IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i8p2142-d1639316.html
   My bibliography  Save this article

Diagnosis of Stator Inter-Turn Short Circuit Faults in Synchronous Machines Based on SFRA and MTST

Author

Listed:
  • Junsheng Ding

    (College of Engineering and Technology, Southwest University, Chongqing 400700, China)

  • Zhongyong Zhao

    (College of Engineering and Technology, Southwest University, Chongqing 400700, China)

Abstract

As a key component of the power system, the good or bad conditions of synchronous machines will directly affect the stable supply of electric energy. The inter-turn short fault of the stator is one of the main dangers to the synchronous machine and is difficult to diagnose. Frequency response analysis has recently been introduced and used for detecting this type of fault; however, the fault degrees and locations cannot be directly recognized by traditional frequency response analysis. Therefore, this study improves the frequency response analysis by combining it with a deep learning model of a multivariate time series transformer. First, the principle of this study is introduced. Second, the frequency response data of short circuit faults are obtained using an artificially simulated experimental platform of a synchronous machine. The deep learning model is then well-trained. Finally, the performance of the proposed method is tested and verified. It concludes that the proposed method has the potential for classifying and diagnosing the inter-turn short circuit of stators in synchronous machines.

Suggested Citation

  • Junsheng Ding & Zhongyong Zhao, 2025. "Diagnosis of Stator Inter-Turn Short Circuit Faults in Synchronous Machines Based on SFRA and MTST," Energies, MDPI, vol. 18(8), pages 1-18, April.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:8:p:2142-:d:1639316
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/8/2142/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/8/2142/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alexandros Sergakis & Marios Salinas & Nikolaos Gkiolekas & Konstantinos N. Gyftakis, 2025. "A Review of Condition Monitoring of Permanent Magnet Synchronous Machines: Techniques, Challenges and Future Directions," Energies, MDPI, vol. 18(5), pages 1-35, February.
    2. Mingsheng Wang & Wuxuan Lai & Hong Zhang & Yang Liu & Qiang Song, 2024. "Intelligent Fault Diagnosis of Inter-Turn Short Circuit Faults in PMSMs for Agricultural Machinery Based on Data Fusion and Bayesian Optimization," Agriculture, MDPI, vol. 14(12), pages 1-27, November.
    3. Meysam Beheshti Asl & Issouf Fofana & Fethi Meghnefi & Youssouf Brahami & Joao Pedro Da Costa Souza, 2025. "A Comprehensive Review of Transformer Winding Diagnostics: Integrating Frequency Response Analysis with Machine Learning Approaches," Energies, MDPI, vol. 18(5), pages 1-38, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      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:18:y:2025:i:8:p:2142-:d:1639316. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.