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JDCTA
2010

A Method of Bearing Fault Feature Extraction Based on Improved Wavelet Packet and Hilbert Analysis

8 years 2 months ago
A Method of Bearing Fault Feature Extraction Based on Improved Wavelet Packet and Hilbert Analysis
In order to supply a gap of current resonance vibration and STFT demodulation method applied to rolling bearing fault feature extraction of city rail vehicle, a fault diagnosis method for rolling bearing is presented, which is based on the integration of improved wavelet packet, frequency energy analysis and Hilbert marginal spectrum. When faults occur in rolling bearing, the energy of the rolling bearing vibration signal would change correspondingly, while the Hilbert energy spectrum can exactly provide the energy distribution of the signal in certain frequency with the change of the time and frequency. Thus, the fault information of the rolling bearing can be extracted effectively from the improved wavelet packet and Hilbert energy spectrum. The experimental result proves that the fault characteristic extracted by improved wavelet packet and Hilbert transform is in accord with the one analyzed from theory, and the fault feature extraction method is effective. The research results pr...
Jian-wei Yang, De-chen Yao, Guo-qiang Cai, Hai-bo
Added 19 May 2011
Updated 19 May 2011
Type Journal
Year 2010
Where JDCTA
Authors Jian-wei Yang, De-chen Yao, Guo-qiang Cai, Hai-bo Liu, Jiao Zhang
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