Automatic pattern identification based on the complex empirical mode decomposition of the startup current for the diagnosis of rotor asymmetries in asynchronous machinesVise 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
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Forskningsprogram
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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
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