{"title":"感应电动机电气和机械故障的诊断","authors":"H. Nakamura, Y. Yamamoto, Y. Mizuno","doi":"10.1109/CEIDP.2006.311984","DOIUrl":null,"url":null,"abstract":"This paper proposes a new method for fault diagnosis of induction motors based on Hidden Markov Model, which is widely used in the field of speech recognition. In order to carry out pattern recognition, current waveforms running in stator winding are analyzed for motors with short circuit fault in stator windings or with broken rotor bars. Frequency spectrum of current are also investigated. The usefulness of the proposed diagnosis method is verified through pattern recognitions for arbitrary current waveforms obtained by experiments.","PeriodicalId":219099,"journal":{"name":"2006 IEEE Conference on Electrical Insulation and Dielectric Phenomena","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Diagnosis of electrical and mechanical faults of induction motor\",\"authors\":\"H. Nakamura, Y. Yamamoto, Y. Mizuno\",\"doi\":\"10.1109/CEIDP.2006.311984\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a new method for fault diagnosis of induction motors based on Hidden Markov Model, which is widely used in the field of speech recognition. In order to carry out pattern recognition, current waveforms running in stator winding are analyzed for motors with short circuit fault in stator windings or with broken rotor bars. Frequency spectrum of current are also investigated. The usefulness of the proposed diagnosis method is verified through pattern recognitions for arbitrary current waveforms obtained by experiments.\",\"PeriodicalId\":219099,\"journal\":{\"name\":\"2006 IEEE Conference on Electrical Insulation and Dielectric Phenomena\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE Conference on Electrical Insulation and Dielectric Phenomena\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CEIDP.2006.311984\",\"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 Conference on Electrical Insulation and Dielectric Phenomena","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEIDP.2006.311984","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Diagnosis of electrical and mechanical faults of induction motor
This paper proposes a new method for fault diagnosis of induction motors based on Hidden Markov Model, which is widely used in the field of speech recognition. In order to carry out pattern recognition, current waveforms running in stator winding are analyzed for motors with short circuit fault in stator windings or with broken rotor bars. Frequency spectrum of current are also investigated. The usefulness of the proposed diagnosis method is verified through pattern recognitions for arbitrary current waveforms obtained by experiments.
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