摘要
研究采用径向基神经网络进行变压器故障诊断,以提高变压器故障诊断率。分析了径向基函数神经网络的结构和工作原理,确立了适合变压器故障诊断的网络学习算法,并设计了一个诊断变压器故障的三层径向基网络。通过采用 MATLAB 进行仿真实验,结果表明径向基神经网络是一很强的分类器,能够有效的对变压器故障进行诊断。
A diagnosis technology adopting Radial Basis Function Neural Networks is introduced to improve the diagnosis efficiency. The structure and fundamental of RBF neural network are analyzed, a study method for transformer fault diagnosis is determined and a three-layer RBF neural network is designed. It is proved by MATLAB experiment that RBF neural network is a strong classifier which is used to diagnose transformer fault effectively.
出处
《电气自动化》
北大核心
2008年第2期69-71,共3页
Electrical Automation
基金
院自然科学基金重点项目 ZK0728
关键词
变压器
径向基神经网络
故障诊断
transformer radial basis function neural network fault diagnosis
