| Title |
Fault Pattern Analysis and Restoration Prediction Model Construction of Pole Transformer Using Data Mining Technique |
| Authors |
황우현(Hwang, Woo-Hyun) ; 김자희(Kim, Ja-Hee) ; 장완성(Jang, Wan-Sung) ; 홍정식(Hong, Jung-Sik) ; 한득수(Han, Deuk-Su) |
| Keywords |
Pole Transformer ; Data mining ; Decision Tree ; CART ; Pole Transformer Fault Pattern ; Fault Restoration Prediction Model |
| Abstract |
It is essential for electric power companies to have a quick restoration system of the faulted pole transformers which occupy most of transformers to supply stable electricity. However, it takes too much time to restore it when a transformer is out of order suddenly because we now count on operator in investigating causes of failure and making decision of recovery methods. This paper presents the concept of 'Fault pattern analysis and Restoration prediction model using Data mining techniques', which is based on accumulated fault record of pole transformers in the past. For this, it also suggests external and internal causes of fault which influence the fault pattern of pole transformers. It is expected that we can reduce not only defects in manufacturing procedure by upgrading quality but also the time of predicting fault patterns and recovering when faults occur by using the result. |