龚瑞昆,周国庆

• 1:华北理工大学

摘要(Abstract)：

传统的BP神经网络诊断模型容易陷入局部最优,且诊断正确率较低,因此,提出将量子遗传算法应用于RBF网络诊断模型。首先确定RBF神经网络的输入输出、建立RBF网络模型,然后把归一化后的数据送入RBF网络模型,利用量子遗传算法对RBF神经网络进行优化,得到最优诊断模型,最后输出诊断结果。用Matlab进行仿真,其结果表明该算法解决了系统容易陷入局部最优的问题,在训练48代后就快速获得最优解,加快了网络的收敛速度。同时RBF神经网络的泛化能力也得到很好的改善,故障诊断正确率达93%,远远高于传统神经网络模型。

关键词(KeyWords)： 变压器;故障诊断;BP神经网络;量子计算;RBF神经网络;量子遗传算法

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(61271402)~~

作者(Author): 龚瑞昆,周国庆

DOI: 10.16652/j.issn.1004-373x.2018.15.029

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