Fault detection of rolling element bearing based on principal component analysis

Proceedings of the 2012 24th Chinese Control and Decision Conference, CCDC 2012

Volumn , Issue , 2012, Pages 2944-2948

  Jiang, Liying ^a   Fu, Xinxin ^a   Cui, Jianguo ^a   Li, Zhonghai ^a  

^a SHENYANG AEROSPACE UNIVERSITY   (China)

Author keywords

Fault Detection; PCA; Rolling Bearing; Vibration Signals

Indexed keywords

BEARING FAULT DETECTION; DRIVE ENDS; FAULT DETECTION AND DIAGNOSIS; HIGH DIMENSIONAL SPACES; MECHANICAL SYSTEMS; ONE-DIMENSIONAL TIME SERIES; PCA; ROLLING BEARINGS; ROLLING ELEMENT BEARING; VIBRATION SIGNAL;

BALL BEARINGS; BEARINGS (MACHINE PARTS); DIGITAL STORAGE; FAULT DETECTION; MULTIVARIANT ANALYSIS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84866677920     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CCDC.2012.6243071     Document Type: Conference Paper

References (12)

1. IEEE Motor reliability working group, Report of Large Motor Reliability Survey of Industrial and Commercial Installations, IEEE Trans. Ind. Applicat. Vol. IA-21, No. 4, 853-872, 1985.
2. C. J. Li, J. Ma, Wavelet Decomposition of Vibrations for Detection of Bearing-Localized Defects, NDT&E International, Vol. 30, No. 3, pp. 143-149, 1997
3. Z. Huang, Y. Xie, Fault Diagnosis of Roller Bearing with Inner and External Fault Based on Hilbert transformation, Journal of Central South University (Science and Technology), Vol. 42, No.7, 1992-1996, 2011.
4. B. Li, M. Y. Chow, Y. Tipsuwan and C. J. Hung, Neural-network-based Motor Rolling Bearing Fault Diagnosis, IEEE Trans. on Industrial Electronics, Vol. 47, No. 5, 1060-1069, 2000.
5. H Ocak, K. A. Loparo, A New Bearing Fault Detection and Diagnosis Scheme Based on Hidden Markov Modeling of Vibration Signals, Acoustics, Speech, and Signal Processing, Vol.5, 3141-3144, 2001.
6. J. E. Jackson, A User's Guide to Principal Components, John Wiley, New York, 1991.
7. P. Normikos and J. F. MacGergor, Monitoring batch processes using multi-way principal component analysis, AIChE Journal, Vol. 40, No. 8, 1361-1375, 1994.
8. P. Normikos and J. F. MacGregor, Multi-way partial least squares in monitoring batch processes, Chemonetrics and Intelligent Laboratory Systems, vol. 30, No. 1, 97-108, 1995.
9. D. Dong and T. J. McAvoy, Batch tracking via nonlinare principal component analysis, American Institute of Chemical Engineering Journal, Vol 42, No. 8, 2199-2208, 1996.
10. S. Rännar, J. F. MacGregor and S. Wold, "Adaptive batch monitoring using hierarchical PCA", Chemometrica and Intelligent Laboratory Systems, vol 41, pp.73-81, 1998.
11. J. Chen and K. Liu, On-line batch process monitoring using dynamic PCA and dynamic PLS models, Chemical Engineering Science, vol. 57, 63-75, 2002.
12. L. Xu, J. M. Zhang, G. M. Zhang and W. Tu, A Method of Rolling Bearing Fault Detection Based on PCA, Computer Simulation, Vol. 27, No. 6, 325-329, 2010.