{"title":"利用电特征分析检测风力发电机绕组和机械问题的现场经验","authors":"K. Alewine, H. Penrose","doi":"10.1109/EIC47619.2020.9158573","DOIUrl":null,"url":null,"abstract":"Electrical Signature Analysis (ESA), while not a new technology, has only recently been utilized in identifying and predicting winding failures in wind turbine generators. This novel application of existing technology has been very successful in identifying problems in several models of generators as well as other drive train issues. This paper will present a review of the basic technology utilized and will present the results from testing several hundred turbines including some with supporting documentation from physical inspections and/or predicted failures. This methodology, which can be trended, provides critical reliability information to help plan and prioritize preventative maintenance actions during low production times as well as periodic provide condition reporting on those turbines where continuous monitoring information is not available.","PeriodicalId":286019,"journal":{"name":"2020 IEEE Electrical Insulation Conference (EIC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Field Experiences Utilizing Electrical Signature Analysis to Detect Winding and Mechanical Problems in Wind Turbine Generators\",\"authors\":\"K. Alewine, H. Penrose\",\"doi\":\"10.1109/EIC47619.2020.9158573\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Electrical Signature Analysis (ESA), while not a new technology, has only recently been utilized in identifying and predicting winding failures in wind turbine generators. This novel application of existing technology has been very successful in identifying problems in several models of generators as well as other drive train issues. This paper will present a review of the basic technology utilized and will present the results from testing several hundred turbines including some with supporting documentation from physical inspections and/or predicted failures. This methodology, which can be trended, provides critical reliability information to help plan and prioritize preventative maintenance actions during low production times as well as periodic provide condition reporting on those turbines where continuous monitoring information is not available.\",\"PeriodicalId\":286019,\"journal\":{\"name\":\"2020 IEEE Electrical Insulation Conference (EIC)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Electrical Insulation Conference (EIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EIC47619.2020.9158573\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Electrical Insulation Conference (EIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIC47619.2020.9158573","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Field Experiences Utilizing Electrical Signature Analysis to Detect Winding and Mechanical Problems in Wind Turbine Generators
Electrical Signature Analysis (ESA), while not a new technology, has only recently been utilized in identifying and predicting winding failures in wind turbine generators. This novel application of existing technology has been very successful in identifying problems in several models of generators as well as other drive train issues. This paper will present a review of the basic technology utilized and will present the results from testing several hundred turbines including some with supporting documentation from physical inspections and/or predicted failures. This methodology, which can be trended, provides critical reliability information to help plan and prioritize preventative maintenance actions during low production times as well as periodic provide condition reporting on those turbines where continuous monitoring information is not available.