A reliability modeling and analysis method for PMS considering common cause failure
-
摘要:
共因失效(CCF)打破了系统内组件失效的独立性假设,会对系统特别是多阶段任务系统(PMS)的可靠性评估产生显著影响。针对多阶段任务系统中随机共因失效(PCCF)对任务可靠性的影响问题,对共因事件之间的关系进行分析,利用贝叶斯理论扩展了共因事件的概率模型,使其适用于互斥、相互独立和统计相关等多种统计关系。在此基础上提出了综合应用二元决策图(BDD)和马尔可夫(Markov)模型的模块化建模分析方法。首先,利用故障树对任务过程建模;然后,在考虑共因失效的情况下采用BDD和Markov模型分别计算系统中静态模块和动态模块;再次,由全概率公式计算任务可靠性;最后,以卫星首次转轨过程为对象,验证了方法的有效性,并通过与已有案例的对比,分析了共因失效对任务可靠性的影响。
-
关键词:
- 多阶段任务系统(PMS) /
- 随机共因失效(PCCF) /
- 二元决策图(BDD) /
- Markov模型 /
- 动态性
Abstract:Common cause failures (CCFs) in a system destroy the hypothesis that the failures are independent, which may significantly impact the reliability evaluation of the system, especially the phased-mission system (PMS). Aimed at the impact of probabilistic common cause failure (PCCF) on reliability of mission in PMS, this paper discussed the relationship between common cause events and extended the probabilistic model of common cause events using Bayesian theory to make the model fit for different statistical relations including mutually exclusive, s-independent and s-dependent. Moreover, a module-based modeling and analysis method using binary decision diagram (BDD) and Markov model was proposed. First, the fault tree of each phase was constructed. Then, considering CCF, BDD and Markov model were used to deal with the static and dynamic module in PMS respectively. Third, mission reliability was evaluated using total probability law. Finally, a case study of satellite for its orbit transfer was supplied to verify the effectiveness of the method. In addition, the result of this paper was compared with the existing case to analyze the influence of CCFs on mission reliability.
-
表 1 组件及分系统介绍
Table 1. Introduction of components and subsystems
分系统 单机 符号 简介 姿轨控 姿态控制计算机 A 含Aa和Ab共2台,冷备份 陀螺 B 含Ba、Bb和Bc共3台,3取2 数字太阳敏感器 C 含Ca、Cb、Cc和Cd共4台,其中仅Ca和Cb热备份 红外地球敏感器 D 含Da和Db共2台,热备份 星敏感器 E 含Ea、Eb和Ec共3台,3取2 推进 490 N发动机 F 1台F 10 N推力器 G 含Ga和Gb共2套,热备份 表 2 组件条件失效概率
Table 2. Conditional failure probability of components
模块 组件 E1/10-5 E2 E3 E4/10-5 E5 E6 E7 E8 M24 Ba4 1.086 1.086×10-5 1.086×10-5 1.086 1.086×10-5 1.086×10-5 1.086×10-5 1.086×10-5 Bb4 1.068 1.068×10-5 1.068×10-5 1.068 1.068×10-5 1.068×10-5 1.068×10-5 1.068×10-5 Bc4 1.068 1.068×10-5 1.068×10-5 1.068 1.068×10-5 1.068×10-5 1.068×10-5 1.068×10-5 M63 Ca3 4.746 4.746×10-5 4.746×10-5 4.746 4.746×10-5 4.746×10-5 4.746×10-5 4.746×10-5 Cb3 4.746 4.746×10-5 4.746×10-5 4.746 4.746×10-5 4.746×10-5 4.746×10-5 4.746×10-5 M34 Cc4 5.478 0.035 4 5.478×10-5 5.478 0.035 4 0.035 4 5.478×10-5 0.035 4 M44 Cd4 5.478 0.035 4 5.478×10-5 5.478 0.035 4 0.035 4 5.478×10-5 0.035 4 M54 Ga4 1.068 0.080 6 1.068×10-5 1.068 0.080 6 0.080 6 1.068×10-5 0.080 6 Gb4 1.068 0.080 6 1.068×10-5 1.068 0.080 6 0.080 6 1.068×10-5 0.080 6 M73 Da3 1.891 1.891×10-5 1.891×10-5 1.891 1.891×10-5 1.891×10-5 1.891×10-5 1.891×10-5 Db3 1.891 1.891×10-5 1.891×10-5 1.891 1.891×10-5 1.891×10-5 1.891×10-5 1.891×10-5 M85 F5 1.643 1.643×10-5 0.0170 1.643 0.017 0 1.643×10-5 0.017 0 0.017 0 表 3 模块条件失效概率
Table 3. Conditional failure probability of modules
模块 E1 E2 E3 E4 E5 E6 E7 E8 M15 1.000×10-8 0.009 87 1.000×10-8 0.009 64 0.009 87 0.004 22 0.009 64 0.004 22 M24 3.422×10-10 3.422×10-10 3.422×10-10 3.422×10-10 3.422×10-10 3.422×10-10 3.422×10-10 3.422×10-10 M63 2.252×10-9 2.252×10-9 2.252×10-9 2.252×10-9 2.252×10-9 2.252×10-9 2.252×10-9 2.252×10-9 M34 5.478×10-5 0.0354 5.478×10-5 5.478×10-5 0.035 4 0.035 4 5.478×10-5 0.035 4 M44 5.478×10-5 0.035 4 5.478×10-5 5.478×10-5 0.035 4 0.035 4 5.478×10-5 0.035 4 M54 1.141×10-10 0.006 5 1.141×10-10 1.141×10-10 0.006 5 0.006 5 1.141×10-10 0.006 5 M73 3.576×10-10 3.576×10-10 3.576×10-10 3.576×10-10 3.576×10-10 3.576×10-10 3.576×10-10 3.576×10-10 M85 1.643×10-5 1.643×10-5 0.017 0 1.64 3×10-5 0.017 0 1.643×10-5 0.017 0 0.017 0 -
[1] XING L, AMARI S V.Reliability of phased-mission systems[M].Berlin:Springer, 2008:349-368. [2] XING L, LEVITIN G.BDD-based reliability evaluation of phased-mission systems with internal/external common-cause failures[J].Reliability Engineering and System Safety, 2013, 112:145-153. doi: 10.1016/j.ress.2012.12.003 [3] WU X Y, YAN H, LI L.Numerical method for reliability analysis of phased mission system using Markov chains[J].Communication Statistics-Theory and Method, 2012, 41(21):3960-3973. doi: 10.1080/03610926.2012.697969 [4] WU X Y, WU X Y.Extended object-oriented Petri net model for mission reliability simulation of repairable PMS with common cause failures[J].Reliability Engineering and System Safety, 2015, 136:109-119. doi: 10.1016/j.ress.2014.11.012 [5] SHRESTHA A, XING L, DAI Y.Reliability analysis of multi-state phased-mission systems with unordered and ordered states[J].IEEE Transactions on Systems, Man, and Cybernetics, Part A:Systems and Humans, 2011, 41(4):625-636. doi: 10.1109/TSMCA.2010.2089513 [6] LU J M, WU X Y.Reliability evaluation of generalized phased-mission systems with repairable components[J].Reliability Engineering and System Safety, 2014, 121:136-145. doi: 10.1016/j.ress.2013.08.005 [7] MO Y, XING L, AMARI S.A multiple-valued decision diagram based method for efficient reliability analysis of non-repairable phased-mission systems[J].IEEE Transactions on Reliability, 2014, 63(1):320-330. doi: 10.1109/TR.2014.2299497 [8] WANG D, TRIVEDI K S.Reliability analysis of phased-mission system with independent component repairs[J].IEEE Transactions on Reliability, 2007, 56(3):540-551. doi: 10.1109/TR.2007.903268 [9] XING L, WANG W. Probabilistic common-cause failures analysis[C]//Proceeding of the 2008 Annual Reliability and Maintainability Symposium. Piscataway, NJ: IEEE Press, 2009: 354-358. [10] XING L, BODDU P, SUN Y, et al.Reliability analysis of static and dynamic fault-tolerant systems subject to probabilistic common-cause failures[J].Journal of Risk and Reliability, 2010, 224(1):43-53. http://www.mendeley.com/research/reliability-analysis-static-dynamic-faulttolerant-systems-subject-probabilistic-commoncause-failures/ [11] WANG C, XING L, LEVITIN G.Explicit and implicit methods for probabilistic common-cause failure analysis[J].Reliability Engineering and System Safety, 2014, 131(3):175-184. http://www.sciencedirect.com/science/article/pii/S0951832014001549 [12] WANG C, XING L, LEVITIN G.Probabilistic common cause failures in phased-mission systems[J].Reliability Engineering and System Safety, 2015, 144:53-60. doi: 10.1016/j.ress.2015.07.004 [13] OU Y, DUGAN J B.Modular solution of dynamic multi-phase systems[J].IEEE Transaction on Reliability, 2004, 53(4):499-508. doi: 10.1109/TR.2004.837305 [14] XING L, AMARI S V.Binary decision diagrams and extensions for system reliability analysis[M].Boston:John Wiley & Sons, 2015. [15] LI S, SI S, DUI H, et al.A novel decision diagrams extension method[J].Reliability Engineering and System Safety, 2014, 126:107-115. doi: 10.1016/j.ress.2014.01.017 [16] 张华, 宗益燕, 韦锡峰, 等.地球同步轨道卫星多阶段任务可靠性建模[J].航天器环境工程, 2016, 33(4):439-445. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=hthj201604019&dbname=CJFD&dbcode=CJFQZHANG H, ZONG Y Y, WEI X F, et al.Phased-mission system reliability modeling of geostationary satellite based on mission profile[J].Spacecraft Environment Engineering, 2016, 33(4):439-445(in Chinese). http://kns.cnki.net/KCMS/detail/detail.aspx?filename=hthj201604019&dbname=CJFD&dbcode=CJFQ [17] 朱海鹏. 基于BDD的多阶段任务系统可靠性建模分析[D]. 成都: 电子科技大学, 2010: 37-38. http://cdmd.cnki.com.cn/Article/CDMD-10614-2010234447.htmZHU H P. Reliability modeling and analysis method for PMS based on BDD[D]. Chengdu: University of Electronic Science and Technology of China, 2010: 37-38(in Chinese). http://cdmd.cnki.com.cn/Article/CDMD-10614-2010234447.htm [18] RAUZY A.New algorithms for fault tree analysis[J].Reliability Engineering and System Safety, 1993, 40(3):203-211. doi: 10.1016/0951-8320(93)90060-C