Neural Networks based fault diagnosis of ac motors

This paper presents an Artificial Neural Network (ANN) technique to recognize the incipient faults of an AC motor such as a synchronous motor. The proposed ANN-based fault detector is developed using the Resilient Error Back Propagation (RPROP) training algorithm. The fast and reliable method f...

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Main Authors: K.S., Rama Rao, Muhammad, Aariff Yahya
Format: Conference or Workshop Item
Language:English
Published: 2008
Subjects:
Online Access:http://scholars.utp.edu.my/id/eprint/2639/
http://scholars.utp.edu.my/id/eprint/2639/1/NN_-_ac_motors_-_IEEE_ITSIM2008_-_Aug_2008.pdf
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author K.S., Rama Rao
Muhammad, Aariff Yahya
author_facet K.S., Rama Rao
Muhammad, Aariff Yahya
author_sort K.S., Rama Rao
building UTP Institutional Repository
collection Online Access
description This paper presents an Artificial Neural Network (ANN) technique to recognize the incipient faults of an AC motor such as a synchronous motor. The proposed ANN-based fault detector is developed using the Resilient Error Back Propagation (RPROP) training algorithm. The fast and reliable method for multilayer neural networks converges much faster than the conventional back propagation algorithm. The main causes to diagnose three major faults are investigated and validated by adopting feed-forward back propagation neural networks.
first_indexed 2025-11-13T07:27:53Z
format Conference or Workshop Item
id oai:scholars.utp.edu.my:2639
institution Universiti Teknologi Petronas
institution_category Local University
language English
last_indexed 2025-11-13T07:27:53Z
publishDate 2008
recordtype eprints
repository_type Digital Repository
spelling oai:scholars.utp.edu.my:26392017-01-19T08:26:09Z http://scholars.utp.edu.my/id/eprint/2639/ Neural Networks based fault diagnosis of ac motors K.S., Rama Rao Muhammad, Aariff Yahya TK Electrical engineering. Electronics Nuclear engineering This paper presents an Artificial Neural Network (ANN) technique to recognize the incipient faults of an AC motor such as a synchronous motor. The proposed ANN-based fault detector is developed using the Resilient Error Back Propagation (RPROP) training algorithm. The fast and reliable method for multilayer neural networks converges much faster than the conventional back propagation algorithm. The main causes to diagnose three major faults are investigated and validated by adopting feed-forward back propagation neural networks. 2008-08-26 Conference or Workshop Item PeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/2639/1/NN_-_ac_motors_-_IEEE_ITSIM2008_-_Aug_2008.pdf K.S., Rama Rao and Muhammad, Aariff Yahya (2008) Neural Networks based fault diagnosis of ac motors. In: IEEE International Symposium on Information Technology 2008, ITSIM 2008, 26-28 Aug 2008, Kuala Lumpur, Malaysia.
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
K.S., Rama Rao
Muhammad, Aariff Yahya
Neural Networks based fault diagnosis of ac motors
title Neural Networks based fault diagnosis of ac motors
title_full Neural Networks based fault diagnosis of ac motors
title_fullStr Neural Networks based fault diagnosis of ac motors
title_full_unstemmed Neural Networks based fault diagnosis of ac motors
title_short Neural Networks based fault diagnosis of ac motors
title_sort neural networks based fault diagnosis of ac motors
topic TK Electrical engineering. Electronics Nuclear engineering
url http://scholars.utp.edu.my/id/eprint/2639/
http://scholars.utp.edu.my/id/eprint/2639/1/NN_-_ac_motors_-_IEEE_ITSIM2008_-_Aug_2008.pdf