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친환경 GIS를 위한 CNN 기반 부분방전 진단 기법 연구
김용화 韓國交通大學校 2023 한국교통대학교 논문집 Vol.58 No.-
This paper presents an analysis of partial discharge pattern recognition in Gas Insulated Switchgear (GIS) under sulfur hexafluoride (SF6) and g3 (Green Gas for Grid) insulations, in compliance with international climate agreements. While conventional studies suggest similarities in Phase Resolved Partial Discharge (PRPD) between SF6 and g3 gases, the proposed method shows differences in partial discharge characteristics using t-distributed Stochastic Neighbor Embedding (t-SNE). Also, we propose a Convolutional Neural Network (CNN)-based algorithm for classifying partial discharge patterns in eco-friendly GIS, achieving a remarkable 100% classification accuracy.