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Proceedings Paper

Improved LMD algorithm based on extraction of extrema of envelope curve
Author(s): Yuqian Song; Jun Zhao; Tiantai Guo; Ming Kong; Yingjun Wang; Liang Shan
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Paper Abstract

Local mean decomposition (LMD) is a time-frequency analysis approach to deal with complex multi-frequency signal. However, as the decomposition process is sensitive to noise, there is a distinct limit when it is applied to analysis of the vibration signals of machinery with serious background noise. An improved LMD algorithm based on extracting the extrema of envelope curve is put forward to reduce the influence of high-frequency noise effectively. To verify its effect, three different de-noising methods, i.e., band-pass filter method, wavelet method and lift wavelet method are used, respectively. And the comparison result of the 4 methods shows that the proposed method has satisfactory reproducibility. Then the new algorithm is applied to real bearing signal, and experimental results show that it is effective and reliable. The method also has certain significance for the subsequent eigenvector research in intelligent fault diagnosis.

Paper Details

Date Published: 6 March 2015
PDF: 9 pages
Proc. SPIE 9446, Ninth International Symposium on Precision Engineering Measurement and Instrumentation, 94462F (6 March 2015); doi: 10.1117/12.2181138
Show Author Affiliations
Yuqian Song, China Jiliang Univ. (China)
Jun Zhao, China Jiliang Univ. (China)
Tiantai Guo, China Jiliang Univ. (China)
Ming Kong, China Jiliang Univ. (China)
Yingjun Wang, China Jiliang Univ. (China)
Liang Shan, China Jiliang Univ. (China)


Published in SPIE Proceedings Vol. 9446:
Ninth International Symposium on Precision Engineering Measurement and Instrumentation
Junning Cui; Jiubin Tan; Xianfang Wen, Editor(s)

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