Noncontact and remote NDE systems and methods are highly desired in a broad range of engineering applications such as material property characterization. This paper aims to develop such a noncontact/remote NDE system based on laser ultrasonic guided waves and establish its fundamental capability for material thickness evaluation. The noncontact system employs pulsed laser (PL) for guided wave actuation and scanning laser Doppler vibrometer (SLDV) for guided wave wavefield sensing. A cylindrical planoconvex lens is adopted to focus the pulsed laser beam to a line source in order to excite broad band signals in the target plate. Aluminum plates with different thicknesses are evaluated through SLDV line scans and 2D time-space wavefields are acquired. Frequency-wavenumber (f-k) spectra are obtained through 2D Fourier transform, and the A 0 dispersion curve for each plate is extracted. Through Comparing the extracted A 0 curve with the theoretical A 0 dispersion curves, the thicknesses of the tested plates are identified. Reflective tape effect on the plates are also studied: the reflective tape attached for SLDV enhancement affects the guided waves in the target plate significantly when the plate is relatively thin.

This paper presents a damage detection and imaging approach using guided waves and through the use of optical fiber Bragg Grating (FBG) sensors for structural health monitoring (SHM) purpose. An FBG array composed with four linearly aligned FBG sensors for guided wave sensing is designed. It is found that FBG sensors are optimized for sensing guided wave coming along the axial direction yet minimized for those along the normal direction. To overcome this limitation and allow for all directional sensing, a FBG phased array beamforming algorithm is derived based on the commonly used delay-and-sum beamforming algorithm principle. The work continues to evaluate the detection capability of the FBG array through two experimental studies on an aluminum plate: (a) guided wave source localization; (b) surface damage detection. The results indicates that both targets are successfully detected and agree well with their actual locations and thus confirms the capability of using presented FBG phased array for rapidly inspecting a large area with limited access.

In this paper, we explore structure-borne elastic wave energy harvesting, both numerically and experimentally, by exploiting a Gradient-Index Phononic Crystal Lens (GRIN-PCL) structure. The proposed GRIN-PCL is formed by an array of blind holes with different diameters on an aluminum plate where the orientation and size of the blind holes are tailored to obtain a hyperbolic secant gradient distribution of refractive index guided by finite-element simulations of the lowest asymmetric mode Lamb wave band diagrams. Under plane wave excitation from a line source, experimentally measured wave field successfully validates the numerical simulation of wave focusing within the GRIN-PCL domain. A piezoelectric energy harvester disk located at the first focus of the GRIN-PCL yields an order of magnitude larger power output as compared to the baseline case of energy harvesting without the GRIN-PCL on the uniform plate counterpart for the same incident plane wave excitation. The power output is further improved by a factor of five using complex electrical load impedance matching through resistive-inductive loading as compared to purely resistive loading case.

One of the challenges in structural health monitoring (SHM) is the power required for sensors to collect and communicate data. Self-powered sensors are able to harvest power by from their environment, i.e., strain and vibration of the host structure. However, the harvested power with current technology is still limited and improving the system’s efficiency requires reducing the power budget. A way to minimize the communication power demand is to transmit the minimum amount of information, namely one bit. The binary signal can be generated at a sensor node according to a local rule based on physical measurements, but interpretation at the global level requires dealing with discrete binary (1 or 0) data, which implies system information with reduced resolution. This study presents an investigation on approaches for the interpretation of such kind of binary data for use in structural assessment and damage identification. Pattern recognition (PR) methods based on image data analysis were adapted for the study. The methods used were classifiers based on deviation of patterns with respect to each other, two-dimensional principal component analysis, and two-dimensional linear discriminant analysis. The PR methods and the performance of the interpretation algorithms were evaluated by using virtual data from finite element simulations on an aluminum plate. The ability for each of the PR methods to identify service demands, load variations and localized material degradation was evaluated. Results indicate that PR methods can be used as damage identification algorithms for binary data sets in novel wireless self-powered sensor networks.

This paper presents damage imaging and quantification by using the spectral field of Lamb waves. The spectral field is acquired through a piezoelectric transducer (PZT)-scanning laser Doppler vibrometer (SLDV) sensing. A wideband chirp signal is used for PZT excitation in order to generate wideband Lamb waves. With the SLDV, the time-space wavefield is acquired, and transformed into the spectral field representation through Fourier transform. The spectral field, which contains wideband Lamb wave responses of the structure, is further analyzed for damage detection and quantification. Using the spatial wavenumber analysis, the local wavenumber at each location are obtained, and represented as a spatial wavenumber image which can be used for damage detection and evaluation. Moreover, the dispersion curve regression method is developed to quantify the thickness change of a defect. For verification, experiments are performed on aluminum plates with blind holes of different depths. The experimental results show that the blind holes can be detected by both the spatial wavenumber imaging and dispersion curve regression. In addition, the dispersion curve regression can further quantify the depths of the blind holes.

This paper discusses theoretical and experimental analyses of the standing harmonic waves through the electro-mechanical impedance spectroscopy (EMIS) and guided surface acoustic waves (SAW) through the guided wave propagation (GWP) analyses. Both EMIS and GWP analyses have been carried out by utilizing piezoelectric wafer active sensors (PWAS) for in situ structural inspection. PWAS has recently been extensively employed in many applications such as nuclear-structural as well as aero-structural health monitoring and non-destructive evaluations (NDE). EMIS method is utilized for high frequency local modal sensing to determine the dynamic characteristics of PWAS bonded on nuclear-structural component for in-situ ultrasonics. Rayleigh waves a.k.a., SAW, were generated in relatively thick isotropic elastic plates. Rayleigh waves have the property of propagating close to the plate surface, with rapid attenuation with depth. The polarization of Rayleigh waves lies in a plane perpendicular to the surface so that the effective penetration depth is less than a wavelength. Rayleigh waves are a high frequency approximation of the first symmetric (S 0 ) and anti-symmetric (A 0 ) Lamb wave modes. As the frequency becomes very high the S 0 and the A 0 wave speeds coalesce, and both have the same value. This value is exactly the Rayleigh wave speed and becomes constant along the frequency. In the first part of the study, simplified theoretical constrained PWAS-EMIS model is briefly discussed in relatively high frequency range (in MHz order of magnitude) in terms of thickness mode. Analytical predictive thickness mode impedance simulations of PWAS bonded on plate-like host structures are presented in corresponding with the experiments. For the experimental analyses, PWAS transducers are affixed on isotropic elastic plates such as aluminum plate in relatively high thickness and on a rail I-beam. The extent of the agreement between the experimental and analytical EMIS analyses of PWAS in thickness mode is presented. The study is followed with GWP tests through the pitch-catch method. Rayleigh wave signal packets which are generated in the relatively thick plate and a rail I-beam in high frequency region are assessed along with the experimental thickness mode PWAS-EMIS results. The tuning curve of Rayleigh wave is determined to show the tuning effect of the structure thickness on producing a dominant Rayleigh wave mode. The significant usage of the tuned Rayleigh wave mode is essentially discussed for the applications in the in-situ inspection of relatively thick structures such as nuclear power plant structures. The paper ends with summary, conclusions and suggestions for future work.

Interest in ultrasonic guided wave based Structural Health Monitoring and a nondestructive evaluation system has grown in recent years, especially to monitor thin plate like structures. However, an effective signal processing and imaging algorithms are essential to achieve necessary performance. This paper describes wave rich laser ultrasonic wavenumber imaging method (UWI) method for damage visualization. Ultrasonic waves were generated by a scanning laser source and acquired using a capacitance air coupled transducer (ACT). However, the inherent existence of multiple Lamb wave modes in signal makes it harder for effective damage evaluation. This is further complicated if the reflections from the boundaries are present in the signal. The use of an ACT with an in-line programmable filter helps to isolate lower order Lamb wave modes (A o and S o ), since the dispersive waves radiate at certain angle from the specimen governed by Snell’s law. By comparing the results from the ultrasonic wavefield image obtained using the ACT and a PZT contact sensor under the same experimental condition, mode isolation phenomena was verified. Such isolated wave mode was processed using a proposed wave rich UWI algorithm where a wave rich field was generated by superposing the wavefields. The mode filtered measurements were arranged in 3D space-time domain where each slice in time domain represents 2D wavefield image. A 2D Fast Fourier Transform (FFT) was applied to this spatial information in time domain which transformed it to a wavenumber domain. A wavenumber filter is then applied and inverse Fourier transformed to get back to the wavenumber filtered measurement. However, instead of applying filter to every 2D slice in time domain, certain frames were selected and merged to replicate wave propagation in total scan-area. This wave rich field not only saves time and space but also reduce computational complexity during post-processing. This method was tested successfully in an aluminum plate with milled area damage and a composite fiber-reinforced plastic (CFRP) wing skin with two impact damages.

Vibration-based energy harvesting using cantilevered piezoelectric beam has been extensively studied over the last decade. In this study, as an alternative to resonant piezoelectric cantilevers, we studied multiple patch-based piezoelectric energy harvesting from multiple vibration modes of thin plates. Analytical electroelastic model of the multiple patch-based piezoelectric harvesters attached on a thin plate is provided based on distributed-parameter modeling approach for series and parallel configurations of the patches. An experimental setup is built with series-configuration of double patch-based harvesters attached on the surfaces of all-four-edges clamped (CCCC) rectangular aluminum plate. Analytical simulations and experimental validations of power generation of the harvesters are performed in a case study. The experimental and analytical frequency response functions (FRF) relating voltage output and vibration response to force input are obtained. The analytical model is validated by comparing analytical and experimental FRFs for a wide range of resistive electrical boundary conditions. The harvested power output across the various resistive loads is explored with a focus on the first four modes of the aluminum plate. Experimental and analytical results are shown to be in agreement for multiple patch-based piezoelectric energy harvesting from multiple vibration modes of thin plates.

In structural health monitoring (SHM), impact detection and characterization techniques often focus on identifying parameters of impact such as the location and velocity of an impacting object. A distributed network of sensors is used to passively detect the mechanical wave created by the impact. Various techniques are used to analyze the signals based on time of arrival, amplitude and phase. A simpler architecture could be used to determine whether an impacting event was benign or caused damage and requires further evaluation. This research focuses on detecting attributes of impact-generated elastic wave signals that are indicative of local damage at the impact site. Waveforms deviate insignificantly for undamaged materials, however, when a material is stressed to plastic deformation or damaged the waveform of propagation through the material is noticeably affected. This change in wave speed may be detectable by SHM sensors, and can be used as an indicator of damage. Low velocity impact experiments were conducted on thin aluminum plates instrumented with piezoelectric and magneto-elastic sensors at various locations. The sensors acquired the initial passage of the impact wave signal before reflections off the boundaries became a significant element. By inspecting the signal for deviations induced by damage (such as plastic deformation), a routine for evaluating damage can be inferred. Further work may correlate features of the signal with damage severity providing an extra level of information in determining the next step in evaluating the damage. Using this approach, it may be possible to evaluate impact damage using limited numbers of passive sensors.

In this paper, the detection for two kinds of cracks is studied: (1) linear notch crack; (2) nonlinear breathing crack. A pitch-catch method with piezoelectric wafer actives sensors (PWAS) is used to interrogate an aluminum plate with a linear notch crack and a nonlinear breathing crack respectively as two cases. The inspection Lamb waves generated by the transmitter PWAS, propagate into the structure, interact with the crack, acquire crack information and are picked up by the receiver PWAS. The linear notch crack case is investigated through: (1) analytical model developed for Lamb waves interacting with a general linear damage; (2) finite element simulation. The breathing crack, which acts as a nonlinear source, is simulated using two approaches: (1) element activation/deactivation technique; (2) contact model. The theory and solving scheme of the proposed element activation/deactivation approach is discussed in detail. The signal features of different damage severities are analyzed. Crack opening, closing, stress concentration, surface collision phenomena are noticed for the breathing cracks. Mode conversion is noticed for both crack cases. The generation mechanism and mode components of the new wave packets are investigated by studying the particle motion through the plate thickness. A damage index is proposed based on the spectral amplitude ratio between the second harmonic and the excitation frequency for the breathing crack. The damage index is found capable of estimating the presence and severity of the breathing crack. The paper finishes with summary and conclusions.

Many structural damage detection methods utilize piezoelectric sensors. While these sensors are efficient in supporting many structural health monitoring (SHM) methodologies, there are a few key disadvantages limiting their use. The disadvantages include the brittle nature of piezoceramics and their dependence of diagnostic results on the quality of the adhesive used in bonding the sensors. One viable alternative is the utilization of Magneto-Elastic Active Sensors (MEAS). Instead of mechanically creating elastic waves, MEAS induce eddy currents in the host structure which, along with an applied magnetic field, generate mechanical waves via the Lorentz force interaction. Since elastic waves are generated electromagnetically, MEAS do not require direct bonding to the host structure and its elements are not as fragile as PWAS. This work explores the capability of MEAS to detect damage in aluminum alloy. In particular, methodologies of detecting fatigue cracks in thin plates were explored. Specimens consisted of two identical aluminum plates featuring a machined slot to create a stress riser for crack formation. One specimen was subjected to cyclic fatigue load. MEAS were used to transmit elastic waves of different characteristics in order to explore several SHM methodologies. Experiments have shown that the introduction of fatigue cracks created measurable amplitude changes in the waves passing through the fatigued region of the aluminum plate. The phase indicated sensitivity to load conditions, but manifestation in the cracked region lacked stability. Nonlinear effects were studied using plate thickness resonance, which revealed birefringence due to local stresses at the site of the fatigue crack. The resonance spectrum has also shown a frequency decrease apparently due to stiffness loss. Preliminary results suggest opportunities for fatigue damage detection using MEAS. Application of MEAS for the diagnosis of complex structures is currently being investigated.

This report discusses the development of an embeddable impact detection system utilizing an array of piezoelectric wafer active sensors (PWAS) and a microcontroller. Embeddable systems are a critical component to successfully implement a complete and robust structural health monitoring system. System capabilities include impact detection, impact location determination and digitization of the impact waveform. A custom algorithm was developed to locate the site of the impact.. The embedded system has the potential for additional capabilities including advanced signal processing and the integration of wireless functionality. For structural health monitoring applications it is essential to determine the extent of damage done to the structure. In an attempt to determine these parameters a series of impact tests were conducted using a ball drop tower on a square aluminum plate. The response of the plate to the impact event was recorded using a piezoelectric wafer sensor network attached to the surface of the plate. From this testing it was determined that several of the impact parameters are directly correlated with the features recorded by the sensor network.

The use of aluminum alloys in the design of naval structures offers the benefit of light-weight ships that can travel at high-speed. However, the use of aluminum poses a number of challenges for the naval engineering community including higher incidence of fatigue-related cracks. Early detection of fatigue induced cracks enhances maintenance of the ships and is critical for preventing the catastrophic failure of the hull. Furthermore, monitoring the integrity of the aluminum hull can provide valuable information for estimating the residual life of hull components. This paper presents a model-based damage detection methodology for fatigue assessment of hulls that are instrumented with a long-term hull monitoring system. At the core of the data driven damage detection approach is a Bayesian model updating algorithm enhanced with systematic enumeration and pruning of candidate solutions. The Bayesian model updating approach significantly reduce the computational effort by systematically narrowing the search space using errors functions constructed using the estimated modal properties associated with the condition of the structure. This study proposes the use of the Bayesian model updating technique to detect damage in an aluminum panel modeled using high-fidelity finite element models. The performance of the proposed damage detection method is tested through simulation of a progressively growing fatigue crack introduced in the vicinity of a welded stiffener element. An experimental study verifies the accuracy of the proposed damage detection method using an aluminum plate excited with a controlled excitation in the laboratory.

Metal-core piezoelectric fiber (MPF) is a new type of piezoelectric ceramic device with small size, and has great potential to be used as structurally integrated transducers for guided-wave (GW) structural health monitoring. This paper focuses on the use of MPF as ultrasonic Lamb wave receivers. First, the MPF sensor voltage response is derived by coupling the direct piezoelectric effect to the wave strain field excited by circular crested actuator. The obtained theoretical result is validated on an aluminum plate. Furthermore, the experiment that compares the MPF response to Lamb wave with the PZT response is performed. The results show that MPF sensors can be used to sense Lamb waves clearly. In the end, the directivity of MPF response to Lamb waves was investigated, and another experiment is performed to examine the directivity of MPF response to Lamb waves. The result shows that MPF has high directivity, which can be exploited to triangulate the location of an ultrasound source without prior knowledge of the wave velocity in the medium.