Improved Genetic Simulated Annealing Algorithm And Its Application In The Damage Identification Of Structure

Due to the coupling effect of environmental erosion, material aging and fatigueeffect of alternating load, the civil engineering structure will be damaged inevitablyin the using process of decades or even hundreds of years. When the damageaccumulated to a certain degree, the resistance of the structure will decay. At the sametime, it will reduce the reliability and securities of the structure even destroy thewhole building and cause catastrophic accidents. Therefore, structural health monitoringhas become an important research direction of civil engineering. It has a greatsignificance to find damage and take corresponding preventive timely. Structuraldamage identification is the core content of structural heath monitoring. Currently，it hasbecome a hot topic that using intelligent algorithms to identify the damage of structure.And it also has achieved good results. So the improved genetic simulated annealingalgorithm is adopted to identify the damage of structure in this paper.Genetic algorithm has an excellent ability to grasp the overall search process, butits local search ability is weak and the convergence speed is slow. Simulated annealingalgorithm has a better effect of the local optimization. The paper formed a kind of moreexcellent performance of the improved genetic simulated annealing algorithm throughthe combination of the two algorithms and improving each other. The improvedalgorithm has good global search ability and local search ability. And its convergencespeed was improved obviously.Structural damage identification consists of two parts-damage location and therecognition of damage degree. In the paper, the finite element method was used to getthe structural overall mass matrix, intact and damaged overall stiffness matrix anddamaged frequency and vibration mode. Using these parameters, the residual forcevector method was adopted to locate the damage of frame structure. Then, the reducingfactors of elements stiffness were used as the optimization variables and the nodalresidual forces were used to construct the optimization object function. Thequantification of the truss and frame structural damage were performed with improvedGenetic-Stimulated Annealing algorithm. Comparing with other recognition methods,the results show that the effectiveness of the proposed method is verified. Simulatedactual situation, the paper also identified the structural damage in the noise circumstances. The results show that the algorithm has a certain resistance to noise andgood practical value.