Abstract：The material information is very important for preventing from generation of the remainders. According to ever research around with sound signal, this paper proposes methods of material classification based on wavelet transform for aerospace relay using acceleration-disturbing signal. The disturbing signal is jointed together for features in focus by detection algorithm with three thresholds. Metallic and nonmetallic particles are categorized by spectrum barycenter defined in frequency domain, and the boundary of classification is determined as 50 kHz in experiments. The definite material of remainder paticles are categorized based on BP neural network by energy distribution vector, which is defined by wavelet transform. The algorithms are validated by experiment using particles whose mass exceed 1 mg, and the classification accuracy is up to 67.78% and 76.67% respectively. The classification methods present in this paper can be applied in remainder detecting for other military electronic components and electronic devices.
翟国富, 王世成, 王淑娟. 基于小波变换的航天继电器多余物材质分类[J]. 电工技术学报, 2009, 24(5): 52-59.
Zhai Guofu, Wang Shicheng, Wang Shujuan. Classification of Remainder Material for Aerospace Relay Based on Wavelet Transform. Transactions of China Electrotechnical Society, 2009, 24(5): 52-59.
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2009, Vol. 24 
