关键词: 支持向量机, 径向基网络, 特征变换, 故障诊断

Abstract: An approach of Radial Basis Function Neural Network（RBF NN） optimization based on support vector machine was proposed to solve the randomness of the network structure and the unstableness of the network’s performance.The number of the hidden neurons，the value of the weight and bias in RBF neural network are determined by the trained SVM.The approach is adopted in modeling and diagnosing the fault of gear case.In the experiment，the input vectors are transformed with the SVM character extraction approach firstly and then trained with the optimized RBF.Experimental results indicate that the optimized RBF network can obtain stable performance and more accurate diagnosis.

Key words: Support Vector Machine, Radial Basis Function Neural Network, character transform, machinery fault diagnosis