Fault Diagnosis Based on Enhancement of Barkhausen Noise Using Hybrid Method Emprical Mode Decomposition-Savitzky-Golay Filter

Year 2020, Volume: 4 Issue: 2, 33 - 38, 29.06.2020

Rabah Abdelkader Mohammed Khorchef Mourad Zergoug

Abstract

The barkhausen noise
carries important information which can be used in early damage detection and
fault diagnosis. The barkhausen noise is corrupted by interference signals from
other sources during the measure and the information of fault can be lost. In
this paper a new algorithm based on Empirical Mode Decomposition (EMD) and
Savitzky-Golay filter is proposed to extract the information about the fault of
materials from a measured barkhausen noise. Firstly, using EMD to decompose the
barkhausen noise signal into elementary function called Intrinsic Mode Function
(IMF). Secondly, we use the energy to select the relevant mode, these selected
IMF is filtered by Savitzky-Golay filter and the reconstructed signal is
obtained by the IMFs filtered. The envelope spectra are used to test the
efficiency of the proposed method in enhancement the quality of barkhausen
noise signal. The proposed method is validated using the measuring chain of
barkhausen noise (Fig (3-8)) and the obtained results show the effectiveness of
the proposed method in fault detection.

Keywords

Barkhausen noise, EMD, energy, envlope spectra

Supporting Institution

Research Center in Industrial Technologies CRTI, P.O.BOX 64, Cheraga 16014 Algiers, Algeria.

Project Number

1

Thanks

thanks

References

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