An artificial neural network application to fault detection of a rotor bearing system

摘要

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.