Rolling bearing fault feature extraction based on VMD and 1.5-dimensional Teager energy spectrum

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Journal of Vibration and Shock ›› 2017, Vol. 36 ›› Issue (18) : 98-104.

Xiang Ling, Zhang Lijia

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Abstract

Rolling bearing fault signal is nonlinear and non-stationary. Combine variational mode decomposition (VMD) with 1.5-dimensional Teager energy spectrum, the purpose of rolling bearing fault diagnosis can be achieved. VMD is a new method of adaptive signal decomposition. 1.5-dimensional Teager energy spectrum not only has the advantage of 1.5-dimensional denoise, but also strengthens transient impact feature signal using Teager operator. Firstly, the rolling bearing fault signal was decomposed using VMD. The two components, which had obvious impact features, were extracted and reconstructed using the kurtosis-correlation coefficient criteria. Secondly, the reconstructed signal was analyzed using the 1.5-dimensional Teager energy spectrum. Lastly, according to the energy spectrum analysis of the reconstructed signal, the inner ring and rolling element fault features were extracted. The analysis of the simulation signal and the test signal verifies the effectiveness of the proposed method. Compared with ensemble empirical mode decomposition, the proposed method would be more distinctive and effectively identify fault feature of the rolling bearing.

Key words

variational mode decomposition / 1.5-dimensional Teager energy spectrum / feature extraction；fault diagnosis；rolling bearing

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Xiang Ling, Zhang Lijia. Rolling bearing fault feature extraction based on VMD and 1.5-dimensional Teager energy spectrum[J]. Journal of Vibration and Shock, 2017, 36(18): 98-104

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