A Comprehensive Approach to DGA. Advancing Transformer Diagnostics in the Era of Modern Power Systems

Dissolved Gas Analysis (DGA) has played a crucial role in transformer diagnostics for over a century. From its origins in early gas detection methods to modern spectrometric techniques, DGA has evolved to become a vital tool for identifying faults and preventing catastrophic failures. This paper provides a historical overview of DGA, covering the progression of gas extraction and measurement techniques and the refinement of diagnostic interpretation from total combustible gas assessment to key gas analysis and graphical fault models. Case studies illustrate the necessity of expert judgment in evaluating gas concentration trends, demonstrating that absolute gas values alone do not always indicate failure, even critical trends. Finally, the paper discusses the role of artificial intelligence in DGA diagnostics and the need for further refinement through expert training and historical data integration.

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Publication Details

Published
2025-06-08
DOI
https://doi.org/10.1109/eic63069.2025.11123208
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
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article

A Comprehensive Approach to DGA. Advancing Transformer Diagnostics in the Era of Modern Power Systems

Marius Grisaru
Power Transformer Diagnostics and Insulation
article

A Comprehensive Approach to DGA. Advancing Transformer Diagnostics in the Era of Modern Power Systems

Marius Grisaru
article en

Abstract

Dissolved Gas Analysis (DGA) has played a crucial role in transformer diagnostics for over a century. From its origins in early gas detection methods to modern spectrometric techniques, DGA has evolved to become a vital tool for identifying faults and preventing catastrophic failures. This paper provides a historical overview of DGA, covering the progression of gas extraction and measurement techniques and the refinement of diagnostic interpretation from total combustible gas assessment to key gas analysis and graphical fault models. Case studies illustrate the necessity of expert judgment in evaluating gas concentration trends, demonstrating that absolute gas values alone do not always indicate failure, even critical trends. Finally, the paper discusses the role of artificial intelligence in DGA diagnostics and the need for further refinement through expert training and historical data integration.

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Power Transformer Diagnostics and Insulation
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