Song Wang1,*, Fei Xie1, Fengye Yang1, Shengxuan Qiu1, Chuang Liu2, Tong Li3
Energy Engineering, Vol.120, No.10, pp. 2273-2285, 2023, DOI:10.32604/ee.2023.030107
- 28 September 2023
Abstract Winding is one of the most important components in power transformers. Ensuring the health state of the winding is of great importance to the stable operation of the power system. To efficiently and accurately diagnose the disc space variation (DSV) fault degree of transformer winding, this paper presents a diagnostic method of winding fault based on the K-Nearest Neighbor (KNN) algorithm and the frequency response analysis (FRA) method. First, a laboratory winding model is used, and DSV faults with four different degrees are achieved by changing disc space of the discs in the winding. Then,… More >
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