Kinetics Analysis And Service Life Prediction Of Laying Head Pipe In High-speed Wire Rod Coiling Process

Laying head pipe is a core part in high-speed wire rod production line. In the wire rod process, stress and wear condition between laying head pipe and wire rod is complex. Meantime, service life flexibility of the pipe has a bad effect on practical working. However, most of high-speed wire rod production lines are lacking in core technology about laying head pipe, for instance, the special curve function. Correspondingly, kinetics analysis of coiling process and prediction of the laying head service life are of great application significance.This paper is based on the project Research on Service Life of laying head pipe in High-speed Wire Rod Production Line. In this paper, DEMAG pipe in a new line for large coil wire rod production is taken as the research object. The kinetic characteristic is mainly discussed. Based upon the research on the spinning process technology, boundary condition, and analytical dynamics are set up with analytical mechanics. Integrated theory of motion and stress condition is set up. Calculation method for the branch speeds and stress conditions is given. Point cloud data are obtained with coordinate measuring machine. Spatial model is then set up. Using mathematical method, the function of spatial curve for DEMAG pipe is found out. According to the mathematical models of motion and stress, using Matlab, motion features such as speed, acceleration, force features such as stress and bending moment are simulated. Distribution law and origins of easily-worn areas are found through the analysis of variation in curvature, speed and stress. These findings are consistent with the practical production, announcing the validity of kinetic models. The results of this paper can provide a direction in the research and advancement of laying head pipe, with the reference function for high speed wire rod production.By field test, data of wire motion, specification, rolling temperature and pipe service life are obtained, which are then trained by post optimized BP neural network. Then service life prediction model competent in various condition are set up. This model can serve as a guidance in reasonable use of laying head pipe and scientific schedule of production.