Hybrid Test model updating method based on statistical cubature Kalman filter

WANG Tao1, LI Meng1, MENG Liyan1, XU Guoshan2, WANG Zhen3

Journal of Vibration and Shock ›› 2022, Vol. 41 ›› Issue (11) : 72-82.

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PDF(5097 KB)
Journal of Vibration and Shock ›› 2022, Vol. 41 ›› Issue (11) : 72-82.

Hybrid Test model updating method based on statistical cubature Kalman filter

  • WANG Tao1, LI Meng1, MENG Liyan1, XU Guoshan2, WANG Zhen3
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Abstract

In order to avoid the influence of the model updating algorithm on the model parameter identification accuracy due to the improper selection of initial parameters, a hybrid testing model updating method of statistical cubature Kalman filter(CKF) was proposed. The method used CKF algorithm to identify model parameters for several times. In order to weaken the influence of the initial parameter selection of the algorithm on the parameter identification results, the sample mean of the statistical parameter identification value was taken as the final identification result. Statistical CKF was used to identify online parameters of self-centering energy dissipation braces model to verify the reliability of statistical CKF under different parameters; The statistical CKF was tested by the hybrid simulation of two layers of bracing frame with self-centering energy dissipation. The results show that the method based on statistical CKF can effectively improve the accuracy and robustness of model update hybrid testing.

Key words

hybrid testing / model updating / cubature Kalman filter / self-centering energy dissipation braces / on-line parameter identification

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WANG Tao1, LI Meng1, MENG Liyan1, XU Guoshan2, WANG Zhen3. Hybrid Test model updating method based on statistical cubature Kalman filter[J]. Journal of Vibration and Shock, 2022, 41(11): 72-82

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