ABSTRACT
In the past few decades, numerous methods have been developed for structural model updating and external excitation of nonlinear structures. The Kalman filter is an effective means of parameter identification and input estimation for a linear or nonlinear structure. Two forms of the extended recursive least-squares algorithm were considered for the identification of system parameter and the tracking of a chirped sinusoid with additive noise (S. Haykin et al. 1997). Other time-variant parameter identification methods are: the online identification of nonlinear hysteretic structure with an adaptive tracking techniques based on
1 INTRODUCTION
Civil infrastructures always suffer from damages and some components may perform nonlinearly during the severe external excitation. The evaluation of the structural parameter and external excitation are two main parts of structural health monitoring, which contribute efficiently to structural maintenance and management. Vibrationbased methods (Doebling, 1998) are investigated actively for decades and they are always applied in the structural health monitoring. Both the structural parameter and external excitation have coupling influence on structural response with the vibration-based structural health monitoring. Therefore, the evaluation of one aspect but omitting the influence of another aspect may cause error in the identification result. Exact knowledge of structural parameter and the excitation time history are essential to the post-event structural condition assessment and the prediction of load-bearing capacity. However, the simultaneous identification of structural parameter and external excitation is a difficult work for structural health monitoring and post-event condition assessment, especially for nonlinear structures.
