Accéder directement au contenu Accéder directement à la navigation
Communication dans un congrès

A Topological and Neural Based Technique for Classification of Faults in Induction Machines

Abstract : This paper presents a data driven approach where at first the most significant features of the three phase current signal are analyzed and then a Curvilinear Component based analysis (CCA), which is a nonlinear manifold learning technique, is performed to compress and interpret the feature behaviour. Finally, a multi-layer perceptron network is used to develop a classifier. The effectiveness of the developed model is verified experimentally with data provided on-line and in real-time.
Type de document :
Communication dans un congrès
Liste complète des métadonnées

https://hal-u-picardie.archives-ouvertes.fr/hal-03631448
Contributeur : Louise DESSAIVRE Connectez-vous pour contacter le contributeur
Soumis le : mardi 5 avril 2022 - 16:25:19
Dernière modification le : vendredi 5 août 2022 - 11:21:50

Identifiants

  • HAL Id : hal-03631448, version 1

Collections

Citation

R. R. Kumar, G. Cirrincione, M. Cirrincione, A. Tortella, M. Andriollo. A Topological and Neural Based Technique for Classification of Faults in Induction Machines. 2018 21ST INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS), Oct 2018, Jeju, South Korea. pp.653-658. ⟨hal-03631448⟩

Partager

Métriques

Consultations de la notice

4