{"title":"基于DCA的多级小故障诊断","authors":"F. Zhou, Tianhao Tang, Chenglin Wen","doi":"10.1109/ICCT.2008.4716084","DOIUrl":null,"url":null,"abstract":"To diagnose multiple faults of multivariate system, DCA (designated component analysis) is introduced to avoid the pattern compounding problem of PCA (principal component analysis). In this paper and a DCA based multi-level small fault diagnosis method is developed for multiple faults diagnosis when small faults are involved in the system. Simulation for observation data involved 4 faults shows its efficiency.","PeriodicalId":259577,"journal":{"name":"2008 11th IEEE International Conference on Communication Technology","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"DCA based multi-level small fault diagnosis\",\"authors\":\"F. Zhou, Tianhao Tang, Chenglin Wen\",\"doi\":\"10.1109/ICCT.2008.4716084\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To diagnose multiple faults of multivariate system, DCA (designated component analysis) is introduced to avoid the pattern compounding problem of PCA (principal component analysis). In this paper and a DCA based multi-level small fault diagnosis method is developed for multiple faults diagnosis when small faults are involved in the system. Simulation for observation data involved 4 faults shows its efficiency.\",\"PeriodicalId\":259577,\"journal\":{\"name\":\"2008 11th IEEE International Conference on Communication Technology\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 11th IEEE International Conference on Communication Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCT.2008.4716084\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 11th IEEE International Conference on Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCT.2008.4716084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
To diagnose multiple faults of multivariate system, DCA (designated component analysis) is introduced to avoid the pattern compounding problem of PCA (principal component analysis). In this paper and a DCA based multi-level small fault diagnosis method is developed for multiple faults diagnosis when small faults are involved in the system. Simulation for observation data involved 4 faults shows its efficiency.
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