Assessment of Existing Structures Based on Identification

Abstract

A nondestructive damage detection approach based on measured structural responses is presented and verified by controlled laboratory experiments and by tests on real structures. In the experiments, defined magnitudes of damages are assigned to reinforced concrete beams, and the dynamic responses of the undamaged and damaged specimens are measured. The measured frequencies of the specimens and their sensitivity to change in mechanical characteristics, called sensitivity factors, are used to predict the location and the magnitude of the damage. The damage locations associated with the investigated test series are predicted with high accuracy by the proposed identification approach. This approach has been applied to real structures, including an existing bridge in Switzerland. In order to provide successful damage detection in cases where the damage does not affect or only marginal affects dynamic structural characteristics, the approach has been extended to handle simultaneous multiple structural response characteristics, such as frequencies, and modal and static displacements. The identification approach satisfies ease-of-use requirements in existing reliability assessment methods for deteriorating structures. The main purposes of this paper are to (1) present the proposed identification algorithm; (2) discuss the adjustment of the stochastic algorithm inputs, such as cross-sectional stiffness, geometrical, and mechanical properties, by monitored structural responses; and (3) present the interaction between the developed identification algorithm and the stratified Monte Carlo randomization technique, thus allowing the application of the algorithm to large engineering structures. Additionally, it is shown that the developed code is suitable for incorporation into commercial software packages.