Based on the Radial Basis Function neural network, a kind of fault auto-diagnosis system of dam safety monitoring is established.

基于径向基函数神经网络，建立了大坝安全自动化监测的非线性故障自诊断系统。

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In this paper, the model structure and the application of Radial Basis Function Neural Network (RBF NN) to fault diagnosis of power transformer is presented.

研究了径向基函数(RBF)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。

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This method can detect not only faults in primary substation, but also fault area in radial line between the primary substation and the secondary one (or switching station).

该方法不仅能够确定一级变电站的故障线路，而且能够在一级变电站与二级变电站(或开闭站)之间的辐射状线路上确定故障区域。

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