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基于遗传-神经网络的凝汽器故障诊断研究
引用本文:吴立锋,郭世利,衡世权,杨广华.基于遗传-神经网络的凝汽器故障诊断研究[J].电站辅机,2004,25(3):8-11.
作者姓名:吴立锋  郭世利  衡世权  杨广华
作者单位:东北电力学院自动化系,吉林省,吉林市,132012;东北电力学院应用化学系,吉林省,吉林市,132012
摘    要:综合遗传算法的全局优化和神经网络的并行计算等特点 ,提出了一种基于遗传 -神经网络的凝汽器故障诊断的方法。用遗传算法来优化神经网络权值 ,克服了神经网络易陷入局部解的缺陷 ,使神经网络具有较好的全局性和收敛速度。具体故障诊断实例表明 ,该方法诊断准确 ,具有一定的应用价值

关 键 词:神经网络  遗传算法  凝汽器  故障诊断
文章编号:1672-0210(2004)03-0008-04
修稿时间:2004年1月8日

Study on Fault Diagnosis of the Steam Condenser based on Genetic-neural Network
WU Lifeng,GUO Shili,HENG Shiquan\,YANG Guanghug\.Study on Fault Diagnosis of the Steam Condenser based on Genetic-neural Network[J].Power Station Auxiliary Equipment,2004,25(3):8-11.
Authors:WU Lifeng  GUO Shili  HENG Shiquan\  YANG Guanghug\
Affiliation:WU Lifeng~1,GUO Shili~2,HENG Shiquan\+2,YANG Guanghug\+1
Abstract:The global search capabilities of the genetic algorithm and the parallel computation of the neural networks is combined and Genetic-based neural networks(GNNs) for the fault diagnosis of steam condenser is presented. The network connection weights are optimized by the genetic algorithm,so the network is in whole and rapid convergence. A real condenser fault is reliably diagnosed by this method.
Keywords:neural network  genetic algorithm  steam condenser  fault diagnosis
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