IDENTIFICATION OF GEOMETRIC PARAMETERS OF DRAWBEAD USING NEURAL NETWORKS
In this paper, a neural network (NN) model was designated to identify the geometric parameters of drawbead in sheet forming processes. The genetic algorithm (GA) was used to determine the neuron numbers of the hidden layers of the neural network, and a sample design method with the strategy of updating training samples was also used for the convergence. The NN model goes through a progressive retraining process and the numerical study shows that this technique can give a good result of the parameter identification of drawbead.
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- 1.H.D. Nine (1982), New drawbead concepts for sheet metal forming. Journal of Applied Metalworking, 2, 3, pp. 185–192.Google Scholar
- 2.N.M. Wang (1982), A mathematical model of drawbead forces in sheet metal forming. Journal of Applied Metalworking, 2, 3, pp. 193–199.Google Scholar
- 10.A.B. Haykin (1994), Neural Networks: Comprehensive Fundamentals. Van Nostrand Reinhold, New York.Google Scholar