| Citation: | WAN Changhao, LIU Zhiguo, TANG Shengjin, et al. Remaining useful life prediction method based on random coefficient regression model with imperfect prior information[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(12): 2542-2551. doi: 10.13700/j.bh.1001-5965.2020.0439(in Chinese)
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Remaining Useful Life (RUL) prediction is a core problem of equipment prognostics and health management. Accurate RUL prediction can make effective maintenance management before the failure occurs to reduce the probability of equipment failure. A heuristic RUL prediction method is proposed to overcome the problem of imperfect prior information or lack of prior information in actual RUL prediction. First, the nonlinear Random Coefficient Regression (RCR) model is used for degradation modelling. Then, the relationship of the parameter estimation results between the Expected Maximization (EM) algorithm and the Maximum Likelihood Estimation (MLE) method based on the field degradation data of single equipment is studied and the conclusion that the result of EM algorithm finally converges to that of MLE method is obtained. Based on this conclusion, a heuristic RUL prediction method is proposed, which fuses both prior information and field information. Finally, the proposed results and algorithm are estimated by the numerical simulation data and practical degradation data of lithium battery. The experimental and simulation results show that, compared to the traditional Bayesian method, the heuristic RUL prediction method can overcome the impact of imperfect prior information and has higher prediction accuracy.
| [1] |
PENG R, MA X, ZHAI Q, et al. Software reliability growth model considering first-step and second-step fault dependency[J]. Journal of Shanghai Jiaotong University (Science), 2019, 24(4): 477-479. doi: 10.1007/s12204-019-2097-z
|
| [2] |
孙博, 康锐, 谢劲松. 故障预测与健康管理系统研究和应用现状综述[J]. 系统工程与电子技术, 2007, 29(10): 1762-1767. doi: 10.3321/j.issn:1001-506x.2007.10.042
SUN B, KANG R, XIE J S. Research and application of the prognostic and health management system[J]. Systems Engineering and Electronics, 2007, 29(10): 1762-1767(in Chinese). doi: 10.3321/j.issn:1001-506x.2007.10.042
|
| [3] |
PANG Z, HU C, SI X, et al. Nonlinear step-stress accelerated degradation modeling and remaining useful life estimation considering multiple sources of variability[J]. IEEE Access, 2019, 7: 124558-124575. doi: 10.1109/ACCESS.2019.2933854
|
| [4] |
雷亚国, 韩天宇, 王彪, 等. XJTU-SY滚动轴承加速寿命试验数据集解读[J]. 机械工程学报, 2019, 55(16): 1-6.
LEI Y G, HAN T Y, WANG B, et al. XJTU-SY rolling element bearing accelerated life test datasets: A tutorial [J]. Journal of Mechanical Engineering, 2019, 55(16): 1-6(in Chinese).
|
| [5] |
蔡忠义, 王泽洲, 张晓丰, 等. 隐含非线性退化设备的剩余寿命在线预测方法[J]. 系统工程与电子技术, 2020, 42(6): 1410-1416.
CAI Z Y, WANG Z Z, ZHANG X F, et al. Online prediction method of remaining useful lifetime for implicit nonlinear degradation equipment[J]. Systems Engineering and Electronics, 2020, 42(6): 1410-1416(in Chinese).
|
| [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(1-2): 219-237. doi: 10.1016/j.ymssp.2012.08.016
|
| [7] |
WANG D, KONG J Z, ZHAO Y, et al. Piecewise model based intelligent prognostics for state of health prediction of rechargeable batteries with capacity regeneration phenomena[J]. Measurement, 2019, 147: 106836. doi: 10.1016/j.measurement.2019.07.064
|
| [8] |
SI X S. Remaining useful life estimation: A review on the statistical data driven approaches [J]. European Journal of Operational Research, 2011, 213(1): 1-14. doi: 10.1016/j.ejor.2010.11.018
|
| [9] |
WANG D, YANG F, TSUI K L, et al. Remaining useful life prediction of lithium-ion batteries based on spherical cubature particle filter[J]. IEEE Transactions on Instrumentation and Measurement, 2016, 65(6): 1282-1291. doi: 10.1109/TIM.2016.2534258
|
| [10] |
FANG X, ZHOU R, GEBRAEEL N. An adaptive functional regression-based prognostic model for applications with missing data [J]. Reliability Engineering and System Safety, 2015, 133: 266-274. doi: 10.1016/j.ress.2014.08.013
|
| [11] |
JIANG R. An adaptive power-law degradation model for modelling wear processes[J]. Engineering Asset Management, 2016, 2018: 99-112.
|
| [12] |
ZHANG Z, SI X, HU C, et al. Degradation data analysis and remaining useful life estimation: A review on wiener-process-based methods[J]. European Journal of Operational Research, 2018, 271(3): 775-796. doi: 10.1016/j.ejor.2018.02.033
|
| [13] |
蔡忠义, 陈云翔, 张诤敏, 等. 非线性步进加速退化数据的可靠性评估方法[J]. 北京航空航天大学学报, 2016, 42(3): 576-582. doi: 10.13700/j.bh.1001-5965.2015.0459
CAI Z Y, CHEN Y X, ZHANG Z M, et al. Reliability assessment method of nonlinear step-stress accelerated degradation data [J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(3): 576-582(in Chinese). doi: 10.13700/j.bh.1001-5965.2015.0459
|
| [14] |
YE Z S. The inverse gaussian process as a degradation model[J]. Technometrics, 2014, 56(3): 302-311. doi: 10.1080/00401706.2013.830074
|
| [15] |
LI Q, GAO Z, TANG D, et al. Remaining useful life estimation for deteriorating systems with time-varying operational conditions and condition-specific failure zones[J]. Chinese Journal of Aeronautics, 2016, 29(3): 662-674. doi: 10.1016/j.cja.2016.04.007
|
| [16] |
WANG Z, WANG W, HU C, et al. A real-time prognostic method for the drift errors in the inertial navigation system by a nonlinear random-coefficient regression model[J]. Acta Astronautica, 2014, 103: 45-54. doi: 10.1016/j.actaastro.2014.06.034
|
| [17] |
LU C J, MEEKER W Q. Using degradation measures to estimate a time-to-failure distribution[J]. Technometrics, 1993, 35(2): 161-174. doi: 10.1080/00401706.1993.10485038
|
| [18] |
PENG C Y, TSHENG T. Mis-specification analysis of linear degradation models[J]. IEEE Transactions on Reliability, 2009, 58(3): 444-455. doi: 10.1109/TR.2009.2026784
|
| [19] |
PARK J I, BAE S J. Direct prediction methods on lifetime distribution of organic light-emitting diodes from accelerated degradation tests[J]. IEEE Transactions on Reliability, 2010, 59(1): 74-90. doi: 10.1109/TR.2010.2040761
|
| [20] |
BAE S J, KVAM P H. A nonlinear random-coefficients model for degradation testing[J]. Technometrics, 2004, 46(4): 460-469. doi: 10.1198/004017004000000464
|
| [21] |
GEBRAEEL N, ELWANY A, JING P. Residual life predictions in the absence of prior degradation knowledge[J]. IEEE Transactions on Reliability, 2009, 58(1): 106-117. doi: 10.1109/TR.2008.2011659
|
| [22] |
TANG S, YU C, WANG X, et al. Remaining useful life prediction of lithium-ion batteries based on the wiener process with measurement error[J]. Energies, 2014, 7(2): 520-547. doi: 10.3390/en7020520
|
| [23] |
WANG L, PAN R, LI X, et al. A Bayesian reliability evaluation method with integrated accelerated degradation testing and field information[J]. Reliability Engineering and System Safety, 2013, 112: 38-47. doi: 10.1016/j.ress.2012.09.015
|
| [24] |
WANG L, PAN R, WANG X, et al. A Bayesian reliability evaluation method with different types of data from multiple sources[J]. Reliability Engineering and System Safety, 2017, 167: 128-135. doi: 10.1016/j.ress.2017.05.039
|
| [25] |
TANG S, XU X, YU C, et al. Remaining useful life prediction with fusing failure time data and field degradation data with random effects[J]. IEEE Access, 2020, 8: 11964-11978. doi: 10.1109/ACCESS.2019.2948263
|
| [26] |
WANG W, CARR M, XU W, et al. A model for residual life prediction based on brownian motion with an adaptive drift[J]. Microelectronics Reliability, 2011, 51(2): 285-293. doi: 10.1016/j.microrel.2010.09.013
|
| [27] |
SI X S. An adaptive prognostic approach via nonlinear degradation modeling: Application to battery data[J]. IEEE Transactions on Industrial Electronics, 2015, 62(8): 5082-5096. doi: 10.1109/TIE.2015.2393840
|
| [28] |
WANG X, HU C, SI X, et al. An adaptive prognostic approach for newly developed system with three-source variability[J]. IEEE Access, 2019, 7: 53091-53102. doi: 10.1109/ACCESS.2019.2911307
|
| [29] |
WANG X, HU C, SI X, et al. An adaptive remaining useful life estimation approach for newly developed system based on nonlinear degradation model[J]. IEEE Access, 2019, 7: 82162-82173. doi: 10.1109/ACCESS.2019.2924148
|
| [30] |
LI N, LEI Y, LIN J, et al. An improved exponential model for predicting remaining useful life of rolling element bearings[J]. IEEE Transactions on Industrial Electronics, 2015, 62(12): 7762-7773. doi: 10.1109/TIE.2015.2455055
|
| [31] |
WANG H, MA X, ZHAO Y. A mixed-effects model of two-phase degradation process for reliability assessment and RUL prediction[J]. Microelectronics Reliability, 2020, 107: 113622. doi: 10.1016/j.microrel.2020.113622
|
| [32] |
WANG D, TSUI K L. Two novel mixed effects models for prognostics of rolling element bearings[J]. Mechanical Systems and Signal Processing, 2018, 99: 1-13. doi: 10.1016/j.ymssp.2017.06.004
|
| [33] |
ZHAI Q, YE Z S. Degradation in common dynamic environments[J]. Technometrics, 2018, 60(4): 461-471. doi: 10.1080/00401706.2017.1375994
|
| [34] |
JIN G, MATTHEWS D E, ZHOU Z. A Bayesian framework for online degradation assessment and residual life prediction of secondary batteries inspacecraft[J]. Reliability Engineering and System Safety, 2013, 113: 7-20. doi: 10.1016/j.ress.2012.12.011
|
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