Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
Title Partial Discharge Pattern Recognition Considering Noise Elimination and Voltage Phase Lag
Authors 윤성호(Sungho Yoon) ; 안범(Beom An) ; 이상군(Sanggoon Lee) ; 김정태(Jeongtae Kim) ; 정연하(Yeonha Jung) ; 장태인(Taein Jang)
DOI https://doi.org/10.5370/KIEE.2020.69.7.1024
Page pp.1024-1032
ISSN 1975-8359
Keywords Partial discharge pattern recognition; Noise elimination; Voltage phase lag; Neural network; SVM
Abstract In this study, the effect of noise elimination and voltage phase lag on the partial discharge pattern recognition was studied to improve the accuracy of the partial discharge diagnosis of the XLPE transmission cable system. Recognition rates were compared by applying Neural Network and SVM techniques using statistical feature values extracted from physical quantities in PRPDA data such as discharge numbers and discharge amounts according to the voltage phase, which were measured through the commercial partial discharge diagnostic system for four different types of partial discharge models. As a result, it was found that the minimum noise elimination method showed high pattern recognition rate because it relatively preserved the partial discharge information, even though the background noise would not be clearly eliminated. In addition, for the effect of the voltage phase lag, the neural network did not show any meaningful effect, whereas SVM showed significantly lowered recognition rate.