Structural damage identification using cloud model based fruit fly optimization algorithm

In this paper, a Cloud Model based Fruit Fly Optimization Algorithm (CMFOA) is presented for structural damage identification, which is a global optimization algorithm inspired by the foraging behavior of fruit fly swarm. It is assumed that damage only leads to the decrease in elementary stiffness. The differences on time-domain structural acceleration data are used to construct the objective function, which transforms the damaged identification problem of a structure into an optimization problem. The effectiveness, efficiency and accuracy of the CMFOA are demonstrated by two different numerical simulation structures, including a simply supported beam and a cantilevered plate. Numerical results show that the CMFOA has a better capacity for structural damage identification than the basic Fruit Fly Optimization Algorithm (FOA) and the CMFOA is not sensitive to measurement noise.