Efficiency of Plasma Generation Optimization for Structural Damage Identification of Skeletal Structures Based on a Hybrid Cost Function

In this paper, a newly developed population-based metaheuristic algorithm, namely plasma generation optimization (PGO), is applied to solving the optimization-based damage detection problem. PGO is a physically based optimizer inspired by the process of plasma generation. Excitation, de-excitation, and ionization are the three physical processes occurring in a repeated manner for providing plasma. In the current optimization problem, an efficient hybrid damage-sensitive cost function is developed based on combing two cost functions, modal strain energy and generalized flexibility matrix changes. The structural damage identification problem is formulated as an inverse optimization problem in which the vector of design variables represents damage severity of the structural elements. To verify the efficiency and robustness of the proposed method in detecting the locations and severity of damage precisely, five skeletal structures are investigated numerically. The results of the paper revealed that the proposed method can identify and quantify the damaged elements accurately using only the first few vibrating modes, even for noise-contaminated data.