Title :
Identification of faulty insulators by using corona discharge analysis based on artificial neural network
Author :
Li, C.R. ; Shi, Q. ; Cheng, Y.C. ; Yu, Chen ; Yichao, Yuan
Author_Institution :
Dept. of Electr. Eng., North China Electr. Power Univ., Qinghe, China
Abstract :
It was found from the tests in our laboratory that statistic analysis of insulator corona current pulses could identify the existence of faulty insulators on strings or transmission line towers. Some basic researches on corona discharge characteristics of insulators and insulator strings were investigated further in terms of polarity, amplitude, and pulse count of corona current pulses. Insulator corona characteristics are observed to be different from piece to piece. Therefore, a BP network was developed to classify voltage across an insulator and further identify the existence of faulty insulators on towers. It is confirmed that the developed BP network method yields satisfactory performance in terms of training time and quality of classification
Keywords :
backpropagation; charge measurement; corona; diagnostic expert systems; fault location; insulator testing; poles and towers; porcelain insulators; power engineering computing; power transmission lines; BP network; artificial neural network; classification; corona discharge analysis; corona discharge characteristics; faulty insulators; identification; insulator corona current pulses; insulator strings; insulators; polarity; porcelain insulator; pulse count; statistic analysis; strings; tests; training time; transmission line towers; Corona; Current measurement; Dielectrics and electrical insulation; Fault diagnosis; Insulator testing; Laboratories; Poles and towers; Power transformer insulation; Pulse measurements; Voltage;
Conference_Titel :
Electrical Insulation, 1998. Conference Record of the 1998 IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-4927-X
DOI :
10.1109/ELINSL.1998.694814