METODOLOGIE ȘI APLICAȚII ÎN MONITORIZAREA TRANSFORMATOARELOR DE PUTERE

This paper presents the importance and applicability of Dissolved Gas Analysis (DGA) for monitoring the health of power transformers, essential in electrical distribution networks. The reliability of transformers is critical, and DGA represents an effective method for early detection of internal faults by measuring dissolved gases in the insulating oil. Different interpretation techniques, such as the Duval Triangle and Roger methods, are discussed for identifying fault types based on the concentration and ratio of the resulting gases. The paper also explores the limitations of these methods and future perspectives, proposing a multi-method approach based on machine learning algorithms to improve the accuracy and consistency of DGA interpretation.

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Publication Details

Journal
ACTUALITĂŢI ŞI PERSPECTIVE ÎN DOMENIUL MAŞINILOR ELECTRICE (ELECTRIC MACHINES MATERIALS AND DRIVES - PRESENT AND TRENDS)
Published
2025-02-07
DOI
https://doi.org/10.36801/apme.2024.1.14
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
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article

METODOLOGIE ȘI APLICAȚII ÎN MONITORIZAREA TRANSFORMATOARELOR DE PUTERE

Dan - Gabriel RADU, Valentin NĂVRĂPESCU
ACTUALITĂŢI ŞI PERSPECTIVE ÎN DOMENIUL MAŞINILOR ELECTRICE (ELECTRIC MACHINES MATERIALS AND DRIVES - PRESENT AND TRENDS)
Power Transformer Diagnostics and Insulation
article

METODOLOGIE ȘI APLICAȚII ÎN MONITORIZAREA TRANSFORMATOARELOR DE PUTERE

Dan - Gabriel RADU, Valentin NĂVRĂPESCU
article en

Abstract

This paper presents the importance and applicability of Dissolved Gas Analysis (DGA) for monitoring the health of power transformers, essential in electrical distribution networks. The reliability of transformers is critical, and DGA represents an effective method for early detection of internal faults by measuring dissolved gases in the insulating oil. Different interpretation techniques, such as the Duval Triangle and Roger methods, are discussed for identifying fault types based on the concentration and ratio of the resulting gases. The paper also explores the limitations of these methods and future perspectives, proposing a multi-method approach based on machine learning algorithms to improve the accuracy and consistency of DGA interpretation.

ACTUALITĂŢI ŞI PERSPECTIVE ÎN DOMENIUL MAŞINILOR ELECTRICE (ELECTRIC MACHINES MATERIALS AND DRIVES - PRESENT AND TRENDS)Vol. 2024(1)
Universitatea Națională de Știință și Tehnologie Politehnica București (RO)
Openalex Percentile: Top 98%
Power Transformer Diagnostics and Insulation
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