Journal of Xi'an Jiaotong Universtity

Two-Stage Structural Damage Detection Method with Genetic Algorithms
Guo Huiyong¹, Zhang Ling¹, Jiang Jian²
(1ª±School of Architectural Engineering and Mechanics, Xi'an Jiaotong University, Xi'an 710049, China; 2. Nanjing Underground
Engineering Architecture Design Institute, Nanjing 210008, China)

Abstract: To efficiently identify structural damage, a two-stage damage detection method with genetic algorithm is presented. The frequency multiple damage location assurance criterion (MDLAC) method and mode shape MDLAC method are applied to obtain original decisions, respectively, and the evidence theory is employed to integrate both frequency identification information and mode shape identification information, which is more accurate than MDLAC methods, thus the damage sites are preliminarily localized according to the combined information. The improved genetic algorithm is finally applied to detect damage extents. The simulation results demonstrate that the evidence theory approach containing both frequencies and mode shapes can more successfully identify multiple damage sites or determine the group of potential damage sites than MDLAC methods, and the improved genetic algorithm can perfectly detect damage extents.
Keywords: genetic algorithm; damage detection; evidence theory; fusion identification