Optimization method for predicting end plane shape of plate, storage medium, and device
By optimizing the calculation method of the longitudinal length difference at the end of the rolled piece, and combining the metal volume ratio and rolling process parameters, the end planar shape curve is fitted, which solves the problem of insufficient prediction accuracy of the existing model at the beginning and end of the rolled piece, and improves the prediction accuracy of the planar shape in the rolling process of medium and heavy plates.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- YANSHAN UNIV
- Filing Date
- 2023-05-06
- Publication Date
- 2026-04-14
AI Technical Summary
Existing planar shape prediction models cannot effectively distinguish between the beginning and end of the rolled piece during the rolling process, resulting in insufficient prediction accuracy.
By acquiring the original data of the rolled piece and the rolling process parameters, important parameters in the rolling process, such as the length of the rolling deformation zone, the length of the forward slip zone, the length of the backward slip zone, and the bite angle, are calculated. Combined with the metal volume ratio, the longitudinal length difference at the end of the rolled piece is optimized, and the end planar shape curve is fitted to improve the prediction accuracy.
It improves the accuracy of end planar shape prediction for medium and heavy plate rolled products without the need for additional hardware. The calculation is simple and highly applicable, and the optimized prediction results have a high degree of agreement with the actual results.
Smart Images
Figure CN116511259B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of automatic control technology for metallurgical rolling, and more particularly to an optimization method for addressing the insufficient end shape prediction accuracy of existing planar shape prediction models in the rolling process of medium and heavy plates. Background Technology
[0002] As a high-energy-consuming industry, the steel industry's equipment and technology are inevitably developing towards higher efficiency, lower consumption, and green environmental protection. Medium and heavy plates, as representative steel products, benefit from the widespread application of planar shape control technology in the rolling process, which is an effective means to improve product yield, reduce cutting rates, and increase economic efficiency.
[0003] Planar shape control technology is a rolling control technique that uses variable thickness rolling to minimize irregular shapes of the rolled piece, making its planar shape tend towards a rectangle. The core of this technology is a planar shape prediction model that effectively and accurately predicts the planar shape of the rolled piece during the rolling process.
[0004] Existing planar shape prediction models mostly employ a slitting approach. The core idea is to establish multiple hypothetical slits along the longitudinal direction of the rolled piece. Due to the widening of the rolled piece during rolling, the longitudinal length of each slit after rolling is obtained based on the principle of constant metal volume. Then, a planar shape curve for the end of the rolled piece is fitted based on the longitudinal lengths of each slit. Currently used planar shape prediction models do not distinguish between the beginning and end of the rolled piece during calculation. However, extensive experimental results show that there are significant differences in the planar shape between the beginning and end of the rolled piece after rolling. Therefore, the prediction accuracy of existing planar shape prediction models needs improvement. Summary of the Invention
[0005] In view of the shortcomings of the prior art, the present invention provides an optimization method to optimize the existing planar shape prediction model, so that the calculation results are closer to the actual situation, thereby improving the prediction accuracy.
[0006] The technical means employed in this invention are as follows:
[0007] An optimization method for predicting the end planar shape of a medium-thick plate includes the following steps:
[0008] Acquire the raw data of the rolled piece, target size data, prediction results of the existing planar shape prediction model, and rolling process parameters;
[0009] Based on the original data of the rolled piece, the target dimensions of the rolled piece, and the rolling process parameters, the important parameters in the rolling process are determined. These important parameters include: the length of the rolling deformation zone, the length of the forward sliding zone, the length of the backward sliding zone, the lateral width on one side, and the bite angle.
[0010] Based on the original data of the rolled piece and the rolling process data, calculate the metal volume of the overall deformation zone, the metal volume of the forward sliding zone and its proportion in the overall deformation zone, and the metal volume of the backward sliding zone and its proportion in the overall deformation zone during the rolling process.
[0011] Calculate the proportion of the maximum longitudinal length difference of the rolled piece in the overall length difference based on the metal volume ratio in the front and rear sliding zones.
[0012] Calculate the maximum length difference between the first and last ends of each strip based on the percentage of the maximum length difference at the ends.
[0013] By combining the width and lateral width data of each imaginary strip in the planar shape prediction model, the endpoint coordinates of the two ends of each imaginary strip can be obtained. Based on the endpoint coordinates, a planar shape curve of the rolled piece end is fitted, thereby optimizing the planar shape prediction.
[0014] The present invention also discloses a storage medium comprising a stored program, wherein, when the program is executed, the above-described optimization method for predicting the end planar shape of a medium-thick plate is performed.
[0015] The present invention also discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-described optimization method for predicting the end planar shape of a medium-thick plate through the computer program.
[0016] Compared with the prior art, the present invention has the following advantages:
[0017] 1) This invention optimizes the shortcomings of existing planar shape prediction models by using existing technical parameters to achieve the optimization process without adding any additional software or hardware.
[0018] 2) The concept of longitudinal length difference at the end of the rolled piece is proposed. The maximum longitudinal length difference at the end is used to describe the planar shape of the irregular part at the corresponding end of the rolled piece. The optimization idea is simple and clear.
[0019] 3) The optimization method described in this invention is simple to calculate, highly applicable, and has a significantly improved prediction accuracy for the end planar shape of medium and heavy plates compared to existing models. Attached Figure Description
[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0021] Figure 1This is a flowchart of an optimization method for predicting the end planar shape of a medium-thick plate according to the present invention.
[0022] Figure 2 This is a schematic diagram of the overall rolling deformation zone division in an embodiment of the present invention.
[0023] Figure 3 This is a schematic diagram of the back-slip zone division in an embodiment of the present invention.
[0024] Figure 4 This is a curve showing the difference in longitudinal length at the ends of each slit after the first rolling pass in an embodiment of the present invention.
[0025] Figure 5a This is a comparison curve of the optimization results of the fifth longitudinal length inspection at the first end in this embodiment of the invention.
[0026] Figure 5b This is a comparison curve of the optimization results of the fifth longitudinal length inspection at the tail end in this embodiment of the invention.
[0027] Figure 6a This is a comparison curve of the optimization results of the first longitudinal length inspection at the 10th stage in this embodiment of the invention.
[0028] Figure 6b This is a comparison curve of the optimization results of the longitudinal length inspection at the tail end in the 10th pass of this invention.
[0029] Figure 7a This is a comparison curve of the optimization results of the first longitudinal length inspection at the 15th stage in this embodiment of the invention.
[0030] Figure 7b This is a comparison curve of the optimization results of the longitudinal length inspection at the tail end in the 15th pass of this invention. Detailed Implementation
[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.
[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0033] The overall process of the optimization method for predicting the end planar shape of a medium-thick plate involved in this invention is as follows: Figure 1 As shown, the specific implementation steps include the following:
[0034] a. Determine the raw data of the rolled piece, including: width, length, thickness, steel grade, roll diameter, and friction coefficient between the rolled piece and the roll. b. Determine the target dimensional data of the rolled piece, including: post-roll width, post-roll thickness, and post-roll length. c. Determine the prediction results of the existing planar shape prediction model, including: the preset number of slits in the planar shape prediction process, and the post-roll length and width of each slit. d. Determine some process parameters during the rolling process, including: rolling passes and reduction rate.
[0035] In this embodiment, the rolled lead specimen underwent necessary machining to ensure uniform thickness and width. The specific dimensions were: thickness 16mm, width 90mm, and length 70mm. The rolling process involved 15 conventional unidirectional rolling passes along the length direction. The first 10 passes had a reduction of 0.6mm per pass, and the last 5 passes had a reduction of 1.2mm per pass. Specific rolling process parameters are shown in Table 1.
[0036] Table 1 Rolling Procedure of Examples
[0037] Rolling passes Thickness / mm Width / mm Indentation / mm reduction rate Width-to-thickness ratio 1 16.0 96.00 0.6 0.038 6.00 2 15.4 96.30 0.6 0.039 6.25 3 14.8 96.06 0.6 0.041 6.49 4 14.2 96.08 0.6 0.042 6.77 5 13.6 96.18 0.6 0.044 7.07 6 13.0 96.36 0.6 0.046 7.41 7 12.4 96.54 0.6 0.048 7.79 8 11.8 96.54 0.6 0.051 8.18 9 11.2 96.68 0.6 0.054 8.63 10 10.6 96.80 0.6 0.057 9.13 11 9.4 96.88 1.2 0.128 10.31 12 8.2 96.90 1.2 0.146 11.82 13 7.0 97.00 1.2 0.171 13.86 14 5.8 97.06 1.2 0.207 16.73 15 4.6 97.10 1.2 0.261 21.11
[0038] The rolling mill roll used in this embodiment has a diameter of 110mm and a friction coefficient of 0.11 between the workpiece and the roll.
[0039] Taking the first pass of this embodiment as an example, the rolled piece is divided into 11 imaginary slivers along the longitudinal direction. After the first pass of rolling, the longitudinal length difference between the 2nd to the 10th slivers can be calculated using an existing planar shape prediction model, as shown in Table 2:
[0040] Table 2. Differences in longitudinal length of each hypothetical strip in the first row.
[0041] Segmentation 2 3 4 5 6 7 8 9 10 ΔLi / mm 0.446 0.582 0.678 0.720 0.792 0.734 0.706 0.640 0.468
[0042] b. Determine some important parameters in the rolling process, including: the length of the rolling deformation zone l, the length of the front slip zone l1, the length of the back slip zone l2, the lateral width on one side u, and the bite angle α.
[0043] Taking the first pass in this embodiment as an example, the calculated length of the rolling deformation zone is 5.54 mm, the length of the front sliding zone is 1.89 mm, the length of the rear sliding zone is 3.65 mm, the lateral width on one side is 0.02 mm, and the bite angle is 5.78.
[0044] c. Calculate the metal volume of the overall deformation zone, the metal volume of the front slip zone and its proportion in the overall deformation zone, and the metal volume of the back slip zone and its proportion in the overall deformation zone during the rolling process.
[0045] c1. Determine the formula for calculating the metal volume within the overall rolling deformation zone, such as... Figure 2 As shown, one-quarter of the metal in the rolling deformation zone is taken for study and divided into four parts, such that V = V1 + V2 + V3 + V4, as shown in the attached figure. Figure 1 As shown. Based on the original data of the workpiece, the target dimensions of the workpiece, the rolling process parameters, and the geometric relationship between the workpiece and the rolls, the four parts are solved separately and then summed to obtain the formula for calculating the volume V of 1 / 4 of the metal in the rolling deformation zone:
[0046]
[0047] Taking the first pass in this embodiment as an example, the volume of 1 / 4 of the metal in the rolling deformation zone is 2034 mm². 3 .
[0048] c2. Determine the metal volume V within the backslip zone. b Calculation formula. The calculation approach is consistent with the approach for calculating the metal volume within the overall deformation zone, such as... Figure 3 As shown, the backslide is divided into 4 parts, each calculated separately and then summed. The calculation formula is:
[0049]
[0050] Taking the first pass in this embodiment as an example, the 1 / 4 metal volume in the back slide zone is 1328 mm². 3 .
[0051] c3. Determine the formula for calculating the metal volume of the front slip zone. According to formulas (1) and (2), the metal volume in the overall deformation zone and the metal volume of the back slip zone can be calculated. Based on the geometric relationship of the rolling deformation zone, the metal volume V of the front slip zone is calculated. f The calculation formula can be expressed as:
[0052] V f =VV b (3)
[0053] Taking the first pass in this embodiment as an example, the 1 / 4 metal volume in the front sliding zone is 706 mm². 3 .
[0054] c4. Calculations show that during the first rolling process in this embodiment, the metal volume ratio in the front sliding zone is 0.35, and the metal volume ratio in the back sliding zone is 0.65.
[0055] d. Calculate the proportion of the maximum longitudinal length difference of the rolled piece in the overall length difference based on the metal volume ratio in the front and rear sliding zones.
[0056] First, apply the adjustment coefficient formula:
[0057]
[0058] The first-end adjustment coefficient in this embodiment can be calculated to be -0.065, and the last-end adjustment coefficient is 0.065.
[0059] The functional relationship between the proportion of the maximum length difference at the application ends in the total length difference and the corresponding proportion of the metal volume in the sliding zone is as follows:
[0060]
[0061] The percentage of the maximum length difference at the beginning of the first rolling pass in this embodiment can be calculated as 0.282, and the percentage of the maximum length difference at the end is 0.718.
[0062] e. Calculate the maximum length difference at the beginning and end of each sliver based on the proportion of the maximum length difference at the ends. Assuming the overall length difference of each imaginary sliver on the rolled piece surface is uniformly distributed across the beginning and end, the distribution ratio of the longitudinal length difference of imaginary slivers 2 to 10 at the beginning and end can be calculated based on the maximum longitudinal length difference L at both ends of the rolled piece. f and L b The proportion in ΔL is calculated as follows:
[0063]
[0064] Taking the first pass of this embodiment as an example, the calculation results of the maximum length difference between the first and last ends of each hypothetical sliver after the first pass of rolling are as follows: Figure 3 As shown:
[0065] Table 3. Difference in longitudinal length at the ends of each hypothetical strip in the first pass.
[0066] Segmentation 2 3 4 5 6 7 8 9 10 <![CDATA[ΔL i mm]]> 0.446 0.582 0.678 0.720 0.792 0.734 0.706 0.640 0.468 <![CDATA[ΔL if mm]]> 0.126 0.164 0.191 0.203 0.223 0.207 0.199 0.180 0.132 <![CDATA[ΔL ib mm]]> 0.320 0.418 0.487 0.517 0.569 0.527 0.507 0.460 0.336
[0067] f. Combining the width and lateral spread data of each imaginary strip in the planar shape prediction model, the endpoint coordinates of both ends of each imaginary strip can be obtained. Based on the endpoint coordinates, the planar shape of the rolled piece end can be fitted, as shown in the attached figure. Figure 4 As shown, this optimizes the prediction of the end planar shape of the rolled piece. The optimization result serves as the input for the planar shape data of the next rolling pass, providing data support for the optimization calculation of the planar shape prediction of the next rolling pass.
[0068] By applying the optimization method of the present invention, the prediction results of subsequent rolling passes are optimized. The unoptimized data, optimized data and actual measurement results of each hypothetical strip in each pass are compared with the curve graphs, as shown in Figures 5, 6 and 7. After 5, 10 and 15 rolling passes, the optimized data and the actual measurement data have a high degree of agreement. Compared with the prediction results without optimization, the prediction accuracy is significantly improved. The optimization method for predicting the end planar shape of medium and heavy plates involved in the present invention is feasible and effective.
[0069] The present invention also discloses a storage medium comprising a stored program, wherein, when the program is executed, the above-described optimization method for predicting the end planar shape of a medium-thick plate is performed.
[0070] The present invention also discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-described optimization method for predicting the end planar shape of a medium-thick plate through the computer program.
[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions 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 invention.
Claims
1. An optimization method for predicting the end planar shape of a medium-thick plate, characterized in that, Includes the following steps: Acquire the raw data of the rolled piece, target size data, prediction results of the existing planar shape prediction model, and rolling process parameters; Based on the original data of the rolled piece, the target dimensions of the rolled piece, and the rolling process parameters, the important parameters in the rolling process are determined. These important parameters include: the length of the rolling deformation zone, the length of the forward sliding zone, the length of the backward sliding zone, the lateral width on one side, and the bite angle. Based on the original data of the rolled piece and the rolling process data, calculate the metal volume of the overall deformation zone, the metal volume of the forward sliding zone and its proportion within the overall deformation zone, and the metal volume of the backward sliding zone and its proportion within the overall deformation zone during the rolling process. This includes dividing the rolling deformation zone into four parts, taking 1 / 4 of the metal for calculation, and calculating the volume of 1 / 4 of the metal within the rolling deformation zone. The calculation formula is: 1 / 4 of the metal back slip zone volume within the rolling deformation zone The calculation formula is: The metal volume of the 1 / 4 metal forward slip zone within the rolling deformation zone The calculation formula can be expressed as: In the formula The width of the workpiece entrance. Where is the radius of the roll. For the bite angle, It is a neutral angle. For the thickness of the rolled product at the exit, For the lateral width of the rolled piece on one side, The length of the rolling deformation zone. The length of the backslip zone; Calculate the proportion of the maximum longitudinal length difference of the rolled piece in the overall length difference based on the metal volume ratio in the front and rear sliding zones. Calculate the maximum length difference between the first and last ends of each strip based on the percentage of the maximum length difference at the ends. By combining the width and lateral width data of each imaginary strip in the planar shape prediction model, the endpoint coordinates of the two ends of each imaginary strip can be obtained. Based on the endpoint coordinates, a planar shape curve of the rolled piece end is fitted, thereby optimizing the planar shape prediction.
2. The optimization method for predicting the end planar shape of a medium-thick plate according to claim 1, characterized in that, The original data of the rolled piece includes the width, length, thickness, steel grade, roll diameter, and friction coefficient between the rolled piece and the roll. The target dimension data includes: post-rolling width, post-rolling thickness, and post-rolling length; The prediction results of the existing planar shape prediction model include: the preset number of slits in the planar shape prediction process and the length and width of each slit after rolling; The rolling process parameters include: number of rolling passes and reduction rate.
3. The optimization method for predicting the end planar shape of a medium-thick plate according to claim 1, characterized in that, The proportion of the maximum longitudinal length difference in the overall length difference is calculated based on the metal volume ratio in the front and rear slip zones, including... The functional relationship between the volume of the sliding zone metal and the maximum length difference at the corresponding end is determined as follows: in, To calculate the maximum longitudinal length difference at the beginning of the rolled piece based on the proportion of the metal volume in the front slip zone within the overall deformation zone. In the overall length difference The adjustment coefficient for the proportion of the middle, To calculate the maximum longitudinal length difference at the tail end of the rolled piece based on the proportion of the metal volume in the back slip zone within the overall deformation zone. In the overall length difference The adjustment factor for the proportion of the middle, the expression for the adjustment factor is: in, and For compression ratio and the width-to-thickness ratio of the rolled piece The constants that have an effect are opposites of each other.
4. The optimization method for predicting the end planar shape of a medium-thick plate according to claim 1, characterized in that, By combining the width and lateral span data of each imaginary strip in the planar shape prediction model, the endpoint coordinates of the first and last ends of each imaginary strip can be obtained. This includes calculating the longitudinal length difference between the first and last ends of each imaginary strip from the maximum length difference at the ends, and the expression is as follows: or in This represents the difference in longitudinal length at the beginning of the i-th line. This represents the longitudinal length difference at the i-th tail end (2≤i≤2n-1).
5. The optimization method for predicting the end planar shape of a medium-thick plate according to claim 1, characterized in that, The optimization method further includes: using the optimization result as input as planar shape data for the next rolling pass.
6. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, it performs the optimization method for predicting the end planar shape of a medium-thick plate as described in any one of claims 1 to 5.
7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the optimization method for predicting the end planar shape of a medium-thick plate as described in any one of claims 1 to 5 through the computer program.