a b s t r a c tAn efficient optimization procedure is proposed to detect multiple damage in structural systems. Natural frequency changes of a structure are considered as a criterion for damage presence. In order to evaluate the required natural frequencies, a finite element analysis (FEA) is utilized. A modified genetic algorithm (MGA) with two new operators (health and simulator operators) is presented to accurately detect the locations and extent of the eventual damage. An efficient correlation-based index (ECBI) as the objective function for the optimization algorithm is also introduced. The numerical results of two benchmark examples considering the measurement noise demonstrate the computational advantages of the proposed method to precisely determine the sites and the extent of multiple structural damage.
An efficient method employing the differential evolution algorithm (DEA) as an optimisation solver is presented here to identify the multiple damage cases of structural systems. Natural frequency changes of a structure are considered as a criterion for damage occurrence. The structural damage detection problem is first transformed into a standard optimisation problem dealing with continuous variables, and then the DEA is utilised to solve the optimisation problem for finding the site and extent of structural damage. In order to assess the performance of the proposed method for structural damage identification, some illustrative examples are numerically tested, considering also measurement noise. All the numerical results demonstrate the effectiveness of the proposed method for accurately determining the site and extent of multiple-structural damage. Also, the performance of the DEA for damage detection compared to the standard particle swarm optimisation is confirmed by a test example.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.