基于模糊贝叶斯网的危害性分析方法

计算机应用 ›› 2014, Vol. 34 ›› Issue (12): 3446-3450.

基于模糊贝叶斯网的危害性分析方法

翟胜¹,师五喜²,³,修春波³

1. 天津工业大学机械工程学院,天津 300387
2. 天津市现代机电装备技术重点实验室,天津 300387
3. 天津工业大学电气工程与自动化学院,天津 300387

收稿日期:2014-06-27 修回日期:2014-08-27 出版日期:2014-12-01 发布日期:2014-12-31
通讯作者: 翟胜
作者简介:翟胜(1969-),男,辽宁大连人,高级工程师,博士研究生,主要研究方向:机电一体化设备、系统可靠性分析；师五喜(1964-),男,甘肃秦安人,教授,博士生导师,主要研究方向:机电一体化设备、机器人、智能控制；修春波(1978-),男,黑龙江大庆人,副教授,博士,主要研究方向:智能控制、模式识别。
基金资助:
国家自然科学基金资助项目

Criticality analysis method based on fuzzy Bayesian networks

QU Sheng¹,SHI Wuxi²,³,XIU Chunbo³

1. School of Mechanical Engineering, Tianjin Polytechnic University, Tianjin 300387,China;
2. Tianjin Key Laboratory of Advanced Mechatronics Equipment Technology, Tianjin 300387, China
3. School of Electrical Engineering and Automation,Tianjin Polytechnic University, Tianjin 300387,China;

Received:2014-06-27 Revised:2014-08-27 Online:2014-12-01 Published:2014-12-31
Contact: QU Sheng

摘要/Abstract

摘要：

针对传统的故障模式、影响与危害性分析(FMECA)方法不足的问题,提出了一个基于模糊贝叶斯网的危害性分析方法。该方法将模糊理论与贝叶斯网推理技术结合起来,用三角模糊数来描述专家的模糊评分值；通过模糊集合映射,将其转化为评级的模糊子集；以置信结构的模糊规则,表示故障模式的属性与危害度之间的关系；利用贝叶斯网络推理算法综合置信结构的模糊规则,通过贝叶斯网推理得到模糊子集形式的危害度,再经过去模糊计算,得到故障危害等级的清晰值,从而确定故障模式的危害程度。实验结果表明,所提方法能够提高传统分析方法的准确性和应用范围。

Abstract:

Considering the defects of traditional Failure Modes,Effect and Criticality Analysis (FMECA), a criticality analysis method based on fuzzy Bayesian networks was proposed. This approach combined the fuzzy theory with Bayesian network techniques, and fuzzy judgments of experts were described using triangular fuzzy numbers which were transformed into forms of fuzzy subsets of ranking through mapping of fuzzy sets. The fuzzy rules with belief structure were used to represent the relationship between the properties and hazards of the failure modes. The Bayesian network inference algorithms were used to synthesize the fuzzy rules of belief structure, and the hazard degree in the form of fuzzy subsets was obtained by Bayesian inference, through defuzzification calculation, a precise value of fault hazard ranking was gained to determine the hazard degree of the failure mode. The experimental results show that the proposed method is able to improve the accuracy and application range of the traditional analysis method.

中图分类号:

TP302.7

翟胜师五喜修春波. 基于模糊贝叶斯网的危害性分析方法[J]. 计算机应用, 2014, 34(12): 3446-3450.

QU Sheng SHI Wuxi XIU Chunbo. Criticality analysis method based on fuzzy Bayesian networks[J]. Journal of Computer Applications, 2014, 34(12): 3446-3450.

参考文献

［1］MANDAL S, MAITI J. Risk analysis using FMEA: fuzzy similarity value and possibility theory based approach［J］. Expert Systems with Applications, 2014, 41(7): 3527-3537.
［2］WANG G, JIA Y, SHEN G, et al. Fuzzy evaluation analysis on cooling system failure mode criticality of machining center［J］. Transactions of the Chinese Society for Agricultural Machinery, 2008, 39(3): 171-174.(王桂萍, 贾亚洲, 申桂香,等. 加工中心冷却系统故障模式危害性模糊评价分析［J］.农业机械学报, 2008,39(3):171-174.)
［3］SHAHIN A. Integration of FMEA and the Kano model: an exploratory examination［J］.International Journal of Quality and Reliability Management, 2004, 21(7): 731-746.
［4］KANG R, SHI R. The technology and application of FMECA［M］. Beijing: National Defense Industry Press,2006: 32-35.(康锐,石荣德. FMECA技术及其应用［M］.北京:国防工业出版社,2006: 32-35.)
［5］HEERALAL G, SANJAY K. Criticality assessment models for failure mode effects and criticality analysis using fuzzy logic ［J］. IEEE Transactions on Reliability, 2011, 60(1):102-110.
［6］YANG Z, BONSALLS, WANG J. Fuzzy rule-based Bayesian reasoning approach for prioritization of failures in FMEA［J］. IEEE Transactions on Reliability, 2008, 5(3): 517-528.
［7］XU K, TANG L, XIE M, et al. Fuzzy assessment of FMEA for engine systems［J］. Reliability Engineering and System Safety,2002,75(1):17-29.
［8］ANTONIO C. Fuzzy inference to risk assessment on nuclear engineering systems［J］. Applied Soft Computing, 2007, 7(1): 17-28.
［9］LIU H, LIU L, BIAN Q, et al. Failure mode and effects analysis using fuzzy evidential reasoning approach and grey theory［J］. Expert Systems with Applications, 2011, 38(4):4403-4415.
［10］HELGE L, LUIGI P. Bayesian networks in reliability［J］. Reliability Engineering System Safety, 2007, 92(1): 92-108.
［11］NIMA K, FAISAL K, PAOL A. Safety analysis in process facilities: comparison of fault tree and Bayesian network approaches ［J］. Reliability Engineering and System Safety, 2011, 96(8): 925-932.
［12］CHEN D, YAO C. Reliability analysis of multi-state system based on fuzzy Bayesian networks and application in hydraulic system［J］. Chinese Journal of Mechanical Engineering, 2012, 48(16):175-183.(陈东宁,姚成玉. 基于模糊贝叶斯网络的多态系统可靠性分析及在液压系统中的应用［J］.机械工程学报,2012,48(16):175-183.)
［13］MA D, ZHOU Z, YU X, et al. Reliability analysis of multi-state Bayesian networks based on fuzzy probability［J］. Systems Engineering and Electronics, 2012, 34(12): 2607-2611.(马德仲,周真,于晓洋,等.基于模糊概率的多状态贝叶斯网络可靠性分析［J］.系统工程与电子技术,2012,34(12):2607-2611.)
［14］NILSSON N. Artificial intelligence［M］. ZHENG K, ZHUANG Y, translated. Beijing: China Machine Press, 2000:203-205.(NILSSON N.人工智能［M］. 郑扣根,庄越挺,译.北京:机械工业出版社,2000:203-205.)
［15］LIU J, YANG J, WANG J, et al. Engineering system safety analysis and synthesis using the fuzzy rule-based evidential reasoning approach ［J］. Quality and Reliability Engineering International, 2005, 21(4):387-411.
［16］YANG J, LIU J, WANG J, et al. Belief rule-base inference methodology using the evidential reasoning approach-RIMER［J］. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans,2006,36(2): 266-285.

[1]	孟慧玲, 王耀彬, 李凌, 杨洋, 王欣夷, 刘志勤. TACLeBench中内核程序循环级推测并行性分析[J]. 计算机应用, 2021, 41(9): 2652-2657.
[2]	安鑫, 杨海娇, 李建华, 任福继. 热安全约束下异构多核系统动态映射方法[J]. 计算机应用, 2021, 41(9): 2631-2638.
[3]	安鑫, 康安, 夏近伟, 李建华, 陈田, 任福继. 基于机器学习的异构感知多核调度方法[J]. 计算机应用, 2020, 40(10): 3081-3087.
[4]	安鑫, 张影, 康安, 陈田, 李建华. 基于机器学习的异构多核处理器系统在线映射方法[J]. 计算机应用, 2019, 39(6): 1753-1759.
[5]	李帅, 孙磊, 郭松辉. 减少上下文切换的虚拟密码设备中断路径优化方法[J]. 计算机应用, 2018, 38(7): 1946-1950.
[6]	肖成龙, 林军, 王珊珊, 王宁. 面向高层次综合的自定义指令自动识别方法[J]. 计算机应用, 2018, 38(7): 2024-2031.
[7]	肖成龙林军王珊珊王宁. 面向高层次综合的自定义指令自动识别方法[J]. 计算机应用, 0, (): 0-0.
[8]	曹云鹏, 王海峰. 面向MapReduce计算模式的中间数据通信优化[J]. 计算机应用, 2018, 38(4): 1078-1083.
[9]	陈大鹏, 张九根, 梁星. 基于免疫粒子群算法的中央空调冷冻水系统优化控制[J]. 计算机应用, 2017, 37(9): 2717-2721.
[10]	张晶, 陈垚, 范洪博, 孙俊. 基于信息物理融合系统执行器输出事件的价值评价调度策略[J]. 计算机应用, 2017, 37(6): 1663-1669.
[11]	张建勋, 古志民. 帮助线程预取质量的实时在线评价方法[J]. 计算机应用, 2017, 37(1): 114-119.
[12]	郭荣佐, 樊相奎, 崔冬霞, 黎明. 嵌入式系统硬件可靠性Copula方法建模与分析[J]. 计算机应用, 2015, 35(2): 550-554.
[13]	唐兵张黎. 面向费用优化的云存储缓存策略[J]. 计算机应用, 2014, 34(11): 3109-3111.
[14]	何艳军罗海勇戴永陈自力. 基于动态射频指纹的调频定位方法[J]. 计算机应用, 2014, 34(11): 3173-3176.
[15]	卫兵郭玉堂宋杰张磊. 具备高存储密度的新型NAND设备管理方案[J]. 计算机应用, 2014, 34(8): 2434-2437.