Identifying harmonic attributes from online partial discharge data

Victoria Catterson, S. Bahadoorsingh, Susan Rudd, Stephen Mcarthur, S.M. Rowland

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Partial discharge (PD) monitoring is a key method of tracking fault progression and degradation of insulation systems. Recent research discovered that the harmonic regime experienced by the plant also affects the PD pattern, questioning the conclusions about equipment health drawn from PD data. This paper presents the design and creation of an online system for harmonic circumstance monitoring of distribution cables, using only PD data. Based on machine learning techniques, the system can assess the prevalence of the 5th and 7th harmonic orders over the monitoring period. This information is key for asset managers to draw correct conclusions about the remaining life of polymeric cable insulation, and prevent overestimation of the degradation trend.
LanguageEnglish
Pages1811-1819
Number of pages9
JournalIEEE Transactions on Power Delivery
Volume26
Issue number3
DOIs
Publication statusPublished - Jul 2011

Fingerprint

Partial discharges
Insulation
Monitoring
Cables
Degradation
Online systems
Learning systems
Managers
Health

Keywords

  • discharges
  • harmonic analysis
  • insulation
  • monitoring
  • partial discharges

Cite this

Catterson, Victoria ; Bahadoorsingh, S. ; Rudd, Susan ; Mcarthur, Stephen ; Rowland, S.M. / Identifying harmonic attributes from online partial discharge data. In: IEEE Transactions on Power Delivery. 2011 ; Vol. 26, No. 3. pp. 1811-1819.
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Identifying harmonic attributes from online partial discharge data. / Catterson, Victoria; Bahadoorsingh, S.; Rudd, Susan; Mcarthur, Stephen; Rowland, S.M.

In: IEEE Transactions on Power Delivery, Vol. 26, No. 3, 07.2011, p. 1811-1819.

Research output: Contribution to journalArticle

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