Parameter identification of large structural systems in time domain

Though many methods of system identification are currently available for pa rameter estimation of structural systems, the challenge lies in the numeric al difficulty in convergence when the number of unknowns is large. In this study, the genetic algorithms (GA) approach is adopted, which has several a dvantages over classical system identification techniques. Nevertheless, if applied directly, this approach requires tremendous computational time whe n dealing with structural systems large in both unknowns and degrees of fre edom. A method is proposed herein to alleviate this problem by conducting a GA search in modal domains of a much smaller dimension than the physical d omain. The objective function is defined based on the estimated modal respo nse in time domain acid the corresponding modal response transformed from t he measured response. With some modification, this method also works well e ven with incomplete response measurement. Numerical examples of structural systems of up to 50 degrees of freedom are presented. Effects of measuremen t noise are considered.