A predictive tool for remaining useful life estimation of rotating machinery components

Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference - DETC2005

Volumn 1 A, Issue , 2005, Pages 509-515

  Liao, Haitao ^a   Qiu, Hai ^a   Lee, Jay ^a   Lin, Daming ^b   Banjevic, Dragan ^b   Jardine, Andrew ^b  

^a UNIVERSITY OF CINCINNATI   (United States)

^b UNIVERSITY OF TORONTO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

MACHINE COMPONENTS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION;

HAZARDS MODELS; MULTIPLE DEGRADATION FEATURES; ROTATING MACHINERY COMPONENTS;

ROTATING MACHINERY;

EID: 33244457036     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1115/detc2005-84095     Document Type: Conference Paper

References (25)

1. Alguindigue, I. E., Loskiewicz-Buczak, A. and Uhrig, R. E., 1993, "Monitoring and diagnosis of rolling element bearings using artificial neural networks", IEEE Transactions on Industrial Electronics, Vol.40, pp.209-217.
2. Banjevic, D. and Jardine, A. K. S., 2005, "Calculation of reliability function and remaining useful life for a Markov failure time process", To appear in IMA Journal of Management Mathematics.
3. Chinnam, R. B., 1999, "On-line reliability estimation of individual components using degradation signal models", IEEE Transactions on Reliability, Vol.48, pp.403-412.
4. Chinnam, R. B. and Baruah, P., 2003, "Autonomous diagnostics and prognostics through competitive learning driven HMM-based clustering", in: Proceedings of the International Joint Conference on Neural Networks 2003, Vols. 1-4, New York, 2003, pp.2466-2471.
5. Chinnam, R. B. and Baruah, P., 2004, "A neuro-fuzzy approach for estimating mean residual life in condition-based maintenance systems", International Journal of Materials & Product Technology, Vol.20, pp.166-179.
6. Cox, D. R., 1972, "Regression models and life tables (with discussion)", Journal of the Royal Statistical Society, Series B, Vol.34, pp. 187-220.
7. Heng, R. B. W. and Nor, M. J. M., 1998, "Statistical analysis of sound and vibration signals for monitoring rolling element bearing condition", Applied Acoustics, Vol.53, pp.211-226.
8. Kalbfleisch, J. D. and Prentice, R. L., 2002, The Statistical Analysis of Failure Time Data, John Wiley & Sons, Hoboken, NJ.
9. Kwan, C., Zhang, X., Xu, R. and Haynes, L., 2003, "A novel approach to fault diagnostics and prognostics", in: 2003 IEEE International Conference on Robotics and Automation, Vols. 1-3, Proceedings, New York, 2003, pp.604-609.
10. Liao, H. T. and Elsayed, E. A., 2004, "Reliability prediction and test plan based on an accelerated degradation rate model", International Journal of Materials & F Technology, Vol.21, pp.402-422.
11. Lin, D. and Makis, V., 2004, "Filters and paramet mation for a partially observable system subject to random failure with continuous-range observations", Advances in Applied Probability, Vol.36, pp.1212-1230.
12. Liu, T. I., Singonahalli, J. H. and Iyer, N. R., 1996, "Detection of roller bearing defects using expert system and fuzzy logic", Mechanical Systems & Signal Processing, Vol.10, pp.595-614.
13. Lu, J. C. and Meeker, W. Q., 1993, "Using degradation measures to estimate a time-to-failure distribution", Technometrics, Vol.35, pp.161-174.
14. Lu, H., Kolarik, W. J. and Lu, S. S., 2001, "Real-time performance reliability prediction", IEEE Transactions on Reliability, Vol.50, pp.353-357.
15. Meeker, W. Q. and Escobar, L. A., 1998, Statistical Methods for Reliability Data, Wiley, New York.
16. Meeker, W. Q., Escobar, L. A. and Lu, J. C., 1998, 'Accelerated degradation tests: modeling arid analysis", Technometrics, Vol.40, pp.89-99.
17. Nelson, W., 1990, Accelerated Testing: Statistical Models, Test Plans and Data Analysis, Wiley, New York.
18. Qiu, H., Lee, J., Lin, J. and Yu, G., 2003, "Robust performance degradation assessment methods for enhanced rolling element bearing prognostics", Advanced Engineering Informatics, Vol.17, pp.127-140.
19. Rubini, R. and Meneghetti, U., 2001, "Application of the envelope and wavelet transform analyses for the diagnosis of incipient faults in ball bearings", Mechanical Systems and Signal Processing, Vol.15, pp.287-302.
20. Samanta, B. and Al-Balushi, K. R., 2003, "Artificial neural network based fault diagnostics of rolling element bearings using time-domain features", Mechanical Systems and Signal Processing, Vol.17, pp.317-328.
21. Tandon, N., 1994, "Comparison of some vibration parameters for the condition monitoring of rolling element bearings", Measurement: Journal of the International Measurement Confederation, Vol.12, pp.285-289.
22. Vlok, P.-J., Wnek, M. and Zygmunt, M., 2004, "Utilising statistical residual life estimates of bearings to quantify the influence of preventive maintenance actions", Mechanical Systems and Signal Processing, Vol.18, pp.833-847.
23. Wang, W., 2002, "A model to predict the residual life of rolling element bearings given monitored condition information to date", IMA Journal of Management Mathematics, Vol.13, pp.3-16.
24. Wang, W., Scarf, P. A. and Smith, M. A. J., 2000, "On the application of a model of condition-based maintenance", Journal of the Operational Research Society, Vol.51, pp.1218-1227.
25. Yan, J., Koc, M. and Lee, J., 2004, "A prognostic algorithm for machine performance assessment and its application", roduction Planning and Control, Vol.15, pp.796-801.