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Using Generic Direct M-SVM Model Improved by Kohonen Map and Dempster–Shafer Theory to Enhance Power Transformers Diagnostic

Hendel Mounia, Meghnefi Fethi, Senoussaoui Mohamed El Amine, Fofana Issouf et Brahami Mostefa. (2023). Using Generic Direct M-SVM Model Improved by Kohonen Map and Dempster–Shafer Theory to Enhance Power Transformers Diagnostic. Sustainability, 15, (21), e15453.

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Many power transformers throughout the world are nearing or have gone beyond their theoretical design life. Since these important assets represent approximately 60% of the cost of the substation, monitoring their condition is necessary. Condition monitoring helps in the decision to perform timely maintenance, to replace equipment or extend its life after evaluating if it is degraded. The challenge is to prolong its residual life as much as possible. Dissolved Gas Analysis (DGA) is a well-established strategy to warn of fault onset and to monitor the transformer’s status. This paper proposes a new intelligent system based on DGA; the aim being, on the one hand, to overcome the conventional method weaknesses; and, on the other hand, to improve the transformer diagnosis efficiency by using a four-step powerful artificial intelligence method. (1) Six descriptor sets were built and then improved by the proposed feature reduction approach. Indeed, these six sets are combined and presented to a Kohonen map (KSOM), to cluster the similar descriptors. An averaging process was then applied to the grouped data, to reduce feature dimensionality and to preserve the complete information. (2) For the first time, four direct Multiclass Support Vector Machines (M-SVM) were introduced on the Generic Model basis; each one received the KSOM outputs. (3) Dempster–Shafer fusion was applied to the nine membership probabilities returned by the four M-SVM, to improve the accuracy and to support decision making. (4) An output post-processing approach was suggested to overcome the contradictory evidence problem. The achieved AUROC and sensitivity average percentages of 98.78–95.19% (p-value < 0.001), respectively, highlight the remarkable proposed system performance, bringing a new insight to DGA analysis.

Type de document:Article publié dans une revue avec comité d'évaluation
Version évaluée par les pairs:Oui
Date:30 Octobre 2023
Nombre de pages:1
Identifiant unique:10.3390/su152115453
Sujets:Sciences naturelles et génie > Génie
Sciences naturelles et génie > Génie > Génie électrique et génie électronique
Sciences naturelles et génie > Sciences appliquées
Département, module, service et unité de recherche:Départements et modules > Département des sciences appliquées > Module d'ingénierie
Unités de recherche > Centre international de recherche sur le givrage atmosphérique et l’ingénierie des réseaux électriques (CENGIVRE) > Vieillissement de l’appareillage installé sur les lignes à haute tension (ViAHT)
Mots-clés:DGA, probabilistic M-SVM, generic M-SVM Model, Dempster–Shafer rule, Kohonen map, M-SVM probabiliste, modèle M-SVM générique, règle de Dempster – Shafer, carte de Kohonen
Déposé le:02 févr. 2024 19:18
Dernière modification:02 févr. 2024 19:18
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