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| 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 |
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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.
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Received: 16 March 2011
Published: 20 March 2014
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| Fund:This work was supported by the National Natural Science Foundation of China (51077036), the Natural Science Foundation of Hebei Province (E2012202048, E2011202040) and the Research and Development Project of Seience and Technology of Hebei Province (11215648). |
| About author:: Zhang Chuang male, born in 1982, is currently a PhD candidate, his major interests include electromagnetic nondestructive testing.Liu Suzhen female, born in 1969, professor, majoring in electromagnetic field computation, magnetic techniques and their applications. |
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2012, Vol. 27 
