Damage Identification of Bridge Structures based on Improved Genetic Algorithms
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Genetic algorithm has powerful global search ability, and its better fitness has been gradually applied to the field of civil structure damage identification. The improved genetic algorithm based on the theory of fuzzy optimization has faster convergence speed and higher operational efficiency. The improved genetic algorithm is applied to damage identification of actual bridge structures. The different data collected by various sensors are processed centrally by data fusion method, which increases the accuracy of identification results. In this paper, the displacement, stress, acceleration and other parameters collected in the field were selected to identify the damage. The feasibility of the method was verified by programming with MATLAB software.
Bridge, genetic algorithms, damage recognition, Fuzzy Optimum Selection, data fusion