Incipient fault diagnosis based on moving average and relevance vector machine

Zhendong yu Chongji/Journal of Vibration and Shock

Volumn 29, Issue 12, 2010, Pages 89-92

  He, Chuang Xin ^a   Li, Yan Ming ^a   Liu, Cheng Liang ^a   Liu, Hai Ning ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Condition monitoring; Fault diagnosis; Moving average; Relevance vector machine; Wavelet packet transform

Indexed keywords

CLASSIFICATION ACCURACY; FAULT DIAGNOSIS; FAULT DIAGNOSIS MODEL; FISHER CRITERION; GEAR FAULT DETECTION; INCIPIENT FAULT DIAGNOSIS; INTELLIGENT FAULT DIAGNOSIS; MOVING AVERAGE; MOVING AVERAGES; NODE ENERGY; ON-LINE FAULT DIAGNOSIS; OPTIMAL DECOMPOSITION; RELEVANCE VECTOR MACHINE; SVM(SUPPORT VECTOR MACHINE); WAVELET PACKET; WAVELET PACKET TRANSFORM; WAVELET PACKET TRANSFORMS;

CONDITION MONITORING; FEATURE EXTRACTION; OPTIMIZATION; VECTORS; WAVELET DECOMPOSITION;

FAULT DETECTION;

EID: 79851480008     PISSN: 10003835     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (10)

1. Yen G G, Lin K C. Wavelet packet feature extraction for vibration monitoring[J]. Ieee Transactions on Industrial Electronics, 2000. 47(3): 650-667.
2. 2009, 45(8): 80-88.
3. 2007, 26(7): 10-12.
4. Hu Q, et al. Fault diagnosis of rotating machinery based on improved wavelet package transform and SVMs ensemble[J]. Mechanical Systems and Signal Processing, 2007, 21(2): 688-705.
5. 2009, 28(6): 131-134.
6. Tipping M E. Sparse bayesian learning and the relevance vector machine[J]. Journal of Machine Learning Research, 2001, 1(3): 211-244.
7. Widodo A, et al. Fault diagnosis of low speed bearing based on relevance vector machine and support vector machine[J]. Expert Systems with Applications, 2009, 36(3, Part 2): 7252-7261.
8. 2008, 27(10): 6-9.
9. 2008, 27(6): 51-54.
10. Ypma A, et al. Pump vibration datasets, Pattern recognition group, Delft University of Technology. Download at http://www.aypma.nl/PhD/pump_sets.html.