J. Andle, Jonathan P. Murray, David Lane, Tom Cunneen
{"title":"无处不在,在线,局部放电趋势","authors":"J. Andle, Jonathan P. Murray, David Lane, Tom Cunneen","doi":"10.1109/EIC.2018.8480888","DOIUrl":null,"url":null,"abstract":"There is an increasing awareness of the role partial discharge monitoring plays in extending the operational life of electric power assets. For years, high value assets have undergone a periodic, off-line testing regimen; however, these tests are cost-prohibitive for the large numbers of transmission and distribution assets or even the electrical balance of plant equipment at generation facilities. This paper seeks to apply layered processing to extract meaningful information from real-time, on-line partial discharge signals, allowing asset health estimations from a highly reduced data stream consistent with distributed control systems.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ubiquitous, On-Line, Partial Discharge Trending\",\"authors\":\"J. Andle, Jonathan P. Murray, David Lane, Tom Cunneen\",\"doi\":\"10.1109/EIC.2018.8480888\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There is an increasing awareness of the role partial discharge monitoring plays in extending the operational life of electric power assets. For years, high value assets have undergone a periodic, off-line testing regimen; however, these tests are cost-prohibitive for the large numbers of transmission and distribution assets or even the electrical balance of plant equipment at generation facilities. This paper seeks to apply layered processing to extract meaningful information from real-time, on-line partial discharge signals, allowing asset health estimations from a highly reduced data stream consistent with distributed control systems.\",\"PeriodicalId\":184139,\"journal\":{\"name\":\"2018 IEEE Electrical Insulation Conference (EIC)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Electrical Insulation Conference (EIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EIC.2018.8480888\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Electrical Insulation Conference (EIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIC.2018.8480888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
There is an increasing awareness of the role partial discharge monitoring plays in extending the operational life of electric power assets. For years, high value assets have undergone a periodic, off-line testing regimen; however, these tests are cost-prohibitive for the large numbers of transmission and distribution assets or even the electrical balance of plant equipment at generation facilities. This paper seeks to apply layered processing to extract meaningful information from real-time, on-line partial discharge signals, allowing asset health estimations from a highly reduced data stream consistent with distributed control systems.