Classification of common discharges in outdoor insulation using acoustic signals and artificial neural network

作     者：Satish Polisetty Ayman El-Hag Shesha Jayram 

作者机构：Electrical and Computer Engineering DepartmentUniversity of WaterlooWaterlooCanada 

出 版 物：《High Voltage》 (高电压（英文）)

年 卷 期：2019年第4卷第4期

页      面：333-338页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 080803[工学-高电压与绝缘技术] 08[工学] 081104[工学-模式识别与智能系统] 0807[工学-动力工程及工程热物理] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：ceramic insulation artificial 

摘      要：Condition monitoring of outdoor insulation systems is crucial to the integrity of distribution and transmission overhead lines and *** objective of this study is to use a commercial acoustic sensor along with artificial neural network(ANN),to classify different typical types of discharges in outdoor insulation ***,ANN was used to distinguish between five common electrical discharges that were generated under controlled ***,this approach was extended to include outdoor ceramic *** types of defects were tested under laboratory conditions,i.e.a crack in the ceramic disc,surface pollution discharge,and corona near the insulator *** a single disc,and three discs connected in an insulator string were tested with respect to these *** both controlled samples and full insulators,a recognition rate of more than 85%was achieved.