{"title":"Statistical Features and Determinism in Partial Discharge Data from Electrical Trees and Voids","authors":"N. Chalashkanov, Conor P. Clarke, S. Dodd","doi":"10.1109/CEIDP50766.2021.9705473","DOIUrl":null,"url":null,"abstract":"Partial discharge (PD) data obtained from electrical trees and void experiments were analyzed. Several correlations were identified between the various statistical parameters traditionally used in PD classification and deterministic features such as average power dissipation. The correlation coefficients were found to have very high values in the case of electrical trees. Numerical simulations of PD activity in tree structures and voids were then used to explain the origin of the observed dependencies. The correlations between the statistical parameters describing the PD data identified in this work, could potentially be used to improve the robustness and reliability of defect classification based on PD measurements.","PeriodicalId":6837,"journal":{"name":"2021 IEEE Conference on Electrical Insulation and Dielectric Phenomena (CEIDP)","volume":"36 1","pages":"598-602"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Conference on Electrical Insulation and Dielectric Phenomena (CEIDP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEIDP50766.2021.9705473","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Partial discharge (PD) data obtained from electrical trees and void experiments were analyzed. Several correlations were identified between the various statistical parameters traditionally used in PD classification and deterministic features such as average power dissipation. The correlation coefficients were found to have very high values in the case of electrical trees. Numerical simulations of PD activity in tree structures and voids were then used to explain the origin of the observed dependencies. The correlations between the statistical parameters describing the PD data identified in this work, could potentially be used to improve the robustness and reliability of defect classification based on PD measurements.