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Fault Detection of Permanent Magnet Synchronous Machines: An Overview.

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Title: Fault Detection of Permanent Magnet Synchronous Machines: An Overview.
Authors: Li, Henghui1 (AUTHOR) hli214@sheffield.ac.uk, Zhu, Zi-Qiang1 (AUTHOR) z.q.zhu@sheffield.ac.uk, Azar, Ziad2 (AUTHOR) ziad.azar@siemensgamesa.com, Clark, Richard2 (AUTHOR) richard.clark@siemensgamesa.com, Wu, Zhanyuan2 (AUTHOR) zhan-yuan.wu@siemensgamesa.com
Source: Energies (19961073). Feb2025, Vol. 18 Issue 3, p534. 44p.
Subjects: Permanent magnets, Demagnetization, Eccentrics (Machinery), Machinery, Signals & signaling
Abstract: These days, as the application of permanent magnet synchronous machines (PMSMs) and drive systems becomes popular, the reliability issue of PMSMs gains more and more attention. To improve the reliability of PMSMs, fault detection is one of the practical techniques that enables the early interference and mitigation of the faults and subsequently reduces the impact of the faults. In this paper, the state-of-the-art fault detection methods of PMSMs are systematically reviewed. Three typical faults, i.e., the inter-turn short-circuit fault, the PM partial demagnetization fault, and the eccentricity fault, are included. The existing methods are firstly classified into signal-, model-, and data-based methods, while the focus of this paper is laid on the signal sources and the signatures utilized in these methods. Based on this perspective, this paper intends to provide a new insight into the inherent commonalities and differences among these detection methods and thus inspire further innovation. Furthermore, comparison is conducted between methods based on different signatures. Finally, some issues in the existing methods are discussed, and future work is highlighted. [ABSTRACT FROM AUTHOR]
Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Fault Detection of Permanent Magnet Synchronous Machines: An Overview.
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  Data: <searchLink fieldCode="AR" term="%22Li%2C+Henghui%22">Li, Henghui</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hli214@sheffield.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Zhu%2C+Zi-Qiang%22">Zhu, Zi-Qiang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> z.q.zhu@sheffield.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Azar%2C+Ziad%22">Azar, Ziad</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> ziad.azar@siemensgamesa.com</i><br /><searchLink fieldCode="AR" term="%22Clark%2C+Richard%22">Clark, Richard</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> richard.clark@siemensgamesa.com</i><br /><searchLink fieldCode="AR" term="%22Wu%2C+Zhanyuan%22">Wu, Zhanyuan</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> zhan-yuan.wu@siemensgamesa.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Feb2025, Vol. 18 Issue 3, p534. 44p.
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  Data: <searchLink fieldCode="DE" term="%22Permanent+magnets%22">Permanent magnets</searchLink><br /><searchLink fieldCode="DE" term="%22Demagnetization%22">Demagnetization</searchLink><br /><searchLink fieldCode="DE" term="%22Eccentrics+%28Machinery%29%22">Eccentrics (Machinery)</searchLink><br /><searchLink fieldCode="DE" term="%22Machinery%22">Machinery</searchLink><br /><searchLink fieldCode="DE" term="%22Signals+%26+signaling%22">Signals & signaling</searchLink>
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  Data: These days, as the application of permanent magnet synchronous machines (PMSMs) and drive systems becomes popular, the reliability issue of PMSMs gains more and more attention. To improve the reliability of PMSMs, fault detection is one of the practical techniques that enables the early interference and mitigation of the faults and subsequently reduces the impact of the faults. In this paper, the state-of-the-art fault detection methods of PMSMs are systematically reviewed. Three typical faults, i.e., the inter-turn short-circuit fault, the PM partial demagnetization fault, and the eccentricity fault, are included. The existing methods are firstly classified into signal-, model-, and data-based methods, while the focus of this paper is laid on the signal sources and the signatures utilized in these methods. Based on this perspective, this paper intends to provide a new insight into the inherent commonalities and differences among these detection methods and thus inspire further innovation. Furthermore, comparison is conducted between methods based on different signatures. Finally, some issues in the existing methods are discussed, and future work is highlighted. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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      – SubjectFull: Permanent magnets
        Type: general
      – SubjectFull: Demagnetization
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      – SubjectFull: Eccentrics (Machinery)
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      – SubjectFull: Signals & signaling
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            NameFull: Li, Henghui
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              M: 02
              Text: Feb2025
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              Y: 2025
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