首页 | 本学科首页   官方微博 | 高级检索  
     检索      

思维进化算法优化模糊神经网络的变压器故障诊断
引用本文:高金兰.思维进化算法优化模糊神经网络的变压器故障诊断[J].科学技术与工程,2011,11(13):2957-2961.
作者姓名:高金兰
作者单位:东北石油大学电气信息工程学院,大庆,163318
摘    要:提出一种基于思维进化算法的模糊神经网络变压器故障诊断方法。该方法利用思维进化算法中的趋同和异化操作,对模糊神经网络中输入变量的隶属度函数位置参数和宽度参数以及神经网络的连接权值进行全局优化,可有效地克服常规模糊神经网络BP算法收敛速度慢、精度不高和遗传算法训练模糊神经网络速度缓慢、易陷入局部极小等缺点,有利于更快地收敛于全局最优解。并将其应用到基于溶解气体分析的变压器故障诊断中,实例表明,采用该方法具有较快的收敛速度和较高的诊断准确度,说明了该方法的正确性和有效性。

关 键 词:变压器  故障诊断  模糊神经网络  思维进化算法
收稿时间:2/15/2011 4:46:13 PM
修稿时间:2/15/2011 4:46:13 PM

Transformer Fault Diagnosis of Fuzzy Neural Network Based on Mind Evolutionary Algorithm
gaojinlan.Transformer Fault Diagnosis of Fuzzy Neural Network Based on Mind Evolutionary Algorithm[J].Science Technology and Engineering,2011,11(13):2957-2961.
Authors:gaojinlan
Institution:(College of Electrical & Information Engineering,Northeast Petroleum University,Daqing 163318,P.R.China)
Abstract:This paper proposes a new transformer fault diagnostic method using fuzzy neural network based on mind evolutionary algorithm. According to the similartaxis and dissimilation of mind evolutionary algorithm, the method optimizes the membership function parameter of input variable and connection weight in fuzzy neural network, and benefits to find the global optimal solution quickly. It can avoid the defects of conventional BP algorithm which has slow convergence and low precision. At the same time, it can remove the defects of GA which has slow training speed and local minimum. Simulation results of transformer fault diagnosis based on the dissolved gas analysis show that this method improved convergence speed and diagnosis accuracy to some extent and it is effective.
Keywords:
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《科学技术与工程》浏览原始摘要信息
点击此处可从《科学技术与工程》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号