Control method, device and equipment for smelting smoke hood subplate and medium

Abstract

The invention relates to a control method, device and equipment for a smelting smoke hood subplate and a medium, and the method comprises the steps: according to the deformation, temperature and airflow field of the smoke hood subplate under different historical smelting furnace powers, simulating and mapping a smoke hood temperature field, a smoke hood airflow field and a smoke hood stress field through multi-physics field coupling, and constructing a digital twin three-dimensional dynamic model; inputting the temperature and the airflow intensity of the auxiliary plate of the smoke hood and the deformation degree of the key area of the auxiliary plate in the smelting process into the digital twin three-dimensional dynamic model to obtain predicted surface temperature distribution, predicted smoke component concentration and predicted smelting furnace power; determining a corrected combined parameter value according to the real smelting power and the predicted smelting furnace power, and correcting the predicted surface temperature distribution and the predicted flue gas component concentration according to the corrected combined parameter value to obtain target surface temperature distribution and target flue gas component concentration; and generating control parameters according to the target surface temperature distribution and the target flue gas component concentration, and controlling the opening degree of the subplate according to the control parameters.

Description

Technical Field

[0001] The present disclosure relates to the technical field of metallurgical industry, and particularly to a control method, device, equipment and medium for a secondary plate of a smelting hood. Background Art

[0002] The secondary plate of the hood is usually used in cooperation with the main hood. Through a reasonably designed air flow channel, it enhances the flue gas suction capacity and reduces the escape of flue gas. At the same time, at the edges or equipment connection points that are difficult to be covered by the main hood, it fills the gaps to ensure the effective collection of flue gas. At the same time, the secondary plate of the hood can guide the flue gas to flow along a predetermined path, increase the contact time between the flue gas and the purification device (such as spraying, filter layer), and improve the purification effect.

[0003] However, the traditional control methods for the secondary plate of the smelting hood mainly rely on manual experience or fixed logic control such as PID regulation, and there are many technical defects. For example, the temperature field control accuracy is insufficient. Depending on the single-point thermocouple for temperature measurement, it cannot capture the overall temperature distribution on the surface of the secondary plate, resulting in local overheating or overcooling and causing thermal stress cracks. At the same time, although the infrared thermal imager can provide two-dimensional temperature field data, there are limitations, resulting in a large prediction error of the internal temperature gradient (the measured deviation often exceeds 20%). Moreover, the control strategy only considers a single physical field (such as only adjusting the air volume to reduce the flue gas temperature), without considering the stress uniformity, resulting in excessive consumption of cooling water; without dynamically balancing the pressure drop and the heat exchange efficiency, resulting in large fluctuations in the flue gas flow rate. Summary of the Invention

[0004] The purpose of the present invention is to provide a control method, device, equipment and medium for a secondary plate of a smelting hood, aiming to improve the accuracy of the control of the secondary plate of the smelting hood, reduce the fluctuation of the flue gas flow rate, and further reduce the consumption of cooling water and save costs.

[0005] To achieve the above purpose, in the first aspect of the embodiments of the present disclosure, a control method for a secondary plate of a smelting hood is provided, and the method includes:

[0006] According to the deformation information, temperature information and air flow field information of the key area of the secondary plate under different historical control parameters of the secondary plate of the hood, map the temperature field, air flow field and stress field of the hood through multi-physical field coupling simulation, and construct a digital twin three-dimensional dynamic model of the secondary plate of the smelting hood;

[0007] Input the temperature, air flow intensity at the secondary plate of the hood and the deformation degree of the key area of the secondary plate obtained during the smelting process into the digital twin three-dimensional dynamic model, and obtain the predicted surface temperature distribution of the secondary plate of the hood during the smelting process, the predicted flue gas component concentration and the predicted smelting furnace power for the smelting furnace output by the digital twin three-dimensional dynamic model;

[0008] According to the actual smelting power of the smelting furnace and the predicted smelting furnace power during the smelting process, the correction combination parameter values for the predicted surface temperature distribution of the fume hood sub-plate and the predicted flue gas component concentration are determined, and the predicted surface temperature distribution and the predicted flue gas component concentration of the fume hood sub-plate are respectively corrected according to the corrected combination parameter values to obtain the target surface temperature distribution and the target flue gas component concentration;

[0009] According to the target surface temperature distribution and the target fume component concentration, control parameters for controlling the smelting fume hood sub-plate are generated, and according to the control parameters, the sub-plate opening of the smelting fume hood sub-plate is controlled.

[0010] In a possible implementation, according to the deformation information, temperature information and airflow field information of the key area of the hood sub-plate under different historical control parameters, the hood temperature field, hood airflow field and hood stress field are mapped through multi-physical field coupling simulation to construct a digital twin three-dimensional dynamic model of the smelting hood sub-plate, including:

[0011] The hood stress field of the hood sub-plate is constructed according to the deformation information of the key area of the sub-plate under different historical control parameters, and the hood temperature field of the hood sub-plate is constructed according to the temperature information of the hood sub-plate under different historical control parameters, and the hood airflow field of the hood sub-plate is constructed according to the airflow field information of the hood sub-plate under different historical control parameters;

[0012] The fume hood stress field of the fume hood sub-plate under different historical control parameters is coupled with the airflow field information to establish a first coupling control equation, and the fume hood temperature field of the fume hood sub-plate under different historical control parameters is coupled with the airflow field information to establish a second coupling control equation;

[0013] Numerically solving and iteratively calculating the equation group consisting of the first coupled control equation and the second coupled control equation to obtain the Jacobian matrix of the equation group and update the solutions of the smoke hood temperature field, the smoke hood airflow field and the smoke hood stress field;

[0014] According to the solutions of the smoke hood temperature field, the smoke hood airflow field and the smoke hood stress field obtained by each iterative calculation update, a digital twin three-dimensional dynamic model of the smelting smoke hood sub-plate is constructed.

[0015] In a possible implementation, numerically solving and iteratively calculating the equation group consisting of the first coupled control equation and the second coupled control equation to obtain the Jacobian matrix of the equation group and update the solutions of the smoke hood temperature field, the smoke hood airflow field, and the smoke hood stress field include:

[0016] After the auxiliary baffle of the hood is opened under different historical control parameters, the air duct formed by the auxiliary baffle of the hood is divided into grids with the minimum opening degree of the auxiliary baffle of the hood as the side length, and the control volume corresponding to each historical control parameter is obtained. Each control volume corresponds to one grid;

[0017] Based on the conservation principle, according to the volume coefficient corresponding to each control volume and the volume coefficients of the adjacent control volumes of each control volume, the equations are integrated on each control volume corresponding to each historical control parameter to obtain the discrete equation corresponding to each historical control parameter;

[0018] The discrete equations corresponding to each historical control parameter are partially differentiated to obtain the Jacobian matrix of the equations, and the discrete equations are solved by an iterative method to obtain and update the solutions of the hood temperature field, the hood air flow field and the hood stress field.

[0019] In a possible implementation manner, after the auxiliary baffle of the hood is opened under different historical control parameters, the air duct formed by the auxiliary baffle of the hood is divided into grids with the minimum opening degree of the auxiliary baffle of the hood as the side length, and the control volume corresponding to each historical control parameter is obtained, including:

[0020] According to the opening degree of the auxiliary baffle of the hood after the auxiliary baffle of the hood is opened under different historical control parameters, the opening angle of the auxiliary baffle of the hood under different historical control parameters is determined. The opening angle is the included angle between the auxiliary baffle of the hood and the horizontal plane under different historical control parameters;

[0021] According to the minimum opening degree of the auxiliary baffle of the hood, the width of the auxiliary baffle of the hood, and the opening angle of the auxiliary baffle of the hood under different historical control parameters, the effective volume of the air duct formed by the auxiliary baffle of the hood under different historical control parameters is determined;

[0022] The air duct formed under different historical control parameters is divided into grids with the minimum opening degree of the auxiliary baffle of the hood as the side length, and the effective volume of the air duct formed under different historical control parameters is divided into grids to obtain the control volume corresponding to each historical control parameter.

[0023] In a possible implementation manner, according to the minimum opening degree of the auxiliary baffle of the hood, the width of the auxiliary baffle of the hood, and the opening angle of the auxiliary baffle of the hood under different historical control parameters, determining the effective volume of the air duct formed by the auxiliary baffle of the hood under different historical control parameters includes:

[0024] According to the opening angle of the auxiliary baffle of the hood under different historical control parameters, calculate the effective windward area of the hood auxiliary baffle when the gas is blocked by the hood auxiliary baffle;

[0025] Move the scanning line along the length direction of the auxiliary baffle of the hood with the minimum opening of the auxiliary baffle of the hood as the step size to obtain the scanning line coordinates of multiple scanning lines along the length direction;

[0026] According to the opening angle of the auxiliary baffle of the hood and the width of the auxiliary baffle of the hood under different historical control parameters, solve the intersection points of each scanning line with the upper and lower boundaries of the air duct formed under different historical control parameters;

[0027] According to the intersection points of the upper and lower boundaries corresponding to each scanning line, determine the area between lines of the area between adjacent scanning lines, and sum the areas between lines under different historical control parameters to obtain the total cross-sectional area under different historical control parameters;

[0028] Along the air flow direction of the air duct under different historical control parameters, discretize the total cross-sectional area with the minimum opening of the auxiliary baffle of the hood as the opening to determine the effective volume of the air duct formed by the auxiliary baffle of the hood under different historical control parameters.

[0029] In a possible implementation manner, the determining the corrected combined parameter values of the predicted surface temperature distribution and the predicted flue gas component concentration for the auxiliary baffle of the hood according to the actual melting power of the melting furnace and the predicted melting furnace power during the melting process includes:

[0030] Determine the prediction deviation according to the actual melting power of the melting furnace and the predicted melting furnace power during the melting process;

[0031] Update the state transition matrix according to the prediction deviation to obtain the updated state transition matrix;

[0032] Multiply the updated state transition matrix by the transpose of the current prediction covariance to obtain the updated state covariance;

[0033] Determine the gain according to the first product of the updated state covariance and the transpose of the observation matrix, and the second product of the observation matrix, the updated prediction covariance and the transpose of the observation matrix;

[0034] Determine a first correction parameter value for the predicted surface temperature distribution of the secondary hood plate according to the predicted surface temperature distribution, the gain, and the predicted deviation, and determine a second correction parameter value for the predicted flue gas component concentration of the secondary hood plate according to the predicted flue gas component concentration, the gain, and the predicted deviation;

[0035] Determine a corrected combined parameter value for the predicted surface temperature distribution and the predicted flue gas component concentration of the secondary hood plate according to the first correction residual value and the second correction parameter value.

[0036] In a possible implementation manner, a cooling pipeline with a direction consistent with the length direction is arranged along the length direction of the secondary hood plate;

[0037] The method further includes:

[0038] Determine the average surface temperature and the maximum temperature difference according to the target surface temperature distribution, and determine whether the cooling water filling condition for activating the cooling pipeline is satisfied according to the first difference between the average surface temperature and a preset average threshold value and the second difference between the maximum temperature difference and a preset temperature difference threshold value;

[0039] When it is determined that the cooling water filling condition is satisfied, determine a first flow rate according to the product of the first difference and a first gain coefficient and a first base flow rate, and determine a second flow rate according to the product of the second difference and a second gain coefficient and a second base flow rate;

[0040] Determine the cooling water flow rate by weighted summation according to the first flow rate, the second flow rate, and the weight corresponding to each flow rate, and control the cooling water filling according to the cooling water flow rate.

[0041] In a second aspect of the embodiments of the present disclosure, a control device for a secondary hood plate of a smelting furnace is provided, including:

[0042] A determination module configured to map the temperature field, the airflow field, and the stress field of the hood through multi-physical field coupling simulation according to the deformation information, temperature information, and airflow field information of the key area of the secondary hood plate under different historical control parameters, and construct a digital twin three-dimensional dynamic model of the secondary hood plate of the smelting furnace;

[0043] An input module configured to input the temperature, airflow intensity, and deformation degree of the key area of the secondary hood plate during the smelting process into the digital twin three-dimensional dynamic model, and obtain the predicted surface temperature distribution, predicted flue gas component concentration of the secondary hood plate during the smelting process, and the predicted smelting furnace power of the smelting furnace output by the digital twin three-dimensional dynamic model;

[0044] A correction module, configured to determine a corrected combined parameter value for the predicted surface temperature distribution and the predicted flue gas component concentration of the hood secondary plate according to the actual smelting power of the smelting furnace and the predicted smelting furnace power during the smelting process, and correct the predicted surface temperature distribution and the predicted flue gas component concentration of the hood secondary plate respectively according to the corrected combined parameter value to obtain a target surface temperature distribution and a target flue gas component concentration;

[0045] A control module, configured to generate control parameters for controlling the hood secondary plate according to the target surface temperature distribution and the target flue gas component concentration, and control the opening degree of the secondary plate of the smelting hood according to the control parameters.

[0046] In a third aspect of the embodiments of the present disclosure, an electronic device is provided, including:

[0047] A memory, on which a computer program is stored;

[0048] A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of the first aspect.

[0049] In a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the steps of the method according to any one of the first aspect are implemented.

[0050] The present invention provides a control method, device, equipment and medium for a smelting hood secondary plate. Compared with the prior art, the following beneficial effects are achieved:

[0051] By integrating multi-physical field data such as deformation, temperature, and airflow field under historical control parameters, a high-fidelity digital twin model is established to accurately map the dynamic control process of the hood secondary plate, and the stress concentration area of the hood can be predicted in advance according to the twin model to avoid control failure caused by deformation. Then, by comparing the actual smelting power with the predicted power, the predicted values of the temperature distribution and the flue gas components are corrected to generate a target surface temperature distribution and a target flue gas component concentration, improving the accuracy of the control parameters. Reducing the frequent adjustment of the hood secondary plate caused by prediction deviation and stabilizing the flue gas flow rate. Generating a control instruction for the opening degree of the secondary plate according to the corrected target parameters to achieve adaptive adjustment. Further, by accurately controlling the opening degree of the secondary plate, the violent change of the airflow is avoided, the impact on the cooling system is reduced, and the fluctuation of the flue gas flow rate is reduced. At the same time, the stable temperature field and airflow field can reduce the cooling water demand, directly reducing the energy consumption and operating costs.

[0052] Other features and advantages of the present disclosure will be described in detail in the subsequent specific implementation part. Description of the Drawings

[0053] The accompanying drawings are used to provide a further understanding of the present disclosure and form a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure, but do not constitute a limitation to the present disclosure. In the accompanying drawings:

[0054] Figure 1 is a flowchart of a control method for a secondary plate of a smelting hood shown according to an embodiment of the specification.

[0055] Figure 2 is a block diagram of a control device for a secondary plate of a smelting hood shown according to an embodiment of the specification.

[0056] Figure 3 is a block diagram of a control device for a secondary plate of a smelting hood shown according to an embodiment of the specification. Specific Embodiments

[0057] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0058] The following will describe in detail the specific embodiments of the present disclosure in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present disclosure, and are not used to limit the present disclosure.

[0059] The present disclosure provides a control method for a secondary plate of a smelting hood, Figure 1 is a flowchart of a control method for a secondary plate of a smelting hood shown according to an embodiment. Specifically, the method includes:

[0060] In step S11, according to the deformation information, temperature information, and airflow field information of the key area of the secondary plate under different historical control parameters of the secondary plate of the hood, the temperature field, airflow field, and stress field of the hood are mapped through multi-physics field coupling simulation, and a digital twin three-dimensional dynamic model of the secondary plate of the smelting hood is constructed;

[0061] Among them, multi-physics coupling simulation can numerically couple physical phenomena such as heat conduction (temperature field), fluid mechanics (airflow field), and structural mechanics (stress field), and simulate multi-physical interactions under actual working conditions. The digital twin three-dimensional dynamic model is a virtual model created using digital technology that is consistent with the height of the secondary plate of the smelting hood. This model not only has the three-dimensional geometric characteristics of the secondary plate of the smelting hood but also can reflect the dynamic changes of the secondary plate of the smelting hood under different working conditions in real time, such as changes in parameters such as temperature, stress, and deformation. Through data interaction with the secondary plate of the smelting hood, monitoring, prediction, and control of the secondary plate of the smelting hood are achieved. The key area is the area where deformation, temperature, or stress concentration occurs in the secondary plate of the hood (such as high-temperature areas and stress crack prone points).

[0062] In the embodiments of the present disclosure, the heat conduction equation can be solved based on the finite element method (FEM), considering heat radiation and convective boundary conditions. Computational fluid dynamics (CFD) is used to simulate the flue gas flow, combined with a turbulence model (such as the k-ε model). The thermal stress and mechanical stress superposition are calculated through structural mechanics analysis. Furthermore, the results of each physical field are mapped to the three-dimensional geometric model to form a dynamically associated digital twin model.

[0063] In the embodiments of the present disclosure, a coupling relationship model among the temperature field of the hood, the airflow field of the hood, and the stress field of the hood is established using multi-physics coupling simulation technology. In the coupling model, the influence of the temperature field on the coefficient of thermal expansion of the material is considered, which in turn affects the stress field; changes in the stress field will cause material deformation and affect the flow of the airflow field; at the same time, the flow of the airflow field will carry away heat and affect the distribution of the temperature field. Through this complex coupling relationship, the historical data collected is mapped to construct a digital twin three-dimensional dynamic model that can reflect the dynamic changes of the secondary plate of the hood under various working conditions. This model can simulate the physical state of the secondary plate of the hood under different conditions in real time.

[0064] In step S12, the temperature, airflow intensity at the secondary plate of the hood, and the degree of deformation of the key area of the secondary plate obtained during the smelting process are input into the digital twin three-dimensional dynamic model, and the digital twin three-dimensional dynamic model outputs the predicted surface temperature distribution of the secondary plate of the hood during the smelting process, the predicted flue gas component concentration, and the predicted smelting furnace power for the smelting furnace.

[0065] Among them, predicting the surface temperature distribution is based on the digital twin model to predict the temperature values and distribution of each position on the surface of the secondary plate of the smelting hood during a specific smelting process according to the input conditions (such as temperature, air flow intensity, deformation degree, etc.) through the internal calculation and analysis of the model. Predicting the concentration of flue gas components is to use the digital twin model to predict the concentration values and distribution of various components (such as carbon monoxide, carbon dioxide, nitrogen oxides, etc.) in the flue gas around the secondary plate of the smelting hood during the smelting process according to the input conditions. Predicting the power of the smelting furnace is that the digital twin model predicts the power value required by the smelting furnace during the smelting process according to the relevant information of the secondary plate of the smelting hood.

[0066] In the embodiments of the present disclosure, during the smelting process, data such as the temperature, air flow intensity at the secondary plate of the smelting hood, and the deformation degree of the key area of the secondary plate are obtained in real time through sensors. These actually measured data are input into the already constructed digital twin three-dimensional dynamic model. The model calculates and analyzes the physical state of the secondary plate of the smelting hood during the smelting process by using the internally established mathematical models and algorithms. Specifically, the model will consider the interaction between the temperature field, air flow field, and stress field to predict the surface temperature distribution of the secondary plate of the smelting hood, that is, the temperature values of each position on the surface of the secondary plate; at the same time, according to factors such as the air flow field and chemical reactions, the concentration distribution of various components in the flue gas is predicted; in addition, in combination with the operating mechanism of the smelting furnace, the power value required by the smelting furnace under the current working conditions is predicted.

[0067] In step S13, according to the actual smelting power of the smelting furnace and the predicted smelting furnace power during the smelting process, a corrected combined parameter value for the predicted surface temperature distribution and the predicted flue gas component concentration of the secondary plate of the smelting hood is determined, and the predicted surface temperature distribution and the predicted flue gas component concentration of the secondary plate of the smelting hood are corrected respectively according to the corrected combined parameter value to obtain the target surface temperature distribution and the target flue gas component concentration;

[0068] In the embodiments of the present disclosure, the actual smelting power of the smelting furnace during the smelting process is compared with the predicted smelting furnace power output by the digital twin model. If there is a difference between the two, it indicates that there may be a certain deviation in the model prediction. In order to make the prediction result more accurate, a corrected combined parameter value needs to be determined. The determination of this corrected combined parameter value needs to comprehensively consider various factors, such as the difference between the actual smelting power and the predicted smelting furnace power, the material properties of the secondary plate of the smelting hood, the requirements of the smelting process, etc. According to the determined corrected combined parameter value, the predicted surface temperature distribution and the predicted flue gas component concentration output by the digital twin model are corrected respectively. The correction method can be to establish a correction function, substitute the corrected combined parameter value into the function, and adjust the prediction result to obtain a target surface temperature distribution and a target flue gas component concentration closer to the actual situation.

[0069] In step S14, according to the target surface temperature distribution and the target flue gas component concentration, control parameters for controlling the auxiliary plate of the smelting hood are generated, and according to the control parameters, the opening degree of the auxiliary plate of the smelting hood is controlled.

[0070] Among them, the opening degree of the auxiliary plate is the opening degree of the auxiliary plate of the smelting hood. By controlling the opening degree of the auxiliary plate, parameters such as the airflow field and temperature field in the hood can be adjusted.

[0071] In the embodiments of the present disclosure, according to the obtained target surface temperature distribution and target flue gas component concentration, combined with the requirements of the smelting process and the working characteristics of the auxiliary plate of the hood, control parameters for controlling the auxiliary plate of the smelting hood are generated. For example, if the target surface temperature distribution shows that the temperature in some areas of the auxiliary plate is too high, it may be necessary to adjust the opening degree of the auxiliary plate to increase the airflow rate to reduce the temperature; if the target flue gas component concentration does not meet the environmental protection requirements, it may be necessary to adjust the opening degree of the auxiliary plate to optimize the airflow field and promote the full combustion and emission of the flue gas. According to the generated control parameters, the opening degree of the auxiliary plate of the smelting hood is controlled in real time through the control system to optimize and adjust the smelting process, improve the smelting efficiency and quality, and at the same time reduce energy consumption and environmental pollution.

[0072] The above technical solution fuses multi-physical field data such as deformation, temperature, and airflow field under historical control parameters, establishes a high-fidelity digital twin model, accurately maps the dynamic control process of the auxiliary plate of the hood, and can predict the stress concentration area of the hood in advance according to the twin model to avoid control failure caused by deformation. Then, by comparing the actual smelting power with the predicted power, the predicted values of the temperature distribution and flue gas components are corrected to generate the target surface temperature distribution and target flue gas component concentration, improving the accuracy of the control parameters. Reduce the frequent adjustment of the auxiliary plate of the hood caused by prediction deviation and stabilize the flue gas flow rate. According to the corrected target parameters, a control command for the opening degree of the auxiliary plate is generated to achieve adaptive adjustment. Further, by accurately controlling the opening degree of the auxiliary plate, the drastic change of the airflow is avoided, the impact on the cooling system is reduced, and the fluctuation of the flue gas flow rate is reduced. At the same time, the stable temperature field and airflow field can reduce the demand for cooling water, directly reducing energy consumption and operating costs.

[0073] In a possible implementation manner, in step S11, according to the deformation information, temperature information, and airflow field information of the key areas of the auxiliary plate of the hood under different historical control parameters, the temperature field, airflow field, and stress field of the hood are mapped through multi-physical field coupling simulation, and the digital twin three-dimensional dynamic model of the auxiliary plate of the smelting hood is constructed, including:

[0074] In step S111, according to the deformation information of the key areas of the auxiliary hood plate under different historical control parameters, construct the hood stress field of the auxiliary hood plate, and according to the temperature information of the auxiliary hood plate under different historical control parameters, construct the hood temperature field of the auxiliary hood plate, and according to the airflow field information of the auxiliary hood plate under different historical control parameters, construct the hood airflow field of the auxiliary hood plate;

[0075] Among them, the stress field is the set of stress states of each point of the auxiliary hood plate, reflecting the stress magnitude, direction and distribution of each point inside the auxiliary hood plate under the action of the airflow. The hood stress field can describe the stress distribution of the auxiliary hood plate under different working conditions due to factors such as temperature change and airflow action. The temperature field is the distribution of temperature in time and space, indicating the temperature values of each point of the auxiliary hood plate and their variation laws with time and space. The hood temperature field describes the temperature distribution of the auxiliary hood plate under different working conditions. The airflow field is used for the gas flow state in the space formed by the auxiliary hood plate, including the distribution of parameters such as the velocity, direction and pressure of the airflow. The hood airflow field describes the gas flow around the auxiliary hood plate.

[0076] In the embodiments of the present disclosure, according to the deformation information of the key areas of the auxiliary hood plate under different historical control parameters, use relevant theories such as material mechanics and elasticity mechanics to establish a relationship model between stress and deformation. For example, according to Hooke's law, within the elastic range, stress is proportional to strain. By collecting the deformation data (such as displacement, strain, etc.) of the key areas of the auxiliary plate and combining the material parameters (such as elastic modulus, Poisson's ratio, etc.) of the auxiliary plate, calculate the stress values of each point inside the auxiliary plate, so as to construct the stress field of the auxiliary hood plate. This stress field reflects the stress distribution of the auxiliary plate under different working conditions due to factors such as external loads and temperature changes.

[0077] In the embodiments of the present disclosure, based on the temperature information of the auxiliary hood plate under different historical control parameters, adopt thermal theories such as heat conduction, heat convection and heat radiation to establish a mathematical model of temperature distribution. For example, for a one-dimensional steady-state heat conduction problem, Fourier's law can be used to establish the relationship between temperature and heat flux density. By collecting the temperature data of each point of the auxiliary plate and combining the boundary conditions and initial conditions, solve the heat conduction equation to obtain the temperature distribution inside the auxiliary plate, and then construct the hood temperature field of the auxiliary hood plate. This temperature field describes the temperature change of the auxiliary plate under different working conditions.

[0078] In the embodiments of the present disclosure, based on the airflow field information of the hood auxiliary plate under different historical control parameters, a mathematical model of airflow is established by applying the theory of fluid mechanics. For example, for the steady flow of an incompressible fluid, the Navier-Stokes equation (N-S equation) can be used to describe the movement of the airflow. By collecting data such as the velocity and pressure of the airflow around the auxiliary plate and combining with boundary conditions (such as inlet velocity, outlet pressure, etc.), the N-S equation is solved to obtain the distribution of parameters such as the flow velocity and flow direction of the airflow, thereby constructing the airflow field of the hood auxiliary plate. This airflow field describes the flow state of the gas around the auxiliary plate.

[0079] In step S112, the hood stress field and the airflow field information of the hood auxiliary plate under different historical control parameters are coupled to establish a first coupled control equation, and the hood temperature field and the airflow field information of the hood auxiliary plate under different historical control parameters are coupled to establish a second coupled control equation.

[0080] Among them, the coupled control equation is a mathematical equation that can be used to describe the interaction relationship between multiple physical fields. In multi-physical field coupled simulation, by establishing the coupled control equation, the variables of different physical fields are connected to achieve the joint solution of multiple physical fields. The first coupled control equation describes the interaction relationship between the hood stress field and the airflow field, and the second coupled control equation describes the interaction relationship between the hood temperature field and the airflow field.

[0081] In the embodiments of the present disclosure, the hood stress field and the airflow field information of the hood auxiliary plate under different historical control parameters are coupled, considering the influence of the stress field on the airflow field and the reaction of the airflow field on the stress field. For example, the pressure exerted by the airflow on the auxiliary plate will generate additional stress, and the stress state of the auxiliary plate will affect its deformation, thereby changing the flow channel and flow state of the airflow. By analyzing the interaction mechanism between the stress field and the airflow field, a coupling relationship between them is established and transformed into a mathematical equation, that is, the first coupled control equation. This equation connects the variables of the stress field (such as stress, strain, etc.) and the variables of the airflow field (such as velocity, pressure, etc.) to achieve the joint solution of the stress field and the airflow field.

[0082] In the disclosed embodiment, the temperature field of the hood and the airflow field information of the hood sub-plate under different historical control parameters are coupled, and the influence of the temperature field on the airflow field and the reaction of the airflow field to the temperature field are considered. For example, the convective heat transfer of the airflow will affect the temperature distribution of the sub-plate, and the temperature change of the sub-plate will cause changes in physical properties such as airflow density and viscosity, thereby affecting the flow of the airflow. By analyzing the interaction mechanism between the temperature field and the airflow field, a coupling relationship between them is established and converted into a mathematical equation, namely the second coupling control equation. This equation links the variables of the temperature field (such as temperature, heat flux density, etc.) and the variables of the airflow field (such as velocity, pressure, etc.) to achieve the joint solution of the temperature field and the airflow field.

[0083] In step S113, numerically solving and iteratively calculating the equation group consisting of the first coupled control equation and the second coupled control equation to obtain the Jacobian matrix of the equation group and update the solutions of the smoke hood temperature field, the smoke hood airflow field and the smoke hood stress field;

[0084] In the disclosed embodiment, the first coupled control equation and the second coupled control equation established in step S112 are combined to form a nonlinear equation group containing multiple unknowns (such as temperature, velocity, pressure, stress, etc.). This equation group comprehensively reflects the complex interaction relationship between the stress field, temperature field and airflow field of the smoke hood sub-plate.

[0085] In the disclosed embodiment, since the system of simultaneous equations is usually nonlinear and difficult to solve directly, numerical solution and iterative calculation methods are adopted. For example, the Newton-Raphson method is used for iterative solution. In each iteration, the Jacobian matrix of the system of equations is first calculated based on the approximate value of the current solution. The Jacobian matrix describes the rate of change of the unknown number of the system of equations, and the correction amount of the solution is obtained by solving the linearized Jacobian matrix equation. Then, the correction amount is added to the approximate value of the current solution to obtain the approximate value of the new solution. Repeat this process until the convergence criterion is met. During the iterative process, the solutions of the smoke hood temperature field, the smoke hood airflow field and the smoke hood stress field are continuously updated so that they gradually approach the true solution.

[0086] In the disclosed embodiment, in each iterative calculation, the Jacobian matrix of the equation group is calculated using numerical differentiation or analytical methods based on the approximate value of the current solution. The calculation of the Jacobian matrix is one of the key steps in the iterative solution, which directly affects the convergence speed and accuracy of the iterative process. By solving the Jacobian matrix equation, the correction amount of the solution is obtained, and the solutions of the smoke hood temperature field, smoke hood airflow field and smoke hood stress field are updated. As the number of iterations increases, the approximate value of the solution gradually converges to the true solution, thereby obtaining a more accurate distribution of the stress field, temperature field and airflow field.

[0087] In step S114, a digital twin three-dimensional dynamic model of the smelting hood sub-plate is constructed according to the solutions of the hood temperature field, the hood airflow field and the hood stress field obtained by each iterative calculation update.

[0088] In the disclosed embodiment, a digital twin three-dimensional dynamic model of the smelting hood sub-plate is constructed based on each physical field solution obtained by each iterative calculation update. The model can display the distribution of parameters such as stress, temperature and airflow of the hood sub-plate under different working conditions in real time, and can simulate the dynamic change process of the hood sub-plate during the smelting process. For example, by interacting with real-time data of the actual smelting process, the digital twin model can reflect the actual state of the hood sub-plate in real time, such as the increase and decrease of temperature, the change and release of stress, the flow and disturbance of airflow, etc.

[0089] In the disclosed embodiment, the digital twin 3D dynamic model presents the physical state and behavior of the hood sub-plate in a 3D dynamic form, so that the operator can intuitively understand the working condition of the hood sub-plate. For example, through the visual interface, the operator can observe the temperature distribution, stress state and airflow of the hood sub-plate in real time, discover potential problems in time and take corresponding measures. This visual display method improves the operator's ability to control the smelting process and helps to improve smelting efficiency and quality.

[0090] The above technical solution achieves accurate simulation and real-time monitoring of the smelting hood sub-plate by independently constructing physical fields, multi-physical field coupling analysis, efficiently solving complex equations, and real-time dynamic simulation and visualization. Its technical effects include improving the accuracy and reliability of simulation and accelerating calculation efficiency.

[0091] In a possible implementation, in step S113, numerically solving and iteratively calculating the equation group consisting of the first coupled control equation and the second coupled control equation to obtain the Jacobian matrix of the equation group and update the solutions of the smoke hood temperature field, the smoke hood airflow field and the smoke hood stress field include:

[0092] In step S1131, after the hood sub-plate is opened under different historical control parameters, the air duct formed by the hood sub-plate is grid-divided with the minimum opening of the hood sub-plate as the side length, to obtain a control volume corresponding to each historical control parameter, and each control volume corresponds to one grid;

[0093] Among them, meshing can discretize the continuous calculation area into a series of small, regular or irregular sub-areas, which are called meshes. Meshing can transform complex continuous problems into problems that need to be calculated on discrete mesh nodes in the numerical solution of partial differential equations. Through meshing, differential equations can be transformed into a set of algebraic equations, which is convenient for numerical solution.

[0094] A control volume is a closed area defined by each grid node. It is used to discretize the computational domain. The shape and size of the control volume can be selected based on the specific problem and computational requirements. Physical quantities (such as temperature, velocity, pressure, etc.) within each control volume are usually assumed to be uniformly distributed or follow a certain distribution law.

[0095] In the disclosed embodiment, when the smoke hood sub-plate is opened, a certain air duct will be formed. In order to perform numerical calculations on the physical field around the smoke hood sub-plate, the air duct area needs to be gridded. Using the minimum opening of the smoke hood sub-plate as the side length for grid division can ensure the uniformity and rationality of the grid, which is convenient for subsequent calculations and analysis. Each grid corresponds to a control volume. In this way, the continuous air duct area is discretized into a series of discrete control volumes, which lays the foundation for subsequent numerical solutions. For example, when calculating the airflow field, each control volume can be regarded as a small airflow unit. By calculating the airflow parameters in each control volume, the airflow field distribution of the entire air duct can be obtained.

[0096] In this way, according to the air duct formed after the hood sub-plate is opened under different historical control parameters, the mesh is divided with the minimum opening of the hood sub-plate as the side length. This division method fully considers the complexity and particularity of the duct structure and can accurately capture the geometric characteristics and physical field changes in the duct. For example, for some duct areas with irregular shapes or more local details, by dividing the mesh with the minimum opening as the side length, it is possible to avoid ignoring important details due to excessively large meshes, thereby improving the accuracy of numerical calculations.

[0097] In step S1132, based on the conservation principle, according to the volume coefficient corresponding to each control volume and the volume coefficient of the control volume adjacent to each control volume, the set of equations is integrated on each control volume corresponding to each historical control parameter to obtain a discrete equation corresponding to each historical control parameter;

[0098] In the disclosed embodiment, based on the conservation principle, the system of equations of the first coupled control equation and the second coupled control equation is integrated on each control volume. The conservation principle ensures that the total amount of physical quantities in the control volume remains unchanged, and the differential equation can be converted into an integral equation by integration. During the integration process, it is necessary to consider the volume coefficient corresponding to each control volume and the volume coefficient of the adjacent control volume. These volume coefficients reflect the influence of the size and shape of the control volume on the integral result. The discrete equation obtained by integration is an algebraic equation about the physical quantities (such as temperature, velocity, pressure, stress, etc.) on the grid nodes. It discretizes the continuous differential equation group into a series of discrete algebraic equations, which is convenient for the computer to perform numerical solution. For example, when calculating the energy conservation equation, by integrating on the control volume, the energy change in each control volume and the energy transfer relationship between the adjacent control volumes can be obtained, thereby obtaining a discrete energy equation.

[0099] Consider the volume coefficients of each control volume and its adjacent control volumes. These volume coefficients reflect the influence of the size and shape of the control volume on the integral result. By reasonably calculating and applying the volume coefficients, the accuracy of the integral can be improved, making the discrete equation more accurately reflect the actual situation of the physical field.

[0100] In step S1133, partially differentiate the discrete equation corresponding to each of the historical control parameters to obtain the Jacobian matrix of the equation group, and solve the discrete equation group by an iterative method to obtain and update the solutions of the smoke hood temperature field, the smoke hood airflow field and the smoke hood stress field.

[0101] In the disclosed embodiment, the discrete equation corresponding to each historical control parameter is partially differentiated to obtain the Jacobian matrix of the equation group. The Jacobian matrix describes the sensitivity of the discrete equation to the unknowns, and it contains the influence information of each unknown on other unknowns. Through the Jacobian matrix, the structure and characteristics of the discrete equation can be understood, and important parameters are provided for iterative solution. After obtaining the Jacobian matrix, an iterative method (such as the Newton-Raphson method) is used to solve the discrete equation group.

[0102] In the disclosed embodiment, the approximate value of the solution is updated through continuous iteration to gradually approach the true solution. In each iteration, the Jacobian matrix and the residual vector are calculated based on the approximate value of the current solution, and then the linearized Jacobian matrix equation is solved to obtain the correction value of the solution. The correction value is added to the approximate value of the current solution to obtain the approximate value of a new solution. This process is repeated until the convergence criterion is met. Through iterative calculation, the solutions of the hood temperature field, the hood airflow field and the hood stress field are obtained and updated, thereby realizing the numerical simulation and analysis of the physical field of the hood sub-plate.

[0103] An iterative method is used to solve the discrete equations to obtain and update the solutions of the hood temperature field, the hood airflow field, and the hood stress field. The iterative solution method can start from an initial guess value and continuously update the approximate value of the solution by repeatedly applying certain calculation rules or formulas until a predetermined convergence criterion is met. This method can effectively handle nonlinear equations and improve the calculation efficiency. For example, when dealing with large-scale multi-physical field coupling problems, the iterative solution method can quickly converge to the true solution and provide accurate physical field data for the construction of the digital twin model.

[0104] In a possible implementation manner, in step S1131, after the hood secondary plate is opened under different historical control parameters, the air duct formed by the hood secondary plate is meshed with the minimum opening degree of the hood secondary plate as the side length to obtain the control volume corresponding to each historical control parameter, including:

[0105] According to the secondary plate opening degree of the hood secondary plate after it is opened under different historical control parameters, determine the opening angle of the hood secondary plate under different historical control parameters, where the opening angle is the included angle between the hood secondary plate and the horizontal plane under different historical control parameters;

[0106] Among them, the opening angle is the included angle between the hood secondary plate and the horizontal plane, and this angle changes with the change of historical control parameters. The size of the opening angle will affect the direction and ventilation effect of the air duct formed by the hood secondary plate, and it is a key index to measure the spatial attitude of the hood secondary plate.

[0107] In the embodiments of the present disclosure, under different historical control parameters, the hood secondary plate will be opened to different degrees, and its secondary plate opening degree will change. According to the secondary plate opening degree, combined with geometric relationships such as the installation position and movement trajectory of the hood secondary plate, the included angle between the hood secondary plate and the horizontal plane, that is, the opening angle, can be calculated by mathematical methods such as trigonometric functions. For example, when the secondary plate opening degree and the fixed point position of the secondary plate are known, the opening angle can be calculated by constructing a right triangle and using sine, cosine, or tangent functions. The accurate determination of the opening angle provides important spatial attitude information for subsequent calculation of the effective volume of the air duct and mesh generation.

[0108] According to the minimum opening degree of the hood secondary plate, the width of the hood secondary plate, and the opening angle of the hood secondary plate under different historical control parameters, determine the effective volume of the air duct formed by the hood secondary plate under different historical control parameters;

[0109] Among them, the effective volume is the spatial volume of the air duct formed after the hood secondary plate is opened that can actually accommodate physical quantities such as gas or affect the air flow, etc., considering the structure of the hood secondary plate (such as the opening degree, width, opening angle, etc.) of the hood secondary plate. The calculation of the effective volume needs to comprehensively consider the geometric shape and spatial position relationship of the hood secondary plate.

[0110] In the embodiments of the present disclosure, after determining the opening angle of the hood secondary plate, combined with the minimum opening degree and width of the hood secondary plate, the geometric volume calculation formula can be used to determine the effective volume of the air duct formed by the hood secondary plate under different historical control parameters. For example, if the air duct can be approximately regarded as an irregular wedge-shaped space, the space can be decomposed into multiple simple geometric bodies (such as a cuboid, a triangular prism, etc.), calculate their volumes respectively, and then add the volumes of each part to obtain the effective volume of the air duct. The calculation of the effective volume takes into account the actual geometric shape and spatial position of the hood secondary plate, and can more accurately reflect the influence range of the air duct on physical quantities such as air flow and temperature.

[0111] Perform grid division with the minimum opening degree of the hood secondary plate as the side length, and perform grid division on the effective volume of the air duct formed under different historical control parameters to obtain the control volume corresponding to each historical control parameter.

[0112] In the embodiments of the present disclosure, grid division is performed with the minimum opening degree of the hood secondary plate as the side length, and the effective volume of the air duct formed under different historical control parameters is discretized. During the grid division process, it is necessary to select an appropriate grid type (such as a structured grid, an unstructured grid) and grid density according to the shape and size of the effective volume.

[0113] Among them, through reasonable grid division, the continuous effective volume is discretized into a series of discrete control volumes, and each control volume corresponds to a grid node. The calculation accuracy can be improved.

[0114] In a possible implementation manner, the determining the effective volume of the air duct formed by the hood secondary plate under different historical control parameters according to the minimum opening degree of the hood secondary plate, the width of the hood secondary plate, and the opening angle of the hood secondary plate under different historical control parameters includes:

[0115] According to the opening angle of the hood secondary plate under different historical control parameters, calculate the windward effective area of the hood secondary plate when the gas is blocked by the hood secondary plate;

[0116] Among them, the windward effective area refers to the effective projected area that actually participates in the interaction of gas flow after the hood sub-panel is opened, taking into account the blocking effect of the sub-panel on the airflow. It reflects the actual range of the sub-panel's influence on the gas flow in the airflow direction and is one of the important parameters for calculating the effective volume of the air duct.

[0117] In the disclosed embodiment, according to the opening angle of the smoke hood sub-plate under different historical control parameters, combined with the geometric shape of the sub-plate, the projection principle is used to calculate the effective windward area of the gas under the blocking effect of the sub-plate. For example, if the sub-plate is a rectangular flat plate, when the opening angle is determined, the projection length of the sub-plate in the airflow direction can be calculated by trigonometric functions, and then multiplied by the width of the sub-plate to obtain the effective windward area. The calculation of the effective windward area takes into account the influence of the spatial posture of the sub-plate on the airflow, which provides a basis for the subsequent accurate calculation of the effective volume of the air duct.

[0118] Moving the scanning line along the length direction of the smoke hood sub-plate with the minimum opening of the smoke hood sub-plate as a step length to obtain a plurality of scanning line coordinates of a plurality of scanning lines along the length direction;

[0119] Among them, scanning line: during the calculation process, a virtual straight line that moves along the length direction of the hood sub-plate with the minimum opening of the hood sub-plate as the step length. The scanning line is used to divide the effective area of the air duct, and the area between the lines is determined by the intersection with the upper and lower boundaries of the air duct, and then the total cross-sectional area is calculated.

[0120] In the disclosed embodiment, the scanning line is moved along the length direction of the hood sub-plate with the minimum opening of the hood sub-plate as the step length. By setting the starting position and moving step length of the scanning line, the position coordinates of each scanning line in the air duct can be determined. The determination of the scanning line coordinates provides a position reference for the subsequent calculation of the area between the lines.

[0121] According to the opening angle of the smoke hood sub-plate and the width of the smoke hood sub-plate under different historical control parameters, solving the intersection points of each scanning line with the upper and lower boundaries of the air duct formed under different historical control parameters;

[0122] In the disclosed embodiment, according to the opening angle and width of the hood sub-plate under different historical control parameters, combined with the geometric shape of the air duct, an equation is established for each scan line to solve the intersection of the scan line and the upper and lower boundaries of the air duct. For example, if the upper and lower boundaries of the air duct are straight lines or curves, the coordinates of the intersection can be solved by solving the scan line equation and the boundary equation simultaneously. The determination of the intersection coordinates provides boundary conditions for calculating the area of the area between the lines.

[0123] Determine the inter-line area of the region between adjacent scan lines based on the intersection points of the upper and lower boundaries corresponding to each scan line, and sum the inter-line areas under different historical control parameters to obtain the total cross-sectional area under different historical control parameters;

[0124] Among them, the inter-line area: the area of the region enclosed by two adjacent scan lines and the upper and lower boundaries of the air duct. Summing up all the inter-line areas can obtain the total cross-sectional area of the air duct at a certain cross-section. The total cross-sectional area: at a specific position (perpendicular to the air flow direction) of the air duct, the sum of all inter-line areas, which reflects the size of the cross-sectional area of the air duct at this position.

[0125] In the embodiments of the present disclosure, based on the intersection points of the upper and lower boundaries corresponding to each scan line, the inter-line area between adjacent scan lines is determined using a geometric method. Then, sum up all the inter-line areas to obtain the total cross-sectional area under different historical control parameters. The calculation of the total cross-sectional area reflects the actual flow-through area size of the air duct at a certain cross-section.

[0126] Along the air flow direction of the air duct under different historical control parameters, discretize the total cross-sectional area with the minimum opening degree of the hood secondary plate as the opening degree to determine the effective volume of the air duct formed by the hood secondary plate under different historical control parameters.

[0127] In the embodiments of the present disclosure, along the air flow direction of the air duct, the total cross-sectional area is discretized with the minimum opening degree of the hood secondary plate as the interval. For each discrete unit, multiply the corresponding total cross-sectional area by the length of the discrete unit (i.e., the minimum opening degree) to obtain the effective volume of the discrete unit. Finally, accumulate the effective volumes of all discrete units to obtain the effective volume of the air duct formed by the hood secondary plate under different historical control parameters.

[0128] The above technical solution can more accurately calculate the effective volume of the air duct by comprehensively considering multiple factors such as the opening angle of the hood secondary plate, the width of the secondary plate, the effective windward area, the intersection points of the scan line and the boundary, and the inter-line area, and adopting an accurate geometric calculation method. Compared with the traditional simplified calculation method, this method can better reflect the actual shape and spatial distribution of the air duct, improving the accuracy of the calculation results. In this way, air ducts with various complex shapes, whether regular geometric shapes or irregular complex shapes, can obtain accurate effective volumes through reasonable mesh division and geometric calculation.

[0129] In a possible implementation manner, in step S13, the determining the corrected combined parameter values of the predicted surface temperature distribution and the predicted flue gas component concentration for the hood secondary plate according to the true melting power of the melting furnace and the predicted melting furnace power during the melting process includes:

[0130] In step S131, a prediction deviation is determined based on the actual smelting power of the smelting furnace during the smelting process and the predicted smelting furnace power.

[0131] In the embodiments of the present disclosure, the actual smelting power of the smelting furnace during the smelting process is subtracted from the predicted smelting furnace power to obtain a prediction deviation. The calculation formula for the prediction deviation is: prediction deviation = actual smelting power - predicted smelting furnace power. By calculating the prediction deviation, the error situation of the prediction model can be intuitively understood.

[0132] In step S132, the state transition matrix is updated according to the prediction deviation to obtain the updated state transition matrix.

[0133] In the embodiments of the present disclosure, the state transition matrix is updated by using an adaptive algorithm or an optimization method according to the prediction deviation. The update of the state transition matrix is an adjustment of the system model parameters based on the prediction deviation, so that the updated state transition matrix can better reflect the actual dynamic characteristics of the smelting furnace system. For example, optimization algorithms such as the gradient descent method and the least squares method can be used to adjust the elements of the state transition matrix according to the principle of minimizing the prediction deviation.

[0134] In step S133, the updated state transition matrix is multiplied by the transpose of the current predicted covariance to obtain an updated state covariance.

[0135] In the embodiments of the present disclosure, the updated state transition matrix is multiplied by the transpose of the current predicted covariance to obtain an updated state covariance. The update formula for the state covariance is: updated state covariance = updated state transition matrix × transpose of the current predicted covariance × (transpose of the updated state transition matrix) + process noise covariance. This step takes into account the uncertainty changes during the system state transition process. By updating the state covariance, the uncertainty degree of the state prediction value can be more accurately described.

[0136] In step S134, a gain is determined based on the first product of the updated state covariance and the transpose of the observation matrix, and the second product of the observation matrix, the updated predicted covariance and the transpose of the observation matrix.

[0137] In an embodiment of the present disclosure, a gain is calculated based on a first product of an updated state covariance and a transpose of an observation matrix, and a second product of the observation matrix, the updated prediction covariance and the transpose of the observation matrix. The calculation formula of the gain is: gain = inverse matrix of (observation matrix × updated state covariance × transpose of observation matrix + observation noise covariance) × updated state covariance × transpose of observation matrix. The calculation of the gain comprehensively considers the uncertainty of state prediction and the influence of observation noise. By adjusting the gain, an optimal balance can be achieved between the predicted value and the observed value.

[0138] In step S135, a first correction parameter value for the predicted surface temperature distribution of the secondary hood plate is determined according to the predicted surface temperature distribution, the gain, and the prediction deviation, and a second correction parameter value for the predicted flue gas component concentration of the secondary hood plate is determined according to the predicted flue gas component concentration, the gain, and the prediction deviation.

[0139] In an embodiment of the present disclosure, a first correction parameter value for the predicted surface temperature distribution of the secondary hood plate is calculated according to the predicted surface temperature distribution, the gain, and the prediction deviation. The calculation formula of the first correction parameter value is: first correction parameter value = gain × prediction deviation (part related to the surface temperature distribution). Similarly, a second correction parameter value for the predicted flue gas component concentration of the secondary hood plate is calculated according to the predicted flue gas component concentration, the gain, and the prediction deviation. The calculation formula of the second correction parameter value is: second correction parameter value = gain × prediction deviation (part related to the flue gas component concentration). By introducing the gain and the prediction deviation, the predicted surface temperature distribution and the predicted flue gas component concentration are corrected, improving the prediction accuracy.

[0140] In step S136, a corrected combined parameter value for the predicted surface temperature distribution and the predicted flue gas component concentration of the secondary hood plate is determined according to the first corrected residual value and the second correction parameter value.

[0141] In an embodiment of the present disclosure, the predicted surface temperature distribution and the predicted flue gas component concentration of the secondary hood plate are comprehensively corrected by comprehensively considering the first correction parameter value and the second correction parameter value to obtain a corrected combined parameter value. The corrected combined parameter value can be calculated by methods such as weighted average and linear combination, and the specific method is selected according to the actual situation and requirements. The corrected combined parameter value can more comprehensively reflect the actual state of the secondary hood plate during the smelting process, providing a more accurate basis for subsequent process control and optimization.

[0142] Through the analysis and correction of the prediction deviation, and combined with the dynamic adjustment of parameters such as the state transition matrix, state covariance, and gain, this technology can significantly improve the prediction accuracy of the predicted surface temperature distribution of the secondary plate of the hood and the predicted flue gas component concentration. Accurate prediction results help to better understand the heat transfer and chemical reaction conditions during the smelting process, providing a more reliable basis for process control. At the same time, an adaptive algorithm is used to update the state transition matrix, enabling the model to automatically adjust parameters according to the changes in the actual smelting process, enhancing the adaptive ability of the model. This enables the model to better adapt to different smelting process conditions and raw material characteristics, improving the generality and practicality of the model.

[0143] In a possible implementation manner, a cooling pipeline is arranged along the length direction of the secondary plate of the hood, and the direction of the cooling pipeline is the same as the length direction.

[0144] The method further includes:

[0145] According to the target surface temperature distribution, determine the surface temperature mean value and the maximum temperature difference, and determine whether the cooling water filling condition for activating the cooling pipeline is satisfied according to the first difference between the surface temperature mean value and the preset mean value threshold and the second difference between the maximum temperature difference and the preset temperature difference threshold.

[0146] In the embodiment of the present disclosure, along the length direction of the secondary plate of the hood and along the direction of the cooling pipeline, by arranging a plurality of temperature sensors, the temperature data of each point on the surface of the secondary plate of the hood is collected in real time. Add up all the collected temperature data, and then divide by the number of temperature sensors to obtain the surface temperature mean value. At the same time, find the highest temperature and the lowest temperature from the collected temperature data, and calculate their difference to obtain the maximum temperature difference. Through these two parameters, the heat load situation and temperature distribution uniformity of the secondary plate of the hood can be comprehensively understood.

[0147] In the embodiment of the present disclosure, calculate the first difference between the surface temperature mean value and the preset mean value threshold, and the second difference between the maximum temperature difference and the preset temperature difference threshold. Compare the first difference and the second difference with the set thresholds respectively. If the first difference is greater than zero and exceeds a certain tolerance range, or the second difference is greater than zero and exceeds a certain tolerance range, it is determined that the cooling water filling condition is satisfied. This judgment process comprehensively considers the average heating degree and temperature distribution uniformity of the secondary plate of the hood to ensure that the cooling system is started in time when cooling is required.

[0148] When it is determined that the cooling water filling condition is satisfied, determine the first flow rate according to the product of the first difference and the first gain coefficient and the first base flow rate, and determine the second flow rate according to the product of the second difference and the second gain coefficient and the second base flow rate.

[0149] In the disclosed embodiment, when it is determined that the cooling water filling conditions are met, the first flow rate is determined based on the product between the first difference and the first gain coefficient, and the first basic flow rate. The specific calculation formula is: first flow rate = first basic flow rate + first difference × first gain coefficient. Similarly, the second flow rate is determined based on the product between the second difference and the second gain coefficient, and the second basic flow rate. The specific calculation formula is: second flow rate = second basic flow rate + second difference × second gain coefficient. By introducing the gain coefficient, the cooling water flow rate can be dynamically adjusted according to the degree of change of the surface temperature mean and the maximum temperature difference, so as to achieve precise cooling of the smoke hood sub-plate.

[0150] The cooling water flow rate is determined by weighted summation according to the first flow rate, the second flow rate and the weight corresponding to each flow rate, and the cooling water filling is controlled according to the cooling water flow rate.

[0151] In the disclosed embodiment, the cooling water flow rate is determined by weighted summation based on the first flow rate, the second flow rate, and the weight corresponding to each flow rate. The specific calculation formula is: cooling water flow rate = first flow rate × first weight + second flow rate × second weight. Among them, the sum of the first weight and the second weight is 1. By adjusting the size of the weight, the degree of influence of the first flow rate and the second flow rate on the cooling water flow rate can be changed, thereby achieving flexible adjustment of the cooling water flow rate. According to the calculated cooling water flow rate, the speed or valve opening of the cooling water pump is controlled to adjust the flow of cooling water to achieve cooling of the smoke hood sub-plate.

[0152] The above technical solution can more accurately judge the cooling needs of the hood sub-plate by comprehensively considering the two parameters of the surface temperature mean and the maximum temperature difference, and dynamically adjust the cooling water flow rate according to different temperature differences to achieve precise cooling control of the hood sub-plate. This helps to avoid damage to the hood sub-plate due to excessive temperature or uneven temperature distribution, and improves the service life of the hood sub-plate. Dynamically adjusting the cooling water flow rate according to the degree of change of the surface temperature mean and the maximum temperature difference can enable the cooling water to more effectively remove the heat from the hood sub-plate and improve the cooling efficiency. Compared with the traditional fixed flow rate cooling method, this technology can adjust the cooling water flow rate according to actual needs and reduce unnecessary energy waste.

[0153] Furthermore, by real-time monitoring of the hood sub-plate temperature and precise cooling control, the hood sub-plate temperature can be kept within a suitable range, reducing the impact of temperature fluctuations on the smelting process and improving the stability of the entire smelting system. A stable smelting system helps to ensure product quality and production efficiency. Precise cooling control can reduce the thermal stress and thermal fatigue of the hood sub-plate, reduce the risk of damage to the hood sub-plate, thereby reducing the frequency of repair and replacement of the hood sub-plate and reducing maintenance costs.

[0154] An embodiment of the present disclosure also provides a control device for a secondary plate of a smelting hood. Refer to Figure 2 as shown, including:

[0155] A determination module 210, configured to map the temperature field, air flow field, and stress field of the hood through multi-physical field coupling simulation according to the deformation information, temperature information, and air flow field information of the key area of the secondary plate under different historical control parameters of the secondary plate of the hood, and construct a digital twin three-dimensional dynamic model of the secondary plate of the smelting hood;

[0156] An input module 220, configured to input the temperature, air flow intensity, and deformation degree of the key area of the secondary plate obtained during the smelting process into the digital twin three-dimensional dynamic model, and obtain the predicted surface temperature distribution, predicted flue gas component concentration, and predicted smelting furnace power of the smelting furnace for the secondary plate of the hood output by the digital twin three-dimensional dynamic model;

[0157] A correction module 230, configured to determine a correction combined parameter value for the predicted surface temperature distribution and the predicted flue gas component concentration of the secondary plate of the hood according to the actual smelting power of the smelting furnace and the predicted smelting furnace power during the smelting process, and correct the predicted surface temperature distribution and the predicted flue gas component concentration of the secondary plate of the hood respectively according to the corrected combined parameter value to obtain a target surface temperature distribution and a target flue gas component concentration;

[0158] A control module 240, configured to generate control parameters for controlling the secondary plate of the smelting hood according to the target surface temperature distribution and the target flue gas component concentration, and control the opening degree of the secondary plate of the smelting hood according to the control parameters.

[0159] In a possible implementation manner, the determination module 210 is configured to:

[0160] Construct the stress field of the hood of the secondary plate according to the deformation information of the key area of the secondary plate under different historical control parameters of the secondary plate of the hood, construct the temperature field of the hood of the secondary plate according to the temperature information of the secondary plate of the hood under different historical control parameters, and construct the air flow field of the hood of the secondary plate according to the air flow field information of the secondary plate of the hood under different historical control parameters;

[0161] Couple the stress field of the hood of the secondary plate with the air flow field information under different historical control parameters of the secondary plate of the hood to establish a first coupled control equation, and couple the temperature field of the hood of the secondary plate with the air flow field information under different historical control parameters of the secondary plate of the hood to establish a second coupled control equation;

[0162] Numerically solving and iteratively calculating the equation group consisting of the first coupled control equation and the second coupled control equation to obtain the Jacobian matrix of the equation group and update the solutions of the smoke hood temperature field, the smoke hood airflow field and the smoke hood stress field;

[0163] According to the solutions of the hood temperature field, the hood airflow field and the hood stress field obtained by each iterative calculation update, a digital twin three-dimensional dynamic model of the smelting hood sub-plate is constructed.

[0164] In a possible implementation, the determining module 210 is configured to:

[0165] After the hood sub-plate is opened under different historical control parameters, the air duct formed by the hood sub-plate is grid-divided with the minimum opening of the hood sub-plate as the side length, to obtain a control volume corresponding to each historical control parameter, and each control volume corresponds to one grid;

[0166] Based on the conservation principle, according to the volume coefficient corresponding to each of the control volumes and the volume coefficient of the control volume adjacent to each of the control volumes, the set of equations is integrated on each of the control volumes corresponding to each of the historical control parameters to obtain a discrete equation corresponding to each of the historical control parameters;

[0167] Partially differentiate the discrete equation corresponding to each of the historical control parameters to obtain the Jacobian matrix of the equation group, and solve the discrete equation group through an iterative method to obtain and update the solutions of the smoke hood temperature field, the smoke hood airflow field and the smoke hood stress field.

[0168] In a possible implementation, the determining module 210 is configured to:

[0169] According to the opening degree of the hood sub-plate after the hood sub-plate is opened under different historical control parameters, the opening angle of the hood sub-plate under different historical control parameters is determined, and the opening angle is the angle between the hood sub-plate and the horizontal plane under different historical control parameters;

[0170] Determine the effective volume of the air duct formed under the different historical control parameters of the hood sub-plate according to the minimum opening of the hood sub-plate, the width of the hood sub-plate and the opening angle of the hood sub-plate under the different historical control parameters;

[0171] The minimum opening of the smoke hood sub-plate is used as the side length for grid division, and the effective volume of the air duct formed under different historical control parameters is grid divided to obtain the control volume corresponding to each historical control parameter.

[0172] In a possible implementation manner, the determining module 210 is configured to:

[0173] Calculate the effective windward area of the gas under the blocking effect of the auxiliary hood plate according to the opening angle of the auxiliary hood plate under different historical control parameters, and determine the effective windward area of the auxiliary hood plate;

[0174] Move the scanning line along the length direction of the auxiliary hood plate with the minimum opening degree of the auxiliary hood plate as the step length to obtain the scanning line coordinates of multiple scanning lines along the length direction;

[0175] Solve the intersection points of each scanning line with the upper and lower boundaries of the air duct formed under different historical control parameters according to the opening angle of the auxiliary hood plate and the width of the auxiliary hood plate under different historical control parameters;

[0176] Determine the area between lines of the area between adjacent scanning lines according to the intersection points of the upper and lower boundaries corresponding to each scanning line, and sum the areas between lines under different historical control parameters to obtain the total cross-sectional area under different historical control parameters;

[0177] Discretize the total cross-sectional area along the air flow direction of the air duct under different historical control parameters with the minimum opening degree of the auxiliary hood plate as the opening degree to determine the effective volume of the air duct formed by the auxiliary hood plate under different historical control parameters.

[0178] In a possible implementation manner, the correction module 230 is configured to:

[0179] Determine the prediction deviation according to the actual melting power of the melting furnace and the predicted melting furnace power during the melting process;

[0180] Update the state transition matrix according to the prediction deviation to obtain the updated state transition matrix;

[0181] Multiply the updated state transition matrix by the transpose of the current prediction covariance to obtain the updated state covariance;

[0182] Determine the gain according to the first product of the updated state covariance and the transpose of the observation matrix, and the second product of the observation matrix, the updated prediction covariance and the transpose of the observation matrix;

[0183] Determine the first correction parameter value for the predicted surface temperature distribution of the auxiliary hood plate according to the predicted surface temperature distribution, the gain and the prediction deviation, and determine the second correction parameter value for the predicted flue gas component concentration of the auxiliary hood plate according to the predicted flue gas component concentration, the gain and the prediction deviation;

[0184] Determine a corrected combined parameter value for the predicted surface temperature distribution and the predicted flue gas component concentration of the auxiliary smoke hood plate according to the first true repair residual value and the second corrected parameter value.

[0185] In a possible implementation manner, a cooling pipeline with a direction consistent with the length direction is arranged along the length direction of the auxiliary smoke hood plate;

[0186] The device further includes: a cooling control module configured to:

[0187] Determine the average surface temperature and the maximum temperature difference according to the target surface temperature distribution, and determine whether the cooling water filling condition for activating the cooling pipeline is satisfied according to a first difference between the average surface temperature and a preset average threshold value and a second difference between the maximum temperature difference and a preset temperature difference threshold value;

[0188] When it is determined that the cooling water filling condition is satisfied, determine a first flow rate according to the product of the first difference and a first gain coefficient and a first base flow rate, and determine a second flow rate according to the product of the second difference and a second gain coefficient and a second base flow rate;

[0189] Determine the cooling water flow rate by weighted summation according to the first flow rate, the second flow rate, and the weight corresponding to each flow rate, and control the filling of the cooling water according to the cooling water flow rate.

[0190] The embodiments of the present disclosure further provide a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method described in any one of the foregoing embodiments are implemented.

[0191] The embodiments of the present disclosure further provide an electronic device, including:

[0192] A memory, on which a computer program is stored;

[0193] A processor, configured to execute the computer program in the memory to implement the steps of the method described in any one of the foregoing embodiments.

[0194] Figure 3The control device 100 of the melting fume hood secondary plate shown includes: a processor 1001 and a memory 1003. Among them, the processor 1001 and the memory 1003 are connected, such as connected through a bus 1002. Optionally, the control device 100 of the melting fume hood secondary plate may further include a communication component 1004, and the communication component 1004 can be used for data interaction between the device 100 and other devices, such as data sending and / or data receiving, etc. It should be noted that in actual scheduling, the communication component 1004 is not limited to one, and the structure of the control device 100 of the melting fume hood secondary plate does not constitute a limitation to the embodiments of the present application.

[0195] The processor 1001 can be a CPU (Central Processing Unit, central processor), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), an ASIC (Application Specific Integrated Circuit, application-specific integrated circuit), an FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logic blocks, modules and circuits described in combination with the disclosure of the present application. The processor 1001 can also be a combination that realizes computing functions, such as a combination including one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0196] The bus 1002 may include a path for transmitting information between the above components. The bus 1002 can be a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or an EISA (Extended Industry Standard Architecture, extended industry standard structure) bus, etc. The bus 1002 can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 3 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0197] The memory 1003 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), magnetic disk storage medium, other magnetic storage devices, or any other medium that can be used to carry or store program code and can be read by a computer, without limitation herein.

[0198] The memory 1003 is used to store program codes for executing the embodiments of the present disclosure, and the execution is controlled by the processor 1001. The processor 1001 is used to execute the program codes stored in the memory 1003 to implement the steps shown in the above-mentioned control method embodiment of the smelting hood sub-plate.

[0199] The embodiment of the present disclosure further provides a computer-readable storage medium having program codes stored thereon. When the program codes are executed by a processor, the steps and corresponding contents of the aforementioned control method embodiment of the smelting fume hood sub-plate can be implemented.

[0200] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments; within the technical concept of the present disclosure, various changes, modifications, substitutions and variations may be made to these embodiments, and these changes, modifications, substitutions and variations all fall within the protection scope of the present disclosure.

[0201] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any appropriate manner without contradiction, and they should also be regarded as the contents disclosed in this disclosure. In order to avoid unnecessary repetition, this disclosure will not further describe various possible combinations. The technical scope of this application is not limited to the contents in the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. A control method for the auxiliary plate of a smelting hood, characterized in that, Said include: According to the deformation information, temperature information and airflow field information of the key areas of the hood sub-plate under different historical control parameters, the hood temperature field, hood airflow field and hood stress field are mapped through multi-physical field coupling simulation to construct a digital twin three-dimensional dynamic model of the smelting hood sub-plate; The temperature of the fume hood sub-plate, the airflow intensity and the deformation degree of the key area of the sub-plate obtained during the smelting process are input into the digital twin three-dimensional dynamic model, and the digital twin three-dimensional dynamic model outputs the predicted surface temperature distribution of the fume hood sub-plate during the smelting process, the predicted flue gas component concentration and the predicted smelting furnace power for the smelting furnace; According to the actual smelting power of the smelting furnace and the predicted smelting furnace power during the smelting process, the correction combination parameter values for the predicted surface temperature distribution of the fume hood sub-plate and the predicted flue gas component concentration are determined, and the predicted surface temperature distribution and the predicted flue gas component concentration of the fume hood sub-plate are respectively corrected according to the corrected combination parameter values to obtain the target surface temperature distribution and the target flue gas component concentration; According to the target surface temperature distribution and the target fume component concentration, control parameters for controlling the smelting fume hood sub-plate are generated, and according to the control parameters, the sub-plate opening of the smelting fume hood sub-plate is controlled.

2. The method according to claim 1, wherein According to the deformation information, temperature information and airflow field information of the key area of the hood sub-plate under different historical control parameters, the hood temperature field, hood airflow field and hood stress field are mapped through multi-physical field coupling simulation to construct a digital twin three-dimensional dynamic model of the smelting hood sub-plate, including: The hood stress field of the hood sub-plate is constructed according to the deformation information of the key area of the sub-plate under different historical control parameters, and the hood temperature field of the hood sub-plate is constructed according to the temperature information of the hood sub-plate under different historical control parameters, and the hood airflow field of the hood sub-plate is constructed according to the airflow field information of the hood sub-plate under different historical control parameters; The fume hood stress field of the fume hood sub-plate under different historical control parameters is coupled with the airflow field information to establish a first coupling control equation, and the fume hood temperature field of the fume hood sub-plate under different historical control parameters is coupled with the airflow field information to establish a second coupling control equation; Numerically solving and iteratively calculating the equation group consisting of the first coupled control equation and the second coupled control equation to obtain the Jacobian matrix of the equation group and update the solutions of the smoke hood temperature field, the smoke hood airflow field and the smoke hood stress field; According to the solutions of the smoke hood temperature field, the smoke hood airflow field and the smoke hood stress field obtained by each iterative calculation update, a digital twin three-dimensional dynamic model of the smelting smoke hood sub-plate is constructed.

3. The method according to claim 2, wherein Numerically solving and iteratively calculating the system of equations obtained by combining the first coupling control equation and the second coupling control equation, obtaining the Jacobian matrix of the system of equations, and updating the solutions of the hood temperature field, the hood airflow field, and the hood stress field, includes: After the hood auxiliary plate is opened under different historical control parameters, dividing the air duct formed by the hood auxiliary plate into grids with the minimum opening of the hood auxiliary plate as the side length, obtaining a control volume corresponding to each historical control parameter, and each control volume corresponds to one grid; Based on the conservation principle, integrating the system of equations on each control volume corresponding to each historical control parameter according to the volume coefficient corresponding to each control volume and the volume coefficients of adjacent control volumes of each control volume, obtaining a discrete equation corresponding to each historical control parameter; Performing partial differentiation on the discrete equations corresponding to each historical control parameter to obtain the Jacobian matrix of the system of equations, and solving the discrete system of equations by an iterative method to obtain and update the solutions of the hood temperature field, the hood airflow field, and the hood stress field.

4. The method according to claim 3, characterized in that, The step of, after the hood auxiliary plate is opened under different historical control parameters, dividing the air duct formed by the hood auxiliary plate into grids with the minimum opening of the hood auxiliary plate as the side length, obtaining a control volume corresponding to each historical control parameter, includes: According to the opening of the auxiliary plate of the hood after the hood auxiliary plate is opened under different historical control parameters, determining the opening angle of the hood auxiliary plate under different historical control parameters, where the opening angle is the angle between the hood auxiliary plate and the horizontal plane under different historical control parameters; According to the minimum opening of the hood auxiliary plate, the width of the hood auxiliary plate, and the opening angle of the hood auxiliary plate under different historical control parameters, determining the effective volume of the air duct formed by the hood auxiliary plate under different historical control parameters; Dividing the effective volume of the air duct formed under different historical control parameters into grids with the minimum opening of the hood auxiliary plate as the side length, obtaining a control volume corresponding to each historical control parameter.

5. The method according to claim 4, wherein The step of, according to the minimum opening of the hood auxiliary plate, the width of the hood auxiliary plate, and the opening angle of the hood auxiliary plate under different historical control parameters, determining the effective volume of the air duct formed by the hood auxiliary plate under different historical control parameters, includes: According to the opening angle of the hood auxiliary plate under different historical control parameters, calculating the windward effective area of the hood auxiliary plate by determining the gas under the blocking effect of the hood auxiliary plate; Moving a scanning line along the length direction of the hood auxiliary plate with the minimum opening of the hood auxiliary plate as the step length, obtaining the scanning line coordinates of multiple scanning lines along the length direction; According to the opening angle of the hood auxiliary plate under different historical control parameters and the width of the hood auxiliary plate, solving the intersection points of each scanning line with the upper and lower boundaries of the air duct formed under different historical control parameters; Determine the inter-line area of the area between adjacent scan lines according to the intersection points of the upper and lower boundaries corresponding to each scan line, and sum the inter-line areas under different historical control parameters to obtain the total cross-sectional area under different historical control parameters; Along the air flow direction of the air duct under different historical control parameters, discretize the total cross-sectional area with the minimum opening of the auxiliary baffle of the smoke hood as the opening to determine the effective volume of the air duct formed by the auxiliary baffle of the smoke hood under different historical control parameters.

6. The method according to any one of claims 1-5, characterized in that, The determining the corrected combined parameter values for the predicted surface temperature distribution and the predicted flue gas component concentration of the auxiliary baffle of the smoke hood according to the actual melting power of the melting furnace and the predicted melting furnace power during the melting process includes: Determine the prediction deviation according to the actual melting power of the melting furnace and the predicted melting furnace power during the melting process; Update the state transition matrix according to the prediction deviation to obtain the updated state transition matrix; Multiply the updated state transition matrix by the transpose of the current prediction covariance to obtain the updated state covariance; Determine the gain according to the first product of the updated state covariance and the transpose of the observation matrix, and the second product of the observation matrix, the updated prediction covariance and the transpose of the observation matrix; Determine the first corrected parameter value for the predicted surface temperature distribution of the auxiliary baffle of the smoke hood according to the predicted surface temperature distribution, the gain and the prediction deviation, and determine the second corrected parameter value for the predicted flue gas component concentration of the auxiliary baffle of the smoke hood according to the predicted flue gas component concentration, the gain and the prediction deviation; Determine the corrected combined parameter values for the predicted surface temperature distribution and the predicted flue gas component concentration of the auxiliary baffle of the smoke hood according to the first corrected residual value and the second corrected parameter value.

7. The method according to any one of claims 1-5 and 6, characterized in that, A cooling pipeline with a direction consistent with the length direction is arranged along the length direction of the auxiliary baffle of the smoke hood; The method further includes: Determine the surface temperature mean value and the maximum temperature difference according to the target surface temperature distribution, and determine whether the cooling water filling condition for activating the cooling pipeline is satisfied according to the first difference between the surface temperature mean value and the preset mean value threshold and the second difference between the maximum temperature difference and the preset temperature difference threshold; When it is determined that the cooling water filling condition is satisfied, determine the first flow rate according to the product of the first difference and the first gain coefficient and the first basic flow rate, and determine the second flow rate according to the product of the second difference and the second gain coefficient and the second basic flow rate; Determine the cooling water flow rate by weighted summation according to the first flow rate, the second flow rate and the weight corresponding to each flow rate, and control the cooling water filling according to the cooling water flow rate.

8. A control device for a secondary plate of a smelting hood, characterized in that, Including: A determination module, configured to map the temperature field, air flow field, and stress field of the smelting hood through multi-physical field coupling simulation based on the deformation information, temperature information, and air flow field information of the key area of the auxiliary plate of the smelting hood under different historical control parameters, and construct a digital twin three-dimensional dynamic model of the auxiliary plate of the smelting hood; An input module, configured to input the temperature, air flow intensity at the auxiliary plate of the smelting hood, and the deformation degree of the key area of the auxiliary plate obtained during the smelting process into the digital twin three-dimensional dynamic model, and obtain the predicted surface temperature distribution, predicted flue gas component concentration of the auxiliary plate of the smelting hood during the smelting process, and the predicted smelting furnace power for the smelting furnace output by the digital twin three-dimensional dynamic model; A correction module, configured to determine a corrected combined parameter value for the predicted surface temperature distribution and the predicted flue gas component concentration of the auxiliary plate of the smelting hood according to the actual smelting power of the smelting furnace and the predicted smelting furnace power during the smelting process, and correct the predicted surface temperature distribution and the predicted flue gas component concentration of the auxiliary plate of the smelting hood respectively according to the corrected combined parameter value to obtain a target surface temperature distribution and a target flue gas component concentration; A control module, configured to generate control parameters for controlling the auxiliary plate of the smelting hood according to the target surface temperature distribution and the target flue gas component concentration, and control the opening degree of the auxiliary plate of the smelting hood according to the control parameters.

9. An electronic device, characterized in that, Comprising: A memory, on which a computer program is stored; A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method according to any one of claims 1-7.

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