Deterioration and degradation of aging structures is a major concern worldwide. It is often necessary to evaluate the integrity of such structural systems. Early detection and eventual quantification of damage are important for improved safety, to prevent potential catastrophic events, and to extend the service life by repairing/retrofitting the components of the structure. Different methodologies have been proposed in the literature for the identification and localization of damage based on optimization techniques and modal-based approaches. The main drawback in using the optimization approach based on evolutionary algorithms is that it requires the evaluation of the objective function for the total population in each generation. As this is computationally intensive, in this study, a multi-stage approach has been proposed. In this, at first, localization of the damage was achieved so as to reduce the number of parameters of the objective function in the optimization approach. These identified damaged elements were analyzed further for exact identification and quantification of the damage using genetic algorithm (GA)-based optimization approach. To demonstrate the efficiency of the proposed hybrid approach, numerical studies have been carried out on selected structures. The approach of using modal strain energy change ratio to identify damage at first-stage identification is found to be very useful in reducing the objective function parameters in the optimization method. This multi-stage approach is found to be very efficient in the exact identification and quantification of damage in structures. The proposed approach could be used for identifying damage in large-scale structures.
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