Fault detection and diagnosis for DC motor in robot movement system using neural network

Citation

Che Soh, Azura and Abdul Rahman, Ribhan Zafira (2009) Fault detection and diagnosis for DC motor in robot movement system using neural network. The Pacific Journal of Science and Technology, 10 (1). pp. 35-43. ISSN 1551-7624

Abstract

Most of intelligent control in movement control involves fuzzy logic and neural network systems. In this research, a neural network is used to detect and diagnose the faults that may occur in a DC motor system during robot operations. The DC motor system is constructed using the SIMULINK® toolbox. This system provides the normal and faulty data that has been used for training purpose in the neural network system to get the normal and faulty models. Finally, from the simulation results, the neural network is able to recognize the system characteristic whether in normal conditions or faulty conditions.

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Additional Metadata

Item Type:	Article
Divisions:	Faculty of Engineering
Publisher:	Akamai University
Keywords:	Intelligent control; Neural network; Digital controller; DC motor; Robot movement
Depositing User:	Nabilah Mustapa
Date Deposited:	14 Aug 2015 12:27
Last Modified:	04 Nov 2015 00:57
URI:	http://psasir.upm.edu.my/id/eprint/14735
Statistic Details:	View Download Statistic

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