Remaining Useful Life Prediction for Hybrid Degradation System

Abstract

Abstract: In this paper, a hybrid Wienerbased model with stochastic and deterministic parameters is proposed for the degradation path involves an additive of linear and nonlinear part. The remaining useful life (RUL) is an approximant rendered in an explicit form based on the concept of the first hitting time (FHT), and the stochastic and deterministic parameters are estimated by Kalman filter and maximum likelihood estimation method respectively. At last, the effectiveness of the proposed method is proved by the gyro testing data.

Key words: degradation modeling； hybrid degradation systems； remaining useful life (RUL)

CLC Number:

DU Dangboa,HU Changhuaa,SI Xiaoshenga,ZHANG Zhengxina,ZHANG Weib. Remaining Useful Life Prediction for Hybrid Degradation System[J]. Journal of Shanghai Jiao Tong University, 2017, 51(7): 886-891.

References

［1］HU C H, ZHOU Z J, ZHANG J X, et al. A survey on life prediction of equipment［J］. Chinese Journal of Aeronautics, 2015, 28(1):2533.
［2］SI X S, WANG W, HU C H, et al. Remaining useful life estimation—A review on the statistical data driven approaches［J］. European Journal of Operational Research, 2011, 213(1):114.
［3］YE Z S, XIE M. Stochastic modelling and analysis of degradation for highly reliable products［J］. Applied Stochastic Models in Business & Industry, 2014, 31(1):1632.
［4］EKER O F, CAMCI F, GUCLU A, et al. A simple statebased prognostic model for railway turnout systems［J］. IEEE Transactions on Industrial Electronics, 2011, 58(5): 17181726.
［5］GEBRAEEL N Z, LAWLEY M A, LI R, et al. Residuallife distributions from component degradation signals: A Bayesian approach［J］. IIE Transactions, 2005, 37(6): 543557.
［6］SI X S, WANG W, HU C H, et al. A Wienerprocessbased degradation model with a recursive filter algorithm for remaining useful life estimation［J］. Mechanical Systems and Signal Processing, 2013, 35(1): 219237.
［7］SI X S, WANG W, HU C H, et al. Remaining useful life estimation based on a nonlinear diffusion degradation process［J］. IEEE Transactions on Reliability, 2012, 61(1): 5067.
［8］SI X S. An adaptive prognostic approach via nonlinear degradation modelling: Application to battery data［J］. IEEE Transactions on Industrial Electronics, 2015, 62(8):11.
［9］SI X S, HU C H, KONG X Y, et al. A residual storage life prediction approach for systems with operation state switches［J］. IEEE Transactions on Industrial Electronics, 2014， 61(11): 63046315.
［10］BIAN L, GEBRAEEL N. Computing and updating the firstpassage time distribution for randomly evolving degradation signals［J］. IIE Transactions, 2012, 44(11): 974987.
［11］YE Z S, TANG L C, XU H Y. A distributionbased systems reliability model under extreme shocks and natural degradation［J］. IEEE Transactions on Reliability, 2011, 60(1): 246256.
［12］LI J, FENG Q M, COIT D W. Modeling zoned shock effects on stochastic degradation in dependent failure processes［J］. IIE Transactions, 2015,47(5): 111.
［13］PENG Y, DONG M. A prognosis method using agedependent hidden semi—Markov model for equipment health prediction［J］. Mechanical Systems and Signal Processing, 2011, 25(1): 237252.
［14］WANG Z Q, HU C H, WANG W, et al. An additive Wiener processbased prognostic model for hybrid deteriorating systems［J］. IEEE Transactions on Reliability, 2014, 63(1): 208222.
［15］SI X S, WANG W B, CHENG M Y, et al. A degradation pathdependent approach for remaining useful life estimation with an exact and closedform solution［J］. European Journal of Operational Research, 2013, 226(1): 5366.

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