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RBF神经网络在异步电机故障诊断中的应用
引用本文:穆丽娟,苏晓娜,李晓明. RBF神经网络在异步电机故障诊断中的应用[J]. 火力与指挥控制, 2012, 37(6): 148-151
作者姓名:穆丽娟  苏晓娜  李晓明
作者单位:1. 山西煤炭职业技术学院,太原,030031
2. 太原理工大学电气与动力工程学院,太原,030024
摘    要:将径向基(RBF)神经网络应用到电机的故障诊断中,建立了异步电机的RBF神经网络诊断模型。为了克服RBF神经网络学习算法的不足,引入了差分进化(DE)算法,并且利用了差分进化(DE)算法的全局搜索能力来优化RBF神经网络基函数的中心、宽度以及网络的连接权值,以获得最优的网络模型。仿真结果表明优化后的RBF神经网络的泛化能力和诊断精度都得到了大幅度提高。

关 键 词:异步电机  故障诊断  径向基神经网络  差分进化算法

The Applications of the RBP Nerve Network in the Fault Diagnosis to the Asynchronous Motor
MU Li-juan , SU Xiao-na , LI Xiao-ming. The Applications of the RBP Nerve Network in the Fault Diagnosis to the Asynchronous Motor[J]. Fire Control & Command Control, 2012, 37(6): 148-151
Authors:MU Li-juan    SU Xiao-na    LI Xiao-ming
Affiliation:1.Shanxi Vocational and Technical College of Coal,Taiyuan 030031,China,2.College of Electrical and Power Engineering,Taiyuan University of Technology,Taiyuan 030024,China)
Abstract:This paper applies RBF neural network into the fault diagnosis of motor and constructs the RBF fault diagnosis model of motor.To overcome the limitations of RBF neural network,differential evolutionary algorithm is imported into this paper.The universal search ability of DE algorithm could help us to optimize center,width of basic function and network float weight of RBF neural network,and build the most suitable network model.The experimental result shows that the optimized RBF neural network’s generalization ability and diagnosis accuracy have be substantially improved.
Keywords:asynchronous motor  fault diagnosis  RBF neural network  differential evolution algorithm
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