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

基于改进BP神经网络的柴油机故障诊断研究
引用本文:黄勇,郭晓平.基于改进BP神经网络的柴油机故障诊断研究[J].汽车科技,2009(2):55-58.
作者姓名:黄勇  郭晓平
作者单位:大连理工大学,内燃机研究所,大连,116024
摘    要:根据柴油发动机故障与征兆之间关系来建立一种采用BP算法前馈型神经网络结构,然而采用标准BP算法对神经网络训练进行训练,但存在收敛速度慢等问题。因此,又采用添加动量项和自适应学习速率两种方法对标准BP算法进行改进,并将改进的BP算法运用于神经网络训练,结果表明改进的BP神经网络能够改善收敛速度慢的缺点,而且预测故障效果较好。

关 键 词:改进BP算法  神经网络  柴油机故障诊断

Fault Diagnosis in Diesel Engine Based on Improved BP Artificial Neural Network
HUANG Yong,GUO Xiao-ping.Fault Diagnosis in Diesel Engine Based on Improved BP Artificial Neural Network[J].Automobile Science and Technology,2009(2):55-58.
Authors:HUANG Yong  GUO Xiao-ping
Institution:Internal Combustion Institute of Dalian University of Technology;Dalian 116024;China
Abstract:This paper introduces a forward neural network with BP learning algorithm based on the relation between faults and symptoms in diesel engine,however,the convergence speed during training neural network with standard BP learning algorithm will be slow sometimes. Therefore,momentum term and self-correcting studying rate should also be adopted to improve BP learning algorithm. The result shows improved BP artificial neural network can accelerate convergence speed in training process,and predict the faults in d...
Keywords:improved BP learning algorithm  neural network  diesel faults diagnosis  
本文献已被 CNKI 维普 万方数据 等数据库收录!
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