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自适应神经网络在发电机组故障诊断中的应用
引用本文:万书亭,李和明,李永刚.自适应神经网络在发电机组故障诊断中的应用[J].华北电力大学学报,2002,29(2):99-102.
作者姓名:万书亭  李和明  李永刚
作者单位:1. 华北电力大学机械工程系,河北保定,071003
2. 华北电力大学电力工程系,河北保定,071003
摘    要:提出了自适应学习率及动量因子的BP神经网络算法和误差逼近度渐近收缩学习的BP神经网络算法,并将其应用于汽轮发电机组振动故障诊断与识别。实例结果表明,该算法学习收敛较快,误差曲线平稳,不会引起误差曲线振荡,对复合故障的识别性能好。

关 键 词:汽轮发电机组  误差逼近度  人工神经网络  故障诊断与识别
文章编号:1007-2691(2002)02-0099-04

Study of adaptive neural network for fault diagnosis of steam-turbine generator unit
WAN Shu-ting,LI He-ming,LI Yong-gang.Study of adaptive neural network for fault diagnosis of steam-turbine generator unit[J].Journal of North China Electric Power University,2002,29(2):99-102.
Authors:WAN Shu-ting  LI He-ming  LI Yong-gang
Abstract:The improved BP algorithms based on adaptive parameters adjustment and error contracting gradually are presented, which are applied successfully to fault diagnosis of steam- turbine generator unit. The simulation results show that these methods have better learning and diagnostic properties to complex faults.
Keywords:steam turbine-generator set  error contracting  artificial neural network  failure diagnosis
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