A novel approach to deal with nonlinear system identification of civil structures subjected to unmeasured excitations is presented. Using only sparse global dynamic structural response, mechanics-based nonlinear finite element (FE) model parameters and unmeasured inputs are estimated. Unmeasured inputs are represented by a time-varying autoregressive (TAR) model. Unknown FE model parameters and TAR model parameters are jointly estimated using an unscented Kalman filter. The proposed method is validated using numerically simulated data from a 3D steel frame subjected to seismic base excitation. Six material parameters and one component of the base excitation are considered as unknowns. Excellent input and model parameter estimations are obtained, even for low order TAR models.
|Title of host publication||Model Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020|
|Number of pages||4|
|State||Published - 2020|
|Event||38th IMAC, A Conference and Exposition on Structural Dynamics, 2020 - Houston, United States|
Duration: 10 Feb 2020 → 13 Feb 2020
|Name||Conference Proceedings of the Society for Experimental Mechanics Series|
|Conference||38th IMAC, A Conference and Exposition on Structural Dynamics, 2020|
|Period||10/02/20 → 13/02/20|
Bibliographical notePublisher Copyright:
© 2020, The Society for Experimental Mechanics, Inc.
- Auto-regressive model
- Finite element model
- Input estimation
- Kalman filter
- Model updating