Structural damage identification based on mode shape sensitivity and sparrow search algorithm

In this study, the recently developed Sparrow Search Algorithm (SSA) is integrated with mode shape sensitivity analysis to identify structural damage. The proposed approach is distinctive in two key aspects. Firstly, it utilizes the mode shape sensitivity equation as the objective function and employs SSA within a predefined search interval to initially identify potential damage locations. Secondly, based on the damage localization outcomes, the mode shape sensitivity equation is simplified, and the generalized inverse (GI) method is applied to precisely locate and quantify the damage. The proposed method, referred to as SSA-GI, can effectively avoid computational instability, slow convergence, and large errors that may arise when using other swarm intelligence optimization algorithms. Moreover, the feedback evaluation based on the generalized inverse can mitigate the randomness and lack of rigorous mathematical justification inherent in the SSA algorithm, thereby ensuring the reliability of the damage assessment results. Numerical and experimental examples are employed to validate the proposed SSA-GI method. The results indicate that the SSA-GI method outperforms existing methods such as Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA), demonstrating high identification accuracy.