Abstract
A new method to identify sympathetic inrush and internal fault current of transformer based on W-DHNN is put forward. Wavelet analysis can detect the abrupt change of the current signal. And extract the feature vectors of the signal. The characteristic values as the input value of discrete Hopfield neural network. Then using discrete Hopfield neural network to discriminate sympathetic inrush and internal fault current. This paper uses PSCAD/EMTDC software to model and emulates different parameters of transformer and fault types. The results show that the method is feasible.
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