Modal parameters identification using the density peaks clustering algorithm

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Journal of Vibration and Shock ›› 2019, Vol. 38 ›› Issue (2) : 172-178.

WANG Fei-yu1, HU Zhi-xiang1, HUANG Xiao2

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Abstract

The sparse component analysis is an efficient approach to handle the underdetermined blind source separation,which contains two steps: calculating the mixing matrix and second,reconstructing the sources.In the paper,the modal shapes were calculated by using the Density Peaks Clustering Algorithm to deal with the cases that the number of sources cannot be known a priori and high order modes are overlapped with each other.Compared to the traditional clustering algorithms,it has two advantages: determining the centers of clusters according to the decision graphs directly and being insensitive to noises.The SL0 algorithm a sparse recovery algorithm,was used to reconstruct the sources.Then the frequency of each mode was identified from the sources in time-frequency domain.The effectiveness of the proposed method was validated via adopting a six degree-of-freedom vibration system as a simulation example.

Key words

modal analysis / sparse component analysis / Density Peaks Clustering Algorithm / SL0 algorithm

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WANG Fei-yu1, HU Zhi-xiang1, HUANG Xiao2. Modal parameters identification using the density peaks clustering algorithm[J]. Journal of Vibration and Shock, 2019, 38(2): 172-178

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