Elie Al-Ahmar, Mohamed Benbouzid, Yassine Amirat, S. Benelghali
{"title":"基于离散小波变换的dfig风电机组故障诊断","authors":"Elie Al-Ahmar, Mohamed Benbouzid, Yassine Amirat, S. Benelghali","doi":"10.1109/ICELMACH.2008.4800033","DOIUrl":null,"url":null,"abstract":"This paper deals with the investigation of a specific transient technique suitable for electrical and mechanical fault diagnosis in a DFIG-based wind turbine. The investigated technique is a combination of the discrete wavelet transform, statistics and the energy. Experimental investigations carried out on a 1.1-kW induction generator based test bench show that the proposed technique can unambiguously diagnose faults under transient conditions.","PeriodicalId":416125,"journal":{"name":"2008 18th International Conference on Electrical Machines","volume":"149 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"DFIG-based wind turbine fault diagnosis using a specific discrete wavelet transform\",\"authors\":\"Elie Al-Ahmar, Mohamed Benbouzid, Yassine Amirat, S. Benelghali\",\"doi\":\"10.1109/ICELMACH.2008.4800033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with the investigation of a specific transient technique suitable for electrical and mechanical fault diagnosis in a DFIG-based wind turbine. The investigated technique is a combination of the discrete wavelet transform, statistics and the energy. Experimental investigations carried out on a 1.1-kW induction generator based test bench show that the proposed technique can unambiguously diagnose faults under transient conditions.\",\"PeriodicalId\":416125,\"journal\":{\"name\":\"2008 18th International Conference on Electrical Machines\",\"volume\":\"149 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 18th International Conference on Electrical Machines\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICELMACH.2008.4800033\",\"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 18th International Conference on Electrical Machines","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICELMACH.2008.4800033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DFIG-based wind turbine fault diagnosis using a specific discrete wavelet transform
This paper deals with the investigation of a specific transient technique suitable for electrical and mechanical fault diagnosis in a DFIG-based wind turbine. The investigated technique is a combination of the discrete wavelet transform, statistics and the energy. Experimental investigations carried out on a 1.1-kW induction generator based test bench show that the proposed technique can unambiguously diagnose faults under transient conditions.