A method and system for controlling production of oxygen-free copper casting blanks

Abstract

This application provides a method and system for controlling the production of oxygen-free copper slabs, applied in the field of continuous casting technology, to address defects caused by differences between the slab state and the normal production state when resuming production after an unplanned shutdown. This method achieves precise control of process parameters during the recovery phase by predicting the slab state, generating a target curve set, monitoring temperature deviations in real time, and dynamically correcting the target curve set. This method has the advantages of reducing slab defects during the recovery phase and ensuring a smooth transition in production.

Description

Technical Field

[0001] The present application relates to the field of continuous casting technology, and in particular to a method and system for controlling the production of oxygen-free copper ingots. Background Art

[0002] The continuous casting process is widely used in the production of oxygen-free copper ingots. In this process, high-purity molten copper is first poured into a tundish and then into a vertical or curved mold through a submerged nozzle at the bottom of the tundish. Within the mold, forced cooling (usually water) causes the copper to initially solidify, forming a thick solidified shell. This shell surrounds the unsolidified copper within, forming the initial ingot. Subsequently, a drawing device (such as nip rollers) continuously and steadily removes the ingot with the solidified shell from the bottom or outlet of the mold. Once removed from the mold, the ingot enters a secondary cooling zone. This zone typically consists of multiple spraying devices or water tanks. By spraying cooling water onto the ingot surface or immersing it in water, it further removes heat from the ingot, promotes further solidification of the liquid metal, and reduces the overall ingot temperature, ultimately forming a finished ingot with the desired cross-sectional shape and internal structure. The entire production process is a complex system that involves the coordinated control of numerous process parameters, including casting temperature, tundish liquid level, casting speed, mold cooling water flow and temperature, and water flow and spray patterns in each secondary cooling section. Precise matching and stable control of these parameters are crucial to ensuring the internal density of the ingot, a smooth, crack-free surface, and dimensional accuracy.

[0003] During the continuous and efficient production of oxygen-free copper ingots, the production line is inevitably subject to various unplanned emergencies, such as temporary fluctuations in the power supply system, brief failures in upstream melting or holding equipment, forced shutdowns to respond to urgent safety incidents, or unplanned maintenance interruptions due to equipment anomalies that require immediate attention. These emergencies can force the continuous casting line to experience unplanned shutdowns or brief interruptions.

[0004] When a production line resumes normal production after an unplanned shutdown, the drawing device needs to be restarted and the pulling speed gradually increased from zero to the speed required for normal, stable production. The core challenge at this point is that the actual state of the stationary strand within the mold and secondary cooling zone (including temperature distribution, solidification shell thickness, solidification front position, etc.) during the shutdown period is significantly different from the ideal or target state under normal, stable production conditions, and this difference is non-uniformly distributed. Simply resuming pulling speed and cooling control using the stable production parameters or a pre-set fixed startup curve before the shutdown is likely to result in a mismatch between the process parameters during the recovery process and the actual state of the strand.

[0005] Therefore, after the oxygen-free copper continuous casting production line experiences an unplanned shutdown, resulting in a static and non-uniform temperature distribution and solidification state changes in the billet along the length direction in the crystallizer and secondary cooling zone, how to dynamically predict and perceive the actual state of the billet in real time based on the shutdown time and cooling conditions during the shutdown process during the resumption of production and the increase of the drawing speed from zero to the normal speed, and based on this, coordinate and dynamically adjust the primary and secondary cooling parameters to minimize the billet defects generated in the recovery stage and ensure a smooth transition in production. In response to the above problems, the existing technology urgently needs to be improved. Summary of the Invention

[0006] In view of the above-mentioned deficiencies in the prior art, the present application provides a method and system for regulating the production of oxygen-free copper ingots, which has the advantages of reducing ingot defects generated during the recovery phase and ensuring a smooth transition in production.

[0007] In a first aspect, a method for controlling the production of oxygen-free copper ingots is provided for resuming production after an unplanned shutdown, the method comprising the steps of:

[0008] S1: Obtain the unplanned parking duration and cooling conditions during parking;

[0009] S2: Based on the unplanned parking duration and the cooling conditions, predicting the temperature distribution and solidification state of the slab in the crystallizer and the secondary cooling zone at the end of the parking, and obtaining slab state prediction information;

[0010] S3: generating target curves for the drawing speed, mold cooling intensity, and water flow rate in each section of the secondary cooling in the recovery phase according to the predicted information of the slab state, to form a target curve group;

[0011] S4: during the process of gradually increasing the drawing speed, collecting the surface temperature of the billet downstream of the secondary cooling zone to obtain billet surface temperature measurement data;

[0012] S5: comparing the measured surface temperature data of the slab with the theoretical surface temperature of the slab at the current position calculated based on the target curve of the drawing speed to obtain a temperature deviation;

[0013] S6: Based on the temperature deviation, the target curves of the drawing speed, the cooling intensity of the crystallizer, and the water flow rate in each section of the secondary cooling are corrected to obtain a corrected target curve group, and the corrected target curve group is used for production.

[0014] This application provides a method for controlling the production of oxygen-free copper slabs, designed to address defects caused by differences between the slab state and normal production conditions when resuming production after an unplanned shutdown. This method achieves precise control of process parameters during the recovery phase by predicting the slab state, generating a target curve set, monitoring temperature deviations in real time, and dynamically correcting the target curve set. This method has the advantages of reducing slab defects during the recovery phase and ensuring a smooth transition to production.

[0015] Furthermore, step S1 includes:

[0016] S11: Determine the duration of the unplanned parking. If the parking duration is less than a preset duration threshold, it is determined to be a short parking; if the parking duration is greater than or equal to the preset duration threshold, it is determined to be a long parking;

[0017] S12: When it is determined to be a short-term shutdown, the crystallizer cooling water flow rate, the cooling water flow rate of each secondary cooling section, and the cooling water temperature are obtained and recorded as the short-term shutdown cooling conditions;

[0018] S13: When it is determined to be a long-term shutdown, determine whether the emergency cooling mode is started; if started, obtain the emergency cooling water flow of the crystallizer, the emergency cooling water flow of each section of the secondary cooling, and the cooling water temperature, and record them as the long-term shutdown cooling conditions; if not started, determine that the cooling condition is natural cooling, and record the ambient temperature.

[0019] The present application provides a method for controlling the production of oxygen-free copper ingots, which aims to solve the impact of unplanned parking time and cooling conditions on the state of the ingots. By distinguishing the parking time and cooling method, the parking information can be obtained more accurately, thereby providing more accurate basic data for subsequent temperature prediction and control.

[0020] Furthermore, step S2 includes:

[0021] S21: Constructing the heat conduction and solidification model of the ingot;

[0022] S22: using the slab heat conduction and solidification model, simulating temperature field changes inside the slab during the shutdown period until the simulation duration reaches the unplanned shutdown duration, and obtaining the temperature distribution of the slab in the crystallizer and the secondary cooling zone at the end of the shutdown;

[0023] S23: judging the solidification state of each position of the ingot based on the temperature distribution;

[0024] S24: Integrate the temperature distribution and the solidification state to generate billet state prediction information, wherein the billet state prediction information includes temperature values ​​at various positions of the billet, solidification shell thickness, and liquidus position.

[0025] The present application provides a method for regulating and controlling the production of oxygen-free copper ingots, which aims to more comprehensively predict the state of the ingots after an unplanned shutdown, and provide a more accurate basis for the subsequent resumption of production.

[0026] Furthermore, step S21 includes:

[0027] S211: Measure the cooling water flow rate, water temperature, and spray density along the length of the ingot, establish a mapping relationship between cooling intensity and position, and obtain the cooling intensity distribution of the mold and secondary cooling zone;

[0028] S212: Obtaining the thermal conductivity, specific heat capacity, and density of the ingot according to the material of the ingot, and establishing a thermophysical function relationship of the thermal conductivity, specific heat capacity, and density as a function of the temperature of the ingot;

[0029] S213: Determine a solidification latent heat release parameter of the ingot according to the specific heat capacity of the ingot;

[0030] S214: Constructing the heat conduction and solidification model of the casting according to the cooling intensity distribution of the crystallizer and the secondary cooling zone, the thermophysical function relationship, and the solidification latent heat release parameter.

[0031] The present application provides a method for controlling the production of oxygen-free copper ingots, which aims to provide a more accurate method for constructing a heat conduction and solidification model of the ingots, thereby improving the accuracy of predicting the ingot state after unplanned shutdown.

[0032] Furthermore, step S3 includes:

[0033] S31: determining the solidified shell thickness of the slab at the mold outlet, the temperature distribution of the central liquid phase region, and the surface temperature distribution of each section of the secondary cooling zone according to the slab state prediction information;

[0034] S32: Calculating a target curve of the drawing speed according to the solidified shell thickness;

[0035] S33: determining a target curve for the cooling intensity of the crystallizer according to the temperature distribution of the central liquid phase region;

[0036] S34: Calculating the required water flow rate for each section of the secondary cooling zone based on the surface temperature distribution of each section of the secondary cooling zone and the target curve of the drawing speed, and generating a target curve of the water flow rate for each section of the secondary cooling zone based on a preset flow distribution strategy;

[0037] The target curve group includes a target curve for drawing speed, a target curve for mold cooling intensity, and a target curve for water flow in each section of secondary cooling.

[0038] Furthermore, step S34 includes:

[0039] S341: Divide the ingot into multiple nodes along the thickness direction and establish the heat conduction equation between the nodes;

[0040] S342: constructing boundary conditions for the heat conduction equation between nodes based on the surface temperature distribution of each section in the secondary cooling zone and the target curve of the drawing speed in the recovery phase. The boundary conditions are used to solve the heat conduction equation between nodes.

[0041] S343: using an iterative algorithm to adjust the water flow required for each section of the secondary cooling zone and solve the heat conduction equation until the deviation between the calculated surface temperature of the ingot and the surface temperature distribution of each section of the secondary cooling zone is less than a preset threshold;

[0042] S344: Based on the adjusted required water flow of each section of the secondary cooling zone and in combination with a preset flow distribution strategy, the total water flow is distributed to each cooling section to generate a target curve of the water flow of each section of the secondary cooling zone.

[0043] Furthermore, step S5 includes:

[0044] S51: obtaining a measurement time when the billet surface temperature measurement data is collected, and calculating a current position of the billet downstream of the secondary cooling zone based on the billet surface temperature measurement data according to the target curve of the drawing speed and the measurement time;

[0045] S52: Calculating the theoretical surface temperature of the slab at the current position according to the target curve group;

[0046] S53: Subtract the theoretical surface temperature of the casting blank from the measured surface temperature data of the casting blank to obtain the temperature deviation.

[0047] Furthermore, step S52 includes:

[0048] S521: extracting the mold cooling intensity target curve and the water flow target curves for each section of the secondary cooling from the target curve group;

[0049] S522: Calculating the surface temperature of the cast strand at the mold outlet according to the mold cooling intensity target curve and the current position of the cast strand;

[0050] S523: Calculate the temperature change of the billet in the secondary cooling zone section by section based on the billet surface temperature at the crystallizer outlet and the water flow target curve of each section of the secondary cooling to obtain the theoretical billet surface temperature at the current position.

[0051] Furthermore, step S6 includes:

[0052] S61: Determine the correction strategy for recovering the casting speed, the cooling intensity of the crystallizer, and the water flow rate in each section of the secondary cooling;

[0053] S62: Based on the correction strategy and the temperature deviation, a correction amount for the drawing speed, a correction amount for the mold cooling intensity, and a correction amount for the water flow rate in each section of the secondary cooling in the recovery phase are calculated;

[0054] S63: The drawing speed correction amount, the mold cooling intensity correction amount and the water flow correction amount of each section of secondary cooling are respectively superimposed on the target curves of the drawing speed, the mold cooling intensity and the water flow of each section of secondary cooling to obtain the corrected target curve group, and the corrected target curve group is used for production.

[0055] In a second aspect, an oxygen-free copper ingot production control system is provided, which is applied to the steps of any of the above methods, and the system comprises:

[0056] Parking information acquisition module: obtains the unplanned parking duration and cooling conditions during parking;

[0057] A slab state prediction module: based on the unplanned stop duration and the cooling conditions, predicts the temperature distribution and solidification state of the slab in the crystallizer and the secondary cooling zone at the end of the stop, and obtains slab state prediction information;

[0058] Target curve generation module: generates target curves for the drawing speed, mold cooling intensity, and water flow rate in each section of secondary cooling in the recovery phase according to the predicted information of the ingot state;

[0059] Temperature data acquisition module: in the process of gradually increasing the drawing speed, collecting the surface temperature of the billet downstream of the secondary cooling zone, obtaining the billet surface temperature measurement data, and forming a target curve group;

[0060] Temperature deviation calculation module: compares the measured surface temperature data of the billet with the theoretical surface temperature of the billet at the current position calculated based on the target curve of the drawing speed to obtain the temperature deviation;

[0061] Parameter correction control module: Based on the temperature deviation, the target curves of the drawing speed, the cooling intensity of the crystallizer and the water flow rate of each section of the secondary cooling are corrected to obtain a corrected target curve group, and the corrected target curve group is used for production.

[0062] Beneficial Effects: This application proposes a method and system for controlling the production of oxygen-free copper slabs, designed to address defects caused by differences between the slab state and normal production conditions when resuming production after an unplanned shutdown. By predicting the slab state, generating a target curve set, monitoring temperature deviations in real time, and dynamically correcting the target curve set, this method achieves precise control of process parameters during the recovery phase. This method has the advantages of reducing slab defects during the recovery phase and ensuring a smooth transition to production. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 This is a flow chart of a method for controlling the production of oxygen-free copper ingots proposed in this application.

[0064] Figure 2 This is a structural diagram of an oxygen-free copper ingot production control system proposed in this application.

[0065] Description of reference numerals: 201, parking information acquisition module; 202, ingot state prediction module; 203, target curve generation module; 204, temperature data acquisition module; 205, temperature deviation calculation module; 206, parameter correction control module. DETAILED DESCRIPTION

[0066] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and marked in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work fall within the scope of protection of the present application.

[0067] It should be noted that similar reference numerals and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined or explained in subsequent figures. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0068] Please refer to Figure 1 A method for controlling the production of oxygen-free copper ingots for resuming production after an unplanned shutdown, comprising the steps of:

[0069] S1: Obtain the unplanned parking duration and cooling conditions during parking;

[0070] S2: Based on the unplanned shutdown duration and cooling conditions, the temperature distribution and solidification state of the billet in the crystallizer and secondary cooling zone at the end of the shutdown are predicted to obtain the billet state prediction information;

[0071] S3: Based on the predicted information of the casting state, target curves of the drawing speed, the cooling intensity of the crystallizer, and the water flow rate in each section of the secondary cooling in the recovery stage are generated respectively to form a target curve group;

[0072] S4: During the process of gradually increasing the drawing speed, the surface temperature of the billet downstream of the secondary cooling zone is collected to obtain billet surface temperature measurement data;

[0073] S5: comparing the measured surface temperature data of the slab with the theoretical surface temperature of the slab at the current position calculated based on the target curve of the drawing speed to obtain a temperature deviation;

[0074] S6: Based on the temperature deviation, the target curves of the drawing speed, the cooling intensity of the crystallizer, and the water flow rate in each section of the secondary cooling are corrected to obtain a corrected target curve group, and the corrected target curve group is used for production.

[0075] After an unplanned shutdown of an oxygen-free copper continuous casting line, the ingot exhibits a static and non-uniform temperature distribution and solidification state along its length within the mold and secondary cooling zone. This technical solution addresses the challenge of dynamically predicting and sensing the ingot's actual state based on the duration of the shutdown and cooling conditions during the shutdown, and then dynamically adjusting the primary and secondary cooling parameters to minimize defects during the recovery phase and ensure a smooth transition to production.

[0076] Among them, the unplanned downtime refers to the time interval between the production line stopping due to sudden reasons from normal operation to restarting, which can be achieved by recording with a timer or reading from the system log.

[0077] The cooling conditions during shutdown refer to the cooling method and intensity acting on the ingot during shutdown, which can be obtained by monitoring parameters such as cooling water flow, water temperature, whether emergency cooling is started or ambient temperature.

[0078] Predicting the temperature distribution and solidification state of the ingot in the crystallizer and secondary cooling zone at the end of the shutdown means determining the temperature value and solid-liquid phase distribution of each point inside the ingot at the end of the shutdown by calculation or simulation methods. This can be achieved by using a numerical simulation method based on a heat transfer solidification model.

[0079] The slab state prediction information refers to a data set describing the predicted slab temperature distribution and solidification state, which may include the temperature values ​​along the length and thickness directions of the slab, the thickness of the solidified shell, and the position of the liquidus line.

[0080] The target curves of the drawing speed, mold cooling intensity and water flow rate in each section of secondary cooling during the recovery phase refer to the expected sequence of control parameter values ​​that change with time or billet position during the production recovery process.

[0081] The surface temperature of the ingot downstream of the secondary cooling zone refers to the outer surface temperature of the ingot measured by non-contact means at the end of the secondary cooling zone or its subsequent position, which can be collected by an infrared thermometer.

[0082] The billet surface temperature measurement data refers to the billet surface temperature value collected in real time.

[0083] The theoretical surface temperature of the ingot refers to the surface temperature of the ingot at the measurement position calculated by the calculation model based on the currently applied drawing speed, crystallizer cooling intensity and the target curve of water flow in each section of secondary cooling. It can be achieved by using the forward calculation method based on the heat conduction equation.

[0084] Temperature deviation refers to the difference between the measured surface temperature of the billet and the theoretical surface temperature of the billet.

[0085] Modifying the target curve means adjusting the original target curves of drawing speed, mold cooling intensity and water flow rate in each section of secondary cooling according to temperature deviation. This can be achieved by using proportional integral differential (PID) control, fuzzy control or rule-based adjustment strategies. The main purpose is to make the actual production process closer to the ideal state and compensate for prediction errors and external disturbances.

[0086] As a preferred embodiment, the solution of this application is specifically implemented as follows: the unplanned downtime duration and cooling conditions are acquired via sensors and a database connected to the production control system. The slab state prediction module utilizes a two-dimensional transient heat transfer solidification model based on the finite difference method. Input parameters include downtime duration, mold cooling water flow rate and temperature, water flow rate and temperature in each secondary cooling section, and ambient temperature. The module calculates the temperature field along the length of the slab and the distribution of solidified shell thickness at the end of the downtime.

[0087] The target curve generation module determines the initial recovery pulling speed based on the predicted solidified shell thickness at the crystallizer outlet, and combines the predicted temperature distribution in the secondary cooling zone to determine the cooling intensity and water flow required in the recovery stage through inverse calculation, thereby generating a piecewise linear target curve that changes with the recovery time.

[0088] An infrared thermometer is installed at the end of the secondary cooling zone to collect real-time surface temperature data. The temperature deviation calculation module uses a forward heat transfer model to calculate the theoretical surface temperature at the temperature measurement location based on the current drawing speed and target curve, and subtracts the actual measured temperature to obtain the deviation. The parameter correction control module utilizes a rule-based expert system. Based on the magnitude and trend of the temperature deviation, it searches a pre-set correction rule table to determine the corrections for the drawing speed, mold cooling intensity, and water flow rate in each secondary cooling section. These corrections are then sent to the actuator to adjust the actual control parameters.

[0089] Through the above scheme, this application can accurately predict the actual state of the billet after an unplanned shutdown and generate a reasonable production resumption control strategy based on this. At the same time, through real-time monitoring and feedback correction, it can cope with prediction errors and uncertainties in the production process, dynamically matching the actual control parameters with the billet state, effectively avoiding defects such as billet surface cracks and internal porosity caused by insufficient or excessive cooling, improving the success rate of production resumption and billet quality, and ensuring a smooth transition and efficient operation of the production line.

[0090] Furthermore, step S1 includes:

[0091] S11: Determine the duration of unplanned parking. If the parking duration is less than a preset duration threshold, it is determined to be a short parking; if the parking duration is greater than or equal to the preset duration threshold, it is determined to be a long parking;

[0092] S12: When it is determined to be a short-term shutdown, the crystallizer cooling water flow rate, the cooling water flow rate of each secondary cooling section, and the cooling water temperature are obtained and recorded as the short-term shutdown cooling conditions;

[0093] S13: When it is determined to be a long-term shutdown, determine whether the emergency cooling mode is started; if started, obtain the emergency cooling water flow of the crystallizer, the emergency cooling water flow of each section of the secondary cooling, and the cooling water temperature, and record them as the long-term shutdown cooling conditions; if not started, determine that the cooling condition is natural cooling, and record the ambient temperature.

[0094] Among them, the preset time threshold refers to the time limit used to distinguish short-term parking from long-term parking, which can be set based on empirical data, simulation calculations or process requirements.

[0095] Among them, short-term shutdown cooling conditions refer to a set of parameters used to describe the cooling effects on the ingot during the shutdown period when the shutdown time is short, which may include the cooling water flow and temperature of the crystallizer and secondary cooling zone.

[0096] Among them, long-term shutdown cooling conditions refer to a set of parameters used to describe the cooling effects on the ingot during the shutdown period when the shutdown time is long. It can include the cooling water flow and temperature during emergency cooling, or the ambient temperature during natural cooling.

[0097] Among them, the emergency cooling mode refers to an enhanced cooling measure taken to quickly reduce the temperature of the ingot or control the solidification state during long-term shutdown. It may involve increasing the cooling water flow, changing the spraying method or using other cooling media.

[0098] Among them, natural cooling refers to the cooling process that occurs when the billet is stopped for a long time and the emergency cooling mode is not activated, and the cooling rate is usually slow.

[0099] As a preferred embodiment, the solution of the present application is specifically implemented as follows: On an oxygen-free copper continuous casting production line, when an unplanned stop occurs, the system automatically records the start time of the stop. After the stop is completed, the stop duration is calculated. For example, the preset time threshold can be set to 10 minutes. If the stop duration is less than 10 minutes, it is determined to be a short stop. At this time, the system automatically reads the data of the crystallizer cooling water flow sensor, the secondary cooling section cooling water flow sensor and the cooling water temperature sensor during the stop period, and records these data, marking them as short-term stop cooling conditions. If the stop duration is greater than or equal to 10 minutes, it is determined to be a long stop. The system will check the operating status of the emergency cooling system. If the emergency cooling system has been manually or automatically started, the system will read the data of the crystallizer emergency cooling water flow, the secondary cooling section emergency cooling water flow and the cooling water temperature sensor during the emergency cooling period, and record them as long-term stop cooling conditions. If the emergency cooling system is not started, the system will read the data of the workshop ambient temperature sensor and record them as natural cooling conditions. The acquired parking time and corresponding cooling condition data are then input into the slab state prediction model to calculate the temperature distribution and solidification state of the slab at the end of the parking.

[0100] Furthermore, step S2 includes:

[0101] S21: Constructing the heat conduction and solidification model of the ingot;

[0102] S22: Using the slab heat conduction and solidification model, simulate the temperature field changes inside the slab during the shutdown period until the simulation duration reaches the unplanned shutdown duration, and obtain the temperature distribution of the slab in the crystallizer and secondary cooling zone at the end of the shutdown;

[0103] S23: judging the solidification state of each position of the ingot based on the temperature distribution;

[0104] S24: Integrate the temperature distribution and the solidification state to generate ingot state prediction information, where the ingot state prediction information includes the temperature value at each position of the ingot, the solidification shell thickness, and the liquidus position.

[0105] Among them, constructing a heat conduction and solidification model of the ingot refers to establishing a mathematical and physical model that can describe the temperature distribution and phase change process of the ingot during the cooling process.

[0106] Simulating the temperature field changes inside the ingot during parking means using the ingot heat conduction and solidification model, inputting the cooling conditions and parking duration during parking, and calculating and predicting the temperature distribution inside the ingot that changes with time.

[0107] Determining the solidification state at various locations within the ingot involves determining whether different locations within the ingot are in a liquid, solid, or a coexistence of solid and liquid phases based on the simulated temperature distribution and the material's solidification characteristics (such as the liquidus and solidus temperatures). Specifically, if the temperature at at least one location within the ingot is less than the ingot's melting point, that location is considered solid; if the temperature at at least one location within the ingot is greater than or equal to the ingot's melting point but less than the ingot's melting temperature, that location is considered to be in a coexistence of solid and liquid phases; and if the temperature at at least one location within the ingot is greater than or equal to the ingot's melting temperature, that location is considered to be liquid.

[0108] Integrating temperature distribution and solidification state means associating and organizing the simulated temperature values ​​and the judged solidification shell thickness, liquidus position and other information to form a structured data set. This can be achieved by data structure definition, database storage or specific file format output.

[0109] The ingot state prediction information refers to an integrated data set that contains information describing the key state parameters of the ingot at the end of the shutdown, which may include the temperature value of each position of the ingot, the thickness of the solidified shell, and the liquidus line position.

[0110] Furthermore, step S21 includes:

[0111] S211: Measure the cooling water flow rate, water temperature, and spray density along the length of the ingot, establish a mapping relationship between cooling intensity and position, and obtain the cooling intensity distribution of the mold and secondary cooling zone;

[0112] S212: Obtaining the thermal conductivity, specific heat capacity, and density of the ingot according to the material of the ingot, and establishing a thermophysical function relationship of the thermal conductivity, specific heat capacity, and density as the temperature of the ingot changes;

[0113] S213: Determine solidification latent heat release parameters of the ingot according to the specific heat capacity of the ingot;

[0114] S214: Construct a heat conduction and solidification model for the ingot based on the cooling intensity distribution, thermophysical function relationship, and solidification latent heat release parameters of the crystallizer and secondary cooling zone.

[0115] Among them, cooling intensity refers to the ability of the cooling medium (such as cooling water) to remove heat from the surface of the ingot. Its size is affected by many factors such as cooling water flow, water temperature, spraying method (spraying density, nozzle type, spraying pressure, etc.) and surface state of the ingot, and can be characterized by the heat transfer coefficient per unit area; the thermophysical function relationship refers to the mathematical expression or data table of physical quantities such as thermal conductivity, specific heat capacity and density of the material changing with temperature. These parameters are the basis for heat conduction calculations and reflect the thermal conductivity and heat storage characteristics of the material at different temperatures; the solidification latent heat release parameter refers to the heat released when a unit mass of metal changes from liquid to solid during the solidification process of the ingot, as well as the release method or distribution law of this heat within the solidification temperature range. This parameter is the key to simulating the solidification process.

[0116] Specifically, the steps of constructing the heat conduction and solidification model of the casting are:

[0117] Get cooling intensity distribution: The mapping relationship between cooling intensity q and position x can be described by the convective heat transfer coefficient h(x). ,in, is the cooling water flow rate, is the cooling water temperature, is the spray density of cooling water.

[0118] Cooling intensity distribution: ,in, Is the billet in position The surface temperature at .

[0119] Based on the cooling intensity distribution, the boundary conditions of the ingot surface in the mold and secondary cooling zone can be obtained: This boundary condition is used to ensure that the heat conduction and solidification model of the billet can reflect the heat exchange behavior between the billet and the cooling medium (such as cooling water) during the actual production process. is the normal temperature gradient of the ingot surface, is the thermal conductivity of the billet, and n is the normal direction of the billet surface.

[0120] The relationship between the change of thermophysical properties (thermal conductivity, specific heat capacity, density) and temperature can be expressed as:

[0121] ; ; .

[0122] Where, T is the theoretical temperature; is a constant term, representing the basic value of thermal conductivity at low temperatures; is the linear coefficient, which indicates the rate at which thermal conductivity changes linearly with temperature; is the quadratic term coefficient, which indicates the nonlinear change of thermal conductivity with temperature; is a constant term, representing the basic value of specific heat capacity at low temperatures; is the linear coefficient, which indicates the rate at which the specific heat capacity changes linearly with temperature; The coefficient of the quadratic term represents the nonlinear variation of specific heat capacity with temperature; is a constant term, representing the basic value of density at low temperatures; is the linear coefficient, which represents the rate at which density changes linearly with temperature; is the quadratic coefficient, representing the nonlinear change of density with temperature. K(T) represents the relationship between the thermal conductivity and temperature, and ρ(T) represents the relationship between the density and temperature.

[0123] The latent heat of solidification L is the heat released when the material changes from liquid to solid, that is, the latent heat release parameter of solidification: ,in is the liquidus temperature, is the solidus temperature, is the relationship between specific heat capacity and temperature.

[0124] The heat conduction equation is: ,in, is the temperature gradient, is the latent heat release term of solidification, which can be expressed as: ,in is the solid fraction, which can be expressed as: .

[0125] In summary, the complete heat conduction and solidification model of the casting includes:

[0126] Heat conduction equation: ,

[0127] Boundary conditions: ,

[0128] Thermophysical function relationship: ; ; .

[0129] Cooling intensity distribution: .

[0130] In practical applications, numerical methods (such as the finite element method or the finite difference method) are usually used to solve the heat conduction and solidification model of the ingot. This can accurately simulate the cooling process of the ingot in the crystallizer and the secondary cooling zone, predict the temperature field and solidification state, and thus optimize the production process and improve the quality of the ingot.

[0131] Furthermore, step S3 includes:

[0132] S31: determining the solidified shell thickness of the slab at the mold outlet, the temperature distribution of the central liquid phase zone, and the surface temperature distribution of each section of the secondary cooling zone based on the slab state prediction information;

[0133] S32: Calculate the target curve of the pulling speed according to the thickness of the solidified shell;

[0134] S33: determining a target curve for the cooling intensity of the crystallizer according to the temperature distribution of the central liquid phase region;

[0135] S34: Calculating the required water flow rate for each section of the secondary cooling zone based on the surface temperature distribution of each section of the secondary cooling zone and the target curve of the drawing speed, and generating a target curve of the water flow rate for each section of the secondary cooling zone based on a preset flow distribution strategy;

[0136] The target curve group includes a target curve for drawing speed, a target curve for mold cooling intensity, and a target curve for water flow in each section of secondary cooling.

[0137] Among them, the ingot state prediction information refers to the estimated data of the temperature distribution and solidification state of the ingot in the crystallizer and secondary cooling zone at the end of the unplanned shutdown, which can be achieved by using a numerical simulation method based on the heat conduction and solidification model.

[0138] The solidified shell thickness refers to the thickness of the solidified shell formed by the ingot at a specific position (such as the mold outlet), which can be determined by judging the position of the solidification front based on the temperature distribution.

[0139] The temperature distribution of the central liquid phase zone refers to the temperature change of the liquid metal that has not yet solidified in the central area of ​​the ingot along the length direction. It can be determined by extracting the center line temperature based on the temperature distribution data.

[0140] The surface temperature distribution of each section in the secondary cooling zone refers to the temperature variation of the surface of the ingot in different cooling sections along the length direction in the secondary cooling zone, which can be determined by extracting the surface temperature based on the temperature distribution data.

[0141] The target curve of the drawing speed refers to the preset trajectory of the speed of the drawing device pulling the billet changing with time or the billet position during the production resumption stage.

[0142] The target curve of the mold cooling intensity refers to the preset trajectory of the intensity of the mold cooling the billet over time or the billet position during the production resumption phase.

[0143] The target curve of the water flow rate in each section of the secondary cooling zone refers to the preset trajectory of the cooling water flow rate sprayed or immersed on the billet in each section of the secondary cooling zone changing with time or billet position during the production resumption stage.

[0144] The preset flow distribution strategy refers to the rule or algorithm for distributing the calculated total required water flow for secondary cooling to each cooling section in the secondary cooling area. The flow ratio of each section can be determined based on the length ratio of each section, the target temperature gradient of each section, or an optimization algorithm.

[0145] Furthermore, step S34 includes:

[0146] S341: Divide the ingot into multiple nodes along the thickness direction and establish the heat conduction equation between the nodes;

[0147] S342: Based on the surface temperature distribution of each section in the secondary cooling zone and the target curve of the drawing speed in the recovery stage, boundary conditions of the heat conduction equation between the nodes are constructed. The boundary conditions are used to solve the heat conduction equation between the nodes.

[0148] S343: Using an iterative algorithm, adjusting the required water flow rate of each section of the secondary cooling zone, and solving the heat conduction equation between the nodes, until the deviation between the calculated surface temperature of the ingot and the surface temperature distribution of each section of the secondary cooling zone is less than a preset threshold;

[0149] S344: Based on the adjusted required water flow of each section of the secondary cooling zone and in combination with a preset flow distribution strategy, the total water flow is distributed to each cooling section to generate a target curve for the water flow of each section of the secondary cooling zone.

[0150] Assuming that the billet is divided into N nodes along the thickness direction and the spacing between adjacent nodes is equal, the heat conduction equation between the nodes can be expressed as: ,in, is the theoretical temperature of the ith node, is the square of the node spacing, represents the next theoretical temperature adjacent to the i-th node, represents the previous theoretical temperature adjacent to the i-th node; is the latent heat release of solidification at the ith node.

[0151] Among them, the surface temperature distribution of each section in the secondary cooling zone is: ;

[0152] is the heat exchange coefficient of the heat conduction equation between nodes, .

[0153] in is the pulling speed at time t. The target curve of the pulling speed in the recovery phase can be expressed as:

[0154] ,in, 、 、 ... It is a coefficient determined according to process requirements and billet characteristics, and t is time.

[0155] Since the drawing speed affects the time the billet stays in each section of the secondary cooling zone, thereby affecting the surface temperature of the billet, the drawing speed can be taken into consideration when constructing the heat exchange coefficient of the heat conduction equation.

[0156] Therefore, combined with the surface temperature distribution of each section in the secondary cooling zone and the target curve of the drawing speed in the recovery stage, the boundary conditions of the heat conduction equation between the nodes are obtained as follows: .

[0157] The formula for adjusting the water flow required for each section of the secondary cooling zone using an iterative algorithm is:

[0158] ,in is the water flow rate of the mth segment at the nth iteration; is the water flow rate of the mth segment at the nth iteration; It is the adjustment coefficient, which plays the role of adjusting the cooling intensity according to the deviation between the surface temperature of the billet and the target billet surface temperature. It can be set according to the experience of technicians and gradually debugged in actual application; is the surface temperature of the ingot calculated at the nth iteration; It is the target billet surface temperature, that is, the temperature you hope to achieve during the production process.

[0159] The finite difference method is used to solve the heat conduction equation and obtain the temperature distribution T(x,t) inside the ingot, which is: ,in is the temperature of the ith node at the nth iteration, is the temperature of the ith node at the n+1th iteration; is the temperature of the i + 1th node at the nth iteration; is the temperature of the i-1th node at the nth iteration; ρ is the density of the ingot, is the relationship between the specific heat capacity of the ingot and the temperature. is the time step. The iteration stops when the deviation between the calculated slab surface temperature and the surface temperature distribution of each segment in the secondary cooling zone is less than a preset threshold. Otherwise, the water flow rate is adjusted and the heat conduction equation between the nodes is re-solved.

[0160] Combining a pre-set flow distribution strategy means, after determining the total water flow required for each section, allocating the total flow to the independently controlled sections of the secondary cooling zone according to pre-set rules or ratios. This can be based on the length ratio of each section, a fixed ratio determined based on experience, or a dynamic ratio distribution strategy based on specific cooling curve requirements.

[0161] Distributing the total water flow to each cooling section means determining the specific water flow rate for each independent control unit within the secondary cooling zone based on the allocation strategy. This can be achieved by controlling the output of valves or pumps and setting the calculated flow rate value to the cooling water control system of each cooling section.

[0162] Furthermore, step S5 includes:

[0163] S51: obtaining the measurement time when the billet surface temperature measurement data is collected, and calculating the current position of the billet downstream of the secondary cooling zone based on the billet surface temperature measurement data according to the target curve of the drawing speed and the measurement time;

[0164] S52: Calculating the theoretical surface temperature of the slab at the current position according to the target curve group;

[0165] S53: Subtract the theoretical surface temperature of the ingot from the measured surface temperature data of the ingot to obtain a temperature deviation.

[0166] Specifically, first, based on the target curve of the drawing speed in the recovery phase and the measurement time when the billet surface temperature measurement data is collected, the actual position of the billet downstream of the secondary cooling zone corresponding to the measurement data is calculated.

[0167] In actual continuous casting production applications, position sensors are easily affected by high temperatures, making it difficult to achieve the required measurement accuracy. Existing high-temperature position sensors, such as eddy current position sensors and magnetostrictive position sensors, are expensive and hinder their widespread industrialization. Furthermore, even with high-temperature position sensors, environmental factors such as cooling water shock and vibration can distort the position sensor's measurement accuracy in continuous casting production lines.

[0168] The reason why this application chooses to use the indirect calculation method is to save costs on the one hand and ensure the accuracy of the current position acquisition on the other hand. In addition, the calculation method is stored in the software, and there is no need to consider the problem of mechanical wear, which provides convenience for later maintenance.

[0169] This application obtains the current position by integrating the velocity of the target drawing speed curve before the measurement time point, thereby determining the distance the billet has traveled from the starting position (e.g., the mold exit) to the measurement point. The actual measured temperature data and the theoretically calculated temperature data are mapped to the same position on the billet to ensure accurate comparison.

[0170] Next, the theoretical surface temperature of the strand at the current position determined above is calculated based on the overall target curve set for the recovery phase. This typically requires the use of a strand heat conduction model. This model uses parameters such as the mold cooling intensity and the water flow rate in each secondary cooling section, as inputs, to simulate the temperature changes along the strand's length during the casting speed recovery process. This model can calculate the theoretical surface temperature that the strand should achieve at the current position when operating according to the target curve.

[0171] Finally, the actual surface temperature measurement data collected is subtracted from the theoretical surface temperature calculated at that location to obtain the temperature deviation. This temperature deviation reflects the difference between the actual surface temperature of the casting during production and the theoretical temperature when running according to the plan (target curve group).

[0172] This method determines the actual position of the billet by combining the drawing speed target curve and the measurement time, and calculates the theoretical surface temperature at that position based on the target curve, thereby achieving a more accurate temperature deviation assessment.

[0173] Furthermore, step S52 includes:

[0174] S521: extracting the mold cooling intensity target curve and the secondary cooling water flow target curves in the target curve group;

[0175] S522: Calculating the surface temperature of the cast strand at the mold outlet according to the mold cooling intensity target curve and the current position of the cast strand;

[0176] S523: Based on the surface temperature of the billet at the crystallizer outlet and the target curve of the water flow rate in each section of the secondary cooling, the temperature change of the billet in the secondary cooling zone is calculated section by section to obtain the theoretical surface temperature of the billet at the current position.

[0177] Specifically, this solution aims to provide a more accurate method for calculating the theoretical surface temperature of the ingot, thereby improving the accuracy of temperature deviation calculation and ultimately improving the production quality of oxygen-free copper ingots.

[0178] First, the target curves for mold cooling intensity and water flow rate in each secondary cooling stage are extracted from the target curve group. These serve as the basis for calculating the theoretical surface temperature of the strand. These target curves are generated based on the predicted state of the strand after the unplanned shutdown and represent the cooling strategy planned for the resumption of production.

[0179] The mold cooling intensity and secondary cooling water flow rate directly affect the cooling rate and temperature distribution of the strand. Therefore, accurately extracting this data is crucial for subsequent calculations. The strand surface temperature at the mold outlet is then calculated based on the mold cooling intensity target curve and the strand's current position. The mold outlet temperature is the initial temperature of the strand upon entering the secondary cooling zone and has a significant impact on subsequent temperature changes. By combining the mold cooling intensity distribution along its length with the strand's motion within the mold, a more accurate estimate of the mold outlet temperature can be achieved.

[0180] Finally, based on the billet surface temperature at the mold outlet and the target water flow curves for each secondary cooling section, the temperature variation of the billet within the secondary cooling zone is calculated section by section to obtain the theoretical billet surface temperature at the current position. This section-by-section calculation method takes into account the differences in cooling intensity within each section of the secondary cooling zone and can more accurately simulate the temperature variation of the billet within the secondary cooling zone, thereby obtaining a more accurate theoretical billet surface temperature.

[0181] Furthermore, step S6 includes:

[0182] S61: Determine the correction strategy for recovering the casting speed, the cooling intensity of the crystallizer, and the water flow rate in each section of the secondary cooling;

[0183] S62: Based on the correction strategy and the temperature deviation, a correction value for the drawing speed in the recovery phase, a correction value for the mold cooling intensity, and a correction value for the water flow rate in each section of the secondary cooling are calculated;

[0184] S63: The drawing speed correction amount, the mold cooling intensity correction amount, and the water flow correction amount of each section of the secondary cooling are respectively superimposed on the target curve group of the drawing speed, the mold cooling intensity, and the water flow of each section of the secondary cooling to obtain a corrected target curve group, and the corrected target curve is used for production.

[0185] The correction strategy refers to the rules or algorithms that determine how to calculate corrections to the drawing speed, mold cooling intensity, and water flow rate in each section of the secondary cooling process based on the magnitude, direction, and trend of temperature deviation. This can be achieved using proportional control, proportional-integral-derivative (PID) control, fuzzy control, model-based control, or table lookup.

[0186] Specifically, during the production resumption process, the solution uses the deviation between the real-time surface temperature of the ingot and the theoretical temperature as a feedback signal to dynamically adjust the target curves of the drawing speed, the cooling intensity of the crystallizer, and the water flow rate in each section of the secondary cooling.

[0187] First, a correction strategy must be pre-set or determined online. This strategy defines how temperature deviations are translated into adjustments to various process parameters. For example, when the measured temperature is higher than the theoretical temperature, the casting speed may need to be reduced and the cooling intensity increased; when the measured temperature is lower than the theoretical temperature, the casting speed may need to be increased and the cooling intensity reduced. Based on this determined correction strategy, the temperature deviation calculated in step S5 is input into the correction algorithm to calculate the required adjustments to the drawing speed, mold cooling intensity, and water flow rate in each section of the secondary cooling at the current moment—the correction amounts.

[0188] These corrections reflect the difference between the actual state of the current slab and the state predicted based on the initial target curve, as well as the parameter adjustment required to eliminate this difference.

[0189] Finally, the calculated correction values ​​are added to the original target curves of the drawing speed, the cooling intensity of the crystallizer, and the water flow rate in each section of the secondary cooling generated in step S3, thereby obtaining a new set of target curves that have been corrected in real time.

[0190] In the subsequent production process, the control system no longer follows the initial target curve set completely, but instead uses this revised target curve set to control the drawing device and cooling system. This process can be carried out continuously, forming a closed-loop control, so that the process parameters can be dynamically adjusted according to the actual temperature state of the billet, thereby more accurately guiding the billet to complete the solidification and cooling process. In this way, the solution combines prediction (S1-S3) with real-time feedback (S4-S5), using temperature deviations to make online corrections to the initial plan, improving the adaptability and accuracy of process control in the production resumption stage.

[0191] Please refer to Figure 2 , an oxygen-free copper ingot production control system, applied to the steps of any of the above methods, the system comprises:

[0192] Parking information acquisition module 201: acquires the unplanned parking duration and cooling conditions during parking;

[0193] The slab state prediction module 202 predicts the temperature distribution and solidification state of the slab in the mold and secondary cooling zone at the end of the unplanned shutdown based on the unplanned shutdown duration and cooling conditions, and obtains slab state prediction information;

[0194] Target curve generation module 203: generates target curves for the drawing speed, mold cooling intensity, and water flow rate in each section of secondary cooling in the recovery phase according to the predicted information of the slab state, forming a target curve group;

[0195] Temperature data acquisition module 204: collects the surface temperature of the billet downstream of the secondary cooling zone during the process of gradually increasing the drawing speed, and obtains billet surface temperature measurement data;

[0196] Temperature deviation calculation module 205: compares the measured surface temperature data of the ingot with the theoretical surface temperature of the ingot at the current position calculated based on the target curve of the drawing speed to obtain the temperature deviation;

[0197] Parameter correction control module 206: Based on the temperature deviation, the target curves of the drawing speed, the cooling intensity of the crystallizer and the water flow rate of each section of the secondary cooling are corrected to obtain a corrected target curve group, and the corrected target curve group is used for production.

[0198] The parking information acquisition module 201 refers to a unit for collecting basic data related to unplanned parking events, which can be implemented by using sensors, data interfaces or manual input interfaces.

[0199] The slab state prediction module 202 is a unit for simulating and calculating the change of the internal thermal state of the slab during the shutdown period, which can be implemented by using a simulation software module based on a physical model (such as finite element, finite difference).

[0200] The target curve generation module 203 is a unit for calculating and outputting preset trajectories of key parameters changing with time or position during the recovery production process according to the predicted billet state, and can be implemented by an algorithm program running on a computer or controller.

[0201] The temperature data acquisition module 204 is a unit for real-time monitoring of the surface temperature of the ingot, which can be implemented by using non-contact or contact temperature sensors such as infrared thermometers and thermocouples.

[0202] The temperature deviation calculation module 205 is a unit for comparing the difference between the actual measured temperature and the theoretical calculated temperature, and can be implemented by a data processing program running on a processing unit.

[0203] The parameter correction control module 206 is a unit for adjusting the target curve group according to the temperature deviation and outputting a control instruction, which can be implemented by a closed-loop control algorithm module running on the controller.

[0204] Specifically, the system functionalizes each step of the above method through modular design, thereby realizing the automated execution of the entire regulation process.

[0205] First, the parking information acquisition module 201 obtains the duration of unplanned parking and the cooling conditions during the parking period. This data is provided to the slab state prediction module 202. Based on this data, the slab state prediction module 202 predicts the temperature distribution and solidification state of the slab at the end of the parking period, generating slab state prediction information. This prediction information reflects the actual internal state of the slab after the parking period, providing a basis for subsequent parameter adjustments.

[0206] Based on the predicted slab state information, the target curve generation module 203 generates initial target curves for the drawing speed, mold cooling intensity, and water flow rate in each secondary cooling section during the recovery phase, providing guidance for resuming production. As the drawing speed gradually increases, the temperature data acquisition module 204 collects real-time slab surface temperature downstream of the secondary cooling zone, generating surface temperature measurement data.

[0207] The temperature deviation calculation module 205 compares the measured temperature with the theoretical surface temperature of the ingot at the current position calculated based on the drawing speed target curve to obtain the temperature deviation.

[0208] Based on temperature deviations, the parameter correction control module 206 modifies the target curves for drawing speed, mold cooling intensity, and water flow in each section of secondary cooling, and uses these modified target curves for production. Through the closed loop of temperature data collection, deviation calculation, and parameter correction control, the system can sense and respond to changes in the billet state in real time, dynamically adjusting production parameters.

[0209] The system automates the complex calculation and judgment processes in the above method, allowing for quick and precise control. As a result, during the resumption of production, the pulling speed and cooling intensity can be dynamically adjusted according to the actual state of the ingot, avoiding defects caused by mismatch between parameters and the ingot state.

[0210] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any actual relationship or order between these entities or operations.

[0211] The foregoing is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. Persons skilled in the art will readily appreciate that the present application may be modified and altered in various ways. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A method for controlling the production of oxygen-free copper ingots for resuming production after an unplanned shutdown, characterized in that: The method comprises the steps of: S1: Obtain the unplanned parking duration and cooling conditions during parking; Step S1 includes: S11: Determine the duration of the unplanned parking. If the parking duration is less than a preset duration threshold, it is determined to be a short parking; if the parking duration is greater than or equal to the preset duration threshold, it is determined to be a long parking; S12: When it is determined to be a short-term shutdown, the crystallizer cooling water flow rate, the cooling water flow rate of each secondary cooling section, and the cooling water temperature are obtained and recorded as the short-term shutdown cooling conditions; S13: When it is determined that the shutdown is long-term, determine whether the emergency cooling mode is activated; if activated, obtain the emergency cooling water flow of the crystallizer, the emergency cooling water flow of each section of the secondary cooling, and the cooling water temperature, and record them as the long-term shutdown cooling conditions; if not activated, determine that the cooling condition is natural cooling, and record the ambient temperature; S2: Based on the unplanned parking duration and the cooling conditions, predicting the temperature distribution and solidification state of the slab in the crystallizer and the secondary cooling zone at the end of the parking, and obtaining slab state prediction information; Step S2 includes: S21: Constructing the heat conduction and solidification model of the ingot; S22: using the slab heat conduction and solidification model, simulating temperature field changes inside the slab during the shutdown period until the simulation duration reaches the unplanned shutdown duration, and obtaining the temperature distribution of the slab in the crystallizer and the secondary cooling zone at the end of the shutdown; S23: judging the solidification state of each position of the ingot based on the temperature distribution; S24: Integrate the temperature distribution and the solidification state to generate billet state prediction information, wherein the billet state prediction information includes temperature values ​​at various positions of the billet, solidification shell thickness, and liquidus position; S3: generating target curves for the drawing speed, mold cooling intensity, and water flow rate in each section of the secondary cooling in the recovery phase according to the predicted information of the slab state, to form a target curve group; S4: during the process of gradually increasing the drawing speed, collecting the surface temperature of the billet downstream of the secondary cooling zone to obtain billet surface temperature measurement data; S5: comparing the measured surface temperature data of the slab with the theoretical surface temperature of the slab at the current position calculated based on the target curve of the drawing speed to obtain a temperature deviation; S6: Based on the temperature deviation, the target curves of the drawing speed, the cooling intensity of the crystallizer, and the water flow rate in each section of the secondary cooling are corrected to obtain a corrected target curve group, and the corrected target curve group is used for production.

2. The method for controlling production of oxygen-free copper casting according to claim 1, wherein: Step S21 includes: S211: Measure the cooling water flow rate, water temperature, and spray density along the length of the ingot, establish a mapping relationship between cooling intensity and position, and obtain the cooling intensity distribution of the mold and secondary cooling zone; S212: Obtaining the thermal conductivity, specific heat capacity, and density of the ingot according to the material of the ingot, and establishing a thermophysical function relationship of the thermal conductivity, specific heat capacity, and density as a function of the temperature of the ingot; S213: Determine a solidification latent heat release parameter of the ingot according to the specific heat capacity of the ingot; S214: Constructing the heat conduction and solidification model of the casting according to the cooling intensity distribution of the crystallizer and the secondary cooling zone, the thermophysical function relationship, and the solidification latent heat release parameter.

3. The method for controlling production of oxygen-free copper casting according to claim 1, wherein: Step S3 includes: S31: determining the solidified shell thickness of the slab at the mold outlet, the temperature distribution of the central liquid phase region, and the surface temperature distribution of each section of the secondary cooling zone according to the slab state prediction information; S32: Calculating a target curve of the drawing speed according to the solidified shell thickness; S33: determining a target curve for the cooling intensity of the crystallizer according to the temperature distribution of the central liquid phase region; S34: Calculating the required water flow rate for each section of the secondary cooling zone based on the surface temperature distribution of each section of the secondary cooling zone and the target curve of the drawing speed, and generating a target curve of the water flow rate for each section of the secondary cooling zone based on a preset flow distribution strategy; The target curve group includes a target curve for drawing speed, a target curve for mold cooling intensity, and a target curve for water flow in each section of secondary cooling.

4. The method for controlling production of oxygen-free copper casting according to claim 3, wherein: Step S34 includes: S341: Divide the ingot into multiple nodes along the thickness direction and establish the heat conduction equation between the nodes; S342: constructing boundary conditions for the heat conduction equation between nodes based on the surface temperature distribution of each section in the secondary cooling zone and the target curve of the drawing speed in the recovery phase. The boundary conditions are used to solve the heat conduction equation between nodes. S343: using an iterative algorithm to adjust the water flow required for each section of the secondary cooling zone and solve the heat conduction equation until the deviation between the calculated surface temperature of the ingot and the surface temperature distribution of each section of the secondary cooling zone is less than a preset threshold; S344: Based on the adjusted required water flow of each section of the secondary cooling zone and in combination with a preset flow distribution strategy, the total water flow is distributed to each cooling section to generate a target curve of the water flow of each section of the secondary cooling zone.

5. The method for controlling production of oxygen-free copper casting according to claim 1, wherein: Step S5 includes: S51: obtaining a measurement time when the billet surface temperature measurement data is collected, and calculating a current position of the billet downstream of the secondary cooling zone based on the billet surface temperature measurement data according to the target curve of the drawing speed and the measurement time; S52: Calculating the theoretical surface temperature of the slab at the current position according to the target curve group; S53: Subtract the theoretical surface temperature of the ingot from the measured surface temperature data of the ingot to obtain the temperature deviation.

6. The method for controlling production of oxygen-free copper casting according to claim 5, characterized in that: Step S52 includes: S521: extracting the mold cooling intensity target curve and the water flow target curves for each section of the secondary cooling from the target curve group; S522: Calculating the surface temperature of the cast strand at the mold outlet according to the mold cooling intensity target curve and the current position of the cast strand; S523: Calculate the temperature change of the billet in the secondary cooling zone section by section based on the billet surface temperature at the crystallizer outlet and the water flow target curve of each section of the secondary cooling to obtain the theoretical billet surface temperature at the current position.

7. The method for controlling production of oxygen-free copper casting according to claim 1, wherein: Step S6 includes: S61: Determine the correction strategy for the casting speed, mold cooling intensity, and water flow rate in each section of secondary cooling during the recovery phase; S62: Based on the correction strategy and the temperature deviation, a correction amount for the drawing speed, a correction amount for the mold cooling intensity, and a correction amount for the water flow rate in each section of the secondary cooling in the recovery phase are calculated; S63: The drawing speed correction amount, the mold cooling intensity correction amount and the water flow correction amount of each section of secondary cooling are respectively superimposed on the target curves of the drawing speed, the mold cooling intensity and the water flow of each section of secondary cooling to obtain the corrected target curve group, and the corrected target curve group is used for production.

8. An oxygen-free copper casting production control system, characterized in that: In the steps of the method according to any one of claims 1 to 7, the system comprises: Parking information acquisition module: obtains the unplanned parking duration and cooling conditions during parking; A slab state prediction module: based on the unplanned stop duration and the cooling conditions, predicts the temperature distribution and solidification state of the slab in the crystallizer and the secondary cooling zone at the end of the stop, and obtains slab state prediction information; Target curve generation module: generates target curves for the drawing speed, mold cooling intensity, and water flow rate in each section of secondary cooling in the recovery phase according to the predicted information of the ingot state, forming a target curve group; Temperature data acquisition module: during the process of gradually increasing the drawing speed, collecting the surface temperature of the billet downstream of the secondary cooling zone to obtain billet surface temperature measurement data; Temperature deviation calculation module: compares the measured surface temperature data of the billet with the theoretical surface temperature of the billet at the current position calculated based on the target curve of the drawing speed to obtain the temperature deviation; Parameter correction control module: Based on the temperature deviation, the target curves of the drawing speed, the cooling intensity of the crystallizer and the water flow rate of each section of the secondary cooling are corrected to obtain a corrected target curve group, and the corrected target curve group is used for production.

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