{"title":"一种考虑系统拓扑的构件重要性度量方法","authors":"Min Luo, Yimiao Yao","doi":"10.1109/PHM-Yantai55411.2022.9942208","DOIUrl":null,"url":null,"abstract":"In order to solve the problem that the current importance measures cannot fully reflect the position of the components in rail transit vehicle, this paper proposes an importance measures method that considering system topology. Firstly, this method describes the topological structure of the system by complex network theory, and distinguishes different nodes by assigning attributes to them. Then, the improved grey relational analysis method is adopted to evaluate the importance of the components in the system by considering the properties of the components themselves and the statistical characteristics based on the complex network. Finally, the feasibility of the method is verified by a case study.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Component Importance Measure Considering System Topology\",\"authors\":\"Min Luo, Yimiao Yao\",\"doi\":\"10.1109/PHM-Yantai55411.2022.9942208\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve the problem that the current importance measures cannot fully reflect the position of the components in rail transit vehicle, this paper proposes an importance measures method that considering system topology. Firstly, this method describes the topological structure of the system by complex network theory, and distinguishes different nodes by assigning attributes to them. Then, the improved grey relational analysis method is adopted to evaluate the importance of the components in the system by considering the properties of the components themselves and the statistical characteristics based on the complex network. Finally, the feasibility of the method is verified by a case study.\",\"PeriodicalId\":315994,\"journal\":{\"name\":\"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PHM-Yantai55411.2022.9942208\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PHM-Yantai55411.2022.9942208","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Component Importance Measure Considering System Topology
In order to solve the problem that the current importance measures cannot fully reflect the position of the components in rail transit vehicle, this paper proposes an importance measures method that considering system topology. Firstly, this method describes the topological structure of the system by complex network theory, and distinguishes different nodes by assigning attributes to them. Then, the improved grey relational analysis method is adopted to evaluate the importance of the components in the system by considering the properties of the components themselves and the statistical characteristics based on the complex network. Finally, the feasibility of the method is verified by a case study.