## 1 Introduction
[8] proposed a damage identification method based on a hybrid adaptive firefly algorithm and verified the validity of the proposed method using a two-story rigid frame structure and beam model, but the results showed that the performance improvement of this algorithm was not obvious compared with other algorithms. [PERSON] et al. [9] embedded the Nelder-Mead algorithm into a particle swarm algorithm to obtain a hybrid particle swarm algorithm and used it for damage identification, and they verified the effectiveness and superiority of the method through the numerical simulation of simply supported beams as well as experiments on rectangular cross-section steel beams; however, because PSO required a lot of calculations, the calculation time was greatly extended. [PERSON], [PERSON] et al. [10] proposed an optimization algorithm based on sunflower motion and successfully identified damage in composite laminates by this algorithm. It tracks the sun's movement patterns and fertilization strategies by simulating sunflowers. The algorithm performed the global search by updating the position and limiting the maximum stride length. The results show that SFO had good accuracy and calculation speed performance in damage identification. [PERSON], [PERSON] et al. [11] proposed a damage identification method based on the social swarm algorithm, modal strain energy, and modal vibrational curvature and verified the effectiveness of the method by a numerical simulation without noise analysis or a performance evaluation. [PERSON], [PERSON] et al. [12] proposed a damage identification method based on the modal frequency strain energy assurance criterion, modal flexibility, and enhanced moth flame optimization algorithm and verified the effectiveness of the method using simply supported beams and triple-shear frame experiments, which showed that this method had good performance in simplicity and convergence speed, although the global search ability was not outstanding, and there was a lack of suitable reference comparisons. [PERSON], [PERSON] et al. [13] proposed an augmented particle swarm algorithm for solving the damage identification problem and successfully applied the method to the damage identification of power transmission towers; however, the structure of transmission towers has its particularity, so the universality of this method had not been verified. [PERSON], [PERSON] et al. [14] proposed a multi-component particle swarm algorithm with cooperative learning for damage identification, which fuses four particle swarm algorithm variants to build a pool of strategies, and the numerical simulation results show that the algorithm possesses higher accuracy in damage identification compared with a single variant and other algorithms; however, it comes at the cost of a huge increase in computing time. [PERSON], [PERSON] et al. [15] proposed a hybrid K-clustering mean optimization algorithm and used it for the identification of damage in small experimental dams, and the results show that this algorithm has high accuracy and computational efficiency for the identification of large and complex structures. [PERSON], [PERSON] et al. [16] proposed the Goby joint search algorithm and used it for damage identification in Guangzhou Tower; the results show that this algorithm has higher damage identification accuracy compared with GAs, genetic particle swarm hybrid algorithms and others. [PERSON], [PERSON] et al. [17] proposed a damage identification method based on a hybrid YUKI-ANN algorithm with a modal strain energy change ratio and successfully applied it for damage identification in plywood, but there was no systematic evaluation of this method. In previous research, the application of INFO [18] in damage identification has been relatively rare. The INFO algorithm is an efficient optimization tool that effectively explores the solution space and quickly converges to the global optimum through a weighted average method, while also having an improved mechanism to enhance its search capabilities and accuracy.