Research of Self-Learning of Plate Deformation Resistance Based on Genetic Algorithm

2010 ◽  
Vol 154-155 ◽  
pp. 260-264
Author(s):  
Chun Yu He ◽  
Zhi Jie Jiao ◽  
Di Wu
Keyword(s):  
Genetic Algorithm ◽  
Rolling Force ◽  
Deformation Resistance ◽  
Learning System ◽  
Model Parameters ◽  
Decision Variable ◽  
Force Model ◽  
Calculation Error ◽  
Force Calculation ◽  
Self Learning

The model parameters value of deformation resistance determines the prediction accuracy of rolling force model during the plate rolling. According to the influencing factors analysis of rolling force calculation error, the genetic algorithm was introduced into the self-learning method of deformation resistance, and searches the optimal value of deformation resistance on the basic of space exploration and optimization ability of genetic algorithm. The decision variable selection, the coding and decoding, the fitness evaluation and the terminal conditions process were implemented during development process of self-learning system. The results show that the optimization speed and accuracy can meet production requirement.

Study of Rolling Force Calculation Models for Cold Rolling Process

2010 ◽  
Vol 154-155 ◽  
pp. 882-885
Author(s):  
Zhi Jie Jiao ◽  
Chun Yu He ◽  
Jian Ping Li ◽  
Xiang Hua Liu
Keyword(s):  
Friction Coefficient ◽  
Cold Rolling ◽  
Rolling Force ◽  
Rolling Process ◽  
Calculation Model ◽  
Deformation Resistance ◽  
Force Model ◽  
Practical Application ◽  
Hill Model ◽  
Force Calculation

For cold rolling process, the theoretical Bland-Ford-Hill model and Hitchcock model are used for the rolling force and roll flatten radius calculation. Friction coefficient and deformation resistance are calculated with empirical regression models. From rolling force model, the recalculation model for the friction coefficient and deformation resistance can be derived. After rolling, with actual measured data, friction coefficient and deformation resistance can be recalculated, and model parameter can be got by regression method. The practical application verifies that the accuracy of rolling force calculation model is good.

scholarly journals An Updated Analytical Structural Pounding Force Model Based on Viscoelasticity of Materials

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Qichao Xue ◽  
Chunwei Zhang ◽  
Jian He ◽  
Guangping Zou ◽  
Jingcai Zhang
Keyword(s):  
Vibration Control ◽  
Viscoelastic Model ◽  
Control Process ◽  
Model Performance ◽  
Analytical Models ◽  
Model Parameters ◽  
Force Model ◽  
Control Analysis ◽  
Proposed Model ◽  
Force Calculation

Based on the summary of existing pounding force analytical models, an updated pounding force analysis method is proposed by introducing viscoelastic constitutive model and contact mechanics method. Traditional Kelvin viscoelastic pounding force model can be expanded to 3-parameter linear viscoelastic model by separating classic pounding model parameters into geometry parameters and viscoelastic material parameters. Two existing pounding examples, the poundings of steel-to-steel and concrete-to-concrete, are recalculated by utilizing the proposed method. Afterwards, the calculation results are compared with other pounding force models. The results show certain accuracy in proposed model. The relative normalized errors of steel-to-steel and concrete-to-concrete experiments are 19.8% and 12.5%, respectively. Furthermore, a steel-to-polymer pounding example is calculated, and the application of the proposed method in vibration control analysis for pounding tuned mass damper (TMD) is simulated consequently. However, due to insufficient experiment details, the proposed model can only give a rough trend for both single pounding process and vibration control process. Regardless of the cheerful prospect, the study in this paper is only the first step of pounding force calculation. It still needs a more careful assessment of the model performance, especially in the presence of inelastic response.

Research and Improvement on the Rolling Force Model of Plate

2010 ◽  
Vol 97-101 ◽  
pp. 3091-3096 ◽  
Author(s):  
Jun Wang ◽  
Chun Li Jia ◽  
Zhong Zhao ◽  
Zhi Jie Jiao ◽  
Jian Ping Wang
Keyword(s):  
Rolling Force ◽  
Rolling Process ◽  
The Self ◽  
Force Model ◽  
Physical Conditions ◽  
The Core ◽  
Predictive Error ◽  
On Line ◽  
Self Learning ◽  
Thickness Layer

Rolling force model is the core of all the mathematical models of plate for rolling process, but the accuracy of traditional rolling force model is not high enough in application, so in this study the rolling force model of plate is researched and improved. The effects of different physical conditions on resistance of deformation are decoupled, and the formula acquired is practical. While the composition, Nb is used to calculate residual strain. At the same time, the self-learning method, which is based on the thickness layer is applied. The on-line application results show that the predictive error between force model calculated and measured can be controlled at less than 9% and 80% of the passes can be controlled within 5%.

scholarly journals Modelling of Deformation Resistance with Big Data and Its Application in the Prediction of Rolling Force of Thick Plate

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Shun Hu Zhang ◽  
Li Zhi Che ◽  
Xin Ying Liu
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Bp Neural Network ◽  
Prediction Accuracy ◽  
Rolling Force ◽  
Deformation Resistance ◽  
Force Model ◽  
The Neural Network ◽  
Bp Neural Network Model

The precision of traditional deformation resistance model is limited, which leads to the inaccuracy of the existing rolling force model. In this paper, the back propagation (BP) neural network model was established according to the industrial big data to accurately predict the deformation resistance. Then, a new rolling force model was established by using the BP neural network model. During the establishment of the neural network model, the data set of deformation resistance was established, which was calculated back from the actual rolling force data. Based on the data set after normalization, the BP neural network model of deformation resistance was established through the optimization of algorithm and network structure. It is shown that both the prediction accuracy of the neural network model on the training set and the test set are high, indicating that the generalization ability of the model is strong. The neural network model of the deformation resistance is compared with the theoretical one, and the maximum error is only 3.96%. Furthermore, by comparison with the traditional rolling force model, it is found that the prediction accuracy of the rolling force model imbedding with the present neural network model is improved obviously. The maximum error of the present rolling force model is just 3.86%. The research in this paper provides a new way to improve the prediction accuracy of rolling force model.

Three-directional contact force model for the ball spinning of a thin-walled tube

2018 ◽  
Vol 233 (3) ◽  
pp. 500-507
Author(s):  
Chun-jiang Zhao ◽  
Meng-ying Su ◽  
Zheng-yi Jiang ◽  
Jiang Lian-yun ◽  
Xiaorong Yang ◽  
...  
Keyword(s):  
Frictional Heating ◽  
Contact Boundary ◽  
Force Model ◽  
Calculation Error ◽  
Coordinate Plane ◽  
Thin Walled Tube ◽  
Ball Spinning ◽  
Thin Walled ◽  
Force Calculation ◽  
Spinning Force

This paper provides a computational model for calculating three-directional ball spinning force in accordance with the theory of space analytic geometry. The contact boundary equation of the ball and tube is obtained. By projection, the two-dimensional curve in each coordinate plane is acquired. The projected area of the contact zone in the coordinate plane is calculated through the curve integral. It is assumed that the average pressure of the forming region is nearly equal to that when the steel ball is pressed into the tube. Hence, the unit pressure of the deformation zone is obtained. Then, the spinning component force and total spinning force are calculated. Using a Tu1 thin-walled tube of oxygen-free copper as experimental object, a ball spinning experiment is conducted, the axial spinning components force are tested and the ball spinning force calculation model is verified. Based on deformation rate, backward sliding accumulation and extension and frictional heating, the factors influencing calculation error are analysed at the end of this paper.

Research on Finishing Rolling Force Model for Hot Rolling Wide and Heavy Stainless Steel Clad Sheets

2014 ◽  
Vol 488-489 ◽  
pp. 213-216 ◽  
Author(s):  
Jin He Rong ◽  
Xiao Hong ◽  
Geng Yong Xiang ◽  
Jiang Jin Shui
Keyword(s):  
Stainless Steel ◽  
Relative Error ◽  
Hot Rolling ◽  
Rolling Force ◽  
Rolling Stock ◽  
Force Model ◽  
Mechanical Coupling ◽  
Hot Rolled ◽  
Force Calculation ◽  
Unit Pressure

In order to effectively improve the calculation accuracy of finishing rolling force model for hot rolling wide and heavy stainless steel clad sheets, based on the E.Orowan unit pressure equilibrium differential equations and R.B.Sims unit pressure formulas, this paper divides hot-rolled composite deformation area into I, II two zones according to rolling stock jamming experiment, and then derives the finishing rolling force calculation formulas. Finally, by ANSYS/LS-DYNA thermal mechanical coupling simulation and experiment, the results show that compared with measured values, the relative error of simulated values is about 20%, the relative error of calculated values is less than 10%. Therefore, the rolling force model can accurately predict the size of rolling force and effectively improve the calculation accuracy of rolling force.

Rolling Force Calculation for Strip Cold Rolling Based on Influence Function Method

2014 ◽  
Vol 633-634 ◽  
pp. 791-794 ◽  
Author(s):  
Hai Zhou ◽  
Jin Lan Bai
Keyword(s):  
Cold Rolling ◽  
Influence Function ◽  
Function Method ◽  
Rolling Force ◽  
Force Model ◽  
Strip Rolling ◽  
Influence Function Method ◽  
Roll Flattening ◽  
Calculation Results ◽  
Force Calculation

The rolling force calculation procedure of strip cold rolling is developed based on influence function method, with consideration of the couple of roll flattening model and rolling force model. With the procedure total rolling force and the distribution of rolling force per width of each pass for HC mill are calculated using sampling data obtained from actual strip rolling. Comparing the calculation results with actual measured value, it is shown that the calculated total rolling forces are similar to actual data, and the distribution of rolling force per width is consistent with the actual status. It proved that the calculation method introduced in this paper is an effective method to calculate rolling force, and it can be used in the process control of strip cold rolling mill.

Precise Rolling Force Calculation for the Tandem Cold Mill

2007 ◽  
Vol 561-565 ◽  
pp. 1883-1886
Author(s):  
Zhi Jie Jiao ◽  
Hao Zhang ◽  
Jing Wang ◽  
Chui Hong Liu ◽  
Xiang Hua Liu
Keyword(s):  
Rolling Force ◽  
Steel Grade ◽  
Rolling Speed ◽  
Force Model ◽  
Technical Parameter ◽  
Calculation Process ◽  
Tandem Cold Mill ◽  
Force Calculation ◽  
Online Process ◽  
Cold Mill

Rolling force is the most important technical parameter for the tandem cold mill. In this paper, the precise models and calculation process for the rolling force are introduced. The rolling force model is based on the Bland-Ford and Hill theory, and the roll flatten radius is calculated with the Hitchcok’s formula. The deformation resistance of the strip is calculated with the model, whose parameters are decided according to the steel grade. The friction coefficient model is built according to rolling speed and rolled length of the roll. The rolling force and the roll flatten radius are calculated with the iterative method. These models are used for online process control of one five-stand tandem cold mill. Comparing the calculation result and the actual data, the precision of the rolling force calculation is high.

The Optimization of Roll Force Model in Hot Strip Mill

2014 ◽  
Vol 926-930 ◽  
pp. 3705-3708
Author(s):  
Geng Sheng Ma ◽  
Fang Chen Yin ◽  
Zhu Wen Yan ◽  
He Nan Bu ◽  
Wen Peng ◽  
...  
Keyword(s):  
Prediction Accuracy ◽  
Rolling Force ◽  
Strip Thickness ◽  
Deformation Resistance ◽  
Hot Strip Mill ◽  
Force Model ◽  
Roll Force ◽  
Adaptive Model ◽  
Hot Strip ◽  
High Prediction

The accuracy of roll force model and the rationality of roll fore adaptive model play a key role in obtaining the thickness of strip with high precision. The roll force model has been established. It includes the elastic flattened roller model and deformation resistance model considering the chemical composition of strip. A deformation resistance-based fitting curve is proposed in rolling force adaption, it can be inherited to any other thick range class. Application results show that the rolling force model and its adaptation are with high prediction accuracy and it has improved the strip thickness accuracy.

A Flatness Control System Design Based on Actuator Efficiency Factors for Cold Rolling Mill

2010 ◽  
Vol 139-141 ◽  
pp. 1889-1893 ◽  
Author(s):  
Peng Fei Wang ◽  
Dian Hua Zhang ◽  
Xu Li ◽  
Jia Wei Liu
Keyword(s):  
Control System ◽  
Rolling Force ◽  
Quantitative Description ◽  
Learning Model ◽  
Feed Forward Control ◽  
Flatness Control ◽  
Stand Type ◽  
Loop Feedback ◽  
Efficiency Factors ◽  
Self Learning

In order to improve the flatness of cold rolled strips, strategies of closed loop feedback flatness control and rolling force feed forward control were established respectively, based on actuator efficiency factors. As the basis of flatness control system, efficiencies of flatness actuators provide a quantitative description to the law of flatness control. For the purpose of obtaining accurate efficiency factors matrixes of actuators, a self-learning model of actuator efficiency factors was established. The precision of actuator efficiency factors could be improved continuously by correlative measurement flatness data inputs. Meanwhile, the self-learning model of actuator efficiency factors permits the application of this flatness control for all possible types of actuators and every stand type. The developed flatness control system has been applied to a 1250mm single stand 6-H reversible UCM cold mill. Applications show that the flatness control system based on actuator efficiency factors is capable to obtain good flatness.

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