تخمين برگشت فنري در شكل دهي غلتكي سرد با استفاده از شبكه هاي عصبي مصنوعي

Using Artificial Neural Networks for Estimation of Spring back in Cold Roll Forming

Cold roll forming is a sheet metal forming process in which the bending occurs gradually in several forming steps from an undeformed strip to a finished profile. Although simple appearance, the process is influenced by several parameters that complicate the process design and control such as spring back. The main purpose in this article is to determine a simple criterion for the spring back and to introduce a fast solution to obtain it and therefore artificial neural network was proposed for achiving this goal. Cold roll forming of a channel section in the first station was simulated by a commercial package named "Msc Marc Mentat". The data obtained from the finite element simulations were used as training and testing sets for neural networks. Perfect performance of neural network was proved when the neural network outputs were compared with the testing set that did not exist in the training set.