Application of generalized flexibility matrix in damage identification using Imperialist Competitive Algorithm

In this article, a new objective function which is formed by using generalized flexibility matrix is presented with the aim of solving the constrained optimization problem in damage detection procedure. The main purpose is to decrease the effects of truncation error which ensue from cutting off the higher order modes. Two different case studies are used to evaluate the proposed approach. These cases include, a 2D-frame and a Howe-Truss structure. In this study, each structure is modeled by finite element method and damages are induced by considering a reduction in the stiffness of the elements. Finally, the inverse problem of damage identification is solved by using the Imperialist Competitive Algorithm (ICA) for each damage scenario. Not only the effect of noise on the obtained results is studied but also a comparison is drawn between the proposed method based on ICA and other conventional optimization algorithms, namely PSO and GA.