Assessing the performance of a differential evolution algorithm in structural damage detection by varying the objective function

Structural damage detection has become an important research topic in certain segments of the engineering community. These methodologies occasionally formulate an optimization problem by defining an objective function based on dynamic parameters, with metaheuristics used to find the solution. In this study, damage localization and quantification is performed by an Adaptive Differential Evolution algorithm, which solves the associated optimization problem. Furthermore, this paper looks at the proposed methodology’s performance when using different functions based on natural frequencies, mode shapes, modal flexibilities, modal strain energies and the residual force vector. Simple and multiple damage scenarios are numerically imposed on truss structures to assess the performance of the proposed methodology. Results show that damage scenarios can be reliably determined by using the analyzed objective functions. However, the methodology does not perform well when the objective function based on natural frequencies and modal strain energies is employed.