Substructural identification for damage assessment of large structures

Abstract

This dissertation presents substructural identification methods for the assessment of local damages in complex and large structural systems. For this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for a substructure to process the measurement data impaired by noises. The sequential prediction error method incorporating several special techniques, such as the exponential data weighting, the global data weighting and the square root estimation of the adaptation gain matrix is used for the estimation of unknown parameters related to damages. Using the substructural methods, the number of unknown parameters for each identification can be significantly reduced, hence the convergence and accuracy of estimation can be improved. For some substructures, the effect of the input excitation is expressed in terms of the responses at the interfaces with the main structure, and substructural identification may be carried out without measuring the actual input excitation to the structure. Secondly, the damage index is defined as the ratio of the current stiffness to the baseline value at each element for the damage assessment. Two methods for the estimation of those element damage indices using the substructural identification are also presented. One is the direct method to estimate those indices directly from the measured time histories of the excitations and responses. The other is the indirect estimation method using the estimated results from the identification of the system matrices using the substructural identification. For the direct method, the sensitivity matrix between the ARMAX and the element damage parameters is derived and sequential prediction error method is employed for the estimation of the element damage indices. For the indirect method, the pseudo-inverse method is used. To demonstrate the proposed techniques, several example analyses are carried out for idealized structural models of a multistory building, ...