An artificial neural network application to fault detection of a rotor bearing system
Abstract
Purpose
To improve the application neural networks predictors on bearing systems and to investigate the exact neural model of the ball‐bearing system.
Design/methodology/approach
A feed forward neural network is designed to model‐bearing system. Two results are compared for finding the exact model of the system.
Findings
The results of the proposed neural network predictor gives superior performance for analysing the behaviour of ball bearing undergoing loading deformation.
Research limitations/implications
The results of the proposed neural network exactly follows desired results of the system. Neural network predictor can be employed in practical applications.
Practical implications
As theoretical and practical study is evaluated together, it is hoped that ball‐bearing designers and researchers will obtain significant results in this area.
Originality/value
This paper fulfils an identified research results need and offers practical investigation for an academic career and research. Also, It should be very helpful for industrial application of ball‐bearing systems.
Keywords
Citation
Taplak, H., Uzmay, İ. and Yıldırım, Ş. (2006), "An artificial neural network application to fault detection of a rotor bearing system", Industrial Lubrication and Tribology, Vol. 58 No. 1, pp. 32-44. https://doi.org/10.1108/00368790610640082
Publisher
:Emerald Group Publishing Limited
Copyright © 2006, Emerald Group Publishing Limited