基于遗传-神经网络的凝汽器故障诊断研究  

Study on Fault Diagnosis of the Steam Condenser based on Genetic-neural Network

作　　者：吴立锋[1] 郭世利[2] 衡世权[2] 杨广华[1] 

机构地区：[1]东北电力学院自动化系,吉林省吉林市132012 [2]东北电力学院应用化学系,吉林省吉林市132012

出　　处：《电站辅机》2004年第3期8-11,共4页Power Station Auxiliary Equipment

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 。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.

关 键 词：神经网络 遗传算法 凝汽器 故障诊断 

分 类 号：TK264.11[动力工程及工程热物理—动力机械及工程]