Wireless fault tolerances decision using artificial intelligence technique
Wireless techniques utilized in industrial applications face significant challenges in preventing noise, collision, and data fusion, particularly when wireless sensors are used to identify and classify fault in real time for protection. This study will focus on the design of integrated wireless faul...
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Asian Research Publishing Network
2016
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Online Access: | http://eprints.utm.my/id/eprint/72583/1/MoneerAliLilo2016_WirelessFaultTolerancesDecision.pdf http://eprints.utm.my/id/eprint/72583/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969524609&partnerID=40&md5=6f9939023a0bb7fbe41b2211e1360a0e |
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my.utm.725832017-11-28T06:09:47Z http://eprints.utm.my/id/eprint/72583/ Wireless fault tolerances decision using artificial intelligence technique Lilo, M. A. Latiff, L. A. Abu, A. B. H. Al Mashhadany, Y. I. TA Engineering (General). Civil engineering (General) Wireless techniques utilized in industrial applications face significant challenges in preventing noise, collision, and data fusion, particularly when wireless sensors are used to identify and classify fault in real time for protection. This study will focus on the design of integrated wireless fault diagnosis system, which is protecting the induction motor (IM) from the vibration via decrease the speed. The filtering, signal processing, and Artificial Intelligent (AI) techniques are applied to improve the reliability and flexibility to prevent vibration increases on the IM. Wireless sensors of speed and vibration and card decision are designed based on the wireless application via the C++ related to the microcontroller, also, MATLAB coding was utilized to design the signal processing and the AI steps. The system was successful to identify the misalignment fault and dropping the speed when vibrations rising for preventing the damage may be happen on the IM. The vibration value reduced via the system producing response signal proportional with fault values based on modify the main speed signal to dropping the speed of IM. Asian Research Publishing Network 2016 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/72583/1/MoneerAliLilo2016_WirelessFaultTolerancesDecision.pdf Lilo, M. A. and Latiff, L. A. and Abu, A. B. H. and Al Mashhadany, Y. I. (2016) Wireless fault tolerances decision using artificial intelligence technique. Journal of Theoretical and Applied Information Technology, 87 (2). pp. 324-335. ISSN 1992-8645 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969524609&partnerID=40&md5=6f9939023a0bb7fbe41b2211e1360a0e |
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TA Engineering (General). Civil engineering (General) Lilo, M. A. Latiff, L. A. Abu, A. B. H. Al Mashhadany, Y. I. Wireless fault tolerances decision using artificial intelligence technique |
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Wireless techniques utilized in industrial applications face significant challenges in preventing noise, collision, and data fusion, particularly when wireless sensors are used to identify and classify fault in real time for protection. This study will focus on the design of integrated wireless fault diagnosis system, which is protecting the induction motor (IM) from the vibration via decrease the speed. The filtering, signal processing, and Artificial Intelligent (AI) techniques are applied to improve the reliability and flexibility to prevent vibration increases on the IM. Wireless sensors of speed and vibration and card decision are designed based on the wireless application via the C++ related to the microcontroller, also, MATLAB coding was utilized to design the signal processing and the AI steps. The system was successful to identify the misalignment fault and dropping the speed when vibrations rising for preventing the damage may be happen on the IM. The vibration value reduced via the system producing response signal proportional with fault values based on modify the main speed signal to dropping the speed of IM. |
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Article |
author |
Lilo, M. A. Latiff, L. A. Abu, A. B. H. Al Mashhadany, Y. I. |
author_facet |
Lilo, M. A. Latiff, L. A. Abu, A. B. H. Al Mashhadany, Y. I. |
author_sort |
Lilo, M. A. |
title |
Wireless fault tolerances decision using artificial intelligence technique |
title_short |
Wireless fault tolerances decision using artificial intelligence technique |
title_full |
Wireless fault tolerances decision using artificial intelligence technique |
title_fullStr |
Wireless fault tolerances decision using artificial intelligence technique |
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Wireless fault tolerances decision using artificial intelligence technique |
title_sort |
wireless fault tolerances decision using artificial intelligence technique |
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Asian Research Publishing Network |
publishDate |
2016 |
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http://eprints.utm.my/id/eprint/72583/1/MoneerAliLilo2016_WirelessFaultTolerancesDecision.pdf http://eprints.utm.my/id/eprint/72583/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969524609&partnerID=40&md5=6f9939023a0bb7fbe41b2211e1360a0e |
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