噪声与振动控制2011，Vol.31Issue(2)：94-98,5.DOI:10.3969/j.issn.1006-1355-2011.02.023
改进的BP神经网络在风机故障诊断中的应用
Application of Improved BP Neural Network in Fault Diagnosis of Fans
米江 1纪国宜1
作者信息
- 1. 南京航空航天大学,振动工程研究所,南京,210016
- 折叠
摘要
Abstract
An improved BP neural network with the methods of momentum and adaptive learning rate is applied to build the fault diagnosis system of the fans.In the process of training, standard training samples and samples with white noise are employed to train the neural network so that the neural network has some ability of fault tolerance.Results of the simulation and the fault diagnosis of a fan show that the improved BP neural network needs less training times, the learning efficiency is raised, and the phenomenon of trapping in the local minimum for the network is effectively repressed.This method is effective for the fault diagnosis of fans.关键词
振动与波/风机/故障诊断/改进的BP神经网络Key words
vibration and wave / fan / fault diagnosis / improved BP neural network分类
机械制造引用本文复制引用
米江,纪国宜..改进的BP神经网络在风机故障诊断中的应用[J].噪声与振动控制,2011,31(2):94-98,5.
