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不完美维护下基于剩余寿命预测信息的设备维护决策模型

裴洪 胡昌华 司小胜 张正新 杜党波

裴洪, 胡昌华, 司小胜, 张正新, 杜党波. 不完美维护下基于剩余寿命预测信息的设备维护决策模型. 自动化学报, 2018, 44(4): 719-729. doi: 10.16383/j.aas.2017.c160534
引用本文: 裴洪, 胡昌华, 司小胜, 张正新, 杜党波. 不完美维护下基于剩余寿命预测信息的设备维护决策模型. 自动化学报, 2018, 44(4): 719-729. doi: 10.16383/j.aas.2017.c160534
PEI Hong, HU Chang-Hua, SI Xiao-Sheng, ZHANG Zheng-Xin, DU Dang-Bo. Remaining Life Prediction Information-based Maintenance Decision Model for Equipment Under Imperfect Maintenance. ACTA AUTOMATICA SINICA, 2018, 44(4): 719-729. doi: 10.16383/j.aas.2017.c160534
Citation: PEI Hong, HU Chang-Hua, SI Xiao-Sheng, ZHANG Zheng-Xin, DU Dang-Bo. Remaining Life Prediction Information-based Maintenance Decision Model for Equipment Under Imperfect Maintenance. ACTA AUTOMATICA SINICA, 2018, 44(4): 719-729. doi: 10.16383/j.aas.2017.c160534

不完美维护下基于剩余寿命预测信息的设备维护决策模型

doi: 10.16383/j.aas.2017.c160534
基金项目: 

国家自然科学基金 61773386

国家自然科学基金 61573365

国家自然科学基金 61374126

国家自然科学基金 61473094

国家自然科学基金 61603398

国家自然科学基金 61573366

中国科协青年人才托举工程 2016QNRC001

详细信息
    作者简介:

    裴洪  火箭军工程大学控制工程系博士研究生.主要研究方向为预测与健康管理, 预测维护和寿命估计.E-mail:ph2010hph@sina.com

    司小胜  火箭军工程大学控制工程系博士研究生.主要研究方向为预测与健康管理, 剩余寿命估计, 可靠性与预测维护.E-mail:sxs09@mails.tsinghua.edu.cn

    张正新  火箭军工程大学控制工程系博士研究生.主要研究方向为预测与健康管理, 预测维护和寿命估计.E-mail:zhangzhengxin13@gmail.com

    杜党波  火箭军工程大学控制工程系博士研究生.主要研究方向为预测与健康管理, 预测维护和寿命估计.E-mail:ddb_efiort@126.com

    通讯作者:

    胡昌华  火箭军工程大学控制工程系教授.主要研究方向为故障诊断, 可靠性工程.本文通信作者.E-mail:hch6603@263.net

Remaining Life Prediction Information-based Maintenance Decision Model for Equipment Under Imperfect Maintenance

Funds: 

National Natural Science Foundation of China 61773386

National Natural Science Foundation of China 61573365

National Natural Science Foundation of China 61374126

National Natural Science Foundation of China 61473094

National Natural Science Foundation of China 61603398

National Natural Science Foundation of China 61573366

Young Elite Scientists Sponsorship Program of China Association for Science and Technology 2016QNRC001

More Information
    Author Bio:

     Ph. D. candidate in the Department of Automation Technology, Xi0an Institute of High Technology. His research interest covers prognostics and health management, predictive maintenance, and lifetime estimation

     Ph. D. candidate in the Department of Automation Technology, Xi0an Institute of High Technology. His research interest covers prognostics and health management, remaining useful life estimation, reliability and predictive maintenance

     Ph. D. candidate in the Department of Automation Technology, Xi0an Institute of High Technology. His research interest covers prognostics and health management, predictive maintenance, and lifetime estimation

     Ph. D. candidate in the Department of Automation Technology, Xi0an Institute of High Technology. His research interest covers prognostics and health management, predictive maintenance, and lifetime estimation

    Corresponding author: HU Chang-Hua  Professor in the Department of Automation Technology, Xi0an Institute of High Technology. His research interest covers fault diagnosis and reliability engineering. Corresponding author of this paper
  • 摘要: 基于剩余寿命预测信息进行设备维护决策的研究中,现有方法通常仅考虑不完美维护对退化量或退化率的单一影响,忽略了不完美维护对两者的双重影响.鉴于此,针对随机退化设备,提出一种考虑不完美维护影响的性能退化模型与维护决策模型,融合了维护活动对设备退化量和退化率的双重影响.首先基于Wiener过程分阶段构建存在不完美维护干预的随机退化模型,在首达时间的意义下推导出剩余寿命的解析概率分布;然后基于剩余寿命的预测结果,以检测间隔和预防性维护阈值为决策变量建立维护决策模型;最后数值仿真实验验证了本文模型的有效性,并对费用参数进行了敏感性分析.实验结果表明本文模型具有潜在的工程应用价值.
    1)  本文责任编委 文成林
  • 图  1  不完美维护干预下的设备退化轨迹

    Fig.  1  Degradation trajectory under the influence of imperfect maintenance

    图  2  预防性替换过程

    Fig.  2  Process of the preventive replacement

    图  3  预防性替换过程

    Fig.  3  Process of the preventive maintenance

    图  4  模型1的决策变量与长期期望维护费用率的关系

    Fig.  4  Relationship between the decision variables of model 1 and long term expected maintenance cost rate

    图  5  模型2的决策变量与长期期望维护费用率的关系

    Fig.  5  Relationship between the decision variables of model 2 and long term expected maintenance cost rate

    图  6  检测费用与最优维护策略及最优长期期望维护费用率的关系

    Fig.  6  Relationship between preventive maintenance cost and maintenance policy with the optimal long term expected maintenance cost rate

    图  7  预防性维护费用与最优维护策略及最优长期期望维护费用率的关系

    Fig.  7  Relationship between monitoring cost and maintenance policy with the optimal long term expected maintenance cost rate

    图  8  预防性替换费用与最优维护策略及最优长期期望维护费用率的关系

    Fig.  8  Relationship between preventive replacement cost and maintenance policy with the optimal long term expected maintenance cost rate

    表  1  相关费用参数

    Table  1  Cost parameters

    参数${C_i}$${C_p}$${C_r}$${C_f}$
    费用(/元)550200500
    下载: 导出CSV
  • [1] Pecht M G. Prognostics and Health Management of Electronics. New Jersey, USA: John Wiley, 2008.
    [2] 周东华, 魏慕恒, 司小胜.工业过程异常检测、寿命预测与维修决策的研究进展.自动化学报, 2013, 39(6):711-722 http://www.aas.net.cn/CN/abstract/abstract18097.shtml

    Zhou Dong-Hua, Wei Mu-Heng, Si Xiao-Sheng. A survey on anomaly detection, life prediction and maintenance decision for industrial processes. Acta Automatica Sinica, 2013, 39(6):711-722 http://www.aas.net.cn/CN/abstract/abstract18097.shtml
    [3] 程志君, 郭波.基于半Markov决策过程的劣化系统检测与维修优化模型.自动化学报, 2007, 33(10):1101-1104 http://www.aas.net.cn/CN/abstract/abstract13421.shtml

    Cheng Zhi-Jun, Guo-Bo. Optimization of inspection and maintenance policy for deteriorating system with semi-Markov decision process. Acta Automatica Sinica, 2007, 33(10):1101-1104 http://www.aas.net.cn/CN/abstract/abstract13421.shtml
    [4] Guo C M, Wang W B, Guo B, Si X S. A maintenance optimization model for mission-oriented systems based on Wiener degradation. Reliability Engineering and System Safety, 2013, 111:183-194 doi: 10.1016/j.ress.2012.10.015
    [5] 涂慧玲, 张胜贵, 司书宾, 兑红炎.面向维修过程的多态混联系统综合重要度计算方法.自动化学报, 2014, 40(1):126-134 http://www.aas.net.cn/CN/abstract/abstract18273.shtml

    Tu Hui-Ling, Zhang Sheng-Gui, Si Shu-Bin, Dui Hong-Yan. The integrated importance measure of multi-state compound systems for maintenance processes. Acta Automatica Sinica, 2014, 40(1):126-134 http://www.aas.net.cn/CN/abstract/abstract18273.shtml
    [6] Zhang M M, Gaudoin O, Xie M. Degradation-based maintenance decision using stochastic filtering for systems under imperfect maintenance. European Journal of Operational Research, 2015, 245(2):531-541 doi: 10.1016/j.ejor.2015.02.050
    [7] Zhang M M, Ye Z S, Xie M. A condition-based maintenance strategy for heterogeneous populations. Computers and Industrial Engineering, 2014, 77:103-114 doi: 10.1016/j.cie.2014.09.001
    [8] 徐晓滨, 张镇, 李世宝, 文成林.基于诊断证据静态融合与动态更新的故障诊断方法.自动化学报, 2016, 42(1):107-121 http://www.aas.net.cn/CN/abstract/abstract18800.shtml

    Xu Xiao-Bin, Zhang Zhen, Li Shi-Bao, Wen Cheng-Lin. Fault diagnosis based on fusion and updating of diagnosis evidence. Acta Automatica Sinica, 2016, 42(1):107-121 http://www.aas.net.cn/CN/abstract/abstract18800.shtml
    [9] 高文科, 张志胜, 周一帆, 刘飏, 刘祺.存在故障相关及不完备检测的主辅并联系统可靠性建模与维修策略.自动化学报, 2015, 41(12):2100-2114 http://www.aas.net.cn/CN/abstract/abstract18783.shtml

    Gao Wen-Ke, Zhang Zhi-Sheng, Zhou Yi-Fan, Liu Yang, Liu Qi. Reliability modeling and maintenance policy for main and supplementary parallel system with failure interaction and imperfect detection. Acta Automatica Sinica, 2015, 41(12):2100-2114 http://www.aas.net.cn/CN/abstract/abstract18783.shtml
    [10] Pham H, Wang H Z. Imperfect maintenance. European Journal of Operational Research, 1996, 94(3):425-438 doi: 10.1016/S0377-2217(96)00099-9
    [11] Mercier S, Castro I T. On the modelling of imperfect repairs for a continuously monitored gamma wear process through age reduction. Journal of Applied Probability, 2013, 50(4):1057-1076 doi: 10.1239/jap/1389370099
    [12] Van P D, Voisin A, Levrat E, Lung B. Remaining useful life based maintenance decision making for deteriorating systems with both perfect and imperfect maintenance actions. In: Proceedings of the 2013 IEEE Conference on Prognostics and Health Management. Gaithersburg, MD, USA: IEEE, 2013. 1-9
    [13] Castro I T. A model of imperfect preventive maintenance with dependent failure modes. European Journal of Operational Research, 2009, 196(1):217-224 doi: 10.1016/j.ejor.2008.02.042
    [14] Wang Z Q, Hu C H, Wang W B, Si X S. A simulation-based remaining useful life prediction method considering the influence of maintenance activities. In: Proceedings of the 2014 Prognostics and System Health Management Conference. Zhangjiajie, China: IEEE, 2014. 284-289
    [15] Khatab A. Hybrid hazard rate model for imperfect preventive maintenance of systems subject to random deterioration. Journal of Intelligent Manufacturing, 2015, 26(3):601 -608 doi: 10.1007/s10845-013-0819-x
    [16] Kijima M. Some results for repairable systems with general repair. Journal of Applied Probability, 1989, 26(1):89-102 doi: 10.2307/3214319
    [17] Nakagawa T. Sequential imperfect preventive maintenance policies. IEEE Transactions on Reliability, 1988, 37(3):295 -298 doi: 10.1109/24.3758
    [18] Zhou X J, Xi L F, Lee J. Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation. Reliability Engineering and System Safety, 2007, 92(4):530-534 doi: 10.1016/j.ress.2006.01.006
    [19] Si X S, Wang W B, Hu C H, Zhou D H. Remaining useful life estimation——a review on the statistical data driven approaches. European Journal of Operational Research, 2011, 213(1):1-14 doi: 10.1016/j.ejor.2010.11.018
    [20] Van P D, Bérenguer C. Condition-based maintenance with imperfect preventive repairs for a deteriorating production system. Quality and Reliability Engineering International, 2012, 28(6):624-633 doi: 10.1002/qre.v28.6
    [21] 司小胜, 胡昌华, 周东华.带测量误差的非线性退化过程建模与剩余寿命估计.自动化学报, 2013, 39(5):530-541 http://www.aas.net.cn/CN/abstract/abstract17879.shtml

    Si Xiao-Sheng, Hu Chang-Hua, Zhou Dong-Hua. Nonlinear degradation process modeling and remaining useful life estimation subject to measurement error. Acta Automatica Sinica, 2013, 39(5):530-541 http://www.aas.net.cn/CN/abstract/abstract17879.shtml
    [22] Huang Z Y, Xu Z G, Ke X J, Wang W H, Sun Y X. Remaining useful life prediction for an adaptive skew-Wiener process model. Mechanical Systems and Signal Processing, 2017, 87:294-306 doi: 10.1016/j.ymssp.2016.10.027
    [23] 葛恩顺, 李庆民, 张光宇, 杨美玲.考虑不完全维修的劣化系统最优视情维修策略.航空学报, 2013, 34(2):316-324 http://www.cnki.com.cn/Article/CJFDTOTAL-YCXX201304004.htm

    Ge En-Shun, Li Qing-Min, Zhang Guang-Yu, Yang Mei-Ling. Optimization of condition-based maintenance for degradation systems under imperfect maintenance. Acta Aeronautica et Astronautica Sinica, 2013, 34(2):316-324 http://www.cnki.com.cn/Article/CJFDTOTAL-YCXX201304004.htm
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出版历程
  • 收稿日期:  2016-07-18
  • 录用日期:  2016-11-08
  • 刊出日期:  2018-04-20

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