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Identification of Time-varying Structural Parameters by Integrated Wavelet Decomposition and Kalman Filter with Partial Response Measurements



Structural parameter identification has been emerged as an interesting and important problem in structural health monitoring (SHM). Structural parameters directly reflect the dynamic characteristics of structures, so the identification of timevarying structural physical parameters is more meaningful to civil engineering structures. To overcome the limitations of requiring full measurements of structural responses in previous research, an algorithm based on the integration of wavelet multiresolution analysis and Kalman filter with partial measurements of structural acceleration responses is proposed. First, the time-varying structural physical parameters are expanded at multi-scale profile by wavelet multiresolution analysis and a time-varying parametric identification problem can be converted into a timeinvariant one. Then, structural states at all dynamic degrees-of-freedom (DOFs) are estimated recursively by the Kalman filter with partial measurements of structural acceleration responses at previous step. The scale coefficients of the expansion can be obtained by minimizing the error between estimated and observed accelerations. Some numerical examples of identifying time-varying structural parameters of a linear three-story shear type frame are used to illustrate the effectiveness and accuracy of the proposed algorithm.


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