Ant lion optimisation algorithm for structural damage detection using vibration data

Structural damage assessment is crucial for structural health monitoring to evaluate the safety and residual service life of the structure. To solve the structural damage detection problem, various optimisation techniques have been in use. However, they fail to identify damage and are prone to converge to local optima for improper tuning of algorithm-specific parameters, which are problem specific. In this study, the recently proposed ant lion optimiser, which is a population-based search algorithm, mimicked the hunting behaviour of antlions, was used for assessing structural damage. The objective function for damage detection was based on vibration data, such as natural frequencies and mode shapes. The effectiveness of the proposed technique was evaluated against several benchmark problems with different damage settings. The results indicate that the proposed algorithm required fewer parameters than other metaheuristic algorithms to identify the location and extent of damage.