Applicability Analysis of Indices-Based Fault Detection Technique of Six-Phase Induction Motor
Type
ArticleKAUST Department
Ali I. Al-Naimi Petroleum Engineering Research Center (ANPERC)Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Electrical and Computer Engineering Program
Date
2021-09-17Permanent link to this record
http://hdl.handle.net/10754/671950
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The multiphase induction motor is considered to be the promising alternative to the conventional three-phase induction motor, especially in safety-critical applications because of its inherent fault-tolerant feature. Therefore, the attention of many researchers has been paid to develop different techniques for detecting various fault types of multiphase induction motors, to securely switch the control mode of the multiphase drive system to its post-fault operation mode. Therefore, several fault detection methods have been researched and adapted; one of these methods is the indices-based fault detection technique. This technique was firstly introduced to detect open-phase fault of multiphase induction motors. The main advantage of this technique is that its mathematical formulation is straightforward and can easily be understood and implemented. In this paper, the study of the indices-based fault detection technique has been extended to test its applicability in detecting some other stator and rotor fault types of multiphase induction motors, namely, open-phase, open-switch, bad connection and broken rotor bar faults. Experimental and simulation validations of this technique are also introduced using a 1 kW prototype symmetrical six-phase induction motor.Citation
Farag, K., Shawier, A., Abdel-Khalik, A. S., Ahmed, M. M., & Ahmed, S. (2021). Applicability Analysis of Indices-Based Fault Detection Technique of Six-Phase Induction Motor. Energies, 14(18), 5905. doi:10.3390/en14185905Publisher
MDPI AGJournal
EnergiesAdditional Links
https://www.mdpi.com/1996-1073/14/18/5905ae974a485f413a2113503eed53cd6c53
10.3390/en14185905
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Except where otherwise noted, this item's license is described as Archived with thanks to Energies. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).