A method for online monitoring of the thickness of solid-liquid slag film near the meniscus of a crystallizer

Abstract

The present invention provides a method for online monitoring of the thickness of the solid-liquid slag film near the meniscus of a crystallizer, and belongs to the field of continuous casting production quality control in the iron and steel metallurgical industry. The present invention establishes a two-dimensional model of initial solidification and slag penetration based on finite element simulation, captures the changes in physical quantities such as the transient crystallizer wall temperature, heat flux density, and billet shell surface temperature near the meniscus, and predicts the thickness of the solid-liquid slag film near the meniscus by direct calculation. The theoretical model guides the arrangement of circumferential temperature sensors near the meniscus of an actual continuous casting crystallizer, and after obtaining the temperature signal, it is imported into the inverse calculation module to obtain the heat flux data, and then enters the continuous casting billet solidification calculation module, and finally the solid-liquid slag film thickness prediction module, thereby reflecting the protective slag thickness near the circumferential meniscus of the crystallizer online. The direct calculation and inverse calculation steps are shown in the figure. The present invention has a high industrial application prospect, and can realize online monitoring of the solidified billet shell and protective slag film conditions near the circumferential meniscus of the crystallizer.

Description

Technical Field

[0001] The invention belongs to the field of continuous casting production quality control in the iron and steel metallurgical industry, and in particular relates to a method for online monitoring the thickness of a solid-liquid slag film near a meniscus of a crystallizer. Background Art

[0002] The quality of the primary ingot inside the crystallizer is jointly determined by the flow and solidification of molten steel, lubrication of protective slag, vibration of the crystallizer, and heat transfer between molten steel and the crystallizer. If the molten steel level fluctuates too violently, the ingot will roll and affect the thickness of the solid / liquid slag film. However, if the molten steel flows too calmly, it is not conducive to the absorption of floating non-metallic slag inclusions by the protective slag and the melting of the powder slag layer into liquid slag. On the other hand, the lubrication of the protective slag is also an important factor affecting the smooth operation of continuous casting. If the liquid slag film is too thick, the dynamic pressure inside the liquid slag channel will increase due to the vibration of the crystallizer, the push and pull of the solid slag ring, and the reciprocating motion of the initial solidified ingot shell, which will cause the vibration mark of the primary ingot shell to deepen. The uneven distribution of liquid slag around the crystallizer induces the non-uniform growth of the primary solidified ingot shell. If the liquid slag film is too thin, it is easy to cause the ingot shell to stick to the crystallizer. If it is not controlled in time, it will cause bonding and steel leakage. If the solid slag film is too thick, the thermal resistance between the crystallizer and the molten steel will increase, which will reduce the thickness of the billet shell at the outlet of the crystallizer. In the top bending straightening area, due to the static pressure of the molten steel, the bulging deformation of the billet will increase. Therefore, online monitoring of the solid-liquid slag film thickness of the crystallizer is of great significance to the quality of the billet and the smooth operation of the continuous casting process.

[0003] At present, there are many relevant technical patents and papers on the technology of online monitoring of ingot quality, but the development of detection technology for online monitoring of the initial solidification of ingots near the meniscus and the lubrication behavior of protective slag is still scarce.

[0004] Chinese patent CN201410485613.9 discloses a method for detecting the liquid level of molten steel and the thickness of the protective slag layer in a crystallizer. This method installs two rows of thermocouples near the hot surface of the crystallizer along the height direction of the crystallizer wall, inputs the temperature signal collected by the thermocouples into the heat flux density inversion module, and obtains the heat flux density data at different heights. Then, the heat flux density is subjected to power spectrum density analysis to obtain the frequency-power spectrum density diagram of the heat flux density at different heights of the hot surface of the crystallizer, and finally, the frequency-power spectrum density diagram of the heat flux density at different heights of the hot surface of the crystallizer is synthesized into a position-frequency-power spectrum density cloud diagram by linear interpolation, and the average distance between the first peak and the second peak is found, which is the thickness of the protective slag layer above the molten steel level, and the first peak is the molten steel level. However, this method cannot simulate the influence of molten steel flow, and only two rows of thermocouples cannot reflect the molten steel level and the thickness and uniformity of the slag channel below the meniscus in the circumferential direction of the crystallizer, and the arrangement of the circumferential thermocouples of the crystallizer is not disclosed.

[0005] Chinese patent CN201610390708.1 discloses a method for testing the thickness of the liquid slag film in a continuous casting crystallizer. The research method is the same as that of Chinese patent CN201410485613.9. This method requires measuring the thickness of the overall protective slag film between the hot surface of the crystallizer and the solidified shell, and then using the thickness of the overall slag film minus the thickness of the liquid slag film to obtain the thickness of the solid slag film. Similarly, this method does not take into account the arrangement of the circumferential thermocouples of the crystallizer.

[0006] The present invention aims to solve the problem that complex solidification heat transfer, molten steel flow and solute transport occur near the meniscus of the continuous casting crystallizer, which seriously affects the quality of the ingot. In addition, current research lacks online monitoring of the meniscus of the crystallizer, and cannot reflect the quality and lubrication condition of the primary solidified ingot shell at the meniscus. A method for online monitoring of the solid-liquid slag film thickness near the meniscus of the crystallizer is proposed. Summary of the invention

[0007] In view of the inadequacy of online monitoring technology for the initial meniscus of the crystallizer, the present invention provides a method for online monitoring the thickness of the solid-liquid slag film near the meniscus of the crystallizer, with the purpose of realizing online monitoring of the quality of the initial solidified shell of the ingot inside the crystallizer and the lubrication behavior of the protective slag.

[0008] In order to achieve the above object, the technical solution adopted by the present invention is:

[0009] A method for online monitoring of the thickness of a solid-liquid slag film near a meniscus of a crystallizer comprises the following steps:

[0010] Step 1: According to the pouring parameters and the thermophysical parameters of the steel grade, a proportional finite element model is established using the finite element software ANSYS to simulate the initial solidification and slag infiltration behavior near the meniscus of the continuous casting crystallizer. The finite element model is a crystallizer initial solidification and slag infiltration model, and the finite element model includes a crystallizer copper plate, an immersion nozzle, molten steel, protective slag and air. The initial meniscus is the area where the molten steel forms an initial solidified shell.

[0011] Step 2: Establish a geometric model according to the casting machine size and use ANSYS ICEM to divide the structural mesh.

[0012] Step 3: The structured grid obtained in step 2 is converted into an unstructured grid and then imported into ANSYS Fluent. The multiphase flow model (VOF) is used to solve the single-component continuity, momentum and energy equations to predict the interface distribution of the steel-slag-gas three-phase in the fluid domain.

[0013] Step 4: After inputting the required physical parameters and boundary conditions based on step 3, select the solver for solution.

[0014] Step 5: After the finite element model calculation is stable, set the monitoring points, monitoring time and monitoring time step for the finite element model according to step 4 to capture the transient changes of the mold wall temperature, heat flux density, shell surface temperature, solid-liquid slag film thickness or other physical quantities in real time. Among them, the monitoring points set in the finite element model are equivalent to temperature sensors.

[0015] The monitoring time step is 0.0001s; the monitoring time is 1s; the monitoring point setting range is from the initial meniscus to 100mm below, the distance between the monitoring points along the throwing direction is 5 to 20mm, and 1 or 2 rows are set in the thickness direction of the crystallizer wall. The farthest temperature sensor is 10 to 14mm away from the hot surface of the crystallizer.

[0016] Step 6: Based on the monitoring results obtained in step 5, use mapping software to plot the changes in the crystallizer wall temperature (copper plate temperature) from the meniscus to 100 mm below, heat flux, shell surface temperature, and solid / liquid slag film thickness, and verify the accuracy of the finite element model. The solid-liquid slag film thickness in the model is predicted by direct calculation to verify the feasibility of this method.

[0017] The forward calculation method is: directly bring the mold wall temperature, heat flux density, and shell surface temperature obtained in step 5 into the solid-liquid slag film thickness calculation module, and predict the solid-liquid slag film thickness in the finite element model to verify the feasibility of installing a temperature sensor near the meniscus.

[0018] Step 7: Based on step 6, the arrangement density of the temperature sensors is guided according to the temperature fluctuation of the crystallizer wall in the model, and the temperature sensors are arranged near the circumferential meniscus of the crystallizer to collect the temperature data of the crystallizer copper plate near the meniscus online.

[0019] Step 8: Input the copper plate temperature data obtained by the temperature sensor in step 7 into the heat flux density inverse calculation module to obtain the heat flux density data from the meniscus of the crystallizer to the copper plate 100 mm below along the billet drawing direction.

[0020] Step 9: Import the heat flux data obtained in step 8 into the continuous casting billet solidification calculation model to obtain the billet shell surface temperature, and finally import it into the online solid-liquid slag film thickness calculation module to realize online monitoring of the solid-liquid slag film thickness.

[0021] Furthermore, in step 6, the mathematical formula for predicting the thickness of the solid-liquid slag film by positive calculation is as follows:

[0022]

[0023] T m / s =T m +q int ×R int(2)

[0024]

[0025]

[0026]

[0027] In formulas (1) to (5), T fsol represents the solidification temperature of the mold slag, K; T m / s represents the cold surface temperature of the solid slag film, K; q s Represents the heat flux density inside the liquid slag film, W / m 2 ; R s represents the thermal resistance of the solid slag film, m 2 K / W; T m represents the temperature of the hot surface of the crystallizer, K; q int represents the heat flux density between the crystallizer copper plate and the solid slag film, where q s =q int , W / m 2 ; R int Represents the thermal resistance between the mold copper plate and the solid slag film, m 2 ·K / W; R s con represents the thermal resistance of the solid slag film, m 2 ·K / W; R s rad represents the radiation thermal resistance of the solid slag film, m 2 ·K / W; k s Represents the thermal conductivity of the solid slag film, W / m 2 K;d s represents the thickness of the solid slag film, mm; m represents the emissivity of the crystallizer; f represents the emissivity of the protective slag; s represents the extinction coefficient of the solid slag film, m -1 ; represents the Stefan-Boltzmann constant, W / m 2 ·K 4 ;m s Represents the refractive index of the solid slag film. The calculation formula for predicting the thickness of the liquid slag film is as follows:

[0028]

[0029]

[0030]

[0031]

[0032] In formulas (6) to (9), T fsol represents the solidification temperature of the mold slag, K; T srepresents the surface temperature of the solidified shell, K; q l Represents the heat flux density inside the liquid slag film, W / m 2 ; R l represents the thermal resistance of the liquid slag film, m 2 ·K / W; R l con represents the thermal resistance of the liquid slag film, m 2 ·K / W; R l rad represents the radiation thermal resistance of the liquid slag film, m 2 ·K / W; k l Represents the thermal conductivity of the liquid slag film, W / m 2 K;d l represents the thickness of the liquid slag film, mm; st represents the emissivity of the ingot; f represents the emissivity of the protective slag; l represents the extinction coefficient of the liquid slag film, m -1 ; represents the Stefan Boltzmann constant, W / m 2 ·K 4 ;m l Represents the refractive index of the liquid slag film.

[0033] Furthermore, in step 7, the installation position of the added temperature sensor is: perpendicular to the direction of the billet drawing, with a horizontal spacing of 150 to 300 mm. Along the direction of the billet drawing, the temperature sensor is installed from the initial meniscus of the crystallizer to 100 mm below, with an average spacing of 25 to 50 mm. In the thickness direction of the crystallizer, one or two temperature sensors are installed at the corresponding points of the temperature sensor perpendicular to the billet drawing direction, with the first temperature sensor being 8 to 13 mm away from the hot surface of the crystallizer, and the second temperature sensor being 5 to 7 mm away from the first temperature sensor.

[0034] Furthermore, in step 8, the back calculation step in the heat flux back calculation module is to input the initial calculation conditions and monitor the copper plate temperature. Start calculating the heat transfer of the crystallizer, and then determine whether the heat transfer calculation is completed. After the end, compare the calculated temperature with the measured copper plate temperature to determine whether the root mean square is less than 3K. If it does not meet the requirements, adjust the heat flow and recalculate until the root mean square is less than 3K. Finally, bring the heat flow result of the copper plate into the continuous casting billet solidification calculation model.

[0035] Furthermore, the following assumptions are made before establishing the continuous casting solidification calculation model in step 9:

[0036] (1) Only the heat transfer along the lateral direction of the casting is considered, while the heat transfer along the longitudinal direction of the casting is ignored. The solidification heat transfer of the casting is regarded as a two-dimensional nonlinear process.

[0037] Steady-state heat transfer behavior;

[0038] (2) Ignore the melting heat absorption of the protective slag above the meniscus;

[0039] (3) Ignore the shrinkage of the ingot due to solidification and the influence of the crystallizer vibration on it.

[0040] Based on the above assumptions, the control equation of the continuous casting billet solidification calculation model is established:

[0041]

[0042] Where, T steel represents the casting temperature, K; ρ steel Represents the density of steel, kg / m 3 ;c steel is the specific heat capacity of the ingot, J / (kg·K); steel is the thermal conductivity of the ingot, W / (m·K); Q sourse is the latent heat of solidification of molten steel, J / kg.

[0043] The above-mentioned method for online monitoring of the thickness of the solid-liquid slag film near the meniscus of the crystallizer is applicable to all continuous casting processes.

[0044] Beneficial effects of the present invention: The present invention targets the complex heat transfer, flow and mass transfer occurring inside the crystallizer, especially near the meniscus, where the quality and lubrication of the primary ingot seriously affect the quality of the continuous casting ingot and the smooth operation of the continuous casting production process. The proposed method explores the law and mechanism of the solidification of molten steel and the infiltration of protective slag near the meniscus based on the established finite element model, sets monitoring points to obtain the changes in the crystallizer copper plate temperature, heat flux density, surface temperature of the solidified ingot shell and protective slag thickness, and verifies the feasibility of arranging temperature sensors on the meniscus to conduct online monitoring of the initial ingot shell solidification and protective slag lubrication. Theory guides practice, and temperature sensors are arranged near the meniscus of the crystallizer to monitor the temperature of the crystallizer wall online. The method is easy to implement and maintain, has high control accuracy, and is green and environmentally friendly, providing a feasible way for online monitoring near the meniscus of continuous casting. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 Schematic diagram of finite element model meshing results and boundary conditions;

[0046] Figure 2 It is a schematic diagram of the arrangement of monitoring points in the finite element model;

[0047] Figure 3 This is the simulation result of the solid-liquid slag film thickness from the meniscus to 100 mm below;

[0048] Figure 4 The thickness of the solid-liquid slag film in the model is compared with the predicted results; Figure 4 (a) is the calculation and prediction results of the solid slag film model. Figure 4 (b) is the calculation and prediction results of the liquid slag film model;

[0049] Figure 5 This is a schematic diagram of the actual arrangement of temperature sensors from the meniscus of the copper plate of the slab crystallizer to 100mm below;

[0050] Figure 6 This is the flow chart for predicting the solid-liquid slag film 100mm below the meniscus.

[0051] Figure 7 The heat flux density and solid-liquid slag layer thickness results are calculated after actually detecting the copper plate temperature. DETAILED DESCRIPTION

[0052] The embodiments of the present invention are further described in detail below with reference to the accompanying drawings.

[0053] Example 1

[0054] The first step is to establish a finite element model of the initial solidification of molten steel and the penetration of protective slag in the crystallizer

[0055] The meshing results and boundary condition application diagram of the finite element model are shown in the figure below. Figure 1 shown. Figure 1 The number of grids in the finite element model is 140,000, the vibration mode of the crystallizer is sinusoidal vibration, and the heat transfer coefficient of the cold surface of the crystallizer is 28000W / (m 2 ·K).

[0056] Step 2: Select the governing equation

[0057] The multiphase flow model (VOF) is used to solve the single component continuity, momentum and energy equations.

[0058] Step 3: Casting parameters and physical parameters

[0059] The model size, boundary conditions and physical parameters are different for different continuous casting parameters and casting steel types. The casting steel type of the model is low carbon steel, the cross section is 1300×247mm, the casting speed is 1.45m / min, the crystallizer amplitude is 3mm, the vibration frequency is 182cpm, and the thermal conductivity of the steel (k steel ), thermal conductivity of mold slag (k slag ) and viscosity ( slag ) is a function related to the fluid temperature, as shown in formulas (1)-(3).

[0060] k steel =13.86+0.01113×(T-273.15) (1)

[0061]

[0062]

[0063] T is temperature (K), ksteel is the thermal conductivity of steel (W / (m·K)), k slag is the thermal conductivity of the mold slag (W / (m·K)), k slag is the viscosity of the mold slag (kg / (m·s)).

[0064] Step 4: Solution process

[0065] ANSYS Fluent 20.0 is used to solve the transient temperature, pressure and velocity fields. The transient solution adopts a pressure-based separation algorithm, namely, pressure implicit operator splitting (PISO).

[0066] Step 5: Set detection points on the finite element model

[0067] After the model calculation is stable, set monitoring points on the finite element model, as follows: Figure 2 As shown, the copper plate temperature, heat flux, solidified shell surface temperature and protective slag film thickness are monitored. The monitoring time is 1s, the monitoring time step is 0.0001s, the monitoring point setting range is 100mm below the initial meniscus (L3 in the figure), the distance between each monitoring point along the billet drawing direction is 5mm (L1 in the figure), and the thickness direction of the crystallizer wall is set to 5mm (L2 in the figure), with a total of 2 columns.

[0068] Step 6: Extract monitoring result data

[0069] Extract monitoring data, simulation results of solid-liquid slag film thickness from the meniscus to 100mm below, as shown below Figure 3 The purpose is to verify the accuracy of the finite element model. In the actual continuous casting process, the temperature change of the copper plate can only be monitored by the temperature sensor. The monitoring points in the model are analogous to the temperature sensor of the copper plate, and the heat flux density and other data are obtained by calculation.

[0070] Step 7. Simulation and prediction results of mold slag film thickness

[0071] According to the positive calculation, the prediction results of the solid-liquid slag film in the model are obtained, such as Figure 4 The black circles in the figure represent the calculation results of the finite element model, and the black triangles represent the prediction results using the solid-liquid slag film calculation model, which shows the feasibility of installing temperature sensors.

[0072] Step 8: Analyze the temperature distribution of the copper plate of the crystallizer

[0073] In the simulation results, the monitoring point is 100 mm below the initial meniscus, and the temperatures of the copper plates of the crystallizer at intervals of 25 mm along the billet drawing direction are 536, 559, 557, 549, and 540 K, respectively. This can guide the arrangement of temperature sensors near the actual meniscus of the crystallizer. The arrangement principle should not affect the heat transfer between the crystallizer and the solidified shell, and can fully and finely reflect the temperature distribution of the copper plates of the crystallizer.

[0074] Step 9: Design the arrangement of temperature sensors near the meniscus of the crystallizer

[0075] The specific arrangement of temperature sensors is as follows Figure 5 As shown. Along the billet drawing direction, the average installation spacing of the temperature sensors from the initial meniscus of the crystallizer to 100mm below (L10 in the figure) is 50mm (L6 in the figure). Perpendicular to the billet drawing direction, the spacing is 200mm (L15 in the figure). In the thickness direction of the crystallizer, two temperature sensors are installed at the corresponding points of the temperature sensors perpendicular to the billet drawing direction. The first temperature sensor is 10mm away from the hot surface of the crystallizer (L7 in the figure), and the second temperature sensor is 5mm away from the first temperature sensor (L8 in the figure). Step 10. Calculate the heat flux density

[0076] The temperature data collected by the crystallizer temperature sensor is input into the back calculation module to obtain the heat flux density data at different positions of the crystallizer copper plate.

[0077] Step 11: Online calculation of solid-liquid slag film thickness

[0078] The heat flux density is imported into the continuous casting solidification calculation model to obtain the data such as the surface temperature of the billet shell, and then imported into the solid-liquid slag film calculation module to obtain the solid-liquid slag film thickness. In this way, the online monitoring of the solid-liquid slag film thickness near the circumferential meniscus of the crystallizer is realized.

[0079] Step 12: Prediction process of solid-liquid slag film 100mm below the meniscus

[0080] The prediction process of solid-liquid slag film 100mm below the meniscus is as follows Figure 6 As shown, the figure includes the calculation process of the forward calculation and reverse calculation modules.

[0081] Step 13: Monitoring data 100 mm below the meniscus

[0082] According to the copper plate temperature obtained by actual crystallizer monitoring, the prediction process in step 12 is used to calculate the heat flux density from the meniscus to 100 mm below, the surface temperature of the billet shell, the thickness of the liquid slag film and the thickness of the solid slag film through the module, such as Figure 7 shown.

[0083] The above-described embodiments merely express the implementation methods of the present invention, but they cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A method for online monitoring of the thickness of the solid-liquid slag film near the meniscus of a crystallizer, characterized in that: The following steps are involved: Step 1: Based on the continuous casting process parameters, the physical properties of the casting steel and the protective slag, a proportional finite element model is established using the finite element software ANSYS to simulate the initial solidification and slag penetration behavior near the meniscus of the continuous casting crystallizer, where the initial meniscus is the area where the molten steel forms the initial solidified shell; Step 2: Establish a geometric model according to the casting machine size and divide the structural mesh using ANSYS ICEM; Step 3: The structured grid divided in step 2 is converted into an unstructured grid and then imported into ANSYS Fluent. The multiphase flow model VOF is used to solve the single-component continuity, momentum and energy equations to predict the interface distribution of the steel-slag-gas three-phase in the fluid domain; Step 4: After inputting the required physical parameters and boundary conditions based on step 3, select the solver to solve; Step 5: After the finite element model calculation is stable, set the monitoring points, monitoring time and monitoring time step for the finite element model according to step 4, and capture the transient changes of the crystallizer wall temperature, heat flux density, billet shell surface temperature and solid-liquid slag film thickness in real time; the monitoring points set in the finite element model are equivalent to temperature sensors; Step 6: Based on the monitoring results obtained in step 5, use mapping software to draw the changes in the crystallizer wall temperature from the meniscus to the lower 100 mm, the heat flux density, the shell surface temperature, and the solid / liquid slag film thickness, and verify the accuracy of the finite element model; predict the solid-liquid slag film thickness in the model through forward calculation to verify the feasibility of the method; Step 7: Based on step 6, the arrangement density of the temperature sensors is guided according to the temperature fluctuation of the crystallizer wall in the model, and the temperature sensors are arranged near the circumferential meniscus of the crystallizer to collect the temperature data of the crystallizer copper plate near the meniscus online; Step 8: Input the copper plate temperature data obtained by the temperature sensor in step 7 into the heat flux density back-calculation module to obtain the heat flux density data from the meniscus of the crystallizer to the copper plate 100 mm below along the billet drawing direction; Step 9: Import the heat flux data obtained in step 8 into the continuous casting billet solidification calculation model to obtain the billet shell surface temperature, and finally import it into the online solid-liquid slag film thickness calculation module to realize online monitoring of the solid-liquid slag film thickness.

2. The method for online monitoring of the thickness of the solid-liquid slag film near the meniscus of a crystallizer according to claim 1, characterized in that: The method comprises the following steps. In step 7, the installation position of the added temperature sensor is: perpendicular to the billet-pulling direction, with a horizontal spacing of 150 to 300 mm; along the billet-pulling direction, the temperature sensor is installed from the initial meniscus of the crystallizer to 100 mm below, with an average spacing of 25 to 50 mm; in the thickness direction of the crystallizer, one or two temperature sensors are installed at the corresponding points of the temperature sensor perpendicular to the billet-pulling direction, the first temperature sensor is 8 to 13 mm away from the hot surface of the crystallizer, and the second temperature sensor is 5 to 7 mm away from the first temperature sensor.

3. The method for online monitoring of the thickness of the solid-liquid slag film near the meniscus of a crystallizer according to claim 1, characterized in that: The method comprises the following steps: in step 5, the monitoring time step is 0.0001s; the monitoring time is 1s; the monitoring point setting range is from the initial meniscus to 100mm below, the distance between the monitoring points along the throwing direction is 5-20mm, and 1 or 2 rows are set in the thickness direction of the crystallizer wall, and the farthest temperature sensor is 10-14mm away from the hot surface of the crystallizer.

4. The method for online monitoring of the thickness of the solid-liquid slag film near the meniscus of a crystallizer according to claim 1, characterized in that: In the step 8, the back calculation step in the heat flux back calculation module is to input the initial calculation conditions and monitor the copper plate temperature; start calculating the heat transfer of the crystallizer, and then determine whether the heat transfer calculation is completed; after the end, compare the calculated temperature with the measured copper plate temperature to determine whether the root mean square is less than 3K. If not, adjust the heat flux and recalculate until the root mean square is less than 3K; finally, bring the heat flux result of the copper plate into the continuous casting billet solidification calculation model.

5. A method for online monitoring of the thickness of the solid-liquid slag film near the meniscus of a crystallizer according to any one of claims 1 to 4, characterized in that: The method for online monitoring of the thickness of the solid-liquid slag film near the meniscus of the crystallizer is applicable to all continuous casting productions.

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