工业过程异常检测、寿命预测与维修决策的研究进展

周东华; 魏慕恒; 司小胜

doi:10.3724/SP.J.1004.2013.00711

工业过程异常检测、寿命预测与维修决策的研究进展

doi: 10.3724/SP.J.1004.2013.00711

周东华^1,2, ,,
魏慕恒^1,2,
司小胜^{1,2 3}

1.
清华大学自动化系北京 100084;
2.
清华信息科学与技术国家实验室北京 100084;
3.
第二炮兵工程大学302教研室西安 710025

基金项目:

国家重点基础研究发展计划(973计划)(2010CB731800, 2009CB32 0602);国家自然科学基金(61210012, 61021063, 61290324, 611740 30)资助

详细信息

通讯作者:
周东华

计量
- 文章访问数: 3418
- HTML全文浏览量: 176
- PDF下载量: 4296
- 被引次数: 0
出版历程
- 收稿日期: 2012-12-28
- 修回日期: 2013-01-07
- 刊出日期: 2013-06-20

A Survey on Anomaly Detection, Life Prediction and Maintenance Decision for Industrial Processes

ZHOU Dong-Hua^{1,2
, ,},
WEI Mu-Heng^1,2,
SI Xiao-Sheng^{1,2 3}

1.
Department of Automation, Tsinghua University, Beijing 100084;
2.
National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084;
3.
Unit 302, Xi'an Institute of High-Technology, Xi'an 710025

Funds:

Supported by National Basic Research Program of China(973 Program)(2010CB731800, 2009CB320602)and National Natural Science Foundation of China(61210012, 61021063, 61290324, 61174030)

摘要

摘要: 作为保障工业过程安全性、可靠性和经济性的重要技术, 异常检测、寿命预测与维修决策在过去几十年得到了越来越广泛的关注和长足的发展. 本文结合异常检测、寿命预测与维修决策各研究环节之间的相互联系, 综述了异常检测、寿命预测与维修决策的联合研究现状,重点总结了异常检测与寿命预测、异常检测与维修决策、寿命预测与维修决策、维修决策与备件管理的联合研究动态. 最后, 探讨了该领域中存在的问题及未来的研究方向.
- 异常检测 /
- 寿命预测 /
- 维修决策 /
- 联合研究
Abstract: The past decades have witnessed an increasingly growing research interest and significant progress on various aspects of anomaly detection, life prediction, and maintenance decision. In this paper, according to the linkages among anomaly detection, life prediction, and maintenance decision, the state of the art of the integrated studies of anomaly detection, life prediction, and maintenance decision are reviewed and the potential issues needed to be solved are highlighted. Particularly, the emphasis is placed on the development of integrated anomaly detection and life prediction, integrated anomaly detection and maintenance decision, integrated life prediction and maintenance decision, and integrated maintenance decision and spare parts ordering. Finally, the unsolved problems and future research directions in the reviewed field are discussed.
- Anomaly detection /
- life prediction /
- maintenance decision /
- integrated study

HTML全文

参考文献(89)

[1]	Zhou Dong-Hua, Ye Yin-Zhong. Fault Diagnosis and Fault-Tolerant Control. Beijing: Tsinghua University Press, 2000(周东华, 叶银忠. 现代故障诊断与容错控制. 北京: 清华大学出版社, 2000)
[2]	Jardine A K S, Lin D M, Banjevic D. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 2006, 20(7): 1483-1510
[3]	Brombacher A. Reliability prediction and "Deepwater Horizon"; lessons learned. Quality and Reliability Engineering International, 2010, 26(5): 397
[4]	Bevilacqua M, Braglia M. The analytic hierarchy process applied to maintenance strategy selection. Reliability Engineering and System Safety, 2000, 70(1): 71-83
[5]	Zhou Dong-Hua, Hu Yan-Yan. Fault diagnosis techniques for dynamic systems. Acta Automatica Sinica, 2009, 35(6): 748-758(周东华, 胡艳艳. 动态系统的故障诊断技术. 自动化学报, 2009, 35(6): 748-758)
[6]	Venkatasubramanian V, Rengaswamy R, Kavuri S N, Kewen Y. A review of process fault detection and diagnosis: Part III: Process history based methods. Computers and Chemical Engineering, 2003, 27(3): 327-346
[7]	Wang H, Chai T Y, Ding J L, Brown M. Data driven fault diagnosis and fault tolerant control: some advances and possible new directions. Acta Automatica Sinica, 2009, 35(6): 739-747
[8]	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
[9]	Zhou Dong-Hua, Xu Zheng-Guo. A survey on real-time reliability evaluation and prediction techniques for engineering systems. Aerospace Control and Application, 2008, 34(4): 3-10(周东华, 徐正国. 工程系统的实时可靠性评估与预测技术. 空间控制技术与应用, 2008, 34(4): 3-10)
[10]	Ahmad R, Kamaruddin S. An overview of time-based and condition-based maintenance in industrial application. Computers and Industrial Engineering, 2012, 63(1): 135-149
[11]	Zio E. Reliability engineering: old problems and new challenges. Reliability Engineering and System Safety, 2009, 94(2): 125-141
[12]	Heng A, Zhang S, Tan A C C, Mathew J. Rotating machinery prognostics: state of the art, challenges and opportunities. Mechanical Systems and Signal Processing, 2009, 23(3): 724-739
[13]	Li Gang. Quality Related Fault Diagnosis and Prognosis for Industrial Processes [Ph.D. dissertation], Tsinghua University, China, 2010(李钢. 工业过程质量相关的故障诊断与预测方法 [博士学位论文], 清华大学, 中国, 2010)
[14]	Sikorskaa J Z, Hodkiewicz M, Ma L. Prognostic modelling options for remaining useful life estimation by industry. Mechanical Systems and Signal Processing, 2011, 25(5): 1803-1836
[15]	GB/T 3187-94, Reliability and maintainability terms, 1994(国家标准. GB/T 3187-94, 可靠性、维修性术语, 1994)
[16]	Chen Xue-Chu. Modern Maintenance Theory. Beijing: National Defence Industry Press, 2003(陈学楚. 现代维修理论. 北京: 国防工业出版社, 2003)
[17]	Fan Hong-Dong. Research on Maintenance Decision Modeling and Optimization Methods for Complex Repairable Systems [Ph.D. dissertation], High Technology Institute of Xi'an, China, 2012(樊红东. 复杂可修系统维修决策建模与优化方法研究 [博士学位论文], 第二炮兵工程大学, 中国, 2012)
[18]	Levy K, Vázquez-Abad F J. Change-point monitoring for online stochastic approximations. Automatica, 2010, 46(10): 1657-1674
[19]	Frisén M. Statistical surveillance. Optimality and methods. International Statistical Review, 2003, 71(2): 403-434
[20]	Polunchenko A S, Tartakovsky A G. State-of-the-art in sequential change-point detection. Methodology and Computing in Applied Probability, 2012, 14(3): 649-684
[21]	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): 590-601 (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): 590-601)
[22]	Wang W B. A model to predict the residual life of rolling element bearings given monitored condition information to date. IMA Journal of Management Mathematics, 2002, 13(1): 3-16
[23]	Wang W B. A two-stage prognosis model in condition based maintenance. European Journal of Operational Research, 2007, 182(3): 1177-1187
[24]	Bae S J, Kvam P H. A change-point analysis for modeling incomplete burn-in for light displays. IIE Transactions, 2006, 38(6): 489-498
[25]	Ng T S A. An application of the EM algorithm to degradation modeling. IEEE Transactions on Reliability, 2008, 57(1): 2-13
[26]	Lin J. A two-stage failure model for Bayesian change point analysis. IEEE Transactions on Reliability, 2008, 57(2): 388-393
[27]	Yuan T, Kuo Y. Bayesian analysis of hazard rate, change point, and cost-optimal burn-in time for electronic devices. IEEE Transactions on Reliability, 2010, 59(1): 132-138
[28]	You M Y, Li L, Meng G, Ni J. Two-zone proportional hazard model for equipment remaining useful life prediction. Journal of Manufacturing Science and Engineering, 2010, 132(4): 041008(1-6)
[29]	Woodall W H. Controversies and contradictions in statistical process control. Journal of Quality Technology, 2000, 32(4): 341-350
[30]	Stoumbos Z G, Reynolds M R Jr, Ryan T P, Woodall W H. The state of statistical process control as we proceed into the 21st century. Journal of the American Statistical Association, 2000, 95(451): 992-998
[31]	Bersimis S, Psarakis S, Panaretos J. Multivariate statistical process control charts: an overview. Quality and Reliability Engineering International, 2006, 23(5): 517-543
[32]	Tagaras G. An integrated cost model for the joint optimization of process control and maintenance. Journal of the Operational Research Society, 1988, 39(8): 757-766
[33]	Cassady C R, Bowden R O, Liew L, Pohl E A. Combining preventive maintenance and statistical process control: a preliminary investigation. IIE Transactions, 2000, 32(6): 471-478
[34]	Yeung T G, Cassady C R, Schneider K. Simultaneous optimization of X control chart and age-based preventive maintenance policies under an economic objective. IIE Transactions, 2007, 40(2): 147-159
[35]	Linderman K, McKone-Sweet K E, Anderson J C. An integrated systems approach to process control and maintenance. European Journal of Operational Research, 2005, 164(2): 324-340
[36]	Ben-Daya M, Rahim M A. Effect of maintenance on the economic design of x-control chart. European Journal of Operational Research, 2000, 120(1): 131-143
[37]	Zhou W H, Zhu G L. Economic design of integrated model of control chart and maintenance management. Mathematical and Computer Modelling, 2008, 47(11-12): 1389-1395
[38]	Wang W. Maintenance models based on the np control charts with respect to the sampling interval. Journal of the Operational Research Society, 2011, 62(1): 124-133
[39]	Panagiotidou S, Tagaras G. Statistical process control and condition-based maintenance: a meaningful relationship through data sharing. Production and Operations Management, 2010, 19(2): 156-171
[40]	Panagiotidou S, Nenes G. An economically designed, integrated quality and maintenance model using an adaptive Shewhart chart. Reliability Engineering and System Safety, 2009, 94(3): 732-741
[41]	Wu J M, Makis V. Economic and economic-statistical design of a chi-square chart for CBM. European Journal of Operational Research, 2008, 188(2): 516-529
[42]	Makis V. Multivariate bayesian control chart. Operations Research, 2008, 56(2): 487-496
[43]	Makis V. Multivariate Bayesian process control for a finite production run. European Journal of Operational Research, 2009, 194(3): 795-806
[44]	Yin Z J, Makis V. Economic and economic-statistical design of a multivariate Bayesian control chart for condition-based maintenance. IMA Journal of Management Mathematics, 2011, 22(1): 47-63
[45]	Wang W B. A simulation-based multivariate Bayesian control chart for real time condition-based maintenance of complex systems. European Journal of Operational Research, 2012, 218(3): 726-734
[46]	Liu L P, Yu M M, Ma Y Z, Tu Y L. Economic and economic-statistical designs of an X control chart for two-unit series systems with condition-based maintenance. European Journal of Operational Research, to be published
[47]	Yang J N, Manning S D. Stochastic crack growth analysis methodologies for metallic structures. Engineering Fracture Mechanics, 1990, 37(5): 1105-1124
[48]	Van Noortwijk J M, Klatter H E. The use of lifetime distributions in bridge maintenance and replacement modelling. Computers and Structures, 2004, 82(13-14): 1091-1099
[49]	Biondini F, Bontempi F, Frangopo D M, Malerba P G. Probabilistic service life assessment and maintenance planning of concrete structures. Journal of Structural Engineering, 2006, 132(5): 810-825
[50]	Kim S, Frangopol D M. Cost-based optimum scheduling of inspection and monitoring for fatigue-sensitive structures under uncertainty. Journal of Structural Engineering, 2011, 137(11): 1319-1331
[51]	Wang Jian. Research on maintenance scheduling for generating units in electricity market environment [Ph.D. dissertation], China Agricultural University, China, 2004(王健. 电力市场环境下发电机组检修计划的研究 [博士学位论文], 中国农业大学, 中国, 2004)
[52]	Si X S, Wang W B, Hu C H, Chen M Y, Zhou D H. A Wiener-process-based degradation model with a recursive filter algorithm for remaining useful life estimation. Mechanical Systems and Signal Processing, 2013, 35(1-2): 219-237
[53]	Kaiser K A, Gebraeel N Z. Predictive maintenance management using sensor-based degradation models. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 2009, 39(4): 840-849
[54]	Gebraeel N Z, Lawley M A, Li R, Ryan J K. Residual-life distributions from component degradation signals: a Bayesian approach. IIE Transactions, 2005, 37(6): 543-557
[55]	Elwany A H, Gebraeel N Z, Maillart L M. Structured replacement policies for components with complex degradation processes and dedicated sensors. Operations Research, 2011, 59(3): 684-695
[56]	You M Y, Liu F, Wang W, Meng G. Statistically planned and individually improved predictive maintenance management for continuously monitored degrading systems. IEEE Transactions on Reliability, 2010, 59(4): 744-753
[57]	You M Y, Li L, Meng G, Ni J. Cost-effective updated sequential predictive maintenance policy for continuously monitored degrading systems. IEEE Transactions on Automation Science and Engineering, 2010, 7(2): 257-265
[58]	Fan Hong-Dong, Hu Chang-Hua, Chen Mao-Yin, Zhou Dong-Hua. A degradation measurement based decision support method for optimal predictive maintenance policy. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2009, 37(Sup.I): 45-48(樊红东, 胡昌华, 陈茂银, 周东华. 基于退化数据的最优预测维护决策支持方法. 华中科技大学学报(自然科学版), 2009, 37(Sup.I): 45-48)
[59]	Si X S, Wang W H, Hu C H. A real-time variable cost-based maintenance model from prognostic information. In: Proceedings of 2012 IEEE Conference on Prognostics and System Health Management. Beijing, China: IEEE, 2012. 1-6
[60]	Wei M H, Chen M Y, Zhou D H. Multi-sensor information based remaining useful life prediction with anticipated performance. IEEE Transactions on Reliability, 2013, 62(1): 183-198
[61]	Si X S, Wang W B, Chen M Y, Hu C H, Zhou D H. A degradation path-dependent approach for remaining useful life estimation with an exact and closed-form solution. European Journal of Operational Research, 2013, 226(1): 53-66
[62]	Si X S, Wang W B, Hu C H, Zhou D H, Pecht M G. Remaining useful life estimation based on a nonlinear diffusion degradation process. IEEE Transactions on Reliability, 2012, 61(1): 50-67
[63]	Li L, You M Y, Ni J. Reliability-based dynamic maintenance threshold for failure prevention of continuously monitored degrading systems. Journal of Manufacturing Science and Engineering, 2009, 131(3): 1010-1018
[64]	Sun J W, Li L, Xi L F. Modified two-stage degradation model for dynamic maintenance threshold calculation considering uncertainty. IEEE Transactions on Automation Science and Engineering, 2012, 9(1): 209-212
[65]	Arnaiz A, Ferreiro S, Buderath M. New decision support system based on operational risk assessment to improve aircraft operability. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2010, 224(3): 137-147
[66]	Hu You-Tao, Hu Chang-Hua, Kong Xiang-Yu, Zhou Zhi-Jie. Real-time lifetime prediction method based on wavelet support vector regression and fuzzy c-means clustering. Acta Automatica Sinica, 2012, 38(3): 331-340(胡友涛, 胡昌华, 孔祥玉, 周志杰. 基于WSVR和FCM聚类的实时寿命预测方法. 自动化学报, 2012, 38(3): 331-340)
[67]	Wang W, Christer A H. Towards a general condition based maintenance model for a stochastic dynamic system. Journal of the Operational Research Society, 2000, 51(2): 145-155
[68]	Wang W B, Hussin B, Jefferis T. A case study of condition based maintenance modelling based upon the oil analysis data of marine diesel engines using stochastic filtering. International Journal of Production Economics, 2012, 136(1): 84-92
[69]	Carr M J, Wang W B. An approximate algorithm for prognostic modelling using condition monitoring information. European Journal of Operational Research, 2011, 211(1): 90-96
[70]	Wang W. Overview of a semi-stochastic filtering approach for residual life estimation with applications in condition based maintenance. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2011, 225(2): 185-197
[71]	Ghasemi A, Yacout S, Ouali M S. Optimal condition based maintenance with imperfect information and the proportional hazards model. International Journal of Production Research, 2007, 45(4): 989-1012
[72]	Xiang Y S, Cassady C R, Pohl E A. Optimal maintenance policies for systems subject to a Markovian operating environment. Computers and Industrial Engineering, 2012, 62(1): 190-197
[73]	Deng Xin-Yang, Deng Yong, Zhang Ya-Juan, Liu Qi. A belief Markov model and its application. Acta Automatica Sinica, 2012, 38(4): 666-672(邓鑫洋, 邓勇, 章雅娟, 刘琪. 一种信度马尔科夫模型及应用. 自动化学报, 2012, 38(4): 666-672)
[74]	Van Noortwijk J M. A survey of the application of gamma processes in maintenance. Reliability Engineering and System Safety, 2009, 94(1): 2-21
[75]	Kennedy W J, Wayne P J, Fredendall L D. An overview of recent literature on spare parts inventories. International Journal of Production Economics, 2002, 76(2): 201-215
[76]	Armstrong M J, Atkins D R. Joint optimization of maintenance and inventory policies for a simple system. IIE Transactions, 1996, 28(5): 415-424
[77]	Allen S G, D’Esopo D A. An ordering policy for repairable stock items. Operations Research, 1968, 16(3): 669-674
[78]	Van Horenbeek A, Buré J, Cattrysse D, Pintelon L, Vansteenwegen P. Joint maintenance and inventory optimization systems: a review. International Journal of Production Economics, 2013, 143(2): 499-508
[79]	Armstrong M J, Atkins D A. A note on joint optimization of maintenance and inventory. IIE Transactions, 1998, 30(2): 143-149
[80]	Acharya D, Nagabhushanam G, Alam S S. Jointly optimal block-replacement and spare provisioning policy. IEEE Transactions on Reliability, 1986, 35(4): 447-451
[81]	Zohrul Kabir A B M, Al-Olayan A S. Joint optimization of age replacement and continuous review spare provisioning policy. International Journal of Operations and Production Management, 1994, 14(7): 53-69
[82]	Wang L, Chu J, Mao W J. A condition-based order-replacement policy for a single-unit system. Applied Mathematical Modelling, 2008, 32(11): 2274-2289
[83]	Jiang Yun-Peng, Chen Mao-Yin, Zhou Dong-Hua. Modeling of condition-based maintenance and spare parts provisioning policy for single-unit system with two-stage degradation. Journal of Nanjing University of Aeronautics and Astronautics, 2011, 43(S1): 147-151(蒋云鹏, 陈茂银, 周东华. 两阶段退化单部件系统的视情维护和备件供给策略建模. 南京航空航天大学学报, 2011, 43(S1): 147-151)
[84]	Wang L, Chu J, Mao W J. A condition-based replacement and spare provisioning policy for deteriorating systems with uncertain deterioration to failure. European Journal of Operational Research, 2009, 194(1): 184-205
[85]	Wang L, Chu J, Mao W J. An optimum condition-based replacement and spare provisioning policy based on Markov chains. Journal of Quality in Maintenance Engineering, 2008, 14(4): 387-401
[86]	Rausch M, Liao H T. Joint production and spare part inventory control strategy driven by condition based maintenance. IEEE Transactions on Reliability, 2010, 59(3): 507-516
[87]	Xie J, Wang H W. Joint optimization of condition-based preventive maintenance and spare ordering policy. In: Proceedings of the 4th International Conference on Wireless Communications, Networking and Mobile Computing. Dalian, China: IEEE, 2008. 1-5
[88]	Elwany A H, Gebraeel N Z. Sensor-driven prognostic models for equipment replacement and spare parts inventory. IIE Transactions, 2008, 40(7): 629-639
[89]	Louit D, Pascual R, Banjevic D, Jardine A K S. Condition-based spares ordering for critical components. Mechanical Systems and Signal Processing, 2011, 25(5): 1837-1848