A method and system for controlling finish rolling large accelerated rolling and forced acceleration self-learning

Abstract

The application provides a method and system for controlling finish rolling large accelerated rolling and forced acceleration self-learning. The method comprises the following steps: judging whether it is suitable to perform large accelerated rolling in a finish rolling area according to steel grade information and thickness information; debugging a new finish rolling area acceleration model table, and writing the debugged finish rolling area acceleration model table into an original finish rolling area acceleration model table. The application combines the equipment capacity and automation degree of the 1780 hot rolling line to design a new control method, which can guarantee the finish rolling temperature control precision of the strip steel and can also guarantee that the strip steel is rolled at the fastest acceleration in the finish rolling area. The application researches a finish rolling temperature control mode suitable for the 1780 hot rolling line of Beiyang Rolling Mill from the aspects of not affecting the finish rolling temperature control precision and guaranteeing that the strip steel is rolled at the fastest acceleration in the finish rolling area.

Description

Technical Field

[0001] This invention relates to the field of hot-rolled strip steel rolling speed control technology, and more particularly to a method and system for controlling high-acceleration rolling in finishing mills and forcing acceleration self-learning. Background Technology

[0002] In hot strip rolling, the accuracy of the final rolling temperature determines the internal metallographic structure and mechanical properties of the steel, directly affecting the quality of the strip (thickness, shape). For hot strip rolling, the main means to ensure the accuracy of the final rolling temperature in the finishing rolling zone is to adjust the cooling water and acceleration between stands to ensure the precision of the final rolling temperature control.

[0003] To ensure the accuracy of final rolling temperature control in the finishing mill of the 1780 hot-rolled strip steel production line at Beiying Steel Rolling Mill, an acceleration self-learning control method is used. This means the magnitude of the strip's acceleration in the finishing mill is determined by the model parameter table and updated through self-learning based on deviations in incoming material temperature and control accuracy. While this control method greatly ensures the accuracy of final rolling temperature control, with the significant increase in production output, some finishing mill acceleration coefficients in the model become extremely unreasonable, leading to a reduction in finishing mill speed during the rolling of certain products.

[0004] While the finishing speed control of the 1780 hot-rolled strip steel production line at Beiying Steel Rolling Mill ensured the accuracy of the final rolling temperature control, it increased the overall strip rolling time, which was detrimental to the overall output of the production line and increased the consumption of energy media (wind, water, electricity, etc.). It is understood that most hot-rolling production lines, both domestically and internationally, typically use a fixed strip threading speed and a pre-set amount of strip cooling water to ensure the strip head temperature during conventional production. Acceleration is adjusted by referring to tables from a model and then adjusting the strip cooling water between stands based on the measured temperature deviation of the strip. This method of adjusting acceleration according to actual production conditions is relatively reasonable. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method and system for controlling high-acceleration rolling in the finishing mill and forcing acceleration self-learning. Combining the capabilities and automation level of the 1780 hot rolling line, this invention designs a new control method that ensures both the accuracy of the final rolling temperature control and the fastest possible acceleration for the strip during finishing. The research focuses on developing a suitable final rolling temperature control mode for the 1780 hot rolling line at Beiying Steel Mill, aiming to achieve both accurate final rolling temperature control and the fastest possible acceleration for the strip during finishing.

[0006] The technical means employed in this invention are as follows:

[0007] A method for controlling high-acceleration rolling in finishing mills and forcing acceleration self-learning includes:

[0008] Based on the steel grade and thickness information, determine whether it is suitable to perform high-acceleration rolling in the finishing rolling area;

[0009] Debug the new acceleration model table for the finishing rolling zone, and write the debugged acceleration model table for the finishing rolling zone into the original acceleration model table for the finishing rolling zone.

[0010] Furthermore, the step of determining whether high-acceleration rolling is suitable in the finishing rolling region based on steel grade and thickness information specifically includes:

[0011] Obtain steel grade information and steel thickness information;

[0012] Based on the obtained steel grade information and steel thickness information, determine whether to turn the finishing rolling speed self-learning switch on or off;

[0013] If the finishing mill speed self-learning switch is turned on, the original finishing mill region acceleration model table will be used to control the finishing mill region acceleration model normally.

[0014] If the finishing mill speed self-learning switch is turned off, a new finishing mill region acceleration model table will be established;

[0015] Based on the obtained steel grade and thickness information, determine the number of cooling water valves to be opened between stands, and use the maximum water spray volume between stands to ensure that the strip passes through the finishing rolling area with the fastest acceleration.

[0016] This invention also provides a self-learning system for controlling high-acceleration rolling in finishing mills and forcing acceleration, implemented based on the self-learning method for controlling high-acceleration rolling in finishing mills and forcing acceleration, comprising: an accelerated rolling unit and a forced acceleration self-learning unit, wherein:

[0017] The accelerated rolling unit is used to determine whether it is suitable to perform high-acceleration rolling in the finishing rolling area based on the steel grade information and thickness information.

[0018] The forced acceleration self-learning unit is used to debug the new finishing mill region acceleration model table and write the debugged finishing mill region acceleration model table into the original finishing mill region acceleration model table.

[0019] Furthermore, the accelerated rolling unit includes:

[0020] The information acquisition module is used to acquire steel grade information and steel thickness information;

[0021] The module for determining the status of the finishing mill speed self-learning switch is used to determine whether to turn the finishing mill speed self-learning switch on or off based on the acquired steel grade information and steel thickness information. If the finishing mill speed self-learning switch is turned on, the original finishing mill region acceleration model table is used to control the finishing mill region acceleration model normally. If the finishing mill speed self-learning switch is turned off, a new finishing mill region acceleration model table is established.

[0022] Furthermore, the forced acceleration self-learning unit includes:

[0023] The finishing mill zone acceleration model table creation module is used to create a new finishing mill zone acceleration model table when the finishing mill speed self-learning switch is off.

[0024] The strip acceleration guarantee module is used to determine the number of inter-stand cooling water valves to be opened based on the obtained steel grade and thickness information, so as to ensure that the strip passes through the finishing rolling area with the fastest acceleration by using the maximum water spray volume between the stands.

[0025] The present invention also provides a storage medium comprising a stored program, wherein, when the program is executed, the self-learning method for controlling high-acceleration rolling and forced acceleration in precision rolling is performed.

[0026] Compared with the prior art, the present invention has the following advantages:

[0027] 1. The method and system for controlling high-acceleration rolling and forcing acceleration self-learning provided by the present invention can not only ensure the accuracy of the final rolling temperature control of the strip, but also ensure that the strip completes rolling at the fastest acceleration in the finishing rolling area.

[0028] 2. The self-learning method and system for controlled high-acceleration rolling and forced acceleration provided by this invention achieves a high finishing temperature hit rate of 95.7% (±15℃), which is not lower than the original control accuracy (original finishing temperature hit rate 95.23%). Currently, the high-acceleration function for 8 steel grades and 6 thickness specifications has been debugged and completed. Calculations show that after the high-acceleration function is implemented, approximately one more piece of steel is rolled per hour. This has achieved the goal of increasing the overall output of the production line, reducing the consumption of energy media (wind, water, electricity, etc.), and creating maximum benefits for the company.

[0029] Based on the above reasons, this invention can be widely applied in fields such as hot-rolled strip steel rolling speed control. Attached Figure Description

[0030] 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.

[0031] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0032] 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.

[0033] 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.

[0034] like Figure 1 As shown, this invention provides a method for controlling high-acceleration rolling in finishing mills and forcing acceleration self-learning, comprising:

[0035] Based on the steel grade and thickness information, determine whether it is suitable to perform high-acceleration rolling in the finishing rolling area;

[0036] Debug the new acceleration model table for the finishing mill area (maximum speed, maximum water spray volume, optimal control accuracy), and write the debugged acceleration model table for the finishing mill area into the original acceleration model table for the finishing mill area.

[0037] In this embodiment, it is determined whether the steel grade and thickness are suitable for high-acceleration rolling in the finishing rolling area. A self-learning shutdown button is added to the process control model, and a new finishing rolling area acceleration model table is established. The maximum water spray volume between stands ensures that the strip passes through the finishing rolling area with the fastest acceleration, thereby increasing the overall output of the production line and reducing the consumption of energy media.

[0038] In specific implementation, as a preferred embodiment of the present invention, please refer to [reference needed]. Figure 1 The step of determining whether high-acceleration rolling is suitable in the finishing rolling zone based on steel grade and thickness information specifically includes:

[0039] Obtain steel grade information and steel thickness information;

[0040] Based on the obtained steel grade information and steel thickness information, determine whether to turn the finishing rolling speed self-learning switch on or off;

[0041] If the finishing mill speed self-learning switch is turned on, the original finishing mill region acceleration model table will be used to control the finishing mill region acceleration model normally.

[0042] If the finishing mill speed self-learning switch is turned off, a new finishing mill region acceleration model table will be established;

[0043] Based on the obtained steel grade and thickness information, determine the number of cooling water valves to be opened between stands, and use the maximum water spray volume between stands to ensure that the strip passes through the finishing rolling area with the fastest acceleration.

[0044] This invention also provides a system for controlling high-acceleration rolling in a finishing mill and forcing acceleration self-learning, based on the above-described method for controlling high-acceleration rolling in a finishing mill and forcing acceleration self-learning. The system includes: an accelerated rolling unit and a forced acceleration self-learning unit, wherein:

[0045] The accelerated rolling unit is used to determine whether it is suitable to perform high-acceleration rolling in the finishing rolling area based on the steel grade information and thickness information.

[0046] The forced acceleration self-learning unit is used to debug the new finishing mill region acceleration model table and write the debugged finishing mill region acceleration model table into the original finishing mill region acceleration model table.

[0047] In a specific implementation, as a preferred embodiment of the present invention, the accelerated rolling unit includes:

[0048] The information acquisition module is used to acquire steel grade information and steel thickness information;

[0049] The module for determining the status of the finishing mill speed self-learning switch is used to determine whether to turn the finishing mill speed self-learning switch on or off based on the acquired steel grade information and steel thickness information. If the finishing mill speed self-learning switch is turned on, the original finishing mill region acceleration model table is used to control the finishing mill region acceleration model normally. If the finishing mill speed self-learning switch is turned off, a new finishing mill region acceleration model table is established.

[0050] In a specific implementation, as a preferred embodiment of the present invention, the forced acceleration self-learning unit includes:

[0051] The finishing mill zone acceleration model table creation module is used to create a new finishing mill zone acceleration model table when the finishing mill speed self-learning switch is off.

[0052] The strip acceleration guarantee module is used to determine the number of inter-stand cooling water valves to be opened based on the obtained steel grade and thickness information, so as to ensure that the strip passes through the finishing rolling area with the fastest acceleration by using the maximum water spray volume between the stands.

[0053] This invention also provides a storage medium, characterized in that the storage medium includes a stored program, wherein when the program is executed, the above-described method for controlling high-acceleration rolling and forcing acceleration self-learning is performed.

[0054] In specific implementation, as a preferred embodiment of the present invention

[0055] Example 1

[0056] Create a new variable `useAccspdop` in the `ctr-uty` table;

[0057] Select steel grade and thickness level pdi.SteelGrade => cpd.thkFmxTgt to switch to the new model table in the ctr-uty model table => FMFTC subroutine for water spray setting => high acceleration adjustment => FMFTC strip cooling water parameter dynamic compensation => reach the target temperature for finishing rolling. Among these:

[0058] useAccspdop represents the self-learning switch for finishing mill speed; 1 is on, 0 is off;

[0059] pdi.SteelGrade indicates PDI steel grade;

[0060] cpd.thkFmxTgt represents the target thickness for finishing rolling;

[0061] ctr-uty represents the thickness grade table under steel grade;

[0062] FMFTC indicates the water spraying subroutine between the finishing mill stands;

[0063] Example 2

[0064] Copy the maximum acceleration model table after debugging to the original CTR-UTY model table and set the variable `useAccspdop` to 0 (disable speed self-learning) => Subroutine `CtlFta` is unavailable in this model table => Disable the variables `accMinPre`, `accMaxPre`, `accMinLmt`, and `accMaxLmt` => `accFmxHead` and `accFmx` are the maximum speed values ​​=> The water spray volume in the machining room is the maximum speed water flow rate => Reach the target temperature for finishing rolling. Where:

[0065] CtlFta represents the speed self-learning subroutine;

[0066] accFmxHead represents the acceleration value during finishing rolling;

[0067] accFmx represents the acceleration value of the finishing mill.

[0068] accMinPre and accMaxPre represent the self-learning limits of the rolling mill acceleration.

[0069] accMinLmt and accMaxLmt represent the self-learning limits of the finishing mill's second acceleration.

[0070] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0071] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0072] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0073] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0074] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0075] 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. A method for controlling high-acceleration rolling in precision rolling mills and forcing acceleration self-learning, characterized in that, include: Based on the steel grade and thickness information, determine whether it is suitable to perform high-acceleration rolling in the finishing rolling area, specifically including: Obtain steel grade information and steel thickness information; Based on the obtained steel grade information and steel thickness information, determine whether to turn the finishing rolling speed self-learning switch on or off; If the finishing mill speed self-learning switch is turned on, the original finishing mill region acceleration model table will be used to control the finishing mill region acceleration model normally. If the finishing mill speed self-learning switch is turned off, a new finishing mill region acceleration model table will be established; Based on the obtained steel grade and thickness information, determine the number of cooling water valves to be opened between stands, and use the maximum water spray volume between stands to ensure that the strip passes through the finishing rolling area with the fastest acceleration. Debug the new acceleration model table for the finishing rolling zone, and write the debugged acceleration model table for the finishing rolling zone into the original acceleration model table for the finishing rolling zone.

2. A self-learning system for controlling high-acceleration rolling in precision rolling mills and forcing acceleration, characterized in that, The method for controlling high-acceleration rolling and forced acceleration self-learning as described in claim 1 includes: an accelerated rolling unit and a forced acceleration self-learning unit, wherein: The accelerated rolling unit is used to determine whether it is suitable to perform high-acceleration rolling in the finishing rolling area based on steel grade and thickness information, including: The information acquisition module is used to acquire steel grade information and steel thickness information; The module for determining the status of the finishing mill speed self-learning switch is used to determine whether to turn the finishing mill speed self-learning switch on or off based on the acquired steel grade information and steel thickness information. If the finishing mill speed self-learning switch is turned on, the original finishing mill region acceleration model table is used to control the finishing mill region acceleration model normally. If the finishing mill speed self-learning switch is turned off, a new finishing mill region acceleration model table is established. The strip acceleration guarantee module is used to determine the number of inter-stand cooling water valves to be opened based on the obtained steel grade information and steel thickness information, so as to ensure that the strip passes through the finishing rolling area with the fastest acceleration by using the maximum water spray volume between the stands. The forced acceleration self-learning unit is used to debug the new finishing mill region acceleration model table and write the debugged finishing mill region acceleration model table into the original finishing mill region acceleration model table.

3. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, the self-learning method for controlling high-acceleration rolling and forced acceleration as described in claim 1 is performed.

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