Prediction the Limiting Drawing Ratio in Deep Drawing Process by Back Propagation Artificial Neural Network

نویسندگان

  • H. Mohammadi Majd
  • M. Jalali Azizpour
  • M. Goodarzi
چکیده

In this paper back-propagation artificial neural network (BPANN) with Levenberg–Marquardt algorithm is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found. Keywords—BPANN, deep drawing, prediction, limiting drawing ratio (LDR), Levenberg–Marquardt algorithm

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تاریخ انتشار 2013