A damage detection method of plate structure using fan-shaped sensor clusters

TL;DR

This paper introduces a fan-shaped sensor cluster for damage detection in plate structures, combining beamforming and LSSC methods to reduce blind areas and improve localization accuracy through simulations and experiments.

Contribution

It proposes a novel fan-shaped sensor cluster that enhances damage localization accuracy by reducing blind spots compared to traditional T-shaped clusters.

Findings

Fan-shaped sensor cluster reduces blind areas.

Improves damage localization accuracy.

Validated through simulations and experiments.

Abstract

Plate structures are widely used in large-scale engineering fields such as aerospace, hull manufacturing, and construction. However, the plate structure is easily damaged during long-term service or when it is impacted by foreign objects. Such a damage may lead to serious safety accidents. Beamforming and L-shaped sensor cluster (LSSC) localization method can be used to locate the damage on the plate. However, when using beamforming or LSSC localization method to locate the damages on plate-like structures, there exists blind area. In this paper, by combining the beamforming and LSSC localization method, a fan-shaped sensor cluster is proposed through arranging five sensors in a fan shape, which can effectively reduce the blind areas. The positions of damages on the plate can be accurately detected by using two groups of fan-shaped sensor clusters and one sensor for transmitting the excitation signal. The feasibility of the fan-shaped sensor cluster localization method is verified through numerical simulations and experiments, and the results are compared with those obtained by using the T-shaped sensor cluster. The results show that the fan-shaped sensor cluster can more accurately identify the damages at different positions. Both simulation and experimental results indicate that the fan-shaped sensor cluster can improve the accuracy of damage location.