Author:

Keywords:

Science & Technology, Technology, Engineering, Civil, Engineering, State estimation, Response prediction, Input estimation, Kalman filter, Force identification, EXTENDED KALMAN FILTER, STATE ESTIMATION, BAYESIAN STATE, IDENTIFICATION, SYSTEMS

Abstract:

The problem of jointly estimating the input forces and states of a structure from a limited number of acceleration measurements is addressed. Utilizing a model-based joint input-state estimation algorithm originally developed for optimal control problems, minimum-variance unbiased estimates of the modal displacements and velocities of a structure as well as the dynamic forces causing these responses, are obtained. The proposed algorithm requires no prior information on the dynamic evolution of the input forces, is easy to implement, and allows online application. Its accuracy and effectiveness are demonstrated using data from an in situ experiment on a footbridge.