Improved modal parameter identification method based on particle swarm optimization

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Journal of Vibration and Shock ›› 2022, Vol. 41 ›› Issue (2) : 255-264.

ZHANG Jindong1, GUO Xiaonong1, LUO Xiaoqun1, ZHANG Yujian1, XU Hongjun1,2

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Abstract

Aiming at the modal parameter identification of multimodal vibration attenuation signals, an improved modal parameter identification method (PSO-AMD) is proposed by combining singular value decomposition (SVD), analytical mode decomposition (AMD), auto regressive power spectral density spectrum (ARPSD) and particle swarm optimization (PSO). The method can be used for modal parameter identification of dense frequency signals in strong noise environment. The analysis results of the simulated vibration response signal show that the improved method proposed in this paper has higher stability and maintains high recognition accuracy for vibration signals with low SNR, dense frequency and large damping. The modal parameter identification method in this paper can be applied to modal parameter identification of large damping and dense frequency vibration attenuation signals in complex noise environment.

Key words

modal parameter identification / singular value decomposition / analytical mode decomposition / particle swarm optimization algorithm / auto regressive power spectral density spectrum

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ZHANG Jindong1, GUO Xiaonong1, LUO Xiaoqun1, ZHANG Yujian1, XU Hongjun1,2. Improved modal parameter identification method based on particle swarm optimization[J]. Journal of Vibration and Shock, 2022, 41(2): 255-264

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