeoff and taxi are computed by using the improved computer program TAXI. This procedure is capable of taking into account both the effects of discrete runway bumps and runway roughness. Thus, sections of significant dynamic response can be determined, and the maintenance and rehabilitation works for airport runways will be conducted.

Experimentation at Wayne State University has lead to the development of a quasi acousto-ultrasonic method that utilizes an acoustic perturbation in the test region to enhance the dispersion of energy in the frequency domain. Analytical modeling has been used to explain this energy redistribution on two crucial levels; harmonic frequency generation, and sideband generation through amplitude modulation. Further refinement in both testing and modeling is planned.

In this paper, guided elastic Lamb wave propagation characteristics in laminated plates are studied using a proper phenomological model for the fiber reinforced composite material. It is well established that ultrasonic waves attenuate in FRP composite material. This is caused by the visco-elastic behavior of the resin ad scattering due to the fiber. The material here is, therefore, numerically modeled using complex material properties. Both the material and frequency-dependent damping for each layer of the laminated plate is incorporated in the formulation. A Rayleigh-Ritz based stiffness method is used to discretize the plate in the vertical direction to determine wave numbers. Furthermore, elasto-dynamic Green functions for both displacement and stress fields in the laminated composite plate are also derived. In this manner, the effect of guided wave attenuation on wave numbers and displacements and stress Green functions are studied. All wave numbers, including those for propagating modes, are complex. However, the relative value of the imaginary part of the wave number of the propagating modes are small, and it is seen that incorporation of damping has an insignificant effect on dispersion characteristics, irrespective of the excitation frequency. However, it significantly affects both displacement and stress fields, especially as the distance from the source increases. This effect is dependent on the excitation frequency. At relative low frequencies, the attenuation of the displacement and stress fields is small. The attenuation increases with excitation frequency, although seemingly the effects on the stress field are relatively less significant than those on the displacement field.

Recently, a new SHM system has been developed at ONERA. This system based on the interaction between an electromagnetic field and a composite structure, allows detecting all types of damages having an influence on the electrical characteristics of the structure such as carbon fiber breaking, organic matrix pyrolysis, liquid ingress... The basic principle of this SHM system, called HELP-Layer (Hybrid ELectromagnetic Performing Layer), consists to induce eddy currents inside the structure and to perform a local measurement of the resulting electric field. All damages inducing a significant variation of the two main electrical parameters (i.e. electrical conductivity and dielectric permittivity), induce a significant variation of the resulting electric field. The sensitivity of this technique depends of the type of damage; as regard to “mechanical” damages (e.g. delaminations, fiber breaking, crack), the sensitivity is comparable to techniques using ultrasonic methods, as regard to other kind of damages (e.g. matrix pyrolysis, liquid ingress...) the electromagnetic method is more sensitive than ultrasonic methods. The analysis of the two resulting components of electric field (i.e. E_x and E_y, the conductivity direction being y) allows to determine the kind of damage (mechanical or other), by resolution of a part of the inverse problem, the direct problem being solved by the DPSM (Distributed Point Source Method) concept.

Many academic and commercial researchers are exploring the design and deployment of wireless sensors that can be used for structural monitoring. The concept of intelligent wireless sensors can be further extended to include actuation capabilities. In this study, the design of a wireless sensing unit that has the capability to command active sensors and actuators is proposed for structural monitoring applications. Active sensors are sensors that can input excitations into a structural system and simultaneously monitor the corresponding system's response. The computational core of the wireless active sensing unit is capable of interrogating response data in real time and can be used to execute embedded damage detection analyses. With high-order vibration modes of structural elements exhibiting greater sensitivity to damage than global structural modes, wireless active sensors can play a major role in a structural health monitoring system because they are capable of exciting high-order modes. A computational framework for analyzing piezoelectric based active sensor signals for indications of structural damage is proposed. For illustration, a simple aluminum plate with piezoelectric active sensors mounted to its surface is used.

Damage detection and prediction is essential for structural health monitoring. Vibration based methods have been used in health monitoring. In this work damage is proposed to be a nonlinear dynamical phenomenon and can be analyzed by utilizing the bifurcation theory. A methodology for predicting failure is proposed which utilizes the concepts of distance to stability boundary as estimated by bifurcation analysis. The proposed methodology is illustrated by developing bifurcation boundary for a two degree of freedom nonlinear mass-spring-damper system. Two damage models are investigated to illustrate the utility the proposed methodology in capturing and estimating the evolution of damage phenomenon.

Conventional finite element approaches for modeling delaminations in laminated composite structures use the Heaviside unit step function at the interfacial nodes in the delaminated zone of the structure to model the possible jumps in the displacement field during “breathing” of the delaminated layers. In quantum mechanics, the Fermi-Dirac distribution applies to Fermion particles whose characteristics are half-integer spins. The present paper uses the Fermi-Dirac distribution function to model a smoother transition in the displacement and the strain fields of the delaminated interfaces during the opening and closing of the delaminated layers under vibratory loads. This paper successfully shows that the Fermi-Dirac distribution function can be used to more accurately model the dynamic effects of delaminations in laminated composite structures. Optimizing the parameters in the Fermi-Dirac distribution function can lead to more accurate modeling of the dynamic and transient behavior of the delaminated zones in laminated composite structures. Further applications of the Fermi-Dirac distribution function in other physics based dynamic models are suggested. This paper also effectively demonstrates how hybrid sensors comprising of out of plane displacement sensors and in plane strain sensors can effectively map a composite structure to detect and locate the delaminated zones. It also shows how simple mode shapes can be used to determine the locations of single and multiple delaminations in laminated composite structures.

This study proposes a semi-model-based method for detecting, locating and quantifying damages that may exist in a structure after a seismic event. The basic concept of the proposed method is to design a monitor for each structural component that needs to be monitored. The monitor is designed based on a residual generator technique and is sensitive only to the damage of the targeted component. The input signals to this monitor are the structural dynamic responses and the excitation. The monitor produces zero or close to zero output when there is no damage in the corresponding component. It produces an obvious nonzero output when the condition of that component has changed. The occurrence and the location of the structural damage can be determined by the display of nonzero output. Furthermore, the severity of the damage can be assessed by using a time-domain system identification technique on the input-output data of the monitor. The proposed method requires some prior knowledge about the structure being monitored. However, as the method can be used to assess and update the structural property of the components, precise modeling of the structure prior to the implementation of the technique is not necessary. A three-story lumped mass shear beam model under a seismic excitation was chosen as a numerical example. Results show that the proposed method can accurately detect, locate and quantify structural damages.

Some advanced aircraft materials or coatings 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, dry-coupled rolling modules were developed at Northwestern University for the transmission of both longitudinal and transverse ultrasonic waves at frequencies up to 10 MHz. Dry-coupled ultrasonic modules contain solid core internal stators and solid or flexible external rotors with the flexible polymer substrates. Two types of the dry-coupled modules are under development. Cylindrical base transducer modules include solid core cylindrical rotors with flexible polymer substrates that rotate around the stators with ultrasonic elements. Dry-coupled modules with elongated bases contain solid core stators and flexible track-like polymer substrates that rotate around the stators as rotors of the modules. The elongated base modules have larger contact interfaces with the inspection surface in comparison with the cylindrical base modules. Some designs of the dry-coupled rolling modules contain several ultrasonic elements with different incident angles or a variable angle unit for rapid adjustments of incident angles. The prototype dry-coupled rolling modules were integrated with the portable ultrasonic inspection systems and tested on a number of Boeing aircraft structures.

A signal decomposition method for extracting boundary effects from an Operational Deflection Shape (ODS) of a structure under harmonic excitation is presented here. It decomposes an ODS into central and boundary solutions using a sliding-window least-squares curve-fitting technique. The obtained boundary solutions can be used to reveal damage locations, and the central solutions can be used to identify boundary conditions. Except an experimental ODS the method requires no model or historical data for comparison. For numerical simulations, exact mode shapes and ODSs of beams with damage are obtained by spectral element analysis. Boundary and central solutions caused by different boundary conditions, different loading conditions, and different damage with or without noise are simulated and characterized. Numerical results show that Gibbs' phenomenon caused by the use of continuous functions to fit ODSs with discontinuous first-, second-, and/or third-order derivatives actually makes boundary solutions excellent damage indicators. Several experiments are performed using a scanning laser vibrometer for sensing and a PZT patch for actuation. The experimental results confirm the feasibility and accuracy of this Boundary Effect Evaluation Method (BEEM) in detecting multiple defects and identifying boundary conditions of beams.

The influences of temperature variations on the use of wave propagation for damage detection are investigated for use with impedance-based structural health monitoring. The equations used to determine the damage based upon a longitudinal wave are presented as derived by Kabeya, et al. Equations are defined in order to determine the damage location in a simulation. Temperature variations are induced, and the resulting errors are presented. A possible application using a realistic temperature differential is proposed. A curve-fit of the modulus of elasticity is implemented to correct damage location error.

Sundry image processing schemes for a high-frequency (1.2 GHz) scanning acoustic microscope that measures amplitude and phase are presented. Particular emphasis is paid to the acquisition of precise in-focus information, like the acoustic reflectivity, of three-dimensional microscopic objects. The brightness of a surface element of any object under observation depends not solely on the reflectivity. It is also affected by the tilt angle of the surface with respect to the axis of the microscope. Vector microscopy with synchronous observation of the phase and amplitude has been employed to determine the tilt from the image in phase contrast and correct the observed brightness in the image in amplitude contrast accordingly. Additionally three-dimensional scanning has been used to determine the maximum intensity obtained for confocal positioning of any surface element. The relevance of such schemes for truly quantitative measurements in biology is demonstrated, with results that have led to the ascertainment of phenotypic plasticity in daphnia (waterfleas) species.

In-service strain monitoring of tires of automobile is quite effective for improving the reliability of tires and Anti-lock Braking System (ABS). Since conventional strain gages have high stiffness and require lead wires, the conventional strain gages are cumbersome for the strain measurements of the tires. In a previous study, the authors proposed a new wireless strain monitoring method that adopts the tire itself as a sensor, with an oscillating circuit. This method is very simple and useful, but it requires a battery to activate the oscillating circuit. In the present study, the previous method for wireless tire monitoring is improved to produce a passive wireless sensor. A specimen made from a commercially available tire is connected to a tuning circuit comprising an inductance and a capacitance as a condenser. The capacitance change of tire causes change of the tuning frequency. This change of the tuned radio wave enables us to measure the applied strain of the specimen wirelessly, without any power supply from outside. This new passive wireless method is applied to a specimen and the static applied strain is measured. As a result, the method is experimentally shown to be effective as a passive wireless strain monitoring of tires.

The objective of this study is to observe the behavior of the living cells after introducing impact, caused by an aluminum bullet shot out from an air gun, onto them via tungsten/polymer plate and culture liquid. An air gun type of apparatus shoots an aluminum bullet, wherein the shape of the bullet is substantially a sphere (diameter: 5 mm), and wherein the velocity of the bullet is controlled by the amount of air used for shooting. The aluminum bullet shot out from the air gun impacts onto the polymer/tungsten plate, located above the living cells grown on the bottom of the container (i.e., thin semi-transparent polymer membrane), which is located on the surface of a 200 kHz Panametrics transducer. The container is supported by a polymer member to prevent movement from shock caused by the bullet impact. The plate generates an acoustic wave (i.e., shock wave) by the mechanical impact (i.e., bullet impact) which is then converted into an electrical signal by the transducer. The amplitude of the electrical signal is measured and monitored by the digital oscilloscope. The transducer is calibrated by hydrophone with its peripheral equipment including computer software. The output voltage from transducer was monitored by the digital oscilloscope. The injury and recovery of the specimen are evaluated by scanned image microscopes. Furthermore, quantitative data showing the injury and recovery of the specimen can be obtained with the electromagnetic measurement.

Structural changes in proteins may result in interactions between proteins themselves or between proteins and other biomolecules, which in turn may introduce deterioration of the health state of the system, might it be biological or biomimetic. The initial structural changes in proteins can not be observed by established methods of material analysis like X-ray diffraction or NMR spectroscopy, because proteins in biological cells have an extremely low abundance and are in the non-crystalline state. An obvious gap exists between sequencing techniques for amino acids and the molecular understanding of the functional properties of a particular protein. Vibrational spectroscopic methods offer the potential of fast and accurate characterization of essential supramolecular properties in the native state of the biomaterial. Imaging techniques recently became available for both FTIR and Raman spectroscopy. Here we report on the utilization of the enormous information content of FTIR and Raman spectra for health monitoring in engineering and medicine.

Phase-sensitive acoustic microscopy (PSAM) is used for investigating bio-soft matter systems constituting the important biopolymer and biomaterial chitosan. Incipient micro-analytic ways for the determination of mechanical properties from the simultaneously obtained amplitude and phase images, allow the coeval estimation of the depth of structures and acoustic velocities, from which the density, stiffness and other elastic parameters may be derived. Chitosan is an important derivative from chitin the major component of the carapace (also examined here) of living species like Daphnia. The results obtained exemplify the unique power of PSAM for revealing essential features and information in biological soft matter.

Breast cancer frequently metastasizes, or spreads, to the bone. Upon colonizing bone tissue, the cancer cells stimulate osteoclasts (cells that break bone down), resulting in large lesions in the bone. It seems that breast cancer cells also affect osteoblasts (cells that build new bone), in addition to osteoclasts. To test this hypothesis, conditioned medium was collected from a bone-metastatic breast cancer cell line, MDA-MB-231, and then cultured with an immature osteoblast cell line, MC3T3-E1. To characterize cell adhesion, MC3T3-E1 osteoblasts were examined with a mechanical scanning acoustic reflection microscope (SAM). The cells were cultured with or without MDA-MB-231 conditioned medium for 2 days, and then assayed microscopically. The SAM indicated that MC3T3-E1 osteoblasts were firmly attached to their plastic substrate. However, MC3T3-E1 cells cultured with MDA-MB-231 conditioned medium displayed both an abnormal shape and poor adhesion at the substrate interface. These data taken together suggest that MDA-MB-231 breast cancer cells alter MC3T3-E1 adhesion. Using optical microscopic techniques, we were not able to observe these differences until the cells were quite confluent after 7 days of culture. However, using the SAM, we were able to detect these changes within 2 days of culture with MDA-MB-231 conditioned medium.

The use of SU-8 in recent years has spawned new developments in MEMS technologies due to its low cost and well characterized mechanical and optical properties. SU-8 is a high contrast, negative tone, chemically amplified, epoxy based photoresist. Considered the poor man's LIGA, the resist is recognized for its high aspect ratio (~15:1), great for vertical sidewalls. Designs of ink jets, micro fluidic devices, and optical devices are a few examples that the material has been used for. Written here is the fabrication and test analysis of a MEMS optical scanner. The scanner is a new stage development to the previous microfabricated Si/SiO₂ cantilever beam which was fabricated for the purpose of endoscope examination. The current design has improved performance and “ease of use” with the implementation of SU-8 as the foundation to the optical waveguide or scanner. With this new device, larger thicknesses were achieved as compared to the previous method. Fabrication of the SU-8 waveguide was measured to be ~85μm as compared to the silixon oxide method of ~3μm. An overall larger device makes coupling a fiber into the waveguide much easier and increases the amount of light coupled into the beam. The optical scanner consists of a cantilever beam with a U-shaped groove for optical coupling. In this paper, we will discuss the image scanning capabilities of the device.

Attempts to develop a Wireless Health Advanced Mobile Bio-diagnostic System (abbreviated as WHAM-BioS) have arisen from the need to monitor the health status of patients under long-term care programs. The proposed WHAM-BioS as presented here was developed by integrating various technologies: nano/MEMS technology, biotechnology, network/communication technology, and information technology. The biochips proposed not only detect certain diseases but will also report any abnormal status readings on the patient to the medical personnel immediately through the network system. Since long-term home care is typically involved, the parameters monitored must be analyzed and traced continuously over a long period of time. To minimize the intrusion to the patients, a wireless sensor embedded within a wireless network is highly recommended. To facilitate the widest possible use of various biochips, a smart sensor node concept was implemented. More specifically, various technologies and components such as built-in micro power generators, energy storage devices, initialization processes, no-waste bio-detection methodologies, embedded controllers, wireless warning signal transmissions, and power/data management were merged and integrated to create this novel technology. The design methodologies and the implementation schemes are detailed. Potential expansions of this newly developed technology to other applications regimes will be presented as well.

Structural health monitoring is an important field concerned with assessing the current state (or "health") of a structural system or component with regard to its ability to perform its intended function appropriately. One approach to this problem is identifying appropriate features obtained from time series vibration responses of the structure that change as structural degradation occurs. In this work, we present a novel technique adapted from the nonlinear time series prediction community whereby the structure is excited by an applied chaotic waveform, and predictive maps built between structural response attractors are used as the feature space. The structural response is measured at several points on the structure, and pairs of attractors are used to predict each other. This approach is applied to detecting the preload loss in a bolted joint in an aluminum frame structure.

Structural health monitoring systems consist of a method to measure the structure's performance at a given point in time and a means to interpret the measured raw data in terms of presence and location of damage. This work focuses on the interpretation of the measured raw data. The concept of structural health monitoring that this work supports is a multi-stage damage identification system where the first, or screening, stage is used to indicate when further inspection is necessary, prior to the degradation of structural parameters. Finding low levels of damage is important for this screening stage. This paper describes the application of a previously presented wavelet based algorithm to detect relatively low levels of structural damage. Typically strain sensor data is used in the algorithm. However, the algorithm does not depend on a specific type of data (strain, stress, displacement, etc.), the conditions (load, boundary, etc.) under which the data was acquired, or the geometry of the structure. The structures examined in this paper are steel plates. Sensor data is either obtained from experimentation or finite element models. In the case of finite element analyses, sensor data in the form of non-linear time histories is extracted, thus producing the equivalent of raw sensor data. The wavelet based algorithm makes use of the continuous wavelet transformation and examines how this feature changes as damage accumulates.

In past work we have demonstrated a vibration based health monitoring methodology which was experimentally validated on several plate and beam systems. The method is based on processing time series data by transforming the data into a state space object, an attractor, and then identifying geometric features of the attractor. The system's structural health or level of damage is monitored by tracking the evolution of the geometric feature as the system evolves. Our previous research indicated that low dimensional inputs work best for characterizing the features. Also discovered was the fact that the features could be characterized with minimal performance loss by using a band limited noise input. The current work assess whether an ambient excitation can serve as the input to the structure and still successfully identify and track geometric features of the system in much the same way that the band limited noise was able to characterize the system. The system in question is a 2D typical section airfoil model with a control surface. A reduced order aerodynamic approach developed by Peters is used to model the fluid loading on the structure. Damage is induced on the structure by introducing increasing amounts of freeplay in the restoring torque of the control surface. The novel and most important component of the model from the stand point of implementing an on-line structural health monitoring system is the use of an ambient source of excitation namely atmospheric gust loading.

A new algorithm is presented for detecting damage in structures subject to ambient or applied excitation. The approach is derived from an attractor-based technique for detecting nonstationarity in time series data and is referred to as recurrence quantification analysis (RQA). Time series data collected from the structure are used to reconstruct the system's dynamical attractor in phase space. The practitioner then quantifies the probabilities that a given trajectory will visit local regions in this phase space. This is accomplished by forming a binary matrix consisting of all points that fall within some predefined radius of each point on the attractor. The resulting recurrence plot reflects correlations in the time series across all available time scales in a probabilistic fashion. Based on the structure found in recurrence plots a variety of metrics are extracted including: percentage of recurrence points, a measure reflecting determinism, and entropy. These "features" are then used to detect and track damage-induced changes to the structure's vibrational response. The approach is demonstrated experimentally in diagnosing the length of a crack in a thin steel plate. Structural response data are recorded from multiple locations on the plate using a novel fiber-based sensing system.

Detecting damage in a panel subjected to transverse loads and undergoing limit cycle oscillations and chaos is investigated. The panel is mounted on a rigid substructure at its ends, and interacts with an unsteady supersonic flow on one side, and with a quiescent flow on the other side. This aeroelastic system includes structural nonlinearity due to the coupling between stretching and bending for deflections of the order of magnitude of the panel thickness. Also, energy dissipation is modeled by accounting for aerodynamic damping in the system. The flow is modeled using third order piston theory which includes aerodynamic nonlinearities. Finally, two types of damage are considered in the panel: (i) a local reduction in the bending stiffness (which may occur in many damage scenarios, such as the cases where yielding occurs or a crack propagates in the material), and (ii) a loss of stiffness in the upstream and/or downstream mounting points of the panel. Multiple damages are detected based on a state space analysis of the attractor of the dynamics of the aeroelastic system. Most of the current studies of such problems are based on linear theories. In contrast, the results presented are obtained using nonlinear dynamics, and have the advantage of an increased accuracy. The sensitivity of the nonlinear system dynamics to parametric changes is shown to be an effective tool for structural health monitoring.

The focus of this work is on damage detection in transient structural response time series data recorded during an underwater shock experiment. A unique data-driven approach where damage features are extracted, evaluated, and determined based on the instantaneous phases of structural waves was applied to detect damage for a large composite structure. Measured time series data was first decomposed adaptively into a set of basis functions, known as Intrinsic Mode Functions (IMFs), using the method of Empirical Mode Decomposition. Instantaneous phases are then defined based on the IMFs, which can be used to represent nonlinear and non-stationary signals. Damage features are then formulated and tracked in order to determine the state of a structure. This approach was developed based on a previously introduced fundamental relationship connecting the instantaneous phases of a measured time series to structural mass and stiffness parameters. A simple damage index based on the instantaneous phase relationship is used to show the effectiveness of this method for structural health monitoring applications.

Diffuse ultrasonic signals received from ultrasonic sensors which are permanently mounted near, on or in critical structures of complex geometry are very difficult to interpret because of multiple modes and reflections constructively and destructively interfering. Both changing environmental and structural conditions affect the ultrasonic wave field, and the resulting changes in the received signals are similar and of the same magnitude. This paper describes a differential feature-based classifier approach to address the problem of determining if a structural change has actually occurred. Classifiers utilizing time and frequency domain features are compared to classifiers based upon time-frequency representations. Experimental data are shown from a metallic specimen subjected to both environmental changes and the introduction of artificial damage. Results show that both types of classifiers are successful in discriminating between environmental and structural changes. Furthermore, classifiers developed for one particular structure were successfully applied to a second one that was created by modifying the first structure. Best results were obtained using a classifier based upon features calculated from time-frequency regions of the spectrogram.

In this paper, we have proposed diagnostic techniques using a multilayered neural network where the weights in the network are updated using node-decoupled extended Kalman filter (NDEKF) training method. Sensor signals in both time domain and frequency domain are analyzed to show the effectiveness of the NDEKF algorithm in each domain. Comparisons of the NDEKF algorithm with other popular neural network training algorithms such as extended Kalman filter (EKF) and backpropagation (BP) will be discussed in the paper through a system identification problem. First, the simulation results reveal the comparison of outputs from actual system and trained neural network. Secondly, the ability of diagnosing a system with one normal condition and three known fault conditions is demonstrated. Thirdly, the robustness of the machine condition monitoring when the inputs to the system vary is shown. The proposed technique works even when there is noise in sensor signals as well.

This paper portrays work for the development of a Lamb wave scanning method for the detection of defects in thin plates. The approach requires the generation of an ultrasonic A_o and S_o-Mode Lamb Wave using an incident transmitter excited with a tone burst centered at a near non-dispersive frequency. With a fixed relative separation both transmitter and receiving transducer, remotely scan a specific line section of the plate. The arrival time information coming from incident and reflected waves contain information associated with the location of reflection surfaces or potential flaws. 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. The arrival times and amplitudes of the notch-reflected energy are used to calculate by means of two geometric methods, the coordinates of the source of the reflections. The resulting coordinates outline the extent and relative direction of notches in two different scenarios. One is having notches in a 0 to 22.5 degree orientation in respect to the far edge of the plate and two with notches of various sizes at a single rivet hole. Results of experiments conducted on 1.6mm-thick Aluminum square plates, with an arrangement of notches as described compare favorably with the actual notches.

Recently, the empirical mode decomposition (EMD) in combination with the Hilbert spectrum method has been proposed to identify the dynamic characteristics of linear structures. In this study, this EMD and Hilbert spectrum method is used to analyze the dynamic characteristics of a damaged reinforced concrete (RC) beam in the laboratory. The RC beam is 4m long with a cross section of 200^mm X 250^mm. The beam is sequentially subjected to a concentrated load of different magnitudes at the mid-span to produce different degrees of damage. An impact load is applied around the mid-span to excite the beam. Responses of the beam are recorded by four accelerometers. Results indicate that the EMD and Hilbert spectrum method can reveal the variation of the dynamic characteristics in the time domain. These results are also compared with those obtained using the Fourier analysis. In general, it is found that the two sets of results correlate quite well in terms of mode counts and frequency values. Some differences, however, can be seen in the damping values, which perhaps can be attributed to the linear assumption of the Fourier transform.

The present research proposes a new automatic damage diagnostic method that does not require data of damaged state. Structural health monitoring is a noticeable technology for civil structures. Multiple damage diagnostic method for has been proposed, and most of them employ parametric method based on modeling or non-parametric method such as artificial neural networks. These methods demand much costs, and first of all, it is impossible to obtain data for training of damaged existing structures. That causes importance of development of the method, which diagnoses damage just from data of the intact state structure for existing structures. Therefore we purpose new statistical diagnostic method for structural damage detection. In the present method, system identification using a response surface is performed and damage is diagnosed by testing the change of this identified system by statistical test. The new method requires data of non-damaged state and does not require the complicated modeling and data of damaged state structure. As an example, the present study deals damage diagnosis of a jet-fan which installed to a tunnel on an expressway as a ventilator fan. Damages are detected from load of turnbuckles. As a result, the damage is successfully diagnosed with the method.

A simple methodology for identification and quantification of nonlinear effects such as Coulomb friction and backlash is desired for use in condition based maintenance programs for both structural and machine based applications. Typically, structural applications are passive and undergo small vibratory motion when an external excitation is presented to the system. A spring-mass system was used as the structural example. Machine applications are typically active and motion is excited by internal actuation of large motion within the system. An industrial SCARA robot was used as the machine based example. The Hilbert transform was tested for detection and quantification of Coulomb friction in both systems.

This paper presents the results obtained during the development of a semi-real-time monitoring methodology based on Neural Network Pattern Recognition of Acoustic Emission (AE) signals for early detection of cracks in couplings used in aircraft and engine drive systems. AE signals were collected in order to establish a baseline of a gear-testing fixture background noise and its variations due to rotational speed and torque. Also, simulated cracking signals immersed in background noise were collected. EDM notches were machined in the driving gear and the load on the gearbox was increased until damaged was induced. Using these data, a Neural Network Signal Classifier (NNSC) was implemented and tested. The testing showed that the NNSC was capable of correctly identifying six different classes of AE signals corresponding to different gearbox operation conditions. Also, a semi-real-time classification software was implemented. This software includes functions that allow the user to view and classify AE data from a dynamic process as they are recorded at programmable time intervals. The software is capable of monitoring periodic statistics of AE data, which can be used as an indicator of damage presence and severity in a dynamic system. The semi-real-time classification software was successfully tested in situations where a delay of 10 seconds between data acquisition and classification was achieved with a hit rate of 50 hits/second per channel on eight active AE channels.

A novel structural damage assessment technique based on the principal component analysis (PCA) and the flexibility matrix approach is proposed in this paper. The technique is a model free method and can be used for detecting damage occurrence and location. The PCA is adopted firstly to decompose a set of correlated structural response measurements into statistically uncorrelated ones. Under the condition of small damping, these uncorrelated data can be shown to be related to modal responses and can be used to estimate the modal properties of a structure. The structural flexibility matrix can then be constructed using the estimated modal parameters. The change in the flexibility matrix gives an indication of the occurrence and location of structural damage. A numerical study on a 7-storey shear beam building model is performed to illustrate the applicability of the proposed technique. The results show that the proposed technique can accurately identify the occurrence and location of structural damage when the building is subjected to various earthquake excitations.

The study aims at implementing a remote online machine fault diagnostic system built up in the architecture of both the BCB software-developing environment and Internet transmission communication. Variant signal-processing computation schemes for signal analysis and pattern recognition purposes are implemented in the BCB graphical user interface. Hence, machine fault diagnostic capability can be extended by using the socket application program interface as the TCP/IP protocol. In the study, the effectiveness of the developed remote diagnostic system is validated by monitoring a transmission-element test rig. A complete monitoring cycle includes data acquisition, signal processing, feature extraction, pattern recognition through the ANNs, and online video monitoring, is demonstrated.

In this paper we propose a neural network-based approach for damage detection of unknown structure systems. Newly developed global H_∞ Filter optimal learning algorithm for the neural network to simulate a structural response is developed. This algorithm is based on the worst-case disturbances design criterion, and is therefore robust with respect to model uncertainties and lack of statistical information to the exogenous signals. Simulation results are presented to identify dynamic response characteristics of nonlinear structural systems corresponding to different degrees of parameters changes, which indicate that damage occurred in the structure. It is shown that the proposed method is highly robust and more appropriate in practical early structural damage detection.

In this paper, we develop a new structural identification algorithm by improving the defect of the classical Monte Carlo Filter (MCF). In the MCF, we identify the probability density function of the state vector which is approximated by many realizations, called particles. In the classical MCF, however, as the degree of freedom of structural model increases, we have to generate exponential order of particles. This results in extreme increase of computation time. To overcome this problem, we developed the relaxation MCF (RMCF) in which we improve the filtering process of the classical MCF. By using this method, we can reduce computation time drastically. Moreover, we developed the GA-RMCF, in which we combine the Genetic Algorithm (GA) with the RMCF. We apply the proposed algorithm, the GA-RMCF, to identifying the dynamic parameters of a five-story model building using observed data obtained through the shaking table tests. The data processed here are from a linear structural model.

The purpose of this paper is to develop an application implementable to a laptop computer by which we can evaluate a structural system from its responses in situ. To show applicability of the application, we analyze the data obtained by a shaking table experiment of a five-story building model. Four Lead Rubber Bearings (LRBs) are placed at the four corner of 1st and 3rd stories of the model building instead of columns to set a clear nonlinear behavior of the structure. Using the test data and the developed application, we identify the dynamic characteristics of five-story building model.

Civil engineering structures require geometrical monitoring to assure their integrity during their life time. The monitoring by geodetic devices or according to GPS technology is not always appropriate, sometimes it is unrealizable. Means for monitoring based on automatic geodetic measurements applying optical scanners are proposed. The sensor for integrity and deformation control of the structure elements and components was designed.

Sensitive skin is a highly desired device for biomechanical devices, wearable computing, human-computer interfaces, exoskeletons, and, most pertinent to this paper, for lower limb prosthetics. The measurement of shear stress is very important because shear effects are key factors in developing surface abrasions and pressure sores in paraplegics and users of prosthetic/orthotic devices. A single element of a sensitive skin is simulated and characterized in this paper. Conventional tactile sensors are designed for measurement of the normal stress only, which is inadequate for comprehensive assessment of surface contact conditions. The sensitive skin discussed here is a flexible array capable of sensing shear and normal forces, as well as humidity and temperature on each element.