Damage detection in plates using two-dimensional directional Gaussian wavelets and laser scanned operating deflection shapes

Abstract

Mode shape analysis by wavelet transform has been used effectively for vibration-based damage detection in plates. As an extension of previous studies, this study focuses on an improved method for damage detection in plates: scrutiny of operating deflection shapes by two-dimensional directional Gaussian wavelet transforms. With this method, the proposed two-dimensional directional Gaussian wavelet can characterize directional information about damage; moreover, the operating deflection shapes can be used to address the real-time dynamic characteristics of a plate. To identify damage, the local surface of the plate is scanned using a scanning laser vibrometer to generate the local operating deflection shape, which is interrogated by two-dimensional directional Gaussian wavelets for damage. The feasibility of the method is numerically demonstrated using a low-magnitude operating deflection shape of a two-sided clamped plate, incorporating white noise with signal-to-noise ratio of 40 dB. The applicability of the method is then experimentally validated by detecting a cross-like notch in a suspended aluminum plate with the operating deflection shapes measured by a scanning laser vibrometer. Numerical and experimental results show that the method is capable of revealing directional features of small damage with high precision and strong robustness against noise. It appears that this damage detection method is related only to the spatially distributed measurement of vibrational responses in local critical regions of the plate. With this local property, the method requires no numerical or physical benchmark models for the entire structure in question nor any prior knowledge of either the material properties or the boundary conditions of the structure. (The Matlab code performing directional Gaussian wavelet transform can be provided by the corresponding author as per request.)