Accelerated guided waves inspection using Compressive sensing and Local wavenumber domain analysis

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, it is necessary to develop faster techniques for damage identification and characterization. Toward this end, this research presents a damage detection methodology based on compressed sensing and local wavenumber estimation techniques that can lead to fast scanning and damage detection procedures. The compressed sensing technique reduces the amount of measurements needed, thus achieving faster scanning. In this method, first full wavefields are reconstructed by applying the compressive sensing technique processed. Then, local wavenumber domain analysis is performed for processing guided wavefield data for fast damage imaging process. In the experiments, guided waves are excited with a piezoelectric transducer bonded to the inspected structure and sensed by an air-coupled probe mounted on a CNC machine. To demonstrate the effectiveness of the proposed techniques, several experiments were performed on an aluminum structure, emulating defect with a mass. The results demonstrate that the techniques are very effective in localizing damage with high inspection speed by sampling just a fraction of the Nyquist scanpoints.