New clustering techniques based on current peak value, charge and energy calculations for separation of partial discharge sources

A. Rodrigo Mor, L. C. Castro Heredia, F. A. Muñoz

Research output: Contribution to journalArticleScientificpeer-review

35 Citations (Scopus)
113 Downloads (Pure)

Abstract

Clustering techniques are of main interest for separation of partial discharge (PD) sources. The separation is achieved if it is possible to extract from the PD pulses specific information related to the source. In this sense, this paper explores the capability of fundamental quantities derived from PD current pulses such as the peak amplitude Ipeak, the apparent charge Q, and the energy E as parameters intended for source separation. For this purpose, an unconventional PD measuring circuit is used to acquire PD pulses from several laboratory test objects. Once the pulses are digitized and stored, the values of Ipeak, Q, and E are computed according to the proposed methods in time and frequency domain. A theoretical analysis is presented to illustrate how values of Ipeak, Q and E can be related to the pulse shape so that they can be used as source separation parameters. Then, the IpeakQE clusters are computed for laboratory measurements. The results showed that these parameters are suitable for separation of sources provided that the pulse shapes are different. This cluster technique was also proved to be independent of the change of the acquisition parameters that are relevant for unconventional measuring systems. In addition, the easiness of the quantities computation makes the clustering technique introduced in this paper feasible for practical applications.
Original languageEnglish
Pages (from-to)340-348
Number of pages9
JournalIEEE Transactions on Dielectrics and Electrical Insulation
Volume24
Issue number1
DOIs
Publication statusPublished - 1 Feb 2017

Bibliographical note

Accepted Author Manuscript

Keywords

  • Corona
  • Discharges (electric)
  • Fault location
  • Partial discharges
  • Pulse measurements
  • Shape
  • charge
  • clustering techniques
  • energy
  • frequency domain
  • pulse shapes
  • time domain

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