Performance comparison of Kalman−based filters for nonlinear structural finite element model updating

Finite element (FE) model updating has emerged as a powerful technique for structural health monitoring and damage identification of civil structures. Updating mechanics-based nonlinear FE models allows for a complete and comprehensive damage diagnosis of large and complex structures, but it is comp...

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Vydáno v:Journal of sound and vibration Ročník 438; s. 520 - 542
Hlavní autoři: Astroza, Rodrigo, Ebrahimian, Hamed, Conte, Joel P.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier Ltd 06.01.2019
Elsevier Science Ltd
Témata:
Accuracy
Computational efficiency
Computer simulation
Concrete construction
Damage detection
Damage identification
Divergence
Earthquake damage
Extended Kalman filter
Finite element analysis
Finite element method
Frame structures
Kalman filters
Kalman-based filter
Mathematical models
Mechanics (physics)
Model updating
Nonlinear finite element model
Parameter estimation
Recursive methods
Reinforced concrete
Robustness (mathematics)
Seismic engineering
Structural damage
Structural health monitoring
Parameter estimation
Damage identification
Kalman-based filter
Nonlinear finite element model
ISSN:0022-460X, 1095-8568
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Shrnutí:Finite element (FE) model updating has emerged as a powerful technique for structural health monitoring and damage identification of civil structures. Updating mechanics-based nonlinear FE models allows for a complete and comprehensive damage diagnosis of large and complex structures, but it is computationally demanding. This paper first introduces an Iterated Extended Kalman filter (IEKF) to update mechanics-based nonlinear FE models of civil structures. Different model updating techniques using the Extended Kalman filter (EKF), Unscented Kalman Filter (UKF) and IEKF, are then compared for their performance in terms of convergence, accuracy, robustness, and computational demand. Finally, a non-recursive estimation procedure is presented and its effectiveness in reducing the computational cost, while maintaining accuracy and robustness, is demonstrated. An application example is presented based on numerically simulated response data for a three-dimensional 5-story 2-by-1 bay reinforced concrete (RC) frame building subjected to bi-directional earthquake excitation. Excellent estimation results are obtained with the EKF, UKF, and IEKF used in conjunction with the proposed non-recursive estimation approach. Because of the analytical linearization used in the EKF and IEKF, abrupt and large jumps in the estimates of the model parameters are observed with these filters, which may lead to divergence of the nonlinear FE model solution procedure. The UKF slightly outperforms the EKF and IEKF, but at a higher computational cost.
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ISSN:0022-460X
1095-8568
DOI:10.1016/j.jsv.2018.09.023