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文章摘要
BP算法的研究及在汽轮机故障诊断中的应用
Research on Neural Network Algorithm and Application in Fault Diagnosis
Received:May 26, 2014  Revised:May 26, 2014
DOI:
中文关键词: L-M算法  N-W方法  BP神经网络  汽轮发电机  故障诊断
英文关键词: L-MSalgorithm  N-W method  BP neural network  turbo generator  fault diagnosis
基金项目:
Author NameAffiliationE-mail
SONG Ren-jie College of Information Engineering,Northeast Dianli University 1939811347@qq.com 
SHI Hai-li* College of Information Engineering,Northeast Dianli University 1303526446@qq.com 
LIU Li-yuan College of Electrical Engineering,Northeast Dianli University  
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中文摘要:
      运用Nguyen-Widrow方法初始化Levenberg-Marquardt算法中的变量参数,在此基础上,L-M算法在训练神经网络中的应用,减少网络训练时权值和阈值的调整次数,加快算法收敛速度,保证了误差为误差平面的全局最小值,并将使用N-W方法的L-M算法应用于汽轮发电机的故障诊断。经理论和实践证明:该方法提高了故障诊断的准确性和可靠性,并为转动机械提供了有效的故障诊断方法。
英文摘要:
      Using Nguyen-Widrow method initializes the variable parameters of the L-M algorithm, based on the application of Levenberg-Marquardt algorithm in multilayer feed-forward neural network training, reduce the number of the adjustment of the threshold value and the weight When the network training, speed up the convergence speed of BP algorithm, which ensures the global minimum of the error of plane, and apply the N-W method combined with L-M algorithm for fault diagnosis of steam turbine. The theory and practice has proved that: this method has improved the accuracy and reliability of fault diagnosis, which provides effective method for the turbo generator fault diagnosis.
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