A defect localization method based on self-sensing and orthogonal matching pursuit

In conventional structural health monitoring (SHM), a sensor array enables to localize a potential defect by using at least three lead zirconate titanate (PZT) patches. To reduce the vast number of patches needed for large-scaled structure, this paper presents an extremely sparse sensor array with only one single PZT patch, which could actuate and sense simultaneously. Firstly, a half-bridge circuit, referred as a self-sensing circuit is developed with a capacitor connected with the PZT patch, and the capacitance parameter and self-sensing performance are studied subsequently. Then, an orthogonal matching pursuit (OMP)-based sparse decomposition and dispersion removal algorithm is proposed to separate and reconstruct wave packets which are acutely overlapped. Subsequently, a matching strategy is proposed to determine the matching relationship between wave packets and wave paths. Finally, the ellipse-type imaging approach is employed to image the defect location. Two cases: one and two defects respectively are implemented to verify its efficacy. Experimental results illustrate that the proposed self-sensing unit and signal process method could erase the adverse effect of sensor-actuator interval and dispersion characteristic to the localization resolution and accuracy.

Automated summary

This paper proposes an extremely sparse sensor array with only one single PZT patch for structural health monitoring. By developing a self-sensing circuit, proposing a sparse decomposition and dispersion removal algorithm, determining the matching relationship, and employing an ellipse-type imaging approach, the localization of defects is achieved.