RREASO Building Structure Physical Parameter Identification Algorithm for Structural Damage Identification

Abstract

With the intensification of human modernization, civil engineering and building structures have become increasingly complex. Their safety hazards have also emerged. Therefore, scientific structural parameter identification algorithms are particularly crucial for health monitoring of current complex building structures. Based on this, the traditional atomic search optimization algorithm is improved ground on the roulette wheel selection strategy, random walk strategy, elite selection strategy, and substructure technology. The numerical simulation experiment results showed that the improved method performed better than the atomic search optimization algorithm in identifying structures with more degrees of freedom. The maximum relative errors for substructure and full structure stiffness identification of the improved algorithm were 13% and 43.1%, respectively, indicating that the combination of the improved algorithm and substructure identification method had better structural parameter identification results. In real structural parameter identification experiments, the identification error of the improved algorithm was less than 10%, the identification stiffness was reduced to 58.9%, and the relative error was around 10%, which was better than the traditional atomic search optimization algorithm. This indicates the effectiveness and feasibility in identifying building structural parameters, which is essential to ensure the safety and durability of real engineered structures.