Fault diagnosis of rolling element bearings using artificial neural networks

被引：0
|
作者：
Rajamani, L [1 ]
Dattagupta, R [1 ]
机构：
[1] Osmania Univ, Dept Comp Sci & Engn, Hyderabad 500007, Andhra Pradesh, India
来源：
CRITICAL LINK: DIAGNOSIS TO PROGNOSIS | 1997年
关键词：
fault diagnosis; artificial neural network; rolling element bearings; vibration analysis; Kohonen network;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The basic concept of neural network and its application to diagnosis of rolling element bearings is described. Neural networks based on neurobiological systems are more adept at classification and identification tasks than conventional statistical and expert systems. In this paper the unsupevised learning method based on Kohonen network is used to study the classification of problem of common faults in rolling element bearings. Example patterns based on vibration analysis are used to train the network. The method successfully predicts the class of faults.
引用
收藏
页码：783 / 789
页数：7
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