Fault diagnosis method for rolling bearings based on fast spectral kurtosis and orthogonal matching pursuit algorithm

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Journal of Vibration and Shock ›› 2020, Vol. 39 ›› Issue (19) : 78-83.

WANG Haiming1,2， LIU Yongqiang1,2， LIAO Yingying2,3

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Abstract

Aiming at the diagnosis effect of fast spectral kurtosis in cases of low signal-to-noise ratio being poor, a new method for rolling bearing fault diagnosis based on fast spectral kurtosis and orthogonal matching pursuit (OMP) algorithm was proposed. The optimal filter parameters were determined with fast spectral kurtosis graph, and then signals were filtered with the optimal filter. Based on the known sparsity of fault signals under Fourier sparse basis, the envelope signal of the filtered signals under Fourier sparse basis was used to reconstruct the envelope signal of bearing vibration signals to reduce influences of noise and other irrelevant components. Finally, spectral analysis was conducted for the reconstructed signal to obtain bearing fault characteristics. Bearing fault simulation data and test data of faulty bearing’s outer and inner rings on platform verified the effectiveness and feasibility of the proposed method.

Key words

rolling bearing / fault diagnosis / fast spectral kurtosis / orthogonal matching pursuit (OMP) / compressive sensing

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WANG Haiming1,2， LIU Yongqiang1,2， LIAO Yingying2,3. Fault diagnosis method for rolling bearings based on fast spectral kurtosis and orthogonal matching pursuit algorithm[J]. Journal of Vibration and Shock, 2020, 39(19): 78-83

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