{"title":"资产故障概率的推导:状态和维护水平的影响","authors":"G. Anders, S. Otal, T. Hjartarson","doi":"10.1109/PES.2006.1708961","DOIUrl":null,"url":null,"abstract":"This paper describes how asset probabilities of failure can be derived from life expectancy curves that are based on asset age, failure data and specific asset knowledge. It is shown how asset failure probabilities can then be adjusted for individual assets through measurement of the actual asset condition by the application of Health Indices. This allows utilities to focus their attention on the highest risk assets and put in place the optimal strategies for intervention to mitigate risks. Such strategies may include adoption of optimal maintenance policies and the paper also presents an overview of a mathematical model for analyzing the effect of maintenance on failure probabilities and overall costs","PeriodicalId":267582,"journal":{"name":"2006 IEEE Power Engineering Society General Meeting","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Deriving asset probabilities of failure: effect of condition and maintenance levels\",\"authors\":\"G. Anders, S. Otal, T. Hjartarson\",\"doi\":\"10.1109/PES.2006.1708961\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes how asset probabilities of failure can be derived from life expectancy curves that are based on asset age, failure data and specific asset knowledge. It is shown how asset failure probabilities can then be adjusted for individual assets through measurement of the actual asset condition by the application of Health Indices. This allows utilities to focus their attention on the highest risk assets and put in place the optimal strategies for intervention to mitigate risks. Such strategies may include adoption of optimal maintenance policies and the paper also presents an overview of a mathematical model for analyzing the effect of maintenance on failure probabilities and overall costs\",\"PeriodicalId\":267582,\"journal\":{\"name\":\"2006 IEEE Power Engineering Society General Meeting\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE Power Engineering Society General Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PES.2006.1708961\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Power Engineering Society General Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PES.2006.1708961","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Deriving asset probabilities of failure: effect of condition and maintenance levels
This paper describes how asset probabilities of failure can be derived from life expectancy curves that are based on asset age, failure data and specific asset knowledge. It is shown how asset failure probabilities can then be adjusted for individual assets through measurement of the actual asset condition by the application of Health Indices. This allows utilities to focus their attention on the highest risk assets and put in place the optimal strategies for intervention to mitigate risks. Such strategies may include adoption of optimal maintenance policies and the paper also presents an overview of a mathematical model for analyzing the effect of maintenance on failure probabilities and overall costs