Structural damage online identification algorithm based on AUKF

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Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (23) : 203-210.

HUANG Ke1,2, SUN Zhan1, HUANG Dukang1, WANG Lei1

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Abstract

In the process of structural damage identification and health monitoring using unscented Kalman filtering, the noise is often unknown and time-varying, and the traditional unscented Kalman filtering is prone to performance degradation and dispersion when the noise is not selected properly. Therefore, an online structural damage identification algorithm based on an adaptive unscented Kalman filter is proposed. The proposed method uses covariance matching and forgetting factor method to identify and update the measurement noise and process noise in real time by residuals and innovations, which improves the accuracy of the unscented Kalman filtering for the identification of unknown parameters and damages of the structure while guaranteeing the positive characterization of the noise matrix. Numerical examples of the bridge model and the nonlinear model are used to verify the effectiveness of the proposed method. The results show that the method in this paper can effectively recognize the location and severity of damage in large civil engineering structures and nonlinear structures and is adaptive and robust to time-varying noise.

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unscented Kalman filter / damage identification / noise identification / structure health monitoring

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HUANG Ke1, 2, SUN Zhan1, HUANG Dukang1, WANG Lei1. Structural damage online identification algorithm based on AUKF[J]. Journal of Vibration and Shock, 2024, 43(23): 203-210

References

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