An optimal variational mode decomposition method based on sparse index

ZHANG Lu1,2,LI Hua1,CUI Jie1,WANG Xiaodong1,XIAO Ling1

Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (8) : 234-250.

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PDF(7723 KB)
Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (8) : 234-250.

An optimal variational mode decomposition method based on sparse index

  • ZHANG Lu1,2,LI Hua1,CUI Jie1,WANG Xiaodong1,XIAO Ling1
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Abstract

This paper presents a sparse index-based variational mode decomposition method to deal with the challenge of determining the decomposition mode number K when the number of composite signal sources is unknown. Based on the sparse prior theory of each component in the VMD decomposition, the adaptive optimal K value of VMD is discovered as the turning point of the sparse index from rising to falling. Considering the energy difference between different components, the energy weight factor is added in the computation of sparsity index. Finally, the sparsity index is determined as the average value of the marginal spectral sparsity of each component after decomposition. The results of simulations and real-world signal decomposition experiments prove the superiority of this method. Compared with the other two modified VMD methods, proposed method determines a more accurate K value and is more adaptive. Moreover, The results of experiment show that the method has a better decomposition effect than other signal decomposition methods like EMD. Proposed method introduces a novel concept for adaptive and efficient VMD decomposition of composite signals with unknown source numbers. To the next level, the robust noise experiment demonstrates that the suggested sparse index approach has a certain anti-noise ability. It shows that this method is relatively robust and it can be developed and applied to practical engineering.

Key words

compound signal decomposition / variational mode decomposition / decomposition mode number / sparse index / adaptive optimization

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ZHANG Lu1,2,LI Hua1,CUI Jie1,WANG Xiaodong1,XIAO Ling1. An optimal variational mode decomposition method based on sparse index[J]. Journal of Vibration and Shock, 2023, 42(8): 234-250

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