damage identification in truss structures using a hybrid pso-hho algorithm with selective natural frequencies and mode shape

Structural damage can be detected non-destructively by comparing the dynamic characteristics of a structure before and after a major event. optimization techniques are effective tools for damage identification using structural dynamic properties, as the problem is formulated and solved inversely. to achieve this, the damage levels in each element are treated as decision variables. the objective is to fine-tune these variables so that the model's response closely aligns with the experimentally observed dynamic characteristics of the damaged structure. this study proposes a hybrid particle swarm optimization- harris hawks optimization algorithm for damage detection in truss structures based on dynamic structural responses. to evaluate the effectiveness of the proposed method, a 15-element planar truss is considered as a numerical example. the results highlight the importance of incorporating modal parameters to accurately identify the damage scenario. the results demonstrate that the hybrid algorithm significantly outperforms the individual algorithms in accurately detecting structural damage.