C. Quan, Liang Lingqiang, Yuan Dongping, Yingkui Gu
{"title":"一种基于模糊故障树和模糊事件树的可靠性风险分析方法","authors":"C. Quan, Liang Lingqiang, Yuan Dongping, Yingkui Gu","doi":"10.1109/ICRMS.2016.8050082","DOIUrl":null,"url":null,"abstract":"Based on the analyses systems of fuzzy fault tree and event tree, this paper proposes a method for a reliability risk analysis to mitigate problems associated with risk modeling of fuzzy and uncertain information. Risk event occurrence probabilities were obtained with fuzzy linguistic variables instead of exact values used in fault tree analysis. Quantitative analysis was applied to the fuzzy fault tree to determine the fuzzy importance degree of each basic event, which were then ranked and divided to distinguish the influence of these basic events. Based on this analysis, a fuzzy event tree was constructed and linguistic terms used to evaluate occurrence probabilities and outcomes. Mitigation measures were put forward for risk events and the expected risk magnitudes were calculated under the mitigation strategies. This ensured the mitigation measures were intuitive and accurate. Finally, an application example was illustrated to verify that the proposed method was effective and feasible.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A reliability risk analysis method based on the fuzzy fault tree and fuzzy event tree\",\"authors\":\"C. Quan, Liang Lingqiang, Yuan Dongping, Yingkui Gu\",\"doi\":\"10.1109/ICRMS.2016.8050082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the analyses systems of fuzzy fault tree and event tree, this paper proposes a method for a reliability risk analysis to mitigate problems associated with risk modeling of fuzzy and uncertain information. Risk event occurrence probabilities were obtained with fuzzy linguistic variables instead of exact values used in fault tree analysis. Quantitative analysis was applied to the fuzzy fault tree to determine the fuzzy importance degree of each basic event, which were then ranked and divided to distinguish the influence of these basic events. Based on this analysis, a fuzzy event tree was constructed and linguistic terms used to evaluate occurrence probabilities and outcomes. Mitigation measures were put forward for risk events and the expected risk magnitudes were calculated under the mitigation strategies. This ensured the mitigation measures were intuitive and accurate. Finally, an application example was illustrated to verify that the proposed method was effective and feasible.\",\"PeriodicalId\":347031,\"journal\":{\"name\":\"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRMS.2016.8050082\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRMS.2016.8050082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A reliability risk analysis method based on the fuzzy fault tree and fuzzy event tree
Based on the analyses systems of fuzzy fault tree and event tree, this paper proposes a method for a reliability risk analysis to mitigate problems associated with risk modeling of fuzzy and uncertain information. Risk event occurrence probabilities were obtained with fuzzy linguistic variables instead of exact values used in fault tree analysis. Quantitative analysis was applied to the fuzzy fault tree to determine the fuzzy importance degree of each basic event, which were then ranked and divided to distinguish the influence of these basic events. Based on this analysis, a fuzzy event tree was constructed and linguistic terms used to evaluate occurrence probabilities and outcomes. Mitigation measures were put forward for risk events and the expected risk magnitudes were calculated under the mitigation strategies. This ensured the mitigation measures were intuitive and accurate. Finally, an application example was illustrated to verify that the proposed method was effective and feasible.