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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Shudong Xiu
Zhejiang Agricultural & Forestry University
Computer Science & IT

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Diagnostic Study Based on Wavelet Packet Entropy and Wear Loss of Support Vector Machine Yunjie Xu; Shudong Xiu
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v12i4.305

Abstract

Against the problems, the ratio of signal to noise of bearing wear is low, the feature extraction is difficult, there are few fault samples and it is difficult to establish the reliable fault recognition model, the diagnostic method is put forward based on wavelet packet features and bearing wear loss of SVM. Firstly, choose comentropy with strong fault tolerance as characteristic parameter, then through wavelet packet decomposition, extract feature entropy of wavelet packet in fault sensitivity band as input vector and finally, apply the Wrapper method of least square SVM to choose optimal character subset. The application in actual bearing fault diagnosis indicates the effectiveness of the proposed method in the article.
Co-Authors Yunjie Xu