| Title |
Model Parameter Estimation of Across-Wind Load Based on Bayesian Approach |
| DOI |
https://doi.org/10.5659/JAIK.2021.37.2.181 |
| Keywords |
Across-wind load; Bayesian filtering; Unscented Kalman Filtering; Load separation; Model parameter estimation |
| Abstract |
It is known that the across-wind load is mainly consist of three components: the buffeting, Strouhal, and feedback load components. The
feedback load can be easily separated from the across-wind load using the structural velocity response and aerodynamic damping ratio.
However, it is difficult to quantitatively and independently evaluate the contribution of the buffeting and Strouhal load since the two load
components are strongly combined in the across-wind load. In this study, it is proposed a new approach to separate the two load components
using Bayesian filtering and to identify the parameters of each mathematical model. This technique consists of a process of estimating the
parameters of the mathematical load model, which can be expressed in the form of a transfer function, in the frequency domain using the
unscented Kalman filter, and sequentially performing load separation. For the validation of the proposed approach, the aeroelastic model test
was performed and wind load was inversely identified from the acceleration response obtained from the wind tunnel test. And then, the
proposed technique is applied on the wind load, which shows that the stable parameter estimation of the buffing and Strouhal load,
respectively, was reliably peformed. |