Crack Identification in Functionally Graded Beams Using Particle Swarm Optimization Algorithm and Artificial Neural Network

In the first part of this paper, a cantilever beam is modeled using Finite Element Method (FEM) and its natural frequencies are obtained for different conditions of cracks. Then two Multi-Layer Feed Forward (MLFF) Artificial Neural Networks (ANNs) are designed for prediction of FGB's Cracks' location and depth. Particle Swarm Optimization (PSO) and Back-Error Propagation (BEP) algorithms are applied for training ANNs. The accuracy of two training methods’ results is investigated.

کلیدواژه ها:

Crack ، Functionally graded beam ، A neural network ، Particle swarm optimization