Application of self organizing map approach to partial discharge pattern recognition of cast-resin current transformers

Wen Yeau Chang, Hong-Tzer Yang

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Partial discharge (PD) measurement and recognition is a significant tool for potential failure diagnosis of a power transformer. This paper proposes the application of self organizing map (SOM) approach to recognize partial discharge patterns of cast-resin current transformer (CRCT). The PD patterns are measured by using a commercial PD detector. A set of features, used as operators, for each PD pattern is extracted through statistical schemes. The proposed SOM classifier has the advantages of high robustness to ambiguous patterns and is useful in recognizing the PD patterns of electrical transformers. To verify the effectiveness of the proposed method, the classifier was verified on 250 sets of field-test PD patterns of CRCTs. The test results show that the proposed approach may achieve quite satisfactory recognition of PD patterns.

Original languageEnglish
Pages (from-to)142-151
Number of pages10
JournalWSEAS Transactions on Computer Research
Volume3
Issue number3
Publication statusPublished - 2008 Mar 1

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Engineering(all)

Fingerprint Dive into the research topics of 'Application of self organizing map approach to partial discharge pattern recognition of cast-resin current transformers'. Together they form a unique fingerprint.

Cite this