Spread prediction model of continuous steel tube based on BP neural network

2nd International Conference on Design, Materials, and Manufacturing

材料科学;机械制造

Zhai, Jian-Wei^1 ; Yu, Hui^1 ; Zou, Hai-Bei^1 ; Wang, San-Zhong^1 ; Liu, Li-Gang^1

College of Mechanical Engineering, Yanshan University, Qinhuangdao, Hebei

066004, China^1

关键词: Accurate prediction;    BP (back propagation) neural network;    BP neural networks;    Continuous rolling;    Outer diameters;    Prediction model;    Seamless steel tube;    Technological parameters;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/220/1/012012/pdf
DOI  :  10.1088/1757-899X/220/1/012012

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

According to the geometric pass of roll and technological parameters of three-roller continuous mandrel rolling mill in a factory, a finite element model is established to simulate the continuous rolling process of seamless steel tube, and the reliability of finite element model is verified by comparing with the simulation results and actual results of rolling force, wall thickness and outer diameter of the tube. The effect of roller reduction, roller rotation speed and blooming temperature on the spread rule is studied. Based on BP(Back Propagation) neural network technology, a spread prediction model of continuous rolling tube is established for training wall thickness coefficient and spread coefficient of the continuous rolling tube, and the rapid and accurate prediction of continuous rolling tube size is realized.