Advanced Video-Based Processing for Low-Cost Damage Assessment of Buildings under Seismic Loading in Shaking Table Tests.

This paper explores the potential of a low-cost, advanced video-based technique for the assessment of structural damage to buildings caused by seismic loading. A low-cost, high-speed video camera was utilized for the motion magnification processing of footage of a two-story reinforced-concrete frame building subjected to shaking table tests. The damage after seismic loading was estimated by analyzing the dynamic behavior (i.e., modal parameters) and the structural deformations of the building in magnified videos. The results using the motion magnification procedure were compared for validation of the method of the damage assessment obtained through analyses of conventional accelerometric sensors and high-precision optical markers tracked using a passive 3D motion capture system. In addition, 3D laser scanning to obtain an accurate survey of the building geometry before and after the seismic tests was carried out. In particular, accelerometric recordings were also processed and analyzed using several stationary and nonstationary signal processing techniques with the aim of analyzing the linear behavior of the undamaged structure and the nonlinear structural behavior during damaging shaking table tests. The proposed procedure based on the analysis of magnified videos provided an accurate estimate of the main modal frequency and the damage location through the analysis of the modal shapes, which were confirmed using advanced analyses of the accelerometric data. Consequently, the main novelty of the study was the highlighting of a simple procedure with high potential for the extraction and analysis of modal parameters, with a special focus on the analysis of the modal shape's curvature, which provides accurate information on the location of the damage in a structure, while using a noncontact and low-cost method.

Deep Learning Approaches for Robust Time of Arrival Estimation in Acoustic Emission Monitoring.

In this work, different types of artificial neural networks are investigated for the estimation of the time of arrival (ToA) in acoustic emission (AE) signals. In particular, convolutional neural network (CNN) models and a novel capsule neural network are proposed in place of standard statistical strategies which cannot handle, with enough robustness, very noisy scenarios and, thus, cannot be sufficiently reliable when the signal statistics are perturbed by local drifts or outliers. This concept was validated with two experiments: the pure ToA identification capability was firstly assessed on synthetic signals for which a ground truth is available, showing a 10× gain in accuracy when compared to the classical Akaike information criterion (AIC). Then, the same models were tested via experimental data acquired in the framework of a localization problem to identify targets with known coordinates on a square aluminum plate, demonstrating an overreaching precision under significant noise levels.

Damage Identification in Various Types of Composite Plates Using Guided Waves Excited by a Piezoelectric Transducer and Measured by a Laser Vibrometer.

Composite materials are widely used in the industry, and the interest of this material is growing rapidly, due to its light weight, strength and various other desired mechanical properties. However, composite materials are prone to production defects and other defects originated during exploitation, which may jeopardize the safety of such a structure. Thus, non-destructive evaluation methods that are material-independent and suitable for a wide range of defects identification are needed. In this paper, a technique for damage characterization in composite plates is proposed. In the presented non-destructive testing method, guided waves are excited by a piezoelectric transducer, attached to tested specimens, and measured by a scanning laser Doppler vibrometer in a dense grid of points. By means of signal processing, irregularities in wavefield images caused by any material defects are extracted and used for damage characterization. The effectiveness of the proposed technique is validated on four different composite panels: Carbon fiber-reinforced polymer, glass fiber-reinforced polymer, composite reinforced by randomly-oriented short glass fibers and aluminum-honeycomb core sandwich composite. Obtained results confirm its versatility and efficacy in damage characterization in various types of composite plates.

Control of Love waves by resonant metasurfaces.

Metasurfaces of mechanical resonators have been successfully used to control in-plane polarized surface waves for filtering, waveguiding and lensing applications across different length scales. In this work, we extend the concept of metasurfaces to anti-plane surface waves existing in semi-infinite layered media, generally known as Love waves. By means of an effective medium approach, we derive an original closed-form dispersion relation for the metasurface. This relation reveals the possibility to control the Love waves dispersive properties by varying the resonators mechanical parameters. We exploit this capability to manipulate the metasurface refractive index and design two gradient index (GRIN) metalenses, i.e. a Luneburg lens and a Maxwell lens. We confirm the performance of the designed lenses using full 3D finite element simulations. Our work demonstrates the possibility of realizing wave control devices for anti-plane waves.

Full Wavefield Analysis and Damage Imaging Through Compressive Sensing in Lamb Wave Inspections.

One of the main challenges faced by the structural health monitoring community is acquiring and processing huge sets of acoustic wavefield data collected from sensors, such as scanning laser Doppler vibrometers or ultrasonic scanners. In fact, extracting information that allows the estimation of the damage condition of a structure can be a time-consuming process. This paper presents a damage detection and localization technique based on a compressive sensing algorithm, which significantly allows us to reduce the acquisition time without losing in detection accuracy. The proposed technique exploits the sparsity of the wavefield in different representation domains, such as those spanned by wave atoms, curvelets, and Fourier exponentials to recover the full wavefield and, at the same time, to infer the damage location, based on comparison between the wavefield reconstructions produced by the different representation domains. The procedure is applied to three different setups related to an aluminum plate with a notch, a glass fiber reinforced polymer plate with a notch, and a composite plate with a delamination. The results show that the technique can be applied in a variety of structural components to reduce acquisition time and achieve high performance in defect detection and localization by removing up to 80% of the Nyquist sampling grid.

Engineered metabarrier as shield from seismic surface waves.

Resonant metamaterials have been proposed to reflect or redirect elastic waves at different length scales, ranging from thermal vibrations to seismic excitation. However, for seismic excitation, where energy is mostly carried by surface waves, energy reflection and redirection might lead to harming surrounding regions. Here, we propose a seismic metabarrier able to convert seismic Rayleigh waves into shear bulk waves that propagate away from the soil surface. The metabarrier is realized by burying sub-wavelength resonant structures under the soil surface. Each resonant structure consists of a cylindrical mass suspended by elastomeric springs within a concrete case and can be tuned to the resonance frequency of interest. The design allows controlling seismic waves with wavelengths from 10-to-100 m with meter-sized resonant structures. We develop an analytical model based on effective medium theory able to capture the mode conversion mechanism. The model is used to guide the design of metabarriers for varying soil conditions and validated using finite-element simulations. We investigate the shielding performance of a metabarrier in a scaled experimental model and demonstrate that surface ground motion can be reduced up to 50% in frequency regions below 10 Hz, relevant for the protection of buildings and civil infrastructures.

Compressive sensing of full wave field data for structural health monitoring applications.

Numerous nondestructive evaluations and structural health monitoring approaches based on guide waves rely on analysis of wave fields recorded through scanning laser Doppler vibrometers (SLDVs) or ultrasonic scanners. The informative content which can be extracted from these inspections is relevant; however, the acquisition process is generally time-consuming, posing a limit in the applicability of such approaches. To reduce the acquisition time, we use a random sampling scheme based on compressive sensing (CS) to minimize the number of points at which the field is measured. The CS reconstruction performance is mostly influenced by the choice of a proper decomposition basis to exploit the sparsity of the acquired signal. Here, different bases have been tested to recover the guided waves wave field acquired on both an aluminum and a composite plate. Experimental results show that the proposed approach allows a reduction of the measurement locations required for accurate signal recovery to less than 34% of the original sampling grid.

Complete band gaps in a polyvinyl chloride (PVC) phononic plate with cross-like holes: numerical design and experimental verification.

In this work the existence of band gaps in a phononic polyvinyl chloride (PVC) plate with a square lattice of cross-like holes is numerically and experimentally investigated. First, a parametric analysis is carried out to find plate thickness and cross-like holes dimensions capable to nucleate complete band gaps. In this analysis the band structures of the unitary cell in the first Brillouin zone are computed by exploiting the Bloch-Floquet theorem. Next, time transient finite element analyses are performed to highlight the shielding effect of a finite dimension phononic region, formed by unitary cells arranged into four concentric square rings, on the propagation of guided waves. Finally, ultrasonic experimental tests in pitch-catch configuration across the phononic region, machined on a PVC plate, are executed and analyzed. Very good agreement between numerical and experimental results are found confirming the existence of the predicted band gaps.

Model-based compressive sensing for damage localization in Lamb wave inspection.

Compressive sensing (CS) has emerged as a potentially viable technique for the efficient compression and analysis of high-resolution signals that have a sparse representation in a fixed basis. In this work, we have developed a CS approach for ultrasonic signal decomposition suitable to achieve high performance in Lamb-wave-based defect detection procedures. In the proposed approach, a CS algorithm based on an alternating minimization (AM) procedure is adopted to extract the information about both the system impulse response and the reflectivity function. The implemented tool exploits the dispersion compensation properties of the warped frequency transform as a means to generate the sparsifying basis for the signal representation. The effectiveness of the decomposition task is demonstrated on synthetic signals and successfully tested on experimental Lamb waves propagating in an aluminum plate. Compared with available strategies, the proposed approach provides an improvement in the accuracy of wave propagation path length estimation, a fundamental step in defect localization procedures.

Ultrasonic guided-waves characterization with warped frequency transforms.

Guided wave (GW) dispersion curves can be extracted from a time-transient measurement by means of timefrequency representations (TFRs). Unfortunately, any TFR is subject to the time-frequency uncertainty principle. This, in general, limits the capability of TFRs to characterize closely spaced guided modes over a wide frequency range. To overcome this limitation, we implemented a new warped frequency transform that presents enhanced mode extraction capabilities because of a more flexible tiling of the time-frequency domain. The tiling is designed to match the dispersive spectro-temporal structure of a GW by selecting an appropriate map of the time-frequency plane. The proposed transformation is fast, invertible, and covariant to group delay shifts. An application to Lamb waves propagating in an aluminum plate is presented. Time-transient GWs propagation events obtained both numerically and experimentally are considered. The results show that the proposed warped frequency transform limits the interference patterns which appear with other TFRs and produces a sparse representation of the Lamb wave pattern that can be suitable for identification and characterization purposes.

Propagation of ultrasonic guided waves in lap-shear adhesive joints: case of incident a0 Lamb wave.

This paper deals with the propagation of ultrasonic guided waves in adhesively bonded lap-shear joints. The topic is relevant to bond inspection by ultrasonic testing. Specifically, the propagation of the lowest-order, antisymmetric a0 mode through the joint is examined. An important aspect is the mode conversion at the boundaries between the single-plate adherents 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 indicate that the dispersive behavior of the guided waves in the multilayer overlap is highly dependent on bond state. Experimental tests are conducted in lap-shear joints by a hybrid, broadband laser/air-coupled ultrasonic setup in a through-transmission configuration. 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.