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| Titre: | Fuzzy logic based broken bar fault diagnosis and behavior study of induction machine |
| Auteur(s): | Chouidira, I.
Khodja, Djalal Eddine
Chakroune, S. |
| Mots-clés: | Diagnosis
Detection
Fast fourier transformation
Induction machine |
| Date de publication: | 2020 |
| Editeur: | International Information and Engineering Technology Association |
| Collection/Numéro: | Journal Europeen des Systemes Automatises Volume 53, Issue 2, April 2020;pp. 233-242 |
| Résumé: | This study aims to display fuzzy logic (FL) technique for diagnosis of fault induction machine. This allows monitoring of fuzzy information from different signals to give more accurate judgment on the health of the engine, through using a multi-winding model of induction machine for the simulation of broken bars. This model allows study the influence of defects and appear the behavior of the machine in the different modes of running conditions (healthy and fault). In this work, we focus the application of a fuzzy logic technique based on the fast Fourier transformation (FFT) by analyzing the stator current for fault detection. The results of the simulation obtained allowed us to show the importance of the fuzzy logic approach based on classification of signals for detecting the faulty. © 2020 Lavoisier. All rights reserved |
| URI/URL: | https://www.scopus.com/record/display.uri?eid=2-s2.0-85087161882&origin=SingleRecordEmailAlert&dgcid=raven_sc_affil_en_us_email&txGid=a370c6cc80fc997849ce9fcac56d65ff
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/6195 |
| ISSN: | 12696935 |
| Collection(s) : | Publications Internationales
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