| Title |
Intelligent Diagnosis System for DGA Using Fuzzy Pattern Classification and Neural Network |
| Authors |
조성민(Cho, Sung-Min) ; 권동진(Kweon, Dong-Jin) ; 남창현(Nam, Chang-Hyun) ; 김재철(Kim, Jae-Chul) |
| Keywords |
DGA ; Diagnosis ; Power Transformer ; Neural Network ; Fuzzy |
| Abstract |
The DGA (Dissolved Gases Analysis) technique has been widely using for fault diagnosis of the power transformers. Some electric power utility company establishes the criteria of DGA to improve reliability, because of difference of operation environment and design of power transformer. In this paper, we introduce intelligent diagnosis system for DGA result of KEPCO (Korea Electric Power Cooperation). This system can classify patterns type of gases ratio that frequently occurs in recent result of gases analysis using Fuzzy Inference. The classification of Patterns let us know that major causes of gases generation based on type of patterns. Finally, Neural Network based on patterns diagnose transformer. NN was trained using result data of DGA of actually faulted transformers recently. Result of intelligent diagnosis system is right well in comparison with actual inner inspection of transformers. |