An intelligent fault identification method of rolling bearings based on LSSVM optimized by improved PSO-Reference-Cited by-同舟云学术

An intelligent fault identification method of rolling bearings based on LSSVM optimized by improved PSO

Published:2013-02 Issue:1-2 Volume:35 Page:167-175
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Xu Hongbo,Chen Guohua

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference27 articles.

1. A comparison study of improved Hilbert–Huang transform and wavelet transform: application to fault diagnosis for rolling bearing;Peng;Mech. Syst. Signal Process.,2005

2. Rolling element bearing faults diagnosis based on optimal Morlet wavelet filter and autocorrelation enhancement;Su;Mech. Syst. Signal Process.,2010

3. Application of mother wavelet functions for automatic gear and bearing fault diagnosis;Rafiee;Expert Syst. Appl.,2010

4. Rolling element bearing fault detection based on optimal antisymmetric real Laplace wavelet;Feng;Measurement,2011

5. Varying compliance vibrations of rolling bearings;Sunnersjo;J. Sound Vib.,1978

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