Neuro-fuzzy Based Condition Prediction of Bearing Health-Reference-Cited by-同舟云学术

Neuro-fuzzy Based Condition Prediction of Bearing Health

Published:2009-03-20 Issue:7 Volume:15 Page:1079-1091
ISSN:1077-5463
Container-title:Journal of Vibration and Control
language:en
Short-container-title:Journal of Vibration and Control

Author:

Fagang Zhao ¹,Jin Chen ²,Lei Guo ²,Xinglin Li ³

Affiliation:

1. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China,

2. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China

3. State Test Laboratory of Hangzhou, Bearing Testing & Research Center, Hangzhou, 310088, China

Abstract

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.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Mechanics of Materials,Aerospace Engineering,Automotive Engineering,General Materials Science

Link

http://journals.sagepub.com/doi/pdf/10.1177/1077546309102665

Reference32 articles.

1. Pattern Classification

2. MULTIPLE BAND-PASS AUTOREGRESSIVE DEMODULATION FOR ROLLING-ELEMENT BEARING FAULT DIAGNOSIS

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