Delamination Detection In Composite Laminates Using Dynamic Finite Element Analysis And Neural Networks

A strategy for detecting delamination of composite laminates is proposed in this paper, which is based on dynamic finite element method in conjunction of Neural Networks scheme. Because of the special performance of composite laminates, various forms of damage will appear, this damage will cause the infirmness of the carrying capacity of the structure. Firstly the author introduce some basic theory and some interrelated conclusion of the Neural Networks scheme, summarize several typical structures of Neural Networks and their method of learning and their train and simulation process. Then a dynamic finite element method is developed for the composite laminates with through-width delamination, and the boundary condition of the composite laminates is one side clamped. And the model of damping is describe, which is based on the theory of the dissipated energy. From the typical examination it can be show that the dynamic finite element method in this paper is reliable. According to the discussion of the input parameter, and the analyse of influences of the length and location of delamination upon the natural frequency and natural damping , the stylebook for the training of the Neural Network is founded. At last back propagation (BP) neural network in the Toolbox of MATLAB software is established for training and testing the network. From the simulating results it can be shown that present strategy is efficient for detecting delamination of the composite laminates.