Exploration of Optimisation Algorithms for Predictive Crack Detection in Functional Gradient Beam Structures

This paper presents a study on the application of the Particle Swarm Optimisation (PSO) algorithm to crack detection in beam structures. The objective is to accurately predict the size and location of an open edge crack in functionally graded beams. The modelling method chosen is based on the use of a rotating spring, the stiffness of which is determined by the size of the crack. The PSO algorithm is used as an optimisation technique to solve this problem. The objective function is defined as the weighted sum of the squared errors between the measured and calculated natural frequencies. The PSO algorithm explores the solution space to find the optimal values of crack size and location that minimise the objective function. The results obtained show that the PSO algorithm approach allows accurate prediction of crack size and location. This method offers an effective alternative for solving the crack detection problem, paving the way for potential applications in the field of predictive maintenance of beam structures. In conclusion, the application of the PSO algorithm demonstrates its relevance and effectiveness in solving crack detection problems, offering a promising solution for preserving the integrity of structures and preventing future failures.