IEEE Access (Jan 2024)

Diagnostics of Partial Discharge Measurements Utilizing Multi-Sensor Temporal Pulse Sequence Analysis

  • Kai Zhang,
  • Alistair Reid,
  • David Clark,
  • Michail Michelarakis,
  • A. Manu Haddad

DOI
https://doi.org/10.1109/ACCESS.2024.3419082
Journal volume & issue
Vol. 12
pp. 88992 – 89001

Abstract

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This paper presents an improved temporal pulse sequence analysis (PSA) method for diagnosing partial discharge (PD) phenomena. The proposed method enables simultaneous high-resolution PD recognition across electrical sensors and ultra-high frequency antennae, facilitating the differentiation of defect types and the quantification of PD severity, as well as, their unique characteristics. This is achieved by utilizing advanced discrete-time integration techniques within two sensor measurement systems. Each PD event is time-stamped in post-processing, with a particular focus on analyzing charge-to-charge and ultra high frequency (UHF) energy-to-energy sequences analysis. The improved temporal PSA merits the advantages of a wide bandwidth of high-frequency current transformers and antennae to improve accuracy and efficiency. To conduct this method, a dual-sensor PD measurement circuit was set up to examine the protrusion on the ground side, the floating electrode, and the free-moving particle defects, which are potentially present in gas-insulated switchgear. Obtained results present dynamic PD variations in both time differences and magnitudes, establishing correlational PD patterns between sensors in a distinct manner. The application of the proposed method can serve as a reliable diagnostics approach for PD detection in gas-insulated switchgear and offer insights into underscoring PD phenomena itself.

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