DAMAGE DETECTION AND OPTIMUM SENSOR LOCALIZATION BASED ON INCOMPLETE DAMAGE INDEXES AND GENETIC ALGORITHMS FOR LONG-SPAN BRIDGES

The methods for damage detection and optimum sensor localization with the incomplete damage indexes based on the incomplete mode shapes are developed, and the multi-species genetic algorithms for the structural health monitoring system of long-span bridges are improved. Two incomplete damage indexes, the difference in the incomplete mode flexibility matrixes, and the change ratio in the truncated mode strain energies, are developed as the fitness parameters in comparison with traditional COMAC. The modified multi-species genetic algorithms combine the advantages of general genetic algorithms and multi-species genetic algorithms, and are better in convergence and global optimization. The FE model of Xihoumen suspension bridge is used as an example for damage detection and optimum sensor localization. The results show the methods are feasible and effective.