Neural networks applied for 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 for mu...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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2008
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| Subjects: | |
| Online Access: | http://scholars.utp.edu.my/id/eprint/294/ http://scholars.utp.edu.my/id/eprint/294/1/paper.pdf |
| _version_ | 1848658953236381696 |
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| author | K.S., Rama Rao Yahya , M.A. |
| author_facet | K.S., Rama Rao Yahya , M.A. |
| 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. © 2008 IEEE.
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| first_indexed | 2025-11-13T07:22:43Z |
| format | Conference or Workshop Item |
| id | oai:scholars.utp.edu.my:294 |
| institution | Universiti Teknologi Petronas |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-13T07:22:43Z |
| publishDate | 2008 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:scholars.utp.edu.my:2942017-01-19T08:26:32Z http://scholars.utp.edu.my/id/eprint/294/ Neural networks applied for fault diagnosis of AC motors K.S., Rama Rao Yahya , M.A. 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 IEEE. 2008 Conference or Workshop Item NonPeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/294/1/paper.pdf K.S., Rama Rao and Yahya , M.A. (2008) Neural networks applied for fault diagnosis of AC motors. In: International Symposium on Information Technology 2008, ITSim, 26 August 2008 through 29 August 2008, Kuala Lumpur. http://www.scopus.com/inward/record.url?eid=2-s2.0-57349153136&partnerID=40&md5=9d2c0c34d9d795bf54d8e52692bd1ded |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering K.S., Rama Rao Yahya , M.A. Neural networks applied for fault diagnosis of AC motors |
| title | Neural networks applied for fault diagnosis of AC motors
|
| title_full | Neural networks applied for fault diagnosis of AC motors
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| title_fullStr | Neural networks applied for fault diagnosis of AC motors
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| title_full_unstemmed | Neural networks applied for fault diagnosis of AC motors
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| title_short | Neural networks applied for fault diagnosis of AC motors
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| title_sort | neural networks applied for fault diagnosis of ac motors |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://scholars.utp.edu.my/id/eprint/294/ http://scholars.utp.edu.my/id/eprint/294/ http://scholars.utp.edu.my/id/eprint/294/1/paper.pdf |