Improved VGG Algorithm in Acoustic Fault Analysis of Substation Equipment
Substation equipment has the risk of failure due to long-term operation,equipment aging,external environment and other reasons.Therefore,effective monitoring and early warning of substation equipment faults has become the key to the safe operation of power system.The visual geometry group(VGG)algorithm is an in-depth analysis model based on convolutional neural network,which has multi-layer convolution and pooling layers,and can extract the fault feature sources from the audio signals of equipment,classify them and finally realize real-time analysis of the operation state of substation equipment.Therefore,this paper improves the audio signal feature extraction of VGG network substation equipment,so as to realize accurate identification and prediction of equipment faults.
visual geometry group(VGG)networksound frequency faultfault warningsubstation equipment
NETL
NSTL
万方数据
