Mechanical Property Prediction Of Hot-Rolled Strip Produced By CSP Technology Base On Artificial Neural Network

The Artificial neural network (ANN) model possesses with good fault tolerance, self- adapted and non-linear mapping, especially it is suitable to resolve complex causal relation non-question and so on determinism inference, judgment, recognition and classification. The ANN has the unique superiority of gaining mathematical model aspect from the empirical datum through automatic studying, it does not need the people to assign the form of formula in advance, but it takes the empirical datum as the foundation, and obtain the mathematical model which reflects empirical datum inherent laws after finite iterative computing. The ANN is especially suitable to process the questions with ambiguity rule , many composition and parameters . Therefore, we can use the ANN actualizing direct mapping between the chemical composition and rolling parameters of hot-tolled strip with the mechanical property, then achieve a better prediction of mechanical property of hot–rolled strip.The theory basis and modeling method of the ANN is investigated in this paper. On the base of chemical composition and rolling parameters of hot-rolled Q345B produced by CSP technology in LY Steel, the paper has established the mechanical property prediction model through BP neural network. This model is typical three layers network , namely the input layer, the hidden layer and the output layer. The input layer has 11 neurons, including the content of C, Si, Mn, P, S, Al, Ca and the F1 mill input velocity, the finishing end temperature, the coiling temperature and fished strip thickness. The output layer has 3 neurons, including yield strength, tensile strength and elongation . The prediction result after training of the ANN which compares the data through field surveying indicates that the BP neural network has good precision in mechanical property prediction and is suitable to extend. At the same time, we can investigate between the chemical composition and rolling parameters with the mechanical property and discover laws easily, which provides the important instruction significance and the reference value for the on-line prediction of mechanical property of finished strip and the optimization and the adjustment of product rolling.