Gearbox Composite Fault Diagnosis based on MRSVD Energy Characteristic and KFCM

A composite gearbox fault diagnosis method based on multi-resolution singular value decomposition (MRSVD) energy characteristic and fuzzy kernel clustering (KFCM) is proposed for the complex fault signal components of the gearbox and the difficulty in identifying fault characteristic. Firstly, the v...

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Bibliographic Details
Main Authors: Haiying Liang, Xin Xu, Hongxia Pan, Zhimin Fu
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2019-09-01
Series:Jixie chuandong
Subjects:
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2019.09.022
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Summary:A composite gearbox fault diagnosis method based on multi-resolution singular value decomposition (MRSVD) energy characteristic and fuzzy kernel clustering (KFCM) is proposed for the complex fault signal components of the gearbox and the difficulty in identifying fault characteristic. Firstly, the vibration signal of the gearbox under different working conditions is acquired to obtain a similar signal and five detail signals by performing MRSVD decomposition. Then, the energy characteristic of the six component signals are extracted and normalized to obtain the relative value of the energy. Finally, KFCM is used for fault diagnosis. The experimental results show that the MRSVD energy characteristic extraction method can effectively extract the composite fault characteristic of the gearbox, and KFCM can accurately diagnose the gearbox composite fault.
ISSN:1004-2539