{"title":"基于广义生存特征的不确定系统可靠性分析","authors":"J. Mi, Jie Hu, Yan-Feng Li, Dong-bai Sun","doi":"10.1109/ISSSR58837.2023.00050","DOIUrl":null,"url":null,"abstract":"Survival Signature is a reliable modeling and analysis method that can effectively separate system structure function and component failure probability. However, the original Survival Signature is appropriate for binary systems, while engineering systems often exhibit multi-state characteristics and are subjected to uncertainties caused by various factors such as dynamic environment and performance degradation. Therefore, this paper introduces the extension of the Survival Signature from binary to multi-state formula and simultaneously considers the impact of mixed uncertainties on system reliability. For the probability distribution of multi-state components, a homogeneous Markov model is used for modeling and derivation. Component importance analysis is implemented and component sensitivity is quantified based on the double-loop Monte Carlo simulation method. Finally, the proposed method is applied to a bridge structure system, and the results show that the method has high feasibility for systems with regular state transition rules.","PeriodicalId":185173,"journal":{"name":"2023 9th International Symposium on System Security, Safety, and Reliability (ISSSR)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reliability Analysis of System with Uncertainty Based on Generalized Survival Signature\",\"authors\":\"J. Mi, Jie Hu, Yan-Feng Li, Dong-bai Sun\",\"doi\":\"10.1109/ISSSR58837.2023.00050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Survival Signature is a reliable modeling and analysis method that can effectively separate system structure function and component failure probability. However, the original Survival Signature is appropriate for binary systems, while engineering systems often exhibit multi-state characteristics and are subjected to uncertainties caused by various factors such as dynamic environment and performance degradation. Therefore, this paper introduces the extension of the Survival Signature from binary to multi-state formula and simultaneously considers the impact of mixed uncertainties on system reliability. For the probability distribution of multi-state components, a homogeneous Markov model is used for modeling and derivation. Component importance analysis is implemented and component sensitivity is quantified based on the double-loop Monte Carlo simulation method. Finally, the proposed method is applied to a bridge structure system, and the results show that the method has high feasibility for systems with regular state transition rules.\",\"PeriodicalId\":185173,\"journal\":{\"name\":\"2023 9th International Symposium on System Security, Safety, and Reliability (ISSSR)\",\"volume\":\"104 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 9th International Symposium on System Security, Safety, and Reliability (ISSSR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSSR58837.2023.00050\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 9th International Symposium on System Security, Safety, and Reliability (ISSSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSSR58837.2023.00050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reliability Analysis of System with Uncertainty Based on Generalized Survival Signature
Survival Signature is a reliable modeling and analysis method that can effectively separate system structure function and component failure probability. However, the original Survival Signature is appropriate for binary systems, while engineering systems often exhibit multi-state characteristics and are subjected to uncertainties caused by various factors such as dynamic environment and performance degradation. Therefore, this paper introduces the extension of the Survival Signature from binary to multi-state formula and simultaneously considers the impact of mixed uncertainties on system reliability. For the probability distribution of multi-state components, a homogeneous Markov model is used for modeling and derivation. Component importance analysis is implemented and component sensitivity is quantified based on the double-loop Monte Carlo simulation method. Finally, the proposed method is applied to a bridge structure system, and the results show that the method has high feasibility for systems with regular state transition rules.