Finite element model updating using variable separation

In the field of structural dynamics, reliable finite element response predictions are becoming increasingly important to industry and there is a genuine interest to improve these in the light of measured frequency response functions. Unlike modal-based model updating formulations, response-based methods have been applied only with limited success due to incomplete measurements and numerical ill-conditioning problems. The least squares approximation method is one of the methods used but often poses a problem of pseudo inverse due to the number of incomplete measurements. The proposed algorithm is a modification and extension of a previously-developed nonlinear least squares method for damage detection and finite element model updating. The paper derives explicit expressions for the first and second order partial derivatives with respect to the correction parameters and for the Jacobian matrix used in the Newton–Raphson solution of the nonlinear set of equations in order to avoid the pseudo inverse and to build a symmetrical system. The proposed method, assigned to a frequency parameterization which considers the minimum distance to be minimized, shows a good numerical stability. The performance of the method in localizing structural damage and updating model is examined using simulated measurements.