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A Multi-label Classification Approach for the Detection of Broken Bars and Mixed Eccentricity Faults Using the Start-up Transient
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-9701-4203
Department of Electrical Engineering and Automation, Aalto University.
Instituto Tecnologico de la Energia, Universitat Politècnica de València.
Laboratory of Knowledge and Intelligent Computing, Department of Computer Engineering, TEI of Epirus, Artas, Kostakioi.
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Number of Authors: 62017 (English)In: IEEE International Conference on Industrial Informatics (INDIN), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 430-433, article id 7819198Conference paper, Published paper (Refereed)
Abstract [en]

In this article a data driven approach for the classification of simultaneously occurring faults in an induction motor is presented. The problem is treated as a multi-label classification problem with each label corresponding to one specific fault, using the power-set approach. The faulty conditions examined, include the existence of a broken bar fault and the presence of mixed eccentricity with various degrees of static and dynamic eccentricity. For the feature extraction stage, the time-frequency representation, resulting from the application of the short time Fourier transform of the start-up current is exploited. The proposed approach is validated using simulation data with promising results.

Place, publisher, year, edition, pages
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 430-433, article id 7819198
Series
IEEE International Conference on Industrial Informatics INDIN, ISSN 1935-4576
Keywords [en]
Information technology - Automatic control
Keywords [sv]
Informationsteknik - Reglerteknik
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-28607DOI: 10.1109/INDIN.2016.7819198ISI: 000393551200061Scopus ID: 2-s2.0-85012894280Local ID: 274db64f-1c9b-4fba-8d65-1d0428bccbe6ISBN: 9781509028702 (electronic)OAI: oai:DiVA.org:ltu-28607DiVA, id: diva2:1001809
Conference
14th IEEE International Conference on Industrial Informatics, INDIN 2016, Poitiers, France, 19-21 July 2016
Projects
Integrated Process Control based on Distributed In-Situ Sensors into Raw Material and Energy Feedstock, DISIRE
Funder
EU, Horizon 2020, 636834Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-05-29Bibliographically approved

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The full text will be freely available from 2019-01-19 15:08
Available from 2019-01-19 15:08

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Georgoulas, GeorgiosNikolakopoulos, George

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Citation style
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