Multiple damage detection in unidirectional graphite-epoxy composite beams using particle swarm optimization and genetic algorithm

This paper presents a methodology for damage detection and localization in composite beams using vibration data, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The data was acquired by developing a program that performs dynamic analysis of unidirectional graphite-epoxy composite beams based on the Finite Element Method (FEM). The objective function makes use of natural frequencies and Modal Assurance Criterion. The proposed methodology is validated using numerically simulated data and experimental data. A comparative study between the performances of PSO and GA in detecting multiple and single damage scenariosis carried out. Then, the effect of noise is investigated by taking different noise levels in the modal data. It appears that the noise has a negligible effect on the performance of the presented approaches.