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Fault Diagnosis of Power Transformers Using Computational Intelligence: A Review

Authors
Publisher
Elsevier Ltd
Volume
14
Identifiers
DOI: 10.1016/j.egypro.2011.12.1080
Keywords
  • Fault Diagnosis
  • Power Transformers
  • Computational Intelligence
Disciplines
  • Computer Science
  • Medicine

Abstract

Abstract This study reviews computational intelligence (CI) approaches for oil-immersed power transformer maintenance by discussing historical developments and by presenting state-of-the-art fault diagnosis methods. The CI-based approaches have emerged as rapidly evolving but highly effective approaches for using dissolved gas analysis (DGA) data for diagnosing power transformer faults. This study reviews the various CI-based methods reported in international journals, including fuzzy logic, neural networks, and evolutionary optimization-based approaches.

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