PARAMÈTRES DE PRÉDICTION DU RÉSEAU DE NEURONES ARTIFICIELS DU MÉLANGE 10 % SF6-90 % N2
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Mots-clés :
Hexafluorure de soufre, Mélange gazeux SF6-N2, Tension de démarrage, Effet couronne, Mobilité ioniqueRésumé
La présente étude décrit l'application des réseaux de neurones artificiels pour la prédiction des paramètres de décharge corona dans le mélange gazeux SF6-N2. La modélisation des réseaux de neurones artificiels est utilisée pour prédire la température de décharge corona, la mobilité ionique et les tensions d'apparition pour différentes pressions de gaz avec un mélange de 10 % de SF6 - 90 % de N2, et en utilisant des données expérimentales obtenues précédemment. Les résultats de la prédiction par les réseaux de neurones artificiels des tensions d'apparition de la mobilité ionique (μ) (Vs) et de la température se situent autour de ± 6% pour la formation ainsi que pour les tests et sont significativement cohérents avec les valeurs expérimentales.
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