Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Online detection of partial discharge inside power transformer winding through IFRA

    Access Status
    Fulltext not available
    Authors
    Mohseni, B.
    Hashemnia, N.
    Islam, Syed
    Date
    2018
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Mohseni, B. and Hashemnia, N. and Islam, S. 2018. Online detection of partial discharge inside power transformer winding through IFRA, 2017 IEEE Power & Energy Society General Meeting, pp. 1-5: IEEE.
    Source Title
    IEEE Power and Energy Society General Meeting
    Source Conference
    2017 IEEE Power & Energy Society General Meeting
    DOI
    10.1109/PESGM.2017.8273725
    ISBN
    9781538622124
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/69107
    Collection
    • Curtin Research Publications
    Abstract

    © 2017 IEEE. Predictive maintenance offers substantial benefits for detecting the early signs of power transformer faults before they burgeon into catastrophic failures. Online impulse frequency response analysis is a recently-developed diagnostic method for in service transformer with a promising outlook. This paper aims to propose an online partial discharge detection method the online IFRA test. To emulate the dynamic performance characteristics of in service transformer, 3D finite element model of the transformer is calculated in Maxwell Software. In post processing, the FEM sub-circuit model is exported into an external Maxwell Spice circuit to study the terminal behaviors of the transformer. A pulse signal simulating PD is injected between sections of the LV winding. The S transform is then applied to the recorded input and output signals in healthy and faulty conditions to construct the electrical impedance as well as the time-frequency contours of the transient responses. Also, a mechanical deformation is imposed on the transformer to compare its impact on online IFRA to the impact of internal partial discharge.

    Related items

    Showing items related by title, author, creator and subject.

    • Application of online impulse technique to diagnose inter-turn short circuit in transformer windings
      Mohseni, B.; Hashemnia, N.; Islam, Syed; Zhao, Z. (2016)
      Inter-turn short circuit fault is a significant problem in power transformers which if not detected at early stages, can propagate in power networks and eventually burgeon into catastrophic faults and substantial costs. ...
    • Finite-Element Performance Evaluation of On-Line Transformer Internal Fault Detection Based on Instantaneous Voltage and Current Measurements
      Masoum, A.; Hashemnia, Naser; Abu Siada, Ahmed; Masoum, Mohammad; Islam, S. (2013)
      This paper investigates the performance of a recently proposed online transformer internal fault detection technique through detailed non-linear three-dimensional finite element modelling of the windings, magnetic core ...
    • Improved Method to Obtain the Online Impulse Frequency Response Signature of a Power Transformer by Multi Scale Complex CWT
      Zhao, Z.; Tang, C.; Yao, C.; Zhou, Q.; Xu, L.; Gui, Y.; Islam, Syed (2018)
      © 2013 IEEE. Online impulse frequency response analysis (IFRA) has proven to be a promising method to detect and diagnose the transformer winding mechanical faults when the transformer is in service. However, the existing ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.