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

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....

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Main Authors: Che Soh, Azura, Abdul Rahman, Ribhan Zafira
Format: Article
Language:English
Published: Akamai University 2009
Online Access:http://psasir.upm.edu.my/id/eprint/14735/1/Fault%20detection%20and%20diagnosis%20for%20DC%20motor%20in%20robot%20movement%20system%20using%20neural%20network.pdf
http://psasir.upm.edu.my/id/eprint/14735/
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spelling my.upm.eprints.147352015-11-04T00:57:13Z http://psasir.upm.edu.my/id/eprint/14735/ Fault detection and diagnosis for DC motor in robot movement system using neural network Che Soh, Azura Abdul Rahman, Ribhan Zafira 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. Akamai University 2009-05 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/14735/1/Fault%20detection%20and%20diagnosis%20for%20DC%20motor%20in%20robot%20movement%20system%20using%20neural%20network.pdf 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
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description 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.
format Article
author Che Soh, Azura
Abdul Rahman, Ribhan Zafira
spellingShingle Che Soh, Azura
Abdul Rahman, Ribhan Zafira
Fault detection and diagnosis for DC motor in robot movement system using neural network
author_facet Che Soh, Azura
Abdul Rahman, Ribhan Zafira
author_sort Che Soh, Azura
title Fault detection and diagnosis for DC motor in robot movement system using neural network
title_short Fault detection and diagnosis for DC motor in robot movement system using neural network
title_full Fault detection and diagnosis for DC motor in robot movement system using neural network
title_fullStr Fault detection and diagnosis for DC motor in robot movement system using neural network
title_full_unstemmed Fault detection and diagnosis for DC motor in robot movement system using neural network
title_sort fault detection and diagnosis for dc motor in robot movement system using neural network
publisher Akamai University
publishDate 2009
url http://psasir.upm.edu.my/id/eprint/14735/1/Fault%20detection%20and%20diagnosis%20for%20DC%20motor%20in%20robot%20movement%20system%20using%20neural%20network.pdf
http://psasir.upm.edu.my/id/eprint/14735/
_version_ 1643825723168784384
score 13.211869

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