Swarm Intelligent Optimization Conjunction with Kriging Model for Bridge Structure Finite Element Model Updating

For the simple bridge structure, finite element model established by drawing and elastic mechanics method is accurate. However, when faced with large complex long-span structures, there are inevitable differences between physical model, where has to be updated. It problematic that updating structural matrix cannot fed back into existing general calculation software in traditional method. In this paper, a parameter-type based on “Kriging + swarm intelligence” optimization proposed. The Kriging Genetic Algorithm (GA), Bird Mating Optimizer (BMO), Particle Swarm Optimization algorithm (PSO), introduced correct design parameters of model. Firstly, truss structure was used verify effectiveness proposed method, then cable-stayed taken as an example. Three methods were update bridge, results three algorithms compared analyzed. show that, other two methods, GA-based least time due small computation. BMO-based consuming algorithms, parameter identification better than GA algorithm. PSO algorithm-based solve repeated, which required amount computation more consuming; however, it had highest correction accuracy.