Abstract: The temper rolling process of thin gauge strip has the features of thin thickness and small reduction, thus it is difficult to calculate its temper rolling force and get a highprecision value. Aiming to solve this problem, this paper established a mathematical model to calculate its temper rolling force based on parameters modification. Meanwhile, the paper predicted the calculation error of the mathematical model above by using RBF neural networks in order to improve its precision further, and completed the modification for temper rolling force model by combining the calculation error and calculated values of original mathematical model. The offline simulation indicates that the precision of new model of temper rolling force for thin gauge strip can reaches 6% after twice modification by its modified parameters and RBF neural networks, which makes it have high value of application in real project.

Key words:  prediction of temper rolling force, thin gauge strip, radial basis function(RBF) neural networks, parameters modification