Friction coefficient estimation in sliding isolators through a nonlinear parametric estimation approach

Nowadays, the structural health monitoring through the identification of nonlinear dynamic systems is frequently applied in the field of civil engineering. An unscented Kalman filter (UKF) is proposed in this paper, to estimate the coefficient of friction of friction-based isolators (Curved Surface Sliders), using the measured accelerations of the isolated superstructure as measurement input in the UKF. The results of a numerical simulation of a two degree of freedom system, isolated with Curved Surface Sliders, are used in order to evaluate the UKF estimation results and to prove its reliability. Simulation results prove an excellent state estimation accuracy obtainable through this approach and the ability of the UKF to identify the coefficient of friction. The methodology can be used for the determination of the friction coefficient of sliding isolators in real applications to identify their state of wear.