Accurate Diagnosis of Rolling Bearing Based on Wavelet Packet and RBF Neural Networks

WANG Guofeng; WANG Ziliang; QIN Xuda; WANG Taiyong

doi:10.13374/j.issn1001-053x.2004.02.018

Volume 26 Issue 2

Aug. 2021

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WANG Guofeng, WANG Ziliang, QIN Xuda, WANG Taiyong. Accurate Diagnosis of Rolling Bearing Based on Wavelet Packet and RBF Neural Networks[J]. Chinese Journal of Engineering, 2004, 26(2): 184-187. doi: 10.13374/j.issn1001-053x.2004.02.018

Citation:

WANG Guofeng, WANG Ziliang, QIN Xuda, WANG Taiyong. Accurate Diagnosis of Rolling Bearing Based on Wavelet Packet and RBF Neural Networks[J]. Chinese Journal of Engineering, 2004, 26(2): 184-187. doi: 10.13374/j.issn1001-053x.2004.02.018

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Accurate Diagnosis of Rolling Bearing Based on Wavelet Packet and RBF Neural Networks

doi: 10.13374/j.issn1001-053x.2004.02.018

1. Mechanical Engineering School, Tianjin University, Tianjin 300072, China;
2. Tianjin University of Technology, Tianjin 300191, China

Received Date: 2002-11-20
Available Online: 2021-08-16

Abstract

Abstract

The accurate diagnosis of rolling bearing was studied. The wavelet packet analysis was used to abstract the characteristic of signals. The signals were decomposed into eight frequency bands and the information in the high band was used as a characteristic vector. RBF neural networks were used to realize the map between the feature and diagnosis. The analysis of data sampled form a workshop testified correctness of the method proposed.
- wavelet packet,
- RBF neural network,
- rolling bearing,
- diagnosis