Fault Detection of Discharge Sound Based on Convolutional Neural Network
A discharge sound detection method based on convolution neural network is proposed.Aiming at the partial discharge phe-nomenon caused by equipment insulation aging in power system,the acoustic signal detection method of terminal edge node is proposed to monitor the normal operation,partial discharge and fault status of the equipment in real time,and feed back the abnormal state to the operation and maintenance center through the edge calculation network.The system collects the audio data of discharge when the fault occurs through the edge node of the device terminal.These faults include normal operation,partial discharge and the state of the fault being occurred.The signal preprocessing and extraction can reflect the fault state of audio features.Then,the processed data are used as the input of the recognition model constructed by the convolutional neural networks.Experiments show that the average recognition rate of the proposed method is about 2%higher than that of classical deep neural network.
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