Combined probability approach and indirect data-driven method for bearing degradation prognostics

IEEE Transactions on Reliability

Volumn 60, Issue 1, 2011, Pages 14-20

  Caesarendra, Wahyu ^a   Widodo, Achmad ^b   Thom, Pham Hong ^a   Yang, Bo Suk ^a   Setiawan, Joga Dharma ^b  

^a Pukyong National University   (South Korea)

^b DIPONEGORO UNIVERSITY   (Indonesia)

Author keywords

Autoregressive moving average; censored data; Dempster Shafer regression; generalized autoregressive conditional heteroscedasticity; prognostics; relevance vector machine; run to failure

Indexed keywords

AUTOREGRESSIVE MOVING AVERAGE; CENSORED DATA; DEMPSTER-SHAFER; GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY; PROGNOSTICS; RELEVANCE VECTOR MACHINE; RUN-TO-FAILURE;

BEARINGS (STRUCTURAL); DEGRADATION; FORECASTING; INTELLIGENT SYSTEMS; PROGRAM PROCESSORS; REGRESSION ANALYSIS; VECTORS;

STATISTICAL PROCESS CONTROL;

EID: 79952195720     PISSN: 00189529     EISSN: None     Source Type: Journal    
DOI: 10.1109/TR.2011.2104716     Document Type: Conference Paper

References (18)

1. A. K. S. Jardine, D. Lin, and D. Banjevic, "A reviewon machinery diagnostics and prognostics implementing condition-based maintenance," Mechanical Systems and Signal Processing, vol. 20, pp. 1483-1510, 2006.
2. A. Heng, S. Zhang, A. C. C. Tan, and J. Mathew, "Rotating machinery prognostics: State of the art, challenges and opportunities," Mechanical Systems and Signal Processing, vol. 23, pp. 724-739, 2009.
3. R. Khotamasu, S. H. Huang, and W. H. Ver Dui, "System health monitoring and prognostics-A review of current paradigms and practices," International Journal of Advanced Manufacturing and Technology, vol. 28, pp. 1012-1024, 1996.
4. H. H. Lee, N. T. Nguyen, and J. M. Kwon, "Bearing diagnosis using time-domain features and decision tree," in Lecture Notes in Computer Science. Berlin/Heidelberg, Germany: Springer, 2007.
5. X. Niu, L. Zhu, and H. Ding, "New statistical moments for the detection of defects in rolling elements bearing," International Journal of Advanced Manufacturing Technology, vol. 26, pp. 1268-1274, 2005. (Pubitemid 41539543)
6. H. R. Martin and F. Honarvar, "Application of statistical moments for the bearing failure detection," Applied Acoustic, vol. 44, pp. 67-77, 1995.
7. T.Williams, X. Ribadeneira, S. Billington, and T. Kurfess, "Rolling element bearing diagnostics in run-to-failure lifetime testing," Mechanical Systems and Signal Processing, vol. 15, pp. 979-993, 2001. (Pubitemid 33112622)
8. J.Yan, M.Koc, and J. Lee, "A prognostic algorithm for machine performance assessment and its application," Production Planning and Control, vol. 15, no. 8, pp. 796-801, 2004.
9. M. E. Tipping et al., "The relevance vector machine," in Advances in Neural Information Processing System, S. Solla, T. Leen, and K. R. Muller, Eds. Cambridge, MA: MIT Press, 2000, pp. 287-289.
10. M. E. Tipping, "Spare bayesian learning and the relevance vector machine," Journal of Machine Learning Research, vol. 1, pp. 211-244, 2001. (Pubitemid 33687203)
11. B. Schölkopf and A. J. Smola, Learning With Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press, 2002.
12. H. T. Pham and B. S. Yang, "Estimation and forecasting of machine health condition using ARMA/GARCH model," Mechanical Systems and Signal Processing, vol. 24, pp. 546-558, 2010.
13. P. D. McFadden and J. D. Smith, "Model for the vibration produced by a single point defect in rolling element bearing," Journal of Sound and Vibration, vol. 96, pp. 69-82, 1984. (Pubitemid 15421328)
14. Y. F.Wang and P. J. Kootsookos, "Modeling of lowshaft speed bearing faults for condition monitoring," Mechanical Systems and Signal Processing, vol. 12, no. 3, pp. 415-426, 1998. (Pubitemid 128379481)
15. N. Z. Gebraeel, M. A. Lawley, R. Li, and J. K. Ryan, "Residual-life distribution from component degradation signals: A Bayesian approach," IIE Transaction, vol. 37, pp. 543-557, 2005. (Pubitemid 40708863)
16. N. Gebraeel, "Sensory-updated residual life distribution for components with exponential degradation pattern," IEEE Trans. Automation Science and Engineering, vol. 3, no. 4, pp. 382-393, 2006. (Pubitemid 44574332)
17. W. Caesarendra, A. Widodo, and B. S. Yang, "Application of relevance vector machine and logistic regression for machine degradation assessment," Mechanical Systems and Signal Processing, vol. 24, pp. 1161-1171, 2010.
18. G. Niu and B. S. Yang, "Dempster-Shafer regression for multi-step ahead time series prediction towards data-driven machinery prognosis," Mechanical Systems and Signal Processing, vol. 23, pp. 740-751, 2009.