Frequency response analysis for three-phase star and delta induction motors: pattern recognition and fault analysis using statistical indicators
This paper presents a new investigation to detect various faults within the three-phase star and delta induction motors (IMs) using a frequency response analysis (FRA). In this regard, experimental measurements using FRA are performed on three IMs of ratings 1 HP, 3 HP and 5.5 HP in normal condition...
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my.utm.1052502024-04-17T06:23:04Z http://eprints.utm.my/105250/ Frequency response analysis for three-phase star and delta induction motors: pattern recognition and fault analysis using statistical indicators Al-Ameri, Salem Mgammal Abdul Malek, Zulkurnain Salem, Ali Ahmed Ahmad Noorden, Zulkarnain Alawady, Ahmed Allawy Mohd. Yousof, Mohd. Fairouz Mosaad, Mohamed Ibrahim Abu Siada, Ahmed Thabit, Hammam Abdurabu TK Electrical engineering. Electronics Nuclear engineering This paper presents a new investigation to detect various faults within the three-phase star and delta induction motors (IMs) using a frequency response analysis (FRA). In this regard, experimental measurements using FRA are performed on three IMs of ratings 1 HP, 3 HP and 5.5 HP in normal conditions, short-circuit fault (SC) and open-circuit fault (OC) conditions. The SC and OC faults are applied artificially between the turns (Turn-to-Turn), between the coils (Coil-to-Coil) and between the phases (Phase-to-Phase). The obtained measurements show that the star and delta IMs result in dissimilar FRA signatures for the normal and faulty windings. Various statistical indicators are used to quantify the deviations between the normal and faulty FRA signatures. The calculation is performed in three frequency ranges: low, middle and high ones, as the winding parameters including resistive, inductive and capacitive components dominate the frequency characteristics at different frequency ranges. Consequently, it is proposed that the boundaries for the used indicators facilitate fault identification and quantification. MDPI 2023-01 Article PeerReviewed application/pdf en http://eprints.utm.my/105250/1/AliAhmedSalem2023_FrequencyResponseAnalysisforThree.pdf Al-Ameri, Salem Mgammal and Abdul Malek, Zulkurnain and Salem, Ali Ahmed and Ahmad Noorden, Zulkarnain and Alawady, Ahmed Allawy and Mohd. Yousof, Mohd. Fairouz and Mosaad, Mohamed Ibrahim and Abu Siada, Ahmed and Thabit, Hammam Abdurabu (2023) Frequency response analysis for three-phase star and delta induction motors: pattern recognition and fault analysis using statistical indicators. Machines, 11 (1). pp. 1-18. ISSN 2075-1702 http://dx.doi.org/10.3390/machines11010106 DOI:10.3390/machines11010106 |
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TK Electrical engineering. Electronics Nuclear engineering Al-Ameri, Salem Mgammal Abdul Malek, Zulkurnain Salem, Ali Ahmed Ahmad Noorden, Zulkarnain Alawady, Ahmed Allawy Mohd. Yousof, Mohd. Fairouz Mosaad, Mohamed Ibrahim Abu Siada, Ahmed Thabit, Hammam Abdurabu Frequency response analysis for three-phase star and delta induction motors: pattern recognition and fault analysis using statistical indicators |
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This paper presents a new investigation to detect various faults within the three-phase star and delta induction motors (IMs) using a frequency response analysis (FRA). In this regard, experimental measurements using FRA are performed on three IMs of ratings 1 HP, 3 HP and 5.5 HP in normal conditions, short-circuit fault (SC) and open-circuit fault (OC) conditions. The SC and OC faults are applied artificially between the turns (Turn-to-Turn), between the coils (Coil-to-Coil) and between the phases (Phase-to-Phase). The obtained measurements show that the star and delta IMs result in dissimilar FRA signatures for the normal and faulty windings. Various statistical indicators are used to quantify the deviations between the normal and faulty FRA signatures. The calculation is performed in three frequency ranges: low, middle and high ones, as the winding parameters including resistive, inductive and capacitive components dominate the frequency characteristics at different frequency ranges. Consequently, it is proposed that the boundaries for the used indicators facilitate fault identification and quantification. |
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Article |
author |
Al-Ameri, Salem Mgammal Abdul Malek, Zulkurnain Salem, Ali Ahmed Ahmad Noorden, Zulkarnain Alawady, Ahmed Allawy Mohd. Yousof, Mohd. Fairouz Mosaad, Mohamed Ibrahim Abu Siada, Ahmed Thabit, Hammam Abdurabu |
author_facet |
Al-Ameri, Salem Mgammal Abdul Malek, Zulkurnain Salem, Ali Ahmed Ahmad Noorden, Zulkarnain Alawady, Ahmed Allawy Mohd. Yousof, Mohd. Fairouz Mosaad, Mohamed Ibrahim Abu Siada, Ahmed Thabit, Hammam Abdurabu |
author_sort |
Al-Ameri, Salem Mgammal |
title |
Frequency response analysis for three-phase star and delta induction motors: pattern recognition and fault analysis using statistical indicators |
title_short |
Frequency response analysis for three-phase star and delta induction motors: pattern recognition and fault analysis using statistical indicators |
title_full |
Frequency response analysis for three-phase star and delta induction motors: pattern recognition and fault analysis using statistical indicators |
title_fullStr |
Frequency response analysis for three-phase star and delta induction motors: pattern recognition and fault analysis using statistical indicators |
title_full_unstemmed |
Frequency response analysis for three-phase star and delta induction motors: pattern recognition and fault analysis using statistical indicators |
title_sort |
frequency response analysis for three-phase star and delta induction motors: pattern recognition and fault analysis using statistical indicators |
publisher |
MDPI |
publishDate |
2023 |
url |
http://eprints.utm.my/105250/1/AliAhmedSalem2023_FrequencyResponseAnalysisforThree.pdf http://eprints.utm.my/105250/ http://dx.doi.org/10.3390/machines11010106 |
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