Training feedforward neural networks for fault diagnosis of ball bearing

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Training feedforward neural networks for fault diagnosis of ball bearing

Vibration-based condition monitoring plays important roles for early fault detection and diagnosis of expensive rotating machinery. This paper presents the application of a novel metaheuristic approach named chaos-enhanced stochastic fractal search (CFS) to train feedforward neural networks (FNNs) f...

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Bibliographic Details
Main Authors:	Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan, Raja Ahmad, Raja Mohd Kamil
Format:	Conference or Workshop Item
Language:	English
Published:	Centre for Advanced Research on Energy, Faculty of Mechanical Engineering, Universiti Teknikal Malaysia Melaka 2018
Online Access:	http://psasir.upm.edu.my/id/eprint/65091/ http://psasir.upm.edu.my/id/eprint/65091/1/68-73-1.pdf

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