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Separation of Partial Discharge Sources Measured in the High-Frequency Range with HFCT Sensors Using PRPD-t Patterns.

Ricardo Albarracín-Sánchez1, Fernando Álvarez-Gómez1, Carlos A Vera-Romero1

  • 1Department of Electrical and Electronic Engineering, Automatic Control and Applied Physics, School of Industrial Design and Engineering (ETSIDI), Universidad Politécnica de Madrid (UPM), Ronda de Valencia 3, 28012 Madrid, Spain.

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Summary

A new method effectively separates and identifies simultaneous partial discharge (PD) sources in high-voltage (HV) systems using non-invasive sensors and real-time data analysis. This technique enhances insulation diagnostics by distinguishing PD signals from noise.

Keywords:
PRPD-teff patternPRPD-time tooleffective timeinsulation conditionnoise rejectionon-line PD measurementspartial dischargespulse source separationwideband PD measurements

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Area of Science:

  • Electrical Engineering
  • Materials Science

Background:

  • On-line partial discharge (PD) measurements are crucial for assessing high-voltage (HV) insulation integrity.
  • Non-conventional electromagnetic methods are widely used for PD detection due to their versatility.
  • Challenges in on-line PD measurements include ambient electrical noise and the presence of multiple signal types.

Purpose of the Study:

  • To present a practical and effective method for separating and identifying simultaneous PD sources in HV systems.
  • To enable accurate in-situ diagnosis of HV installations during measurements.
  • To reduce post-processing time through real-time data acquisition.

Main Methods:

  • Utilizing non-invasive high-frequency current transformers (HFCT) as sensors.
  • Implementing a Matlab application (PRPD-time tool) for data analysis.
  • Analyzing Phase-Resolved Partial Discharge (PRPD) patterns combined with interactive graphical representations.
  • Incorporating effective time (t_eff) as a third axis in the PRPD pattern (PRPD-t_eff) for pulse analysis.

Main Results:

  • The proposed method successfully separates and identifies various simultaneous PD sources and pulse-type noise interferences.
  • Interactive PRPD-t_eff diagrams facilitate pulse source separation and clustering.
  • Real-time data acquisition streamlines the diagnostic process.

Conclusions:

  • The developed method and Matlab application provide an effective solution for complex on-line PD analysis in HV systems.
  • Accurate source separation enhances the diagnostic capabilities for insulation condition assessment.
  • The PRPD-t_eff pattern offers a valuable tool for distinguishing between different pulse sources.