Identification of unknown inputs considering structural parametric uncertainties

Abstract

Due to the inevitable uncertainties in structural parameters and difficulty in measuring external excitations, it is necessary to consider the effects of structural parametric uncertainties in identifying unknown inputs to structures. In this paper, considering structural parametric uncertainties, two excitation identification approaches are proposed accounting for the different scenarios of sensor deployments. The first algorithm is based on the improved Kalman filter with unknown input (KF-UI) recently proposed by the authors, in which acceleration responses are measured at the locations where unknown inputs applied. The second method is based on modal Kalman filter with unknown input (MKF-UI) to consider the scenario that acceleration responses at the locations of unknown inputs are unmeasured. For the uncertainties of structural parameters, probability model or interval model are studied, respectively. Numerical examples are performed and Monte Carlo simulation is applied in comparison to validate the effectiveness and accuracy of the unknown input identification.