Research On Structural Damage Detection Base On Particle Swarm Optimization Algorithm

Civil engineering structure will be affected by the environment load, fatigue load, chemical corrosion, material aging and other unfavorable factors during the long-term service, the mechanical properties of the structure will be changed and the integrity of the structure will be broken. By increasing the number of structural health monitoring system, it can effectively diagnose the structure damage state in time and avoid safety accident happen. Therefore, the structural health monitoring is becoming hot research issue of the world wide attention. Which kinds of structure damage detection technologies to use is the primary issue to be solved.In this paper, on the basis of existing research achievements, do the following:(1) On the basis of the research of structural damage diagnosis technology at home and abroad, the traditional particle swarm optimization(PSO) was combined with frequency response function, and using CSAC and CAF of the measured frequency response function and calculating the frequency response function to construct the optimization object function of PSO, through the international benchmark structure which is put forward by the sharing platform in order to verify the optimization algorithm is effective, the calculations show that the proposed optimization algorithm in this paper is equally effective as well as GA in existing literature, and even better than GA in some cases.(2) Specific improvement measures were put forward for the problem of the particles was easily plunged into local optimum, resulting in unable to search again, global searching performance degradation, the "precocious" phenomenon appear. The measures is intervene to the position of particles in the process of each iteration, enhance cognitive ability and social ability of PSO, advance the diversity of PSO and global searching performance, to improve the deficiency of the traditional particle swarm optimization algorithm.(3) The improved particle swarm optimization was combined with frequency response function, a five internodes of truss structures was modal analysis through finite element, extraction the top 5 order natural frequency of the structure and the complete information for damage identification required, and the recognition result was compared with the traditional particle swarm optimization algorithm, the result display, the convergence speed of the improved particle swarm algorithm is faster, and the identification result of the improved particle swarm algorithm is superior to the traditional particle swarm optimization algorithm.