Structural model updating and damage detection based on artificial fish swarm algorithm
LI Cheng1,2,YU Ling1,2,3
1. College of Civil and Architectural Engineering, China Three Gorges University, Yichang 443002, China;2. MOE Key Lab of Disaster Forecast and Control in Engineering, Jinan University, Guangzhou 510632, China;3. Department of Mechanics and Civil Engineering, Jinan University, Guangzhou 510632, China
An artificial fish swarm algorithm (AFSA) based novel method is proposed for structural model updating and damage detection, which is often converted into a constrained optimization problem in mathematics and is hopefully solved by the AFSA proposed in this paper. The basic principle of AFSA is introduced, some key parameters defined and four fish swarm behaviors simulated simultaneously, including searching, swarm, chasing and random behaviors. An objective function is defined as minimizing the discrepancies between the experimental and analytical modal parameters (namely natural frequencies and mode shapes). One numerical two-story portal frame structure and one laboratory-tested three-story steel frame structure are both adopted to evaluate the efficiency of the proposed method. Some illustrated results show that the proposed AFSA based method can effectively update finite element models, locate damaged elements of structures and identify extents of structural damages under different noise levels and all the damage cases.
李 成;余 岭;. 基于人工鱼群算法的结构模型修正与损伤检测[J]. , 2014, 33(2): 112-116.
LI Cheng;YU Ling;. Structural model updating and damage detection based on artificial fish swarm algorithm. , 2014, 33(2): 112-116.