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Demagnetization Fault Diagnosis of a PMSM Using Auto-Encoder and K-Means Clustering

Author

Listed:
  • Lien-Kai Chang

    (Department of Mechanical Engineering, National Cheng Kung University, Tainan 701, Taiwan)

  • Shun-Hong Wang

    (Department of Mechanical Engineering, National Cheng Kung University, Tainan 701, Taiwan)

  • Mi-Ching Tsai

    (Department of Mechanical Engineering, National Cheng Kung University, Tainan 701, Taiwan)

Abstract

In recent years, many motor fault diagnosis methods have been proposed by analyzing vibration, sound, electrical signals, etc. To detect motor fault without additional sensors, in this study, we developed a fault diagnosis methodology using the signals from a motor servo driver. Based on the servo driver signals, the demagnetization fault diagnosis of permanent magnet synchronous motors (PMSMs) was implemented using an autoencoder and K-means algorithm. In this study, the PMSM demagnetization fault diagnosis was performed in three states: normal, mild demagnetization fault, and severe demagnetization fault. The experimental results indicate that the proposed method can achieve 96% accuracy to reveal the demagnetization of PMSMs.

Suggested Citation

  • Lien-Kai Chang & Shun-Hong Wang & Mi-Ching Tsai, 2020. "Demagnetization Fault Diagnosis of a PMSM Using Auto-Encoder and K-Means Clustering," Energies, MDPI, vol. 13(17), pages 1-12, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4467-:d:406187
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    References listed on IDEAS

    as
    1. Luqman Maraaba & Zakariya Al-Hamouz & Mohammad Abido, 2018. "An Efficient Stator Inter-Turn Fault Diagnosis Tool for Induction Motors," Energies, MDPI, vol. 11(3), pages 1-18, March.
    2. Maciej Skowron & Marcin Wolkiewicz & Teresa Orlowska-Kowalska & Czeslaw T. Kowalski, 2019. "Effectiveness of Selected Neural Network Structures Based on Axial Flux Analysis in Stator and Rotor Winding Incipient Fault Detection of Inverter-fed Induction Motors," Energies, MDPI, vol. 12(12), pages 1-20, June.
    3. Yumin Hsueh & Veeresha Ramesha Ittangihala & Wei-Bin Wu & Hong-Chan Chang & Cheng-Chien Kuo, 2019. "Condition Monitor System for Rotation Machine by CNN with Recurrence Plot," Energies, MDPI, vol. 12(17), pages 1-13, August.
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    Cited by:

    1. Piotr Mynarek & Janusz Kołodziej & Adrian Młot & Marcin Kowol & Marian Łukaniszyn, 2021. "Influence of a Winding Short-Circuit Fault on Demagnetization Risk and Local Magnetic Forces in V-Shaped Interior PMSM with Distributed and Concentrated Winding," Energies, MDPI, vol. 14(16), pages 1-16, August.
    2. Yinquan Yu & Pan Zhao & Yong Hao & Dequan Zeng & Yiming Hu & Bo Zhang & Hui Yang, 2022. "Multi Objective Optimization of Permanent Magnet Synchronous Motor Based on Taguchi Method and PSO Algorithm," Energies, MDPI, vol. 16(1), pages 1-11, December.

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