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Principal component analysis of the start-up transient and hidden Markov modeling for broken rotor bar fault diagnosis in asynchronous machines
Department of Informatics and Communications Technology, Technical Educational Institute of Epirus, 47100 Artas, Kostakioi.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Siemens Industry Sector, Automation and Drives, Large Drives, Nuremberg, Germany.
Instituto de Ingeniera Energtica, Universitat Politcnica de Valncia, 46022 Valencia.
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2013 (English)In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 40, no 17, p. 7024-7033Article in journal (Refereed) Published
Abstract [en]

This article presents a novel computational method for the diagnosis of broken rotor bars in three phase asynchronous machines. The proposed method is based on Principal Component Analysis (PCA) and is applied to the stator’s three phase start-up current. The fault detection is easier in the start-up transient because of the increased current in the rotor circuit, which amplifies the effects of the fault in the stator’s current independently of the motor’s load. In the proposed fault detection methodology, PCA is initially utilized to extract a characteristic component, which reflects the rotor asymmetry caused by the broken bars. This component can be subsequently processed using Hidden Markov Models (HMMs). Two schemes, a multiclass and a one-class approach are proposed. The efficiency of the novel proposed schemes is evaluated by multiple experimental test cases. The results obtained indicate that the suggested approaches based on the combination of PCA and HMM, can be successfully utilized not only for identifying the presence of a broken bar but also for estimating the severity (number of broken bars) of the fault.

Place, publisher, year, edition, pages
2013. Vol. 40, no 17, p. 7024-7033
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-8816DOI: 10.1016/j.eswa.2013.06.006ISI: 000326214700036Scopus ID: 2-s2.0-84880548512Local ID: 75ce03a1-4a5d-4db3-aaff-268cc906b321OAI: oai:DiVA.org:ltu-8816DiVA, id: diva2:981754
Projects
Feldetektering i elektriska maskiner
Note
Validerad; 2013; 20130610 (geonik)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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Mustafa, Mohammed ObaidNikolakopoulos, George

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