Research on the Intelligent Identification Method of the Substation Equipment Faults Based on Deep Learning
Wenle Song, Xiangyu Liu, Junlei Zhao, Menglin Wang, Yang Liu · 2020 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS) · 2020
With the rapid development of the intelligent power grid, the intelligent identification technology of the substation equipment faults also becomes more important. In this paper, the intelligent identification method of the substation equipment faults based on deep learning is designed. Alex Net and Dense Net of the two-channel network's convolutional neural network is used to conduct the intelligent identification for fever faults of power transformation equipment to do intelligent identification, so as to confirm the fever temperature and position of the equipment. This method helps a lot to overhaul fever faults for the substation equipment.