Broken Rotor Bars Fault Detection Based on Envelope Analysis Spectrum and Neural Network in Induction Motors
Keywords:Induction motors, Broken rotor bars, Faults detection, Envelope analysis, Neural networks
In this paper, a study has presented the performance of a neural networks technique to detect the broken rotor bars (BRBs) fault in induction motors (IMs). In this context, the fast Fourier transform (FFT) applied on Hilbert modulus obtained via the stator current signal has been used as a diagnostic signal to replace the FFT classic, the characteristics frequency are selected from the Hilbert modulus spectrum, in addition, the different load conditions are used as three inputs data for the neural networks. The efficiency of the proposed method is verified by simulation in MATLAB environment.
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Copyright (c) 2018 Saddam BENSAOUCHA, Sid Ahmed BESSEDIK, Aissa AMEUR, Abdellatif SEGHIOUR
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.