考虑随机冲击影响的自适应Wiener过程剩余寿命预测方法

doi:10.7527/S1000-6893.2022.25914

Abstract

Abstract: The existing method for predicting the Remaining Useful Life (RUL) of the degraded equipment with random shock is not suitable for the situation with uneven measurement intervals and inconsistent measurement frequencies. This type of method also ignores the variability of adaptive drift in the future degradation process. In view of this, based on the adaptive Wiener process, this paper proposes a RUL prediction method for the non-linearly degraded equipment with random shock. Firstly, the normal distribution is used to describe the influence of random shock on equipment degradation, and an adaptive Wiener process degradation model considering random shock is established. Then, the analytical expression of RUL is derived in the sense of the first arrival time. Considering the variability of degradation drift and the influence of random impact on the degradation rate, a state space model is developed to realize online update of equipment RUL, and the model parameter estimation is conducted based on expectation maximization algorithm. Finally, numerical simulation, inertial navigation system gyroscope and lithium battery examples verify the effectiveness and practicability of the proposed method from different angles.

Key words: random shock, adaptive Wiener process, normal distribution, expectation maximization, remaining useful life

CLC Number:

V240.2

DONG Qing, ZHENG Jianfei, HU Changhua, YU Tonghui, MU Hanxiao. Remaining useful life prediction for adaptive Wiener process method with random shock[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 225914-225914.

References

[1] LU N Y, CHEN C, JIANG B, et al. Latest progress on maintenance strategy of complex system: From condition-based maintenance to predictive maintenance[J]. Acta Automatica Sinica, 2021, 47(1): 1-17 (in Chinese). 陆宁云, 陈闯, 姜斌, 等. 复杂系统维护策略最新研究进展: 从视情维]护到预测性维护[J]. 自动化学报, 2021, 47(1): 1-17.
[2] WANG Z Z, CHEN Y X, CAI Z Y, et al. Equipment remaining useful lifetime online prediction based on accelerated degradation modeling with the proportion relationship[J]. Systems Engineering and Electronics, 2021, 43(2): 584-592 (in Chinese). 王泽洲, 陈云翔, 蔡忠义, 等. 基于比例关系加速退化建模的设备剩余寿命在线预测[J]. 系统工程与电子技术, 2021, 43(2): 584-592.
[3] HU J W, SUN Q Z, YE Z S, et al. Joint modeling of degradation and lifetime data for RUL prediction of deteriorating products[J]. IEEE Transactions on Industrial Informatics, 2020, 17(7): 4521-4531.
[4] WANG X, HU C H, REN Z Q, et al. Performance degradation modeling and remaining useful life prediction for aero-engine based on nonlinear Wiener process[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(2): 223291 (in Chinese). 王玺, 胡昌华, 任子强, 等. 基于非线性Wiener过程的航空发动机性能衰减建模与剩余寿命预测[J]. 航空学报, 2020, 41(2): 223291.
[5] YUAN Y, ZHANG Y, DING H. Research on key technology of industrial artificial intelligence and its application in predictive maintenance[J]. Acta Automatica Sinica, 2020, 46(10): 2013-2030 (in Chinese). 袁烨, 张永, 丁汉. 工业人工智能的关键技术及其在预测性维护中的应用现状[J]. 自动化学报, 2020, 46(10): 2013-2030.
[6] PECHT M G. Prognostics and Health Management of Electronics[M]. New York: John Wiley & Sons, Inc., 2008.
[7] CHAI T Y. Challenges of optimal control for plant-wide production processes in terms of control and optimization theories[J]. Acta Automatica Sinica, 2009, 35(6): 641-649 (in Chinese). 柴天佑. 生产制造全流程优化控制对控制与优化理论方法的挑战[J]. 自动化学报, 2009, 35(6): 641-649.
[8] SI X S, WANG W B, 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.
[9] ZHANG Y J, MA Y Z, OUYANG L H, et al. Reliability modeling and maintenance strategy for a single-unit system based on competing failure processes[J]. Systems Engineering and Electronics, 2017, 39(11): 2623-2630 (in Chinese). 张延静, 马义中, 欧阳林寒, 等. 基于竞争失效的单部件系统可靠性建模与维修[J]. 系统工程与电子技术, 2017, 39(11): 2623-2630.
[10] SUN F Q, LI Y H, CHENG Y Y. Competing failure modeling for degradation-shock dependence systems with shock toughness[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(12): 2195-2202 (in Chinese). 孙富强, 李艳宏, 程圆圆. 考虑冲击韧性的退化-冲击相依竞争失效建模[J]. 北京航空航天大学学报, 2020, 46(12): 2195-2202.
[11] WANG H W, XI W J, FENG Y G. Remaining life prediction based on competing risks of degradation failure and traumatic failure for missiles[J]. Acta Aeronautica et Astronautica Sinica, 2016, 37(4): 1240-1248 (in Chinese). 王浩伟, 奚文骏, 冯玉光. 基于退化失效与突发失效竞争的导弹剩余寿命预测[J]. 航空学报, 2016, 37(4): 1240-1248.
[12] WANG H W, GAO J, WU H Q. Residual remaining life prediction based on competing failures for aircraft engines[J]. Journal of Mechanical Engineering, 2014, 50(6): 197-205 (in Chinese). 王华伟, 高军, 吴海桥. 基于竞争失效的航空发动机剩余寿命预测[J]. 机械工程学报, 2014, 50(6): 197-205.
[13] BAI C, HU C H, SI X S, et al. Remaining useful life prediction method for degradation equipment with random shocks[J]. Systems Engineering and Electronics, 2018, 40(12): 2729-2735 (in Chinese). 白灿, 胡昌华, 司小胜, 等. 随机冲击影响的非线性退化设备剩余寿命预测[J]. 系统工程与电子技术, 2018, 40(12): 2729-2735.
[14] SI X S, WANG W, HU C H, et al. Remaining useful lifeestimation based on a nonlinear diffusion degradation process[J]. IEEE Transactionson Reliability, 2012, 61(1): 50-67.
[15] ZHAI Q Q, YE Z S. RUL prediction of deteriorating products using an adaptive Wiener process model[J]. IEEE Transactions on Industrial Informatics, 2017, 13(6): 2911-2921.
[16] NAKAGAWA T. Shock and damage models in reliability theory[M]. London: Springer, 2007.
[17] WANG J, LI Z G, BAI G H, et al. An improved model for dependent competing risks considering continuous degradation and random shocks[J]. Reliability Engineering & System Safety, 2020, 193: 106641.
[18] ZHANG J X, HU C H, HE X, et al. Lifetime prognostics for deteriorating systems with time-varying random jumps[J]. Reliability Engineering & System Safety, 2017, 167: 338-350.
[19] WANG Y P, PHAM H. Modeling the dependent competing risks with multiple degradation processes and random shock using time-varying copulas[J]. IEEE Transactions on Reliability, 2011, 61(1): 13-22.
[20] GAO H D, CUI L R, QIU Q G. Reliability modeling for degradation-shock dependence systems with multiple species of shocks[J]. Reliability Engineering & System Safety, 2019, 185: 133-143.
[21] SI X S, WANG W B, CHEN 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.
[22] ZHANG Z X, SI X S, HU C H, et al. An adaptive prognostic approach incorporating inspection influence for deteriorating systems[J]. IEEE Transactions on Reliability, 2018, 68(1): 302-316.
[23] LI X, DING Q, SUN J Q. Remaining useful life estimation in prognostics using deep convolution neural networks[J]. Reliability Engineering & System Safety, 2018, 172: 1-11.
[24] YAN T, LEI Y G, LI N P, et al. Degradation modeling and remaining useful life prediction for dependent competing failure processes[J]. Reliability Engineering & System Safety, 2021, 212: 107638.
[25] LISTOU ELLEFSEN A, BJØRLYKHAUG E, AESØY V, et al. Remaining useful life predictions for turbofan engine degradation using semi-supervised deep architecture[J]. Reliability Engineering & System Safety, 2019, 183: 240-251.
[26] SAHA B, GOEBEL K. Battery data set[EB/OL]. (2022-06-30)[2021-06-07]. http://www.nasa.gov/intelligent-systems-division.

Remaining useful life prediction for adaptive Wiener process method with random shock

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