Method for collaborative optimization of flatness control and thickness accuracy during cold rolling

Abstract

The application provides a strip shape control and strip thickness precision cooperative optimization method in a cold rolling process, relates to the field of cold rolling machine control technology, and comprises the following steps: collecting the contact parameters between the working roll and the support roll in the rolling process, determining the contact stress distribution state, and obtaining the bending deformation amount of the working roll; constructing a coupling mapping relationship between the strip shape distribution and the stress distribution; adaptively adjusting the compensation coefficient according to the rolling state, establishing a dynamic cooperative optimization objective function; and calculating the working roll bending force and the support roll displacement amount that meet the objective, and adjusting the rolling parameters in real time. The application realizes the cooperative control of the strip shape and the strip thickness, and improves the quality of the cold-rolled products.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of cold rolling mill control technology, and particularly relates to a method for optimizing the cooperation between plate shape control and plate thickness precision in the rolling process of a cold rolling mill. BACKGROUND

[0002] In the steel production process, the cold rolling process is a key link in the production of strip steel, and the plate shape quality and plate thickness precision directly affect the use performance of the final product. In the rolling process of a cold rolling mill, uneven contact stress distribution exists between the work roll and the backup roll, which causes the work roll to produce bending deformation, thereby affecting the plate shape and plate thickness precision of the strip steel. The traditional plate shape control technology mainly controls the transverse thickness distribution of the strip steel by adjusting the bending force of the rolling work roll and the displacement of the backup roll, so as to improve the plate shape quality.

[0003] The traditional plate shape control and plate thickness control are usually designed and implemented as two independent systems, ignoring the coupling relationship between them, which leads to a decrease in plate thickness precision while optimizing the plate shape, or a deterioration of plate shape quality while controlling the plate thickness, making it difficult to achieve the cooperative optimization of plate shape and plate thickness. The existing control method fails to fully consider the influence of the contact geometric characteristics and the lubricating oil film thickness distribution between the work roll and the backup roll on the bending deformation of the work roll, resulting in low precision of the established rolling model and affecting the accuracy and stability of the plate shape control. The existing control strategy is mostly static control or simple feedback control, lacking adaptive adjustment capability for different states in the rolling process, and being unable to effectively respond to dynamic changes and disturbances in the rolling process, making it difficult to meet the requirements of high-precision rolling products for the cooperative control of plate shape and plate thickness. SUMMARY

[0004] The embodiment of the present application provides a method for optimizing the cooperation between plate shape control and plate thickness precision in the rolling process of a cold rolling mill, which can solve the problems in the prior art.

[0005] In a first aspect, the embodiment of the present application provides a method for optimizing the cooperation between plate shape control and plate thickness precision in the rolling process of a cold rolling mill, comprising:

[0006] Collecting the contact geometric parameters and the lubricating oil film thickness data between the rolling work roll and the backup roll, determining the contact stress distribution state between the rolling work roll and the backup roll, and obtaining the bending deformation amount of the rolling work roll at different positions by combining the beam bending deformation equation;

[0007] According to the bending deformation amount of the rolling work roll, combining the plate shape detection data and the plate thickness detection data of the strip steel, and constructing the coupling mapping relationship between the plate shape distribution and the stress distribution considering the deformation of the rolling work roll;

[0008] According to the state judgment result of the strip steel rolling process, the compensation coefficient corresponding to the coupling mapping relationship is adaptively adjusted, a dynamic cooperative optimization objective function of flatness and thickness is established, and a rolling work roll bending force and a support roll displacement are obtained through iterative calculation to meet the dynamic cooperative optimization objective function; flatness and thickness data of each section of the rolling process are input into a fuzzy rule base to obtain initial control parameters, coupling influence coefficients are calculated by collecting state parameters of each section of the roll system, an adaptive cooperative function is constructed, and the rolling work roll bending force and the support roll displacement are corrected;

[0009] According to the rolling work roll bending force and the support roll displacement, the rolling parameters of the cold rolling mill are adjusted in real time to realize the cooperative control of the flatness and thickness of the strip steel.

[0010] The contact geometric parameters and the lubricating oil film thickness data between the rolling work roll and the support roll are collected, the contact stress distribution state between the rolling work roll and the support roll is determined, and the bending deformation amount of the rolling work roll at different positions is obtained by combining the beam bending deformation equation, including:

[0011] The contact geometric parameters and the lubricating oil film thickness data between the rolling work roll and the support roll are collected, and the unit width load and the contact area coordinate in the contact area are determined according to the contact geometric parameters and the lubricating oil film thickness data;

[0012] Based on the unit width load and the contact area coordinate, the contact stress distribution state is calculated by combining the Hertz contact theory, and the contact stress distribution state is lubricated and corrected according to the lubricating oil film thickness data;

[0013] The corrected contact stress distribution state is input as a distributed load into the beam bending deformation equation to establish the corresponding relationship between the bending deformation of the rolling work roll and the contact stress;

[0014] According to the position of the support roll, the boundary constraint condition of the rolling work roll is determined, the boundary constraint condition is combined with the action effect of the rolling force and the bending force, and the beam bending deformation equation is solved;

[0015] According to the solving result of the beam bending deformation equation, the bending deformation amount of the rolling work roll along the rolling direction is obtained, and the working position of the rolling work roll is adjusted based on the bending deformation amount.

[0016] According to the bending deformation amount of the rolling work roll, the flatness distribution and the stress distribution considering the deformation of the rolling work roll are constructed by combining the flatness detection data and the thickness detection data of the strip steel, including:

[0017] Collecting actual plate thickness distribution data in the strip rolling process, comparing the actual plate thickness distribution data with preset target plate thickness data, calculating the relative plate shape deviation of the strip, and establishing a plate shape-stress initial mapping function according to the corresponding relationship between the relative plate shape deviation and the bending deformation amount of the rolling work roll;

[0018] Obtaining the actual roll gap value of the rolling work roll, calculating the distribution relationship between the rolling force and the contact arc length according to the actual roll gap value, substituting the distribution relationship into the plate shape-stress initial mapping function, and constructing the coupling mapping relationship between the plate shape distribution and the stress distribution considering the deformation of the rolling work roll.

[0019] Establishing a dynamic cooperative optimization objective function of plate shape and plate thickness, and obtaining the bending force of the rolling work roll and the displacement amount of the support roll through iterative calculation to meet the dynamic cooperative optimization objective function, including:

[0020] Constructing a comprehensive objective function including plate shape control targets, plate thickness control targets and control costs, and assigning corresponding weight coefficients to the plate shape control targets, plate thickness control targets and control costs in the comprehensive objective function;

[0021] Obtaining process parameters in the rolling process, establishing process constraints based on the process parameters, and applying the process constraints to the comprehensive objective function;

[0022] Collecting real-time state data of the rolling process, calculating the gradient value of the comprehensive objective function based on the real-time state data, and iteratively updating the control variables according to the gradient value;

[0023] Calculating the control variable difference and the objective function difference of the adjacent two iterations, and taking the control variable difference and the objective function difference as the convergence criterion;

[0024] According to the converged control variable, the bending force of the rolling work roll is calculated, the displacement amount of the support roll is determined based on the relationship between the bending force and the rolling pressure, and the cooperative control of the plate shape and the plate thickness is realized by adjusting the bending force and the displacement amount of the support roll.

[0025] Inputting the plate shape and plate thickness data of each section of the rolling process into the fuzzy rule base to obtain the initial control parameters, collecting the state parameters of each section of the roll system to calculate the coupling influence coefficient and construct the adaptive cooperative function, and correcting the bending force of the rolling work roll and the displacement amount of the support roll, including:

[0026] Inputting the plate shape data and the plate thickness data of the inlet section, the middle section and the outlet section of the strip rolling process into the corresponding fuzzy rule base, and obtaining the initial control parameters of each section through fuzzy reasoning operation, the initial control parameters including the bending force of the rolling work roll and the displacement amount of the support roll;

[0027] Collecting state parameters of the rolling work rolls and the backup rolls in each section, calculating coupling influence coefficients between the sections according to the state parameters; constructing an adaptive coordination function based on the coupling influence coefficients, inputting initial control parameters of each section into the adaptive coordination function, calculating coordination compensation amounts between the sections, and modifying the initial control parameters of each section according to the coordination compensation amounts;

[0028] Adjusting the bending force of the rolling work rolls and the displacement amount of the backup rolls in each section according to the modified control parameters.

[0029] Constructing an adaptive coordination function based on the coupling influence coefficients, inputting initial control parameters of each section into the adaptive coordination function, calculating coordination compensation amounts between the sections, and modifying the initial control parameters of each section according to the coordination compensation amounts include:

[0030] Constructing a transfer function matrix based on the coupling influence coefficients, calculating dynamic transfer relationships between the rolling sections according to the transfer function matrix, and distributing coordination weights of the rolling sections according to the dynamic transfer relationships; inputting initial bending forces of the rolling sections and backup roll displacements into the transfer function matrix, calculating compensation coefficients of the rolling sections according to the coordination weights, and constructing an adaptive coordination compensation function based on the compensation coefficients;

[0031] Collecting control deviations of the rolling sections, dynamically updating the coordination weights according to the control deviations, substituting the updated coordination weights and the initial control parameters into the adaptive coordination compensation function, and obtaining bending force compensation amounts and backup roll displacement compensation amounts of the rolling sections;

[0032] Stacking the bending force compensation amounts and the backup roll displacement compensation amounts to the initial control parameters of the rolling sections to obtain modified control parameters.

[0033] The second aspect of the embodiment of the application provides a plate shape control and plate thickness precision coordination optimization system in a cold rolling process, which comprises:

[0034] A first unit is configured to collect contact geometric parameters and lubricating oil film thickness data between the rolling work rolls and the backup rolls, determine contact stress distribution states between the rolling work rolls and the backup rolls, and obtain bending deformation amounts of the rolling work rolls at different positions by combining a beam bending deformation equation;

[0035] A second unit is configured to construct a coupling mapping relationship between plate shape distribution and stress distribution considering deformation of the rolling work rolls according to the bending deformation amounts of the rolling work rolls, and combining plate shape detection data and plate thickness detection data of the strip steel;

[0036] The third unit is configured to adaptively adjust a compensation coefficient corresponding to the coupling mapping relationship according to a state judgment result of the strip rolling process, establish a dynamic cooperative optimization objective function of the plate shape and the plate thickness, and obtain a rolling work roll bending force and a support roll displacement amount satisfying the dynamic cooperative optimization objective function through iterative calculation; input plate shape and plate thickness data of each section of the rolling process into a fuzzy rule base to obtain initial control parameters, collect roll system state parameters to calculate a coupling influence coefficient and construct an adaptive cooperative function, and correct the rolling work roll bending force and the support roll displacement amount.

[0037] The fourth unit is configured to adjust rolling parameters of the cold rolling mill in real time according to the rolling work roll bending force and the support roll displacement amount, and realize cooperative control of the strip plate shape and the plate thickness.

[0038] The third aspect of the embodiment of the application,

[0039] An electronic device is provided, comprising:

[0040] A processor;

[0041] A memory for storing processor-executable instructions;

[0042] The processor is configured to invoke the instructions stored in the memory to execute the method described above.

[0043] The fourth aspect of the embodiment of the application,

[0044] A computer-readable storage medium is provided, which stores computer program instructions, and the computer program instructions are executed by a processor to implement the method described above.

[0045] The beneficial effects of the present application are as follows:

[0046] By collecting the contact geometric parameters and the lubricating oil film thickness data between the rolling work roll and the support roll, the contact stress distribution state is determined, and the beam bending deformation equation is combined, so that the bending deformation amount of the work roll at different positions can be accurately obtained, which provides accurate basic data for the cooperative control of the plate shape and the plate thickness, and improves the accuracy of the plate shape control.

[0047] According to the bending deformation amount of the work roll, the coupling mapping relationship is constructed in combination with the plate shape detection data and the plate thickness detection data, so that the system can effectively capture the mutual influence between the plate shape distribution and the stress distribution, the compensation coefficient is adaptively adjusted, the dynamic cooperative optimization of the plate shape and the plate thickness control target is realized, and the comprehensive quality of the cold-rolled strip is improved.

[0048] Based on the coupling influence coefficient of the initial control parameter and the roll system state parameter of the fuzzy rule base, an adaptive coordination function is constructed, which can correct the bending force of the working roll and the displacement of the support roll in real time, so that the system has stronger adaptability to the dynamic changes in the rolling process, effectively reduces the plate shape defects and the plate thickness fluctuation, and improves the quality stability and rolling efficiency of the strip steel product. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 A flowchart of a plate shape control and plate thickness precision collaborative optimization method in a rolling process of a cold rolling mill according to an embodiment of the present application is shown in

[0050] Figure 2 A flowchart of an iterative calculation of a dynamic collaborative optimization objective function is shown in DETAILED DESCRIPTION

[0051] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0052] The technical solutions of the present application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described in some embodiments.

[0053] Figure 1 A flowchart of a plate shape control and plate thickness precision collaborative optimization method in a rolling process of a cold rolling mill according to an embodiment of the present application is shown in Figure 1 The method comprises the following steps:

[0054] The contact geometric parameters and the lubricating oil film thickness data between the rolling working roll and the support roll are collected, the contact stress distribution state between the rolling working roll and the support roll is determined, and the bending deformation amount of the rolling working roll at different positions is obtained by combining the beam bending deformation equation;

[0055] According to the bending deformation amount of the rolling working roll, the coupling mapping relationship between the plate shape distribution and the stress distribution considering the deformation of the rolling working roll is constructed by combining the plate shape detection data and the plate thickness detection data of the strip steel;

[0056] According to the state judgment result of the strip rolling process, the compensation coefficient corresponding to the coupling mapping relationship is adaptively adjusted, a dynamic cooperative optimization objective function of the plate shape and the plate thickness is established, and the bending force of the rolling work roll and the displacement of the support roll are obtained through iterative calculation to meet the dynamic cooperative optimization objective function; the plate shape and the plate thickness data of each section of the rolling process are input into the fuzzy rule base to obtain initial control parameters, the coupling influence coefficient is calculated by collecting the state parameters of each section of the roll system, the adaptive cooperative function is constructed, and the bending force of the rolling work roll and the displacement of the support roll are corrected.

[0057] According to the bending force of the rolling work roll and the displacement of the support roll, the rolling parameters of the cold rolling mill are adjusted in real time to realize the cooperative control of the plate shape and the plate thickness of the strip.

[0058] In an alternative embodiment, the contact geometric parameters and the lubricating oil film thickness data between the rolling work roll and the support roll are collected, the contact stress distribution state between the rolling work roll and the support roll is determined, and the bending deformation amount of the rolling work roll at different positions is obtained by combining the beam bending deformation equation, including:

[0059] The contact geometric parameters and the lubricating oil film thickness data between the rolling work roll and the support roll are collected, and the unit width load and the contact area coordinate in the contact area are determined according to the contact geometric parameters and the lubricating oil film thickness data;

[0060] Based on the unit width load and the contact area coordinate, the contact stress distribution state is calculated by combining the Hertz contact theory, and the contact stress distribution state is lubricated and corrected according to the lubricating oil film thickness data;

[0061] The corrected contact stress distribution state is input as a distributed load into the beam bending deformation equation to establish the corresponding relationship between the bending deformation of the rolling work roll and the contact stress;

[0062] The boundary constraint condition of the rolling work roll is determined according to the position of the support roll, the boundary constraint condition is combined with the action effect of the rolling force and the bending force, and the beam bending deformation equation is solved;

[0063] According to the solving result of the beam bending deformation equation, the bending deformation amount of the rolling work roll along the rolling direction is obtained, and the working position of the rolling work roll is adjusted based on the bending deformation amount.

[0064] A high-precision displacement sensor and a pressure sensor are installed near the contact area between the rolling work roll and the backup roll to collect the contact geometric parameters between the two rolls, including the contact width, the contact length, and the contact radius of curvature. At the same time, an ultrasonic thickness gauge is used to measure the lubricating oil film thickness in the contact area, which is usually in the range of 5-20 microns. For example, in a certain measurement, the contact width is 12 mm, the contact length is 1500 mm, the work roll radius of curvature is 300 mm, the backup roll radius of curvature is 600 mm, and the average lubricating oil film thickness is 8 microns.

[0065] Based on the collected parameters, a coordinate system of the contact area is established by scanning the entire contact area, where the x-axis is along the rolling direction and the y-axis is along the roll body width direction, and the coordinate values of each discrete point and the corresponding unit width load are determined. For example, when rolling a plate with a width of 1500 mm, the contact area is equally divided into 150 units, each with a width of 10 mm, and the coordinates of the center points of each unit and the corresponding unit width load are recorded. The maximum unit width load is measured to be 12000 N / mm, which occurs at the center position of the contact area.

[0066] Using the collected data, the contact stress distribution state is calculated based on the Hertz contact theory, considering the material elastic modulus and Poisson's ratio (for example, the work roll material elastic modulus is 210 GPa and Poisson's ratio is 0.3), and the contact stress of each point is calculated. Under typical working conditions, the maximum contact stress can reach 900 MPa, located at the contact center, and gradually decreases to zero along the edge of the contact area.

[0067] Considering the influence of lubrication effect on contact stress, the data of lubricating oil film thickness is corrected. The presence of oil film will reduce the actual contact stress, and the correction coefficient is negatively related to the thickness of lubricating oil film. For example, when the oil film thickness is 8 microns, the contact stress correction coefficient is about 0.92, which reduces the maximum contact stress after correction to 828 MPa.

[0068] The corrected contact stress distribution is used as a distributed load to substitute into the beam bending deformation equation, in which the rolling work roll is simplified as a beam with a certain cross-sectional moment of inertia. For example, a work roll with a roll body diameter of 500 mm has a cross-sectional moment of inertia of about 3.07 x 10 9 square millimeters, and a model of the relationship between the bending deformation of the work roll and the contact stress is established.

[0069] The boundary conditions are determined according to the actual arrangement of the backup roll. In a four-high rolling mill, there are usually two backup rolls located on both sides of the work roll to provide support points for the work roll, which constitute the constraint conditions of the work roll. For example, if the backup rolls are located 400 mm away from the two ends of the work roll, respectively, the displacement and bending moment at these two positions become the boundary conditions of the solving equation.

[0070] At the same time, the effects of rolling force and bending force need to be taken into account in the calculation. The rolling force usually acts on the middle part of the work roll vertically downward, and the bending force acts on the roll end to adjust the roll gap shape. For example, in a certain rolling process, the rolling force is 15000 kN, and the bending force is 500 kN. The distribution and size of these forces directly affect the bending deformation of the work roll.

[0071] The beam bending deformation equation is solved by numerical integration or finite difference method. When the grid is divided, the length direction of the roll body is usually divided into 300 units, and the length of each unit is about 5-10 mm to ensure the calculation accuracy. The calculation result gives the bending deformation of the work roll at each position. For example, under the above working condition, the maximum bending deformation of the middle part of the work roll is about 1.25 mm, and the deformation of the two end support points is close to zero.

[0072] According to the calculated bending deformation, the axial and radial positions of the work roll are adjusted by hydraulic cylinders or electric mechanisms to compensate for the effects of deformation. For example, when it is detected that the deformation at a certain position exceeds the set threshold (such as 1.5 mm), the roll gap at the corresponding position will be automatically adjusted to ensure the thickness accuracy and flatness quality of the rolled product. The whole adjustment process realizes closed-loop control, ensuring the stability of the rolling process and the consistency of the product quality.

[0073] In an alternative embodiment, the coupling mapping relationship between the flatness distribution and the stress distribution considering the deformation of the rolling work roll is constructed according to the bending deformation of the rolling work roll, combined with the flatness detection data and the thickness detection data of the strip steel, including:

[0074] The actual thickness distribution data of the strip steel in the rolling process is collected, the actual thickness distribution data is compared with the preset target thickness data, the relative flatness deviation of the strip steel is calculated, and the flatness-stress initial mapping function is established according to the corresponding relationship between the relative flatness deviation and the bending deformation of the rolling work roll;

[0075] The actual roll gap value of the rolling work roll is obtained, the distribution relationship between the rolling force and the contact arc length is calculated according to the actual roll gap value, the distribution relationship is substituted into the flatness-stress initial mapping function, and the coupling mapping relationship between the flatness distribution and the stress distribution considering the deformation of the rolling work roll is constructed.

[0076] In the process of strip rolling, the work roll will be deformed by bending under the action of rolling force. This bending deformation will directly affect the shape quality of the final rolled strip. In order to accurately describe the influence relationship, the bending deformation data of the work roll in the rolling process is collected through actual production process. Specifically, on a certain cold rolling production line, a displacement sensor array is arranged uniformly along the width direction of the work roll to monitor the bending deformation of each point of the work roll in real time during rolling. For example, on a work roll with a width of 1800mm, a sensor is arranged every 200mm, and the bending deformation data of 9 measuring points are obtained. Under typical working conditions, the maximum bending deformation of the middle region of the work roll reaches 0.15mm, and the deformation of the two end regions is about 0.03mm.

[0077] The shape and thickness data of the strip are measured in real time using the shape meter and thickness meter installed at the outlet of the rolling mill. The shape meter reflects the flatness of the strip by measuring the tension distribution of each transverse position of the strip, and the thickness meter directly measures the actual thickness distribution of the strip. For example, for a cold-rolled strip with a width of 1500mm, the shape meter is provided with 15 measuring regions in the transverse direction, each with a width of 100mm, and the tension values of each region are measured respectively; at the same time, the thickness meter measures the actual thickness of the strip at the same position. In one measurement, the tension value of the middle region of the strip is 280MPa, and that of the edge region is 260MPa, indicating that the middle region of the strip has a slight wave; at the same time, the actual thickness of the middle region is 0.505mm, and that of the edge region is 0.508mm, which deviates from the target thickness of 0.5mm.

[0078] Based on the collected actual thickness distribution data of the strip, the relative shape deviation is calculated by comparing it with the preset target thickness data. The calculation method of the relative shape deviation is to subtract the target thickness from the actual thickness and then divide by the target thickness. Using the above example data, the relative shape deviation of the middle region is calculated to be 1%, and that of the edge region is 1.6%. At this time, the corresponding relationship between these relative shape deviations and the bending deformation of the rolling work roll is established to form a preliminary mapping function. This corresponding relationship can be established by data fitting, which is expressed as: when the bending deformation of the middle region of the work roll is 0.15mm, the relative shape deviation of the middle region of the strip is 1%; when the bending deformation of the edge region of the work roll is 0.03mm, the relative shape deviation of the edge region of the strip is 1.6%.

[0079] The actual roll gap value data is obtained through the rolling mill control system. For example, in the above rolling process, the roll gap value in the middle of the rolling mill is 0.48mm, and the edge roll gap value is 0.51mm. Based on these roll gap values, the distribution relationship between the rolling force and the contact arc length is calculated: according to the Hertz contact theory, there is a relationship between the contact arc length L, the roll gap value h, the work roll radius R and the material deformation resistance k: where Ah is the roll gap change, and the contact arc length at different positions is calculated by substituting the middle roll gap value of 0.48 mm and the edge roll gap value of 0.51 mm, respectively; the rolling force P can be calculated by the formula where b is the unit width of the strip, k is the deformation resistance, and Q is the influence coefficient, which is related to the friction coefficient and the degree of deformation of the strip; in actual calculation, the rolling mill is uniformly divided into 9 calculation units in the transverse direction, and the rolling force and the contact arc length at each unit are calculated to obtain the complete transverse distribution relationship. In specific calculation, the distribution of the rolling force in the transverse direction is obtained by considering factors such as the deformation resistance of the strip and the friction coefficient. For example, the rolling force is 800 kN in the middle region and 700 kN in the edge region; and the corresponding contact arc lengths are 5.2 mm in the middle region and 4.8 mm in the edge region.

[0080] The above rolling force and contact arc length distribution relationship are substituted into the plate shape-stress initial mapping function to construct the coupling mapping relationship between the plate shape distribution and the stress distribution considering the deformation of the rolling work roll. This coupling mapping relationship reflects how the change of the plate shape of the strip affects the internal stress distribution under the condition of a specific bending deformation of the work roll, and vice versa. For example, in this rolling condition, when the bending deformation of the work roll in the middle increases by 0.01 mm, the stress in the middle of the strip will increase by about 5 MPa; and when the bending deformation of the edge decreases by 0.01 mm, the stress of the edge will decrease by about 4 MPa.

[0081] Through this coupling mapping relationship, accurate prediction and control of the plate shape during rolling can be achieved. For example, when a middle wave defect is detected in the strip, the coupling mapping relationship can be used to calculate the bending deformation amount of the work roll that needs to be adjusted, and the roll gap distribution of the rolling mill can be adjusted accordingly to eliminate the plate shape defect. In an actual application, the strip with an original plate shape deviation value I5 of 35 was improved to an I5 value of less than 15 through adjustment guided by the coupling mapping relationship, significantly improving the product quality.

[0082] In an alternative embodiment, a dynamic collaborative optimization objective function of plate shape and plate thickness is established, and the bending force of the rolling work roll and the displacement amount of the support roll that satisfy the dynamic collaborative optimization objective function are obtained through iterative calculation, including:

[0083] An integrated objective function including a plate shape control objective, a plate thickness control objective, and a control cost is constructed, and corresponding weight coefficients are assigned to the plate shape control objective, the plate thickness control objective, and the control cost in the integrated objective function;

[0084] Process parameters in the rolling process are obtained, and process constraints are established based on the process parameters, and the process constraints are applied to the integrated objective function;

[0085] Collecting real-time state data of the rolling process, calculating gradient values of the comprehensive objective function based on the real-time state data, and iteratively updating control variables according to the gradient values;

[0086] Calculating a difference value of the control variables and a difference value of the objective function between two adjacent iterations, and taking the difference values as a convergence criterion;

[0087] According to the converged control variables, calculating a bending force of the work roll, determining a displacement amount of the backup roll based on a relationship between the bending force and the rolling pressure, and realizing the collaborative control of the plate shape and the plate thickness by adjusting the bending force and the displacement amount of the backup roll.

[0088] As shown in Figure 2 , the method comprises:

[0089] A comprehensive objective function is constructed, which includes a plate shape control target, a plate thickness control target, and a control cost. The function can be expressed as a weighted sum of three parts: the first part represents the sum of squares of plate shape deviations, representing the difference between the actual plate shape and the target plate shape; the second part represents the sum of squares of plate thickness deviations, representing the difference between the actual plate thickness and the target plate thickness; and the third part represents the control cost, representing the adjustment amplitude of the control variables. For the plate shape control target, a weight coefficient of 0.5 can be assigned; for the plate thickness control target, a weight coefficient of 0.4 can be assigned; and for the control cost, a weight coefficient of 0.1 can be assigned. These weight coefficients can be adjusted according to production needs, for example, when the plate shape quality requirement is higher, the weight coefficient of the plate shape control target can be increased to 0.6, and the other weight coefficients can be correspondingly reduced.

[0090] Key parameters such as inlet plate thickness, outlet plate thickness, rolling speed, rolling force, and rolling temperature need to be collected to obtain process parameters in the rolling process. Taking a certain cold rolling production line as an example, the inlet plate thickness is 2.5 mm, the outlet plate thickness target value is 0.8 mm, the rolling speed is 800 m / min, and the rolling temperature is 60℃. Based on these process parameters, process constraint conditions are established, including that the bending force value range is 0-800 kN, the backup roll displacement amount value range is ±100 mm, and the rolling pressure does not exceed 2000 kN. These constraint conditions are applied to the comprehensive objective function by adding a penalty term, when the control variables exceed the constraint range, the penalty term will greatly increase the objective function value, guiding the optimization algorithm to search within the constraint region.

[0091] The plate shape and plate thickness data in the rolling process are collected by a plate shape instrument and a thickness gauge respectively, the sampling frequency is 100 Hz, and auxiliary data such as rolling force, rolling torque, rolling speed and the like are collected at the same time, based on the collected real-time state data, the gradient value of the comprehensive objective function to the control variable is calculated. In specific calculation, the finite difference method can be used to approximate the gradient, that is, the gradient value is estimated by the change of the objective function value before and after the slight disturbance of the control variable. For example, when the bending roll force increases from 300 kN to 301 kN, if the objective function value decreases from 0.85 to 0.84, the gradient value can be estimated as -0.01 / 1 = -0.01, indicating that increasing the bending roll force is beneficial to the reduction of the objective function value.

[0092] According to the calculated gradient value, the control variable is iteratively updated, and the gradient descent method is used for updating, that is, the new value of the control variable is equal to the current value minus the product of the learning rate and the gradient value, the learning rate can be set to 0.05, and can be gradually reduced to 0.01 with the increase of the iteration number, so as to ensure the convergence of the algorithm.

[0093] In the iteration process, the difference value of the control variable and the objective function between adjacent two iterations needs to be calculated as a convergence criterion, specifically, when the Euclidean distance of the control variable is less than a preset threshold (such as 0.001) and the change of the objective function value is less than a preset threshold (such as 0.0001), it is considered that the iteration converges. In actual application, the bending roll force changes from 299.5 kN to 299.52 kN in a certain iteration, the Euclidean distance of the control variable is 0.0208, the objective function value changes from 0.84 to 0.8399, and the difference value is 0.0001, which all meet the convergence condition, so the iteration is terminated.

[0094] According to the converged control variable, the bending roll force of the rolling work roll is calculated, and the converged bending roll force is 299.52 kN in the above example, the displacement amount of the support roll is determined based on the relationship between the bending roll force and the rolling pressure, and the relationship between the rolling pressure P and the bending roll force F can be obtained by fitting the experimental data, for example, the relationship can be expressed as P = 1500 - 0.5F (unit: kN), when the bending roll force is 299.52 kN, the rolling pressure is 1350.24 kN. The support roll displacement amount is related to the bending roll force and the rolling pressure, and can be calculated by support roll displacement amount = 35 + 0.02 x bending roll force - 0.01 x rolling pressure, and the numerical value is substituted to obtain the support roll displacement amount as 35 + 0.02 x 299.52 - 0.01 x 1350.24 = 27.488 mm.

[0095] By adjusting the bending force and the displacement of the support roller, the shape and thickness of the plate can be controlled simultaneously. In actual production, when the shape of the plate is detected to have a wave edge defect, the bending force will be automatically increased and the displacement of the support roller will be adjusted according to the shape deviation. When the thickness of the plate is detected to be out of tolerance, the displacement of the support roller will be adjusted and the bending force will be adjusted accordingly according to the thickness deviation, so as to realize the simultaneous optimization control of the shape and thickness of the plate.

[0096] In an optional embodiment, the shape and thickness data of each section of the rolling process are input into the fuzzy rule base to obtain initial control parameters, the coupling influence coefficient is calculated by collecting the state parameters of each section of the roller system, and the adaptive cooperative function is constructed. The bending force of the rolling work roller and the displacement of the support roller are modified, including:

[0097] The shape and thickness data of the entry section, the middle section and the exit section of the strip rolling process are input into the corresponding fuzzy rule base, and the initial control parameters of each section are obtained by fuzzy reasoning operation. The initial control parameters include the bending force of the rolling work roller and the displacement of the support roller.

[0098] The state parameters of the rolling work roller and the support roller of each section are collected, and the coupling influence coefficient between each section is calculated according to the state parameters. Based on the coupling influence coefficient, the adaptive cooperative function is constructed, the initial control parameters of each section are input into the adaptive cooperative function, the cooperative compensation amount between each section is calculated, and the initial control parameters of each section are modified according to the cooperative compensation amount.

[0099] The bending force of the rolling work roller and the displacement of the support roller of each section are adjusted according to the modified control parameters.

[0100] The strip rolling process is usually divided into three main regions: entry section, middle section and exit section. Each region needs independent and coordinated control parameters to ensure the uniformity of the shape and thickness of the final plate. The shape and thickness data of each section are collected by a sensor network. The shape data is usually represented by crown value. For example, for a strip with a width of 1200mm, the entry section crown is about 0.03mm, the middle section crown is about 0.025mm, and the exit section crown is about 0.02mm. The thickness data includes transverse thickness distribution, such as entry section thickness 3.2±0.05mm, middle section thickness 2.8±0.04mm, and exit section thickness 2.5±0.03mm.

[0101] The collected data are input into a pre-established fuzzy rule base for processing. The fuzzy rule base is established based on expert experience and historical data and contains a set of "if-then" rules. For example, the fuzzy rules for the entry section include: "if the crown is a large positive value and the thickness deviation is a small positive value, then the bending force of the work roll is set to be medium-high and the displacement of the backup roll is set to be a small negative value." The fuzzy reasoning process involves three steps of fuzzification, rule matching, and defuzzification. The precise crown and thickness values are converted into fuzzy linguistic variables such as "large", "medium", and "small" using membership functions. Then, the fuzzy values of the control parameters are calculated according to the rules. Finally, the precise control amounts are obtained through defuzzification methods such as the center of gravity method.

[0102] Through this fuzzy reasoning, initial control parameters for each rolling section can be generated. For example, for the entry section, the bending force of the work roll is 800 kN and the displacement of the backup roll is -2.5 mm; for the middle section, the bending force is 650 kN and the displacement is -1.8 mm; and for the exit section, the bending force is 500 kN and the displacement is -1.2 mm.

[0103] The state parameters of the work roll and the backup roll are collected, including the wear condition, temperature distribution, and bending stiffness of the work roll, as well as the position accuracy and bearing state of the backup roll. For example, the surface temperature of the work roll is 85°C for the entry section, 78°C for the middle section, and 70°C for the exit section; the wear amount of the work roll is 0.015 mm for the entry section, 0.012 mm for the middle section, and 0.008 mm for the exit section.

[0104] Based on these state parameters, coupling influence coefficients between sections are calculated, which reflect the degree of influence of changes in the control parameters of one section on other sections. The calculation method is based on a rolling mechanics model and takes into account roll deformation, contact stress distribution, and thermal expansion effects. When calculating, the roll stiffness ratio, wear degree, temperature gradient, and stress distribution are considered, combined with the geometric distance between sections, to form an influence coefficient matrix, which is then normalized and dynamically corrected. For example, the influence coefficient of the entry section on the middle section is 0.65, the influence coefficient of the entry section on the exit section is 0.32, and the influence coefficient of the middle section on the exit section is 0.78.

[0105] In an alternative embodiment, an adaptive coordination function is constructed based on the coupling influence coefficients. The initial control parameters of each section are input into the adaptive coordination function, the coordination compensation amounts between sections are calculated, and the initial control parameters of each section are modified according to the coordination compensation amounts.

[0106] A transfer function matrix is constructed based on the coupling influence coefficients, a dynamic transmission relationship between the rolling sections is calculated according to the transfer function matrix, and a cooperative weight of each rolling section is distributed according to the dynamic transmission relationship; initial bending force and support roller displacement of each rolling section are input into the transfer function matrix, a compensation coefficient of each rolling section is calculated according to the cooperative weight, and an adaptive cooperative compensation function is constructed based on the compensation coefficient;

[0107] A control deviation of each rolling section is collected, the cooperative weight is dynamically updated according to the control deviation, the updated cooperative weight and the initial control parameter are substituted into the adaptive cooperative compensation function, and a bending force compensation amount and a support roller displacement compensation amount of each rolling section are obtained.

[0108] The bending force compensation amount and the support roller displacement compensation amount are superimposed to the initial control parameter of each rolling section, and a corrected control parameter is obtained.

[0109] The coupling influence coefficient reflects the mutual influence degree between different rolling sections. Assuming that a four-roll rolling mill includes N rolling sections, and there are two control quantities of bending force and support roller displacement in each rolling section, a 2N*2N transfer function matrix T can be constructed. The element Tij in the matrix represents the influence degree of the jth control quantity on the ith control quantity. For the coupling relationship between the bending force and the support roller displacement, the experimental data fitting can be used. For example, for a three-section cold rolling mill, when the first section bending force changes by 1000 kN, it will cause the second section outlet plate thickness to increase by 0.02 mm, and the corresponding transfer coefficient is 0.00002 mm / kN.

[0110] By analyzing the historical running data of each rolling section, the corresponding relationship between the control parameter change and the final rolling effect is extracted, and a dynamic transmission model is constructed. The model can automatically adjust the transmission coefficient according to the current rolling working condition. For example, in actual application, when the strip thickness is reduced from 2.0 mm to 1.0 mm, the transmission coefficient increases from 0.00002 mm / kN to 0.00003 mm / kN, and the transfer function matrix is automatically updated according to this change.

[0111] The importance evaluation method is used to determine the weight coefficient of each rolling section. For the rolling section that has a greater influence on the downstream rolling section, a higher cooperative weight is given; for the rolling section that is greatly affected by the upstream, a lower cooperative weight is given. Taking a three-section cold rolling mill as an example, assuming that the first section has a significant influence on the downstream, it can be given a weight coefficient of 0.5; the second section has a moderate influence, it can be given a weight coefficient of 0.3; and the third section has a smaller influence, it can be given a weight coefficient of 0.2.

[0112] When calculating the compensation coefficients of each rolling section according to the coordination weight, the importance and control sensitivity of each section are comprehensively considered, and the compensation coefficients are calculated by using a weighted average method. For the bending roll force compensation coefficient CB and the support roll displacement compensation coefficient CS, they are calculated based on the coordination weight W and the corresponding transfer coefficient T of each section, respectively. For example, for the second section, the bending roll force compensation coefficient can be expressed as W2 x (T21 x C1 + T23 x C3), wherein C1 and C3 are the control deviations of the first section and the third section, respectively.

[0113] Based on the compensation coefficients, an adaptive coordination compensation function is constructed by using a nonlinear mapping method, the compensation coefficients are converted into specific control adjustment amounts, and the function can adaptively adjust the compensation intensity according to the current control deviation. For a small deviation, a linear compensation strategy is adopted; for a large deviation, a nonlinear suppression strategy is adopted to avoid excessive compensation and cause system instability.

[0114] Actual rolling parameters are monitored in real time by sensors such as thickness gauges and tension gauges installed in each rolling section. Taking the plate thickness control as an example, if the set thickness is 1.0 mm and the actual measured thickness is 1.02 mm, the control deviation is 0.02 mm. These deviation values are fed back to the control algorithm in real time.

[0115] When the control deviation of a certain rolling section continuously increases, the coordination weight of the section is increased by using an adaptive adjustment strategy to dynamically update the coordination weight according to the control deviation; when the deviation decreases, the weight is appropriately reduced. This dynamic adjustment mechanism ensures that the system can respond to changes in the rolling process in a timely manner. For example, when the control deviation of the first section increases from 0.01 mm to 0.03 mm, the coordination weight of the first section is adjusted from 0.5 to 0.6, and the weights of the other sections are correspondingly reduced.

[0116] The updated coordination weight and the initial control parameters are substituted into the adaptive coordination compensation function. The optimal compensation amount is calculated by comprehensively considering the current control state and historical data. For the example of a three-section cold rolling mill, if a thickness deviation of 0.03 mm occurs in the first section, according to the coordination compensation function, the bending roll force of the first section needs to be increased by 200 kN for compensation, and the support roll displacement needs to be reduced by 0.1 mm for compensation; at the same time, the bending roll force of the second section needs to be increased by 100 kN for compensation, and the support roll displacement needs to be reduced by 0.05 mm for compensation.

[0117] The calculated compensation amount is directly added to the original set value. Taking the first section in the above example as an example, the corrected bending roll force is 8000 kN + 200 kN = 8200 kN, and the corrected support roll displacement is 5 mm - 0.1 mm = 4.9 mm. These corrected control parameters will be sent to the rolling mill control system as new execution instructions to achieve accurate control.

[0118] Through the adaptive cooperative control method, the coupling influence between the sections in the rolling process can be effectively handled, and the control precision of the rolling mill and the product quality stability are improved. The actual application shows that after the method is adopted, the thickness deviation of the plate can be reduced from ±0.03mm to ±0.01mm, and the flatness deviation can be reduced from ±5I units to ±2I units, and the product quality is significantly improved.

[0119] The plate shape control and plate thickness precision cooperative optimization system in the rolling process of the cold rolling mill according to the embodiment of the application comprises:

[0120] The first unit is used for collecting the contact geometric parameters and the lubricating oil film thickness data between the rolling work roll and the support roll, determining the contact stress distribution state between the rolling work roll and the support roll, and obtaining the bending deformation amount of the rolling work roll at different positions by combining the beam bending deformation equation;

[0121] The second unit is used for constructing the coupling mapping relationship between the plate shape distribution and the stress distribution considering the deformation of the rolling work roll according to the bending deformation amount of the rolling work roll, and combining the plate shape detection data and the plate thickness detection data of the strip steel;

[0122] The third unit is used for adaptively adjusting the compensation coefficient corresponding to the coupling mapping relationship according to the state judgment result of the strip steel rolling process, establishing a dynamic cooperative optimization objective function of the plate shape and the plate thickness, and obtaining the rolling work roll bending force and the support roll displacement amount satisfying the dynamic cooperative optimization objective function through iterative calculation; the plate shape and the plate thickness data of each section in the rolling process are input into a fuzzy rule base to obtain initial control parameters, the coupling influence coefficient is calculated by collecting the state parameters of each section of the roll system, the adaptive cooperative function is constructed, and the rolling work roll bending force and the support roll displacement amount are corrected;

[0123] The fourth unit is used for adjusting the rolling parameters of the cold rolling mill in real time according to the rolling work roll bending force and the support roll displacement amount, and realizing the cooperative control of the strip steel plate shape and the plate thickness.

[0124] The third aspect of the embodiment of the application provides an electronic device, comprising:

[0125] a processor;

[0126] a memory for storing processor-executable instructions;

[0127] The processor is configured to invoke the instructions stored in the memory to execute the method described above.

[0128] The fourth aspect of the embodiment of the application provides a computer-readable storage medium having computer program instructions stored thereon, and the computer program instructions are executed by a processor to implement the method described above.

[0129] The present application can be a method, an apparatus, a system, and / or a computer program product. The computer program product can include a computer readable storage medium (or media) having computer readable program instructions thereon for performing various aspects of the present application.

[0130] Finally, it should be noted that the above-mentioned embodiments are merely used to illustrate the technical solutions of the present application, rather than limit the present application; even though the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some or all of the technical features thereof can be replaced equivalently; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for shape control and gauge accuracy collaborative optimization in cold rolling process of a cold rolling mill, characterized in that, The method comprises the following steps: Collecting contact geometry parameters and lubricating oil film thickness data between the rolling work roll and the backup roll, determining the contact stress distribution state between the rolling work roll and the backup roll, and combining the beam bending deformation equation to obtain the bending deformation amount of the rolling work roll at different positions; According to the bending deformation amount of the rolling work roll, combining the strip shape detection data and the strip thickness detection data, a coupling mapping relationship between the strip shape distribution and the stress distribution considering the deformation of the rolling work roll is constructed; According to the state judgment result of the strip rolling process, the compensation coefficient corresponding to the coupling mapping relationship is adaptively adjusted, A dynamic collaborative optimization objective function of strip shape and strip thickness is established, and the bending force of the rolling work roll and the displacement amount of the backup roll satisfying the dynamic collaborative optimization objective function are obtained through iterative calculation, comprising: An integrated objective function including a strip shape control target, a strip thickness control target and a control cost is constructed, and corresponding weight coefficients are assigned to the strip shape control target, the strip thickness control target and the control cost in the integrated objective function; Obtaining process parameters in the rolling process, establishing process constraints based on the process parameters, and applying the process constraints to the integrated objective function; Collecting real-time state data of the rolling process, calculating the gradient value of the integrated objective function based on the real-time state data, and iteratively updating the control variables according to the gradient value; The control variable difference and the objective function difference of adjacent two iterations are calculated, and the control variable difference and the objective function difference are taken as convergence criteria; According to the converged control variable, the bending force of the rolling work roll is calculated, the displacement amount of the backup roll is determined based on the relationship between the bending force and the rolling pressure, and the bending force and the displacement amount of the backup roll are adjusted to realize the collaborative control of the strip shape and the strip thickness; The strip shape and strip thickness data of each section of the rolling process are input into the fuzzy rule base to obtain the initial control parameters, the coupling influence coefficient is calculated by collecting the state parameters of each section of the roll system, the adaptive collaborative function is constructed, and the bending force of the rolling work roll and the displacement amount of the backup roll are corrected; According to the bending force of the rolling work roll and the displacement amount of the backup roll, the rolling parameters of the cold rolling mill are adjusted in real time to realize the collaborative control of the strip shape and the strip thickness.

2. The method of claim 1, wherein, Collecting contact geometry parameters and lubricating oil film thickness data between the rolling work roll and the backup roll, determining the contact stress distribution state between the rolling work roll and the backup roll, and combining the beam bending deformation equation to obtain the bending deformation amount of the rolling work roll at different positions, comprising: Collecting contact geometry parameters and lubricating oil film thickness data between the rolling work roll and the backup roll, and determining the unit width load in the contact area and the contact area coordinates according to the contact geometry parameters and the lubricating oil film thickness data; Based on the unit width load and the contact area coordinates, the contact stress distribution state is calculated combined with the Hertz contact theory, and the contact stress distribution state is lubricated and corrected according to the lubricating oil film thickness data; The corrected contact stress distribution state is input as a distributed load into the beam bending deformation equation to establish the corresponding relationship between the bending deformation of the rolling work roll and the contact stress; Determine the boundary constraint condition of the rolling work roll according to the position of the support roll, combine the effect of the rolling force and the bending force of the roll to solve the beam bending deformation equation; According to the solving result of the beam bending deformation equation, the bending deformation amount of the rolling work roll along the rolling direction is obtained, and the working position of the rolling work roll is adjusted based on the bending deformation amount.

3. The method of claim 1, wherein, According to the bending deformation amount of the rolling work roll, the coupling mapping relationship between the strip shape distribution and the stress distribution considering the deformation of the rolling work roll is constructed by combining the strip shape detection data and the strip thickness detection data, including: Acquire the actual strip thickness distribution data in the strip rolling process, compare the actual strip thickness distribution data with the preset target strip thickness data, calculate the relative strip shape deviation of the strip, and establish the initial mapping function of strip shape-stress according to the corresponding relationship between the relative strip shape deviation and the bending deformation amount of the rolling work roll; Obtain the actual roll gap value of the rolling work roll, calculate the distribution relationship of the rolling force and the contact arc length according to the actual roll gap value, substitute the distribution relationship into the initial mapping function of strip shape-stress, and construct the coupling mapping relationship between the strip shape distribution and the stress distribution considering the deformation of the rolling work roll.

4. The method of claim 1, wherein, Input the strip shape and strip thickness data of each section of the rolling process into the fuzzy rule base to obtain the initial control parameters, acquire the state parameters of each section of the roll system to calculate the coupling influence coefficient, and correct the bending force of the rolling work roll and the displacement amount of the support roll, including: Input the strip shape data and strip thickness data of the entry section, middle section and exit section of the strip rolling process into the corresponding fuzzy rule base, and obtain the initial control parameters of each section through fuzzy reasoning operation, wherein the initial control parameters include the bending force of the rolling work roll and the displacement amount of the support roll; Acquire the state parameters of the rolling work roll and the support roll of each section, calculate the coupling influence coefficient between each section according to the state parameters, construct an adaptive cooperative function based on the coupling influence coefficient, input the initial control parameters of each section into the adaptive cooperative function, calculate the cooperative compensation amount between each section, and correct the initial control parameters of each section according to the cooperative compensation amount; Adjust the bending force of the rolling work roll and the displacement amount of the support roll according to the corrected control parameters.

5. The method of claim 4, wherein, Construct an adaptive cooperative function based on the coupling influence coefficient, input the initial control parameters of each section into the adaptive cooperative function, calculate the cooperative compensation amount between each section, and correct the initial control parameters of each section according to the cooperative compensation amount, including: Construct a transfer function matrix based on the coupling influence coefficient, calculate the dynamic transfer relationship between each rolling section according to the transfer function matrix, and distribute the cooperative weight of each rolling section according to the dynamic transfer relationship; input the initial bending force of each rolling section and the displacement of the support roll into the transfer function matrix, calculate the compensation coefficient of each rolling section according to the cooperative weight, and construct an adaptive cooperative compensation function based on the compensation coefficient; Collecting control deviations of each rolling section, dynamically updating the coordination weight according to the control deviations, substituting the updated coordination weight and the initial control parameter into the adaptive coordination compensation function to obtain a bending force compensation amount and a support roller displacement compensation amount of each rolling section; Superimposing the bending force compensation amount and the support roller displacement compensation amount to the initial control parameter of each rolling section to obtain a corrected control parameter.

6. A system for shape control and gauge accuracy synergy optimization during cold rolling in a cold rolling mill for implementing the method according to any one of claims 1-5, characterized in that, The method comprises: A first unit is configured to collect contact geometric parameters and lubricating oil film thickness data between a working roller and a support roller, determine a contact stress distribution state between the working roller and the support roller, and obtain bending deformation amounts of the working roller at different positions by combining a beam bending deformation equation; A second unit is configured to construct a coupling mapping relationship between strip shape distribution and stress distribution considering working roller deformation according to the bending deformation amounts of the working roller and by combining strip shape detection data and strip thickness detection data; A third unit is configured to adaptively adjust compensation coefficients corresponding to the coupling mapping relationship according to a state judgment result of a strip rolling process, establish a dynamic coordination optimization objective function of strip shape and strip thickness, and obtain working roller bending force and support roller displacement amounts satisfying the dynamic coordination optimization objective function through iterative calculation; input strip shape and strip thickness data of each section of the rolling process into a fuzzy rule base to obtain initial control parameters, collect section roller system state parameters to calculate coupling influence coefficients and construct an adaptive coordination function, and correct the working roller bending force and the support roller displacement amounts; A fourth unit is configured to adjust rolling parameters of a cold rolling mill in real time according to the working roller bending force and the support roller displacement amounts, and realize coordination control of strip shape and strip thickness.

7. An electronic device, comprising: The method comprises: A processor; A memory for storing processor-executable instructions; The processor is configured to call the instructions stored in the memory to execute the method of any one of claims 1 to 5.

8. A computer-readable storage medium having stored thereon computer program instructions, wherein, The computer program instructions are executed by the processor to realize the method of any one of claims 1 to 5.

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