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Automatic pattern identification based on the complex empirical mode decomposition of the startup current for the diagnosis of rotor asymmetries in asynchronous machines
Department of Informatics Engineering, Technological Educational Institute of Epirus, Arta, Greece.ORCID-id: 0000-0001-9701-4203
Large Drives R&D, Siemens Industry Sector, Nuremberg, Germany.
Instituto de Ingeniería Energética, Universitat Politècnica de València, Valencia, Spain.
Instituto de Ingeniería Energética, Universitat Politècnica de València, Valencia, Spain.
Vise andre og tillknytning
2014 (engelsk)Inngår i: IEEE Transactions on Industrial Electronics, ISSN 0278-0046, E-ISSN 1557-9948, Vol. 61, nr 9, s. 4937-4946, artikkel-id 6616605Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

This paper presents an advanced signal processing method applied to the diagnosis of rotor asymmetries in asynchronous machines. The approach is based on the application of complex empirical mode decomposition to the measured start-up current and on the subsequent extraction of a specific complex intrinsic mode function. Unlike other approaches, the method includes a pattern recognition stage that makes possible the automatic identification of the signature caused by the fault. This automatic detection is achieved by using a reliable methodology based on hidden Markov models. Both experimental data and a hybrid simulation-experimental approach demonstrate the effectiveness of the proposed methodology

sted, utgiver, år, opplag, sider
Institution of Electrical Engineers of Japan (IEEJ), 2014. Vol. 61, nr 9, s. 4937-4946, artikkel-id 6616605
HSV kategori
Forskningsprogram
Reglerteknik
Identifikatorer
URN: urn:nbn:se:ltu:diva-68096DOI: 10.1109/TIE.2013.2284143ISI: 000333467900051Scopus ID: 2-s2.0-84897381468OAI: oai:DiVA.org:ltu-68096DiVA, id: diva2:1193860
Tilgjengelig fra: 2018-03-28 Laget: 2018-03-28 Sist oppdatert: 2025-04-28bibliografisk kontrollert

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