Rolling stock (2) composed of metal is rolled in rolling stands (3a to 3f) of a roll train (1) under the control of a control device. The control device, on the basis of a variable (δQ) (which is characteristic of the change in the cross section with which the rolling stock (2) is supposed to run out of a rolling stand (3e) of the roll train (1)), first determines all provisional manipulated variables (Sb to Se) for the rolling stand (3e) and rolling stands (3b to 3d) located upstream of the rolling stand (3e), and uses said provisional manipulated variables to determine final manipulated variables (Sb′ to Se′), which influence the cross section with which the rolling stock (2) runs out of the respective rolling stand (3b to 3e). The control device determines the provisional manipulated variables (Sb to Sd) for the upstream rolling stands (3b to 3d) by frequency filtering.

A rolling line for rolling a flat rolling material (2) includes a number of roll stands (1). Prior to the rolling, a control system (3) receives actual variables (I) of the material (2) before the rolling and target variables (Z) after the rolling. The control system (3) determines desired control variables (S*) for the roll stands (1), based on the actual (I) and target variables (Z), in combination with a description (B) of the rolling line, using a model (10) of the rolling line. The control system (3) determines the desired values (S*) such that expected variables (E1) for the material (2) after its rolling are aligned as far as possible with the target variables (Z). The control system (3) transfers the desired values (S*) to the roll stands (1) such that the material (2) is rolled according to the transferred desired values (S*). The target variables (Z) comprise at least one freely selectable, discrete characteristic variable (K1 to K5, K2′ to K4′, K2″ to K4″) defining the contour (K) of the flat rolling material (2).

A rolling line for rolling a flat rolling material (2) includes a number of roll stands (1). Prior to the rolling, a control system (3) receives actual variables (I) of the material (2) before the rolling and target variables (Z) after the rolling. The control system (3) determines desired control variables (S*) for the roll stands (1), based on the actual (I) and target variables (Z), in combination with a description (B) of the rolling line, using a model (10) of the rolling line. The control system (3) determines the desired values (S*) such that expected variables (E1) for the material (2) after its rolling are aligned as far as possible with the target variables (Z). The control system (3) transfers the desired values (S*) to the roll stands (1) such that the material (2) is rolled according to the transferred desired values (S*). The target variables (Z) comprise at least one freely selectable, discrete characteristic variable (K1 to K5, K2′ to K4′, K2″ to K4″) defining the contour (K) of the flat rolling material (2).

The present disclosure provides a strip flatness prediction method considering lateral spread during rolling. The method includes: step 1: acquiring strip parameters, roll parameters and rolling process parameters; step 2: introducing a change factor of a lateral thickness difference before and after rolling and a lateral spread factor by considering lateral metal flow, and constructing a strip flatness prediction model based on the coupling of flatness, crown and lateral spread; step 3: constructing a three-dimensional (3D) finite element model (FEM) of a rolling mill and a strip, simulating strip rolling by the 3D FEM, extracting lateral displacement and thickness data of the strip during a stable rolling stage, calculating parameters of the strip flatness prediction model based on the coupling of flatness, crown and lateral spread; and step 4: predicting the flatness of the strip by the strip flatness prediction model based on the coupling of flatness, crown and lateral spread.

The present disclosure provides a strip flatness prediction method considering lateral spread during rolling. The method includes: step 1: acquiring strip parameters, roll parameters and rolling process parameters; step 2: introducing a change factor of a lateral thickness difference before and after rolling and a lateral spread factor by considering lateral metal flow, and constructing a strip flatness prediction model based on the coupling of flatness, crown and lateral spread; step 3: constructing a three-dimensional (3D) finite element model (FEM) of a rolling mill and a strip, simulating strip rolling by the 3D FEM, extracting lateral displacement and thickness data of the strip during a stable rolling stage, calculating parameters of the strip flatness prediction model based on the coupling of flatness, crown and lateral spread; and step 4: predicting the flatness of the strip by the strip flatness prediction model based on the coupling of flatness, crown and lateral spread.

A rolling mill control system and method includes use of sensors located between rolling mill stands to directly measure metal sheet or plate flatness, thickness profile, position, and the camber of the rolls in the mill. A feedback loop control system adjusts or adapts rolling mill control mechanisms to control the rolling process.

A rolling mill control system and method includes use of sensors located between rolling mill stands to directly measure metal sheet or plate flatness, thickness profile, position, and the camber of the rolls in the mill. A feedback loop control system adjusts or adapts rolling mill control mechanisms to control the rolling process.

A rolling mill control system and method includes use of sensors located between rolling mill stands to directly measure metal sheet or plate flatness, thickness profile, position, and the camber of the rolls in the mill. A feedback loop control system adjusts or adapts rolling mill control mechanisms to control the rolling process.

A rolling mill control system and method includes use of sensors located between rolling mill stands to directly measure metal sheet or plate flatness, thickness profile, position, and the camber of the rolls in the mill. A feedback loop control system adjusts or adapts rolling mill control mechanisms to control the rolling process.

The present invention discloses a method for channel decoupling of a whole-roller flatness meter for a cold-rolled strip. The method includes the following steps: 1, setting a channel number and a channel breadth of the flatness meter; 2, obtaining an influence matrix under the condition of coupled channels; 3, calculating an inverse matrix of the influence matrix; 4, decoupling the channel by the inverse matrix of the influence matrix; and 5, obtaining flatness distribution after channel decoupling. The present invention decouples the channel of the whole-roller flatness meter by inverting the influence matrix and multiplying with the detection force vector. The present invention reproduces the true force vector and flatness distribution, and provides a new method for improving the flatness detection accuracy.