Abstract
In order to make the transmission line fault diagnosis more intelligent and adapt to the needs of big data, this paper proposes a transmission line fault diagnosis method based on variational mode decomposition (VMD) and bidirectional long-short-term memory network (BiLSTM). The bidirectional longterm and short-term memory network includes a bidirectional LSTM layer, a fully connected layer, and a softmax layer. The zero-sequence current after line fault is extracted, and it is subjected to variational modal decomposition. The decomposed modal signal and the original signal are input into the bidirectional long-short-term memory network for fault diagnosis. Through simulation comparison with other fault diagnosis methods, it is proved that the method of this paper has higher diagnostic accuracy and the method of this paper has high stability.
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