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, Résumé substantiel

, Cette thèse aété mené dans le cadre d'une convention de collaboration entre la société Hager et l'Institut Jean Lamour. Le principal sujet abordé dans la thèse est la détection de défaut d'arcélectrique pour les installations domestiques

, Si un défaut d'arc est maintenu pendant une durée suffisamment longue, l'énergie produite par l'arcélectrique peut conduireà départ d'un incendie. Pour protégerà nouveau ce phénomène, des dispositifs de détection de défauts d'arcsélectriques sont demandés dans plusieurs installationsélectriques depuis une vingtaine d'années. LesÉtats-Unis et le Canada exigeaient qu'ils protègent la plupart des points des prises d'électrique résidentiels. En Europe, l'adoption des dispositifs de détection de défauts d'arc commenceégalement, 2017.

, Jusqu'à présent, aucune solution ne peut garantir la détection de tous les défauts de l'arc sans jamais produire de déclenchement intempestif. C'est la raison [11, 13], donc AFF peutêtre déduite sansétape supplémentaire. Dans les autres méthodes de détection, la partie extraction de caractéristiques peutêtre divisée en deux sous-parties: transformation et les descripteurs. Plusieurs transformations ont eté utilisées pour la détection d'arc, telles que, Il existe sur le marché de nombreux dispositifs de détection des défauts d'arc? electriques

, De même, un certain descripteurs peuventêtre listées: variation de l'énergie du sous-spectre entre deux cycles de puissance adjacents en tant que descripteur pour la transformée de Fourier discrète (DFT) [14], le rapport harmonique -DFT [19], la valeur moyenne de la différences

, La partie classification peutêtre simple, comme un seuil fixe pour les AFFs [23], ou plus complexe

, La technique de comptage ou la logique floue sont utilisées comme stratégie de décision, vol.21

, La principale difficulté de la détection des défauts d'arc en série est la distinction entre les situations d'arc et les situations normales

, En général, pour détecter une condition d'arc dangereuse

, Les AFF les plus utilisés sont: le passageà zéro, le bruit large bande, les caractères aléatoires de la variation du courant, vol.18

, Cependant, ces fonctionnalités peuventégalementêtre trouvées dans un réseau de fonctionnement normal

, Par exemple, un aspirateur peut produire de nombreuses caractéristiques d'arc

Z. Wang and W. Yan,

C. Liu,

L. Guennec and A. , proposées des méthodes de classification basées sur certaines variantes de CNN, vol.57

, Les résultats concernant la précision de la classification pour les séries temporelles avec apprentissage en profondeur sont parfois meilleurs que ceux obtenus avec les méthodes classiques, vol.61

, Nous avons appliqué deux techniques d'apprentissage en profondeur pour la tâche de détection de défaut d'arc. Le résultat donné par les auto-encodeurs est moyen (96.2%). Les méthodes de détection basées sur CNN offrent de meilleures perfor

Y. Dans-le and . Liu, Plusieurs méthodes peuventêtre utilisées pour classifier les séries temporelles de longueur des variables pour la détection des défauts d'arc. Les deux approches les plus utilisées sont des caractéristiques indépendantes de la durée d'analyse, telles que la fréquence ou le domaine temps-fréquence, et des fenêtres d'analyse prédéfinies, combinées avec les méthodes statistiques. Par exemple

O. Artale, a développé un algorithme de détection basé sur l'analyse de fréquence utilisant différentes fenêtres d'observation de tailles différentes pour s'adapter au valeur RMS du courant [21] Edwin et al. ont présenté une méthode qui détecte un arc dans un temps variable, pp.20-200

, En plus de cela, l'adaptation temporelle dynamique aété largement utilisé pour la classification dans d'autres domaines

. Cependant,