摘要
在对径向基概率神经网络进行理论分析基础上,采用减法聚类方法确定它的隐中心矢量。提出了基于径向基概率神经网络的变压器故障诊断方法,并进行了实验研究。实验结果表明,径向基概率神经网络在准确性和快速性方面适用于变压器故障诊断。
On the basis of analyzing RBPNN in theory, subtractive clustering is used to detemine its hidden eentrie vector . A fault diagnosis of transformer is proposed based on RBPNN, and experimental study is carried out. The experimental result shows that it is applicable to fault diagnosis of transformer in accuracy and rapidness.
出处
《煤矿机械》
北大核心
2007年第10期198-200,共3页
Coal Mine Machinery
关键词
径向基概率神经网络
变压器
故障诊断
减法聚类
radial basis probabilistic neural networks
transformer
fault diagnosis
subractive clustering
