Visual control method for secondary cooling water distribution curve of multi-strand billet continuous casting machine

Abstract

The invention discloses a secondary cooling water distribution curve visual control method for a multi-strand billet continuous casting machine, which belongs to the technical field of metallurgy, and comprises the following steps: step S1, VBA programming and water distribution curve generation; s2, PLC program calculation is carried out; s3, PID adjustment is carried out; the method has the advantages that the set water distribution curve can be visually reflected, the matching accuracy is high, dynamic and accurate control can be conducted in combination with real-time parameters, and the diversified production requirements of the multi-strand billet continuous casting machine can be met. The problems that according to an existing control method, a set water distribution curve cannot be visually reflected, the corresponding cooling water amount cannot be accurately matched, dynamic accurate control combined with real-time parameters is lacked, a mechanism for evaluating and optimizing a water distribution program regularly based on production data is not formed, and then high-quality diversified production of the multi-flow billet continuous casting machine cannot be met are solved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of metallurgy, and particularly relates to a secondary cooling water distribution curve visual control method for a multi-strand square billet continuous caster. BACKGROUND

[0002] In the prior art, as an intermediate link between steelmaking and rolling, the quality of the secondary cooling water distribution system directly determines the quality of the cast billet. With the development of computer and PLC technology, the secondary cooling water distribution has been automatically controlled. Common mathematical models include proportional control method and parameter control method. The control system of the multi-strand square billet continuous caster usually adopts the programmable controller of the ALLEN-BRADLEY of the ROCKWELL company in the United States, and the configuration software selects RSView32 or FTVIEWSE. Some continuous casters manage the water distribution parameters by storing and calling parameters through the formula file in RSView32.

[0003] However, the prior art still has the following problems in actual use: 1. Although the traditional proportional control method is simple in parameter modification and calling, it cannot intuitively reflect the set water distribution curve, and the operator cannot judge the rationality of the water distribution scheme in real time.

[0004] 2. In actual casting, the pulling speed is often between the preset fixed value, and the traditional calculation method cannot accurately match the corresponding cooling water amount, and lacks dynamic and accurate control in combination with real-time ladle steel temperature, billet pulling speed and other parameters.

[0005] 3. There is no mechanism to periodically evaluate and optimize the water distribution program based on production data, resulting in insufficient cooling precision, affecting the stability of the cast billet quality, and being difficult to meet the diversified production needs of the multi-strand square billet continuous caster. SUMMARY

[0006] In view of the problems in the prior art, the present application provides a secondary cooling water distribution curve visual control method for a multi-strand square billet continuous caster, which has the advantages of being able to intuitively reflect the set water distribution curve, having high matching accuracy, being able to dynamically and accurately control in combination with real-time parameters, and being able to meet the diversified production needs of the multi-strand square billet continuous caster, thereby solving the problems that the existing control method cannot intuitively reflect the set water distribution curve, cannot accurately match the corresponding cooling water amount, lacks dynamic and accurate control in combination with real-time parameters, and has no mechanism to periodically evaluate and optimize the water distribution program based on production data, and thus cannot meet the high-quality and diversified production of the multi-strand square billet continuous caster.

[0007] The present application is implemented as follows: a secondary cooling water distribution curve visual control method for a multi-strand square billet continuous caster, comprising the following steps: Step S1, VBA programming and water distribution curve generation: Using the VBA programming embedded in RSView32, insert a page control and create at least three pages, corresponding to the foot roll section, the first stage, and the second stage cooling area of ​​the multi-strand billet continuous casting machine, respectively. Set the X-axis of the water distribution curve to the casting speed and the Y-axis to the secondary cooling water volume. The casting speed ranges from 0 to 4.4 m / min, and divides the X-axis into 22 equal parts at intervals of 0.2 m / min, forming 23 fixed casting speed values. Select three corresponding points (x1, y1), (x2, y2), and (x3, y3) on any page, based on the parabolic equation y=ax 2 +bx+c lists a system of equations with a, b, and c as unknowns. Solving the system of equations yields the values ​​of a, b, and c. Then, based on 23 fixed pulling speed values, the corresponding 22 secondary cooling water volume values ​​are calculated. A connection is established with the tag database in the RSView32 project through the gTagDb object. The 22 water volume values ​​are saved to the project recipe file and downloaded to the PLC processor. Step S2, PLC program calculation: The PLC processor receives 22 corresponding values ​​downloaded. During the actual casting process, if the casting speed V is between two fixed casting speed values, the following calculation is performed: First, calculate V1 = V × 5, round V1 to the nearest integer and assign the result to n; Given V1≥n, calculate Z = (V×100-n×20) / 100, then use Y = (Y X（n＋1） -Y Xn ) / 0.2×Z+Y Xn The setpoint for the secondary cooling water is obtained, where Y Xn Let Y be the water volume corresponding to the nth fixed pulling speed value on the X-axis. X（n+1） This represents the water volume corresponding to the (n+1)th fixed pulling speed value. V1 < n, calculate Z = [V × 100 - (n - 1) × 20] / 100, then use Y = (Y Xn -Y X（n-1） ) / 0.2×Z+Y Xn The setpoint for the secondary cooling water is obtained, where Y X（n-1） This represents the water volume corresponding to the (n-1)th fixed pulling speed value. Step S3, PID adjustment: PID control is implemented through programming. Based on the real-time monitoring parameters of the molten steel temperature in the ladle and the billet casting speed of the multi-strand billet continuous casting machine, the cooling water volume of the foot roll section, the first stage and the second stage cooling zone is automatically adjusted. Step S4, Continuous Improvement: Regularly evaluate and optimize the secondary cooling water distribution program, collect billet quality data and equipment operation data during the production process, and adjust water distribution parameters and control strategies in conjunction with production process improvements, equipment upgrades and steel grade changes.

[0008] As a preferred embodiment of the present invention, in step S1, the three pages created by the page control are named foot roller, first section, and second section, respectively.

[0009] In a preferred embodiment of the present invention, in step S1, the set of equations is: y1=ax1 2 +bx1+c y2=ax2 2 +bx2+c y3=ax3 2 +bx3+c.

[0010] As a preferred embodiment of the present invention, solving the system of equations yields: a = [y1 - y2 - (x1 - x2) (y2x3)] 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 )] / (x1 2 -x2 2 ) b = (y²x³) 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 ) c=y1-x1 2 [y1-y2-(x1-x2)(y2x3 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2-x1x3 2 -x2x1 2 )] / (x1 2 -x2 2 )-x1(y2x3 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 ).

[0011] In a preferred embodiment of the present invention, the adjustment logic of the PID control in step S3 is as follows: When the temperature of the molten steel in the ladle is higher than the preset threshold in real time, the cooling water volume in the corresponding cooling area is increased. When the casting speed is increased, the cooling water volume in the corresponding cooling zone is increased.

[0012] As a preferred embodiment of the present invention, in step S4, the billet quality data includes the surface crack rate and the center porosity of the billet, and the equipment operation data includes the cooling water consumption and the PLC operating status data.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. Visualized water distribution curves and convenient operation: The water distribution curves are presented intuitively through VBA programming. Operators can directly view the curve shape on the page without relying on formula derivation to judge the rationality of water distribution. Parameter modification is simple, and curve generation is automated, reducing the difficulty of operation and meeting the needs of user-friendly operation.

[0014] 2. Precise water volume calculation, closely following the preset curve: For situations where the actual pumping speed is between fixed values, the PLC program uses interpolation calculations to ensure that the water volume strictly follows the preset parabolic curve, avoiding the deviation of traditional calculation methods and improving water distribution accuracy.

[0015] 3. Dynamic and precise control, adapting to real-time production: PID regulation combined with real-time parameters such as molten steel temperature in the ladle and billet drawing speed can dynamically adjust the water volume, solving the shortcomings of static water distribution in traditional control methods, ensuring that the cooling intensity matches the production conditions, and reducing defects such as surface cracks and central porosity of the billet.

[0016] 4. Continuous optimization and strong stability: The regular evaluation and optimization mechanism, combined with data collection and analysis, can adapt to changes in processes, equipment and steel grades in a timely manner, improve production efficiency, reduce cooling water consumption, reduce production costs, and operate stably, meeting the diverse needs of multi-strand billet continuous casting machines. Attached Figure Description

[0017] Figure 1 This embodiment of the invention provides a secondary cooling water distribution curve for casting steel grade Q215 with a casting cross-section of 150mm×150mm. Detailed Implementation

[0018] To further understand the invention's content, features, and effects, the following embodiments are provided, and detailed descriptions are given in conjunction with the accompanying drawings.

[0019] The structure of the present invention will now be described in detail with reference to the accompanying drawings.

[0020] refer to Figure 1 The present invention provides a method for visually controlling the secondary cooling water distribution curve of a multi-strand billet continuous casting machine, comprising the following steps: Step S1, VBA programming and water distribution curve generation: Using the VBA programming embedded in RSView32, insert a page control and create at least three pages, corresponding to the foot roll section, the first stage, and the second stage cooling area of ​​the multi-strand billet continuous casting machine, respectively. Set the X-axis of the water distribution curve to the casting speed and the Y-axis to the secondary cooling water volume. The casting speed ranges from 0 to 4.4 m / min, and divides the X-axis into 22 equal parts at intervals of 0.2 m / min, forming 23 fixed casting speed values. Select three corresponding points (x1, y1), (x2, y2), and (x3, y3) on any page, based on the parabolic equation y=ax 2 +bx+c lists a system of equations with a, b, and c as unknowns. Solving the system of equations yields the values ​​of a, b, and c. Then, based on 23 fixed pulling speed values, the corresponding 22 secondary cooling water volume values ​​are calculated. A connection is established with the tag database in the RSView32 project through the gTagDb object. The 22 water volume values ​​are saved to the project recipe file and downloaded to the PLC processor. Step S2, PLC program calculation: The PLC processor receives 22 corresponding values ​​downloaded. During the actual casting process, if the casting speed V is between two fixed casting speed values, the following calculation is performed: First, calculate V1 = V × 5, round V1 to the nearest integer and assign the result to n; Given V1≥n, calculate Z = (V×100-n×20) / 100, then use Y = (Y X（n＋1） -Y Xn ) / 0.2×Z+Y XnThe setpoint for the secondary cooling water is obtained, where Y Xn Let Y be the water volume corresponding to the nth fixed pulling speed value on the X-axis. X（n+1） This represents the water volume corresponding to the (n+1)th fixed pulling speed value. V1 < n, calculate Z = [V × 100 - (n - 1) × 20] / 100, then use Y = (Y Xn -Y X（n-1） ) / 0.2×Z+Y Xn The setpoint for the secondary cooling water is obtained, where Y X（n-1） This represents the water volume corresponding to the (n-1)th fixed pulling speed value. Step S3, PID adjustment: PID control is implemented through programming. Based on the real-time monitoring parameters of the molten steel temperature in the ladle and the billet casting speed of the multi-strand billet continuous casting machine, the cooling water volume of the foot roll section, the first stage and the second stage cooling zone is automatically adjusted. Step S4, Continuous Improvement: Regularly evaluate and optimize the secondary cooling water distribution program, collect billet quality data and equipment operation data during the production process, and adjust water distribution parameters and control strategies in conjunction with production process improvements, equipment upgrades and steel grade changes.

[0021] Furthermore, in step S1, the three pages created by the page control are named Foot Roller, Section 1, and Section 2, respectively.

[0022] Further, in step S1, the system of equations is: y1=ax1 2 +bx1+c y2=ax2 2 +bx2+c y3=ax3 2 +bx3+c.

[0023] Furthermore, solving the system of equations yields: a = [y1 - y2 - (x1 - x2) (y2x3)] 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 )] / (x1 2 -x2 2 ) b = (y²x³) 2 +y1x2 2 +y3x12 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 ) c=y1-x1 2 [y1-y2-(x1-x2)(y2x3 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 )] / (x1 2 -x2 2 )-x1(y2x3 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 ).

[0024] Further, in step S3, the adjustment logic of the PID control is as follows: When the temperature of the molten steel in the ladle is higher than the preset threshold in real time, the cooling water volume in the corresponding cooling area is increased. When the casting speed is increased, the cooling water volume in the corresponding cooling zone is increased.

[0025] Furthermore, in step S4, the billet quality data includes the surface crack rate and center porosity of the billet, and the equipment operation data includes cooling water consumption and PLC operating status data.

[0026] Example 1 Taking the production of SUP9 steel grade (150mm×150mm cross-section) using a 150t continuous casting 10-strand small square billet continuous casting machine (compatible with 150mm×150mm and 180mm×180mm cross-sections, producing more than fifty kinds of alloy steel) as an example: Hardware configuration: The main controller is an Allen-Bradley programmable controller from Rockwell Automation, USA, and the configuration software is RSView32 to ensure normal communication between the PLC and RSView32.

[0027] Parameter presets: The preset threshold for molten steel temperature in the ladle is set to 1535℃ (for SUP9 steel grade), the standard range for billet drawing speed is 0.8-3.6m / min, and the secondary cooling water distribution area is divided into foot roll section, first section, and second section.

[0028] Step S1: VBA programming and water distribution curve generation Open RSView32 software, create a new project and enter the VBA editing interface, insert a page control, create three pages and name them foot roller, first stage and second stage respectively, and configure the input areas for pulling speed and water volume parameters on each page; On a page (for a 150mm×150mm cross section of SUP9 steel), the operator selects three corresponding points: (x1=1.0m / min, y1=10.14L / min), (x2=2.0m / min, y2=19.4L / min), (x3=3.0m / min, y3=23.2L / min). Substitute the coordinates of the three points into the system of equations: y1=ax1 2 +bx1+c y2=ax2 2 +bx2+c y3=ax3 2 +bx3+c The formula is solved using the preset a, b, and c: a = [y1 - y2 - (x1 - x2) (y2x3)] 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 )] / (x1 2 -x2 2 ) b = (y²x³) 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 ) c=y1-x1 2 [y1-y2-(x1-x2)(y2x3 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 )] / (x1 2 -x2 2 )-x1(y2x3 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3) 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 ) Solving for a, b, and c, we get a = -0.32, b = 17.45, and c = -5.91 (the equation of the parabola is y = -0.32x). 2 +17.45x-5.91); Based on 23 fixed pulling speed values ​​(0, 0.2...4.4 m / min), 22 water volume values ​​are calculated by substituting them into the above parabolic equation; A connection to the RSView32 tag database is established using the VBA gTagDb object, 22 water volume values ​​are stored in the recipe file, and the water volume values ​​are transferred to the ALLEN-BRADLEY PLC.

[0029] Step S2, PLC program calculation In the actual casting process, if the billet pulling speed V = 1.3 m / min (between 1.2 m / min and 1.4 m / min): Calculate V1 = V × 5 = 1.3 × 5 = 6.5, round V1 to get n = 7; Since V1=6.5<n=7, according to the formula, Z=[1.3×100-(7-1)×20] / 100=(130-120) / 100=0.1; Given Y X6 (Water volume corresponding to a pulling speed of 1.2 m / min) = 16.9 L / min, Y X7 (Water volume corresponding to a pulling speed of 1.4 m / min) = 18.9 L / min, substituting into the formula Y = (Y X7 -Y X6 ) / 0.2×Z+Y X7 = (18.9-16.9) / 0.2×0.1+18.9=10×0.1+18.9=19.9L / min, and this Y value is the secondary cooling water set value corresponding to a pulling speed of 1.3m / min.

[0030] Step S3, PID adjustment The real-time monitoring showed that the temperature of the molten steel in the ladle was 1542℃ (higher than the preset threshold of 1535℃), and the billet pulling speed was maintained at 1.3m / min. The PID controller receives a signal indicating that the temperature exceeds the limit and automatically adjusts the water flow rate in a cooling zone from 19.9L / min to 20.5L / min to enhance the cooling intensity and prevent the molten steel temperature from being too high, which could lead to defects in the casting billet. When the temperature of the molten steel in the ladle drops to 1533℃ (below the threshold), the PID controller adjusts the water flow back to 19.8L / min to ensure that the cooling intensity matches the temperature.

[0031] Step S4, Continuous Improvement Monthly production data for this continuous casting machine is collected, including: billet quality data (surface crack rate of SUP9 steel is 0.5%, and center porosity is 0.8%), and equipment operation data (average cooling water consumption is 28m³). 3 / h, PLC stops without abnormality); Data analysis revealed that when the steel grade was changed to Q215 (low carbon steel), the water distribution using the original formula document increased the porosity of the billet center to 1.1%, indicating that the cooling intensity of the original water distribution curve was insufficient. Adjust the three-point parameters on the foot roller page, recalculate the parabolic coefficients a, b, and c, generate 22 new water volume values, save them as a new formula file, and download them to the PLC; After applying the new formulation, the center porosity of Q215 steel decreased to 0.3%, and the cooling water consumption decreased to 26m³. 3 / h, the optimization effect is significant.

[0032] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0033] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A secondary cooling water distribution curve visualization control method for a multi-strand billet continuous caster, characterized by, Comprising the following steps: Step S1, VBA programming and water distribution curve generation: using the embedded VBA programming of RSView32, inserting page controls and establishing at least three pages corresponding to the foot roller section, the first section and the second section of the multi-flow billet continuous casting machine, setting the X-axis of the water distribution curve as the casting speed and the Y-axis as the secondary cooling water flow, the casting speed value range is 0-4.4 m / min, and the X-axis is equally divided into 22 parts with an interval of 0.2 m / min, forming 23 fixed casting speed values, selecting three corresponding points (x1, y1), (x2, y2), (x3, y3) in any page, listing the equation group with a, b, c as unknown numbers based on the parabolic equation y=ax 2 +bx+c, solving the equation group to obtain the values of a, b and c, and then calculating the corresponding 22 secondary cooling water flow values according to the 23 fixed casting speed values, establishing a connection with the tag database in the RSView32 project through the gTagDb object, saving the 22 water flow values to the project formula file, and downloading the water flow values to the PLC processor; Step S2, PLC program calculation: the PLC processor receives the downloaded 22 corresponding values, in the actual casting process, the casting speed V is between two fixed casting speed values, then the following calculation is performed: Firstly, calculate V1=V×5, round V1 and assign the result to n; V1≥n, calculate Z = (V x 100 - n x 20) / 100, and then through Y = (Y X（n＋1） - Y Xn ) / 0.2 x Z + Y Xn to obtain the secondary cooling water setting value, wherein Y Xn is the water quantity corresponding to the nth fixed pulling speed value on the X axis, and Y X（n+1） is the water quantity corresponding to the n+1th fixed pulling speed value. V1 < n, calculate Z = [V x 100 - (n - 1) x 20] / 100, and then through Y = (Y Xn - Y X（n-1） ) / 0.2 x Z + Y Xn to get the secondary cooling water setting value, wherein Y X（n-1） is the water quantity corresponding to the n-1th fixed pulling speed value; Step S3, PID adjustment: realize PID control through programming, according to the real-time monitored tundish molten steel temperature and casting speed parameters of the multi-strand square billet continuous casting machine, automatically adjust the cooling water quantity of the foot roller section, the first section and the second section cooling area; Step S4, continuous improvement: periodically evaluate and optimize the secondary cooling water distribution program, collect the casting billet quality data and equipment operation data in the production process, adjust the water distribution parameters and control strategy combined with the production process improvement, equipment update and steel grade change.

2. The secondary cooling water distribution curve visualization control method for a multi-strand square billet continuous casting machine according to claim 1, characterized in that: In step S1, the three pages established by the page control are named as foot roller, first section and second section respectively.

3. The secondary cooling water distribution curve visualization control method for a multi-strand square billet continuous casting machine according to claim 1, characterized in that: In step S1, the equation set is: y1=ax1 2 +bx1+c y2=ax2 2 +bx2+c y3=ax3 2 +bx3+c.

4. The secondary cooling water distribution curve visualization control method for a multi-strand square billet continuous casting machine according to claim 3, characterized in that: Solving the equation set obtains: a=[y1-y2-(x1-x2)(y2x3 2 +y1x2 2 +y3x1 2 -y3x2 2 -y1x3 2 -y2x1 2 ) / (x2x3 2 +x1x2 2 +x3x1 2 -x3x2 2 -x1x3 2 -x2x1 2 ] / (x1 2 -x2 2 ) b = (y2x3 2 + y1x2 2 + y3x1 2 - y3x2 2 - y1x3 2 - y2x1 2 ) / (x2x3 2 + x1x2 2 + x3x1 2 - x3x2 2 - x1x3 2 - x2x1 2 ) c = y1 - x1 2 [y1 - y2 - (x1 - x2)(y2 - x3 2 + y1x2 2 + y3x1 2 - y3x2 2 - y1x3 2 - y2x1 2 )] / (x2 - x3 2 + x1x2 2 + x3x1 2 - x3x2 2 - x1x3 2 - x2x1 2 ) ] / (x1 2 - x2 2 - x1(y2 - x3 2 + y1x2 2 + y3x1 2 - y3x2 2 - y1x3 2 - y2x1 2 ) / (x2 - x3 2 + x1x2 2 + x3x1 2 - x3x2 2 - x1x3 2 - x2x1 2 ).

5. The secondary cooling water distribution curve visualization control method for a multi-strand square billet continuous casting machine according to claim 1, characterized in that: In step S3, the adjustment logic of the PID control is: When the real-time monitored tundish molten steel temperature is higher than the preset threshold value, increase the cooling water quantity of the corresponding cooling area; When the casting speed increases, increase the cooling water quantity of the corresponding cooling area.

6. The secondary cooling water distribution curve visualization control method for a multi-strand square billet continuous casting machine according to claim 1, characterized in that: In step S4, the casting billet quality data includes the casting billet surface crack rate and the center porosity rate, and the equipment operation data includes the cooling water consumption and the PLC operation state data.

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