Bayesian Neural Network of Rolling Force Prediction for Hot-Strip Mill

2014 ◽  
Vol 12 (5) ◽  
Author(s):  
Xiaodan Zhang ◽  
Rui LI ◽  
Yanliang YE
Keyword(s):  
Neural Network ◽  
Rolling Force ◽  
Hot Strip Mill ◽  
Bayesian Neural Network ◽  
Force Prediction ◽  
Hot Strip

A 3-D Differential Method for Solving Rolling Force of PC Hot Strip Mill

2010 ◽  
Vol 17 (9) ◽  
pp. 36-39 ◽  
Author(s):  
Xue-song Wang ◽  
Yan Peng ◽  
Li-pu Xu ◽  
Hong-min Liu
Keyword(s):  
Rolling Force ◽  
Differential Method ◽  
Hot Strip Mill ◽  
Hot Strip

Research on Online Model of Vertical Rolling Force in Hot Strip Roughing Trains

2010 ◽  
Vol 145 ◽  
pp. 198-203 ◽  
Author(s):  
Guo Ming Yuan ◽  
Jian Wang ◽  
Hong Xiao ◽  
Ming Lei Li
Keyword(s):  
Rolling Force ◽  
Fem Simulation ◽  
Simulation Software ◽  
External Stress ◽  
New Method ◽  
Hot Strip Mill ◽  
Deformation Degree ◽  
Hot Strip ◽  
New Formula ◽  
Force Calculation

For low prediction precision of online model for vertical rolling force in roughing trains of hot strip mill, the process of hot strip roughing trains was simulated by the FEM simulation software DEFORM. The cause of low prediction precision of rolling force during vertical rolling was analyzed. Then the new method for calculating deformation degree when edge rolling was presented by analysis of the FEM simulated results. The formula of external stress status modulus, which is fit for the vertical rolling force calculation, was obtained by analytic regression. Furthermore, a new formula about rolling force calculation was gained. It was approved that the prediction precision was obviously enhanced compared with the practical data for vertical rolling force.

Rolling Force Prediction Method Based on Fuzzy Identification

2012 ◽  
Vol 229-231 ◽  
pp. 365-368
Author(s):  
Zhi Yong Wang ◽  
Yi Geng Li
Keyword(s):  
Least Squares Method ◽  
Rolling Force ◽  
Fuzzy Model ◽  
Recursive Least Squares ◽  
Rolled Strip ◽  
Hot Strip Mill ◽  
Load Prediction ◽  
Strip Rolling ◽  
Fuzzy Identification ◽  
Force Prediction

To improve the precision and efficiency of rolling force prediction on hot rolled strip, a new rolling load prediction of finishing stands method was set up by fuzzy identification. It was based on T-S fuzzy model using clustering subjection functions to calculate the grade of membership for each given pattern, and using recursive least squares method to identify the consequent parameters of fuzzy model. On the basis of the measured data of the 1580 mm, the relation between the main hot strip mill parameters and rolling force was established using fuzzy model. Experimental results show that the prediction precision is higher, responds quickly and steady. The method can satisfy on line control requirements in a hot mill strip rolling process.

Applying Deformation Resistance Estimation Method to Predict Nine Stand Hot Strip Mill Rolling Force

2012 ◽  
Vol 472-475 ◽  
pp. 451-455
Author(s):  
Yan Bing He ◽  
Yu Hua Pang ◽  
Jin Zhi Zhang ◽  
Li Peng Zhu
Keyword(s):  
High Speed ◽  
Rolling Force ◽  
Estimation Method ◽  
Deformation Resistance ◽  
Forecasting Model ◽  
Hot Strip Mill ◽  
Continuous Rolling ◽  
Hot Strip ◽  
Hot Continuous Rolling ◽  
Rolling Production

The rolling force of the nine stand hot continuous rolling production line is predicted on the base of the deformation resistance estimation method. The predicted error is turned out to be about 10% through the comparing analysis of the predicted rolling force and actual rolling force, which proves the feasibility of the forecasting model. One can get the deformation resistance without experiments by using this method, besides, this method works in a high speed.

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