1 |
YAN B, MA X, YANG L, et al. A novel degradation-rate-volatility related effect Wiener process model with its extension to accelerated ageing data analysis[J]. Reliability Engineering & System Safety, 2020, 204: 107138.
|
2 |
TANG S J, GUO X S, YU C Q, et al. Real time remaining useful life prediction based on nonlinear Wiener based degradation processes with measurement errors[J]. Journal of Central South University, 2014, 21(12): 4509-4517.
|
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, 2021, 17(7): 4521-4531.
|
4 |
李天梅, 司小胜, 张建勋. 多源传感监测线性退化设备数模联动的剩余寿命预测方法[J]. 航空学报, 2023, 44(8): 227190.
|
|
LI T M, SI X S, ZHANG J X. Data-model interactive remaining useful life prediction method for multi-sensor monitored linear stochastic degrading devices[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(8): 227190 (in Chinese).
|
5 |
HU G, XU Z Q, WANG G R, et al. Forecasting energy consumption of long-distance oil products pipeline based on improved fruit fly optimization algorithm and support vector regression[J]. Energy, 2021, 224: 120153.
|
6 |
LIU D, WANG S Q. Reliability estimation from lifetime testing data and degradation testing data with measurement error based on evidential variable and Wiener process[J]. Reliability Engineering & System Safety, 2021, 205: 107231.
|
7 |
WANG X, WANG B X, JIANG P H, et al. Accurate reliability inference based on Wiener process with random effects for degradation data[J]. Reliability Engineering & System Safety, 2020, 193: 106631.
|
8 |
ZHENG Z X, SI X S, HU C H, 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.
|
9 |
SI X S, WANG W B, 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.
|
10 |
李天梅,司小胜,刘翔,等.大数据下数模联动的随机退化设备剩余寿命预测技术[J].自动化学报,2022,48(9):2119-2141.
|
|
LI T M, SI X S, LIU X, et al. Data-model interactive remaining useful life prediction technologies for stochastic degrading devices with big data[J]. Acta Automatica Sinica,2022,48(9):2119-2141 (in Chinese).
|
11 |
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.
|
12 |
BIAN L K, GEBRAEEL N. Computing and updating the first-passage time distribution for randomly evolving degradation signals[J]. IIE Transactions, 2012, 44(11): 974-987.
|
13 |
GEBRAEEL N, ELWANY A, PAN J. Residual life predictions in the absence of prior degradation knowledge[J]. IEEE Transactions on Reliability, 2009, 58(1): 106-117.
|
14 |
TSAI C C, TSENG S T, BALAKRISHNAN N. Mis-specification analyses of gamma and Wiener degradation processes[J]. Journal of Statistical Planning and Inference, 2011, 141(12): 3725-3735.
|
15 |
PENG W, LI Y F, YANG Y J, et al. Inverse Gaussian process models for degradation analysis: A Bayesian perspective[J]. Reliability Engineering & System Safety, 2014, 130: 175-189.
|
16 |
任子强, 司小胜, 胡昌华, 等. 融合多传感器数据的发动机剩余寿命预测方法[J]. 航空学报, 2019, 40(12): 223312.
|
|
REN Z Q, SI X S, HU C H, et al. Remaining useful life prediction method for engine combining multi-sensors data[J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(12): 223312 (in Chinese).
|
17 |
LIU D, WANG S, ZHANG C. Reliability estimation by fusing multiple-source information based on evidential variable and Wiener process[J]. Computers & Industrial Engineering, 2021, 162: 107745.
|
18 |
董青,郑建飞,胡昌华,等.考虑随机冲击影响的自适应Wiener过程剩余寿命预测方法[J].航空学报,2022,43(9): 225914.
|
|
DONG Q, ZHENG J F, HU C H, et al. Remaining useful life prediction for adaptive Wiener process method with random shock [J]. Acta Aeronautica et Astronautica Sinica, 2022, 43(9): 225914 (in Chinese).
|
19 |
杨家鑫, 唐圣金, 李良, 等. 基于隐含非线性维纳退化过程的剩余寿命预测[J/OL]. 北京航空航天大学学报, (2022-05-30) [2022-06-22]. .
|
|
YANG J X, TANG S J, LI L, et al. Remaining useful life prediction based on implicit nonlinear Wiener degradation process [J/OL]. Journal of Beijing University of Aeronautics and Astronautics, (2022-05-30) [2022-06-22]. (in Chinese).
|
20 |
郑建飞, 胡昌华, 司小胜, 等. 考虑不确定测量和个体差异的非线性随机退化系统剩余寿命估计[J]. 自动化学报, 2017, 43(2): 259-270.
|
|
ZHENG J F, HU C H, SI X S, et al. Remaining useful life estimation for nonlinear stochastic degrading systems with uncertain measurement and unit-to-unit variability[J]. Acta Automatica Sinica, 2017, 43(2): 259-270 (in Chinese).
|
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 |
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.
|
23 |
WANG X, HU C H, SI X S, et al. An adaptive prognostic approach for newly developed system with three-source variability[J]. IEEE Access, 2019, 7: 53091-53102.
|
24 |
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.
|
25 |
HUANG Z Y, XU Z G, WANG W H, et al. Remaining useful life prediction for a nonlinear heterogeneous Wiener process model with an adaptive drift[J]. IEEE Transactions on Reliability, 2015, 64(2): 687-700.
|
26 |
FENG L, WANG H L, SI X S, et al. A state-space-based prognostic model for hidden and age-dependent nonlinear degradation process[J]. IEEE Transactions on Automation Science and Engineering, 2013, 10(4): 1072-1086.
|
27 |
TANG S J, YU C Q, 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.
|
28 |
CAI Z Y, CHEN Y X, ZHANG Q, et al. Residual lifetime prediction model of nonlinear accelerated degradation data with measurement error[J]. Journal of Systems Engineering and Electronics, 2017, 28(5): 1028-1038.
|
29 |
TANG S J, XU X D, YU C Q, et al. Remaining useful life prediction with fusing failure time data and field degradation data with random effects[J]. IEEE Access, 2019, 8: 11964-11978.
|
30 |
WANG L, PAN R, LI X, et al. A Bayesian reliability evaluation method with integrated accelerated degradation testing and field information[J]. Reliability Engineering & System Safety, 2013, 112: 38-47.
|
31 |
PANG Z N, SI X S, HU C H, et al. A Bayesian inference for remaining useful life estimation by fusing accelerated degradation data and condition monitoring data[J]. Reliability Engineering & System Safety, 2021, 208: 107341.
|
32 |
ZHANG Y, JIA X, GUO B. Bayesian framework for satellite rechargeable lithium battery synthesizing bivariate degradation and lifetime data[J]. Journal of Central South University, 2018, 25(2): 418-431.
|
33 |
TANG S J, WANG W F, SUN X Y, et al. Unbiased parameters estimation and mis-specification analysis of Wiener process-based degradation model with random effects[J]. Applied Mathematical Modelling, 2022, 109: 134-160.
|
34 |
王凤飞, 唐圣金, 孙晓艳, 等. 考虑随机效应的多源信息融合剩余寿命预测[J/OL]. 北京航空航天大学学报, (2022-03-01) [2022-06-22]. .
|
|
WANG F F, TANG S J, SUN X Y, et al. Remaining useful life prediction based on multi source information with considering random effects [J/OL]. Journal of Beijing University of Aeronautics and Astronautics, (2022-03-01) [2022-06-22]. (in Chinese).
|
35 |
CAI Z Y, WANG Z Z, CHEN Y X, et al. Remaining useful lifetime prediction for equipment based on nonlinear implicit degradation modeling[J]. Journal of Systems Engineering and Electronics, 2020, 31(1): 194-205.
|
36 |
SI X S, WANG W B, HU C H, et al. Estimating remaining useful life with three-source variability in degradation modeling[J]. IEEE Transactions on Reliability, 2014, 63(1): 167-190.
|
37 |
TANG S J, GUO X S, ZHOU Z J. Mis-specification analysis of linear Wiener process-based degradation models for the remaining useful life estimation[J]. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2014, 228(5): 478-487.
|
38 |
YANG J X, TANG S J, FANG P Y, et al. Remaining useful life prediction of implicit linear Wiener degradation process based on multi-source information[J/OL]. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, (2022-11-19) [2022-11-20], .
|
39 |
YE Z S, WANG Y, TSUI K L, et al. Degradation data analysis using Wiener processes with measurement errors[J]. IEEE Transactions on Reliability, 2013, 62(4): 772-780.
|
40 |
HAN Y Y, MA C L, TANG S J, et al. Residual life estimation of lithium-ion batteries based on nonlinear Wiener process with measurement error[J]. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2023, 237(1): 133-151.
|
41 |
万昌豪, 刘志国, 唐圣金, 等. 基于不完美先验信息的随机系数回归模型剩余寿命预测方法[J]. 北京航空航天大学学报, 2021, 47(12): 2542-2551.
|
|
WAN C H, LIU Z G, TANG S J, 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 (in Chinese).
|
42 |
PENG C Y, TSENG S T. Mis-specification analysis of linear degradation models[J]. IEEE Transactions on Reliability, 2009, 58(3): 444-455.
|
43 |
HONG S, YUE T Y, LIU H. Vehicle energy system active defense: A health assessment of lithium-ion batteries[J]. International Journal of Intelligent Systems, 2022, 37(12): 10081-10099.
|
44 |
JIN G, MATTHEWS D E, ZHOU Z. A Bayesian framework for on-line degradation assessment and residual life prediction of secondary batteries inspacecraft[J]. Reliability Engineering & System Safety, 2013, 113: 7-20.
|
45 |
LU C J, MEEKER W O. Using degradation measures to estimate a time-to-failure distribution[J]. Technometrics, 1993, 35(2): 161-174.
|
46 |
WANG X, BALAKRISHNAN N, GUO B. Residual life estimation based on a generalized Wiener degradation process[J]. Reliability Engineering & System Safety, 2014, 124: 13-23.
|