In this article, an interturn short-circuit (ITSC) fault detection method is presented based on the wavelet packet decomposition (WPD) and locus of three-phase currents in 3-D space for squirrel-cage induction motors (SCIMs). The proposed method is able to accurately identify the fault severity and location under any load condition and any type of motor power supply. A comprehensive dynamic model is also proposed for SCIMs having ITSC fault in one phase or a combination of multiple phases. The proposed signal-based fault detection method is separately evaluated based on the data extracted from the proposed model, the finite-element method (FEM), and the experimental test rig, which consists of two 1.5-kW induction motors, a 3-kW self-excitation generator, three LA55-P/SP1 Hall effect current sensors, a TMS320F28379D digital signal processor (DSP), and an electric drive system. The efficacy of the proposed fault detection method is evident from the results.


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    Titel :

    Stator Winding Interturn Short-Circuit Fault Modeling and Detection of Squirrel-Cage Induction Motors


    Beteiligte:
    Agah, G. R. (Autor:in) / Rahideh, A. (Autor:in) / Faradonbeh, V. Z. (Autor:in) / Kia, S. Hedayati (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.09.2024


    Format / Umfang :

    10187432 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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