Signal Recognition and Experiment for Electromagnetically Induced Acoustic Emission
Zhang Chuang1, Liu Suzhen1, Yang Qingxin1, 2, Jin Liang2, Yang Sumei1
1. Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Hebei University of Technology Tianjin 300130 China 2. Tianjin Polytechnic University Tianjin 300160 China
Abstract：Electromagnetically induced acoustic emission (EMAE) technique is a new nondestructive testing (NDT). It does nondestructive detection with the effect of dynamic electromagnetic loading to generate a stress field stimulating stress waves from the defects. The principle and implementation procedure of the EMAE is analyzed. It adopts the neural network recognition method based on wave analysis. The characteristic parameters of EMAE signal are extracted using wavelet packet transform. The recognition system of back-propagation (BP) network consists of 10 input elements, 18 hidden elements and single output. In order to overcome the shortcoming of low constringency speed, this paper proposes a kind of neural network recognition with adaptive number of neurons on the input layer method. The experiment results show it can identify the crack in the metal plate quickly and accurately.
张闯, 刘素贞, 杨庆新, 金亮, 杨素梅. 电磁声发射的实验与信号识别研究[J]. 电工技术学报, 2012, 27(4): 18-23.
Zhang Chuang, Liu Suzhen, Yang Qingxin, Jin Liang, Yang Sumei. Signal Recognition and Experiment for Electromagnetically Induced Acoustic Emission. Transactions of China Electrotechnical Society, 2012, 27(4): 18-23.
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2012, Vol. 27 
