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弹性BP神经网络的旋转机械故障诊断
Fault diagnosis for rotating machinery based on RPROP neural network
【摘要】 针对BP神经网络存在局部极小值和收敛速度慢等问题,提出了一种resilient backpropagation(RPROP)的改进BP网络。RPROP神经网络具有优良的非线性映射能力,可以很好地描述频率特征和诊断结果之间的关系,经改进算法训练的网络适合旋转机械故障诊断。
【Abstract】 A kind of BP neural network based on resilient backpropagation(RPROP)optimization algorithm is introduced in detail to overcome the disadvantages of standard BP algorithm.RPORP neural network is effective for dealing with non-linear mapping which can satisfactorily describe the non-linear relations between frequency character and diagnosis results.The improved BP neural network is suitable for diagnosis of rotating mechanical fault.
【关键词】 神经网络;
故障诊断;
旋转机械;
MATLAB;
【Key words】 neural network; fault diagnosis; rotating machinery; MATLAB;
【Key words】 neural network; fault diagnosis; rotating machinery; MATLAB;
【基金】 国家自然科学基金资助项目(50375017);北京市自然科学基金资助项目(3062008);北京市属市管高校人才强教计划资助项目;机电系统测控北京市重点实验室开放课题资助项目(KF20061123201,KF20061123202)
- 【文献出处】 北京机械工业学院学报 ,Journal of Beijing Institute of Machinery , 编辑部邮箱 ,2007年02期
- 【分类号】TP183;TP277
- 【被引频次】15
- 【下载频次】230