{"title":"Partial discharge measurements: becoming a fundamental tool for quality control and risk assessment of electrical systems?","authors":"G. Montanari","doi":"10.1109/ELINSL.2006.1665312","DOIUrl":null,"url":null,"abstract":"This paper will introduce innovative technologies for partial discharge (PD) measurements, trying to answer to the common question that is associated with PD detection, that is, its effectiveness regarding fundamental items for asset management as risk assessment and maintenance planning. To this aim, the application of PD diagnosis to various electrical apparatus, specifically cables, generators and transformers, is discussed, emphasizing important features for PD detection and diagnosis such as noise cancellation, PD phenomena separation and identification, and PD source location","PeriodicalId":427638,"journal":{"name":"Conference Record of the 2006 IEEE International Symposium on Electrical Insulation","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of the 2006 IEEE International Symposium on Electrical Insulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELINSL.2006.1665312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
This paper will introduce innovative technologies for partial discharge (PD) measurements, trying to answer to the common question that is associated with PD detection, that is, its effectiveness regarding fundamental items for asset management as risk assessment and maintenance planning. To this aim, the application of PD diagnosis to various electrical apparatus, specifically cables, generators and transformers, is discussed, emphasizing important features for PD detection and diagnosis such as noise cancellation, PD phenomena separation and identification, and PD source location