A method for predicting molten steel temperature in a VD furnace

Abstract

The present invention discloses a method for predicting the molten steel temperature in a VD furnace. The method includes constructing a prediction model for the temperature of the VD ladle: VD ladle temperature = liquidus temperature + temperature drop from the VD ladle to the tundish + tundish superheat; constructing a prediction model for the temperature when entering the VD furnace: VD furnace inlet temperature = VD ladle temperature + soft blowing temperature drop + vacuum temperature drop. The soft blowing temperature drop includes T 软吹温降* soft blowing time t1, and the vacuum temperature drop includes T 真空温降* vacuum time t2. Taking the production rhythm of the continuous caster as the center, the time sequence of each heat in each process of the VD furnace is deduced backwards. Based on the time sequence, and determined according to the steel type, heat number, large and small repair ladles, the temperature drop of the ladle is calculated to obtain the prediction model for the VD ladle temperature and the prediction model for the VD furnace inlet temperature of each heat, and the process control temperature that converts the time flow into the temperature flow is generated, solving the problem that the ladle transfer temperature is not associated with the production rhythm, and the improper control of the molten steel temperature caused by errors in the manual estimation process, ensuring the castability of the molten steel in the continuous caster and the smooth progress of casting the steel billet in the continuous caster.

Description

Technical Field

[0001] The invention belongs to the field of steel smelting, and in particular relates to a method for predicting the temperature of molten steel in a VD furnace. Background Art

[0002] When smelting steel, the chemical reaction of molten iron, scrap steel, ferroalloys and other smelting materials in the ladle is used to smelt steel. When using a converter to smelt steel, the temperature is generally controlled by the heat of the molten iron itself and the use of an oxygen lance to blow oxygen into the molten iron. The heat released by the oxidation reaction of oxygen with Si, C, P, S and other elements in the molten iron. Temperature control mainly includes process temperature control and terminal temperature control. The quality of temperature control will directly affect the energy in the smelting process, the recovery rate of alloy elements, the service life of the furnace lining and the quality of the finished steel and other technical indicators. Scientific and reasonable control of the temperature in the smelting process is an important process means to control the direction and limit of metallurgical reactions.

[0003] In order to ensure the stable and controlled quality of the ingot, the continuous casting controls the "constant temperature and constant drawing speed" casting. Temperature management is the premise of constant drawing speed casting and is closely related to timing management. Therefore, it is necessary to establish a temperature flow management-time flow management method. When using the data ledger to refer to the temperature drop of the ladle, there are many factors such as the ladle online temperature, refining time, and ladle downtime that cannot be referenced. The degree of influence of the temperature drop factor is unknown. In the prior art, the ladle transition temperature has not been associated with the production rhythm, and there is no temperature prediction method suitable for VD furnace vacuum refining molten steel. It only relies on time control and repeated temperature measurements. When the operator does not have enough understanding of the factors affecting the temperature drop of the ladle, it is misleading when used in steel smelting. The manual estimation process is wrong, resulting in improper control of the molten steel temperature, which is easy to cause abnormal continuous casting, affecting the normal production and the castability of the continuous casting machine. Therefore, the temperature of each process of steelmaking must be strictly controlled to ensure the smooth casting of steel ingots by the continuous casting machine. Summary of the invention

[0004] The present invention aims to solve at least one of the above-mentioned technical problems to a certain extent. To this end, the present invention proposes a method for predicting the temperature of molten steel in a VD furnace. Through a VD ladle temperature prediction model and a VD station entry temperature prediction model, a process control temperature of converting a time flow into a temperature flow is generated. The problem that the ladle transfer temperature is not associated with the production rhythm and the artificial estimation process errors lead to improper control of the molten steel temperature is solved, thereby ensuring the castability of the molten steel of the continuous casting machine and the smooth casting of the steel ingots by the continuous casting machine.

[0005] The technical solution of the present invention is:

[0006] A method for predicting the temperature of molten steel in a VD furnace comprises: constructing a VD ladle temperature prediction model and a VD station entry temperature prediction model, reversing the time sequence of each furnace in each process of the VD furnace based on the production rhythm of a continuous casting machine, calculating the VD ladle temperature prediction model and the VD station entry temperature prediction model of each furnace according to the time sequence and the ladle temperature drop, and generating a process control temperature for converting a time flow into a temperature flow.

[0007] The above-mentioned method for predicting the temperature of molten steel in a VD furnace preferably comprises: determining the type of steel and the liquidus corresponding to the type of steel according to the carbon content, and constructing a VD ladle temperature prediction model based on the liquidus and the ladle temperature drop;

[0008] The ladle temperature drop includes the temperature drop from VD ladle to tundish and the tundish superheat corresponding to the type of steel. The VD ladle temperature prediction model is: VD ladle temperature = liquidus + temperature drop from VD ladle to tundish + tundish superheat.

[0009] The above-mentioned VD furnace molten steel temperature prediction method preferably obtains the heat to determine the temperature drop from the VD hanging ladle to the tundish and the tundish superheat, and the heat includes the first ladle of the startup furnace, the second ladle of the continuous casting furnace and the continuous ladle of the continuous casting furnace;

[0010] The temperature of the first VD ladle of medium carbon steel in the start-up furnace drops to 42±4℃, and the overheat of the tundish is 35±2℃. The temperature of the second VD ladle of medium carbon steel drops to 41±3℃. The temperature of the continuous VD ladle of medium carbon steel drops to 27±3℃, and the overheat of the tundish of the continuous casting furnace of medium carbon steel is 25±2℃.

[0011] The temperature of the first ladle of low carbon steel from VD hanging ladle to tundish of the startup furnace drops to 45±2℃, and the overheat of the tundish is 35±2℃. The temperature of the second ladle of low carbon steel from VD hanging ladle to tundish drops to 36±2℃. The temperature of the continuous ladle of low carbon steel from VD hanging ladle to tundish drops to 27±1℃, and the overheat of the tundish of the continuous casting furnace of low carbon steel is 25±2℃.

[0012] The above-mentioned VD furnace molten steel temperature prediction method preferably includes a compensation coefficient K1 for determining the temperature drop from the hanging ladle to the tundish based on the large and small repair packages of the process, and the compensation coefficient K1 is 4.7-5.2°C.

[0013] The above-mentioned VD furnace molten steel temperature prediction method preferably comprises: determining the type of steel according to the carbon content, and constructing a VD station entry temperature prediction model based on the VD ladle temperature prediction model and the ladle temperature drop corresponding to the steel type;

[0014] The ladle temperature drop corresponding to the steel type includes soft blowing temperature drop and vacuum temperature drop. The VD inlet temperature prediction model is: VD inlet temperature = VD ladle temperature + soft blowing temperature drop + vacuum temperature drop. The soft blowing temperature drop includes T 软吹温降 *t1, vacuum temperature drop includes T真空温降 *t2,T 软吹温降 is the rate of change of soft blowing temperature drop over time, T 真空温降 is the rate of change of vacuum temperature drop with time, t1 is the soft blowing time, and t2 is the vacuum time.

[0015] The above VD furnace molten steel temperature prediction method preferably obtains the heat to determine T 软吹温降 , specifically including:

[0016] Medium carbon steel heats are T of the 1st to nth heats 软吹温降 0.5±0.05℃ / min, medium carbon steel heat is greater than the T of the nth heat 软吹温降 0.5±0.05℃ / min; T of any heat of low carbon steel 软吹温降 It is 0.5±0.05℃ / min; the unit of t1 and t2 is min, n is an integer greater than 2, and n large packages are treated in a cycle in the VD furnace as a group.

[0017] The above VD furnace molten steel temperature prediction method preferably obtains the heat to determine T 真空温降 , including:

[0018] Medium carbon steel heat is T of the first heat 真空温降 2±0.03℃ / min, medium carbon steel heat is T of the 2nd to nth heat 真空温降 1.6±0.05℃ / min, medium carbon steel heat is T of the (n+1)-2n heats 真空温降 1.5±0.05℃ / min, medium carbon steel heat is greater than T of the 2nth heat 真空温降 1.4±0.05℃ / min;

[0019] The low carbon steel heat is T of the first heat 真空温降 2.1±0.1℃ / min, low carbon steel heat is T of the 2nd to nth heat 真空温降 1.7±0.05℃ / min, low carbon steel heat is greater than the T of the nth heat 真空温降 It is 1.5±0.1℃ / min; the unit of t1 and t2 is min; n is an integer greater than 2, and n large packages are treated in a cycle through the VD furnace as a group.

[0020] The above-mentioned VD furnace molten steel temperature prediction method is preferably based on the process large and small repair packages to determine the soft blowing temperature drop including the large and small repair temperature drop K2*t1, and the vacuum temperature drop including the large and small repair temperature drop K3*t2, K1 is 0.3-0.35℃ / min, K2 is 0.18-0.22℃ / min, t1 is the soft blowing time, t2 is the vacuum time, and the units of t1 and t2 are min.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] (1) A VD ladle temperature prediction model is constructed based on the liquidus line and ladle temperature drop corresponding to the steel type. The VD ladle temperature = liquidus line + temperature drop from VD ladle to tundish + tundish superheat. The temperature drop from VD ladle to tundish and the tundish superheat are determined according to the furnace. This makes the prediction accuracy of the first ladle of the start-up furnace, the second ladle of the continuous casting furnace, and the ladle used in the continuous casting furnace for medium and low carbon steel good.

[0023] (2) Based on the VD ladle temperature prediction model and the ladle temperature drop corresponding to the steel type, a VD inlet temperature prediction model is constructed. VD inlet temperature = VD ladle temperature + soft blowing temperature drop + vacuum temperature drop. The soft blowing temperature drop includes T 软吹温降 *t1, vacuum temperature drop includes T 真空温降 *t2, t1 is the soft blowing time, t2 is the vacuum time, and T is determined according to the furnace 软吹温降 、T 真空温降 , which improves the prediction accuracy of the first bag of medium and low carbon steel startup furnace, the second bag of continuous casting furnace, and the continuous bags of continuous casting furnaces.

[0024] (3) According to the large and small repair packages of the process, the soft blowing temperature drop includes the temperature drop from VD hanging ladle to the middle ladle, including the compensation coefficient K1, the large and small ladle repair temperature drop K2*t1, and the vacuum temperature drop includes the large and small ladle repair temperature drop K3*t2; the VD hanging ladle temperature prediction model and the VD inlet temperature prediction model can well resist the abnormal large and small ladle repair times.

[0025] In summary, by taking the production rhythm of the continuous casting machine as the center and working back the timing of each furnace of the VD furnace in each process, the VD ladle temperature prediction model and the VD inlet temperature prediction model of each furnace are calculated according to the timing and the temperature drop of the ladle, and the process control temperature of converting the time flow into the temperature flow is generated. This solves the problem that the ladle transfer temperature is not associated with the production rhythm and the improper control of the molten steel temperature due to errors in the manual estimation process. It provides a scientific and reasonable prediction method for the temperature control of the VD furnace during the smelting process in the operating area, ensuring the castability of the molten steel of the continuous casting machine and the smooth casting of the steel ingots by the continuous casting machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a method flow chart of an embodiment of the present invention;

[0027] Figure 2 is a flow chart for determining the temperature drop of a ladle according to an embodiment of the present invention;

[0028] Figure 3 It is a rendering of an embodiment of the present invention;

[0029] Figure 4 It is a comparison chart of the continuous-casting furnace packages for medium-carbon steel according to the accuracy analysis of the present invention.

[0030] Figure 5It is a comparison chart of the continuous-use package of the low-carbon steel continuous casting furnace for accuracy analysis of the present invention. DETAILED DESCRIPTION

[0031] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0032] Figure 1-2 A preferred implementation of the VD furnace molten steel temperature prediction method is shown, including: constructing a VD ladle temperature prediction model and a VD station entry temperature prediction model, reversing the timing of each furnace of the VD furnace in each process based on the production rhythm of the continuous casting machine, calculating the VD ladle temperature prediction model and the VD station entry temperature prediction model for each furnace according to the timing and ladle temperature drop, and generating a process control temperature that converts the time flow into the temperature flow.

[0033] The above-mentioned method for predicting the temperature of molten steel in a VD furnace preferably comprises: determining the type of steel and the liquidus corresponding to the type of steel according to the carbon content, and constructing a VD ladle temperature prediction model based on the liquidus and the ladle temperature drop;

[0034] The ladle temperature drop includes the temperature drop from VD ladle to tundish and the tundish superheat corresponding to the type of steel. The VD ladle temperature prediction model is: VD ladle temperature = liquidus + temperature drop from VD ladle to tundish + tundish superheat.

[0035] The above-mentioned VD furnace molten steel temperature prediction method preferably obtains the heat to determine the temperature drop from the VD hanging ladle to the tundish and the tundish superheat, the heat includes the first ladle of the startup furnace, the second ladle of the continuous casting furnace and the continuous casting furnace joint ladle, the temperature drop from the VD hanging ladle to the tundish and the tundish superheat are shown in Table 1 below:

[0036] Table 1 Temperature drop from VD ladle to tundish and tundish superheat corresponding to steel type and heat

[0037]

[0038] Heat number = 1 is the first pack of the start-up furnace, heat number = 2 is the second pack of the continuous casting furnace, and heat number > 2 is the continuous casting furnace pack.

[0039] The above-mentioned VD furnace molten steel temperature prediction method preferably includes a compensation coefficient K1 for determining the temperature drop from the hanging ladle to the tundish based on the large and small repair packages of the process, and the compensation coefficient K1 is 4.7-5.2°C.

[0040] The above-mentioned VD furnace molten steel temperature prediction method preferably comprises: determining the type of steel according to the carbon content, and constructing a VD station entry temperature prediction model based on the VD ladle temperature prediction model and the ladle temperature drop corresponding to the steel type;

[0041] The ladle temperature drop corresponding to the steel type includes soft blowing temperature drop and vacuum temperature drop. The VD inlet temperature prediction model is: VD inlet temperature = VD ladle temperature + soft blowing temperature drop + vacuum temperature drop. The soft blowing temperature drop includes T 软吹温降 *t1, vacuum temperature drop includes T 真空温降 *t2,T 软吹温降 is the rate of change of soft blowing temperature drop over time, T 真空温降 is the rate of change of vacuum temperature drop with time, t1 is the soft blowing time, and t2 is the vacuum time.

[0042] The above VD furnace molten steel temperature prediction method preferably obtains the heat to determine T 软吹温降 , t1 and t2 are in units of min, T 软吹温降 As shown in Table 2 below:

[0043] Table 2 Steel type, heat corresponding to T 软吹温降

[0044]

[0045] n is an integer greater than 2, and n large bags are treated in a cycle in the VD furnace as a group. The specific value of n is determined according to the actual production rhythm;

[0046] The above VD furnace molten steel temperature prediction method preferably obtains the heat to determine T 真空温降 , t1 and t2 are in units of min, T 真空温降 As shown in Table 3 below:

[0047] Table 3 Steel type, heat corresponding to T 真空温降

[0048]

[0049] n is an integer greater than 2, and n large bags are treated in a cycle in the VD furnace as a group. The specific value of n is determined according to the actual production rhythm;

[0050] The above-mentioned VD furnace molten steel temperature prediction method is preferably determined based on the process large and small repair packages. The soft blowing temperature drop includes the large and small repair temperature drop K2*t1, and the vacuum temperature drop includes the large and small repair temperature drop K3*t2, K1 is 0.3-0.35℃ / min, K2 is 0.18-0.22℃ / min, t1 is the soft blowing time, t2 is the vacuum time, and the unit of t1 and t2 is min, that is, VD inlet temperature = VD hanging bag temperature + soft blowing temperature drop + vacuum temperature drop, soft blowing temperature drop = (T 软吹温降+K1)*t1, vacuum temperature drop = (T 真空温降 +K2)*t2, t1 is the soft blowing time, t2 is the vacuum time, and the major and minor repair packages are the ladle overhaul or minor repair procedures.

[0051] The above-mentioned VD furnace molten steel temperature prediction method preferably comprises the following steps:

[0052] S1: Calculate the start-up time of the tundish according to the start-up time of the continuous casting machine and the replacement time of the tundish, and prepare for the baking of the tundish;

[0053] S2: Based on the production rhythm of the continuous casting machine, the timing of each furnace of the VD furnace in each process is reversed. The reverse timing is shown in Table 4 below

[0054] Table 4 Process sequence

[0055]

[0056] After the ladle receives the molten steel, the VD enters the station. The VD process includes soft blowing and vacuum operation of the molten steel in the ladle by the VD furnace. The molten steel transfer includes VD lifting of the ladle treated by the VD furnace, transferring the molten steel from the ladle to the tundish, and injecting the molten steel from the tundish to the continuous casting machine. A group of n ladle is circulated through the VD furnace, where n is an integer greater than 2. The furnace order is determined by reverse timing.

[0057] S3: Calculate the VD inlet temperature using the VD furnace molten steel temperature prediction system; the VD furnace molten steel temperature prediction system includes an input unit, a VD hanging ladle temperature prediction model, a VD hanging ladle temperature prediction unit and a display unit, such as Figure 3 As shown, the input unit is used to input the liquidus line (the unit of liquidus line is ℃), the furnace, the type of steel (medium carbon steel / low carbon steel), and the ladle condition (normal / major or minor repair ladle);

[0058] A VD ladle temperature prediction model is constructed based on the liquidus line and ladle temperature drop corresponding to the steel type. The VD ladle temperature prediction model is: VD ladle temperature = liquidus line + temperature drop from VD ladle to tundish + tundish superheat. The temperature drop from VD ladle to tundish and tundish superheat of the VD ladle temperature prediction model are constructed by using Table 1. The VD ladle temperature prediction unit obtains the VD ladle temperature by performing a logical operation on the VD ladle temperature prediction model according to the input unit. The display unit is used to display the VD ladle temperature.

[0059] There is no large or small repair package in the first ladle of the startup furnace. During the ladle transfer process, the furnaces after the first ladle of the startup furnace have large and small repair packages according to the needs. According to the process, large and small repair packages are carried out, and the temperature drop from the VD hanging ladle to the tundish includes the compensation coefficient K1, which is 4.7-5.2℃;

[0060] S4: Calculate the VD inlet temperature using the VD furnace molten steel temperature prediction system; the VD furnace molten steel temperature prediction system also includes a VD inlet temperature prediction model and a VD inlet temperature prediction unit, such as Figure 3 As shown, the input unit is also used to input the soft blowing time t1 and the vacuum time t2, and the units of t1 and t2 are min;

[0061] Based on the VD ladle temperature prediction model and the ladle temperature drop corresponding to the steel type, a VD inlet temperature prediction model is constructed. The VD inlet temperature prediction model is: VD inlet temperature = VD ladle temperature + soft blowing temperature drop + vacuum temperature drop. The soft blowing temperature drop includes T 软吹温降 *t1, vacuum temperature drop includes T 真空温降 *t2,T 软吹温降 is the rate of change of soft blowing temperature drop over time, T 真空温降 is the rate of change of vacuum temperature drop with time, t1 is the soft blowing time, t2 is the vacuum time, and T of the VD inlet temperature prediction model is 软吹温降 Table 2 is used to determine the construction and T 真空温降 Table 3 was used to determine the construction;

[0062] There is no large or small repair package in the first package of the start-up furnace. In the process of ladle transfer, the furnaces after the first package of the start-up furnace have large or small repair packages according to the needs. According to the large and small repair packages of the process, the soft blowing temperature drop includes the large and small package repair temperature drop K2*t1, and the vacuum temperature drop includes the large and small package repair temperature drop K3*t2. K1 is 0.3-0.35℃ / min, K2 is 0.18-0.22℃ / min, t1 is the soft blowing time, t2 is the vacuum time, and the unit of t1 and t2 is min;

[0063] The VD station entry temperature prediction unit is used to obtain the VD station entry temperature by performing a logical operation on the VD station entry temperature prediction model according to the input unit;

[0064] S5: The display unit is used to display the VD bag temperature and VD station entry temperature, and generate the process control temperature by converting the time flow into the temperature flow, that is, based on the production rhythm of the continuous casting machine, the timing of each furnace of the VD furnace in each process is reversed and converted into the VD bag temperature and VD station entry temperature of each furnace, so as to control the process temperature and avoid the defects of repeated measurement and inaccurate temperature control of traditional methods.

[0065] The carbon content of medium carbon steel is 0.25% to 0.60%, and the carbon content of low carbon steel is less than 0.25%. Steps S3 and S4 determine whether the steel type belongs to medium carbon steel or low carbon steel based on the carbon content, and determine the liquidus corresponding to the steel type. The liquidus refers to the temperature of the intersection of molten steel in solid and liquid states, which is equivalent to the lower limit temperature of molten steel produced by the continuous casting machine. The liquidus range is between 1490 and 1530°C.

[0066] like Figure 3The embodiment shown: n is 6, input liquidus (℃) 1513, furnace number is 6, steel type is low carbon steel, ladle condition is normal, soft blowing time (min) is 21, vacuum time (min) is 25, click VD hanging ladle temperature to calculate VD hanging ladle temperature = liquidus + VD hanging ladle to tundish temperature drop + tundish superheat = 1513 + 27 + 27 = 1567, click VD station temperature to calculate VD station temperature = VD hanging ladle temperature + T 软吹温降 *t1+T 真空温降 *t2=1567+0.5*21+1.7*25=1620.0.

[0067] The accuracy analysis and effect verification of the above VD furnace molten steel temperature prediction method are carried out:

[0068] The predicted VD ladle temperature (°C) and the predicted VD inlet temperature (°C) under the corresponding liquidus line are calculated by the above-mentioned VD furnace molten steel temperature prediction method, and the VD inlet temperature (°C) is obtained by detecting the inlet molten steel temperature, the VD ladle temperature (°C) is obtained by detecting the ladle molten steel temperature, and the molten steel casting temperature (°C) is detected;

[0069] (1) In the steelmaking PES system, five groups of data from the first batch of medium carbon steel furnaces were randomly selected. The data comparison results are shown in Table 5 below:

[0070] Table 5 Comparison of the first package of medium carbon steel furnace

[0071]

[0072] (2) Five groups of data from the second ladle of a medium carbon steel continuous casting furnace were randomly selected in the steelmaking PES system. The data comparison is shown in Table 6 below:

[0073] Table 6 Comparison of the second ladle of medium carbon steel continuous casting furnace

[0074]

[0075] It can be seen from Table 5-6 that the average error between the predicted VD ladle temperature and the detected VD ladle temperature of the first ladle of medium carbon steel start-up furnace of different brands is about 2°C, and the average error between the predicted VD inlet temperature and the detected VD inlet temperature is about 4°C. The errors between the VD ladle temperature and the detected VD ladle temperature and the VD inlet temperature and the detected VD inlet temperature of the second ladle of continuous casting furnace are about 7°C, and the molten steel casting temperature (°C) is greater than the liquidus, which ensures the castability of the molten steel of the continuous casting machine, indicating that the prediction accuracy is good.

[0076] (3) In the steelmaking PES system, 20 groups of medium carbon steel molds with different grades were randomly selected and the VD hanging ladle temperature and VD inlet temperature under different furnaces were experimentally analyzed for continuous casting. The analysis results are as follows: Figure 4 As shown. Figure 4 (a) It can be seen that the average error between the VD bag temperature and the predicted VD bag temperature is about 6°C, and the maximum error is about 7°C; Figure 4 (b) It can be seen that the errors between the VD inlet temperature and the predicted VD inlet temperature are mostly within 5°C. The range of the two error values ​​is small, indicating that the prediction effect is good. The analyses of (1)-(3) are all based on the temperature conditions of the ladle under normal conditions.

[0077] (4) In the steelmaking PES system, five groups of data on medium carbon steel ladle repairs were randomly selected, and the robustness analysis of the model was performed on the abnormal conditions of ladle repairs. The data comparison results are shown in Table 7 below:

[0078] Table 7 Comparison of medium carbon steel repair kits

[0079]

[0080] It can be seen from Table 7 that the errors between the VD ladle temperature and the detected VD ladle temperature and between the VD station temperature and the detected VD station temperature are very close, and the molten steel casting temperature (℃) is greater than the liquidus line, ensuring the castability of the molten steel of the continuous casting machine. The model can well resist the abnormalities of large and small repairs of the ladle.

[0081] (5) Five groups of data on the first package of low-carbon steel furnace were randomly selected in the steelmaking PES system. The data comparison results are shown in Table 8 below:

[0082] Table 8 Comparison of the first package of low carbon steel furnace

[0083]

[0084] (6) In the steelmaking PES system, five groups of data from the second ladle of the low-carbon steel continuous casting furnace were randomly selected. The data comparison results are shown in Table 9 below:

[0085] Table 9 Comparison of the second ladle of low carbon steel continuous casting furnace

[0086]

[0087] It can be seen from Table 8-9 that the average error between the predicted VD ladle temperature and the detected VD ladle temperature, the predicted VD inlet temperature and the detected VD inlet temperature of the first ladle of low-carbon steel start-up furnace of different brands is about 6°C, while the errors between the VD ladle temperature and the detected VD ladle temperature and the VD inlet temperature and the detected VD inlet temperature of the second ladle of the continuous casting furnace are within 10°C, and the molten steel casting temperature (°C) is greater than the liquidus, which ensures the castability of the molten steel of the continuous casting machine, indicating that the prediction effect is good.

[0088] (7) In the steelmaking PES system, 20 groups of low-carbon steel molds of different grades were randomly selected and the VD hanging ladle temperature and VD inlet temperature under different furnaces were experimentally analyzed for continuous casting. The analysis results are as follows: Figure 5 As shown. Figure 5 (a) It can be seen that the average error between the VD bag temperature and the predicted VD bag temperature is about 4°C; Figure 5 (b) It can be seen that the error between the VD inlet temperature and the predicted VD inlet temperature is mostly within 5°C, and the range of the two error values ​​is small, indicating that the prediction effect is good and can well guide the temperature control of the working area. The analyses of (5)-(7) are all the temperature conditions of the ladle under normal conditions.

[0089] (8) Five groups of data on small and large repair kits of low carbon steel were randomly selected in the steelmaking PES system. The data comparison results are shown in Table 10 below:

[0090] Table 10 Comparison of small and large low carbon steel repair kits

[0091]

[0092] It can be seen from Table 10 that the errors between the VD ladle temperature and the detected VD ladle temperature and between the VD station temperature and the detected VD station temperature are very close, and the molten steel casting temperature (℃) is greater than the liquidus line, ensuring the castability of the molten steel of the continuous casting machine. The model can well resist the abnormalities of large and small repairs of the ladle.

[0093] In summary, the present invention reversely deduces the timing of each furnace of the VD furnace in each process based on the production rhythm of the continuous casting machine, calculates the VD ladle temperature prediction model and the VD inlet temperature prediction model of each furnace according to the timing and the temperature drop of the ladle, and generates a process control temperature for converting the time flow into the temperature flow. That is, the production can be guided by predicting the VD ladle temperature and the VD inlet temperature of each furnace, and there is no need to repeatedly measure the temperature. This solves the problem that the ladle transfer temperature is not associated with the production rhythm and the artificial estimation process errors lead to improper control of the molten steel temperature. This provides a scientific and reasonable prediction method for the temperature control of the VD furnace during the smelting process in the operating area, and ensures the castability of the molten steel of the continuous casting machine and the smooth casting of the steel ingot by the continuous casting machine.

[0094] It should be understood that although this specification is described according to various embodiments, not every embodiment contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

[0095] The series of detailed descriptions listed above are only specific descriptions of feasible embodiments of the present invention. They are not intended to limit the scope of protection of the present invention. All equivalent embodiments or changes that do not deviate from the technical spirit of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for predicting the temperature of molten steel in a VD furnace, characterized in that: The method comprises: S1: Calculate the start-up time of the tundish according to the start-up time of the continuous casting machine and the replacement time of the tundish, and prepare for the baking of the tundish; S2: Based on the production rhythm of the continuous casting machine, reverse the timing of each furnace of the VD furnace in each process; S3: Calculate the VD ladle temperature using the VD furnace molten steel temperature prediction system; the VD furnace molten steel temperature prediction system includes an input unit, a VD ladle temperature prediction model, a VD ladle temperature prediction unit and a display unit; The VD hanging bag temperature prediction model is: VD hanging bag temperature = liquidus + temperature drop from VD hanging bag to tundish + tundish superheat; S4: Calculate the VD inlet temperature using the VD furnace molten steel temperature prediction system; the VD furnace molten steel temperature prediction system includes a VD inlet temperature prediction model and a VD inlet temperature prediction unit; The VD inlet temperature prediction model is: VD inlet temperature = VD bag temperature + soft blowing temperature drop + vacuum temperature drop, soft blowing temperature drop includes T 软吹温降* t1, vacuum temperature drop includes T 真空温降* t2,T 软吹温降 is the rate of change of soft blowing temperature drop over time, T 真空温降 is the rate of change of vacuum temperature drop with time, t1 is the soft blowing time, and t2 is the vacuum time; S5: The display unit is used to display the VD bag temperature and the VD station entry temperature, and to generate the process control temperature of converting the time flow into the temperature flow, that is, to reverse the timing of each furnace of the VD furnace in each process based on the production rhythm of the continuous casting machine, and convert it into the VD bag temperature and VD station entry temperature of each furnace.

2. A method for predicting molten steel temperature in a VD furnace according to claim 1, characterized in that: The method comprises: determining the type of steel and the liquidus corresponding to the type of steel according to the carbon content, and constructing a VD ladle temperature prediction model based on the liquidus and the ladle temperature drop.

3. A method for predicting molten steel temperature in a VD furnace according to claim 1, characterized in that: Obtain the heat to determine the temperature drop from the VD hanging ladle to the tundish and the tundish superheat. The heats include the first ladle of the startup furnace, the second ladle of the continuous casting furnace, and the continuous ladle of the continuous casting furnace; The temperature of the first VD ladle of medium carbon steel in the start-up furnace drops to 42±4℃, and the overheat of the tundish is 35±2℃. The temperature of the second VD ladle of medium carbon steel drops to 41±3℃. The temperature of the continuous VD ladle of medium carbon steel drops to 27±3℃, and the overheat of the tundish of the continuous casting furnace of medium carbon steel is 25±2℃. The temperature of the first ladle of low carbon steel from VD hanging ladle to tundish of the startup furnace drops to 45±2℃, and the overheat of the tundish is 35±2℃. The temperature of the second ladle of low carbon steel from VD hanging ladle to tundish drops to 36±2℃. The temperature of the continuous ladle of low carbon steel from VD hanging ladle to tundish drops to 27±1℃, and the overheat of the tundish of the continuous casting furnace of low carbon steel is 25±2℃.

4. A method for predicting molten steel temperature in a VD furnace according to claim 1, characterized in that: The temperature drop from the hanging package to the intermediate package is determined based on the large and small repair packages of the process, including the compensation coefficient K1, which is 4.7-5.2℃.

5. A method for predicting molten steel temperature in a VD furnace according to any one of claims 1 to 4, characterized in that: The method comprises: determining the type of steel according to the carbon content, and constructing a VD inlet temperature prediction model based on the VD ladle temperature prediction model and the ladle temperature drop corresponding to the type of steel.

6. A method for predicting molten steel temperature in a VD furnace according to claim 5, characterized in that: Get the furnace number to determine T 软吹温降 , specifically including: Medium carbon steel heats are T of the 1st to nth heats 软吹温降 0.5±0.05℃ / min, medium carbon steel heat is greater than the T of the nth heat 软吹温降 0.5±0.05℃ / min; T of any heat of low carbon steel 软吹温降 It is 0.5±0.05℃ / min; the unit of t1 and t2 is min, n is an integer greater than 2, and n large packages are treated in a cycle in the VD furnace as a group.

7. A method for predicting molten steel temperature in a VD furnace according to claim 5, characterized in that: Get the furnace number to determine T 真空温降 , specifically including: Medium carbon steel heat is T of the first heat 真空温降 2±0.03℃ / min, medium carbon steel heat is T of the 2nd to nth heat 真空温降 1.6±0.05℃ / min, medium carbon steel heat is T of the (n+1)-2n heats 真空温降 1.5±0.05℃ / min, medium carbon steel heat is greater than T of the 2nth heat 真空温降 1.4±0.05℃ / min; The low carbon steel heat is T of the first heat 真空温降 2.1±0.1℃ / min, low carbon steel heat is T of the 2nd to nth heat 真空温降 1.7±0.05℃ / min, low carbon steel heat is greater than the T of the nth heat 真空温降 It is 1.5±0.1℃ / min; the unit of t1 and t2 is min; n is an integer greater than 2, and n large packages are treated in a cycle through the VD furnace as a group.

8. A method for predicting molten steel temperature in a VD furnace according to claim 5, characterized in that: According to the process of large and small repair packages, the soft blowing temperature drop is determined, including the large and small package repair temperature drop K 2* t1. Vacuum temperature drop includes large and small repair temperature drop K 3* t2, K1 is 0.3-0.35℃ / min, K2 is 0.18-0.22℃ / min, t1 is the soft blowing time, t2 is the vacuum time, and the unit of t1 and t2 is min.

Images