A Model-Based Method for Remaining Useful Life Prediction of Machinery

IEEE Transactions on Reliability

Volumn 65, Issue 3, 2016, Pages 1314-1326

  Lei, Yaguo ^a   Li, Naipeng ^a   Gontarz, Szymon ^b   Lin, Jing ^a   Radkowski, Stanislaw ^b   Dybala, Jacek ^b  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b WARSAW UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Health indicator; parameter initialization; particle filtering; remaining useful life (RUL) prediction

Indexed keywords

BEARINGS (MACHINE PARTS); MACHINERY; MAXIMUM LIKELIHOOD; MAXIMUM LIKELIHOOD ESTIMATION; ROLLER BEARINGS;

ACCELERATED DEGRADATION TESTS; DEGRADATION PROCESS; MINIMUM QUANTIZATION ERRORS; MUTUAL INFORMATIONS; PREDICTIVE MAINTENANCE; REMAINING USEFUL LIFE PREDICTIONS; ROLLING ELEMENT BEARING; UNSCHEDULED MAINTENANCE;

FORECASTING;

EID: 84976510006     PISSN: 00189529     EISSN: None     Source Type: Journal    
DOI: 10.1109/TR.2016.2570568     Document Type: Article

References (40)

1. Y. G. Lei, J. Lin, Z. J. He, M. J. Zuo, "A review on empirical mode decomposition in fault diagnosis of rotating machinery, " Mech. Syst. Signal Process., vol. 35, nos. 12, pp. 108-126, Feb. 2013.
2. Y. G. Lei, Z. J. He, Y. Y. Zi, "Fault diagnosis of rotating machinery based on multiple ANFIS combination with GAs, " Mech. Syst. Signal Process., vol. 21, no. 5, pp. 2280-2294, Jul. 2007.
3. F. Q. Zhao, Z. G. Tian, E. Bechhoefer, Y. Zeng, "An integrated prognostics method under time-varying operating conditions, " IEEE Trans. Rel., vol. 64, no. 2, pp. 673-686, Jun. 2015.
4. Y. G. Lei, J. Lin, M. J. Zuo, Z. J. He, "Condition monitoring and fault diagnosis of planetary gearboxes: A review, " Meas., vol. 48, pp. 292-305, 2014.
5. J. Lee, F. J. Wu, W. Y. Zhao, M. Ghaffari, L. X. Liao, D. Siegel, "Prognostics and health management design for rotary machinery systems-Reviews, methodology and applications, " Mech. Syst. Signal Process., vol. 42, nos. 12, pp. 314334, Jan. 2014.
6. L. R. Cui, S. Du, A. G. Hawkes, "A study on a single-unit repairable system with state aggregations, " IIE Trans., vol. 44, pp. 10221032, 2012.
7. X. F. Zhao, T. Nakagawa, M. J. Zuo, "Optimal replacement last with continuous and discrete policies, " IEEE Trans. Rel., vol. 63, no. 4, pp. 868880, Dec. 2014.
8. Z. Q. Wang, W. B. Wang, C. H. Hu, X. S. Si, W. Zhang, "A prognosticinformation-based order-replacement policy for a non-repairable critical system in service, " IEEE Trans. Rel., vol. 64, no. 2, pp. 721735, Jun. 2015.
9. J. Liu, W. Wang, F. Ma, Y. B. Yang, C. S. Yang, "A data-model-fusion prognostic framework for dynamic system state forecasting, " Eng. Appl. Artif. Intell., vol. 25, no. 4, pp. 814-823, Jun. 2012.
10. J. Liu, W. Wang, F. Golnaraghi, "Amulti-step predictorwith a variable input pattern for system state forecasting, " Mech. Syst. Signal Process., vol. 23, pp. 1586-1599, 2009.
11. Z. Y. Huang, Z. G. Xu, W. H. Wang, Y. X. Sun, "Remaining useful life prediction for a nonlinear heterogeneous Wiener process model with an adaptive drift, " IEEE Trans. Rel., vol. 64, no. 2 pp. 687-700, Jun. 2015.
12. H. Hanachi, J. Liu, A. Banerjee, Y. Chen, A. Koul, "A physics-based modeling approach for performance monitoring in gas turbine engines, " IEEE Trans. Rel., vol. 64, no. 1, pp. 197-205, Mar. 2015.
13. H. Y. Dui, S. B. Si, M. J. Zuo, S. D. Sun, "Semi-Markov process-based integrated importance measure for multi-state systems, " IEEE Trans. Rel., vol. 64, no. 2, pp. 754765, Jun. 2015.
14. L. R. Cui, Y. Xu, X. Zhao, "Developments and applications of the finite Markov chain imbedding approach in reliability, " IEEE Trans. Rel., vol. 59, no. 4, pp. 685690, Dec. 2010.
15. X. S. Si, W. B. Wang, M. Y. Chen, C. H. Hu, D. H. Zhou, "A degradation path-dependent approach for remaining useful life estimation with an exact and closed-form solution, " Eur. J. Oper. Res., vol. 226, no. 1, pp. 5366, Apr. 2013.
16. X. S. Si, W. B. Wang, C. H. Hu, D. H. Zhou, M. G. Pecht, "Remaining useful life estimation based on a nonlinear diffusion degradation process, " IEEE Trans. Rel., vol. 61, no. 1, pp. 5067, Mar. 2012.
17. J. B. Yu, "Health degradation detection and monitoring of lithium-ion battery based on adaptive learning method, " IEEE Trans. Instrum. Meas., vol. 63, no. 7, pp. 1709-1721, Jul. 2014.
18. J. B. Yu, "A nonlinear probabilistic method and contribution analysis for machine condition monitoring, " Mech. Syst. Signal Process., vol. 37, no. 1, pp. 293-314, 2013.
19. F. Camci, K. Medjaher, N. Zerhouni, P. Nectoux, "Feature evaluation for effective bearing prognostics, " Quality Rel. Eng. Int., vol. 29, no. 4, pp. 477-486, 2013.
20. R. Li andD. He, "Rotationalmachine health monitoring and fault detection using EMD-based acoustic emission feature quantification, " IEEE Trans. Instrum. Meas., vol. 61, no. 4, pp. 9901001, Apr. 2012.
21. Y. N. Qian, S. J. Hu, R. Q. Yan, "Bearing performance degradation evaluation using recurrence quantification analysis and auto-regression model, " in Proc. IEEE Int. Conf. Instrum. Meas. Tech., Minneapolis, MN, USA, May 69, 2013, pp. 17131716.
22. H. Qiu, J. Lee, J. Lin, G. Yu, "Robust performance degradation assessmentmethods for enhanced rolling element bearing prognostics, " Adv. Eng. Inform., vol. 17, no. 34, pp. 127140, Jul. 2003.
23. R. Q. Huang, L. F. Xi, X. L. Li, C. R. Liu, H. Qiu, J. Lee, "Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods, " Mech. Syst. Signal Process., vol. 21, no. 1, pp. 193207, Jan. 2007.
24. J. B. Yu, "Health condition monitoring of machines based on hidden Markov model and contribution analysis, " IEEE Trans. Instrum. Meas., vol. 61, no. 8, pp. 22002211, Aug. 2012.
25. M. S. Arulampalam, S. Maskell, N. Gordon, T. Clapp, "A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, " IEEE Trans. Signal Process., vol. 50, no. 2, pp. 174-188, Feb. 2002.
26. A. Doucet, N. D. Freitas, N. Gordon, "An introduction to sequential Monte Carlo methods, " in Sequential Monte Carlo Methods in Practice, New York, NY, USA: Springer, 2001, ch. 1, pp. 3-14.
27. M. E. Orchard, B. Wu, G. Vachtsevanos, "A particle filtering framework for failure prognosis, " in Proc. World Tribology Congr. III, 2005, pp. 883-884.
28. D. An, J. H. Choi, N. H. Kim, "Prognostics 101: A tutorial for particle filter-based prognostics algorithm using Matlab, " Rel. Eng. Syst. Safety, vol. 115, pp. 161169, 2013.
29. C. C. Chen, G. Vachtsevanos, M. E. Orchard, "Machine remaining useful life prediction: An integrated adaptive neuro-fuzzy and highorder particle filtering approach, " Mech. Syst. Signal Process., vol. 28, pp. 597607, Apr. 2012.
30. M. Corbetta, C. Sbarufatti, A. Manes, M. Giglio, "Real-time prognosis of crack growth evolution using sequential Monte Carlo methods and statistical model parameters, " IEEE Trans. Rel., vol. 64, no. 2, pp. 736-753, Jun. 2015.
31. M. E. Orchard, P. Hevia-Koch, B. Zhang, L. Tang, "Risk measures for particle-filtering-based state-of-charge prognosis in lithium-ion batteries, " IEEE Trans. Ind. Electron., vol. 60, no. 11, pp. 5260-5269, Nov. 2013.
32. P. C. Paris and F. Erdogan, "A critical analysis of crack propagation laws, " J. Fluids Eng., vol. 85, no. 4, pp. 528-533, 1963.
33. C. Spearman, "The proof and measurement of association between two things, " Amer. J. Psychol., vol. 15, no. 1, pp. 72101, 1904.
34. K. Javed, R. Gouriveau, N. Zerhouni, P. Nectoux, "Enabling health monitoring approach based on vibration data for accurate prognostics, " IEEE Trans. Ind. Electron., vol. 62, no. 1, pp. 647656, Jan. 2015.
35. M. K. Pakhira, S. Bandyopadhyay, U. Maulik, "Validity index for crisp and fuzzy clusters, " Pattern Recog., vol. 37, pp. 487501, 2004.
36. Y. G. Lei, Z. J. He, Y. Y. Zi, Q. Hu, "Fault diagnosis of rotating machinery based on a newhybrid clustering algorithm, " Int. J. Adv. Manuf. Technol., vol. 35, no. 9-10, pp. 968-977, 2006.
37. P. Nectoux, R. Gouriveau, K. Medjaher, E. Ramasso, B. Chebel-Morello et al., "PRONOSTIA: An experimental platform for bearings accelerated degradation tests, " in Proc. Int. Conf. Prognost. Health Manage., Jun. 18-21, 2012, pp. 1-8.
38. Y. G. Lei and M. J. Zuo, "Gear crack level identification based on weighted K nearest neighbor classification algorithm, " Mech. Syst. Signal Process., vol. 23, no. 5, pp. 15351547, 2009.
39. S. Hong, Z. Zhou, E. Zio, K. Hong, "Condition assessment for the performance degradation of bearing based on a combinatorial feature extraction method, " Digit. Signal Process., vol. 27, pp. 159166, 2014.
40. E. Sutrisno, H. Oh, A. S. S. Vasan, M. Pecht, "Estimation of remaining useful life of ball bearings using data driven methodologies, " in Proc. Int. Conf. Prognost. Health Manage., June 18-21, 2012, pp. 1-7.