基于径向基函数网络的大型电力变压器故障诊断

Power Transformer Fault Diagnosis Based on Radial Basis Function Network

研究了径向基函数(R BF)神经网络的模型结构及其在电力变压器故障诊断中的实现方法,介绍了变压器故障诊断的R BF模型。通过故障诊断及仿真实例分析,将RB F网络与BP网络的性能进行比较,得出R BF神经网络训练速度快、逼近误差小、能够更有效地解决电力变压器故障诊断问题的结论。

In this paper, the model structure and the application of radial basis function neural network for fault diagnosis of power transformer is presented. By means of simulation test,the performances of RBF neural network and BP neural network are compared. The simulation result shows that the training rate and approaching error of the RBF neural network is higher and less respectively than those of the BP neural network. The RBF neural network is more effective for fault diagnosis.