Enhancing Salp Swarm Optimization with Orthogonal Diagonalization Transformation for Damage Detection in Truss Bridge

다국어 초록 (Multilingual Abstract)

This paper proposes a novel approach for structural damage identification using the Salp Swarm Algorithm (SSA) combined with Orthogonal Diagonalization (OD). SSA is an optimization algorithm developed in recent years and has been considered for addressing complex and computationally expensive engineering problems. However, due to the utilization of only the leader salp to search for optimal solutions, there is an imbalance between the exploitation and exploration capabilities of the salp swarm. To address this issue, we suggest the use of OD to enhance the search capability of the leader salp. OD plays a crucial role in reducing the search space and selecting high-quality salp elements in subsequent iterations. From that idea, the algorithm is tested with 12 benchmark functions, and the results demonstrate superior convergence for all of these compared to the algorithm without OD. A comprehensive study with various damage scenarios is also conducted with the Cua Rao bridge. The outcomes indicate that the accuracy, with a deviation rate when using OD, is only 1.412%, whereas it is 2.224% for the SSA in the case of a single damage scenario. As the number of damaged elements increases, the error of SSA rises to 99.667% when identifying damaged elements, while errors using OD remain below 10%. Additionally, the computational speed is significantly enhanced by approximately 40% in both scenarios.