Parameter and Aerodynamic Force Identification of Single-Degree-of-Freedom System in Wind Tunnel Test

Abstract

The extended Kalman filter with unknown inputs (EKF-UI) method has been extensively studied for application in system and input identification of multiple-degrees-of-freedom systems. The inverse problem is, however, unidentifiable for the case of a single-degree-of-freedom system with unknown system parameters and excitation. This study presents a strategy to address this problem based on output using only the EKF-UI method. A numerical example is given to validate the proposed method for system parameters and input identification. The strategy is then applied to identify the aerodynamic load and system parameters of a tower model in a wind tunnel test. Both system stiffness and damping were found to vary with the incident wind speed, and the vortex shedding-induced excitation in the cross-wind direction was clearly noted in the power spectrum of the identified wind load.