Combined Data with Particle Swarm Optimization for Structural Damage Detection

الملخص EN

This paper proposes a damage detection method based on combined data of static and modal tests using particle swarm optimization (PSO).

To improve the performance of PSO, some immune properties such as selection, receptor editing, and vaccination are introduced into the basic PSO and an improved PSO algorithm is formed.

Simulations on three benchmark functions show that the new algorithm performs better than PSO.

The efficiency of the proposed damage detection method is tested on a clamped beam, and the results demonstrate that it is more efficient than PSO, differential evolution, and an adaptive real-parameter simulated annealing genetic algorithm.