Fault Diagnosis Method of Rolling Bearing Based on BP Neural Network

被引：2
|
作者：
Huang Zhonghua [1 ,2 ]
Xie Ya [3 ]
机构：
[1] Cent S Univ, Coll Mech & Elect, Changsha, Hunan, Peoples R China
[2] China Aviat Power Plant Res Inst, Zhuzhou, Peoples R China
[3] College Int Econ, Dept Comp, Changsha, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION, VOL I | 2009年
基金：
中国国家自然科学基金;
关键词：
fault diagnosis; rolling bearing; BP neural network;
D O I：
10.1109/ICMTMA.2009.246
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A fault diagnosis method of rolling bearing based on BP neural network and time domain parameters of vibration signal was proposed to realize fast fault diagnosis. The input vectors of the BP neural network were skewness, kurtosis, peak and margin of vibration signal. The structure of the neural network was determined with simulation research. Gradient descending method,was used to train the parameters of BP neural network. Experiment results of fault diagnosis showed that with this method fast diagnosis of rolling bearing faults could be realized effectively.
引用
收藏
页码：647 / 649
页数：3
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