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Applicability Analysis of Indices-Based Fault Detection Technique of Six-Phase Induction Motor

Author

Listed:
  • Khaled Farag

    (Department of Electrical Engineering, Alexandria University, Alexandria 21544, Egypt)

  • Abdullah Shawier

    (Department of Electrical Engineering, Alexandria University, Alexandria 21544, Egypt)

  • Ayman S. Abdel-Khalik

    (Department of Electrical Engineering, Alexandria University, Alexandria 21544, Egypt)

  • Mohamed M. Ahmed

    (Department of Electrical Engineering, Alexandria University, Alexandria 21544, Egypt)

  • Shehab Ahmed

    (CEMSE Division, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia)

Abstract

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.

Suggested Citation

  • Khaled Farag & Abdullah Shawier & Ayman S. Abdel-Khalik & Mohamed M. Ahmed & Shehab Ahmed, 2021. "Applicability Analysis of Indices-Based Fault Detection Technique of Six-Phase Induction Motor," Energies, MDPI, vol. 14(18), pages 1-23, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5905-:d:637728
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    References listed on IDEAS

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    1. Federico Barrero & Mario Bermudez & Mario J. Duran & Pedro Salas & Ignacio Gonzalez-Prieto, 2019. "Assessment of a Universal Reconfiguration-less Control Approach in Open-Phase Fault Operation for Multiphase Drives," Energies, MDPI, vol. 12(24), pages 1-12, December.
    2. Maciej Skowron & Teresa Orlowska-Kowalska & Marcin Wolkiewicz & Czeslaw T. Kowalski, 2020. "Convolutional Neural Network-Based Stator Current Data-Driven Incipient Stator Fault Diagnosis of Inverter-Fed Induction Motor," Energies, MDPI, vol. 13(6), pages 1-21, March.
    3. Zuolu Wang & Jie Yang & Haiyang Li & Dong Zhen & Yuandong Xu & Fengshou Gu, 2019. "Fault Identification of Broken Rotor Bars in Induction Motors Using an Improved Cyclic Modulation Spectral Analysis," Energies, MDPI, vol. 12(17), pages 1-20, August.
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    Cited by:

    1. Sarahi Aguayo-Tapia & Gerardo Avalos-Almazan & Jose de Jesus Rangel-Magdaleno & Juan Manuel Ramirez-Cortes, 2023. "Physical Variable Measurement Techniques for Fault Detection in Electric Motors," Energies, MDPI, vol. 16(12), pages 1-21, June.

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