Research on Detection Method of Transformer Interturn Short Circuit Based on Wavelet Analysis
Distribution transformer is an important device in the power supply system, once its failure can cause power outages. According to statistics, 70% -80% of the transformer accident was caused by a short circuit between the transformer turns. Based on the large number of experimental data analysis and processing, a new inter-turn short circuit transformer diagnostic methods is proposed. In this paper, the ground current of transformer core as the signal source, Using wavelet multi-resolution technology the signal wavelet multiscale decomposition, the decomposition of different signals of the same scale, get the high frequency components of the signal, achieve short-circuit fault diagnosis between transformer winding turns by comparing the number of the high-frequency component contained in different signals in the decomposition of the same scale. To illustrate the effectiveness of the method, the paper through a series of experiments and data processing, verify the effectiveness and feasibility of the method.