Plate rolling post-rolling controlled cooling method, device and electronic equipment

Abstract

This application provides a method, apparatus, and electronic device for controlled cooling after rolling of medium and heavy plates. The method includes: performing a first-stage cooling operation on the target rolled steel plate according to set cooling parameters; calculating the first-stage final cooling temperature of the target steel plate based on the set cooling parameters and the steel plate parameters of the target steel plate; determining the current cooling parameters based on the first-stage final cooling temperature; and performing a second-stage cooling operation on the target steel plate based on the current cooling parameters.

Description

Technical Field

[0001] This application relates to the field of steel rolling control technology, and more specifically, to a method, apparatus, and electronic equipment for controlling cooling after rolling of medium and heavy plates. Background Technology

[0002] In the production of medium and heavy plates, the controlled cooling process after rolling refers to controlling the cooling rate and temperature of the rolled steel, and using different cooling paths to regulate the microstructure and properties of the steel. To automate the controlled cooling process, the current approach is to determine the cooling procedure based on various state data of the steel plate, the detected start-up cooling temperature, the cooling water temperature, and other data. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide a method, apparatus, and electronic device for controlled cooling after rolling of medium and heavy plates. This can improve the temperature regulation of the steel plate.

[0004] In a first aspect, the embodiments provide a method for controlled cooling after rolling of medium-thick plates, including:

[0005] The first stage of cooling operation was carried out on the target steel plate according to the set cooling parameters;

[0006] Based on the set cooling parameters and the steel plate parameters of the target steel plate, calculate the first-stage final cooling temperature of the target steel plate;

[0007] The current cooling parameters are determined based on the final cooling temperature of the first stage;

[0008] The target steel plate is subjected to a second-stage cooling operation based on the current cooling parameters.

[0009] In an optional implementation, the step of determining the current cooling parameters based on the final cooling temperature of the first stage includes:

[0010] If the final cooling temperature of the first stage is greater than the target reddening temperature, the current cooling parameters are determined based on the final cooling temperature of the first stage and the target reddening temperature.

[0011] The controlled cooling method for medium-thick plates after rolling provided in this application has two stages. The first stage involves controlled cooling from the completion of rolling until the phase transformation temperature occurs. During this stage, the rolled steel plate enters the cooling zone as quickly as possible to reduce the precipitation of proeutectoid ferrite and prevent subsequent grain coarsening. Simultaneously, a sufficiently high cooling rate is maintained to control the microstructure of the deformed austenite. The steel plate rapidly passes through the austenite region without recrystallization, preventing austenite grain growth and increasing the driving force for phase transformation. The second stage of cooling controls the phase transformation process of the steel. A cooling control process is formulated based on the different microstructures and processing performance requirements of the steel plate to ensure that the steel obtains the desired microstructure and mechanical properties after rapid cooling. This achieves effective cooling of the steel plate.

[0012] In an optional implementation, the step of determining the current cooling parameters based on the first-stage final cooling temperature and the target reddening temperature if the first-stage final cooling temperature is greater than the target reddening temperature includes:

[0013] If the final cooling temperature of the first stage is greater than the target reddening temperature, then the corresponding multiple cooling rates are determined according to the steel plate parameters of the target steel plate and multiple cooling water flow rates.

[0014] Determine the target cooling rate based on the target reddening temperature;

[0015] The required water flow rate is determined based on the target cooling rate and the multiple cooling rates.

[0016] The current cooling parameters are determined based on the required water flow rate. The current cooling parameters include at least one of the following: the number of cooling manifolds open, the water flow rate of each cooling manifold, the roller speed, and the roller acceleration.

[0017] The controlled cooling method for medium and heavy plates after rolling provided in this application embodiment can also determine suitable cooling parameters by combining the parameters of various cooling equipment, thereby achieving stable cooling of steel plates.

[0018] In an optional implementation, the method further includes:

[0019] During the second stage of cooling operation, real-time cooling parameters, roller speed change data, and the state parameters of the target steel plate are acquired according to a preset time cycle.

[0020] Based on the real-time cooling parameters, the speed change data of the roller conveyor, and the state parameters of the target steel plate, the cooling rate of the target steel plate during the second stage cooling operation is calculated.

[0021] The controlled cooling method for medium and heavy plates after rolling provided in this application embodiment can also perform statistical analysis on the cooling in the second stage, which can facilitate understanding of the cooling status in the second stage.

[0022] In an optional implementation, the step of determining the current cooling parameters based on the final cooling temperature of the first stage includes:

[0023] If the final cooling temperature of the first stage is lower than the target reddening temperature, then the set cooling parameters are adjusted to obtain the current cooling parameters.

[0024] The controlled cooling method for medium and heavy plates after rolling provided in this application embodiment can also fine-tune the above-mentioned set cooling parameters if the final cooling temperature in the first stage is less than the target reddening temperature, thereby achieving simple adjustment to make the steel plate reach the required target reddening temperature.

[0025] In an optional implementation, the step of calculating the first-stage final cooling temperature of the target steel plate based on the set cooling parameters and the steel plate parameters of the target steel plate includes:

[0026] Calculate the physical property parameters of the target steel plate based on its steel plate parameters;

[0027] The temperature field of the target steel plate is calculated based on the physical property parameters and the set cooling parameters.

[0028] The first-stage final cooling temperature of the target steel plate is determined based on the temperature field.

[0029] The controlled cooling method for medium and heavy plates after rolling provided in this application calculates the final cooling temperature of the first stage based on the data of the steel plate. This is more accurate than the temperature detected by the detection element, thus providing a data basis for determining the cooling parameters of the second stage.

[0030] In an optional embodiment, prior to the step of performing the first-stage cooling operation on the target steel plate according to the set cooling parameters, the method further includes:

[0031] The set cooling parameters corresponding to the target steel plate are determined based on the type of the target steel plate.

[0032] The controlled cooling method for medium and heavy plates after rolling provided in this application determines a fixed set cooling parameter for different types of steel plates, so that the method in this application can adapt to the cooling requirements of different steel plates.

[0033] Secondly, the embodiments provide a controlled cooling device for medium-thick plates after rolling, comprising:

[0034] The first cooling module is used to perform the first stage of cooling operation on the target steel plate according to the set cooling parameters.

[0035] The first calculation module is used to calculate the first-stage final cooling temperature of the target steel plate based on the set cooling parameters and the steel plate parameters of the target steel plate.

[0036] The first determining module is used to determine the current cooling parameters based on the final cooling temperature of the first stage;

[0037] The second cooling module is used to perform a second-stage cooling operation on the target steel plate according to the current cooling parameters.

[0038] Thirdly, an embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the machine-readable instructions are executed by the processor to perform the steps of the method described in any of the foregoing embodiments.

[0039] Fourthly, embodiments provide a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the method described in any of the foregoing embodiments.

[0040] The medium-thick plate post-rolling controlled cooling method, apparatus, electronic equipment, and computer-readable storage medium provided in this application embodiment employ pre-defined cooling parameters in the first stage, thus fixing the initial speed of the roller conveyor, the water volume in the manifold, and the opening method of the ultra-fast cooling process. This ensures that the steel plate enters the cooling zone quickly after rolling and has a sufficiently high cooling rate at the start of water cooling. Therefore, it reduces the time from rolling to the start of water cooling, and provides a high cooling rate during the water cooling process. This reduces the amount of proeutectoid ferrite precipitation in the steel plate and avoids subsequent grain coarsening. The steel plate can quickly pass through the austenite region without recrystallization, or with a consistent amount or degree of partial recrystallization. The final cooling temperature difference of the steel plate after the first stage of cooling is small, and the cooling rate difference caused by the cooling parameters determined in the second stage is also small. Ultimately, the difference in the mechanical properties of the steel plate can be reduced, and the stability of the plate shape after cooling can be improved, thereby improving production stability and steel plate performance stability.

[0041] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, specific embodiments are described below in conjunction with the accompanying drawings. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a block diagram of an electronic device provided in an embodiment of this application.

[0044] Figure 2 A flowchart of a controlled cooling method for medium-thick plates after rolling provided in an embodiment of this application.

[0045] Figure 3 A detailed flowchart of step 203 of the controlled cooling method for medium and heavy plates after rolling provided in the embodiments of this application.

[0046] Figure 4 This is a schematic diagram of the functional modules of the medium-thick plate post-rolling controlled cooling device provided in the embodiments of this application. Detailed Implementation

[0047] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0048] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0049] In the production of medium and heavy plates, cooling control of rolled steel plates is required. In one implementation method, the cooling procedure is a key part of the fully automatic cooling mode of the cooling system. The cooling procedure depends on the calculation rationality of the cooling model, which affects the output of the automatic cooling control system (cooling water volume, plate speed, cooling rate, etc.), and thus directly affects the microstructure and shape quality of the cooled steel plate.

[0050] In one implementation, the cooling procedure of the medium-thick plate controlled cooling system is calculated by the cooling model. The cooling model determines the parameters required for the cooling procedure based on the obtained steel plate state data, start-up cooling temperature, and water temperature. It calls the basic cooling procedure from the pre-stored table. Based on the average cooling rate requirement and the final cooling temperature required by the process, the cooling model calculates the correction amount of each parameter in the basic cooling procedure through a mathematical model, and then sends the corrected parameters of the basic cooling procedure to the cooling system for execution.

[0051] The inventors of this application have studied the above-mentioned method, but the above-mentioned method still has the following shortcomings: First, the cooling process calculated directly through the cooling model is relatively discrete, and the cooling rate of the rolled piece at different stages is not consistent, which affects the stability of the steel plate performance; Second, thick rolled pieces may exhibit a red-hot phenomenon after cooling, and the discreteness of the cooling process affects the hit rate of the red-hot temperature, resulting in large changes in the steel plate performance.

[0052] Post-rolling controlled cooling of medium and heavy plates is an extremely complex process. Although the aforementioned controlled cooling system is equipped with a cooling model and has a relatively high level of automation, the numerous uncertainties in the on-site working conditions mean that the cooling model may not be able to provide cooling methods according to the personalized needs of some product types. In particular, fluctuations in the post-rolling temperature of the steel plate, changes in water temperature, residual water on the surface of the steel plate before water cooling, and the composition and state of the iron oxide scale on the steel plate surface can cause temperature measurement distortions. This directly or indirectly results in relatively discrete cooling procedures output by the cooling model. Especially when the cooling rate needs to be controlled in stages during the cooling process, the cooling model arbitrarily adjusts the manifold water volume, opening method, roller speed, etc., based only on the average cooling rate obtained during the cooling process. This causes significant fluctuations in the cooling rate at different stages of the cooling process, exhibiting characteristics that are clearly unsuitable for the stability requirements of product quality control, and resulting in large fluctuations in product performance during continuous production.

[0053] For thick steel plates, the phenomenon of reddening after cooling is unavoidable. The cooling process calculated by the cooling model is relatively discrete. Especially when the opening mode of the manifold in the fast cooling section and the water volume of the manifold change greatly, the reddening temperature of the steel plate measured by the high temperature meter used for subsequent calculation will have large differences. This will result in large differences in the calculation results of the self-learning model, and ultimately lead to frequent fluctuations in the reddening temperature of different steel plates, resulting in large fluctuations in the performance of the final product.

[0054] In response to the above research, this application provides a method, apparatus, and electronic device for controlled cooling of steel plates after rolling. The method involves cooling the steel plate in two stages. First, the steel plate is rapidly cooled using a fixed cooling procedure in the first stage. Then, based on a cooling model and the final cooling temperature requirement, parameters such as the manifold flow rate and manifold opening method are calculated for the second stage. The cooling procedure is output based on the calculation results, which solves the above problems and improves the performance stability of the steel plate during continuous production. The detailed process of the above method is described below through several examples.

[0055] Example 1

[0056] To facilitate understanding of this embodiment, the electronic equipment for implementing the controlled cooling method for medium and heavy plates after rolling as disclosed in this application will first be described in detail.

[0057] like Figure 1 The diagram shown is a block diagram of an electronic device. The electronic device 100 may include a memory 111, a memory controller 112, a processor 113, a peripheral interface 114, an input / output unit 115, and a display unit 116. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device 100. For example, the electronic device 100 may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1The different configurations shown.

[0058] The aforementioned memory 111, memory controller 112, processor 113, peripheral interface 114, input / output unit 115, and display unit 116 are electrically connected directly or indirectly to each other to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines. The aforementioned processor 113 is used to execute executable modules stored in the memory.

[0059] The memory 111 can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory 111 stores programs, and the processor 113 executes these programs upon receiving execution instructions. The methods executed by the electronic device 100 as defined in any embodiment of this application can be applied to the processor 113, or implemented by the processor 113.

[0060] The aforementioned processor 113 may be an integrated circuit chip with signal processing capabilities. The processor 113 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a digital signal processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor.

[0061] The peripheral interface 114 described above couples various input / output devices to the processor 113 and the memory 111. In some embodiments, the peripheral interface 114, the processor 113, and the memory controller 112 can be implemented on a single chip. In other instances, they can be implemented on separate chips.

[0062] The input / output unit 115 described above is used to provide user input data. The input / output unit 115 may be, but is not limited to, a mouse and keyboard.

[0063] The aforementioned display unit 116 provides an interactive interface (e.g., a user interface) between the electronic device 100 and the user, or displays image data for the user's reference. In this embodiment, the display unit can be a liquid crystal display (LCD) or a touch screen. If it is a touch screen, it can be a capacitive touchscreen or a resistive touchscreen that supports single-point and multi-point touch operations. Supporting single-point and multi-point touch operations means that the touch screen can sense touch operations generated simultaneously from one or more locations on the touch screen and pass the sensed touch operations to the processor for calculation and processing. In this embodiment, the display unit 116 can be used to display the changing trends of various state data of the steel plate during the cooling process.

[0064] In one example, the cooling device of the controlled cooling system in a production line consists of two zones with a total of twenty-four sets of nozzles. The first zone is a rapid cooling section, with the first four sets being slit nozzles and the last eight sets being high-density nozzles. The second zone is a slow cooling section, composed of twelve sets of high-density nozzles. This enables laminar flow cooling and ultra-rapid cooling, allowing for online controlled cooling and online quenching heat treatment.

[0065] In this embodiment, a control program is installed in the electronic device. This control program can be a fully automatic cooling control system that controls the cooling system. After rolling, the steel plate enters the first zone. The operation of the cooling device is controlled by setting cooling parameters. The cooling parameters are then calculated and output by the cooling model of the fully automatic cooling control system. The cooling parameters may include the number of open manifolds, the distribution of open manifolds, the water volume of each group of manifolds, the water flow ratio between the upper and lower manifolds, the roller speed, the roller acceleration, and other control parameters. The calculation results are sent to the basic automation system for execution. This basic automation system is used to control the various components in the cooling device to achieve cooling control. For example, the cooling model of the fully automatic cooling control system consists of mathematical models such as a temperature field calculation model, a self-learning model, a heat transfer coefficient calculation model, and a latent heat of phase change calculation model. The temperature of the target steel plate is calculated using the above models, thereby determining the required cooling parameters based on the temperature. Optionally, the above temperature field calculation model, self-learning model, heat transfer coefficient calculation model, and latent heat of phase change calculation model can be software programs stored in memory 111 and run by processor 113.

[0066] The electronic device 100 in this embodiment can be used to execute various steps in the various methods provided in the embodiments of this application. The implementation process of the controlled cooling method after rolling of medium and heavy plates is described in detail below through several embodiments.

[0067] Example 1

[0068] Please see Figure 2 This is a flowchart of the controlled cooling method for medium-thick plates after rolling provided in the embodiments of this application. The following will describe... Figure 2 The specific process shown will be explained in detail.

[0069] Step 201: Perform the first stage of cooling operation on the target steel plate according to the set cooling parameters.

[0070] Since different types of steel plates have different dimensions, thicknesses, and other parameters, different cooling parameters may be required for the first stage of the process. Therefore, in this embodiment, before step 201, the post-rolling controlled cooling method for medium-thick plates further includes: determining the set cooling parameters corresponding to the target steel plate based on its type.

[0071] Optionally, the set cooling parameters can be determined based on historical cooling data. For example, for a target type of steel plate, the cooling parameters corresponding to the best stability of the steel plate during a specified time period can be used as the set cooling parameters for that target type of steel plate.

[0072] Optionally, the pre-stored cooling parameters required for each type of steel plate can also be obtained.

[0073] Alternatively, the aforementioned cooling parameters can also be obtained by acquiring cooling parameters set by relevant process engineers. For example, the cooling parameters corresponding to each type of steel plate can be stored in a table, and the cooling parameters can be obtained by retrieving data from this table. For instance, the cooling parameters corresponding to each type of steel plate can be stored in a CSV (Comma-Separated Values) table.

[0074] In this embodiment, step 201 is used to cool the steel plate within the phase transformation temperature range after rolling. For example, the target steel plate can enter the fixed cooling process of step 201 as soon as possible after rolling, thereby reducing the amount of proeutectoid ferrite precipitation and preventing subsequent grain coarsening. Simultaneously, a sufficiently high cooling rate is ensured during cooling to control the microstructure of the deformed austenite. The steel plate rapidly passes through the austenite region without recrystallization, preventing austenite grain growth and increasing the phase transformation driving force.

[0075] In this embodiment, the target steel plate is cooled in the first stage using fixed cooling parameters. This fixes the initial speed of the roller conveyor, the water volume in the manifold, and the opening method of the ultra-fast cooling process. This ensures that the steel plate enters the cooling zone quickly after rolling and has a sufficiently high cooling rate at the start of water cooling. Therefore, the time from rolling to the start of water cooling is reduced, and a high cooling rate is maintained during water cooling, thereby reducing the amount of proeutectoid ferrite precipitation and preventing subsequent grain coarsening. The steel plate can quickly pass through the austenite region without recrystallization, or with a consistent amount or degree of partial recrystallization. If a phase transformation has already occurred during cooling in section A, the fixed cooling procedure ensures consistent microstructure and grain size during the phase transformation process.

[0076] In one example, a 40mm thick reduced-weight low-alloy steel plate Q390B / C is processed using the novel cooling procedure calculation method described in the embodiments of this application.

[0077] In this embodiment, in order to enable the target steel plate to enter the cooling process as soon as possible, the roller speed is relatively increased, the manifold is opened in a relatively dense manner, and at the same time, a certain interval is considered for the opening of the manifold during the rapid cooling process. The water volume control is comprehensively considered based on the equipment capacity, the final reddening temperature, product performance, and the characteristics of the production line process.

[0078] For example, for the reduced-weight low-alloy steel plate Q390B / C with a thickness of 40mm in the medium-thickness plate production line, the cooling parameters for the first stage can be set as follows:

[0079] Thickness (mm) Area A Centralized Management System Activation Method Water volume (l / h) Roller conveyor speed (m / s) acceleration water ratio 40 （0111）（0111）（0111） 200 / 140 / 120 1.1 0.006 1.6 / 2.2 / 2.3

[0080] By using the above-mentioned implementation effect 1: the yield strength CPK (Process Capability Index) of 40mm thick reduced-weight low-alloy steel plate Q390B / C increased from 0.98 to 1.35, the tensile strength CPK increased from 1.12 to 1.43, and the elongation CPK increased from 0.83 to 1.21.

[0081] Step 202: Calculate the first-stage final cooling temperature of the target steel plate based on the set cooling parameters and the steel plate parameters of the target steel plate.

[0082] In this embodiment, the first-stage final cooling temperature of the steel plate after the first stage of cooling can be calculated based on physical property parameters such as specific heat, thermal conductivity and density, as well as the chemical composition of the steel plate, final rolling temperature, number of cooling manifolds opened, water flow rate of each cooling manifold, and running speed of the steel plate, using the physical property parameter model and temperature analysis model involved in the cooling process and their boundary conditions.

[0083] Optionally, step 202 includes: calculating the physical property parameters of the target steel plate based on the steel plate parameters of the target steel plate; calculating the temperature field of the target steel plate based on the physical property parameters and the set cooling parameters; and determining the first-stage final cooling temperature of the target steel plate based on the temperature field.

[0084] Optionally, based on the composition, size, initial temperature, and cooling method of the target steel plate, the corresponding physical properties such as thermal conductivity, heat transfer coefficient, and specific heat are obtained. According to the target process requirements, the thickness is meshed, a reasonable step size is calculated, and the temperature field of the steel plate is solved using the finite element method.

[0085] For example, the temperature field can be calculated using the third type of boundary conditions and initial conditions of the heat conduction differential equation. For instance, in this example, the third type of boundary condition can represent the temperature Tf and heat transfer coefficient α of the fluid medium in contact with the target steel plate, expressed as:

[0086]

[0087] Where k represents the correction value for the air-cooled heat transfer coefficient; α and Tf can be constants or functions that vary with time and location. If α and Tf are not constants, their average value is often taken piecewise as a constant in numerical calculations.

[0088] The initial condition is that the temperature distribution throughout the target steel plate is known at the start of the process, as expressed by the formula:

[0089] or,

[0090] Where T0 is a known constant, indicating that the initial temperature of the target steel plate is uniform, and the unit is ℃; φ(x,y) represents a known function, indicating that the initial temperature of the object is non-uniform, and the unit is ℃.

[0091] By combining the temperature field equations with the third type of boundary conditions and initial conditions, the entire temperature field distribution can be analyzed and solved. For the cooling process of medium-thick plates, the third type of boundary conditions are applicable. In summary, based on the heat conduction differential equations, the third type of boundary conditions, and the initial conditions described above, the key to solving the equations lies in determining the physical properties such as thermal conductivity, heat transfer coefficient, specific heat, and density.

[0092] For example, the thermal conductivity can be obtained by using a piecewise interpolation method based on the known measured thermal conductivity of different steel grades at different temperatures.

[0093] For example, the specific heat capacity of the steel plate can be obtained by linear interpolation based on a table of the steel plate's chemical composition and temperature.

[0094] For example, since the density of a steel plate does not change much when the temperature varies within the range of 0 to 1200°C, the density can be considered to be a constant, which is 7850 kg / m³.

[0095] For example, the heat loss from convective heat transfer between the steel plate and the surrounding air is mainly due to the contact between the steel plate surface and the air. Therefore, the heat transfer coefficient can be calculated using the following formula:

[0096]

[0097] In the formula, k represents the correction value of the air-cooled heat transfer coefficient; T and Tα represent the surface temperature of the rolled steel plate and the ambient air temperature, respectively; σ represents the emissivity of the target steel plate (σ≤1). For medium and thick plates, the value should be taken according to the degree of iron oxide scale on the surface. When there is a lot of iron oxide scale on the surface, the value can be taken as 0.8. For the steel plate that has just been rolled or has a relatively smooth surface, the value can be taken as 0.5~0.7.

[0098] In the temperature field calculation of steel plate cooling, the water-cooling convective heat transfer coefficient is a crucial parameter that significantly impacts the accuracy of the cooling model. The water-cooling heat transfer coefficient is primarily related to factors such as water flow density, steel plate surface temperature, and steel grade, making it a complex and difficult-to-determine parameter. Based on the on-site process control model, within a certain temperature range (average temperature above 500℃), its regression model can be simplified as follows:

[0099]

[0100] Where α represents the water cooling heat transfer coefficient, with a temperature of W / (㎡·℃); a, b, and c represent the model regression coefficients; q represents the water flow density, with a unit of L(㎡·min); and T represents the surface temperature of the target steel plate.

[0101] In one example, the heat transfer coefficient under different temperatures and water flow densities can be roughly determined based on regression curves derived from experience and measured data. The regression equation is as follows:

[0102]

[0103] In one example, the computational model for the temperature field can be as follows:

[0104] If we consider the steel plate as an infinitely large flat plate, then we can only consider the temperature change in the thickness direction, while ignoring the changes in the width and length directions. Furthermore, assuming there is no internal heat source, we can simplify the one-dimensional unsteady-state heat conduction differential equation:

[0105]

[0106] in, , which is the thermal conductivity coefficient; d represents the thickness of the target steel plate.

[0107] Step 203: Determine the current cooling parameters based on the final cooling temperature of the first stage.

[0108] In one embodiment, step 203 may include: if the final cooling temperature of the first stage is less than the target reddening temperature, then adjust the set cooling parameters to obtain the current cooling parameters.

[0109] Alternatively, the number of cooling water groups in the settings can be reduced; for example, one cooling water group can be reduced.

[0110] For thick steel plates, a higher cooling rate results in higher heat exchange efficiency, which can easily lead to a large internal temperature difference. During the cooling process, the surface cooling effect cannot be quickly transferred to the core, resulting in a large temperature gradient between the core and the surface. This leads to strong heat conduction. Therefore, during the air cooling process after cooling, energy in the core of the steel plate is rapidly transferred to the surface. However, due to the very low heat exchange efficiency of the steel plate surface during air cooling, the energy transferred to the surface cannot be carried away in time, resulting in accumulation and an increase in surface temperature. This leads to a smaller temperature drop rate in the core of the thick plate during the water cooling stage and a significant red-hot phenomenon on the surface during the air cooling stage. The cooling process calculated by the cooling model is relatively discrete, especially when there are large changes in the opening method of the manifold in the fast cooling section and the manifold water volume. The red-hot temperature of the steel plate after cooling measured by the pyrometer used to calculate the temperature value will show a large difference, resulting in large differences in the calculation results of the self-learning model. Ultimately, this leads to frequent fluctuations in the red-hot temperature of different steel plates, resulting in large fluctuations in the final product performance. Therefore, based on the requirements of the steel plate, the set cooling parameters can be fixed to achieve rapid cooling first, and then the cooling parameters can be adjusted adaptively to enter slow cooling, so as to reduce the fluctuation of product performance.

[0111] In another embodiment, step 203 may include: if the final cooling temperature of the first stage is greater than the target reddening temperature, then the current cooling parameters are determined based on the final cooling temperature of the first stage and the target reddening temperature.

[0112] In this embodiment, after obtaining the PDI data of the target steel plate, the controlled cooling mode is determined by using the process parameters such as the chemical composition of the steel plate, the target reddening temperature, and the target cooling rate, as well as the physical property parameters such as specific heat, thermal conductivity, and density.

[0113] By using the physical property parameter model and temperature analysis model involved in the cooling process and their boundary conditions, the cooling process of each steel plate is calculated. The number of cooling manifolds to be opened, the water flow rate of each cooling manifold, and the running speed of the steel plate are set, thereby calculating the cooling curves under various water flow conditions. The actual cooling rate is then calculated from the cooling curves, and the combined control of steel plates with different cooling processes is performed.

[0114] Optionally, such as Figure 3 As shown, determining the current cooling parameters based on the final cooling temperature of the first stage and the target reddening temperature may include the following steps.

[0115] Step 2031: Determine the corresponding cooling rates based on the steel plate parameters of the target steel plate and various cooling water flow rates.

[0116] Step 2032: Determine the target cooling rate based on the target red temperature.

[0117] Step 2033: Determine the required water flow rate based on the target cooling rate and the multiple cooling rates.

[0118] Step 2034: Determine the current cooling parameters based on the required water flow rate.

[0119] The current cooling parameters include at least one of the following: the number of cooling manifolds open, the water flow rate of each cooling manifold, the roller speed, the roller acceleration, and the manifold opening method.

[0120] In this embodiment, steps 2031-2034 described above can be implemented using a cooling model.

[0121] Step 204: Perform a second-stage cooling operation on the target steel plate according to the current cooling parameters.

[0122] The second stage of cooling involves controlling the phase transformation process of the steel. Based on the different microstructures and process performance requirements of the steel plate, a cooling control process is formulated to ensure that the steel obtains the required metallographic structure and mechanical properties after rapid cooling.

[0123] If the final cooling temperature in the first stage is higher than the target reddening temperature, the target steel plate can continue cooling in the second stage. The second stage controls the phase transformation process and the microstructure of the target steel plate after the phase transformation. During the second stage of cooling, cooling parameters are calculated by a mathematical model based on the required cooling rate and the target reddening temperature, ensuring that the final cooling temperature of the target steel plate reaches the range set by the process. Ultimately, this allows the steel plate to transform into a uniform and fine ferrite, pearlite, or bainite microstructure. Because the cooling parameters set in the first stage are fixed, the difference in the final cooling temperature of the steel plate after the first stage is small. The difference in the cooling rate calculated by the model when the steel plate enters the second stage of cooling is also small. This reduces the difference in the mechanical properties of the steel plate and improves the stability of the plate shape after cooling, thereby improving production stability and the stability of steel plate performance.

[0124] In this embodiment, the cooling parameters can also be adjusted in real time during the second-stage cooling process. For example, the adjustment of the cooling parameters can be based on the real-time status data of the steel plate during the cooling process.

[0125] Optionally, the moving speed curve of the target steel plate can be corrected based on the actual temperature of the target steel plate, the running speed of the target steel plate, and the water flow distribution. This allows the determination of the time it takes for the target steel plate to enter the cooling phase.

[0126] After the steel plate is rolled, information such as the measured thickness of the target steel plate, the temperature of the steel plate, and the equipment status parameters can be obtained.

[0127] Optionally, the pre-calculated cooling parameters can be corrected based on the deviation between the final cooling temperature of the first stage and the target reddening temperature.

[0128] In this embodiment, the current temperature of the target steel plate can be determined according to the temperature calculation method for calculating the final cooling temperature of the first stage. Based on this current temperature, the required operating speed of the target steel plate is calculated. The speed curve of the target steel plate will use the minimum area approximation calculation for each segment of the steel plate to approximate the optimal cooling time, and the current temperature of the target steel plate and the steel plate speed will be approximated together. This speed calculation takes into account the constraints of the roller control system in the rolling and straightening areas.

[0129] In this embodiment, cooling data from the second stage can also be collected to update the cooling model. The controlled cooling method for medium-thick plates after rolling in this embodiment further includes: during the second stage cooling operation, acquiring real-time cooling parameters, roller speed change data, and the state parameters of the target steel plate according to a preset time period; and calculating the cooling rate of the target steel plate during the second stage cooling operation based on the real-time cooling parameters, the roller speed change data, and the state parameters of the target steel plate.

[0130] Optionally, the preset cycle mentioned above can be to collect the current status data of the target steel plate once every minute.

[0131] After the cooling process is completed in the first and second stages, the temperature change, roller speed change and manifold flow rate of the target steel plate during the first and second stages of cooling can be recorded. The cooling rate can be calculated based on these data, which can be used by the self-learning model to correct the parameters in the subsequent cooling model of the steel plate.

[0132] In this embodiment, the parameters in the cooling model can include a relevant correction coefficient. By calculating the data during the cooling process, the calculated value and the actual value can be compared, and a correction coefficient can be calculated to correct the cooling model parameters.

[0133] For example, the self-learning of the correction parameters of the cooling model can be either short-term or long-term. Short-term self-learning is used for parameter correction from piece to piece within the same batch, and the learned parameter values ​​automatically replace the original parameter values ​​for the next piece of the same type. Long-term self-learning is used for long-term parameter correction of the same type of pieces from different batches, and the learned parameter values ​​can selectively replace existing parameter values ​​in the cooling model.

[0134] Based on the above assessment and research of the influencing parameters of subsequent cooling steel plates, combined with production statistics, production evaluation standards are processed, and various adaptive methods for production data analysis, application, and maintenance are classified.

[0135] In this embodiment, if the cooling of a steel plate has ended, a correction coefficient can be adaptively calculated. This correction coefficient is a function related to the final cooling temperature deviation of the actual steel plate series. Then, the average value of the correction coefficient can be used to calculate the adaptive coefficient for cooling the next steel plate of the same series. For example, this adaptive coefficient will be used in the pre-calculation model to adapt to adjustments in the cooling conditions of that steel series. The cooling model is controlled to perform self-learning corrections on the heat transfer coefficient and cooling rate. The correction method is as follows:

[0136] The calculation method for the self-learning coefficient correction of cooling rate is expressed as follows:

[0137]

[0138] in, This is expressed as the self-learning coefficient for cooling rate; This represents the actual average cooling rate, in °C / s. This represents the average cooling rate, expressed in °C / s.

[0139] The calculation method for the self-learning coefficient correction of the heat transfer coefficient is as follows:

[0140]

[0141] in, Represented as the heat transfer coefficient self-learning coefficient; It is expressed as the difference between the measured average of the initial cooling temperature and the measured average of the final cooling temperature; the unit is ℃. This represents the difference between the calculated average starting cooling temperature and the calculated average final cooling temperature, expressed in °C.

[0142] Through the self-learning method described above, the corrected heat transfer coefficient is stored in the corresponding layer for easy indexing and retrieval later.

[0143] This application provides a novel fully automatic cooling procedure calculation method for a medium-thick plate controlled cooling system, which combines a fixed cooling procedure with a cooling model calculation. This method achieves highly intelligent automatic cooling control, allowing for customized cooling methods based on the specific production needs of medium-thick plate products. It ensures a relatively fixed cooling rate at different stages of the cooling process, and through improvements in automation, it meets the production requirements of alloy reduction steel for medium-thick plate enterprises, guarantees the stability and uniformity of the final product performance, and saves production costs.

[0144] This application embodiment can change the relatively random output mode of calculating the procedure through a single mathematical model, make up for the disadvantages of the model being highly complex and poorly stable, and improve the calculation method of the cooling procedure: fix the cooling rate of the steel plate in the first stage of the cooling process (fix the roller speed, manifold flow rate, manifold opening mode, etc. in the first stage), the mathematical model calculates the final cooling temperature of the first stage based on the cooling procedure formed by the set cooling parameters of the first stage, the initial temperature of the steel plate, the water temperature and the PDI information of the steel plate. The cooling model calculates the roller speed, manifold flow rate, manifold opening mode, etc. required for the second stage based on the required target reddening temperature and the final cooling temperature of the first stage as the starting temperature of the second stage, and performs logical judgment on the final cooling temperature hit after the implementation of the cooling procedure based on the changes in working conditions and different final cooling temperature requirements. The cooling process is automatically controlled in a closed loop, thereby adapting to the needs of improving the stability of steel plate performance and product development, improving control accuracy and the flexibility of functions, and realizing flexible production technology.

[0145] Example 2

[0146] Based on the same application concept, this application also provides a medium-thick plate post-rolling controlled cooling device corresponding to the medium-thick plate post-rolling controlled cooling method. Since the principle of the device in this application is similar to the medium-thick plate post-rolling controlled cooling method described above in this application, the implementation of the device in this application can refer to the description in the above method embodiment, and the repeated parts will not be described again.

[0147] Please see Figure 4 This is a functional module diagram of the controlled cooling device for medium and heavy plates after rolling provided in this application embodiment. Each module in the controlled cooling device for medium and heavy plates after rolling in this embodiment is used to execute the steps in the above method embodiments. The controlled cooling device for medium and heavy plates after rolling includes: a first cooling module 301, a first calculation module 302, a first determination module 303, and a second cooling module 304; wherein,

[0148] The first cooling module 301 is used to perform the first stage cooling operation on the target steel plate according to the set cooling parameters.

[0149] The first calculation module 302 is used to calculate the first-stage final cooling temperature of the target steel plate based on the set cooling parameters and the steel plate parameters of the target steel plate.

[0150] The first determining module 303 is used to determine the current cooling parameters based on the final cooling temperature of the first stage;

[0151] The second cooling module 304 is used to perform a second-stage cooling operation on the target steel plate according to the current cooling parameters.

[0152] In one possible implementation, the first determining module 303 is configured to:

[0153] If the final cooling temperature of the first stage is lower than the target reddening temperature, then the set cooling parameters are adjusted to obtain the current cooling parameters.

[0154] In one possible implementation, the first determining module 303 is configured to:

[0155] If the final cooling temperature of the first stage is greater than the target reddening temperature, the current cooling parameters are determined based on the final cooling temperature of the first stage and the target reddening temperature.

[0156] In one possible implementation, the first determining module 303 includes: a rate determining unit, a target determining unit, a density determining unit, and a parameter determining unit;

[0157] A rate determination unit is used to determine the corresponding multiple cooling rates based on the steel plate parameters of the target steel plate and multiple cooling water flow rates if the final cooling temperature of the first stage is greater than the target reddening temperature.

[0158] The target determination unit is used to determine the target cooling rate based on the target's reddening temperature.

[0159] A density determination unit is used to determine the required water flow rate based on the target cooling rate and the multiple cooling rates;

[0160] The parameter determination unit is used to determine the current cooling parameters based on the required water flow rate. The current cooling parameters include at least one of the following: the number of cooling manifolds open, the water flow rate of each cooling manifold, the roller speed, and the roller acceleration.

[0161] In one possible implementation, the controlled cooling device for medium-thick plates after rolling in this embodiment further includes:

[0162] The acquisition module is used to acquire real-time cooling parameters, roller speed change data, and target steel plate state parameters according to a preset time cycle during the second stage cooling operation.

[0163] The second calculation module is used to calculate the cooling rate of the target steel plate during the second stage cooling operation based on the real-time cooling parameters, the speed change data of the roller conveyor, and the state parameters of the target steel plate.

[0164] In one possible implementation, the first computing module 302 is used for:

[0165] Calculate the physical property parameters of the target steel plate based on its steel plate parameters;

[0166] The temperature field of the target steel plate is calculated based on the physical property parameters and the set cooling parameters.

[0167] The first-stage final cooling temperature of the target steel plate is determined based on the temperature field.

[0168] In one possible implementation, the post-rolling controlled cooling device for medium-thick plates provided in this embodiment may further include:

[0169] The second determining module is used to determine the set cooling parameters corresponding to the target steel plate based on the model of the target steel plate.

[0170] Furthermore, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the controlled cooling method for medium-thick plate rolling as described in the above method embodiments.

[0171] The computer program product of the controlled cooling method for medium and heavy plates after rolling provided in this application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the steps of the controlled cooling method for medium and heavy plates after rolling as described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0172] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0173] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0174] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a 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 this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks. It should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0175] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0176] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for controlled cooling after rolling of medium-thick plates, characterized in that, include: The target steel plate is subjected to a first-stage cooling operation according to the set cooling parameters, wherein the set cooling parameters are cooling parameters corresponding to the target steel plate determined according to the model of the target steel plate; Based on the set cooling parameters and the steel plate parameters of the target steel plate, the first-stage final cooling temperature of the target steel plate is calculated, wherein the steel plate parameters of the target steel plate include: the composition, size, initial temperature, and cooling method of the target steel plate; The current cooling parameters are determined based on the final cooling temperature of the first stage; If the final cooling temperature of the first stage is greater than the target reddening temperature, then the current cooling parameters are determined based on the final cooling temperature of the first stage and the target reddening temperature, including: determining the corresponding multiple cooling rates based on the steel plate parameters of the target steel plate and multiple cooling water flow rates; determining the target cooling rate based on the target reddening temperature; determining the required water flow rate based on the target cooling rate and the multiple cooling rates; and determining the current cooling parameters based on the required water flow rate, wherein the current cooling parameters include at least one of the following: the number of cooling manifolds opened, the water flow rate of each cooling manifold, the roller speed, and the roller acceleration. If the final cooling temperature of the first stage is lower than the target reddening temperature, then the set cooling parameters are adjusted to obtain the current cooling parameters; The target steel plate is subjected to a second-stage cooling operation based on the current cooling parameters. The method further includes: During the second stage of cooling operation, real-time cooling parameters, roller speed change data, and the state parameters of the target steel plate are acquired according to a preset time cycle. Based on the real-time cooling parameters, the speed change data of the roller conveyor, and the state parameters of the target steel plate, the cooling rate of the target steel plate during the second stage cooling operation is calculated. The step of calculating the first-stage final cooling temperature of the target steel plate based on the set cooling parameters and the steel plate parameters of the target steel plate includes: Based on the steel plate parameters of the target steel plate, calculate the physical property parameters of the target steel plate, wherein the physical property parameters include: thermal conductivity, heat transfer coefficient, and specific heat; The temperature field of the target steel plate is calculated based on the physical property parameters and the set cooling parameters. The first-stage final cooling temperature of the target steel plate is determined based on the temperature field.

2. An electronic device, characterized in that, include: The device includes a processor and a memory, the memory storing machine-readable instructions executable by the processor, which, when the electronic device is running, are executed by the processor to perform the steps of the method as described in claim 1.

3. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the method as described in claim 1.

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