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Motion Characteristics and Defect Diagnosis of Metallic Particles in GIS/GIL.

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Title: Motion Characteristics and Defect Diagnosis of Metallic Particles in GIS/GIL.
Authors: He, Long1 (AUTHOR), Cao, Chen2 (AUTHOR) caochen@sut.edu.cn, Zhu, Yongming1 (AUTHOR), Ma, Baojun1,2 (AUTHOR), Lei, Huan1 (AUTHOR), Hu, Yan2 (AUTHOR)
Source: Energies (19961073). May2026, Vol. 19 Issue 9, p2138. 23p.
Subject Terms: *Particle motion, *Fault diagnosis, *Hilbert-Huang transform, *Partial discharge measurement, *Mechanical oscillations, *Electric power system reliability, *Metal inclusions
Abstract: The operational reliability of gas-insulated switchgear/gas-insulated transmission lines (GIS/GIL) is critically threatened by internal metallic particles, which serve as primary triggers for insulation degradation. Conventional partial discharge (PD) detection methods often lack sensitivity during the early stages of particle movement. To overcome these limitations, this study aims to develop a novel non-intrusive defect diagnosis methodology based on the analysis of mechanical vibration signals. The coupled particle motion model integrating the electrostatic field, particle tracking, and multibody dynamics has been established. This model reveals the dynamic law that metallic particles migrate toward the conductor and undergo charge polarity reversal after collision, with a maximum speed of 2.7 m/s. Meanwhile, the peak vibration acceleration excited by the collision is calculated as 0.02 m/s2. Accordingly, the high-voltage experimental platform with the full-scale prototype is built to simulate the actual operating conditions of the power grid. With the particle defects set inside the prototype, vibration signals are collected by using an accelerometer, and the measured peak vibration acceleration is 0.017 m/s2. Finally, a defect diagnosis method based on the Hilbert–Huang Transform (HHT) and correlation coefficient analysis is proposed. This method uses Empirical Mode Decomposition (EMD) to extract the IMF4 component of the signal in the vicinity of the 1000 Hz frequency band. When particle defects occur, the correlation coefficient between the IMF4 component and the original signal exceeds 0.7668. This vibration-based monitoring technique provides an alternative for the condition-based maintenance of GIS/GIL, offering significant engineering value for enhancing the safety and reliability of power transmission infrastructure. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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  Availability: 1
Header DbId: enr
DbLabel: Energy & Power Source
An: 193716034
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Motion Characteristics and Defect Diagnosis of Metallic Particles in GIS/GIL.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22He%2C+Long%22">He, Long</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cao%2C+Chen%22">Cao, Chen</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> caochen@sut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhu%2C+Yongming%22">Zhu, Yongming</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ma%2C+Baojun%22">Ma, Baojun</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lei%2C+Huan%22">Lei, Huan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hu%2C+Yan%22">Hu, Yan</searchLink><relatesTo>2</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2026, Vol. 19 Issue 9, p2138. 23p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Particle+motion%22">Particle motion</searchLink><br />*<searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink><br />*<searchLink fieldCode="DE" term="%22Hilbert-Huang+transform%22">Hilbert-Huang transform</searchLink><br />*<searchLink fieldCode="DE" term="%22Partial+discharge+measurement%22">Partial discharge measurement</searchLink><br />*<searchLink fieldCode="DE" term="%22Mechanical+oscillations%22">Mechanical oscillations</searchLink><br />*<searchLink fieldCode="DE" term="%22Electric+power+system+reliability%22">Electric power system reliability</searchLink><br />*<searchLink fieldCode="DE" term="%22Metal+inclusions%22">Metal inclusions</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The operational reliability of gas-insulated switchgear/gas-insulated transmission lines (GIS/GIL) is critically threatened by internal metallic particles, which serve as primary triggers for insulation degradation. Conventional partial discharge (PD) detection methods often lack sensitivity during the early stages of particle movement. To overcome these limitations, this study aims to develop a novel non-intrusive defect diagnosis methodology based on the analysis of mechanical vibration signals. The coupled particle motion model integrating the electrostatic field, particle tracking, and multibody dynamics has been established. This model reveals the dynamic law that metallic particles migrate toward the conductor and undergo charge polarity reversal after collision, with a maximum speed of 2.7 m/s. Meanwhile, the peak vibration acceleration excited by the collision is calculated as 0.02 m/s2. Accordingly, the high-voltage experimental platform with the full-scale prototype is built to simulate the actual operating conditions of the power grid. With the particle defects set inside the prototype, vibration signals are collected by using an accelerometer, and the measured peak vibration acceleration is 0.017 m/s2. Finally, a defect diagnosis method based on the Hilbert–Huang Transform (HHT) and correlation coefficient analysis is proposed. This method uses Empirical Mode Decomposition (EMD) to extract the IMF4 component of the signal in the vicinity of the 1000 Hz frequency band. When particle defects occur, the correlation coefficient between the IMF4 component and the original signal exceeds 0.7668. This vibration-based monitoring technique provides an alternative for the condition-based maintenance of GIS/GIL, offering significant engineering value for enhancing the safety and reliability of power transmission infrastructure. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/en19092138
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 23
        StartPage: 2138
    Subjects:
      – SubjectFull: Particle motion
        Type: general
      – SubjectFull: Fault diagnosis
        Type: general
      – SubjectFull: Hilbert-Huang transform
        Type: general
      – SubjectFull: Partial discharge measurement
        Type: general
      – SubjectFull: Mechanical oscillations
        Type: general
      – SubjectFull: Electric power system reliability
        Type: general
      – SubjectFull: Metal inclusions
        Type: general
    Titles:
      – TitleFull: Motion Characteristics and Defect Diagnosis of Metallic Particles in GIS/GIL.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: He, Long
      – PersonEntity:
          Name:
            NameFull: Cao, Chen
      – PersonEntity:
          Name:
            NameFull: Zhu, Yongming
      – PersonEntity:
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            NameFull: Ma, Baojun
      – PersonEntity:
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            NameFull: Lei, Huan
      – PersonEntity:
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            NameFull: Hu, Yan
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          Dates:
            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 19961073
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              Value: 19
            – Type: issue
              Value: 9
          Titles:
            – TitleFull: Energies (19961073)
              Type: main
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