Application of CMRDE in bearing fault diagnosis

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Journal of Vibration and Shock ›› 2022, Vol. 41 ›› Issue (19) : 55-63.

CHEN Yan, ZHENG Jinde, PAN Haiyang, TONG Jinyu

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Abstract

The vibration signals are often nonlinear and non-stationary when the fault occurs. Reverse dispersion entropy (RDE) can effectively extract nonlinear dynamic fault features from vibration signals. However, the RDE value at a single scale cannot fully reflect the complexity and nonlinear characteristics of vibration signals. Inspired by multi-scale entropy (MSE) and aiming at the problem of coarse-graining in MSE, composite multi-scale reverse dispersion entropy (CMRDE) was proposed. CMRDE is compared with multi-scale reverse dispersion entropy (MRDE) and RDE through simulation signal analysis and the results show that it can reflect the difference of signal complexity at different scales and its varying trend is much smoother and the fluctuation is much smaller. Based on this, CMRDE was applied to the fault feature extraction of rolling bearings and a new rolling bearing fault diagnosis method was proposed based on CMRDE, ensemble empirical mode decomposition and cuckoo search support vector machine. The proposed fault diagnosis method was applied to analyze experimental data of rolling bearing with comparing with the existing methods and the analysis results indicate that the proposed method can effectively identify the fault location of rolling bearing and the errors of extracted fault feature is smaller and the fault recognition rate is higher than the compared methods.
Key words: reverse dispersion entropy; composite multi-scale reverse dispersion entropy; rolling bearing; fault diagnosis

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reverse dispersion entropy / composite multi-scale reverse dispersion entropy / rolling bearing / fault diagnosis

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CHEN Yan, ZHENG Jinde, PAN Haiyang, TONG Jinyu. Application of CMRDE in bearing fault diagnosis[J]. Journal of Vibration and Shock, 2022, 41(19): 55-63

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