计算机与数字工程2017，Vol.45Issue(2)：291-298,8.DOI:10.3969/j.issn.1672-9722.2017.02.018
基于BP和WTA神经网络的滚动轴承故障诊断方法研究
Fault Diagnosis Method of Rolling Bearing Used BP and WTA Neural Networks
摘要
Abstract
This paper presents a novel pattern recognition method of fault diagnosis of rolling bearing which is based on BP and WTA neural networks.In the course of fault diagnosis, data on rolling bearing fault is transformed into desired feature vector to input to train BP-WTA, and diagnostic classification of BP and WTA neural network is obtained.By 144 experimental group samples to classify the degree of bearing damage, the diagnostic accuracy is expected to be 100% compared the BP and WTA Neural Networks with traditional method of BP and HMM, which shows that the proposed method is effective and practical in bearing fault diagnosis.关键词
BP/WTA/神经网络/滚动轴承/故障诊断/忆阻器Key words
BP/WTA/neural networks/rolling bearing/fault diagnosis/memristor分类
信息技术与安全科学引用本文复制引用
李成,于永斌,王舜燕,徐斌,金颖涛..基于BP和WTA神经网络的滚动轴承故障诊断方法研究[J].计算机与数字工程,2017,45(2):291-298,8.基金项目
国家自然科学基金(编号:61370202 （）
61550110248) （）
中央高校基本业务费(编号:ZYGX2013J041)资助. （编号:ZYGX2013J041）
