Fault feature extraction method of rolling bearing based on the improved composite interpolation envelope empirical mode decomposition
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TN911. 7;TH165. 3

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    Abstract:

    Aiming at the problem that the composite interpolation envelope empirical mode decomposition (CIEEMD) method is lack of self-adaptability in the selection of non-stationary coefficient threshold, an improved composite interpolation envelope empirical mode decomposition (ICIEEMD) method is proposed. Firstly, the fractal box dimension is calculated from the vibration signal covered by grids with side length of ε, and the non-stationary threshold is adaptively selected. After decomposition, some intrinsic mode functions (IMF) are obtained. Secondly, combining with the correlation coefficient, the kurtosises of time domain signal and of envelope spectrum to establish the composite index of correlation coefficient and TE kurtosises (C-indexTE), then the effective IMF components were selected and reconstructed into a new signal. The energy spectrum of the reconstructed signal is obtained by using Teager energy operator, and the fault feature extraction of rolling bearing is realized. Finally, based on the simulation signal and the experimental data set of rolling bearing, the experimental analysis is carried out. The proposed method can extract more clear fault feature frequencies than the CIEEMD and spectral kurtosis methods, which proves the effectiveness and feasibility of the proposed method.

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  • Online: June 15,2023
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