With the continuous expansion of power grid,the system structure becomes more and more complex,and multiple faults occur frequently,which is the key and difficult point of fault diagnosis.In order to solve the problem of the large amount of fault processing data and the need for fast and accurate fault diagnosis of power grid,a fault diagnosis model of distribution network based on fuzzy optimized graph convolution neural network is proposed in this paper.Firstly,the collected characteristic data of distribution network fault lines are processed.Secondly,a fault diagnosis model based on graph convolutional neural network is built,and the membership function of distribution network faults is established by fuzzy theory.Finally,the trained model is used to diagnose the distribution network faults.The simulation results show that the accuracy of fuzzy optimized graph convolutional neural network for multi-fault diagnosis is higher than that of convolu-tional neural network and other methods.The diagnosis results of the proposed method are more accurate and the compre-hensive diagnosis effect is the best.
fuzzy optimizationgraph convolutional neural networkdistribution networkfault diagnosisclassification unit
万方数据
维普
