EACS 2016 paper - Unscented Kalman filter for simultaneous identification of structural.pdf (359.73 kB)
EACS 2016 paper - Unscented Kalman filter for simultaneous identification of structural parameters and unknown excitations of a building structure
journal contributionposted on 2017-03-28, 15:15 authored by Hongjun Liu, Qin Huang
EACS 2016 Paper No. 107
Identification of structural parameters under unknown excitations is an import task in structural health monitoring. This paper presents an efficient algorithm for simultaneously identifying structural parameters of a building structure and unknown excitations based on unscented Kalman filter (UKF). To utilize the UKF method directly, the observation equation of the structural system with unknown excitations is firstly transformed from a multiple linear regression equation to a simple linear regression equation by projecting on to the column space of influence matrix of unknown excitations. Then, an analytical recursive UKF algorithm is developed for identifying unknown excitations and structural parameters such as stiffness and damping. The feasibility and accuracy of the proposed algorithm are finally demonstrated in terms of an example shear building, in which the measurement noise is included. The results clearly exhibit that the proposed algorithm can simultaneously identify unknown excitations and structural parameters efficiently and accurately.