Study on Experiments and Feature Extraction Algorithm of vibration signals Based on Sparse Coding

Miao Zhonghua Zhou Guangxing Liu Haining Liu Chengliang

Journal of Vibration and Shock ›› 2014, Vol. 33 ›› Issue (15) : 76-81.

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PDF(1738 KB)
Journal of Vibration and Shock ›› 2014, Vol. 33 ›› Issue (15) : 76-81.
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Study on Experiments and Feature Extraction Algorithm of vibration signals Based on Sparse Coding

  • Miao Zhonghua 1 Zhou Guangxing 1 Liu Haining2 Liu Chengliang 2
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Abstract

To solve the problem of status information feature's extraction of the mass redundant data in device, an effective feature extraction method of vibration signal which is continuously sampled in a long time is presented. This method is rooted in the principle of information processing in the biological perceptual system's redundancy compression, and based on sparse coding algorithm in neuroscience research. The two problems of the sparse coding algorithm (Coefficient solving and Dictionary learning) are researched in detail. Experiments about the proposed method have been accomplished based on the artificial bearing fault data sets. The results indicate that the proposed vibration signal feature extraction method not only can effectively extract status characteristics from the device information, but also has good separability in the sparse feature. This method can be used for equipment's fault diagnosis, and also provides an effective tool for intelligent maintenance of equipment based on state.

Key words

feature extraction / sparse coding / fault diagnosis / vibration signal analysis

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Miao Zhonghua Zhou Guangxing Liu Haining Liu Chengliang . Study on Experiments and Feature Extraction Algorithm of vibration signals Based on Sparse Coding[J]. Journal of Vibration and Shock, 2014, 33(15): 76-81
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