Modal data-based approach to structural damage identification by means of imperialist competitive optimization algorithm

In this paper, an eective method for structural damage detection is put forth in which an objective function based on the natural frequencies and modal shapes of the structure is established to identify and detect structural damage. The problem is dened and solved as an optimization problem employing Imperialist Competition Algorithm (ICA). Moreover, four numerical examples are examined each of which has dierent damage scenarios in order that the applicability of the method would be clearly proved. The results show the eciency of the method in detecting single and multiple damages to dierent structures. Afterwards, the eects of measurement noises are included in some of the examples so that the method can be more consistent with real situations. Besides, a comparison among several evolutionary optimization algorithms in the research is made to enlighten the accuracy, robustness and reliability of the method. All of the results lead to the conclusion that the suggested method of the paper is of good accuracy and, therefore, can be both used and trusted in solving damage detection problems, even in the case of measurement noises.