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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.

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A novel strategy to design piezoelectric sensors suited for direction of arrival (DoA) estimation of incoming Lamb waves is presented in this work. The designed sensor is composed by two piezoelectric patches (P1, P2) bonded on the structure to be inspected. In particular, by exploiting the Radon transform, the proposed procedure computes the shape of P2 given the shape of P1 so that the difference in time of arrival (DToA) of the Lamb waves at the two patches is linearly related to the DoA while being agnostic of the waveguide dispersion curves. With a dedicated processing procedure, the waveforms acquired from the two electrodes and digitized can be used to retrieve the DoA information. Numerical and experimental results show that DoA estimation performed by means of the proposed shaped transducers is extremely robust.

Within the SARISTU project, the Application Scenario 5 (AS05) was devoted primarily to the development of methodologies based on ultrasonic guided waves for Structural Health Monitoring (SHM) implementation on wing structural elements made of composite materials for detecting BVID or hidden flaws. These methodologies have been mainly developed by the authors of this paper, technologically integrated, and applied on small-scale structural elements within Scenario 5 (unstiffened and stiffened plates) focusing, at the end of the work, also on statistical assessment of damage thresholds levels for each methodology propaedeutic to a probability of detection (POD) evaluation of each approach. The paper will shortly present the methodologies developed and implemented, the main experimental and numerical results in terms of damage detection, and the statistical assessment of threshold damage detection levels. Finally, a short comparison about pros and cons of the methodologies as well as the migration strategy of the methodologies to the Integration Scenario 12 for full-scale wing implementation will be presented.

When citing, please refer to the published version.

This work describes a network of low power/low-cost microelectromechanical-(MEMS-) based three-axial acceleration sensors with local data processing and data-to-cloud capabilities. In particular, the developed sensor nodes are capable to acquire acceleration time series and extract their frequency spectrum peaks, which are autonomously sent through an ad hoc developed gateway device to an online database using a dedicated transfer protocol. The developed network minimizes the power consumption to monitor remotely and in real time the acceleration spectra peaks at each sensor node. An experimental setup in which a network of 5 sensor nodes is used to monitor a simply supported steel beam in free vibration conditions is considered to test the performance of the implemented circuitry. The total weight and energy consumption of the entire network are, respectively, less than 50 g and 300 mW in continuous monitoring conditions. Results show a very good agreement between the measured natural vibration frequencies of the beam and the theoretical values estimated according to the classical closed formula. As such, the proposed monitoring network can be considered ideal for the SHM of civil structures like long-span bridges.