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Novel Diagnostic Techniques for Rotating Electrical Machines—A Review

Author

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  • Lucia Frosini

    (Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Via Ferrata 5, 27100 Pavia, Italy)

Abstract

This paper aims to update the review of diagnostic techniques for rotating electrical machines of different type and size. Each of the main sections of the paper is focused on a specific component of the machine (stator and rotor windings, magnets, bearings, airgap, load and auxiliaries, stator and rotor laminated core) and divided into subsections when the characteristics of the component are different according to the type or size of the machine. The review considers both the techniques currently applied on field for the diagnostics of the electrical machines and the novel methodologies recently proposed by the researchers in the literature.

Suggested Citation

  • Lucia Frosini, 2020. "Novel Diagnostic Techniques for Rotating Electrical Machines—A Review," Energies, MDPI, vol. 13(19), pages 1-26, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5066-:d:420450
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    Citations

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    Cited by:

    1. Karolina Kudelina & Bilal Asad & Toomas Vaimann & Anton Rassõlkin & Ants Kallaste & Huynh Van Khang, 2021. "Methods of Condition Monitoring and Fault Detection for Electrical Machines," Energies, MDPI, vol. 14(22), pages 1-20, November.
    2. Artem Ermolaev & Vladimir Erofeev & Aleksandr Plekhov & Dmitry Titov, 2022. "Magnetic Vibration in Induction Motor Caused by Supply Voltage Distortion," Energies, MDPI, vol. 15(24), pages 1-11, December.
    3. Maciej Skowron & Czeslaw T. Kowalski & Teresa Orlowska-Kowalska, 2022. "Impact of the Convolutional Neural Network Structure and Training Parameters on the Effectiveness of the Diagnostic Systems of Modern AC Motor Drives," Energies, MDPI, vol. 15(19), pages 1-22, September.
    4. Tomas Garcia-Calva & Daniel Morinigo-Sotelo & Vanessa Fernandez-Cavero & Rene Romero-Troncoso, 2022. "Early Detection of Faults in Induction Motors—A Review," Energies, MDPI, vol. 15(21), pages 1-18, October.
    5. Muhammad Amir Khan & Bilal Asad & Karolina Kudelina & Toomas Vaimann & Ants Kallaste, 2022. "The Bearing Faults Detection Methods for Electrical Machines—The State of the Art," Energies, MDPI, vol. 16(1), pages 1-54, December.
    6. Xiaohua Song & Jing Liu & Chaobo Chen & Song Gao, 2022. "Advanced Methods in Rotating Machines," Energies, MDPI, vol. 15(15), pages 1-3, July.

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