Comparative study on modal parametric identification methods based on complexity pursuit

HU Zhixiang, HUANG Lei, ZHI Lunhai, HU Feng

Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (15) : 22-31.

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PDF(3540 KB)
Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (15) : 22-31.

Comparative study on modal parametric identification methods based on complexity pursuit

  • HU Zhixiang, HUANG Lei, ZHI Lunhai, HU Feng
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Abstract

Complexity Pursuit (CP) is a classical method for blind source separation of vibration signals. Two main approaches for estimating the de-mixing matrix using Complexity Pursuit are Complexity Pursuit-Gradient Descent (CP-GD), based on the complexity calculation of source signals, and Temporal Predictability-Generalized Eigenvalue Decomposition (TP-GED), based on the temporal predictability. The equivalence and computational performance of these two algorithms were studied based on vibration simulation. Firstly, the specific theories and algorithm procedures of CP-GD and TP-GED algorithms were presented. Secondly, the variations of source signal complexity and predictability corresponding to the de-mixed vectors were intuitively demonstrated and compared using two- and three-degree-of-freedom vibration systems. Finally, the accuracy and computation cost of the two algorithms were compared through modal parameter identification examples with multiple operating conditions and multiple degrees of freedom. The research results show that under low damping ratio and high signal-to-noise ratio conditions, the de-mixing matrices obtained with both methods are the same. Considering the computational cost of calculating signal complexity and performing gradient descent, the CP-GD algorithm has a higher computational cost than the TP-GED algorithm.

Key words

blind source separation(BSS) / modal parameter identification / kolmogoroff complexity / temporal predictability / gradient descent / generalized eigenvalue decomposition

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HU Zhixiang, HUANG Lei, ZHI Lunhai, HU Feng. Comparative study on modal parametric identification methods based on complexity pursuit[J]. Journal of Vibration and Shock, 2024, 43(15): 22-31

References

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