Abstract: A multi-scale full-convolution timing model is proposed in order to detect the partial discharge phenomenon of high-voltage power lines in a timely manner. This method uses a multi-scale fully convolutional timing model to train the power signal data collected in high-voltage power lines. The trained model can be used to monitor the future continuous signal to detect whether it has a partial discharge phenomenon. The experimental results show that the model proposed has good accuracy on the used data set.

Key words: high-voltage power line, long short-term memory ( LSTM), multi-scale, full convolution, deep learning, partial discharge