Continuous-time T-S Dynamic Fault Tree Analysis Method

doi:10.3901/JME.2020.10.244

Abstract

Abstract: Compared with DUGAN dynamic fault tree analysis method, discrete-time T-S dynamic fault tree analysis method enhances the ability of the fault tree to describe static and dynamic failure behavior, and can directly analyze a system directly quantitatively, but it has analysis and calculation errors, and can not reflect the change trend of system reliability. To this end, continuous-time T-S dynamic fault tree analysis method is proposed. The continuous-time T-S dynamic gates describing static and dynamic failure behavior are defined, a method of constructing continuous-time T-S dynamic gates describing rules based on the temporal relationship of lower-level events and the description of events occurrence impulse function and the possibility of higher-level event occurrence is proposed by using the integral characteristic of impulse function at impulse point. Then analysis and calculation methods based on the description of the rule execution degree and the possibility of the higher-event and the higher-event failure probability density function and the failure probability distribution function of the impulse function integration are proposed. The proposed continuous-time T-S dynamic fault tree analysis method has stronger failure behavior description ability than DUGAN dynamic fault tree analysis method, it solves the problem of analysis and calculation errors of discrete-time T-S dynamic fault tree analysis method and can reflect the change trend of system failure probability. Compared with Markov chain, discrete-time Bayesian network, continuous-time Bayesian network solving DUGAN dynamic fault tree and discrete-time T-S dynamic fault tree analysis method, the feasibility of continuous-time T-S dynamic fault tree analysis method is verified and continuous-time T-S dynamic fault tree analysis method has more advantages.

Key words: fault tree, dynamic fault tree, T-S dynamic fault tree, T-S dynamic gate, continuous-time

CLC Number:

TB114
TH137

YAO Chengyu, WANG Chuanlu, CHEN Dongning, WEI Xing, Lü Shijun. Continuous-time T-S Dynamic Fault Tree Analysis Method[J]. Journal of Mechanical Engineering, 2020, 56(10): 244-256.

References

[1] VOLK M,JUNGES S,KATOEN J P. Fast dynamic fault tree analysis by model checking techniques[J]. IEEE Transactions on Industrial Informatics,2018,14(1):370-379.
[2] 李垚,朱才朝,宋朝省,等. 风电机组液压系统动态故障树的可靠性建模与评估[J]. 太阳能学报,2018,39(12):3584-3593. LI Yao,ZHU Caichao,SONG Chaosheng,et al. Reliability modeling and assessment of dynamic fault tree for hydraulic system of wind turbines[J]. Acta Energiae Solaris Sinica,2018,39(12):3584-3593.
[3] 冯芬玲,阎美好. 基于BDD的铁路快运货物损失风险评估[J]. 北京交通大学学报,2018,42(6):48-54. FENG Fenling,YAN Meihao. Risk evaluation for railway express cargo loss based on BDD[J]. Journal of Beijing Jiaotong University,2018,42(6):48-54.
[4] RUIJTERS E,STOELINGA M. Fault tree analysis:A survey of the state-of-the-art in modeling,analysis and tools[J]. Computer Science Review,2015,15-16(3):29-62.
[5] 姚成玉,陈东宁. 基于最小割集综合排序的液压系统故障定位方法[J]. 中国机械工程,2010,21(11):1357-1361. YAO Chengyu,CHEN Dongning. Fault localization method of hydraulic system based on minimum cut sets' comprehensive rank[J]. China Mechanical Engineering,2010,21(11):1357-1361.
[6] SONG H,ZHANG H Y,CHAN C W. Fuzzy fault tree analysis based on T-S model with application to INS/GPS navigation system[J]. Soft Computing,2009,13(1):31-40.
[7] 姚成玉,赵静一. 基于T-S模型的液压系统模糊故障树分析方法研究[J]. 中国机械工程,2009,20(16):1913-1917. YAO Chengyu,ZHAO Jingyi. Research on fuzzy fault tree analysis method for hydraulic system based on T-S model[J]. China Mechanical Engineering,2009,20(16):1913-1917.
[8] DONG L,SONG H,LIU W,et al. The application of T-S fuzzy fault tree analysis in satellite attitude control system[C]//IEEE 10th International Conference on Industrial Informatics,July 25-27,2012,Beijing,China. IEEE,2012:208-213.
[9] 孙利娜,黄宁,仵伟强,等. 基于T-S模糊故障树的多态系统性能可靠性[J]. 机械工程学报,2016,52(10):191-198. SUN Lina,HUANG Ning,WU Weiqiang,et al. Performance reliability of polymorphic systems by fuzzy fault tree based on T-S model[J]. Journal of Mechanical Engineering,2016,52(10):191-198.
[10] 罗彦斌,陈建勋,王梦恕. 基于T-S模糊故障树理论的公路隧道冻害分析方法[J]. 北京交通大学学报,2012,36(4):55-60. LUO Yanbin,CHEN Jianxun,WANG Mengshu. Method for analyzing the highway tunnel freeze injury based on the T-S fuzzy fault tree theory[J]. Journal of Beijing Jiaotong University,2012,36(4):55-60.
[11] 姚成玉,陈东宁,王斌. 基于T-S故障树和贝叶斯网络的模糊可靠性评估方法[J]. 机械工程学报,2014,50(2):193-201. YAO Chengyu,CHEN Dongning,WANG Bin. Fuzzy reliability assessment method based on T-S fault tree and Bayesian network[J]. Journal of Mechanical Engineering,2014,50(2):193-201.
[12] 李莎莎,崔铁军,马云东. 基于空间故障树理论的系统可靠性评估方法研究[J]. 中国安全生产科学技术,2015,11(6):68-74. LI Shasha,CUI Tiejun,MA Yundong. Study on assessment method of system reliability based on space fault tree theory[J]. Journal of Safety Science and Technology,2015,11(6):68-74.
[13] 姚成玉,吕军,陈东宁,等. 凸模型T-S故障树及重要度分析方法[J]. 机械工程学报,2015,51(24):184-192. YAO Chengyu,LÜ Jun,CHEN Dongning,et al. Convex model T-S fault tree and importance analysis methods[J]. Journal of Mechanical Engineering,2015,51(24):184-192.
[14] DUGAN J B,BAVUSO S J,BOYD M A. Fault trees and sequence dependencies[J]. Microelectronics Reliability,1991,31(5):286-293.
[15] WALKER M,PAPADOPOULOS Y. Qualitative temporal analysis:Towards a full implementation of the fault tree handbook[J]. Control Engineering Practice,2009,17(10):1115-1125.
[16] 吴奇烜,马建峰,孙聪,等. 针对扩展动态故障树的约束分析方法[J]. 通信学报,2017,38(9):159-166. WU Qixuan,MA Jianfeng,SUN Cong,et al. Constraint analysis for extended dynamic fault tree[J]. Journal on Communications,2017,38(9):159-166.
[17] 兰杰,袁宏杰,夏静. 基于离散时间贝叶斯网络的动态故障树分析的改良方法[J]. 系统工程与电子技术,2018,40(4):948-953. LAN Jie,YUAN Hongjie,XIA Jing. Improve method for dynamic fault tree analysis based on discrete-tine Bayesian network[J]. Systems Engineering and Electronics,2018,40(4):948-953.
[18] BOUDALI H,CROUZEN P,STOELINGA M. Dynamic fault tree analysis using input/output interactive Markov chains[C]//37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks,June 25-28,2007,Edinburgh,UK. IEEE,2007:708-717.
[19] YEVKIN O. An efficient an efficient approximate Markov chain method in dynamic fault tree analysis[J]. Quality and Reliability Engineering International,2016,32:1509-1520.
[20] 朱正福,李长福,何恩山,等. 基于马尔可夫链的动态故障树分析方法[J]. 兵工学报,2008,29(9):1104-1107. ZHU Zhengfu,LI Changfu,HE Enshan,et al. The dynamic fault tree analysis method based on Markov chain[J]. Acta Armamentarii,2008,29(9):1104-1107.
[21] MANNO G,CHIACCHIO F,COMPAGNO L,et al. MatCarloRe:An integrated FT and Monte Carlo simulink tool for the reliability assessment of dynamic fault tree[J]. Expert Systems with Applications,2012,39(12):10334-10342.
[22] 孙东旭,杨媛媛,王红春,等. 面向航电计算平台的多态动态故障树分析方法[J]. 微电子学与计算机,2017,34(5):12-20. SUN Dongxu,YANG Yuanyuan,WANG Hongchun,et al. Multi-state dynamic fault tree analysis method for avionics computing platform[J]. Microelectronics and Computer,2017,34(5):12-20.
[23] 李志强,徐廷学,顾钧元,等. 基于动态贝叶斯网络的某控制单元可靠性分析[J]. 航空兵器,2017,(5):83-88. LI Zhiqiang,XU Tingxue,GU Junyuan,et al. Reliability analysis of a control unit based on dynamic Bayesian network[J]. Aero Weaponry,2017,(5):83-88.
[24] 魏亚荣,李长俊,吴瑕. 基于贝叶斯网络的页岩气集输管道失效概率计算方法研究[J]. 中国安全生产科学技术,2019,15(1):121-127. WEI Yarong,LI Changjun,WU Xia. Study on calculation method of failure probability for gathering pipeline of shale gas based on Bayesian network[J]. Journal of Safety Science and Technology,2019,15(1):121-127.
[25] FAKHRAVAR D,KHAKZAD N,RENIERS G,et al. Security vulnerability assessment of gas pipelines using discrete-time Bayesian network[J]. Process Safety and Environmental Protection,2017,111:714-725.
[26] GE D,LIN M,YANG Y,et al. Quantitative analysis of dynamic fault trees using improved sequential binary decision diagrams[J]. Reliability Engineering and System Safety,2015,142:289-299.
[27] 熊小萍,谭建成,林湘宁. 基于动态故障树的变电站通信系统可靠性分析[J]. 中国电机工程学报,2012,32(34):135-141. XIONG Xiaoping,TAN Jiancheng,LIN Xiangning. Reliability analysis of communication system in substation based on dynamic fault tree[J]. Proceedings of the CSEE,2012,32(34):135-141.
[28] 余建星,任杰,杨政龙,等. 基于动态故障树法的深海采油树系统定量风险评估[J]. 中国海洋平台,2019,34(1):72-78. YU Jianxing,REN Jie,YANG Zhenglong,et al. Quantitative risk analysis of deep-sea christmas tree system based on dynamic fault tree[J]. China Offshore Platform,2019,34(1):72-78.
[29] 房丙午,黄志球,李勇,等. 基于贝叶斯网络的复杂系统动态故障树定量分析方法[J]. 电子学报,2016,44(5):1234-1239. FANG Bingwu,HUANG Zhiqiu,LI Yong,et al. Quantitative analysis method of dynamic fault tree of complex system using Bayesian network[J]. Acta Electronica Sinica,2016,44(5):1234-1239.
[30] BOUDALI H,DUGAN J B. A continuous-time Bayesian network reliability modeling and analysis framework[J]. IEEE Transaction on Reliability,2006,55(1):86-97.
[31] 李佩昌,袁宏杰,兰杰,等. 基于顺序二元决策图的动态故障树分析[J]. 北京航空航天大学学报,2017,43(1):167-175. LI Peichang,YUAN Hongjie,LAN Jie,et al. Dynamic fault tree analysis using sequential binary decision diagrams[J]. Journal of Beijing University of Aeronautics and Astronautics,2017,43(1):167-175.
[32] 姚成玉,饶乐庆,陈东宁,等. T-S动态故障树分析方法[J]. 机械工程学报,2019,55(16):17-32. YAO Chengyu,RAO Leqing,CHEN Dongning,et al. T-S dynamic fault tree analysis method[J]. Journal of Mechanical Engineering,2019,55(16):17-32.
[33] 王家序,周青华,肖科,等. 不完全共因失效系统动态故障树模型分析方法[J]. 系统工程与电子技术,2012,34(5):1062-1067. WANG Jiaxu,ZHOU Qinghua,XIAO Ke,et al. Dynamic fault tree model analysis of systems subjected to incomplete common-cause failure[J]. Systems Engineering and Electronics,2012,34(5):1062-1067.
[34] BOUDALI H,DUGAN J B. A discrete-time Bayesian network reliability modeling and analysis framework[J]. Reliability Engineering and System Safety,2005,87(3):337-349.
[35] 姚成玉,陈东宁. T-S故障树理论及其应用[M]. 北京:国防工业出版社,2020. YAO Chengyu,CHEN Dongning. T-S fault tree theory and applications[M]. Beijing:National Defense Industry Press,2020.