UPDATING ANALYTICAL MODELS BY USING LOCAL AND GLOBAL PARAMETERS AND RELAXED OPTIMIZATION REQUIREMENTS

Two methods aimed at improving the robustness of the identification pr ocess in the presence of more or less unavoidable idealisation and mea surement errors are described. The first method splits the uncertain p arameters into two groups. The first group contains the local physical parameters related to those areas of the structure (called the main s tructure), where parameter uncertainties can be assigned a priori; the second group contains global generalised parameters related to the re maining structure (the residual structure), where it is difficult to a ssign uncertain parameters. These global parameters compensate for all the effects resulting from non-parametric modeling errors. This appro ach has the additional advantage of restricting the measurement of the mode shapes to those critical areas where local parameter uncertainti es are expected. The second method describes a technique for smoothing the experimental mode shapes in order to reduce the influence of rand om and systematic measurement errors. Constructing the objective funct ion from the differences between the analytical and the smoothed exper imental mode shapes together with the related eigenfrequencies relaxes the minimisation requirements and tends to improve the robustness of the identification process. The applicability of these methods is demo nstrated by updating the parameters related to bolted joints of an exp erimental frame structure. (C) 1998 Academic Press Limited.