Intelligent Detection Model for Power Grids Based on Graph Neural Networks
Guoliang Zhang, Yi Zhang, Zexu Du, Xiangquan Zhang, Liping Wang, Zhouqiang He · 2022 3rd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE) · 2022
With the rapid development of artificial intelligence and machine vision technology, power grid inspection system based on vision is widely used. However, the power grid intelligent inspection system has the problem of unsatisfactory accuracy of small target detection. To address this problem, this paper proposes an intelligent detection model for power grids based on graph neural networks. Firstly, the VGG16 model is used to construct the trunk feature extraction network. Secondly, the graph relation network between target and background is constructed. Finally, the defect detection model based on graph neural network is constructed. The model proposed in this article is compared with the existing object recognition model in the simulation of the different datasets. The average recognition accuracy of the proposed model is 0.858, which is improved by9.71%.