{"title":"电力电子学中数据驱动预测的综述","authors":"Ahsanul Kabir, Chris Bailey, Hua Lu, S. Stoyanov","doi":"10.1109/ISSE.2012.6273136","DOIUrl":null,"url":null,"abstract":"The discipline that connects prognostics and system lifecycle management is often referred to as prognostics and health management (PHM). Though prognostics is one of the main parts of PHM, it is the least mature. This paper is based on the past work of data driven prognostics applied in the field of power electronics modules and primarily concerned with the data driven prognostics methods that take advantage of measured characteristics of individual systems or components in order to predict the remaining useful life (RUL).","PeriodicalId":277579,"journal":{"name":"2012 35th International Spring Seminar on Electronics Technology","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"A review of data-driven prognostics in power electronics\",\"authors\":\"Ahsanul Kabir, Chris Bailey, Hua Lu, S. Stoyanov\",\"doi\":\"10.1109/ISSE.2012.6273136\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The discipline that connects prognostics and system lifecycle management is often referred to as prognostics and health management (PHM). Though prognostics is one of the main parts of PHM, it is the least mature. This paper is based on the past work of data driven prognostics applied in the field of power electronics modules and primarily concerned with the data driven prognostics methods that take advantage of measured characteristics of individual systems or components in order to predict the remaining useful life (RUL).\",\"PeriodicalId\":277579,\"journal\":{\"name\":\"2012 35th International Spring Seminar on Electronics Technology\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 35th International Spring Seminar on Electronics Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSE.2012.6273136\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 35th International Spring Seminar on Electronics Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSE.2012.6273136","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A review of data-driven prognostics in power electronics
The discipline that connects prognostics and system lifecycle management is often referred to as prognostics and health management (PHM). Though prognostics is one of the main parts of PHM, it is the least mature. This paper is based on the past work of data driven prognostics applied in the field of power electronics modules and primarily concerned with the data driven prognostics methods that take advantage of measured characteristics of individual systems or components in order to predict the remaining useful life (RUL).
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
