Hot rolling strip steel coiling temperature control method and related equipment

Abstract

The invention discloses a hot-rolled strip steel coiling temperature control method and related equipment, and relates to the technical field of hot-rolled strip steel, and the method comprises the following steps: determining a constant finish rolling speed of strip steel through a quadratic programming optimization algorithm based on a finish rolling outlet speed set value and a target finish rolling temperature of the strip steel; controlling the strip steel to pass through a laminar cooling area at a constant finish rolling speed and reach a target finish rolling temperature; the steel type specification, the constant finish rolling speed and the target finish rolling temperature of the strip steel are input into the heat flow density prediction model, and the heat flow density self-adaptive coefficient of the laminar cooling area is output through the heat flow density prediction model; based on the heat flow density self-adaptive coefficient and the target coiling temperature of the strip steel, the head preset header water quantity of the strip steel is determined; and in the process that the strip steel passes through the laminar cooling area, the head actual header water quantity of the strip steel is adjusted to the head preset header water quantity, so that the coiling temperature of the strip steel reaches the target coiling temperature.

Description

Technical Field

[0001] This application relates to the field of hot-rolled strip steel technology, and in particular to a method and related equipment for controlling the coiling temperature of hot-rolled strip steel. Background Technology

[0002] Currently, in the hot rolling industry, the strip coiling temperature is a key process parameter affecting the microstructure and properties of hot-rolled strip products. During the cooling process after strip slag removal, regardless of whether air cooling or water cooling is used, parameters such as strip speed and temperature have a significant impact on cooling heat transfer.

[0003] Thin strip steel is rolled at a faster speed and has a longer length. The speed fluctuation caused by the same change in speed is more obvious. Speed ​​fluctuation can significantly affect heat flux density, leading to errors in the system's calculation of the strip. Errors in the temperature during the cooling of the strip head will also affect the final rolling temperature hit rate of the strip.

[0004] Thick strip steel has a slower rolling speed, shorter length, and temperature difference in the thickness direction. It is also easily affected by fluctuations in running speed. Therefore, it is more difficult to control the coiling temperature of thick strip steel. The complex and intersecting factors such as surface sheet, plate shape, and pattern control lead to greater fluctuations in coiling temperature and greater difficulty in control compared to ordinary wide and thick pipeline steel, resulting in a decrease in the final rolling temperature hit rate. Summary of the Invention

[0005] The embodiments of this application provide a method and related equipment for controlling the coiling temperature of hot-rolled strip steel, which can at least to some extent control the coiling temperature of hot-rolled strip steel of different specifications.

[0006] The summary section introduces a series of simplified concepts, which will be further explained in detail in the detailed description section. This summary section is not intended to limit the key and essential technical features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0007] This application specifically includes the following aspects: Firstly, this application proposes a method for controlling the coiling temperature of hot-rolled strip steel, comprising: Based on the set value of the strip finishing exit speed and the target finishing temperature, a constant finishing speed of the strip is determined by a quadratic programming optimization algorithm, so as to control the strip to pass through the laminar cooling zone at the constant finishing speed and reach the target finishing temperature. The steel grade and specifications of the strip, the constant finishing rolling speed, and the target final rolling temperature are input into the heat flux density prediction model, so as to output the heat flux density adaptive coefficient of the laminar cooling zone through the heat flux density prediction model. Based on the heat flux density adaptive coefficient and the target coiling temperature of the strip, the preset head manifold water volume of the strip is determined. During the process of the strip passing through the laminar flow cooling zone, the actual water volume in the head manifold of the strip is adjusted to the preset water volume in the head manifold so that the coiling temperature of the strip reaches the target coiling temperature.

[0008] In one feasible implementation, the constant finishing speed of the strip is determined using a quadratic programming optimization algorithm based on the setpoint of the strip's finishing exit speed and the target finishing temperature, so as to control the strip to pass through the laminar cooling zone at the constant finishing speed and reach the target finishing temperature, including: Based on the set value of the finishing mill exit speed, the preset threading speed of each stand of the finishing mill is determined; Based on the target final rolling temperature, the preset temperature acceleration and preset power acceleration of the cooling water between each stand are determined; Based on the preset threading speed, the preset temperature acceleration, and the preset power acceleration, the constant finishing speed of the strip is obtained through the quadratic programming optimization algorithm. The strip is controlled to pass through the laminar flow cooling zone at the constant finishing rolling speed, and the strip reaches the target final rolling temperature by adjusting the parameters of the cooling water between each stand.

[0009] In one feasible implementation, prior to the step of inputting the steel grade and specifications of the strip, the constant finishing rolling speed, and the target finishing rolling temperature into the heat flux density prediction model, the method further includes: Collect historical production data of the strip steel, including the steel grade and specifications, rolling speed, final rolling temperature and coiling temperature of the strip steel; Based on the steel grade specifications, the rolling speed, and the final rolling temperature, determine the input feature vector; Based on the deviation between the winding temperature and the first preset winding temperature, the heat flux density adaptive coefficient is determined; An initial heat flux density prediction model is constructed based on the input feature vector and the heat flux density adaptive coefficient. The initial heat flux density prediction model is trained based on the historical production data until the target model convergence condition is met, thus generating the trained heat flux density prediction model.

[0010] In one feasible implementation, determining the head header water volume of the strip based on the heat flux density adaptive coefficient and the target coiling temperature of the strip includes: The heat flux density adaptive coefficient and the initial manifold water volume at the head of the strip are input into the laminar flow cooling process model to output the second preset coiling temperature of the strip through the laminar flow cooling process model. Adjust the initial head manifold water volume until the deviation between the second preset winding temperature and the target winding temperature is less than or equal to a preset threshold. Then, use the current head manifold water volume as the head preset manifold water volume.

[0011] In one feasible implementation, after the step of adjusting the actual manifold water volume at the head of the strip to the preset manifold water volume, the method further includes: The heat flux density adaptive coefficient is updated based on the deviation between the current coiling temperature of the strip and the first preset coiling temperature. Store the updated adaptive heat flux density coefficients.

[0012] In one feasible implementation, after the step of adjusting the actual water volume in the head manifold of the strip to the preset water volume during the process of the strip passing through the laminar flow cooling zone, the method further includes: Maintain the actual water volume in the head's manifold at a constant level equal to the preset water volume in the head's manifold.

[0013] In one feasible implementation, maintaining the actual water volume in the header constant equal to the preset water volume in the header includes: Based on the preset water volume of the head manifold, determine the target valve opening of the laminar flow cooling manifold; The laminar flow cooling valve is controlled to operate at the target valve opening so that the actual water volume in the head manifold maintains the preset water volume in the head manifold.

[0014] Secondly, this application proposes a hot-rolled strip coiling temperature control system, applied to the hot-rolled strip coiling temperature control method described in any of the above embodiments, comprising: The speed determination module is used to determine the constant finishing speed of the strip steel based on the set value of the finishing exit speed and the target finishing temperature through a quadratic programming optimization algorithm, so as to control the strip steel to pass through the laminar cooling zone at the constant finishing speed and reach the target finishing temperature. The model processing module is used to input the steel grade and specifications of the strip, the constant finishing rolling speed and the target final rolling temperature into the heat flux density prediction model, so as to output the heat flux density adaptive coefficient of the laminar cooling zone through the heat flux density prediction model. The manifold water volume determination module is used to determine the preset manifold water volume at the head of the strip based on the heat flux density adaptive coefficient and the target coiling temperature of the strip. The target winding temperature adjustment module is used to adjust the actual water volume of the head manifold of the strip to the preset water volume of the head manifold during the process of the strip passing through the laminar flow cooling zone, so that the winding temperature of the strip reaches the target winding temperature.

[0015] Thirdly, an electronic device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program stored in the memory to implement the steps of the hot-rolled strip coiling temperature control method as described in any of the first aspects above.

[0016] Fourthly, this application also proposes a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the hot-rolled strip coiling temperature control method of any one of the first aspects.

[0017] In summary, the hot-rolled strip coiling temperature control method proposed in this application has achieved groundbreaking results in the field of hot-rolled strip coiling temperature control through the collaborative implementation of a technical closed loop of "constant speed rolling - data-driven prediction - constant water volume execution": First, based on a quadratic programming optimization algorithm, the strip passes through the laminar cooling zone at a constant finishing speed and accurately reaches the target final rolling temperature, fundamentally eliminating the interference of speed fluctuations on the cooling process; Second, by using a heat flux density prediction model to integrate steel grade specifications, constant speed rolling parameters, and the target final rolling temperature, the adaptive coefficient of heat flux density in the laminar cooling zone is output with high precision, significantly improving the reliability of the head coiling temperature prediction; Furthermore, based on this coefficient and the target coiling temperature, the preset head manifold water volume is determined, and by forcibly maintaining this preset water volume constant along the entire strip length, the control oscillation and overshoot problems caused by lag and detection distortion in traditional dynamic water adjustment models are completely avoided.

[0018] The hot-rolled strip coiling temperature control method proposed in this application, along with other advantages, objectives, and features of this application, will be partly apparent from the following description and partly understood by those skilled in the art through study and practice of this application. Attached Figure Description

[0019] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit this specification. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a schematic flowchart of a hot-rolled strip coiling temperature control method provided in an embodiment of this application. Figure 2 A comparison chart of measured and calculated trends of final rolling temperature for X65 steel grade is provided for embodiments of this application. Figure 3 A water control curve for the final rolling temperature between stands - F1 stand - is provided in the embodiments of this application; Figure 4 A water control curve for the final rolling temperature between stands - F2 stand - is provided in the embodiments of this application; Figure 5 A water control curve for the final rolling temperature between stands - F3 stand - is provided in the embodiments of this application; Figure 6 A water control curve for the final rolling temperature between stands - F4 stand - is provided for embodiments of this application; Figure 7 A water control curve for the final rolling temperature between stands - F5 stand - is provided for embodiments of this application; Figure 8 A water control curve for the final rolling temperature between stands - F6 stand - is provided for embodiments of this application; Figure 9 A comprehensive comparison chart of water control parameters across all racks is provided for embodiments of this application; Figure 10 A schematic diagram of the functional modules of a hot-rolled strip steel coiling temperature control system provided in this application embodiment; Figure 11 This is a schematic diagram of an electronic device for controlling the coiling temperature of hot-rolled strip steel, provided as an embodiment of this application. Detailed Implementation

[0020] To better understand the technical solutions provided in the embodiments of this specification, the technical solutions of the embodiments of this specification will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of this specification and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of this specification, rather than limitations on the technical solutions of this specification. In the absence of conflict, the embodiments of this specification and the technical features in the embodiments can be combined with each other.

[0021] In this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying 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 one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The term "two or more" includes two or more cases.

[0022] Please see Figure 1 This is a schematic flowchart of a hot-rolled strip steel coiling temperature control method provided in an embodiment of this application, which may specifically include: S110. Based on the set value of the strip finishing exit speed and the target finishing temperature, a constant finishing speed of the strip is determined by a quadratic programming optimization algorithm to control the strip to pass through the laminar cooling zone at a constant finishing speed and reach the target finishing temperature.

[0023] For example, a quadratic programming optimization algorithm is used to calculate the constant speed of the strip throughout the rolling process, based on the set finishing mill exit speed and target final rolling temperature. This step ensures that the strip passes through the laminar cooling zone at a stable speed, avoiding the impact of speed fluctuations on temperature control.

[0024] S120. Input the steel grade and specifications of the strip, constant finishing rolling speed and target final rolling temperature into the heat flux density prediction model, so as to output the heat flux density adaptive coefficient of the laminar cooling zone through the heat flux density prediction model.

[0025] For example, the steel grade and specifications of the strip, the constant finishing rolling speed, and the target finishing rolling temperature are input into a pre-trained heat flux density prediction model, which outputs an adaptive coefficient to correct the cooling process. This coefficient can dynamically compensate for heat transfer differences under different operating conditions.

[0026] S130. Based on the heat flux density adaptive coefficient and the target coiling temperature of the strip, determine the preset head manifold water volume of the strip.

[0027] For example, based on the heat flux density adaptive coefficient and the target winding temperature, the amount of water in the manifold that needs to be turned on when the strip head enters the laminar flow cooling zone is calculated. This is a key parameter to ensure uniform temperature along the entire length of the strip.

[0028] S140. During the process of the strip passing through the laminar flow cooling zone, the actual water volume of the head manifold of the strip is adjusted to the preset water volume of the head manifold so that the coiling temperature of the strip reaches the target coiling temperature.

[0029] For example, during the process of the strip steel passing through the laminar flow cooling zone, the actual water volume in the manifold is dynamically adjusted to a preset value and kept constant. The number of manifolds opened is locked by the control system to ensure consistent cooling conditions along the entire length of the strip steel.

[0030] In some examples, a constant finishing speed for the strip is determined using a quadratic programming optimization algorithm based on the strip's finishing exit speed setpoint and target finishing temperature. This ensures the strip passes through the laminar cooling zone at a constant finishing speed and reaches the target finishing temperature. Examples include: Based on the set value of the finishing mill exit speed, determine the preset threading speed of each stand in the finishing mill unit; Based on the target final rolling temperature, the preset temperature acceleration and preset power acceleration of the cooling water between each stand are determined; Based on preset threading speed, preset temperature acceleration, and preset power acceleration, a constant finishing speed for the strip is obtained through a quadratic programming optimization algorithm. The strip is controlled to pass through the laminar flow cooling zone at a constant finishing rolling speed, and the strip reaches the target final rolling temperature by adjusting the parameters of the cooling water between each stand.

[0031] For example, based on the setpoint of the strip exit speed, the preset strip threading speed of each stand in the finishing mill is first determined. This preset threading speed is generated by converting the setpoint of the finishing mill exit speed through a speed allocation algorithm to ensure the speed coordination of each stand. Based on the target final rolling temperature, combined with the thermal properties of the strip and the thermodynamic model of rolling deformation, preset temperature acceleration constraints and preset power acceleration constraints for the cooling water between stands are determined. The preset temperature acceleration constraint is used to limit the rate of strip temperature drop, and the preset power acceleration constraint is used to limit the power fluctuation range of the main motor of the mill. The quadratic programming optimization algorithm is input with preset threading speed, preset temperature acceleration constraints, and preset power acceleration constraints. Using the threading speed as the reference speed and temperature and power acceleration as boundary conditions, it solves for a constant finishing speed solution that satisfies the target final rolling temperature and outputs a constant finishing speed for the strip. Finally, the strip is controlled to pass through the laminar cooling zone at this constant finishing speed, and the temperature fluctuations during the rolling process are compensated by dynamically adjusting the valve opening and water percentage of the cooling water between each stand, so that the absolute value of the deviation between the measured final rolling temperature and the target final rolling temperature along the entire length of the strip does not exceed ±15℃.

[0032] The preset strip threading speed must meet the speed bite conditions of the finishing mill and the equipment's safety speed limit. Essentially, it involves distributing the finishing mill exit speed setting to a coordinated speed with equal flow rates between stands based on the reduction rate of each stand. The preset temperature acceleration constraint is calculated using the strip's specific heat capacity, thermal conductivity, and thickness specifications, limiting the temperature drop gradient caused by cooling water between stands to no more than 50℃ / s to prevent quenching cracks on the strip surface. The preset power acceleration constraint is set based on the rated power and dynamic response characteristics of the mill's main motor, limiting the power change rate to no more than 5% / s of the rated value to prevent over-extension of the equipment. The circuit breaker trips; the quadratic programming optimization algorithm uses the preset threading speed as the initial solution, and under the dual constraints of temperature and power acceleration, iteratively solves for the constant finishing speed that minimizes the variance of the final rolling temperature. This speed must meet the requirement of no speed adjustment during the rolling process (speed change ≤ 0.05 m / s); during the passage stage in the laminar cooling zone, by real-time monitoring of the high temperature gauge data at the finishing mill exit, the opening of the cooling water valves between stands is dynamically adjusted using a PID controller to make the measured final rolling temperature quickly converge to the target value. The water volume adjustment range is limited by the preset temperature acceleration constraint to ensure the stability of constant speed rolling.

[0033] This application achieves, for the first time, high-precision final rolling temperature control of thick strip steel under constant-speed rolling through the coordinated allocation of preset threading speed, rigid constraints of temperature / power acceleration, and speed optimization via quadratic programming. The decision to maintain a constant finishing rolling speed reduces the speed fluctuation of the strip steel as it passes through the laminar cooling zone to below 0.05 m / s, completely eliminating the interference of speed changes on cooling uniformity. The dual constraints of temperature and power acceleration ensure the thermodynamic stability of the rolling process, avoiding surface defects caused by excessive temperature drop or equipment failures caused by power over-limit. Based on real-time monitoring and closed-loop water volume regulation, the final rolling temperature control accuracy is improved to within ±15℃ under constant speed conditions, which is 60% higher than the accuracy of the traditional dynamic speed regulation mode. At the same time, it reduces the number of speed adjustments during the threading stage by more than 90%, significantly reducing the scrap rate of the tongue-shaped head of thick pipeline steel. This coordinated control mechanism lays a stable speed and temperature boundary condition for the subsequent high-precision control of coiling temperature, directly supporting the realization of the core process of "constant speed, constant temperature, and constant water volume".

[0034] In some examples, the steps of inputting the strip steel grade, constant finishing speed, and target finishing temperature into the heat flux density prediction model include: Collect historical production data for strip steel, including steel grade and specifications, rolling speed, final rolling temperature, and coiling temperature. The input feature vector is determined based on the steel grade, rolling speed, and final rolling temperature. The heat flux density adaptive coefficient is determined based on the deviation between the winding temperature and the first preset winding temperature. An initial heat flux density prediction model is constructed based on the input feature vector and the heat flux density adaptive coefficient. The initial heat flux density prediction model is trained based on historical production data until the target model convergence condition is met, thus generating the trained heat flux density prediction model.

[0035] For example, historical production data of strip steel is collected, and steel composition, rolling speed, and final rolling temperature are extracted as input features. Coiling temperature deviation is used as the output label to construct an initial neural network model. The model is then iteratively trained using a gradient descent algorithm, stopping when the loss function is less than a preset value, thus generating the final prediction model.

[0036] In some examples, the head header water volume of the strip is determined based on the heat flux density adaptive coefficient and the target coiling temperature of the strip, including: The heat flux density adaptive coefficient and the initial manifold water volume at the head of the strip are input into the laminar cooling process model to output the second preset coiling temperature of the strip through the laminar cooling process model. Adjust the initial head manifold water volume until the deviation between the second preset winding temperature and the target winding temperature is less than or equal to the preset threshold. Then, use the current head manifold water volume as the head preset manifold water volume.

[0037] For example, the heat flux density adaptive coefficient and the initial head manifold water volume of the strip are input into the laminar cooling process model. The heat flux density adaptive coefficient is used to correct the heat exchange efficiency of the cooling process, and the initial head manifold water volume is set based on historical production data of the same specification or a default water volume percentage. The laminar cooling process model is based on the thermodynamic heat transfer equation, combined with constant finishing speed, cooling water temperature, and water pressure boundary conditions, to calculate the theoretical coiling temperature (i.e., the second preset coiling temperature) of the strip head under a given water volume. The absolute value of the deviation between the theoretical coiling temperature and the target coiling temperature is compared. If the deviation is greater than a preset threshold (e.g., ±10℃), the initial head manifold water volume is modified by a preset adjustment step size (e.g., ±5% water volume) and re-input into the model for calculation. The process is iterated until the deviation is less than or equal to the preset threshold, and finally the current manifold water volume that meets the accuracy requirements is determined as the preset head manifold water volume.

[0038] In some examples, after adjusting the actual manifold water flow at the head of the strip to the preset manifold water flow, the following steps are also included: The heat flux density adaptive coefficient is updated based on the deviation between the current coiling temperature of the strip and the first preset coiling temperature. Store the updated adaptive heat flux density coefficients.

[0039] For example, based on the deviation between the current coiling temperature (directly measured by a coiling pyrometer) collected in real time in the coiling area and the first preset coiling temperature (i.e., the theoretical coiling temperature) calculated by the laminar flow cooling process model, a heat flux density adaptive coefficient update mechanism is triggered. The updated heat flux density adaptive coefficients need to be stored in the shared memory area of ​​the process control system according to the strip specifications. The storage key value is generated by combining the steel grade code, thickness specification, and target coiling temperature. The storage process adopts a double buffering mechanism to avoid read and write conflicts: the front-end buffer receives the updated coefficients, and the back-end buffer writes them to the database in batches at regular intervals. At the same time, the storage triggers the instantaneous adaptive function, associating the new coefficients with the production plan of subsequent strips of the same specification. When a strip with the same key value is detected to enter the production queue, the coefficient is automatically preloaded into the heat flux density prediction model. For strips without matching key values, the historical best average coefficient is used by default, and the new key value used for the first time is recorded for subsequent learning.

[0040] In some examples, after adjusting the actual manifold water flow at the head of the strip to a preset manifold water flow during the strip's passage through the laminar flow cooling zone, the method further includes: Maintain the actual water volume in the head manifold as constant as the preset water volume in the head manifold.

[0041] For example, after the water volume in the strip head manifold is adjusted to the preset value, the execution command of the laminar flow cooling system is locked by the water volume control flag: when the water volume control flag is set to the disabled state, the dynamic water volume adjustment request (including feedforward compensation and feedback correction commands) issued by the laminar flow cooling process model is intercepted in real time, and all control signals of non-preset water volume are discarded; the preset water volume forced execution module is activated simultaneously, which converts the preset water volume in the head manifold into the opening set value of the laminar flow cooling valve, and sends a fixed opening command to the valve actuator through the real-time bus at a period of such as 4ms; at the same time, the feedback value of the actual water flow meter is monitored. If the flow rate deviates from the preset value by ±2% for more than 200ms, the closed-loop PID fine-tuning (adjustment range ≤ 0.5% opening) is triggered, and the actual water volume is forced to return to the preset value, forming a rigid water volume control closed loop for the entire length of the strip.

[0042] In some examples, the actual manifold flow rate is kept constant equal to the preset manifold flow rate, including: Based on the preset water volume in the head manifold, determine the target valve opening for the laminar flow cooling manifold. Control the laminar flow cooling valve to operate at the target valve opening so that the actual water volume in the head manifold maintains the preset water volume in the head manifold.

[0043] For example, maintaining a preset manifold water volume by controlling the opening of the laminar flow cooling valve involves two stages: target opening calculation and valve servo control. For instance, if 80% of the target manifold water volume corresponds to a valve opening of 65°, the system sends a 65° command to the servo controller, and uses PID control to stabilize the actual opening within the range of 65° ± 0.5°. The valve position feedback signal is sampled every 100ms to ensure a dynamic response time of less than 0.3 seconds.

[0044] The technical solution of this application will be further described in detail below through specific embodiments.

[0045] During the production of the same batch of products (with stable thermal properties such as thermal conductivity and specific heat capacity), under the premise that the cooling equipment and cooling conditions (cooling water temperature, cooling water pressure, cooling water flow state, side spray state, etc.) in the cooling zone are stable, the three most critical boundary conditions affecting heat transfer during strip cooling are: strip speed, initial strip surface temperature, and changes in manifold water volume. Therefore, improving these three boundary conditions is extremely crucial for coiling temperature control.

[0046] This application simplifies the complexities of heat transfer calculations for wide and thick pipeline steel products under complex boundary conditions by employing a dedicated "three-constant" technology. "Constant speed" refers to maintaining a constant speed throughout the entire length of the strip as it passes through the rolling mill and laminar cooling zone; "constant temperature" ensures a relatively constant final rolling temperature at each point of the strip entering the laminar cooling zone; and "constant manifold water volume" refers to a constant volume of laminar cooling water throughout the entire length of each strip passing through the laminar cooling zone. Therefore, achieving high-precision final rolling temperature control at constant speed, high-precision coiling temperature prediction, and constant manifold control along the entire length are crucial for ensuring the accuracy of the entire coiling temperature control.

[0047] First, a high-precision final rolling temperature model based on an optimization algorithm achieves both "constant temperature" and "constant speed." Final rolling temperature is one of the key factors affecting the quality of the finished strip steel. To maintain the control precision of the final rolling temperature, speed adjustment is often used. However, dynamic adjustment of the rolling speed leads to dynamic adjustment of the manifold water during the laminar cooling process. When the rolling speed fluctuation exceeds the adjustment range of the laminar cooling manifold, it will also lead to uncontrolled coiling temperature. Therefore, to achieve the FDT target value while obtaining better stable control of the coiling temperature, using a constant rolling speed is a better approach. A quadratic programming optimization method is used to optimize the model, achieving high-precision control of the final rolling temperature.

[0048] Taking steel grade X65 with specifications of 10.54 mm × 1879 mm as an example, and adopting a water adjustment + constant speed mode to control the final rolling temperature, the process parameters are shown in Table 1.

[0049]

[0050] Table 1 The information that needs to be set in the strategy table includes: temperature acceleration, power acceleration, water switch status between racks, initial water volume between racks, and water priority between racks, as shown in Table 2.

[0051]

[0052] Table 2 For steel grade X65, a water-adjusting + constant-speed mode was adopted, and the final rolling temperature profile of the strip along its entire length is as follows: Figure 2 As shown, the strip's overall final rolling temperature control hit rate is 100%, meeting the control requirements for final rolling temperature stability and uniformity; the temperature model's calculation process for water between stands and the actual water-boiling process are as follows. Figures 3 to 9 As shown, when massflowshift is fixed at 0, it means that the strip speed is constant throughout the rolling process, and the speed change is 0.

[0053] After applying the water adjustment and constant speed control technology online, statistical analysis of X65 production data showed that the temperature deviation was within ±20℃, with a hit rate exceeding 100%. The results indicate that the control model has a fast response speed and high calculation accuracy, meeting the final rolling temperature control requirements of X65 under complex operating conditions, thereby improving the stability of strip rolling and the accuracy of final rolling temperature control.

[0054] Secondly, a data-driven high-precision coiling temperature prediction model achieves high-precision prediction of the "head" coiling temperature. The temperature drop of strip steel during the post-rolling cooling process is affected by multiple factors, including rolling speed, final rolling temperature, and steel grade. However, in actual production, rolling speed fluctuates significantly, and a wide variety of steel grades are produced, each with different thickness specifications, making it difficult to quantify the impact of these factors on strip temperature drop using a single model. To address the issue of varying heat transfer during cooling due to different steel grades, specifications, and rolling processes, an adaptive heat flux density coefficient is introduced into the traditional mechanistic model. This coefficient is directly used to correct boundary conditions and is crucial to the accuracy of the cooling process model calculation. Based on massive historical data, a data-driven model for the adaptive coefficient is established, achieving high-precision prediction of the adaptive coefficient and ensuring the accuracy of strip head coiling temperature control.

[0055] Further development of the "constant manifold water volume" control model. The post-rolling cooling control module for the Qian Steel 2160mm production line mainly includes the following sub-modules: pre-setting calculation, real-time correction calculation, real-time adaptation (intra-coil self-learning), and instant adaptation (coil-to-coil self-learning). Before optimization, the Siemens heat transfer model calculates the number and location of valves that need to be opened at each strip point to reach the set coiling temperature and sends the calculation results to the basic automation system. When a strip point passes the coiling pyrometer, the measured coiling temperature is obtained, triggering the real-time adaptation function. The model adjusts and corrects the heat flux density adaptation coefficient in real time based on the deviation between the measured and calculated temperatures. When a certain position of the strip (adaptive position) passes the coiling pyrometer, the instant adaptation function is triggered, recording the current strip heat flux density adaptation coefficient and storing it in the corresponding file or shared memory so that the model can be corrected in advance when rolling the same specification steel grade next time.

[0056] Building upon the aforementioned "constant speed and constant temperature" principle, a "constant manifold water volume" function needs to be independently developed within the existing control system to ensure the precision of temperature control along the strip's length. To guarantee the accuracy of manifold quantity calculations across batches or within the same batch of strip under fluctuating basic operating conditions such as incoming strip threading speed and on-site chilled water temperature, the development of the "constant manifold water volume" function, in addition to ensuring a constant number of manifolds at each point along the strip's winding length, also needs to meet the following requirements: The real-time adaptive function that learns the heat flux density adaptive coefficient based on the measured temperature and the calculated temperature deviation is operating normally, thereby ensuring the normal operation of the instantaneous adaptive function, i.e. the data-driven high-precision head winding temperature prediction function. The water volume of the manifold at each moment is calculated, but this calculated water volume is not distributed to the first level, thus ensuring that the pre-calculated water volume of the manifold remains unchanged for all strip steel coiling at any given time.

[0057] The specific implementation process is as follows: Add a calculation flag bit to the configuration file flag.txt to read the settings of the control system. During the pre-calculation of each strip steel coil, the flag bit is read to determine whether the water volume of the manifold is issued. That is, the corresponding flag bit is 1 during normal real-time control, and the flag bit is set to 0 during the production of this steel grade.

[0058] It should be noted that the above embodiments are merely best examples and are not intended to limit the implementation of this application.

[0059] Furthermore, this application also proposes a hot-rolled strip coiling temperature control system, applied to any of the above-mentioned hot-rolled strip coiling temperature control methods, specifically as follows: Figure 10 The diagram shown is a functional module schematic of a hot-rolled strip steel coiling temperature control system proposed in this application, including: The speed determination module 21 is used to determine the constant finishing speed of the strip steel based on the set value of the finishing exit speed and the target finishing temperature through a quadratic programming optimization algorithm, so as to control the strip steel to pass through the laminar cooling zone at a constant finishing speed and reach the target finishing temperature. The model processing module 22 is used to input the steel grade and specifications of the strip, the constant finishing rolling speed and the target finishing rolling temperature into the heat flux density prediction model, so as to output the heat flux density adaptive coefficient of the laminar cooling zone through the heat flux density prediction model. The manifold water volume determination module 23 is used to determine the preset manifold water volume at the head of the strip based on the heat flux density adaptive coefficient and the target coiling temperature of the strip. The target coiling temperature adjustment module 24 is used to adjust the actual water volume of the head manifold of the strip to the preset water volume of the head manifold during the process of the strip passing through the laminar flow cooling zone, so that the coiling temperature of the strip reaches the target coiling temperature.

[0060] like Figure 11 As shown, this application embodiment also provides an electronic device 300, including a processor 310, a memory 320, and a computer program 321 stored in the memory 320 and executable on the processor. When the processor 310 executes the computer program 321, it implements the steps of any of the above-described hot-rolled strip coiling temperature control methods.

[0061] Since the electronic device described in this embodiment is the device used to implement the hot-rolled strip coiling temperature control method in the embodiments of this application, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this embodiment based on the method described in the embodiments of this application. Therefore, how the electronic device implements the method in the embodiments of this application will not be described in detail here. Any device used by those skilled in the art to implement the method in the embodiments of this application falls within the scope of protection of this application.

[0062] In practical implementation, when the computer program 321 is executed by the processor, it can achieve the following: Figure 1 Any of the corresponding implementation methods in the embodiments.

[0063] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0064] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-readable program code.

[0065] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0066] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0067] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes ​ The steps of the function specified in one or more boxes.

[0068] This application also provides a computer program product, which includes computer software instructions that, when executed on a processing device, cause the processing device to execute a process for controlling the temperature of hot-rolled strip steel coiling.

[0069] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0070] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

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

[0075] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application 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 of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

[0076] Although preferred embodiments have been described in this specification, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this specification.

[0077] Obviously, those skilled in the art can make various modifications and variations to this specification without departing from its spirit and scope. Therefore, if such modifications and variations fall within the scope of the claims and their equivalents, this specification is also intended to include such modifications and variations.

Claims

1. A method for controlling the coiling temperature of hot-rolled strip steel, characterized in that, include: Based on the set value of the strip finishing exit speed and the target finishing temperature, a constant finishing speed of the strip is determined by a quadratic programming optimization algorithm, so as to control the strip to pass through the laminar cooling zone at the constant finishing speed and reach the target finishing temperature. The steel grade and specifications of the strip, the constant finishing rolling speed, and the target final rolling temperature are input into the heat flux density prediction model, so as to output the heat flux density adaptive coefficient of the laminar cooling zone through the heat flux density prediction model. Based on the heat flux density adaptive coefficient and the target coiling temperature of the strip, the preset head manifold water volume of the strip is determined. During the process of the strip passing through the laminar flow cooling zone, the actual water volume in the head manifold of the strip is adjusted to the preset water volume in the head manifold so that the coiling temperature of the strip reaches the target coiling temperature.

2. The method for controlling the coiling temperature of hot-rolled strip steel according to claim 1, characterized in that, The constant finishing speed of the strip is determined by a quadratic programming optimization algorithm based on the setpoint of the strip's finishing exit speed and the target finishing temperature, so as to control the strip to pass through the laminar cooling zone at the constant finishing speed and reach the target finishing temperature, including: Based on the set value of the finishing mill exit speed, the preset threading speed of each stand of the finishing mill is determined; Based on the target final rolling temperature, the preset temperature acceleration and preset power acceleration of the cooling water between each stand are determined; Based on the preset threading speed, the preset temperature acceleration, and the preset power acceleration, the constant finishing speed of the strip is obtained through the quadratic programming optimization algorithm. The strip is controlled to pass through the laminar flow cooling zone at the constant finishing rolling speed, and the strip reaches the target final rolling temperature by adjusting the parameters of the cooling water between each stand.

3. The method for controlling the coiling temperature of hot-rolled strip steel according to claim 1, characterized in that, Before the step of inputting the steel grade and specifications of the strip, the constant finishing rolling speed, and the target finishing rolling temperature into the heat flux density prediction model, the method further includes: Collect historical production data of the strip steel, including the steel grade and specifications, rolling speed, final rolling temperature and coiling temperature of the strip steel; Based on the steel grade specifications, the rolling speed, and the final rolling temperature, determine the input feature vector; Based on the deviation between the winding temperature and the first preset winding temperature, the heat flux density adaptive coefficient is determined; An initial heat flux density prediction model is constructed based on the input feature vector and the heat flux density adaptive coefficient. The initial heat flux density prediction model is trained based on the historical production data until the target model convergence condition is met, thus generating the trained heat flux density prediction model.

4. The method for controlling the coiling temperature of hot-rolled strip steel according to claim 3, characterized in that, The step of determining the preset head manifold water volume of the strip based on the heat flux density adaptive coefficient and the target coiling temperature of the strip includes: The heat flux density adaptive coefficient and the initial manifold water volume at the head of the strip are input into the laminar flow cooling process model to output the second preset coiling temperature of the strip through the laminar flow cooling process model. Adjust the initial head manifold water volume until the deviation between the second preset winding temperature and the target winding temperature is less than or equal to a preset threshold. Then, use the current head manifold water volume as the head preset manifold water volume.

5. The method for controlling the coiling temperature of hot-rolled strip steel according to claim 4, characterized in that, After the step of adjusting the actual water volume in the head of the strip to the preset water volume in the head pipe, the method further includes: The heat flux density adaptive coefficient is updated based on the deviation between the current coiling temperature of the strip and the first preset coiling temperature. Store the updated adaptive heat flux density coefficients.

6. The method for controlling the coiling temperature of hot-rolled strip steel according to claim 1, characterized in that, After adjusting the actual water volume in the head manifold of the strip to the preset water volume during the process of the strip passing through the laminar flow cooling zone, the method further includes: Maintain the actual water volume in the head's manifold at a constant level equal to the preset water volume in the head's manifold.

7. The method for controlling the coiling temperature of hot-rolled strip steel according to claim 6, characterized in that, Maintaining the actual water volume in the header to be constant equal to the preset water volume in the header includes: Based on the preset water volume of the head manifold, determine the target valve opening of the laminar flow cooling manifold; The laminar flow cooling valve is controlled to operate at the target valve opening so that the actual water volume in the head manifold maintains the preset water volume in the head manifold.

8. A hot-rolled strip steel coiling temperature control system, applied to the hot-rolled strip steel coiling temperature control method according to any one of claims 1 to 7, characterized in that, include: The speed determination module is used to determine the constant finishing speed of the strip steel based on the set value of the finishing exit speed and the target finishing temperature through a quadratic programming optimization algorithm, so as to control the strip steel to pass through the laminar cooling zone at the constant finishing speed and reach the target finishing temperature. The model processing module is used to input the steel grade and specifications of the strip, the constant finishing rolling speed and the target final rolling temperature into the heat flux density prediction model, so as to output the heat flux density adaptive coefficient of the laminar cooling zone through the heat flux density prediction model. The manifold water volume determination module is used to determine the preset manifold water volume at the head of the strip based on the heat flux density adaptive coefficient and the target coiling temperature of the strip. The target winding temperature adjustment module is used to adjust the actual water volume of the head manifold of the strip to the preset water volume of the head manifold during the process of the strip passing through the laminar flow cooling zone, so that the winding temperature of the strip reaches the target winding temperature.

9. An electronic device, comprising: The memory and processor are characterized in that the processor is used to execute a computer program stored in the memory to implement the steps of the hot-rolled strip coiling temperature control method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the hot-rolled strip coiling temperature control method as described in any one of claims 1 to 7.

Images