Abstract The paper presents the possibility of using neural networks in the detection of stator and rotor electrical faults of induction motors. Fault detection and identification are based on the analysis of symptoms obtained from the fast Fourier transform of the voltage induced by an axial flux in a measurement coil. Neural network teaching and testing were performed in a MATLAB–Simulink environment. The effectiveness of various neural network structures to detect damage, its type (rotor or stator damage) and damage levels (number of rotor bars cracked or stator winding shorted circuits) is presented.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Application of Neural Networks and Axial Flux for the Detection of Stator and Rotor Faults of an Induction Motor


    Contributors:

    Published in:

    Publication date :

    2019




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English


    Classification :

    BKL:    53.35 Stromrichter, Transformatoren / 53.35$jStromrichter$jTransformatoren / 53.33 Elektrische Maschinen und Antriebe / 53.33$jElektrische Maschinen und Antriebe



    Diagnostic System for Induction Motor Stator Winding Faults Based on Axial Flux

    Wolkiewicz, Marcin / Skowron, Maciej | Online Contents | 2017



    AXIAL-FLUX MOTOR HAVING DOUBLE STATOR ASSEMBLIES AND SINGLE ROTOR ASSEMBLY AND UAV MOTOR DEVICE

    CHANG CHIN-HONG / HSU FU-CHUAN / HUA JUI-MING et al. | European Patent Office | 2025

    Free access


    Dual Independent Rotor Axial Flux Induction Motor for Electric Vehicle Applications

    Alireza Hesari / Ahmad Darabi / Fazel Pourmirzaei Deylami | DOAJ | 2024

    Free access