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Many structural health monitoring techniques rely on the full field analysis related to stress guided waves propagation. Such techniques can be quite slow as in general the acquisition of the full wave field and its processing, aimed at extracting damage related information, are time consuming processes. Therefore, strategies to reduce the acquisition time and improve the damage detection and quantification...
In recent years, accurate location and characterization of damage has motivated the engineering community to develop several damage identification techniques. Many of the nondestructive evaluations and structural health monitoring techniques are based on the analysis of huge amount of data collected from acousto-ultrasonic sensors. Such analysis is typically a very time-consuming process. Therefore,...
This research presents a damage detection technique based on a compressive sensing (CS) algorithm applied to full wavefield data. The aim is to realize an effective tool for damage detection and localization which allows to reduce the acquisition time. The proposed technique exploits the compressive sensing framework to infer the damage location and entity from the comparison between the wavefield...
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