Identification of nonlinear aerodynamic damping from stochastic crosswind response of tall buildings using unscented Kalman filter technique

Wu, Yanchi; Chen, Xinzhong

doi:10.1016/j.engstruct.2020.110791

Cited by 17 publications

(2 citation statements)

References 30 publications

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“…Specific structural types under investigation include bridges, tall buildings, aircraft, etc. [ 74 ]. Apart from previous review articles that are mainly about nonlinear system identification [ 1 , 2 , 23 ], the focus of this study resides on the development of various NDI methods.…”

Section: Nonlinear Damping Identification Methodsmentioning

confidence: 99%

A Critical Review of Nonlinear Damping Identification in Structural Dynamics: Methods, Applications, and Challenges

Al-hababi

Cao

Saleh

et al. 2020

Sensors

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In recent decades, nonlinear damping identification (NDI) in structural dynamics has attracted wide research interests and intensive studies. Different NDI strategies, from conventional to more advanced, have been developed for a variety of structural types. With apparent advantages over classical linear methods, these strategies are able to quantify the nonlinear damping characteristics, providing powerful tools for the analysis and design of complex engineering structures. Since the current trend in many applications tends to more advanced and sophisticated applications, it is of great necessity to work on developing these methods to keep pace with this progress. Moreover, NDI can provide an effective and promising tool for structural damage detection purposes, where the changes in the dynamic features of structures can be correlated with damage levels. This review paper provides an overview of NDI methods by explaining the fundamental challenges and potentials of these methods based on the available literature. Furthermore, this research offers a comprehensive survey of different applications and future research trends of NDI. For potential development and application work for nonlinear damping methods, the anticipated results and recommendations of the current paper can assist researchers and developers worldwide to find out the gaps and unsolved issues in the field of NDI.

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Section: Nonlinear Damping Identification Methodsmentioning

confidence: 99%

A Critical Review of Nonlinear Damping Identification in Structural Dynamics: Methods, Applications, and Challenges

Al-hababi

Cao

Saleh

et al. 2020

Sensors

View full text Add to dashboard Cite

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“…A brief review of the UKF can be found in Appendix B. The readers are also referred to previous works 27–30 for comprehensive study about this technique. Since UKF works in a two‐step recursive process, that is, predicting the current state variables according to the discrete‐time state equation, and updating the state variables by the use of the observation equation, the state equation and the observation equation for the base‐isolated building are defined as follows.…”

Section: Laboratory Test Of Two‐story Base‐isolated Buildingmentioning

confidence: 99%

Displacement measurement and nonlinear structural system identification: A vision‐based approach with camera motion correction using planar structures

Jiao

Guo

Fujita

et al. 2021

Struct Control Health Monit

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Summary Knowledge of the camera motion is important in the applications of structural dynamic response measurement using a vision‐based approach because in most of the field measurements, such motion can be non‐trivial and the accuracy of dynamic response measurements is strongly affected by the camera motion. This paper presents a new framework for camera motion estimation and vision‐based displacement measurement, which greatly lowers the barriers to the application of generally positioned cameras from strictly stationary cameras. The contributions in this paper are twofold. First, camera motion as well as reconstructed structural displacement are calculated based on reference planar structures visible in a given scene. In this case, a homography is more effective at describing view changes and planar geometric constraints can be incorporated early in the reconstruction process, thereby improving the quality and effectiveness of the estimates. The second contribution is that the homography of the planar structure is estimated by a newly proposed tracking algorithm that combines RANSAC algorithm and Efficient Second‐order Minimization (ESM) technique, which refines the final estimates to sub‐pixel accuracy and avoids tracking drift and non‐smoothness effectively. Experimental results indicate that the quality of the camera motion estimation and displacement reconstruction can be significantly improved by the judgmatical use of the proposed algorithm for planar structure homography estimation. Furthermore, nonlinear structural system identification is carried out to additionally verify the proposed algorithm using unscented Kalman filter.

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Reliability assessment of a building complex with four long-span roof structures based on wind tunnel experiments

Huang

Gui

2021

J Civil Struct Health Monit

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Identification of nonlinear aerodynamic damping from stochastic crosswind response of tall buildings using unscented Kalman filter technique

Cited by 17 publications

References 30 publications

A Critical Review of Nonlinear Damping Identification in Structural Dynamics: Methods, Applications, and Challenges

A Critical Review of Nonlinear Damping Identification in Structural Dynamics: Methods, Applications, and Challenges

Displacement measurement and nonlinear structural system identification: A vision‐based approach with camera motion correction using planar structures

Reliability assessment of a building complex with four long-span roof structures based on wind tunnel experiments

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