IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i9p1644-d227146.html
   My bibliography  Save this article

Mode Recognition and Fault Positioning of Permanent Magnet Demagnetization for PMSM

Author

Listed:
  • Caixia Gao

    (School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China)

  • Yanjie Nie

    (School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China)

  • Jikai Si

    (School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China
    College of Electric Engineering, Zheng Zhou University, Zhengzhou 450001, China)

  • Ziyi Fu

    (School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China)

  • Haichao Feng

    (School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China)

Abstract

This paper proposes a demagnetization fault detection, mode recognition, magnetic pole positioning, and degree evaluation method for permanent magnet synchronous motors. First, the analytical model of the single-coil no-load back electromotive force (EMF) of demagnetization fault for Permanent magnet synchronous motor (PMSM) arbitrary magnetic poles is established. In the analytical model, the single-coil no-load back EMF residual of the health state and the single magnetic pole sequential demagnetization fault are calculated and normalized. Model results are used as the fault sample database. Second, the energy interval database of the single-coil no-load back EMF residual with different numbers of magnetic pole demagnetization is established. Demagnetization fault detection and degree evaluation are performed by the real-time acquired amplitudes of the single-coil no-load back EMF residual. The number of demagnetization poles is determined by comparing the energy of the single-coil no-load back EMF residual with the energy interval database. Demagnetization mode recognition and magnetic pole positioning are realized by analyzing the correlation coefficients between normalized the single-coil no-load back EMF residual and the fault sample database. Finally, results of analysis of the finite element simulation validate the feasibility and effectiveness of the proposed method.

Suggested Citation

  • Caixia Gao & Yanjie Nie & Jikai Si & Ziyi Fu & Haichao Feng, 2019. "Mode Recognition and Fault Positioning of Permanent Magnet Demagnetization for PMSM," Energies, MDPI, vol. 12(9), pages 1-14, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1644-:d:227146
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/9/1644/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/9/1644/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jie Chen & Jiajun Wang & Bo Yan, 2022. "Simulation Research on Deadbeat Direct Torque and Flux Control of Permanent Magnet Synchronous Motor," Energies, MDPI, vol. 15(9), pages 1-15, April.
    2. 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.
    3. Yinquan Yu & Haixi Gao & Qiping Chen & Peng Liu & Shuangxia Niu, 2022. "Demagnetization Fault Detection and Location in PMSM Based on Correlation Coefficient of Branch Current Signals," Energies, MDPI, vol. 15(8), pages 1-17, April.
    4. Jing Tang & Yongheng Yang & Jie Chen & Ruichang Qiu & Zhigang Liu, 2019. "Characteristics Analysis and Measurement of Inverter-Fed Induction Motors for Stator and Rotor Fault Detection," Energies, MDPI, vol. 13(1), pages 1-17, December.
    5. Apostolos Lamprokostopoulos & Epameinondas Mitronikas & Alexandra Barmpatza, 2022. "Detection of Demagnetization Faults in Axial Flux Permanent-Magnet Synchronous Wind Generators," Energies, MDPI, vol. 15(9), pages 1-15, April.
    6. Carlos Candelo-Zuluaga & Jordi-Roger Riba & Dinesh V. Thangamuthu & Antoni Garcia, 2020. "Detection of Partial Demagnetization Faults in Five-Phase Permanent Magnet Assisted Synchronous Reluctance Machines," Energies, MDPI, vol. 13(13), pages 1-17, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1644-:d:227146. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.