Cross-process temper mill rolling force calculation method, device and system and storage medium

Abstract

The invention discloses a cross-process temper mill rolling force calculation method, device and system and a storage medium, and the method comprises the steps: S1, constructing a cold continuous rolling process control model, and S2, obtaining a deformation resistance data set according to the cold continuous rolling process control model; and S3, according to the deformation resistance data set, performing leveling rolling force calculation through data fusion based on cross-process. By the adoption of the technical scheme, the problem that in the prior art, the flattening rolling force precision is low is solved, and therefore the plate shape quality of plate strip steel products is remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of plate and strip steel rolling production, and in particular relates to a method and device, a system and a storage medium for calculating the rolling force of a cross-process leveler. Background Art

[0002] As a key process in the production of plate and strip steel, flattening directly affects the surface quality, mechanical properties and plate shape quality of the product. After cold rolling and annealing, the plate and strip steel is usually thinned by a small deformation amount of flattening to eliminate the yield platform of the strip (generally the elongation after flattening is less than 3%), thereby reducing or eliminating the Luders band phenomenon in the stamping process. Therefore, the setting accuracy of the flattening rolling force directly affects the shape of the load-bearing roll gap, and then affects the threading stability of the unit and the plate shape quality, mechanical properties and surface roughness of the finished strip. Since the pressure reduction of flattening rolling is very small, its deformation mechanism is very different from that of ordinary rolling, so it is difficult for ordinary rolling force models to accurately predict the flattening rolling force. At present, the modeling methods of flattening rolling force can be divided into three categories: mechanism method, intelligent method, and a method combining mechanism or intelligent model with parameter self-learning. Plate and strip production is a typical process industry. The systems of traditional hot rolling and cold rolling processes and production lines are relatively independent. Although the process and quality data of each production process are collected, the multi-dimensional process quality information within the process is still scattered in different systems, and the information cannot be effectively utilized. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a method and device, system, and storage medium for calculating the rolling force of a flat-pass mill across processes, so as to solve the problem of low precision of the flat-pass rolling force in the prior art, thereby significantly improving the plate shape quality of plate and strip steel products.

[0004] To achieve the above object, the present invention adopts the following technical solution:

[0005] A method for calculating rolling force of a skin-pass mill across processes, comprising:

[0006] Step S1, constructing a cold rolling process control model; wherein the cold rolling process control model includes: a rolling force model, a friction coefficient model and a deformation resistance model;

[0007] Step S2, obtaining a deformation resistance data set according to a cold rolling process control model;

[0008] Step S3: According to the deformation resistance data set, a flat rolling force calculation model based on cross-process data fusion is obtained, and at the same time, the actual production data of cold rolling is input into the flat rolling force calculation model for rolling force prediction.

[0009] Preferably, in step S2, according to actual production data of tandem cold rolling, the rolling force model, the friction coefficient model and the deformation resistance model are deformed by inverse calculation based on the deformation resistance of tandem cold rolling to obtain the average actual deformation resistance of each stand of tandem cold rolling.

[0010] Preferably, step S3 comprises:

[0011] The actual deformation resistance of the strip is obtained by inversely solving the average actual deformation resistance of each cold rolling stand;

[0012] According to the average actual deformation resistance of each cold rolling stand and the actual deformation resistance of the strip, a flat rolling force calculation model based on cross-process mechanism-data fusion is constructed;

[0013] The actual production data of cold rolling is input into the temper rolling force calculation model to predict the rolling force.

[0014] The present invention also provides a cross-process skin-pass mill rolling force calculation device, comprising:

[0015] A construction module is used to construct a cold rolling process control model; wherein the cold rolling process control model includes: a rolling force model, a friction coefficient model and a deformation resistance model;

[0016] A calculation module, used to obtain a deformation resistance data set according to a cold rolling process control model;

[0017] The prediction module is used to obtain a flat rolling force calculation model based on cross-process data fusion according to the deformation resistance data set, and at the same time input the actual production data of cold rolling into the flat rolling force calculation model for rolling force prediction.

[0018] Preferably, the calculation module deforms the rolling force model, friction coefficient model and deformation resistance model according to the actual production data of cold rolling by inverse calculation based on the deformation resistance of cold rolling to obtain the average actual deformation resistance of each cold rolling frame.

[0019] Preferably, the prediction module comprises:

[0020] A calculation unit, used for inversely solving the average actual deformation resistance of each cold rolling stand to obtain the actual deformation resistance of the strip;

[0021] A construction unit is used to construct a temper rolling force calculation model based on cross-process mechanism-data fusion according to the average actual deformation resistance of each cold rolling stand and the actual deformation resistance of the strip;

[0022] The prediction unit is used to input the actual production data of cold rolling into the flat rolling force calculation model to predict the rolling force.

[0023] An embodiment of the present invention also provides a cross-process flat-pass mill rolling force calculation system, comprising: a memory and a processor, wherein the memory stores a computer program run by the processor, and when the computer program is run by the processor, it executes a cross-process flat-pass mill rolling force calculation method.

[0024] An embodiment of the present invention further provides a storage medium having a computer program stored thereon, and the computer program executes a method for calculating the rolling force of a flat-pass mill across processes when the computer program is run.

[0025] The present invention establishes a deformation resistance back-calculation model through numerical simulation modeling and accumulation of production data using actual data from the upstream cold rolling process. On this basis, the cold rolling deformation resistance is applied to the flattening mill, and a cross-process flattening rolling force calculation model is established to solve the problem of low precision of flattening rolling force in the prior art, thereby significantly improving the plate shape quality of plate and strip steel products. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0027] Figure 1 This is a flow chart of a method for calculating rolling force of a skin-pass mill across processes according to an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of the mesh division of the working roll and the strip steel, where: Figure 2 (a) is a schematic diagram of the overall mesh division of the working roll. Figure 2 (b) is a schematic diagram of the local mesh division of the working roll. Figure 2 (c) is a schematic diagram of the grid division of the contact position between the working roll and the strip;

[0029] Figure 3 This is a schematic diagram of the vertical reaction force at the center of the working roll during stable rolling;

[0030] Figure 4 This is a schematic diagram of the flattened shape after leveling;

[0031] Figure 5 Schematic diagram of contact arc length under different strip elongation rates;

[0032] Figure 6 Schematic diagram of contact arc length under different strip yield strengths;

[0033] Figure 7Schematic diagram of contact arc length under different friction coefficients;

[0034] Figure 8 Schematic diagram of contact arc length under different working roll diameters;

[0035] Fig. 9 Schematic diagram of contact arc length under different thicknesses;

[0036] Fig.10 Schematic diagram of contact arc length under different tensions;

[0037] Fig.11 It is a schematic diagram of the particle swarm algorithm process;

[0038] Fig.12 Schematic diagram of the comparison between actual rolling force and predicted rolling force. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0041] Embodiment 1:

[0042] like Figure 1 As shown, an embodiment of the present invention provides a method for calculating the rolling force of a skin-pass mill across processes, comprising:

[0043] Step S1: Establishing a cold rolling process control model

[0044] 1) Rolling force model

[0045] Rolling force is the core part of the cold rolling process setting. The calculation result of the rolling force model is the basis for the roll gap setting. Therefore, the accuracy of the rolling force model will directly affect the thickness and shape quality of the strip. At the same time, the rolling force setting is also the basis for some setting calculations in the cold rolling process control, and its influence involves the entire cold rolling cycle. The rolling force model used in this article is the Bland-Ford-Hill model, and the form of the rolling force model is shown in the formula.

[0046]

[0047] Among them, P is the rolling force, B is the strip width, is the dynamic deformation resistance of the i-th rack, k T is the tension influence coefficient, Q s is the stress state coefficient; R' i is the flattening radius of the working roll of the i-th stand, H i is the inlet thickness of the i-th rack, h i is the outlet thickness of the i-th rack.

[0048] Among them, the stress state coefficient of the model is expressed as:

[0049]

[0050] in, is the pass reduction rate of the i-th rack; μ i is the friction coefficient.

[0051] The calculation formula for the pass reduction rate is shown in the formula.

[0052]

[0053] The flattening radius of the working roll can be calculated by the following formula, in which both the rolling force and the flattening radius are present, which can be achieved by iterative or explicit calculation.

[0054]

[0055] Among them, v i is the rolling speed of the ith stand, and E is the elastic modulus of the working roll.

[0056] The tension in the cold rolling process is a factor that cannot be ignored. The tension factor in the rolling force model is expressed by the tension influence coefficient, as shown in the formula.

[0057]

[0058] in, is the front tension of the i-th rack, is the back tension of the i-th rack; is the dynamic deformation resistance of the i-th rack.

[0059] 2) Friction coefficient model

[0060] In the cold rolling process, the friction state between the strip and the working roll is expressed by the friction coefficient. The factors affecting the friction coefficient include the surface conditions of the strip and the roll, the rolling lubrication state, the rolling speed, etc. In the relevant setting calculation of the cold rolling process control level, the calculation accuracy of the friction coefficient will affect the calculation accuracy of the rolling force, so the setting of the friction coefficient has an important influence on the product quality. The friction coefficient model used in the present invention is shown in the following formula.

[0061]

[0062] Among them, μ0~μ6 are the model parameters of the mold friction coefficient; N r It is the number of rolled coils after roll change.

[0063] 3) Deformation resistance model

[0064] Deformation resistance is an important control parameter in the cold rolling process. As an important module in the calculation of the rolling force model, it is also the core part of the high-precision plate shape control calculation. The deformation resistance of the strip mainly depends on the yield limit of the material, but the cold rolling process is a three-dimensional plastic deformation process of metal materials after multiple processing. Therefore, the deformation resistance of cold rolling is affected by the process such as deformation degree and deformation speed, and cannot be directly characterized by the yield limit. At the same time, it is also affected by the metal processing hardening effect. The deformation resistance in the cold rolling process is a complex setting parameter that integrates material properties and process characteristics.

[0065] One of the main factors affecting deformation resistance is the deformation degree of the material. According to the production mode of cold rolling process, several reduction rates of the material are first defined, as shown in the formula.

[0066]

[0067] in, is the rolling reduction rate of the i-th stand; is the rolling reduction rate of the i-th stand; is the average pressing rate of the i-th rack; a r It is an empirical value, usually 0.75.

[0068] According to the above-mentioned reduction rates, the static deformation resistance is shown in the formula.

[0069]

[0070] in, is the static deformation resistance of the i-th stand, k0 is the deformation resistance reference value, which is related to the inherent properties of the material; m and n are model coefficients, and their values ​​are related to the material properties and the cold rolling hardening effect.

[0071] In order to make the deformation resistance model more consistent with the actual rolling situation, the influence of deformation rate is added on the basis of considering the deformation degree, and the deformation resistance calculated by considering the deformation rate is called dynamic deformation resistance. Dynamic deformation resistance is now widely used in cold rolling process settings. The calculation of deformation rate can be obtained according to the S.Ekelend formula, as shown in the formula.

[0072]

[0073] Among them, ε i is the deformation rate of the i-th rack.

[0074] Combining the above formulas, we can get the dynamic deformation resistance calculation formula, as shown in the formula.

[0075]

[0076] Where η is the strain rate sensitivity coefficient.

[0077] Step S2: Establishing a deformation resistance data set based on the inverse calculation of cold rolling deformation resistance

[0078] 1) Collect and process cold rolling data

[0079] The actual historical production data of the cold rolling mill is obtained through the cold rolling mill data platform. The data of the cold rolling mill mainly includes the hot rolling incoming coil number, cold rolling export coil number, steel grade, entrance thickness, entrance width, and the reduction rate, rolling force, entrance tension, etc. of each frame. The data is preprocessed and the empty values ​​in the data are deleted; there are multiple rows of identical data in the data. It is known that each roll of strip steel has a different export coil number. The export coil number can be screened to delete the redundant data; the data that is obviously illogical in the data is processed, and the processed data is saved in preparation for establishing a deformation resistance prediction model.

[0080] 2) Back calculation of cold rolling deformation resistance

[0081] In the current cold rolling process, there is no effective means to detect the actual deformation resistance of the strip during the rolling process of each stand. In the process of establishing a deformation resistance prediction model, the actual deformation resistance is an indispensable data. The actual deformation resistance can be obtained by inverse calculation of the deformation resistance. The principle is to use the rolling force in the rolling force model as a known quantity based on the measured rolling force, replace other process data with measured values, and perform inverse calculation on the deformation resistance as an unknown quantity to obtain the actual deformation resistance.

[0082] According to the deformation resistance model and rolling force model described in the previous section, the rolling force is taken as a known quantity and the deformation resistance is taken as an unknown quantity, and the rolling force formula is separated to obtain the following formula.

[0083]

[0084] in, is the actual deformation resistance, k' T is the measured tension coefficient; P mea is the measured rolling force, Q' S is the stress state coefficient of the measured thickness; are the measured inlet thickness and outlet thickness.

[0085] Expand the tension coefficient on the left side of the above equation and let the right side of the equation be A1, then the equation is as follows.

[0086]

[0087] in, is the measured front tension, It is the measured tension.

[0088] Upward After separation and arrangement, the inverse operation model of deformation resistance is obtained, as shown in the formula.

[0089]

[0090] By back-calculating the production data of the cold rolling mill using this formula, the average actual deformation resistance of each roll of strip in each rack can be obtained, which serves as the data resource basis for the next step of establishing the prediction model.

[0091] Step S3: Calculation of temper rolling force based on cross-process mechanism-data fusion

[0092] In actual production, the deformation mechanism of temper rolling is very different from that of cold rolling. It is difficult for traditional rolling force models to accurately predict the temper rolling force. The large deviation between the setting of rolling force and the actual rolling force will lead to fluctuations in the elongation of the plate and strip steel, which will have an adverse effect on the surface roughness and plate shape control. Domestic and foreign scholars have developed a variety of temper rolling force calculation models. For example, Roberts WL developed a set of explicit calculation models for temper rolling force based on the process characteristics of temper rolling. However, the derivation of this model is based on a large reduction rate and cannot be directly used for rolling conditions with a small elongation. The rolling force calculated using the temper rolling force formula has a large error with the actual rolling force. Therefore, by analyzing the reasons for the calculation error of the Roberts temper rolling force formula, at the same time, in the temper rolling process, deformation resistance is one of the important factors affecting the temper rolling force, but the deformation resistance cannot be accurately obtained. Considering the use of cross-process data combined with actual production data to optimize the calculation model, a temper rolling force calculation model based on cross-process mechanism-data fusion is established.

[0093] 1) Classical temper rolling force calculation model

[0094] The Roberts temper rolling force calculation formula is as follows:

[0095] P=fB

[0096]

[0097] Among them, P is the rolling force, f is the rolling force per unit width, B is the strip width, L is the contact arc length between the roll and the strip in the rolling deformation zone, D is the working roll diameter, ε is the strip elongation, μ is the friction coefficient, h0 is the entrance thickness, σ p is the deformation resistance, is the strain rate, v is the rolling speed, a is the strain rate coefficient, σ s It is the yield strength measured under very low tensile strain rate conditions.

[0098] Select the actual production data of a certain leveling unit, the selected data range is shown in the table below, and select 49 groups of data in the unit within the above range. Substitute the selected data into the Roberts leveling rolling force calculation formula and compare it with the actual production rolling force. The result obtained by the Roberts calculation model differs from the actual leveling rolling force data by about 6.9 times.

[0099] Table 1

[0100] parameter Numerical range Elongation / % 0.7 Yield strength / MPa 180 Thickness range / mm 0.6—0.7 Width range / mm 1500—1600 <![CDATA[Rolling speed range / m·min -1 > 101—109 Inlet tension / kN 34—45.6 Outlet tension / kN 40—50.64

[0101] Based on the actual tempering rolling force, the Roberts formula was used for back calculation, and the average value of the calculated contact arc length was 9.2 mm. However, this value is significantly different from the empirical value of the contact arc length between the working roll and the strip during the tempering process. During the tempering process, the calculation accuracy of the contact arc length is directly related to the calculation accuracy of the tempering rolling force, and is a key factor in ensuring the accuracy of the rolling force calculation.

[0102] 2) Two-dimensional finite element model of temper rolling process

[0103] As mentioned in the previous section, the traditional contact arc length calculation formula has a large error when used to calculate the contact arc length of the leveling process. Therefore, the simulation of the leveling process will be used as a means to calculate the contact arc length between the working roll and the strip under different working conditions.

[0104] ① Model simplification and assumptions

[0105] Assuming that the strip is an ideal elastic-plastic body with finite length, assuming that the rolling process is symmetrical in the vertical direction, establishing a 1 / 2 model, and assuming that the working roll is an elastic body. Table 2 shows the material properties of the working roll and strip.

[0106] Table 2

[0107] parameter Numeric Working roll elastic model / MPa 225000 Poisson's ratio of working roll 0.3 Working roll density <![CDATA[7.85×10 3 ]]> Strip steel elastic model / MPa 206000 Poisson's ratio of strip steel 0.3 Strip density <![CDATA[7.85×10 3 ]]>

[0108] ②Interaction settings

[0109] The work roll and the strip are kept tangent in the initial geometry, and the type of interaction is surface-to-surface contact, where the work roll surface is the master surface and the strip surface is the slave surface. The normal contact is hard contact, and the tangential contact property is penalty. In order to facilitate the application of load at the center of the work roll, a small circle with a radius of 25 mm is divided at the center of the work roll and constrained as a rigid body.

[0110] ③Analysis step setting

[0111] The simulation process is divided into three analysis steps, namely, applying tension, working roll reduction and rolling. The analysis step type is static general, and geometric nonlinearity is turned on.

[0112] ④Load and boundary conditions

[0113] A reference point RP is established at the center of the work roll, and a downward displacement perpendicular to the strip is applied. A symmetric constraint in the vertical direction is applied to the lower surface of the strip, and a normal load is applied to the head and tail end faces of the strip to simulate the tension of the strip. A rotation angle is applied at the reference point RP at the center of the work roll to simulate the rotation of the work roll.

[0114] ⑤ Grid division and unit selection

[0115] The unit type of the working roll and the strip steel is CPE4R. The mesh size of the working roll is larger than the mesh size of the strip steel. Figure 2 (a) shows a schematic diagram of mesh division of the overall structure of the working roll. In the model, only the 30° sector of the contact area between the working roll and the strip is finely meshed to improve the calculation efficiency. Figure 2 As shown in (b); the grid size of the contact area between the working roll and the strip is 0.1×0.1mm, the grid size of the strip is 0.05×0.05mm, and the grid division of the contact area between the working roll and the strip is as follows Figure 2 As shown in (c), the total number of finite element model elements is 168176.

[0116] 3) Two-dimensional finite element simulation study on the flattening deformation behavior of working rolls

[0117] ① Analysis of elastic-plastic deformation of working rolls and strip steel in rolling zone

[0118] A set of working conditions of the skin-pass mill during the skin-pass rolling process is selected for simulation. The working roll diameter is 650 mm, the working roll linear speed is 80 m / min, the strip inlet thickness is 0.5 mm, the strip elongation is 2.8%, the yield strength is 400 MPa, the strip tension before and after is 40.2 MPa, and the friction coefficient between the working roll and the strip is 0.12.

[0119] When the model is in stable rolling, the average rolling force per unit plate width is 3188N, as follows Figure 3 As shown, the surface displacement of the strip in the rolling zone is as follows Figure 4 shown.

[0120] ②Effect of strip yield strength on contact arc length

[0121] The parameters that affect the contact arc length during the simulation process are shown in Table 3.

[0122] Table 3

[0123]

[0124] like Figures 5 to 6 As shown in the figure, with the increase of the elongation of the strip during the flattening process, the contact arc length increases almost linearly. When the elongation is 0.8%, the contact arc length is 5.5mm, and when the elongation is 3%, the contact arc length is 6.47mm. With the increase of the yield strength of the strip, the contact arc length increases. When the yield strength increases from 250MPa to 550MPa, the contact arc length increases from 5.61 to 11.25mm.

[0125] like Figures 7 to 8 As shown in the figure, as the friction coefficient between the working roll and the strip increases, the contact arc length increases. The friction coefficient increases from 0.06 to 0.15, and the contact arc length increases from 4.23 to 6.3 mm. As the diameter of the working roll increases, the contact arc length increases. The diameter of the working roll increases from the minor diameter of 600 mm to 650 mm, and the contact arc length increases from 3.84 to 5.61 mm.

[0126] like Figures 9 to 10 As shown in the figure, with the increase of strip thickness, the contact arc length increases, the thickness increases from 0.3mm to 1.2mm, and the contact arc length increases from 5.4 to 6.25mm; with the increase of tension, the contact arc length decreases, the tension increases from 0 to 30% of the yield strength, and the contact arc length shortens from 6.59mm to 5.31mm.

[0127] ③ Data-mechanism fusion model of temper rolling force

[0128] Based on the influence of strip thickness, working roll diameter, elongation and other parameters on the contact arc length in the previous section, the contact arc length formula in the Roberts temper rolling force formula is reconstructed as shown below.

[0129] P=fB

[0130]

[0131] Table 4 shows the names of the parameters and the units used for calculation. All units are in the International System of Units.

[0132] Table 4

[0133]

[0134] Among them, k0-k8 are the coefficients to be optimized in the contact arc length formula.

[0135] ④ Cross-process mechanism-data fusion flat rolling force calculation model

[0136] In the original flat rolling force calculation formula, the value of deformation resistance is a relatively fixed value for the same type of strip steel. However, in fact, the deformation resistance of the strip steel will be affected by many factors, such as deformation temperature, deformation rate, deformation degree, etc. The strip steel of the same type will produce different deformation resistance. Therefore, the use of the above formula cannot reflect the actual deformation resistance of the strip steel.

[0137] In order to reflect the real deformation resistance of the strip, the previous cold rolling process of the flattening process was selected, and the actual production data of cold rolling was used to solve the actual deformation resistance of the strip through the inverse calculation formula of deformation resistance. This actual deformation resistance value was applied to the flattening rolling force calculation model of mechanism-data fusion, and the flattening rolling force calculation model of cross-process mechanism-data fusion was established.

[0138] P=fB

[0139]

[0140] Among them, the relationship between each factor and the contact arc length determines the value range of each unknown parameter, as shown in Table 5.

[0141] Table 5

[0142]

[0143]

[0144] The real data of the skin-pass mill is used as samples, and the inlet material number of the strip is matched to the production data of the cold rolling mill to inversely calculate the actual deformation resistance. 80% of the samples are selected for parameter training and optimization, and the remaining 20% ​​are used for prediction. The parameter optimization algorithm is the particle swarm algorithm. Fig.11 As shown in Figure 2, the particle swarm algorithm process is as follows:

[0145] ④ Cross-process mechanism-data fusion flat rolling force calculation model prediction results

[0146] The predicted value of the temper rolling force calculation model using cross-process mechanism-data fusion is as follows Fig.12 As shown, the relative error between the data prediction value and the actual value is within 15%, 94.02%. The established cross-process mechanism-data flat rolling force prediction calculation model has high accuracy.

[0147] Embodiment 2:

[0148] The embodiment of the present invention further provides a cross-process skin-pass mill rolling force calculation device, comprising:

[0149] A construction module is used to construct a cold rolling process control model; wherein the cold rolling process control model includes: a rolling force model, a friction coefficient model and a deformation resistance model;

[0150] A calculation module, used to obtain a deformation resistance data set according to a cold rolling process control model;

[0151] The prediction module is used to obtain a flat rolling force calculation model based on cross-process data fusion according to the deformation resistance data set, and at the same time input the actual production data of cold rolling into the flat rolling force calculation model for rolling force prediction.

[0152] As an implementation mode of an embodiment of the present invention, the calculation module deforms the rolling force model, friction coefficient model and deformation resistance model according to the actual production data of cold rolling through inverse calculation based on the deformation resistance of cold rolling, so as to obtain the average actual deformation resistance of each cold rolling frame.

[0153] As an implementation of an embodiment of the present invention, the prediction module includes:

[0154] A calculation unit, used for inversely solving the average actual deformation resistance of each cold rolling stand to obtain the actual deformation resistance of the strip;

[0155] A construction unit is used to construct a temper rolling force calculation model based on cross-process mechanism-data fusion according to the average actual deformation resistance of each cold rolling stand and the actual deformation resistance of the strip;

[0156] The prediction unit is used to input the actual production data of cold rolling into the flat rolling force calculation model to predict the rolling force.

[0157] Embodiment 3:

[0158] An embodiment of the present invention also provides a cross-process flat mill rolling force calculation system, comprising: a memory and a processor, wherein the memory stores a computer program run by the processor, and the computer program executes a cross-process flat mill rolling force calculation method when run by the processor.

[0159] Embodiment 4:

[0160] An embodiment of the present invention further provides a storage medium, on which a computer program is stored, and when the computer program is run, a method for calculating the rolling force of a flat-pass mill across processes is executed.

[0161] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for calculating the rolling force of a skin-pass mill across processes, characterized in that: include: Step S1, constructing a cold rolling process control model; wherein the cold rolling process control model includes: a rolling force model, a friction coefficient model and a deformation resistance model; Step S2, obtaining a deformation resistance data set according to a cold rolling process control model; Step S3: According to the deformation resistance data set, a flat rolling force calculation model based on cross-process data fusion is obtained, and at the same time, the actual production data of cold rolling is input into the flat rolling force calculation model for rolling force prediction.

2. The method for calculating the rolling force of a skin-pass mill across processes according to claim 1, characterized in that: In step S2, according to actual production data of cold rolling, the rolling force model, friction coefficient model and deformation resistance model are deformed by inverse calculation based on the deformation resistance of cold rolling to obtain the average actual deformation resistance of each stand of cold rolling.

3. The method for calculating the rolling force of a skin-pass mill across processes according to claim 2, characterized in that: In step S2, step S3 includes: The actual deformation resistance of the strip is obtained by inversely solving the average actual deformation resistance of each cold rolling stand; According to the average actual deformation resistance of each cold rolling stand and the actual deformation resistance of the strip, a flat rolling force calculation model based on cross-process mechanism-data fusion is constructed; The actual production data of cold rolling is input into the temper rolling force calculation model to predict the rolling force.

4. A rolling force calculation device for a cross-process skin-pass mill, characterized in that: include: A construction module is used to construct a cold rolling process control model; wherein the cold rolling process control model includes: a rolling force model, a friction coefficient model and a deformation resistance model; A calculation module, used to obtain a deformation resistance data set according to a cold rolling process control model; The prediction module is used to obtain a flat rolling force calculation model based on cross-process data fusion according to the deformation resistance data set, and at the same time input the actual production data of cold rolling into the flat rolling force calculation model for rolling force prediction.

5. The rolling force calculation device for a skin-pass mill across processes according to claim 4, characterized in that: In step S2, the calculation module deforms the rolling force model, the friction coefficient model and the deformation resistance model according to the actual production data of the cold rolling by inverse calculation based on the deformation resistance of the cold rolling, so as to obtain the average actual deformation resistance of each frame of the cold rolling.

6. The rolling force calculation device for a skin-pass mill across processes according to claim 5, characterized in that: In step S2, the prediction module includes: A calculation unit, used for inversely solving the average actual deformation resistance of each cold rolling stand to obtain the actual deformation resistance of the strip; A construction unit is used to construct a temper rolling force calculation model based on cross-process mechanism-data fusion according to the average actual deformation resistance of each cold rolling stand and the actual deformation resistance of the strip; The prediction unit is used to input the actual production data of cold rolling into the flat rolling force calculation model to predict the rolling force.

7. A cross-process skin-pass mill rolling force calculation system, characterized in that: include: A memory and a processor, wherein the memory stores a computer program executed by the processor, and when the computer program is executed by the processor, the method for calculating the rolling force of a cross-process flat-pass mill as described in any one of claims 1 to 3 is executed.

8. A storage medium, characterized in that: The storage medium stores a computer program, which executes the method for calculating the rolling force of a cross-process skin-pass mill as claimed in any one of claims 1 to 3 when running.

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