Blind vibration component separation and nonlinear feature extraction applied to the nonstationary vibration signals for the gearbox multi-fault diagnosis-Reference-Cited by-同舟云学术

Blind vibration component separation and nonlinear feature extraction applied to the nonstationary vibration signals for the gearbox multi-fault diagnosis

Published:2013-01 Issue:1 Volume:46 Page:259-271
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Li Zhixiong,Yan Xinping,Tian Zhe,Yuan Chengqing,Peng Zhongxiao,Li Li

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference34 articles.

1. Virtual prototype and experimental research on gear multi-fault diagnosis using wavelet-autoregressive model and principal component analysis method;Li;Mechanical Systems and Signal Processing,2011

2. Diesel engine fuel injection monitoring using acoustic measurements and independent component analysis;Albarbar;Measurement,2010

3. A new data mining approach for gear crack level identification based on manifold learning;Li;Mechanika,2012

4. A novel intelligent gear fault diagnosis model based on EMD and multi-class TSVM;Shen;Measurement,2012

5. Fault diagnosis of rotating machinery based on auto-associative neural networks and wavelet transforms;Sanza;Journal of Sound and Vibration,2007

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