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Multi-Class Classification Approach for the Diagnosis of Broken Rotor Bars based on Air-Gap Magnetic Flux Density
Laboratoire d’Etude et Développement des Matériaux Semi-Conducteurs et Diélectriques, Université Amar Telidji de Laghouat, Laghouat.
Laboratoire d’Etude et Développement des Matériaux Semi-Conducteurs et Diélectriques, Université Amar Telidji de Laghouat, Laghouat.
Laboratoire d’Etude et Développement des Matériaux Semi-Conducteurs et Diélectriques, Université Amar Telidji de Laghouat, Laghouat.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-9701-4203
2017 (English)In: Electrotehnica, Electronica, Automatica (EEA), ISSN 1582-5175, Vol. 65, no 2, p. 31-39Article in journal (Refereed) Published
Abstract [en]

In this paper, condition monitoring of induction machines using air-gap magnetic flux density spectrum via artificial neural networks is presented. The proposed scheme is chosen due to its effectiveness, simplicity, and low cost that used for the detection of broken rotor bar faults. The spectrum of the air-gap magnetic flux density is estimated using the Fast Fourier Transform, which can capture the fault related to harmonic components. The extracted information is then utilized by a machine-learning paradigm in a Multi-class classification approach for the detection of broken rotor bars, for both, adjacent and non-adjacent using artificial neural networks as a classification method. The obtained simulation results of the healthy and faulty conditions using finite elements prove the applicability of the proposed method.

Place, publisher, year, edition, pages
ICPE SA - Electra House of Publishing , 2017. Vol. 65, no 2, p. 31-39
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-64728Scopus ID: 2-s2.0-85020784677OAI: oai:DiVA.org:ltu-64728DiVA, id: diva2:1118890
Available from: 2017-07-03 Created: 2017-07-03 Last updated: 2017-11-24Bibliographically approved

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Georgoulas, Georgios

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CiteExportLink to record
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  • apa
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