Method for determining a strip cooling control based on a gap time, control device and electronic device

Abstract

This application discloses a method, control device, and electronic equipment for strip cooling control based on gap time determination. The method includes: obtaining the time t0 when the tail of the strip leaves the detection point, the first temperature T0 of the cooling water in the cooling water tank at time t0, the total water consumption A of the current rolling process, the estimated gap time t for long shutdowns at the strip operation site, and the ambient temperature T at the first pipeline at the strip operation site. ambient Based on the first temperature T0 、 Ambient temperature T ambient Given the preset cooling rate k, determine the cooling water temperature T(t) at time (t0+t) during spraying; based on the cooling water temperature T(t) at time (t0+t) and the steel grade of the strip, obtain the water volume correction coefficient C. a Based on the total water consumption A and the water consumption correction factor C a The rated water volume and timing configuration of the cooling water manifolds are determined to ascertain the opening status of the water valves in each cooling water manifold. This method can reduce the performance imbalance between the beginning and end of the laminar flow cooling process caused by variations in the laminar flow cooling process, ensuring consistent performance between the beginning and end of the steel strip.

Description

Technical Field

[0001] This application belongs to the technical field of blast furnace production, and particularly relates to a method, control device and electronic equipment for determining the layer cooling control of strip steel based on the interval time. Background Technology

[0002] In the production of hot-rolled strip steel, the continuous tandem cooling (CTC) system is the core component for controlling the phase transformation microstructure and mechanical properties of the steel. The control objective of laminar flow cooling is to ensure that the strip reaches the set coiling temperature (CT) before coiling through precise cooling process management, thereby ensuring uniform coiling performance and stable microstructure. Modern hot-rolling production lines generally employ a control model based on the fusion of heat conduction theory and real-time data. This model integrates parameters such as strip speed, spray flow rate, and cooling water temperature to dynamically calculate and distribute cooling strategies, achieving closed-loop control of the coiling temperature.

[0003] The current mainstream CTC model does not consider the attenuation effect of equipment failure, waiting for temperature, roller changing and other downtime intervals on pipeline water temperature, and still directly uses the actual measured water temperature in the water tank as the basis for cooling calculation, which leads to inaccurate control in the early stage of production recovery.

[0004] Therefore, there is an urgent need for a method to control the quality stability of steel products under unsteady operating conditions. Summary of the Invention

[0005] This application provides a method, control device, and electronic equipment for determining the layer cooling control of strip steel based on the gap time. It can control the appropriate cooling intensity, ensure the consistency of strip steel performance and target microstructure, reduce the problem of large deviations in strip steel performance at the beginning and end due to gap time, and ensure the consistency and balance of strip steel performance at the beginning and end.

[0006] In a first aspect, embodiments of this application provide a method for determining the layer cooling control of strip steel based on the gap time. The method is used in a cooling device, which includes a cooling water tank, a first pipe, and multiple cooling water manifolds. The cooling water tank is connected to the first pipe, and the first pipe is connected to the multiple cooling water manifolds. The cooling water is stored in the cooling water tank and sprayed onto the strip steel through the outlets of the first pipe and the multiple cooling water manifolds. The method includes: S100, obtaining the time t0 when the tail of the strip leaves the detection point, the first temperature T0 of the cooling water in the cooling water tank at time t0, the total water consumption A of the current rolling process, the estimated interval time t of the long shutdown at the strip operation site, and the ambient temperature T at the first pipeline at the strip operation site. ambient ; S200, based on the first temperature T0 、 Ambient temperature Tambient Given the preset cooling rate k of the cooling water, determine the cooling water temperature T(t) at time (t0+t) during spraying; S300. Based on the cooling water temperature T(t) at time (t0+t) and the steel grade of the strip, the water volume correction coefficient C for the laminar cooling model is obtained. a ; S400, based on total water consumption A and water consumption correction factor C a The rated water volume and timing configuration of each cooling water manifold are determined to establish the opening status of the water valves in each cooling water manifold, so as to control the laminar flow cooling of the strip steel.

[0007] In some embodiments, S200, the first temperature T0, and the ambient temperature T ambient Given a preset cooling rate k, determine the cooling water temperature T(t) at time (t0+t), including: According to formula (2), the cooling water temperature T(t) at time (t0+t) is obtained. T(t) = T ambient +(T0 T ambient )×e kt Formula (2), where T ambient The ambient temperature is represented by T(t); the cooling water temperature at time (t0+t) is represented by T0, where T0 represents the initial temperature, and k represents the preset cooling rate in minutes. -1 t represents the time interval, in minutes, T0, T(t), T ambient The units are ℃.

[0008] In some embodiments, S300, the water volume correction coefficient C of the layer cooling model is obtained based on the cooling water temperature T(t) at time (t0+t). a ,include: S301. Based on the first temperature T0 and the water temperature confirmation model, obtain the water temperature intervention coefficient C. E The water temperature confirmation model is a piecewise function based on water temperature. The piecewise function predefines multiple water temperature ranges and intervention coefficient values ​​corresponding to each water temperature range. S302, based on the first temperature T0 、 The cooling water temperature T(t), the steel grade of the strip, and the water temperature intervention coefficient C E The water volume correction coefficient C for the layer cooling model is obtained. a .

[0009] In some embodiments, S301, the water temperature confirmation model is constructed in the following manner: A preset water temperature node array [W1, W2, ..., Wn] and an intervention coefficient array [M1, M2, ..., Mn] corresponding one-to-one with the water temperature node array, where n is an integer greater than 1; When the current water temperature value is obtained, the interval in which the current water temperature value falls within the water temperature node array is determined, and the corresponding water temperature intervention coefficient C is obtained through interpolation or direct assignment. E .

[0010] In some embodiments, S302, the step of adjusting according to the first temperature T0 、 The cooling water temperature T(t), the steel grade of the strip, and the water temperature intervention coefficient C E The water volume correction coefficient C for the layer cooling model is obtained. a ,include: According to formula (1), the water volume correction coefficient C of the layer cooling model is obtained. a , C a =C E -(T0-T(t))×K' formula (1), where K' represents the water cooling sensitivity coefficient of the strip steel grade; T(t) represents the cooling water temperature, T0 represents the first temperature, C E C represents the water temperature intervention coefficient. a This represents the water volume correction factor for the laminar cooling model.

[0011] In some embodiments, S400, based on the total water consumption A and the water volume correction factor C of the layer cooling model... a The rated water volume and timing configuration of each cooling water manifold are determined, and the opening status of the water valves in each cooling water manifold is determined to control the laminar flow cooling of the strip steel, including: S401, Compare the total water consumption A with the water volume correction factor C of the chilled floor model. a Multiply by these to obtain the corrected target total water volume A'; S402. Based on the corrected target total water volume A' and the rated water volume of each cooling water manifold, determine the cooling water manifold combination to be opened and its corresponding water valve opening sequence through a preset algorithm.

[0012] In some embodiments, the ambient temperature T at the strip steel operating site ambient The ambient temperature T is obtained by installing a temperature sensor at the laminar flow roller of the first pipeline and connecting the temperature sensor to the laminar flow model. The laminar flow model collects the detected value of the temperature sensor in real time as the ambient temperature T. ambient .

[0013] In some embodiments, the ambient temperature T at the strip steel operating site ambientThe ambient temperature T is obtained by: pre-constructing a historical temperature data table within the layered cooling model, which records the average ambient temperature values ​​for different months; and then querying and retrieving the corresponding average ambient temperature value from the historical temperature data table based on the month of the current date, as the ambient temperature T. ambient .

[0014] In some embodiments, the gap time t is determined by the time difference between the tail of the previous strip and the head of the next strip passing the same detection point.

[0015] Secondly, embodiments of this application provide a control device for determining strip cooling based on the gap time, used to implement the method described in the first aspect, the control device comprising: The acquisition module is used to obtain the time t0 when the tail of the strip leaves the detection point, the first temperature T0 of the cooling water in the cooling water tank at time t0, the total water consumption A of the current rolling process, the estimated interval time t of long shutdowns at the strip operation site, and the ambient temperature T at the first pipeline at the strip operation site. ambient ; Cooling water temperature determination module, used to determine the temperature based on a first temperature T0 、 The ambient temperature T ambient Given the cooling rate k of the cooling water, determine the cooling water temperature T(t) at time (t0+t) during spraying; The water volume correction coefficient determination module is used to obtain the water volume correction coefficient C of the laminar cooling model based on the cooling water temperature T(t) at time (t0+t). a ; The cooling control module is used to determine the total water consumption A and the water consumption correction coefficient C. a The rated water volume and timing configuration of each cooling water manifold are determined to determine the opening status of the water valves in each cooling water manifold, so as to control the laminar flow cooling of the strip steel.

[0016] Thirdly, embodiments of this application provide an electronic device, the device including: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the method for layer cooling control of strip steel based on gap time determination as described above.

[0017] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the method for layer cooling control of strip steel based on gap time determination as described above.

[0018] Fifthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform any of the above-mentioned methods for determining layer cooling control of strip steel based on gap time.

[0019] The method for controlling the layer cooling of strip steel based on the interval time in this application embodiment determines the cooling time based on the downtime interval t and the ambient temperature T. ambient Based on the thermal decay law, the actual water temperature T(t) at the spraying moment is predicted, and a water volume correction coefficient C is generated accordingly. a Finally, the opening strategy of each manifold water valve is adjusted to control the laminar flow cooling of the strip steel. Compared with the traditional CTC model that treats water temperature as a constant input, the prediction error of the cooling water temperature at the head and tail of the strip steel is ≤2℃, the uniformity of the strip steel structure is improved, and the scrap rate of unqualified strip steel is reduced by more than 40%. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating a method for determining the layer cooling control of strip steel based on the gap time, as provided in an embodiment of this application. Figure 2 This is a flowchart illustrating yet another method for controlling the layer cooling of strip steel based on the interval time provided in this application embodiment; Figure 3 This is a schematic diagram of the structure of a strip cooling control device based on gap time determination provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application.

[0022] Explanation of the markings in the attached figures: 500. Control device; 501. Acquisition module; 502. Cooling water temperature determination module; 503. Water volume correction coefficient determination module; 504. Cooling control module; 601. Processor; 602. Memory; 603. Communication interface; 610. Bus. Detailed Implementation

[0023] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0024] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, 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, predicting 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, predicting method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, predicting method, article, or apparatus that includes the element.

[0025] Modern hot-rolled strip steel production lines generally employ multi-level automated control systems, among which the secondary control model of the rolling line is the core for achieving high-precision and high-stability rolling. The secondary model of the rolling line refers to the entire automated system, including multiple sub-models such as rolling force model, temperature model, strip shape model, and self-learning model. The secondary model can be based on systems such as Primetals, TMEIC, Danieli, or domestically developed systems. The control method in this application is based on further improvements to existing models.

[0026] This secondary control model for the rolling mill uses a series of interconnected mathematical models to dynamically set and optimize the process parameters throughout the entire process, from the furnace outlet to the coiler inlet. A typical secondary control model for a rolling mill generally includes a roughing setpoint model (RSU), a roller conveyor temperature tracking model (HTT), a finishing setpoint model (FSU), a shape control model (GSM), a final rolling temperature control model (FDTC), and a laminar flow cooling temperature control model (CTC), which together form a closed-loop control architecture covering the entire process of "roughing-finishing-cooling-coiling".

[0027] Among them, the RSU model is responsible for setting the billet temperature, thickness, and width specifications in the roughing stage, and outputs control commands for equipment such as the mill (RM), vertical rolls (VE), automatic width control (AWC), and bending rolls (CB); the HTT model accurately tracks and predicts the billet temperature in the roll table section from roughing to finishing; the FSU model dominates the temperature, thickness, and speed specifications of the finishing mill, and coordinates the finishing mill (FM), looper, and automatic thickness control (AGC) system; the GSM model focuses on strip shape quality, and controls the bending rolls, shifting rolls, and other actuators through crown and flatness targets; the FDTC model ensures that the finishing mill exit temperature is stable within the target window by adjusting the rolling speed and the cooling water between stands.

[0028] In this system, the laminar flow cooling temperature control model (CTC) plays a key role in the final microstructure and performance regulation. By dynamically calculating the spray water volume, number of opening groups and cooling sequence of the laminar flow cooling zone, the strip is cooled to the target coiling temperature, thereby ensuring the consistency of the through-coil mechanical properties and microstructure.

[0029] However, existing CTC models lack accurate perception of the actual water temperature within the pipes when dealing with cooling water temperature drift caused by production intervals (such as shutdowns, roll changes, and waiting for warm-up), which can easily lead to deviations in performance and microstructure imbalances at the head and tail of the strip. Therefore, it is urgent to carry out intelligent optimization within the existing model framework to improve control robustness under unsteady conditions.

[0030] The CTC model refers to the laminar flow cooling temperature control model involving processes such as rolling and coiling, and is part of the secondary model of the rolling line. In the CTC model, under the continuous rolling state of the strip, the cooling water temperature is usually collected in real time by a pyrometer at the water tank outlet or on the main pipeline, and serves as a key input to the secondary model of the rolling line that includes the CTC model.

[0031] Because the strip steel continuously radiates heat, the temperature of the cooling water flowing in the pipe is basically consistent with the temperature measured in the water tank, resulting in high model control accuracy. However, in actual production, discontinuous operating conditions are unavoidable, such as equipment downtime, process waiting time (more than 10 minutes), and gaps in roll changing operations. These gaps can range from 1 to 10 minutes. During these periods, the cooling water in the pipe is stagnant and exposed to ambient temperature for an extended period, dissipating heat to the surrounding air through the pipe wall. This causes its actual temperature to be significantly lower than the temperature measured in the water tank—especially in low-temperature seasons, where the deviation can reach more than 10°C. When rolling resumes, the cooling water temperature that the first coil of strip comes into contact with is far lower than the model's preset value, resulting in excessively high actual heat transfer intensity, low coiling temperature, and increased temperature difference between the beginning and end of the coil. This can easily lead to uneven microstructure, abnormal yield plateau, or even performance failure.

[0032] To address the problems of the prior art, embodiments of this application provide a method, control device and electronic equipment, storage medium and program product for determining the layer cooling control of strip steel based on the interval time. The method for determining the layer cooling control of strip steel based on the interval time provided in this application embodiment will be described first below.

[0033] Figure 1 A schematic flowchart of a method for controlling the layer cooling of strip steel based on gap time, according to an embodiment of this application, is shown. The method is used in a cooling device including a cooling water tank, a first pipe, and multiple cooling water manifolds. The cooling water tank is connected to the first pipe, and the first pipe is connected to the multiple cooling water manifolds. Cooling water is stored in the cooling water tank and sprayed onto the strip steel through the outlets of the first pipe and the multiple cooling water manifolds.

[0034] like Figure 1 As shown, a method for determining the layer cooling control of strip steel based on the gap time may include the following steps S100 to S400: S100, obtain the time t0 when the tail of the strip leaves the detection point, the first temperature T0 of the cooling water in the cooling water tank at time t0, the total water consumption A of the current rolling process, the estimated interval time t of the long shutdown at the strip operation site, and the ambient temperature T at the first pipeline at the strip operation site. ambient ; S200, based on the first temperature T0 、 The ambient temperature T ambient Based on the preset cooling rate k of the cooling water, the cooling water temperature T(t) at time (t0+t) during spraying is determined; S300. Based on the cooling water temperature T(t) at time (t0+t) and the steel grade of the strip, the water volume correction coefficient C for the laminar cooling model is obtained. a ; S400, Based on the total water consumption A and the water consumption correction coefficient C a The rated water volume and timing configuration of each cooling water manifold are determined to determine the opening status of the water valves in each cooling water manifold, so as to control the laminar flow cooling of the strip steel.

[0035] Compared to traditional CTC models that treat water temperature as a constant input and use the measured water temperature in the tank as the basis for cooling water calculation and adjustment, ignoring the thermal decay caused by the intermittent time t; the method in this application embodiment, based on the downtime t and ambient temperature T, ambient Based on the thermal decay law, the actual water temperature T(t) at the spraying moment is predicted, and a water volume correction coefficient C is generated accordingly. aFinally, the opening strategy of each manifold water valve was adjusted to control the laminar flow cooling of the strip steel, so that the prediction error of the cooling water temperature at the head and tail of the strip steel is ≤2℃, which is significantly better than the traditional method (the error is often >8℃); the uniformity of the strip steel structure is improved, and the scrap rate of unqualified strip steel is reduced by more than 40%.

[0036] Furthermore, the gap time t is automatically calculated by the time difference between the front and rear strips passing the same detection point, without the need for manual intervention. Through a four-step closed loop of "time perception - temperature prediction - water volume correction - manifold execution", the previously ignored gap time is transformed into a controllable process variable, eliminating the control blind spot of temperature difference between the head and tail of the strip and improving the robustness of the model under unsteady conditions. It reduces the reliance on manual intervention and promotes the evolution of layer cooling control towards intelligence and self-adaptation. It ensures the consistency of coil quality for high-end steel grades and supports the stable production of high-strength steel, silicon steel and other products that are sensitive to cooling paths.

[0037] This method is fully embedded in existing two-level model architectures (such as RSU / FSU / CTC, etc.), requires no new hardware, and can achieve significant benefits through software logic optimization alone, making it highly valuable for industrial application.

[0038] The interval time (t) refers to the downtime between the tail of the previous strip leaving the detection point in the cooling zone and the head of the next strip entering the cooling zone. It is usually caused by non-continuous production conditions such as equipment failure, roll changing, and waiting for the temperature to reach the target temperature. The duration is generally 1 to 30 minutes, and can be selected as 5 to 30 minutes. To prevent model instability caused by small fluctuations, this value is verified, and it is generally assumed that the interval time (t) is greater than or equal to 5 minutes.

[0039] The cooling water tank is the main container for storing circulating cooling water. Its first temperature T0 is monitored in real time by a pyrometer and serves as the input parameter for the traditional CTC model.

[0040] The first pipeline refers to the conveying pipeline connecting the cooling water tank and the laminar flow cooling spray manifold. During the intermittent time, the water inside is stagnant and easily affected by environmental heat dissipation.

[0041] The cooling rate constant (k) is a physical parameter characterizing how quickly the cooling water in a pipe dissipates heat to the environment, and its unit is min. -1 It is related to the pipe material, insulation conditions, specific heat capacity of the water and ambient wind speed, and can be obtained through on-site calibration or set as a system parameter for use.

[0042] Total water consumption A refers to the original theoretical total cooling water volume calculated by the laminar cooling model based on the strip steel grade, thickness, speed, and target coiling temperature, without considering the water temperature drift during the intermittent time. The unit is usually m³. 3 Or L / s·m.

[0043] Water quantity correction factor (C) a) refers to the proportional factor used to dynamically adjust the total water consumption of the layer-cooled model, compensating for the deviation in heat exchange efficiency caused by the actual spray water temperature deviating from the water tank temperature.

[0044] Water temperature intervention coefficient (C) E () refers to the preset empirical correction value based on the range of the first temperature T0, reflecting the sensitivity of the system to water temperature fluctuations under different base water temperatures.

[0045] Water cooling sensitivity coefficient (K'): A process parameter related to steel grade, characterizing the steel grade's response to changes in cooling water temperature. For example, high-strength steel is more sensitive to water temperature, and its K' value is larger. In some embodiments, S200, the first temperature T0, and the ambient temperature T ambient Given a preset cooling rate k, determine the cooling water temperature T(t) at time (t0+t), including: According to formula (2), the cooling water temperature T(t) at time (t0+t) is obtained. T(t) = T ambient +(T0 T ambient )×e kt Formula (2), where T ambient The ambient temperature is represented by T(t); the cooling water temperature at time (t0+t) is represented by T0, where T0 represents the initial temperature, and k represents the preset cooling rate in minutes. -1 t represents the time interval, in minutes, T0, T(t), T ambient The units are ℃.

[0046] The actual temperature T(t) of the sprayed water during the recovery rolling process is calculated using Newton's law of cooling, and a water volume correction coefficient Ca is generated accordingly. Finally, the opening strategy of each manifold water valve is adjusted, which is conducive to further precise temperature control of the head and tail of the running strip, and to achieving a balance of microstructure and performance.

[0047] In some embodiments, the pre-calibrated cooling device is obtained at the ambient temperature T. ambient The cooling rate curve is used to determine the preset cooling rate k.

[0048] Cooling rate curve: A functional relationship obtained through field experiments, describing the law of k changing with ambient temperature, and stored in the secondary model in the form of a data table or fitting formula.

[0049] Traditional methods often use a fixed k value, ignoring the impact of ambient temperature on heat dissipation efficiency; by using an environment-adaptive k acquisition mechanism, the prediction error of T(t) is reduced, the water volume correction coefficient is more reliable, and the performance stability of the first volume is better.

[0050] During production line commissioning or regular maintenance, conduct shutdown heat dissipation calibration experiments: record the decay curve of pipeline water temperature over time under different seasons / ambient temperatures; fit the cooling rate curve based on the experimental data and store it in a database that can be accessed; in actual operation, obtain the corresponding k value by looking up a table or interpolating based on the current value from the sensor or the historical monthly average value, and use it for T(t) calculation.

[0051] In some embodiments, the method further includes: acquiring real-time liquid level information of the cooling water tank; if the real-time liquid level information is lower than a preset minimum liquid level threshold, initiating a water replenishment program during the long downtime interval to maintain the water level in the cooling water tank.

[0052] If the water tank evaporates or leaks during a long shutdown, causing the liquid level to drop too low, even if the water temperature is accurate, cooling failure may occur due to pump cavitation or insufficient spray pressure. Therefore, it is necessary to avoid unexpected temperature rises caused by abnormal water supply and improve the overall robustness of the system.

[0053] Real-time liquid level information can be continuously collected by a level gauge (such as an ultrasonic or float type) installed on the cooling water tank, which can collect the current water level height or volume percentage of the tank.

[0054] Minimum liquid level threshold: a preset safety lower limit (e.g., 30% of the water tank capacity). Below this value, water pump cavitation, insufficient spray pressure, or drastic fluctuations in water temperature may occur.

[0055] Effective temperature range: refers to the range of cooling water temperature that the laminar flow cooling system can stably control (e.g., 15℃≤T(t)≤45℃). Outside this range, the nonlinearity of heat transfer behavior increases, and model predictions become inaccurate.

[0056] Default temperature correction factor: A safety backup parameter (such as fixed CE'=1.0) activated when T(t) exceeds the limit to avoid loss of control in water volume calculation due to abnormal water temperature.

[0057] In some embodiments, the cooling water tank level signal can be collected in real time. If the detected level is less than the minimum level threshold and the system is in a long shutdown interval (t≥5 minutes), the water replenishment pump will be automatically started. Water replenishment will continue until the level recovers to a safe range (e.g., ≥50%), ensuring that the water supply pressure and flow rate are stable when rolling is resumed.

[0058] In summary, the above methods solve the problem of water temperature deviation caused by the gap time. Furthermore, through calibration-driven parameter adaptation and liquid level-water temperature linkage, a highly robust, self-protective, and engineering-friendly intelligent laminar cooling control system is constructed.

[0059] In some embodiments, in S300, the water volume correction coefficient C of the layer cooling model is obtained based on the cooling water temperature T(t) at time (t0+t). a ,include S301. Based on the first temperature T0 and the water temperature confirmation model, obtain the water temperature intervention coefficient C. E The water temperature confirmation model is a piecewise function based on water temperature. The piecewise function predefines multiple water temperature ranges and intervention coefficient values ​​corresponding to each water temperature range. S302, based on the first temperature T0 、 The cooling water temperature T(t), the steel grade of the strip, and the water temperature intervention coefficient C E The water volume correction coefficient C for the layer cooling model is obtained. a .

[0060] Traditional methods adjust the water volume linearly based on the water temperature deviation, ignoring the nonlinear heat exchange characteristics in different water temperature ranges. By using a segmented water temperature confirmation model, a higher CE is assigned in the low temperature range (e.g., 20–25℃) (because the water temperature is low and the heat exchange is strong, more careful water replenishment is required), and a lower CE is assigned in the high temperature range (e.g., 35–40℃), which conforms to the actual heat exchange law, improves the rationality of the correction starting point, and prevents overcompensation or undercompensation. Steel grades in strip steel, such as high-strength steel (e.g., DP1180), are extremely sensitive to cooling rates; even slight changes in water temperature can lead to abrupt changes in microstructure. In contrast, ordinary carbon steel has a higher tolerance. By configuring specific K′ values ​​for different steel grades (e.g., K′=0.08 for high-strength steel and K′=0.03 for ordinary carbon steel), the Ca correction range is matched to material requirements. Therefore, under the same water temperature deviation, high-strength steel receives greater water volume adjustment, ensuring its microstructure stability, avoiding performance fluctuations, and accurately quantifying the difference between the "expected water temperature" and the "actual water temperature." This facilitates adjusting the correction direction, achieving cooling → water reduction and heating → water addition, avoiding reverse adjustment. This embodiment, through the collaborative design of a segmented water temperature confirmation model and steel grade sensitivity coefficients, upgrades the originally single, static water volume correction to a multi-dimensional, dynamic, material-aware intelligent compensation mechanism. This not only solves the water temperature drift problem caused by intermittent time but also achieves differentiated and precise control of different steel grades under unsteady-state conditions, improving the uniformity of strip steel performance and microstructure.

[0061] The steel grade of strip steel refers to the chemical composition and target microstructure of the rolled strip steel (such as DP980, X80, silicon steel, etc.). Different steel grades have different sensitivities to changes in cooling water temperature due to differences in thermal conductivity, latent heat of phase transformation and hardenability.

[0062] The water temperature confirmation model is a pre-defined piecewise function model that divides the water temperature range into several intervals, such as [20,25), [25,30), [30,35)℃, etc. Each interval corresponds to an empirically set first water temperature intervention coefficient CE, which is used to reflect the initial sensitivity of the system to cooling intensity under different base water temperatures.

[0063] In some embodiments, S301, the water temperature confirmation model is constructed in the following manner: A preset water temperature node array [W1, W2, ..., Wn] and an intervention coefficient array [M1, M2, ..., Mn] corresponding one-to-one with the water temperature node array, where n is an integer greater than 1; When the current water temperature value is obtained, the interval in which the current water temperature value falls within the water temperature node array is determined, and the corresponding water temperature intervention coefficient C is obtained through interpolation or direct assignment. E .

[0064] For example, a piecewise function in the water temperature confirmation model is as follows: WaterTemp=13,!WaterTempsNumPts, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 70.0, 80.0, 90.0, 100.0.

[0065] WaterTempMul=13,!WaterTempsNumPts, 1.36, 1.27, 1.18, 1.09, 1.00, 0.91, 0.82, 0.73, 0.64, 0.45, 0.27, 0.19, 0.09.

[0066] `WaterTemp=13,!WaterTempsNumPts` is a typical data logging or instrument output format, combining data values ​​and status markers. Here, the water temperature is 13℃. `!WaterTempsNumPts` indicates the number of sampling points or measurements used to calculate this water temperature value. It can be understood as: the current water temperature is 13℃, but the number of valid sampling points for this measurement was not recorded (or cannot be obtained). For example, when the water temperature is 20℃, the corresponding water temperature intervention coefficient C... E It is 1.36.

[0067] In some embodiments, prior to S301, the method further includes: Determine whether the interval time t is greater than or equal to a preset time threshold; the preset time threshold is 3~8 min, and can be selected as 5 min.

[0068] In some embodiments, prior to S301, the method further includes: If the interval time t ≥ 5 minutes, then perform subsequent water volume correction calculation based on the cooling water temperature T(t).

[0069] In some embodiments, prior to S301, the method further includes: If the interval time t < 5 minutes, the effect of water temperature decay is ignored, and the first temperature T0 is directly used as the cooling water temperature for layer cooling control or water temperature intervention coefficient C. E It is 1.0.

[0070] In some embodiments, S302, the step of adjusting according to the first temperature T0 、 The cooling water temperature T(t), the steel grade of the strip, and the water temperature intervention coefficient C E The water volume correction coefficient C for the layer cooling model is obtained. a ,include According to formula (1), the water volume correction coefficient C of the layer cooling model is obtained. a , C a =C E -(T0-T(t))×K' formula (1), where K' represents the water cooling sensitivity coefficient of the strip steel grade; T(t) represents the cooling water temperature, T0 represents the first temperature, C E C represents the water temperature intervention coefficient. a This represents the water volume correction factor for the laminar cooling model.

[0071] Under different base water temperatures, the heat transfer change caused by the same water temperature deviation is nonlinear. By using a segmented water temperature verification model, a higher baseline value is set for the low-temperature zone (due to strong heat transfer, a more conservative water replenishment is needed), and a lower value is set for the high-temperature zone. This avoids excessively high winding temperatures due to overcompensation under low water temperature conditions. Therefore, C... E A static baseline is provided; T0-T(t) quantifies the "dynamic deviation," reflecting the actual thermal disturbance and determining the direction of water volume correction; different steel grades are configured with dedicated K′ to match the correction magnitude with material requirements, enabling adaptive linear correction; since low-temperature water has higher heat exchange efficiency, the cooling water volume needs to be reduced to maintain the target coiling temperature, so this deviation term is subtracted from CE. K′ serves as a weighting factor to amplify or reduce the correction magnitude, thereby driving the manifold allocation method to obtain a suitable C. a The water distribution in the manifold is driven by a water volume correction factor C. a The calculation uses deviation-driven methods to achieve closed-loop control of the winding temperature, which can improve the hit rate of the first winding temperature and reduce the temperature difference between the beginning and end, which is significantly better than the traditional model.

[0072] In summary, this dynamic water volume correction mechanism based on thermal attenuation prediction and steel grade sensitivity weighting conforms to the principles of Newtonian cooling and heat transfer enhancement, and can effectively suppress the performance fluctuations of the first coil caused by the gap time.

[0073] In some embodiments, the method further includes: Based on the cooling water temperature T(t) at time (t0+t), determine whether it exceeds the preset effective temperature range; If the temperature exceeds the limit, an alarm will be issued, and the temperature correction factor CE' will be replaced with a preset default temperature correction factor, or the entry of the strip into the cooling zone will be suspended.

[0074] Figure 2 A flowchart illustrating a method for determining the layer cooling control of strip steel based on the gap time, according to an embodiment of this application, is shown.

[0075] like Figure 2 As shown, the method for determining the layer cooling control of strip steel based on the gap time may include the following steps S100 to S300, S410 and S420: wherein S410 and S420 include: S410, Combine the total water consumption A with the water volume correction coefficient C of the layer cooling model. a Multiply by these to obtain the corrected target total water volume A'; S420. Based on the corrected target total water volume A' and the rated water volume of each cooling water manifold, determine the cooling water manifold combination to be opened and its corresponding water valve opening sequence through a preset algorithm.

[0076] The corrected target total water volume A' refers to the corrected actual total water volume required, which serves as the input benchmark for subsequent manifold allocation.

[0077] Cooling water manifold: Multiple independent spray units (usually 10–30 sets) are arranged along the running direction of the strip in the laminar flow cooling zone. Each set is equipped with an independent water valve, which can be individually controlled to open / close and in sequence.

[0078] Rated water volume: refers to the maximum design flow rate of a single cooling water manifold when fully open. It is determined by the pipe diameter, water pressure and nozzle specifications, and is a fixed equipment parameter.

[0079] Target cooling curve: refers to the preset ideal temperature drop trajectory along the length of the strip (from head to tail), reflecting the cooling intensity required in different sections (such as rapid cooling at the head to prevent grain coarsening, slow cooling in the middle to control phase transformation, and fine-tuning at the tail to maintain CT).

[0080] Preset algorithm: refers to the mathematical or rule engine that decomposes the target total water volume A' into each manifold according to the target cooling curve, such as linear allocation, weight mapping, and dynamic programming intelligent scheduling model.

[0081] Traditional methods use the total water consumption A, ignoring the impact of water temperature changes on heat exchange efficiency, leading to actual cooling intensity deviating from expectations. This embodiment uses a water consumption correction factor C. aThe corrected target total water volume A' is dynamically scaled to keep the total heat exchange (rather than the total water volume) constant; this can reduce the overall offset of the coiling temperature in the next process, thereby reducing the standard deviation of the longitudinal temperature of the strip and the fluctuation of the yield strength of the coil; this method does not require new hardware, but only requires a secondary model software upgrade to achieve the control effect of the first coil life on products such as high-strength steel and silicon steel that are sensitive to the cooling path.

[0082] In some embodiments, the preset algorithm allocates the opening time and flow rate of each cooling water manifold based on the target cooling curve along the strip length direction.

[0083] Target cooling curve: This refers to the preset ideal temperature-position relationship curve along the length of the strip (from head to tail), reflecting the required cooling intensity in different sections. This curve is formulated based on the phase transformation kinetics of the steel grade, microstructure control requirements, and coiling temperature targets, and is usually characterized by non-uniform distribution (e.g., strong cooling at the head, slow cooling in the middle, and fine-tuning at the tail).

[0084] Strip length direction: refers to the longitudinal axis along which the strip runs during the rolling process, and serves as the spatial reference for cooling control. The strip is divided into multiple logical segments (such as one segment per meter or per manifold coverage area) to map cooling requirements.

[0085] Opening time: refers to the duration of the opening of a manifold water valve when the strip steel passes underneath it, which determines the cooling time of that section.

[0086] Flow rate: refers to the amount of cooling water passing through a manifold per unit time, which can be controlled in stages by adjusting the opening of the water valve or the water supply pressure.

[0087] Preset algorithm: refers to the mathematical or rule engine that transforms the target cooling curve into specific manifold control commands, such as based on thermal balance inversion, weight allocation, dynamic programming or machine learning models. Its core function is to discretize continuous cooling demand into manifold combination strategies.

[0088] The execution flow of the preset algorithm is as follows: Input target cooling curve: Based on the current strip steel grade, thickness, speed and coiling temperature target, call the corresponding ideal temperature-position curve from the process database; Next, the strip is cooled by discretization: the entire length of the strip is divided into N control segments, each segment corresponding to the coverage area of ​​one or more cooling manifolds to achieve cooling; Heat load mapping: Calculate the heat to be removed for each segment (based on specific heat capacity, latent heat of phase change and temperature drop requirements) and convert it into equivalent cooling water volume requirements; Pipe allocation optimization: The corrected total water volume A′ is used as the upper limit of the constraint; the optimal opening combination is solved based on the cooling demand ratio of each section, combined with the rated flow rate and coverage of the pipes. Output the starting position (or time) of each manifold opening and the water valve opening degree (or flow rate).

[0089] Issuing control commands: The allocation results are sent to the primary control system in real time to drive the water valves to operate in sequence.

[0090] The steel grade process library provides the target cooling curve; the preset algorithm decomposes it into a manifold control strategy; the primary system executes it precisely, and the actual temperature is fed back for model self-learning, thereby improving the stability of steel product quality.

[0091] In some embodiments, the ambient temperature T at the strip steel operating site ambient Obtain it through the following methods: A temperature sensor is installed at the laminar flow roller of the first pipeline, and the temperature sensor is connected to the laminar flow model. The laminar flow model collects the detection value of the temperature sensor in real time as the ambient temperature T. ambient .

[0092] Temperature sensors can be installed in industrial-grade temperature measuring devices (such as PT100 or infrared sensors) near the first pipe and on the cold roller conveyor to collect local ambient temperature in real time.

[0093] Detection point: Photoelectric / thermal metal detectors located at the entrance or exit of the cooling zone, used to accurately capture the head and tail position signals of the strip.

[0094] For example, a temperature sensor can be installed in the laminar cooling roller conveyor area near the first pipe, and its signal can be connected to the secondary control system. Before each calculation, the laminar cooling model reads the current value of the sensor in real time as the ambient temperature to ensure high accuracy and timeliness of the input. The real-time sensing mode provides accurate ambient temperature updated in seconds, which can be used in high-end production lines with stringent control requirements.

[0095] In some embodiments, the ambient temperature T at the strip steel operating site ambient Obtain it through the following methods: A historical temperature data table is pre-built in the laminar cooling model, which records the average ambient temperature values ​​corresponding to different months. Based on the month of the current date, the corresponding average ambient temperature value is retrieved from the historical temperature data table and used as the ambient temperature T. ambient .

[0096] Historical temperature data tables can be stored in a pre-configured, callable database, storing the multi-year average ambient temperature values ​​of the production line's location by month (e.g., January: 5℃, July: 32℃), for temperature estimation in sensorless scenarios.

[0097] If no sensors are deployed on-site or the signal is abnormal, the built-in historical temperature data table is called. The system automatically identifies the month based on the current date and queries the corresponding monthly average temperature value as the ambient temperature. It can still operate without hardware. The historical lookup mode serves as a fallback backup, and can still provide reasonable estimates in the event of sensor failure or in old production lines.

[0098] In some embodiments, the gap time t is determined by detecting the time difference between the tail of the previous strip and the head of the next strip passing the same detection point. Using detection signals from the same physical location eliminates errors introduced by multi-point clock asynchrony or strip speed fluctuations. Compared to relying on mill stop signals or manual input, this method is objective, automatic, and highly resistant to interference, improving the accuracy of gap time identification and providing a reliable time reference for subsequent water temperature prediction.

[0099] As an example, the detection results are shown in Table 1.

[0100] Based on the method for determining the layer cooling control of strip steel based on the gap time provided in the above embodiments, this application also provides a specific implementation of the device for determining the layer cooling control of strip steel based on the gap time. Please refer to the following embodiments.

[0101] Figure 3 This application provides a control device for strip cooling based on the interval time. For example... Figure 3 As shown, the control device 500 may include the following modules: acquisition module 501, cooling water temperature determination module 502, water volume correction coefficient determination module 503, and cooling control module 504.

[0102] The acquisition module 501 is used to obtain the time t0 when the tail of the strip leaves the detection point, the first temperature T0 of the cooling water in the cooling water tank at time t0, the total water consumption A of the current rolling process, the estimated interval time t of the long shutdown at the strip operation site, and the ambient temperature T at the first pipeline at the strip operation site. ambient ; Cooling water temperature determination module 502 is used to determine the temperature based on a first temperature T0. 、 The ambient temperature T ambient Given the cooling rate k of the cooling water, determine the cooling water temperature T(t) at time (t0+t) during spraying; The water volume correction coefficient determination module 503 is used to obtain the water volume correction coefficient C of the laminar cooling model based on the cooling water temperature T(t) at time (t0+t). a ; Cooling control module 504 is used to adjust the total water consumption A and the water consumption correction coefficient C according to the total water consumption A and the water consumption correction coefficient C. aThe rated water volume and timing configuration of each cooling water manifold are determined to determine the opening status of the water valves in each cooling water manifold, so as to control the laminar flow cooling of the strip steel.

[0103] In some embodiments, the water quantity correction factor determination module 503 includes The water temperature intervention coefficient determination module is used to obtain the water temperature intervention coefficient C based on the first temperature T0 and the water temperature confirmation model. E The water temperature confirmation model is a piecewise function based on water temperature. The piecewise function predefines multiple water temperature ranges and intervention coefficient values ​​corresponding to each water temperature range. The water volume correction coefficient calculation module calculates the water volume based on the first temperature T0. 、 The cooling water temperature T(t), the steel grade of the strip, and the water temperature intervention coefficient C E The water volume correction coefficient C for the layer cooling model is obtained. a .

[0104] In some embodiments, the water quantity correction factor determination module 503 includes The water temperature confirmation model construction module specifically includes: The water temperature confirmation model construction module is used to preset the water temperature node array [W1,W2,…,Wn] and the intervention coefficient array [M1,M2,…,Mn] corresponding one-to-one with the water temperature node array, where n is an integer greater than 1; The output module is used to determine the interval of the current water temperature value in the water temperature node array when the current water temperature value is obtained, and to obtain the corresponding water temperature intervention coefficient C by interpolation or direct assignment. E .

[0105] In some embodiments, the water quantity correction coefficient calculation module specifically includes: According to formula (1), the water volume correction coefficient C of the layer cooling model is obtained. a , C a =C E -(T0-T(t))×K' formula (1), where K' represents the water cooling sensitivity coefficient of the strip steel grade; T(t) represents the cooling water temperature, T0 represents the first temperature, C E C represents the water temperature intervention coefficient. a This represents the water volume correction factor for the laminar cooling model.

[0106] In some embodiments, the cooling water temperature determination module 502 specifically includes: According to formula (2), the cooling water temperature T(t) at time (t0+t) is obtained. T(t) = T ambient +(T0 T ambient )×e kt Formula (2), where T ambient The ambient temperature is represented by T(t); the cooling water temperature at time (t0+t) is represented by T0, where T0 represents the initial temperature, and k represents the preset cooling rate in minutes. -1 t represents the time interval, in minutes, T0, T(t), T ambient The units are ℃.

[0107] In some embodiments, the cooling control module 504 specifically includes: The target total water volume determination module is used to compare the total water volume A with the water volume correction factor C of the layer cooling model. a Multiply by these to obtain the corrected target total water volume A'; The cooling control execution module determines the cooling water manifold combination to be opened and its corresponding water valve opening sequence based on the corrected target total water volume A' and the rated water volume of each cooling water manifold through a preset algorithm.

[0108] Figure 4 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown.

[0109] The electronic device may include a processor 601 and a memory 602 storing computer program instructions.

[0110] Specifically, the processor 601 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0111] Memory 602 may include mass storage for data or instructions. For example, and not limitingly, memory 602 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 602 may include removable or non-removable (or fixed) media. Where appropriate, memory 602 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 602 is non-volatile solid-state memory.

[0112] In a particular embodiment, memory 602 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Thus, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the prediction method according to one aspect of this disclosure.

[0113] The processor 601 reads and executes computer program instructions stored in the memory 602 to implement any of the methods for determining the layer cooling control of strip steel based on the gap time in the above embodiments.

[0114] In one example, the electronic device may also include a communication interface 603 and a bus 610. For example, Figure 4 As shown, the processor 601, memory 602, and communication interface 603 are connected through bus 610 and complete communication with each other.

[0115] The communication interface 603 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0116] Bus 610 includes hardware, software, or both, that couples components of an electronic device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 610 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0117] This electronic device can execute the method for layer cooling control of strip steel based on gap time determination in the embodiments of this application, thereby achieving a combination of Figure 1 and Figure 2 The method and apparatus described herein are for controlling the layer cooling of strip steel based on the interval time.

[0118] Furthermore, in conjunction with the method for determining the layer cooling control of strip steel based on the gap time in the above embodiments, this application embodiment can provide a computer-readable storage medium for implementation. This computer-readable storage medium stores computer program instructions; when executed by a processor, these computer program instructions implement any of the methods for determining the layer cooling control of strip steel based on the gap time in the above embodiments.

[0119] This application also provides a computer program product, including a computer program that, when executed, implements any of the methods described above for determining layer cooling control of strip steel based on gap time.

[0120] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known prediction methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the prediction method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0121] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0122] It should also be noted that the exemplary embodiments mentioned in this application describe some prediction methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0123] The foregoing flowcharts and / or block diagrams of prediction methods, apparatus (systems), and computer program products according to embodiments of the present disclosure have described various aspects of the present disclosure. It should be understood that each block in the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts 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, a special-purpose computer, or other programmable data processing apparatus to create a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowcharts and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0124] The above are merely specific embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing prediction method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for controlling the layer cooling of strip steel based on the interval time, characterized in that, The method is used in a cooling device, which includes a cooling water tank, a first pipe, and multiple cooling water manifolds. The cooling water tank is connected to the first pipe, and the first pipe is connected to the multiple cooling water manifolds. The cooling water is stored in the cooling water tank and sprayed onto the strip steel through the outlets of the first pipe and the multiple cooling water manifolds. The method includes: The following data are obtained: the time t0 when the strip tail leaves the detection point, the first temperature T0 of the cooling water in the cooling water tank at time t0, the total water consumption A of the current rolling process, the estimated interval t of long shutdowns at the strip operation site, and the ambient temperature T at the first pipeline at the strip operation site. ambient ; Based on the first temperature T0 、 The ambient temperature T ambient Based on the preset cooling rate k of the cooling water, the cooling water temperature T(t) at time (t0+t) during spraying is determined; Based on the cooling water temperature T(t) at time (t0+t) and the steel grade of the strip, the water volume correction coefficient C for the laminar cooling model is obtained. a ; Based on the total water consumption A and the water consumption correction factor C a The rated water volume and timing configuration of each cooling water manifold are determined to determine the opening status of the water valves in each cooling water manifold, so as to control the laminar flow cooling of the strip steel.

2. The method according to claim 1, characterized in that, The water volume correction coefficient C for the layer cooling model is obtained based on the cooling water temperature T(t) at time (t0+t). a ,include: Based on the first temperature T0 and the water temperature confirmation model, the water temperature intervention coefficient C is obtained. E The water temperature confirmation model is a piecewise function based on water temperature. The piecewise function predefines multiple water temperature ranges and intervention coefficient values ​​corresponding to each water temperature range. Based on the first temperature T0, the cooling water temperature T(t), the steel grade of the strip, and the water temperature intervention coefficient C E The water volume correction coefficient C for the layer cooling model is obtained. a .

3. The method according to claim 2, characterized in that, The water temperature confirmation model is constructed in the following way: A preset water temperature node array [W1, W2, ..., Wn] and an intervention coefficient array [M1, M2, ..., Mn] corresponding one-to-one with the water temperature node array, where n is an integer greater than 1; When the current water temperature value is obtained, the interval in which the current water temperature value falls within the water temperature node array is determined, and the corresponding water temperature intervention coefficient C is obtained through interpolation or direct assignment. E .

4. The method according to claim 2, characterized in that, The first temperature T0 、 The cooling water temperature T(t), the steel grade of the strip, and the water temperature intervention coefficient C E The water volume correction coefficient C for the layer cooling model is obtained. a ,include: According to formula (1), the water volume correction coefficient C of the layer cooling model is obtained. a , C a =C E -(T0-T(t))×K' Formula (1), where K' represents the water cooling sensitivity coefficient of the strip steel grade; T(t) represents the cooling water temperature; T0 represents the first temperature; C E C represents the water temperature intervention coefficient. a This represents the water volume correction factor for the laminar cooling model.

5. The method according to claim 1, characterized in that, The first temperature T0 and the ambient temperature T ambient Given a preset cooling rate k, determine the cooling water temperature T(t) at time (t0+t), including: According to formula (2), the cooling water temperature T(t) at time (t0+t) is obtained. T(t) = T ambient +(T0 T ambient )×e kt Formula (2), where T ambient The ambient temperature is represented by T(t); the cooling water temperature at time (t0+t) is represented by T0, where T0 represents the initial temperature, and k represents the preset cooling rate in minutes. -1 t represents the time interval, in minutes, T0, T(t), T ambient The units are ℃.

6. The method according to claim 1, characterized in that, The total water consumption A and the water volume correction coefficient C of the layer cooling model are used. a The rated water volume and timing configuration of each cooling water manifold are determined to ascertain the opening status of the water valves in each cooling water manifold for laminar flow cooling control of the strip steel, including: The total water consumption A is compared with the water volume correction factor C of the layer cooling model. a Multiply by these to obtain the corrected target total water volume A'; Based on the corrected target total water volume A' and the rated water volume of each cooling water manifold, the cooling water manifold combination to be opened and its corresponding water valve opening sequence are determined by a preset algorithm.

7. The method according to claim 1, characterized in that, The ambient temperature T at the strip steel operating site ambient Obtain it through the following methods: A temperature sensor is installed at the laminar flow roller of the first pipeline, and the temperature sensor is connected to the laminar flow model. The laminar flow model collects the detection value of the temperature sensor in real time as the ambient temperature T. ambient ;or, A historical temperature data table is pre-built in the laminar cooling model, which records the average ambient temperature values ​​corresponding to different months. Based on the month of the current date, the corresponding average ambient temperature value is retrieved from the historical temperature data table and used as the ambient temperature T. ambient .

8. The method according to claim 1, characterized in that, The interval time t is determined by the time difference between the tail of the previous strip and the head of the next strip passing the same detection point.

9. A control device for strip cooling based on gap time, characterized in that, For implementing the method according to any one of claims 1 to 8, the control device comprises: The acquisition module is used to obtain the time t0 when the tail of the strip leaves the detection point, the first temperature T0 of the cooling water in the cooling water tank at time t0, the total water consumption A of the current rolling process, the estimated interval time t of long shutdowns at the strip operation site, and the ambient temperature T at the first pipeline at the strip operation site. ambient ; Cooling water temperature determination module, used to determine the temperature based on a first temperature T0 、 The ambient temperature T ambient Given the cooling rate k of the cooling water, determine the cooling water temperature T(t) at time (t0+t) during spraying; The water volume correction coefficient determination module is used to obtain the water volume correction coefficient C of the laminar cooling model based on the cooling water temperature T(t) at time (t0+t). a ; The cooling control module is used to determine the total water consumption A and the water consumption correction coefficient C. a The rated water volume and timing configuration of each cooling water manifold are determined to determine the opening status of the water valves in each cooling water manifold, so as to control the laminar flow cooling of the strip steel.

10. An electronic device, characterized in that, The device includes: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements the method as described in any one of claims 1 to 8.

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