|
Depot Institutionnel de l'UMBB >
Publications Scientifiques >
Publications Internationales >
Veuillez utiliser cette adresse pour citer ce document :
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/6098
|
| Titre: | Induction Machine Faults Detection and Localization by Neural Networks Methods |
| Auteur(s): | Chouidira, Ibrahim
Khodja, Djalal Eddine
Chakroune, Salim |
| Mots-clés: | Induction machine
Faults detection and localization
Broken bars |
| Date de publication: | 2019 |
| Editeur: | IIETA |
| Collection/Numéro: | Revue d'Intelligence Artificielle, 33(6);pp. 427-434 |
| Résumé: | The objective of this study is to present artificial intelligence (AI) technique for detection and localization of fault in induction machine fault, through a multi-winding model for the simulation of four adjacent broken bars and three-phase model for the simulation of short-circuit between turns. In this work, it was found that the application of artificial neural networks (ANN) based on Root mean square values (RMS) plays a big role for fault detection and localization. The simulation and obtained results indicate that ANN is able to detect the faulty with high accuracy |
| URI/URL: | http://www.iieta.org/journals/ria/paper/10.18280/ria.330604
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/6098 |
| ISSN: | 1958-5748 |
| Collection(s) : | Publications Internationales
|
Fichier(s) constituant ce document :
|
Tous les documents dans DSpace sont protégés par copyright, avec tous droits réservés.
|
