Method and system for predicting dissolution time of inclusions in slag

Abstract

The invention discloses a method and system for predicting dissolution time of inclusions in slag, and the method comprises the following steps: (1) preparing an experimental material: preparing experimental slag according to a component proportion, and pre-melting the experimental slag by using high-temperature equipment; selecting aluminum oxide, calcium aluminate and magnesium aluminate spinel particles, and grinding to the same size; (2) high-temperature confocal experiment: putting the inclusions and the pre-molten slag into a high-temperature confocal microscope according to a certain placement method, and heating to observe and record the dissolution process of the inclusions in the molten slag; (3) experimental data processing: calculating dissolution time and sizes of inclusions at different moments according to experimental records; and (4) establishing a prediction model: fitting experimental data and establishing a prediction model for dissolution of different inclusions according to a data fitting result, so that guidance can be provided for adjusting and designing refining slag components and improving the refining efficiency.

Description

Technical Field

[0001] The invention belongs to the technical field of iron and steel metallurgy, and in particular relates to a method and a system for predicting the dissolution time of inclusions in slag. Background Art

[0002] Non-metallic inclusions in steel are one of the main factors affecting steel cleanliness, and removing inclusions in steel is one of the difficulties in clean steel production. Since refined slag has an adsorption effect, inclusions will be adsorbed by the refined slag when they float to the steel-slag interface and thus removed. Therefore, through appropriate refining processes and the use of appropriate refined slag systems, the composition and quantity of non-metallic inclusions in molten steel can be effectively controlled.

[0003] High temperature confocal microscopy can observe physical and chemical phenomena in situ under high temperature conditions. In the field of inclusion control, it is mainly used to study the dissolution, collision and growth of inclusions. By observing the adsorption process of inclusions on refined slag in situ with high temperature confocal microscopy, the dissolution rate and principle of inclusions in slag can be clarified, which is helpful to adjust and design the composition of refined slag and provide guidance for improving refining efficiency.

[0004] The dissolution process of inclusions in slag is affected by many factors. The dissolution rate and complete dissolution time of inclusion particles in refined slag are often characterized by the saturation concentration difference of inclusions in the slag and the viscosity of the slag (ΔC / η). As the ΔC / η value increases, the dissolution time of inclusions decreases. The larger the saturation concentration difference of inclusions in the slag, the smaller the viscosity, and the more conducive to the dissolution of inclusions in the slag. However, ΔC / η does not take into account the effect of inclusion size on its dissolution, and it is difficult to use ΔC / η to accurately characterize the dissolution process of all inclusions. The concepts of inclusion capacity (Zh) and dimensionless dissolution rate (Ry) in refined slag characterize the dissolution process of inclusions in slag, which not only considers the physical and chemical properties of the slag, but also the influence of inclusion size. In addition, both Zh number and Ry number are dimensionless numbers, which can more accurately assess the degree of physical phenomena.

[0005] During the refining process, when aluminum is used for deoxidation, the deoxidation product is alumina inclusions, the refractory in the ladle is corroded by the molten steel to form magnesia-aluminate spinel inclusions, and calcium treatment produces calcium aluminate inclusions, so there may be three types of inclusions in the steel: alumina, magnesia-aluminate spinel and calcium aluminate. Therefore, it is necessary to establish a model and method for predicting the dissolution time of alumina, calcium aluminate and magnesia-aluminate spinel inclusions in the slag based on the concepts of inclusion capacity (Zh) and dimensionless dissolution rate (Ry) in the refined slag. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention proposes a method and system for predicting the dissolution time of inclusions in molten slag. By establishing a prediction model for the dissolution of inclusions of different sizes and types in slags of different compositions, it can provide guidance for adjusting and designing the composition of refined slag and improving refining efficiency.

[0007] To achieve the above object, the present invention provides the following solutions:

[0008] A method for predicting the dissolution time of inclusions in slag comprises the following steps:

[0009] Obtaining inclusions to be predicted in the pre-melted slag, wherein the pre-melted slag comprises: preparing experimental slag according to a component ratio, and pre-melting the experimental slag using a preset high-temperature device, and the inclusions include: alumina, calcium aluminate and magnesium aluminum spinel particles;

[0010] Placing the inclusions and the pre-molten slag into a preset high-temperature confocal microscope according to a predetermined placement method, obtaining the dissolution rate of the inclusions and the size of the inclusions at different times, and performing data fitting;

[0011] According to the data fitting results, a prediction model for the dissolution of different inclusions is established;

[0012] The inclusions to be predicted are input into the prediction model for the dissolution of different inclusions to obtain the dissolution time of inclusions of different sizes and types in slags of different components.

[0013] Preferably, the experimental slag basicity CaO / SiO2 is 5.0, CaO / Al2O3 is 1.4, the composition is prepared based on the refined slag used in the refining process of the current production process of aluminum deoxidized steel, and 0%, 3% and 6% MgO content are added to the slag.

[0014] Preferably, placing the inclusions and the pre-molten slag into a preset high-temperature confocal microscope according to a predetermined placement method comprises:

[0015] The inclusion particles are placed on the surface of the pre-melted slag in a Pt crucible and heated in an argon atmosphere. The heating temperature is measured and controlled by a thermocouple. The heating temperature is 1500°C. During the heating process, it is first heated to 50°C below the heating temperature and then raised to the heating temperature.

[0016] Preferably, obtaining the dissolution rate of the inclusions and the sizes of the inclusions at different times comprises:

[0017] ImageJ was used to measure the area of ​​inclusion particles at different times during the dissolution process, and the equivalent circular diameter of the particles was calculated based on the particle area;

[0018] The dissolution rate of the inclusions is calculated based on the dissolution time and equivalent diameter of the inclusions, wherein the dissolution time includes: the timing starts when the temperature in the high-temperature confocal microscope reaches the heating temperature, and the timing ends when the inclusions are completely dissolved.

[0019] Preferably, inputting the inclusions to be predicted into the prediction model for the dissolution of different inclusions to obtain the time for the inclusions of different sizes and types to dissolve in the slag of different components comprises:

[0020] The inclusion capacity Zh and dimensionless dissolution rate Ry in refined slag are used to characterize the solubility and dissolution rate of inclusions in refined slag and the relationship between the physicochemical properties of slag and the size of inclusions.

[0021] According to the data fitting results, the exponential relationship between Zh number and Ry number is obtained;

[0022] Using the exponential relationship between Zh number and Ry number, the relationship between MgO content in refined slag and fitting parameters was obtained;

[0023] According to the relationship between the MgO content in the refined slag and the fitting parameters, the relationship between the MgO content in the slag and the Ry number is obtained;

[0024] According to the relationship between MgO content and Ry number in slag, the dissolution time of various inclusions of different sizes in refined slag with different MgO concentrations is predicted.

[0025] Preferably, the inclusion capacity Zh and dimensionless dissolution rate Ry in the refined slag are used to respectively characterize the solubility and dissolution rate of inclusions in the refined slag and the relationship between the physicochemical properties of the slag and the size of inclusions, including:

[0026]

[0027]

[0028] Where g is the acceleration due to gravity, m / s 2 ρ slag Slag is the density of refined slag, kg / m 3 ; C saturation is the saturated mass of inclusions in the slag, %; C is the mass fraction of inclusions in the refined slag, %; ν slag is the kinematic viscosity of inclusions in refined slag, m 2 / s; η slag is the dynamic viscosity, kg / (m·s); d p,0 is the initial diameter of the inclusion particles, m; is the inclusion dissolution rate, m 3 / s.

[0029] Preferably, the exponential relationship between the Zh number and the Ry number includes:

[0030] Ry=a·Zh n ;

[0031] Where a is the fitting coefficient and n is the fitting index.

[0032] Preferably, the relationship between the MgO content in the slag and the Ry number includes:

[0033]

[0034] Where τ is the time for inclusions to be completely dissolved in the refined slag, s; r is the initial radius of the inclusion, m.

[0035] The present invention also discloses a prediction system for the dissolution time of inclusions in slag, comprising: an acquisition module, a calculation module, a construction module and a prediction module;

[0036] The acquisition module is used to acquire inclusions to be predicted in the pre-melted slag, wherein the pre-melted slag comprises: preparing experimental slag according to a component ratio, and pre-melting the experimental slag using a preset high-temperature device, and the inclusions include: alumina, calcium aluminate and magnesium aluminum spinel particles;

[0037] The calculation module is used for placing the inclusions and the pre-molten slag into a preset high-temperature confocal microscope according to a predetermined placement method, obtaining the dissolution rate of the inclusions and the size of the inclusions at different times, and performing data fitting;

[0038] The building module is used to establish a prediction model for the dissolution of different inclusions based on the data fitting results;

[0039] The prediction module is used to input the inclusions to be predicted into the prediction model for the dissolution of different inclusions, and obtain the time for the inclusions of different sizes and types to dissolve in slags of different components.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] The method of the present invention provides a new research method for exploring the dissolution of different types of inclusions in slag. (1) The method of the present invention uses a high-temperature confocal device to design and simulate the dissolution experiment of various inclusions in slag, and observes the dissolution process of inclusions in slag in situ; (2) The method of the present invention uses the concepts of inclusion capacity (Zh) and dimensionless dissolution rate (Ry) in refined slag to characterize the solubility and dissolution rate of inclusions in refined slag and the relationship between the physicochemical properties of slag and the size of inclusions; (3) The method of the present invention fits the experimental data to establish a prediction model for the dissolution of various inclusions of different sizes in different slags. The present invention can provide guidance for adjusting and designing the composition of refined slag and improving refining efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0043] Figure 1 A schematic diagram of a high temperature confocal experiment placement method according to an embodiment of the present invention;

[0044] Figure 2 A schematic diagram of a temperature increase system for a high temperature confocal experiment according to an embodiment of the present invention;

[0045] Figure 3 A schematic diagram of the dissolution process of aluminum oxide particles in a high temperature confocal experiment according to an embodiment of the present invention;

[0046] Figure 4 Schematic diagrams of the dissolution process of inclusion particles in a high-temperature confocal experiment of an embodiment of the present invention, wherein (a) is a schematic diagram of the dissolution process of Al2O3 particles, (b) is a schematic diagram of the dissolution process of CaAl4O7 particles, and (c) is a schematic diagram of the dissolution process of MgAl2O4 particles;

[0047] Figure 5 Schematic diagram of the relationship between the Zh number and the Ry number of inclusions in the high temperature confocal experiment of the embodiment of the present invention, wherein (a) is a schematic diagram of the relationship between the Zh number and the Ry number of Al2O3, (b) is a schematic diagram of the relationship between the Zh number and the Ry number of CaAl4O7, and (c) is a schematic diagram of the relationship between the Zh number and the Ry number of MgAl2O4;

[0048] Figure 6 Schematic diagram of the relationship between the MgO content in the slag and the fitting coefficient (a) and the fitting index (n) according to an embodiment of the present invention, wherein (a) is a schematic diagram of the MgO content in the slag and the fitting coefficient (a), and (b) is a schematic diagram of the MgO content in the slag and the fitting index (n);

[0049] Figure 7 Schematic diagrams of the prediction results of dimensionless dissolution rate of inclusions with a diameter of 1-1000 μm according to an embodiment of the present invention, wherein (a) is a schematic diagram of the prediction results of dimensionless dissolution rate of Al2O3, (b) is a schematic diagram of the prediction results of dimensionless dissolution rate of CaAl4O7, and (c) is a schematic diagram of the prediction results of dimensionless dissolution rate of MgAl2O4;

[0050] Figure 8Schematic diagrams of the prediction results of the dissolution time of inclusions with a diameter of 1-1000 μm according to an embodiment of the present invention, wherein (a) is a schematic diagram of the prediction results of the dissolution time of Al2O3, (b) is a schematic diagram of the prediction results of the dissolution time of CaAl4O7, and (c) is a schematic diagram of the prediction results of the dissolution time of MgAl2O4;

[0051] Fig. 9 A schematic flow chart of a method for predicting the dissolution time of inclusions in slag according to an embodiment of the present invention;

[0052] Fig.10 Schematic diagram of studying the dissolution of alumina, calcium aluminate and magnesium aluminate spinel inclusions in slags with different MgO contents according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0055] Embodiment 1

[0056] like Fig. 9 As shown, the present invention provides a method for predicting the dissolution time of inclusions in slag, comprising the following steps:

[0057] Obtaining inclusions to be predicted in the pre-melted slag, wherein the pre-melted slag comprises: preparing experimental slag according to a component ratio, and pre-melting the experimental slag using a preset high-temperature device, and the inclusions include: alumina, calcium aluminate and magnesium aluminum spinel particles;

[0058] Placing inclusions and pre-melted slag into a preset high-temperature confocal microscope according to a predetermined placement method, obtaining the dissolution rate of the inclusions and the size of the inclusions at different times, and performing data fitting;

[0059] According to the data fitting results, a prediction model for the dissolution of different inclusions is established;

[0060] The inclusions to be predicted are input into the prediction model of different inclusion dissolution to obtain the dissolution time of inclusions of different sizes and types in slags of different compositions.

[0061] The dissolution of alumina, calcium aluminate and magnesia aluminate spinel inclusions in slags with MgO contents of 0%, 3% and 6% was studied. Fig.10 As shown, the method comprises the following steps:

[0062] S1: Experimental slag and inclusion preparation:

[0063] The slag basicity (CaO / SiO2) used in the experiment is 5.0, CaO / Al2O3 is 1.4, and its composition is designed based on the refined slag used in the current production process of aluminum deoxidized steel. 0%, 3% and 6% MgO content are added to the slag. The slag composition is shown in Table 1. According to the designed refined slag composition, a sufficient amount of high-purity powders of silicon oxide (≥99.5%), aluminum oxide (≥99.5%), calcium oxide (≥98.0%) and magnesium oxide (≥98.5%) are weighed, and the powder is fully ground and rolled in an agate mortar to ensure the homogenization of the refined slag composition. Then a tablet press is used to press the powder into discs. Insert the disc into the platinum crucible Finally, the platinum crucible containing the slag powder was placed in the high-temperature furnace of the high-temperature confocal microscope for pre-melting at a temperature of 1550°C. Alumina, calcium aluminate and magnesium aluminate spinel particles were selected and crushed into small particles using a mortar. Sandpaper was used to grind the inclusion particles into a nearly spherical shape with a diameter of 500 μm to ensure experimental consistency.

[0064] Table 1 Experimental slag composition

[0065]

[0066] S2: High temperature confocal experiment:

[0067] Nearly spherical inclusion particles are placed on the surface of pre-melted slag in a Pt crucible, and then the Pt crucible containing the pre-melted slag and inclusions is placed on a thermocouple holder in a high-temperature confocal high-temperature furnace, such as Figure 1 As shown. An Al2O3 gasket is placed between the platinum crucible and the thermocouple holder to prevent chemical reactions between the platinum crucible and the thermocouple holder under high temperature conditions, causing the two to stick together. After placing the experimental sample in the high-temperature confocal high-temperature furnace, the high-temperature furnace must be evacuated and argon-blown to ensure that the gas in the high-temperature furnace can be completely evacuated. Turn on the argon blowing device during the experiment to ensure that the experiment is always carried out in an inert atmosphere.

[0068] Focus the objective lens on the surface of the refined slag, and find the inclusion particles by adjusting the direction operating lever and the fine focus screw button. Then heat it to 50°C below the experimental temperature at a faster heating rate. Using the high-temperature confocal equipment model VL2000DX-SVF18SP, rapid heating can be achieved, and the maximum heating rate does not exceed 1000°C / min, which can achieve in-situ observation of the experimental sample at high temperature; then reduce the heating rate and heat it to the experimental temperature. This operation is to prevent the influence of temperature overshoot during the heating process and the experimental error caused by the premature dissolution of the refined slag. The heating system is as follows Figure 2 As shown in the figure. When the temperature in the high temperature furnace reaches the experimental temperature, the timing starts, and when the inclusions are completely dissolved, the timing ends. The melting process of Al2O3 inclusions with a diameter of 500μm is shown in the figure. Figure 3 As shown in Figure 2, it completely melted at 174.47s. To improve reliability, each experiment was repeated twice and the results are summarized in Table 2.

[0069] Table 2 Experimental results of inclusion dissolution in slag

[0070]

[0071]

[0072] S3: Experimental data processing:

[0073] Assuming that the inclusion particles remain spherical during the dissolution process, ImageJ was used to measure the area of ​​the inclusion particles at different times during the dissolution process, and the equivalent circular diameter of the particles was calculated based on the particle area. The dissolution rate of the inclusions was calculated based on the dissolution time and equivalent diameter of the inclusions. The volume changes of Al2O3, CaAl4O7 and MgAl2O4 inclusions with time in slags with MgO contents of 0%, 3% and 6% are shown in Figure 2. Figure 4 As shown, as the dissolution proceeds, inclusion particles with a diameter of about 500 μm gradually disappear in the slag.

[0074] S4: Build a prediction model:

[0075] The viscosity (η) and the saturation concentration difference (ΔC) of the refined slag with MgO content of 0%-6% were calculated using FactSage 8.2 software, and the slag density (ρ) was calculated using the Mills model. The physical and chemical properties of the three experimental slags are shown in Table 3.

[0076] Table 3 Composition and physicochemical properties of experimental slag

[0077]

[0078] The concepts of inclusion capacity (Zh) and dimensionless dissolution rate (Ry) in refined slag are used to characterize the dissolution process of inclusions in slag. Their definitions are respectively as follows:

[0079]

[0080]

[0081] Where g is the acceleration due to gravity, m / s 2 ρ slag Slag is the density of refined slag, kg / m 3 ; C saturation is the saturated mass of inclusions in the slag, %; C is the mass fraction of inclusions in the refined slag, %; ν slag is the kinematic viscosity of inclusions in refined slag, m 2 / s; η slag is the dynamic viscosity, kg / (m·s); d p,0 is the initial diameter of the inclusion particles, m; is the inclusion dissolution rate, m 3 / s.

[0082] By fitting the experimental data, the relationship between the Zh number and the Ry number can be obtained, as shown in formula (3).

[0083] Ry=a·Zh n (3)

[0084] In the formula, m 3 / s; a is the fitting coefficient; n is the fitting index.

[0085] The Zh and Ry numbers of different inclusions in different slags were calculated using equations (1) and (2), as follows: Figure 5 As shown. Since the inclusions are irregular spherical and will move and rotate during the dissolution process, the experimental data points will fluctuate. By fitting the experimental data points, the relationship between the Zh number and the Ry number of the inclusions in the slag can be obtained, as shown in formula (3). The relationship between the fitting coefficient (a) and the fitting index (n) in the relationship between the MgO content in the slag and the Zh number and Ry number is fitted again, as shown in formulas (4) and (5). The fitting results are shown in Figure 6 shown.

[0086] a=b1+k1x (4)

[0087] n=b2+k2x (5)

[0088] Where x is the MgO content in the slag, b1, b2, k1, k2 are the parameters in the fitting relationship between the fitting coefficient (a) and the fitting index (n) and the MgO content in the slag.

[0089] According to the viscosity (η) of the refined slag with MgO content of 0%-6% and the saturation concentration difference of inclusions in the slag (ΔC) calculated by FactSage 8.2 software, and the slag density (ρ) calculated by the Mills model, the Zh number of inclusions with a diameter of 1-1000μm can be calculated using formula (1). Then, based on the relationship between the fitting coefficient (a) and the fitting index (n) in the relationship between the MgO content in the slag and the Zh number and the Ry number obtained by fitting, the dimensionless dissolution rate of inclusion particles with a diameter of 1-1000μm in different slags, that is, the Ry number, can be predicted using formula (3). The results are as follows: Figure 7 As shown. Formula (4) can be used to predict the dissolution time (τ) of inclusion particles with a diameter of 1-1000 μm in different slags. The prediction results are shown in Figure 8 shown.

[0090]

[0091] Where τ is the time for inclusions to be completely dissolved in the refined slag, s; r is the initial radius of the inclusion, m.

[0092] Embodiment 2

[0093] The present invention also discloses a prediction system for the dissolution time of inclusions in slag, comprising: an acquisition module, a calculation module, a construction module and a prediction module;

[0094] The acquisition module is used to acquire the inclusions to be predicted in the pre-melted slag, wherein the pre-melted slag comprises: preparing experimental slag according to the component ratio, and pre-melting the experimental slag using a preset high-temperature device, and the inclusions include: alumina, calcium aluminate and magnesium aluminum spinel particles;

[0095] The calculation module is used for placing the inclusions and pre-melted slag into a preset high-temperature confocal microscope according to a predetermined placement method, obtaining the dissolution rate of the inclusions and the size of the inclusions at different times, and performing data fitting;

[0096] The construction module is used to establish a prediction model for the dissolution of different inclusions based on the data fitting results;

[0097] The prediction module is used to input the inclusions to be predicted into the prediction model of different inclusion dissolution, and obtain the dissolution time of inclusions of different sizes and types in slags of different components.

[0098] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for predicting the dissolution time of inclusions in slag, characterized in that: The following steps are involved: Obtaining inclusions to be predicted in the pre-melted slag, wherein the pre-melted slag comprises: preparing experimental slag according to a component ratio, and pre-melting the experimental slag using a preset high-temperature device, and the inclusions include: alumina, calcium aluminate and magnesium aluminum spinel particles; Placing the inclusions and the pre-molten slag into a preset high-temperature confocal microscope according to a predetermined placement method, obtaining the dissolution rate of the inclusions and the size of the inclusions at different times, and performing data fitting; According to the data fitting results, a prediction model for the dissolution of different inclusions is established; The inclusions to be predicted are input into the prediction model for the dissolution of different inclusions to obtain the dissolution time of inclusions of different sizes and types in slags of different components.

2. The method for predicting the dissolution time of inclusions in slag according to claim 1, characterized in that: The experimental slag basicity CaO / SiO2 is 5.0, CaO / Al2O3 is 1.4, the composition is prepared based on the refined slag used in the refining process of the current production process of aluminum deoxidized steel, and 0%, 3% and 6% MgO content are added to the slag.

3. The method for predicting the dissolution time of inclusions in slag according to claim 1, characterized in that: Placing the inclusions and the pre-molten slag into a preset high-temperature confocal microscope according to a predetermined placement method comprises: The inclusion particles are placed on the surface of the pre-melted slag in a Pt crucible and heated in an argon atmosphere. The heating temperature is measured and controlled by a thermocouple. The heating temperature is 1500°C. During the heating process, it is first heated to 50°C below the heating temperature and then raised to the heating temperature.

4. The method for predicting the dissolution time of inclusions in slag according to claim 1, characterized in that: Obtaining the dissolution rate of the inclusion and the size of the inclusion at different times comprises: ImageJ was used to measure the area of ​​inclusion particles at different times during the dissolution process, and the equivalent circular diameter of the particles was calculated based on the particle area; The dissolution rate of the inclusions is calculated based on the dissolution time and equivalent diameter of the inclusions, wherein the dissolution time includes: the timing starts when the temperature in the high-temperature confocal microscope reaches the heating temperature, and the timing ends when the inclusions are completely dissolved.

5. The method for predicting the dissolution time of inclusions in slag according to claim 2, characterized in that: Inputting the inclusions to be predicted into the prediction model of the dissolution of different inclusions to obtain the time for the dissolution of inclusions of different sizes and types in slags of different components includes: The inclusion capacity Zh and dimensionless dissolution rate Ry in refined slag are used to characterize the solubility and dissolution rate of inclusions in refined slag and the relationship between the physicochemical properties of slag and the size of inclusions. According to the data fitting results, the exponential relationship between Zh number and Ry number is obtained; Using the exponential relationship between Zh number and Ry number, the relationship between MgO content in refined slag and fitting parameters was obtained; According to the relationship between the MgO content in the refined slag and the fitting parameters, the relationship between the MgO content in the slag and the Ry number is obtained; According to the relationship between MgO content and Ry number in slag, the dissolution time of various inclusions of different sizes in refined slag with different MgO concentrations is predicted.

6. The method for predicting the dissolution time of inclusions in slag according to claim 5, characterized in that: The inclusion capacity Zh and dimensionless dissolution rate Ry in refined slag are used to characterize the solubility and dissolution rate of inclusions in refined slag and the relationship between the physicochemical properties of slag and inclusion size, including: Where g is the acceleration due to gravity, m / s 2 ρ slag Slag is the density of refined slag, kg / m 3 ; C saturation is the saturated mass of inclusions in the slag, %; C is the mass fraction of inclusions in the refined slag, %; ν slag is the kinematic viscosity of inclusions in refined slag m 2 / s; η slag is the dynamic viscosity, kg / (m·s); d p,0 is the initial diameter of the inclusion particles, m; is the inclusion dissolution rate.

7. The method for predicting the dissolution time of inclusions in slag according to claim 6, characterized in that: The exponential relationship between Zh and Ry numbers includes: Ry=a·Zh n ; Where a is the fitting coefficient and n is the fitting index.

8. The method for predicting the dissolution time of inclusions in slag according to claim 7, characterized in that: The relationship between MgO content and Ry number in slag includes: Where τ is the time for inclusions to be completely dissolved in the refined slag, s; r is the initial radius of the inclusion, m.

9. A prediction system for the dissolution time of inclusions in slag, characterized in that: include: Acquisition module, calculation module, construction module and prediction module; The acquisition module is used to acquire inclusions to be predicted in the pre-melted slag, wherein the pre-melted slag comprises: preparing experimental slag according to a component ratio, and pre-melting the experimental slag using a preset high-temperature device, and the inclusions include: alumina, calcium aluminate and magnesium aluminum spinel particles; The calculation module is used for placing the inclusions and the pre-molten slag into a preset high-temperature confocal microscope according to a predetermined placement method, obtaining the dissolution rate of the inclusions and the size of the inclusions at different times, and performing data fitting; The building module is used to establish a prediction model for the dissolution of different inclusions based on the data fitting results; The prediction module is used to input the inclusions to be predicted into the prediction model of the dissolution of different inclusions to obtain the time for the inclusions of different sizes and types to dissolve in slags of different components.

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