Algerian Journal of Signals and Systems
Volume 3, Numéro 3, Pages 106-116
2018-09-30

Broken Rotor Bars Fault Detection Based On Envelope Analysis Spectrum And Neural Network In Induction Motors



Authors : Bensaoucha Saddam . Bessedik Sid Ahmed . Ameur Aissa . Seghiour Abdellatif .

Abstract

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..

Keywords

induction motors, broken rotor bars, fault detection, envelope analysis, neural networks

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