Nondestructive Incipient Crack Detection based on Wavelet and Jensen-Shannon Divergence in the NICA framework

Abstract

The nondestructive crack detection is an important issue in industrial engineering. However, the detection of incipient cracks that can cause non obvious changes in the conductive material impedance map is difficult. In our paper, we propose a new method based on wavelet and Jensen-Shannon divergence in the framework of Noisy Independent Component Analysis (NICA) to address this problem. The source signals with fault features are obtained by the application of the Independent Component Analysis regarding the noise. Then, the wavelet decomposition is considered as the denoising method to partially reduce the noise influence. The Jensen-Shannon divergence(JSD) which has been proved as an efficient incipient fault detection algorithm in previous works is used here for incipient crack detection. The detection performances of the proposed method is compared with the ones obtained with the Kullback-Leibler divergence often proposed in the literature.