ON THE USE OF CONSISTENT AND SIGNIFICANT INFORMATION TO REDUCE ILL-CONDITIONING IN DYNAMIC-MODEL UPDATING

A dynamic model updating technique, force residual updating-interactiv e technique (FRU-IT), is described. The technique is based on minimisa tion of the force (input) residual. Like most parametric identificatio n problems, dynamic model updating is affected strongly by measurement errors due to the ill-conditioning of the problem. The proposed metho d is used to define and solve the set of updating equations in order t o minimise the influence of measurement errors. This includes the sele ction of experimental degrees of freedom to ensure data consistency, t he choice of the working frequencies to pursue data significance, and the use of regularisation techniques; specifically, an interactive use is made of the truncated singular value decomposition. The performanc e of the method is demonstrated by test cases. (C) 1998 Academic Press Limited.