Abstract
The problem of blending in empirical mode decomposition (EMD) method has led to the proposal of a new technique called ensemble empirical mode decomposition analysis (EEMD). As EEMD has a problem with reconstruction error, so a new technique has been proposed in this paper to check the ability to separate blending modes, and the method is complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). In this paper, Hilbert spectroscopic analysis was performed to verify the patterns extracted from different frequencies. Further, EEMD is implemented to correct the mode mixing problem in EMD. Moreover, due to noise in modes extracted from EEMD, CEEMDAN is implemented here. Other parameters such as mean value and entropy of patterns of all the discussed methods over here are calculated to find out the comparison between all three methods (EMD, EEMD and CEEMDAN). From the simulation results, it can be concluded that CEEMDAN is a better detector for defect in bearing.
Published Version
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