{"title":"一种基于信号检测理论的工况指标性能评估方法","authors":"Lun Zhang, N. Hu, Lei Hu, Zhe Cheng","doi":"10.1109/PHM.2016.7819863","DOIUrl":null,"url":null,"abstract":"Condition indicators are significant elements in condition monitoring systems. A condition indicator (CI) performance assessment method would help users to select effective CIs and improve fault diagnosis performance of condition monitoring system (CMS). Investigating of measurement influence factors shows that CIs obey normal distribution. Taking advantage of signal detection theory, a CI assessment method is proposed; Discriminability Index is used to evaluate ability of CIs to distinguish fault from health. Finally, the method is validated with experimental signals of bearing and gear, the result show that this method is effective to assess CI performance, and it could help to select CIs in CMS system.","PeriodicalId":202597,"journal":{"name":"2016 Prognostics and System Health Management Conference (PHM-Chengdu)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A condition indicator performance assessment method based on signal detection theory\",\"authors\":\"Lun Zhang, N. Hu, Lei Hu, Zhe Cheng\",\"doi\":\"10.1109/PHM.2016.7819863\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Condition indicators are significant elements in condition monitoring systems. A condition indicator (CI) performance assessment method would help users to select effective CIs and improve fault diagnosis performance of condition monitoring system (CMS). Investigating of measurement influence factors shows that CIs obey normal distribution. Taking advantage of signal detection theory, a CI assessment method is proposed; Discriminability Index is used to evaluate ability of CIs to distinguish fault from health. Finally, the method is validated with experimental signals of bearing and gear, the result show that this method is effective to assess CI performance, and it could help to select CIs in CMS system.\",\"PeriodicalId\":202597,\"journal\":{\"name\":\"2016 Prognostics and System Health Management Conference (PHM-Chengdu)\",\"volume\":\"96 1\",\"pages\":\"0\"},\"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 Prognostics and System Health Management Conference (PHM-Chengdu)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PHM.2016.7819863\",\"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 Prognostics and System Health Management Conference (PHM-Chengdu)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PHM.2016.7819863","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A condition indicator performance assessment method based on signal detection theory
Condition indicators are significant elements in condition monitoring systems. A condition indicator (CI) performance assessment method would help users to select effective CIs and improve fault diagnosis performance of condition monitoring system (CMS). Investigating of measurement influence factors shows that CIs obey normal distribution. Taking advantage of signal detection theory, a CI assessment method is proposed; Discriminability Index is used to evaluate ability of CIs to distinguish fault from health. Finally, the method is validated with experimental signals of bearing and gear, the result show that this method is effective to assess CI performance, and it could help to select CIs in CMS system.