Neuro-fuzzy Based Condition Prediction of Bearing Health

被引：65
|
作者：
Zhao, Fagang [1 ]
Chen, Jin [1 ]
Guo, Lei [1 ]
Li, Xinglin [2 ]
机构：
[1] Shanghai Jiao Tong Univ, State Key Lab Mech Syst & Vibrat, Shanghai 200240, Peoples R China
[2] Bearing Testing & Res Ctr, State Test Lab Hangzhou, Hangzhou 310088, Zhejiang, Peoples R China
来源：
JOURNAL OF VIBRATION AND CONTROL | 2009年 / 15卷 / 07期
基金：
国家高技术研究发展计划(863计划); 中国国家自然科学基金;
关键词：
Prediction; neuro-fuzzy; bearing vibration; RBF network; RESIDUAL LIFE; MODEL;
D O I：
10.1177/1077546309102665
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
A reliable prognostic model is very useful for industries to forecast equipment behaviors. The aim of this research is to verify the effectiveness of the neuro-fuzzy model in predicting the health condition of bearings. Simulation and an experiment have been carried out to verify the model, with results showing that the neuro-fuzzy model is a reliable and robust forecasting tool, and more accurate than a radial basis function network. In the experiment, vibration data collected from the equipment is used to predict the future condition.
引用
收藏
页码：1079 / 1091
页数：13
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