2026-10-19T01:36:16Zhttps://ebyu-rdlopen.rawdatalibrary.net/oai/request

oai:ebyu-rdlopen.rawdatalibrary.net:ebyu/161062026-10-18T20:30:55Zopenairedrivercom_ebyu_10000col_ebyu_10001

Early fault detection of broken rotor bars using sliding window symbol sequence statisticsAydin, IlhanKarakose, MehmetAkin, ErhanBroken rotor bar faultsFault detectionHubert transformInduction motorsSliding windowEnergy conservationMotorsWindowsBroken rotor barBroken rotor bar faultEarly faultFault identificationsHigh degree of accuracyHilbert transformInduction machinesInformation entropyNo-load conditionsPhase currentsPhase motorSymbol sequence statisticsThis paper presents a new fault detection approach to detect and locate automatically the broken rotor bar faults of the induction machine. The signatures of the fault are created from the Hilbert transform of one phase motor current. A sliding window symbol sequence statistics-based method is proposed to detect the early faults of broken rotor bars. The different sized periods of phase current are taken as window. The information entropy of symbol tree is used as fault index. One and two broken rotor bar faults are detected on no-load conditions. The results indicate that the method yields a high degree of accuracy in fault identification, as evidenced by given experimental results.2009Conference Objecthttps://rdlopen.rawdatalibrary.net/r/ebyu/16106978-086396718-4enAUPEC'09 - 19th Australasian Universities Power Engineering Conference: Sustainable Energy Technologies and Systemsinfo:eu-repo/semantics/openAccessinfo:eu-repo/semantics/conferenceObjecthttps://ebyu-rdlopen.rawdatalibrary.net/tr/items/ebyu/16106