Three-time spray cooling system for horizontal continuous casting and control method

Abstract

The invention relates to the technical field of horizontal continuous casting, in particular to a three-time spray cooling system for horizontal continuous casting and a control method. The control method specifically comprises the steps that the heat exchange coefficient between a cast iron profile and cooling water is analyzed, the correlation between the heat exchange coefficient and the cooling water turbidity is constructed, and the heat exchange coefficient variation at each moment is calculated; based on the temperature before cooling and the temperature after cooling, cooling speed errors at all moments are analyzed, and water quality change errors at all moments are calculated in combination with the heat exchange coefficient variable quantity; calculating a system change error at each moment based on the water spray pressure, the water spray flow and the variable quantity of the cooling speed at adjacent moments; further determining an adaptive feedback gain coefficient at each moment, and performing water spray pressure control in combination with an active-disturbance-rejection controller; the problem that the actual cooling speed deviates from the expected cooling speed due to the fact that a fixed feedback gain coefficient is used in traditional active-disturbance-rejection control, and then the cooling effect of the cast iron profile is affected is solved, and the stability of the cooling process of the cast iron profile is improved.

Description

Technical Field

[0001] This application relates to the field of horizontal continuous casting technology, and specifically to a three-stage spray cooling system and control method for horizontal continuous casting. Background Technology

[0002] Horizontal continuous casting is a casting method that continuously pours high-temperature molten metal into profiles or billets. In this process, the molten metal flows from the furnace and, through specific equipment and processes, continuously solidifies into solid products of a certain shape and size. Cast iron profiles produced by horizontal continuous casting are divided into two main categories: pearlitic matrix and ferritic matrix. Pearlitic matrix cast iron profiles generally have higher performance. To transform the matrix structure into pearlite during horizontal continuous casting, three stages of spray cooling can be performed when the profile temperature is close to the eutectoid transformation point. This allows the matrix structure of the profile to undergo a non-equilibrium eutectoid transformation at a greater degree of supercooling, resulting in a pearlitic or pearlite-dominant structure.

[0003] To increase the pearlite content in the matrix of cast iron profiles, active disturbance rejection control (ADRC) can be used to control the spray cooling process parameters to achieve the desired cooling effect. In three-stage spray cooling, the cooling water used for spray cooling is usually recycled. During the circulation process, mineral concentration due to evaporation can occur, leading to changes in water quality. Even though the recycled water is filtered in the recovery tank, changes in spray pressure can disturb the water in the tank, causing a sudden drop in water quality. This drop in water quality leads to a decrease in the heat transfer coefficient, thus reducing the cooling effect. However, traditional ADRC uses a fixed feedback gain coefficient, which may lead to cooling runaway when water quality changes suddenly. This is because the fixed feedback gain coefficient cannot promptly increase the control input to compensate, resulting in a slower cooling rate and a decrease in the pearlite content in the cast iron profile matrix. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a three-stage spray cooling system and control method for horizontal continuous casting. The specific technical solution adopted is as follows: In a first aspect, embodiments of this application provide a method for controlling three-stage spray cooling in horizontal continuous casting, the method comprising the following steps: The temperature of the cast iron profile before and after cooling was collected at each time point, as well as the turbidity, spray pressure and spray flow rate of the cooling water at each time point. For the heat transfer coefficient between cooling water and cast iron profiles, the correlation between the heat transfer coefficient and the turbidity of cooling water is analyzed by measuring the heat transfer coefficient at various cooling water turbidity levels. Combined with the cooling water turbidity at each time point, the change in heat transfer coefficient at each time point is calculated. Based on the temperature before cooling and the temperature after cooling, the actual cooling rate at each time point is calculated, the cooling rate error at each time point is analyzed, and combined with the change in heat transfer coefficient, the water quality change error at each time point is calculated. The system variation error at each moment is calculated based on the changes in water spray pressure, water spray flow rate and the actual cooling rate at adjacent moments. The adaptive feedback gain coefficient at each moment is calculated based on the water quality change error and the system change error. Based on the adaptive feedback gain coefficient and the correlation between the cooling rate of the cooling water and the spray pressure, the control law of the active disturbance rejection controller at the current moment is determined, and the spray pressure is controlled by the active disturbance rejection controller.

[0005] In one embodiment, the process of obtaining the change in heat transfer coefficient at each time point is as follows: The linear fitting equation between heat transfer coefficient and turbidity was determined by measuring the heat transfer coefficient when the cooling water was at various turbidity levels. Let the change in heat transfer coefficient at time t be denoted as , The expression is: In the formula, k is the slope of the linear fitting equation. Let t be the turbidity of the cooling water at time t.

[0006] In one embodiment, the process of obtaining the cooling rate error at each moment is as follows: Calculate the difference between the temperature before cooling and the temperature after cooling at each moment, and take the ratio between the difference and the cooling time of the cast iron profile as the actual cooling rate of the cast iron profile at each moment; take the absolute value of the difference between the actual cooling rate and the preset expected cooling rate as the cooling rate error at each moment.

[0007] In one embodiment, the process of obtaining the water quality change error at each time point is as follows: By combining the energy conservation equation and the convective heat transfer formula, the relationship between the cooling rate v and the heat transfer coefficient h is obtained. Based on this relationship, the change in cooling rate when the heat transfer coefficient changes by a unit amount is determined. The change in cooling rate when the heat transfer coefficient changes by a unit amount at time t is denoted as... ;based on The change in heat transfer coefficient and the error in cooling rate are used to calculate the water quality change error at each moment.

[0008] In one embodiment, the expression for the water quality change error is: In the formula, The error in water quality change at time t; This represents the change in the heat transfer coefficient at time t; This represents the cooling rate error at time t.

[0009] In one embodiment, the expression for the system change error at each time point is: In the formula, This represents the system change error at time t. , and These represent the changes in cooling rate, water spray pressure, and water spray flow rate between time t and time t-1, respectively.

[0010] In one embodiment, the expression for the adaptive feedback gain coefficient at each time step is: In the formula, This represents the adaptive feedback gain coefficient at time t+1. This represents the adaptive feedback gain coefficient at time t. This represents the error in water quality change at time t. This represents the system change error at time t. This represents the normalization function.

[0011] In one embodiment, the water spray pressure control based on the adaptive feedback gain coefficient and in conjunction with the active disturbance rejection controller specifically includes: The linear fitting equation between water spray pressure and cooling rate is determined by the cooling rate corresponding to various water spray pressures under the current state, and is denoted as the first fitting equation. Based on the slope and intercept of the first fitting equation, combined with the error between the current cooling rate and the desired cooling rate, and the adaptive feedback gain coefficient for the next moment calculated based on the data collected at the current moment, the control law for the current moment is calculated. The thermal conductivity, initial heat transfer coefficient of the cast iron profile, and various parameters of the cooling water at the initial moment are used as the initial inputs of the active disturbance rejection controller. The control law at the current moment is used as the control law of the active disturbance rejection controller, and the output is a control signal for adjusting the water spray pressure. Based on the control signal, the opening of the valve is controlled by the pressure regulating valve to adjust the water spray pressure.

[0012] In one embodiment, the expression for the control law at the current moment is: In the formula, and These are the slope and intercept of the first fitted equation, respectively. Indicates the desired cooling rate; This indicates the error between the current cooling rate and the desired cooling rate; Yes Differentiate; The adaptive feedback gain coefficient for the next time step is calculated based on the data collected at the current time step. This represents the differential gain of the preset active disturbance rejection control algorithm. The unknown disturbance in the observer of the active disturbance rejection controller.

[0013] Secondly, embodiments of this application also provide a three-stage spray cooling system for horizontal continuous casting, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of any of the methods described above.

[0014] The embodiments of this application have at least the following beneficial effects: This application calculates the change in heat transfer coefficient by varying the turbidity of the cooling water, obtains the theoretical cooling rate by combining the heat balance formula and the convection heat transfer formula, then calculates the partial derivative of the heat transfer coefficient to obtain the change in cooling rate when the heat transfer coefficient changes by a unit amount, and calculates the water quality change error by combining the actual cooling rate error. Considering that water quality changes also affect the spray pressure and spray flow rate, the system change error is calculated. Furthermore, an adaptive feedback gain coefficient is obtained, and based on the adaptive feedback gain coefficient, spray pressure control is performed in conjunction with an active disturbance rejection controller. This avoids the problem of traditional active disturbance rejection control using a fixed feedback gain coefficient, which causes the actual cooling rate to deviate from the desired cooling rate, thus affecting the cooling effect, and improves the stability of the cooling process. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating the steps of a three-stage spray cooling control method for horizontal continuous casting provided in one embodiment of this application; Figure 2 This is a schematic diagram illustrating the process of obtaining the cooling rate error at various times. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the three-stage spray cooling system and control method for horizontal continuous casting proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the three-stage spray cooling system and control method for horizontal continuous casting provided in this application.

[0020] Please see Figure 1 The diagram illustrates a flowchart of a three-stage spray cooling control method for horizontal continuous casting according to an embodiment of this application. The method includes the following steps: Step S1: Collect the temperature of the cast iron profile before and after cooling at each time point, as well as the turbidity, spray pressure and spray flow rate of the cooling water at each time point.

[0021] The three-stage cooling device includes an inlet pipe, three square water tanks, and a recovery tank. The cast iron profile passes through the middle of the three square water tanks, and each square water tank has four nozzles that spray and cool the cast iron profile.

[0022] There is a pressure regulating valve at the water inlet pipe, which is used to regulate the spray pressure of the nozzle on the square water jacket. Turbidity sensor, temperature sensor, flow sensor and pressure sensor are installed 2cm after the pressure regulating valve, which are used to measure the turbidity of the cooling water, the spray temperature, the spray flow rate and the spray pressure, respectively. Temperature sensor 1 is installed on the support of the first square water tank, and temperature sensor 2 is installed on the support of the third square water tank. Temperature sensor 1 and temperature sensor 2 are used to measure the temperature of the cast iron profile before and after cooling, respectively.

[0023] For data acquisition from each of the aforementioned sensors, in this embodiment, the data acquisition frequency for each sensor is set to 10Hz. In other embodiments of this application, the implementer can set the data acquisition frequency according to actual conditions. All acquired data is cleaned to remove outliers, and the cleaned data is then interpolated using a data interpolation algorithm to fill in missing data. Both data cleaning and data interpolation algorithms are well-known techniques, and their specific processes will not be described in detail.

[0024] Step S2: For the heat transfer coefficient between cooling water and cast iron profile, the correlation between the heat transfer coefficient and the turbidity of cooling water is analyzed by measuring the heat transfer coefficient at various cooling water turbidity levels. Combined with the cooling water turbidity at each time, the change in heat transfer coefficient at each time is calculated. Based on the temperature before cooling and the temperature after cooling, the actual cooling rate at each time is calculated, the cooling rate error at each time is analyzed, and the water quality change error at each time is calculated by combining the change in heat transfer coefficient.

[0025] Pearlitic cast iron profiles have higher mechanical properties. In order to increase the pearlite content of cast iron profiles, three water spray cooling processes can be performed when the profiles are close to the eutectoid transformation temperature, resulting in a greater cooling rate. This allows the matrix structure of the profiles to undergo a non-equilibrium eutectoid transformation under greater supercooling, becoming a pearlitic or pearlitic-dominant structure.

[0026] In horizontal continuous casting, the cooling rate has a crucial impact on pearlite formation. When the cooling rate is too fast, carbon atom diffusion is insufficient, potentially leading to the transformation of austenite into non-pearlitic structures such as bainite or martensite. Conversely, when the cooling rate is too slow, the residence time at high temperatures is too long, allowing sufficient time for carbon atom diffusion, which may increase the precipitation of proeutectoid ferrite. With the precipitation of proeutectoid ferrite, the carbon content in austenite relatively increases, reducing the amount of pearlite formed during the eutectoid transformation.

[0027] Water spray pressure is a key factor affecting the cooling rate. By controlling the water spray pressure, the intensity of convective heat transfer between the cooling water and the casting billet can be adjusted, thereby controlling the cooling rate. Therefore, using an active disturbance rejection control algorithm to maintain the water spray pressure at a suitable value can control the cooling rate.

[0028] Because the cooling water is recycled, the evaporation of the water after spray cooling leads to mineral concentration and changes in water quality. When the cooling water has a high content of suspended solids, i.e., poor water quality, the heat transfer coefficient will decrease, and the cooling speed will slow down if the spray pressure remains unchanged. Moreover, the suspended solids in the cooling water may also clog the nozzles, reducing the spray flow rate and thus slowing down the cooling speed.

[0029] Therefore, it is necessary to consider the impact of water quality changes on the pearlite content in the matrix of cast iron profiles. Traditional active disturbance rejection control algorithms use a fixed feedback gain coefficient, which cannot respond in time when the water quality changes suddenly, which may cause the cooling rate to deviate from the desired cooling rate and cause a decrease in pearlite content. Therefore, by adjusting the feedback gain coefficient, the algorithm can respond quickly when the water quality changes and keep the cooling rate near the desired cooling rate.

[0030] In the active disturbance rejection control algorithm, there are two feedback gain coefficients, namely... and ,in Primarily used in the proportional gain stage of the algorithm, it directly adjusts the control input based on the error magnitude, with the adjustment effect being directly proportional to the error size. (Feedback gain coefficient) The larger the value, the greater the fluctuation range of the water spray pressure, meaning the faster the cooling rate adjusts to meet changes in water quality, quickly approaching the desired cooling rate; conversely, the feedback gain coefficient... The smaller the pressure, the smaller the fluctuation range of the water spray pressure. When changes in water quality cause errors in the cooling rate, the adjustment of the water spray pressure is more gentle, so as to avoid excessive adjustment that causes the cooling rate to fluctuate frequently around the ideal value and maintain the stability of the system.

[0031] (1) The heat transfer coefficient refers to the amount of heat transferred per unit area per unit time and per unit temperature difference. It is a physical quantity that measures the ease with which heat is transferred between two objects at different temperatures. In the embodiments of this application, the two objects at different temperatures refer to cooling water and cast iron profiles, respectively. When the cooling water contains a large number of mineral ions, suspended scale will form due to evaporation. These suspended scales increase the thermal resistance of heat transfer, making it more difficult for heat to be transferred from the cast iron profiles to the cooling water, thereby reducing the heat transfer coefficient. When the turbidity of the cooling water is 0, the heat transfer coefficient between the cooling water and the cast iron profiles is: Let be the initial heat transfer coefficient. The method for obtaining the initial heat transfer coefficient is a well-known technique, and the specific process will not be elaborated further.

[0032] To analyze the relationship between the turbidity and heat transfer coefficient of cooling water, the relationship between the heat transfer coefficient and turbidity is first expressed as: Where h is the current heat transfer coefficient, Let be the initial heat transfer coefficient, and k be the relationship coefficient. This represents the current turbidity of the cooling water.

[0033] The relationship coefficient k is a coefficient characterizing the degree of influence of turbidity on the heat transfer coefficient. It can be obtained by measuring the heat transfer coefficient of water samples with different turbidities, then performing linear fitting on the measurement results to obtain a fitting equation, and finally obtaining the relationship coefficient k based on the slope of the fitting equation. In this embodiment, the value of the relationship coefficient k is... The method for obtaining the fitted equation is a well-known technique, and the specific process will not be described in detail here.

[0034] Furthermore, the change in heat transfer coefficient at each moment is calculated based on the change in impurity content in the cooling water, characterizing the change in heat transfer capacity. The expression is: In the formula, represents the change in heat transfer coefficient at time t; k represents the relationship coefficient; This represents the turbidity of the cooling water at time t.

[0035] A smaller change in the heat transfer coefficient indicates lower turbidity in the cooling water, meaning a higher heat transfer coefficient. This indicates stronger heat exchange capacity in the cooling system, possibly due to the addition of new cooling water to the supply tank reducing suspended solids and improving water quality. In this case, the feedback gain coefficient should be reduced to minimize the fluctuation in spray pressure, thus bringing the cooling rate closer to the desired level and preventing frequent fluctuations. Conversely, a larger change indicates worse water quality, requiring an increase in the feedback gain coefficient to quickly adjust the spray pressure and prevent a slowdown in cooling speed.

[0036] (2) To analyze the error caused by changes in water quality, it can be determined based on the cooling rate error. In this embodiment, the expected cooling rate is: As another embodiment of this application, the implementer can set the desired cooling rate according to the actual situation; and the actual cooling rate can be calculated based on the temperature of the cast iron profile measured by the temperature sensor before and after spraying, specifically: The time taken for the cast iron profile to be drawn from temperature sensor 1 to temperature sensor 2 is recorded as the cooling time. Then, taking time t as an example, the temperature of temperature sensor 1 at time t is collected and recorded as the temperature before cooling at time t; the temperature of temperature sensor 2 at time t is collected and recorded as the temperature after cooling at time t; the difference between the temperature before cooling and the temperature after cooling at time t is calculated, and the ratio of this difference to the cooling time is taken as the actual cooling rate of the cast iron profile at time t.

[0037] Furthermore, the cooling rate error at time t is the absolute value of the difference between the expected cooling rate and the actual cooling rate of the cast iron profile at that time.

[0038] The larger the cooling rate error at time t, the less suitable the cooling rate is at that time, and the faster the water quality may change. In other words, the feedback gain coefficient should be increased to respond faster. Conversely, the smaller the cooling rate error at that time, the closer the cooling rate is to the expected cooling rate. In other words, the feedback gain coefficient should be decreased to reduce the variation in water spray pressure and maintain a stable cooling process.

[0039] (3) Since changes in the heat transfer coefficient will inevitably affect the cooling rate, and the error between the cooling rate and the expected cooling rate is calculated from the data measured by the sensor, which includes the sensor's own error and errors caused by other reasons, direct use may lead to an excessively large estimation error. To determine the influence of water quality changes, the water quality change error at each moment can be calculated based on the change in heat transfer coefficient and the cooling rate error, expressed as: In the formula, This represents the error in water quality change at time t; This represents the change in the heat transfer coefficient at time t; This represents the cooling rate error at time t; This represents the change in cooling rate when the heat transfer coefficient changes by a unit amount at time t, quantifying the degree of influence of the change in heat transfer coefficient on the cooling rate at that time. Among these, The acquisition process is as follows: First, obtain the cooling rate. The relationship between the heat transfer coefficient h and the heat transfer coefficient is as follows: Based on the principle of heat balance, the heat released by the cast iron profile per unit time is equal to the heat absorbed by the cooling water. The heat released by the cast iron profile is denoted as h. The heat absorbed by the cooling water is denoted as ,in, It can be derived from the formula = The calculation yields the result, and according to the convective heat transfer formula, we can obtain... This immediately yields the expression relating the theoretical cooling rate v to the heat transfer coefficient h. Then, by taking the partial derivative with respect to h, we can obtain the partial derivative number. The calculation expression is as follows: The formulas for calculating the heat released by the cast iron profile and the heat absorbed by the cooling water are both well-known. In the formulas, This indicates the density of the cast iron profile; in this embodiment, the density is 7200. V represents the volume of the cast iron profile in contact with water; This indicates the specific heat capacity of the cast iron profile; in this embodiment, the specific heat capacity is 500. A represents the surface area of ​​the cast iron profile in contact with water; This indicates the surface temperature of the cast iron profile. In this embodiment, the surface temperature is the average of the current temperatures of temperature sensor 1 and temperature sensor 2. This represents the current temperature of the cooling water, i.e., the spray temperature. Substituting the values ​​of the above parameters at the current moment into the partial derivative... In the calculation expression, the result represents the change in cooling rate when the current heat transfer coefficient changes by a unit amount. The principles of heat balance and convective heat transfer formulas are well-known techniques, and their specific processes will not be elaborated upon.

[0040] By multiplying the change in heat transfer coefficient by the partial derivative of cooling rate with respect to heat transfer coefficient, we can obtain the change in cooling rate caused by the change in heat transfer coefficient. Dividing this by the cooling rate error gives us the proportion of error caused by the change in heat transfer coefficient. Error caused by changes in water quality can be considered as a result of changes in heat transfer coefficient.

[0041] The larger the error caused by water quality changes, the greater the error in cooling rate caused by water quality changes. In this case, the feedback gain coefficient should be increased to achieve a fast response. Conversely, the smaller the part of the cooling rate error caused by water quality changes, the greater the error may be caused by sensor error or other reasons. In this case, the feedback gain coefficient should be decreased to maintain a stable cooling process.

[0042] Step S3: Calculate the system variation error at each time point based on the changes in water spray pressure, water spray flow rate, and the actual cooling rate at adjacent time points.

[0043] The water quality change error only considers the error caused by the change in heat transfer coefficient due to water quality changes. However, water quality changes not only affect the heat transfer coefficient but also the spray flow rate. Suspended matter formed by deteriorating water quality can clog the nozzle outlet, reducing the spray flow rate within the same time frame, thus slowing down the cooling rate and causing a discrepancy with the expected cooling rate. Furthermore, without using a pressure regulating valve to adjust the spray pressure, a decrease in spray flow rate may lead to an increase in the spray pressure within the square water jacket.

[0044] Therefore, the system variation error, excluding the error caused by water quality changes, can be calculated based on the changes in water flow rate and water pressure. The expression is: In the formula, This represents the system change error at time t. , and These represent the changes in actual cooling rate, water spray pressure, and water spray flow rate between time t and the previous time, respectively. The actual cooling rate change is the absolute value of the difference between the actual cooling rate at each time and the actual cooling rate at the previous time. The changes in water spray pressure and water spray flow rate are calculated using the same method as the actual cooling rate change.

[0045] The system variation error reflects the change in control input, that is, the degree to which the cooling rate changes when the water spray pressure and water spray flow change by one unit. Therefore, when the control input changes due to water quality changes, the cooling rate also changes, and the feedback gain coefficient should be adjusted in time.

[0046] The larger the system variation error, the greater the impact of water quality changes on the water spray flow rate and pressure. In other words, the feedback gain coefficient should be increased to enable the controller to respond quickly and adjust the water spray pressure in time so that the cooling rate is close to the desired cooling rate. Conversely, the smaller the impact of changes in water spray pressure and flow rate, the smaller the feedback gain coefficient should be.

[0047] Step S4: Calculate the adaptive feedback gain coefficient at each time point based on the water quality change error and the system change error.

[0048] The desired cooling rate in this embodiment is set based on the eutectoid temperature of the cast iron profile. However, the actual cooling rate will deviate from the ideal value due to the interference of water quality changes. The error between the actual cooling rate and the desired cooling rate reflects the degree of this deviation. The purpose of adaptive control is to reduce the error and make the actual cooling rate approach the desired cooling rate.

[0049] Therefore, the adaptive feedback gain coefficient at each moment is calculated based on the water quality change error and system change error at each moment, and the expression is as follows: In the formula, This represents the adaptive feedback gain coefficient at time t+1. This represents the adaptive feedback gain coefficient at time t. This represents the error in water quality change at time t. This represents the system change error at time t. This represents the normalization function. Multiplying by 2 limits the adaptive adjustment range of the feedback gain coefficient. It should be noted that when t is 1, the initial feedback gain coefficient is used as the adaptive feedback gain coefficient at that moment. Preferably, in this embodiment, the initial feedback gain coefficient is set to 0.5; simultaneously, the product of the water quality change error and the system change error at that moment is set to 1. As other embodiments of this application, the implementer can set the product of the water quality change error and the system change error at that moment, as well as the initial feedback gain coefficient, according to actual conditions.

[0050] Step S5: Based on the adaptive feedback gain coefficient and the correlation between the cooling rate of the cooling water and the spray pressure, determine the control law of the active disturbance rejection controller at the current moment, and use the active disturbance rejection controller to control the spray pressure.

[0051] When using an active disturbance rejection controller to control the water spray pressure, the water spray pressure under the current state must first be determined. and cooling speed Specifically, in this embodiment, under the current spraying state, the cooling rate is measured at multiple preset spray pressures through experiments. All spray pressures and their corresponding measured cooling rates are used as inputs for least squares linear fitting. The resulting linear fitting equation is denoted as... ,in and These represent the slope and intercept of the linear fitting equation, respectively. The method for obtaining the linear fitting equation between water spray pressure and cooling rate, as well as the least squares linear fitting method, are well-known techniques, and their specific processes will not be elaborated upon here.

[0052] Subsequently, the thermal conductivity and initial heat transfer coefficient of the cast iron profile, as well as the initial spray pressure, initial spray temperature, initial spray flow rate, spray distance, and spray length of the cooling water, are used as the initial inputs to the controller. In this embodiment, the thermal conductivity of the cast iron profile is... The initial spray pressure, initial spray temperature, and initial spray flow rate of the cooling water can be measured by the sensor corresponding to the initial moment. The measurement method is a well-known technology, and the specific process will not be described in detail. The spray distance refers to the distance from the nozzle to the cast iron profile, and the spray length refers to the length of the cast iron profile covered by the spray range of the three square water jackets.

[0053] For the interference observer, an extended state observer is used, assuming... , Its state equation is , Where D represents unknown interference. , The derivative of the state variable. , This represents the estimated value of the state variable. The initial estimated value and the initial disturbance are both set to 0. In this embodiment, the estimated value is calculated using the Euler method. , Indicating the observer gain, preferably, in this embodiment, it will be... Set the value to 100, The value is set to 20. As another embodiment of this application, the implementer may set it according to the actual situation.

[0054] Equations of state and It is the derivative of the state variable, which describes the rate of change of the state variable over time. This represents the linear relationship of cooling rate based on water spray pressure. This demonstrates the impact of unknown disturbances on the rate of change of cooling speed. and It is the observer's correction term, in which , These are observer gains, which play a role in adjusting the performance of the observer. It is the error between the actual state and the estimated state. This error feedback is used to continuously correct the estimated value, so that the observer can track the actual state more accurately.

[0055] It should be noted that this application provides only one calculation method for the estimated value. There are many existing methods for calculating the estimated value, and implementers may also use other algorithms to calculate the estimated value. This application does not impose any specific restrictions.

[0056] Calculate the control law at the current moment Its formula is ,in Indicates the desired cooling rate; This indicates the error between the current cooling rate and the desired cooling rate; Yes Differentiate; The adaptive feedback gain coefficient for the next time step is calculated based on the data collected at the current time step. This represents the differential gain of the active disturbance rejection control algorithm. Preferably, in the embodiments of this application, The initial value is set to 0.5. The initial value is set to 0.1. As another embodiment of this application, the implementer can set it according to the actual situation. initial value and The initial value.

[0057] Furthermore, the control law at the current moment is used as the control law of the active disturbance rejection controller. The output of the active disturbance rejection controller is a control signal for adjusting the water spray pressure. This control signal is then sent to the actuator, which controls the opening of the valve through the pressure regulating valve, thereby adjusting the water spray pressure.

[0058] A schematic diagram illustrating the process of obtaining the cooling rate error at various times is shown below. Figure 2 As shown.

[0059] Based on the same inventive concept as the above methods, embodiments of this application also provide a three-stage spray cooling system for horizontal continuous casting, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the three-stage spray cooling control methods for horizontal continuous casting described above.

[0060] In summary, this application provides a three-stage spray cooling control method for horizontal continuous casting. It calculates the change in heat transfer coefficient by analyzing the change in turbidity in the cooling water, obtains the theoretical cooling rate by combining the heat balance formula and the convective heat transfer formula, calculates the partial derivative of the heat transfer coefficient to obtain the change in cooling rate per unit change in the heat transfer coefficient, and then calculates the water quality change error by combining the actual cooling rate error. Considering that water quality changes also affect the spray pressure and flow rate, the system change error is also calculated. Furthermore, an adaptive feedback gain coefficient is obtained, and based on this adaptive feedback gain coefficient, the spray pressure is controlled using an active disturbance rejection controller. This avoids the problem of traditional active disturbance rejection control using a fixed feedback gain coefficient, which causes the actual cooling rate to deviate from the desired cooling rate, thus affecting the cooling effect and improving the stability of the cooling process.

[0061] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this application. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0062] The various embodiments in this application are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0063] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A three-stage spray cooling control method for horizontal continuous casting, characterized in that, The method includes the following steps: The temperature of the cast iron profile before and after cooling was collected at each time point, as well as the turbidity, spray pressure and spray flow rate of the cooling water at each time point. For the heat transfer coefficient between cooling water and cast iron profiles, the correlation between the heat transfer coefficient and the turbidity of cooling water is analyzed by measuring the heat transfer coefficient at various cooling water turbidity levels. Combined with the cooling water turbidity at each time point, the change in heat transfer coefficient at each time point is calculated. Based on the temperature before cooling and the temperature after cooling, the actual cooling rate at each time point is calculated, the cooling rate error at each time point is analyzed, and combined with the change in heat transfer coefficient, the water quality change error at each time point is calculated. The system variation error at each moment is calculated based on the changes in water spray pressure, water spray flow rate and the actual cooling rate at adjacent moments. The adaptive feedback gain coefficient at each moment is calculated based on the water quality change error and the system change error. Based on the adaptive feedback gain coefficient and the correlation between the cooling rate of the cooling water and the spray pressure, the control law of the active disturbance rejection controller at the current moment is determined, and the spray pressure is controlled by the active disturbance rejection controller.

2. The three-stage spray cooling control method for horizontal continuous casting as described in claim 1, characterized in that, The process for obtaining the change in heat transfer coefficient at each time point is as follows: The linear fitting equation between heat transfer coefficient and turbidity was determined by measuring the heat transfer coefficient when the cooling water was at various turbidity levels. Let the change in heat transfer coefficient at time t be denoted as , The expression is: In the formula, k is the slope of the linear fitting equation. Let t be the turbidity of the cooling water at time t.

3. The three-stage spray cooling control method for horizontal continuous casting as described in claim 1, characterized in that, The process for obtaining the cooling rate error at each moment is as follows: Calculate the difference between the temperature before cooling and the temperature after cooling at each moment, and take the ratio between the difference and the cooling time of the cast iron profile as the actual cooling rate of the cast iron profile at each moment; take the absolute value of the difference between the actual cooling rate and the preset expected cooling rate as the cooling rate error at each moment.

4. The three-stage spray cooling control method for horizontal continuous casting as described in claim 1, characterized in that, The process for obtaining the water quality change error at each time point is as follows: By combining the energy conservation equation and the convective heat transfer formula, the relationship between the cooling rate v and the heat transfer coefficient h is obtained. Based on this relationship, the change in cooling rate when the heat transfer coefficient changes by a unit amount is determined. The change in cooling rate when the heat transfer coefficient changes by a unit amount at time t is denoted as... ;based on The change in heat transfer coefficient and the error in cooling rate are used to calculate the water quality change error at each moment.

5. The three-stage spray cooling control method for horizontal continuous casting as described in claim 4, characterized in that, The expression for the water quality change error is: In the formula, The error in water quality change at time t; This represents the change in the heat transfer coefficient at time t; This represents the cooling rate error at time t.

6. The three-stage spray cooling control method for horizontal continuous casting as described in claim 1, characterized in that, The expression for the system change error at each time point is: In the formula, The error representing the system change at time t. , and These represent the changes in cooling rate, water spray pressure, and water spray flow rate between time t and time t-1, respectively.

7. The three-stage spray cooling control method for horizontal continuous casting as described in claim 1, characterized in that, The expression for the adaptive feedback gain coefficient at each time point is: In the formula, This represents the adaptive feedback gain coefficient at time t+1. This represents the adaptive feedback gain coefficient at time t. This represents the error in water quality change at time t. The error representing the system change at time t. This represents the normalization function.

8. The three-stage spray cooling control method for horizontal continuous casting as described in claim 1, characterized in that, The water spray pressure control based on the adaptive feedback gain coefficient and in conjunction with the active disturbance rejection controller is specifically as follows: The linear fitting equation between water spray pressure and cooling rate is determined by the cooling rate corresponding to various water spray pressures under the current state, and is denoted as the first fitting equation. Based on the slope and intercept of the first fitting equation, combined with the error between the current cooling rate and the desired cooling rate, and the adaptive feedback gain coefficient for the next moment calculated based on the data collected at the current moment, the control law for the current moment is calculated. The thermal conductivity, initial heat transfer coefficient of the cast iron profile, and various parameters of the cooling water at the initial moment are used as the initial inputs of the active disturbance rejection controller. The control law at the current moment is used as the control law of the active disturbance rejection controller, and the output is a control signal for adjusting the water spray pressure. Based on the control signal, the opening of the valve is controlled by the pressure regulating valve to adjust the water spray pressure.

9. The three-stage spray cooling control method for horizontal continuous casting as described in claim 8, characterized in that, The expression for the control law at the current moment is: In the formula, and These are the slope and intercept of the first fitted equation, respectively. Indicates the desired cooling rate; This indicates the error between the current cooling rate and the desired cooling rate; Yes Differentiate; The adaptive feedback gain coefficient for the next time step is calculated based on the data collected at the current time step. This represents the differential gain of the preset active disturbance rejection control algorithm. The unknown disturbance in the observer of the active disturbance rejection controller.

10. A three-stage spray cooling system for horizontal continuous casting, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-9.

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