Research on Fault Detection Method for Substation Primary Equipment Based on Deep Convolutional Neural Network
This paper designs a substation primary equipment fault detection method:collecting images of the primary equipment in different lighting environments,creating equipment datasets and preprocessing them,and extracting equipment features for detection based on deep convolutional neural networks.After testing,this method can significantly reduce the missed and false alarm rates of primary equipment faults in substations.
万方数据
维普
