Ladle refining alloying real-time cost optimization control method

Abstract

The invention discloses a steel ladle refining alloying real-time cost optimization control method. The method comprises the steps that the current steelmaking furnace number, the steel grade, the chemical component requirement of finished molten steel, the alloy type during steel grade refining, the converter smelting end point and information of materials added in the converter tapping process are obtained; calculating the amount of molten steel, the dynamic mean value of the yield of alloy elements in the refining period, the apparent yield of aluminum alloy in the refining period, constraint conditions of the desulfurization process in the refining period and chemical components of molten steel in the refining period; an alloy price management system and an alloy inventory management system are combined, and the optimal alloy proportion is obtained according to the full-caliber price, the warehousing price and the current market price defined in an enterprise; rules of component control early warning, component out-of-grid warning and alloy adding amount warning are established, when the alloy element components and the single alloy adding amount exceed the set upper limit and the set lower limit, abnormal trend early warning and abnormal data warning are generated, and an analysis report is obtained. The production cost of the alloy can be effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis and process control optimization in intelligent manufacturing in the metallurgical industry, and in particular to a real-time cost optimization control method for ladle refining and alloying. Background Art

[0002] At present, with the increasingly fierce market competition, the industry has noticed that the alloy cost can be saved by adjusting the ratio in the process of molten steel refining and alloying. However, due to the well-known fact in the industry: the process data of the molten steel refining process is very divergent and fluctuates greatly. The existing methods for optimizing alloy ratios are not satisfactory. From a methodological perspective, there are three categories: the first is to achieve a certain degree of optimization and improvement of the alloy ratio through manual data analysis by process personnel and judgment based on the analysis results plus a limited number of trial calculations. The limitation of this method is that the optimization degree of the ratio is limited and the labor input cost is relatively high; the second is to use mathematical optimization methods and establish corresponding mathematical models, but due to the complexity and variability of actual working conditions, more assumptions are made to the model, so that the reference value of the output results of the method becomes relatively limited; the third is to establish a relatively complete mathematical optimization model and model-related initial conditions and boundary conditions, but these initial conditions and boundary conditions are difficult to overcome in the process of defining them. The problem caused by the "drift" of these two types of conditions with the changes in time and space conditions (that is, slow changes with time and space changes) and the problem of partial missing (difficult to define) of the two types of conditions often caused by fluctuations in production rhythm. Summary of the invention

[0003] The purpose of the present invention is to provide a real-time cost optimization control method for ladle refining alloying, ensure the timeliness of the system output results, ensure that the system's optimized output results can be directly connected to the primary control system in real time, and realize an alloy ratio optimization system with industrial application level.

[0004] The present invention adopts the following technical solution: a real-time cost optimization control method for ladle refining alloying, comprising the following steps:

[0005] S1. Get the current steelmaking furnace number through dynamic query and rapid analysis result reporting system; determine the steel grade and chemical composition requirements of finished molten steel through process card management system; determine the alloy type during steel refining through system parameter configuration module.

[0006] S2. Obtain the converter smelting endpoint information through the secondary control system; obtain the material addition information during the converter steelmaking process through the production lean management system.

[0007] S3. Calculate the amount of molten steel based on the information from steps S1-S2.

[0008] S4. Based on the information from steps S1-S2, the dynamic mean of the alloy element yield during the refining period is calculated.

[0009] S5. Based on the information from steps S1-S2, calculate the apparent yield of aluminum alloy during refining.

[0010] S6. Based on the information from steps S1-S2, the constraints of the desulfurization process in the refining phase are obtained.

[0011] S7. Calculate the chemical composition of the molten steel during the refining period based on the information from steps S1-S2.

[0012] S8. Based on the calculation results of steps S3-S7, in combination with the alloy price management system and the alloy inventory management system, the optimal alloy ratio is obtained according to the full-caliber price, storage price and current market price defined within the enterprise.

[0013] S9. Establish rules for component control warning, component deviation warning and alloy addition warning. When the alloy element composition and the amount of a single alloy added exceed the set upper and lower limits, abnormal trend warnings and abnormal data alarms are generated, and analysis reports are obtained.

[0014] Furthermore, in step S2, the converter smelting endpoint information includes temperature, oxygen content and chemical composition; the material addition information during the converter steelmaking process includes metallic aluminum, other types of alloys, lime and tempering agents.

[0015] Further, in step S3, calculating the amount of molten steel includes the following:

[0016] The total amount of ingots produced in the workshop is obtained by using the rolling average method, converted into the total amount of molten steel, the total amount of molten iron added and the amount of scrap steel added are obtained, the metal recovery rates of molten iron and scrap steel are calculated, and the amount of molten steel is obtained.

[0017] Further, in step S4, calculating the dynamic mean of alloy element yield includes the following contents:

[0018] Select the data range and calculate the rolling mean R1av of the alloy element recovery rate with a time length of one period; perform multivariate linear regression on the alloy element data with a time length of two periods and calculate the rolling mean R2av of the recovery rate; calculate the multivariate linear regression mean R3av of the alloy element recovery rate with a time length of three periods.

[0019] Calculate the absolute value of the mean difference respectively. The specific formula is:

[0020] delta_R1=|R1av-Rav|

[0021] delta_R2=|R2av-Rav|

[0022] delta_R3=|R3av-Rav|

[0023] Among them, delta_R1, delta_R2 and delta_R3 represent the absolute values ​​of the mean differences of the first, second and third phases respectively, and Rav represents the actual amount of alloy added and the average of the actual alloy element yield obtained by sampling and analyzing the finished molten steel.

[0024] The weight coefficient is allocated according to the absolute value of the mean difference. The specific formula is:

[0025]

[0026]

[0027] Among them, W1, W2 and W3 represent the weight coefficients of the absolute values ​​of the mean differences of the first, second and third periods respectively.

[0028] The calculation formula of the dynamic mean R of alloy element recovery rate is:

[0029] R=W1*R1av+W2*R2av+W3*R3av.

[0030] Furthermore, in step S5, the apparent yield of aluminum alloy R AL The calculation formula is:

[0031]

[0032] Among them, W hotmetal Indicates the weight of molten iron added; W scrap Indicates the weight of scrap steel added; R metal-BOF Indicates the metal recovery rate of converter smelting; [%AL] LF-ARR Indicates the aluminum content of molten steel when the ladle arrives at the LF refining station; W AL[0] It indicates the amount of aluminum consumed by all the oxygen dissolved in the molten steel at the end of the converter. [% O] TSO Indicates the oxygen content of molten steel measured by the auxiliary gun at the end of blowing; W AL Indicates the weight of aluminum added to the steel.

[0033] Furthermore, in step S6, the desulfurization process during the refining period includes the initial sulfur content of the molten steel in the refining process, the sulfur content expected to be removed during the refining process, and the sulfur content expected to be removed during the refining process, and the corresponding constraints are:

[0034]

[0035] Where, [%S] TSO Indicates the sulfur content of the sample at the time of the secondary gun TSO measurement, W i Indicates the weight of the i-th alloying element added, [%S]i represents the sulfur content in the i-th alloy element, W molten-steel Indicates the weight of molten steel, delta_[%S] LF-DeS Indicates the sulfur content removed during the refining process, [%S] SPEC-UPPER It indicates the upper limit of sulfur content in finished molten steel, and n indicates the total number of alloying elements.

[0036] Further, in step S7, calculating the chemical composition of the molten steel includes the following contents:

[0037] Based on the dynamic mean of alloy element recovery rate, combined with the initial content of an element at steel tapping and the amount of alloy containing the element added, the content of the element at the refining station is obtained. The specific formula is:

[0038] [%E i ] ARR =[%E i ] TAP +delta_[%E i ] ALLOY

[0039] Among them, [%E i ] ARR represents the final composition of the ith alloy element at the refining station, [%E i ] TAP Indicates the composition of the i-th alloy element in the molten steel when the converter is tapped, delta_[%E i ] ALLOY It represents the composition change of the i-th alloying element in the molten steel after alloying in the converter.

[0040] Furthermore, in step S8, obtaining the optimal alloy ratio includes the following:

[0041] By solving the minimum value of the optimization function, the optimal alloy ratio is obtained; the specific formula of the optimization function and its constraints is:

[0042]

[0043] [%E i ] SPEC-LOWER <[%E i ] OPT <[%E i ] SPEC-UPPER

[0044] W ij >0

[0045] Where, f represents the optimization function; W ij P represents the weight of the jth alloy element added to the i-th alloy element; jrepresents the price of the jth alloy type; [%E i ] SPEC-LOWER Indicates the lower limit of the finished product specification of the i-th alloy element; [%E i ] OPT represents the content of the ith alloy element under the alloy cost optimization condition; [%E i ] SPEC-UPPER represents the upper limit of the finished product specification of the i-th alloy element; m represents the total number of alloy types.

[0046] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0047] The present invention is based on a method of real-time communication between the optimization model and the production system and between the model and the primary control system, thereby realizing the transmission of the model optimization results to the control system and the issuance of execution commands, and achieving direct guidance of alloying operations within a predetermined range of alloy types by outputting the optimized ratio results and transmitting them in real time to the primary operating system, thereby ultimately achieving the purpose of reducing alloy costs and increasing product profits. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is an overall implementation flow chart of the present invention.

[0049] Figure 2 It is an interface diagram of the alloying cost optimization control and analysis system of the present invention.

[0050] Figure 3 It is an interface diagram for monitoring and early warning of key process parameters of the present invention.

[0051] Figure 4 2 is a graph showing cost reduction results for different steel grades in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0053] To achieve the above object, the present invention proposes a real-time cost optimization control method for ladle refining alloying, such as Figure 1 As shown, the specific steps are as follows:

[0054] S1. Get the current steelmaking furnace number through dynamic query, rapid analysis result reporting system and related logical judgment; determine the steel grade and chemical composition requirements of finished molten steel through the data interface of the process card management system; determine the alloy type during steel refining through the system parameter configuration module.

[0055] S2. Through the data interface and related logical judgment of the secondary control system, the converter smelting endpoint information is obtained, which includes temperature, oxygen content and chemical composition; through the data interface and related logical judgment of the production lean management system, the material addition information during the converter steelmaking process is obtained, which includes metallic aluminum, other types of alloys, lime and tempering agents.

[0056] S3, based on the information of steps S1-S2, calculate the amount of molten steel; the specific content is:

[0057] The accurate calculation of the amount of molten steel has a direct impact on the accuracy of the results of the alloy optimization ratio calculation. Calculating the amount of molten steel is equivalent to calculating the metal recovery rate, that is, the metal recovery rate of molten iron and scrap steel.

[0058] The total amount of ingots produced in the workshop is obtained by the rolling average method, which is then converted into the total amount of molten steel. The total amount of molten iron added and the amount of scrap steel added are obtained. The metal recovery rates of molten iron and scrap steel are calculated to obtain the amount of molten steel.

[0059] S4. Based on the information of steps S1-S2, the dynamic mean of the alloy element recovery rate during the refining period is calculated; the specific content is:

[0060] During the alloying process, the accuracy of the yield of each alloying element directly affects the accuracy and use value of subsequent related calculation results. However, the yield fluctuates greatly and is affected by many factors.

[0061] Among the methods of achieving cost optimization by optimizing alloy ratios during alloying, the most core and difficult one is to obtain the accurate and reliable yield of different alloy elements. Under the current level of process control and rapid composition analysis technology, the yield of alloy elements fluctuates greatly between different furnaces. How to find a reliable value is the fundamental premise and guarantee for the reliability of the calculation results of alloy cost optimization.

[0062] The past 10 furnaces were selected as the data range, and the average recovery rate R1av of alloy elements in 365 days was calculated on a rolling basis. After performing multiple linear regression on the alloy element data of the time length corresponding to the first 50 furnaces, the rolling average recovery rate R2av was calculated. The multiple linear regression average R3av of the recovery rate of alloy elements in the time length corresponding to the first 10 furnaces was calculated.

[0063] Calculate the absolute value of the mean difference respectively. The specific formula is:

[0064] delta_R1=|R1av-Rav|

[0065] delta_R2=|R2av-Rav|

[0066] delta_R3=|R3av-Rav|

[0067] Among them, delta_R1, delta_R2 and delta_R3 represent the absolute values ​​of the mean differences of the first, second and third phases respectively, and Rav represents the actual amount of alloy added and the average of the actual alloy element yield obtained by sampling and analyzing the finished molten steel.

[0068] The weight coefficient is allocated according to the absolute value of the mean difference. The specific formula is:

[0069]

[0070]

[0071] Among them, W1, W2 and W3 represent the weight coefficients of the absolute values ​​of the mean differences of the first, second and third periods respectively.

[0072] The calculation formula of the dynamic mean R of alloy element recovery rate is:

[0073] R=W1*R1av+W2*R2av+W3*R3av.

[0074] S5. Based on the information from steps S1-S2, calculate the apparent yield of aluminum alloy during refining; the specific contents are:

[0075] Aluminum is a metal that must be used in the smelting and refining process of each furnace of steel. Its functions are: as a strong deoxidizer to remove dissolved oxygen in molten steel, and as one of the alloy components to meet the performance requirements of the final product. Due to the high chemical activity of aluminum, the yield rate varies greatly during use.

[0076] The recovery rate of aluminum added during the steel-making process is calculated separately, and the recovery rate during the refining process is calculated separately. In addition, for the accuracy of the calculation, the recovery rate of the aluminum element in the converter smelting part adopts the concept of apparent recovery rate, that is, it is considered that the recovery part includes aluminum Al that first dissolves into the molten steel but then reacts with oxygen O dissolved in the molten steel, generating aluminum oxide Al2O3 and floating to the slag layer in addition to the aluminum content in the molten steel composition at the refining station.

[0077] Converter aluminum alloy apparent yield R AL The calculation formula is:

[0078]

[0079] Among them, W hotmetal Indicates the weight of molten iron added, in tons; W scrap Indicates the weight of scrap steel added, in tons; R metal-BOF Indicates the metal recovery rate of converter smelting, [%AL] LF-ARR Indicates the aluminum content of molten steel arriving at the LF refining station from the ladle, in wt%; W AL[0]It indicates the amount of aluminum consumed by all the oxygen dissolved in the molten steel at the end of the converter, in tons; W AL Indicates the weight of aluminum added to the steel, in tons.

[0080] The chemical reaction between aluminum and oxygen dissolved in the molten steel at the end of the converter is:

[0081] 2[AL]+3[O]=(AL2O3).

[0082] Then W AL[0] The calculation formula is:

[0083]

[0084] Among them, [%O] TSO It indicates the oxygen content of molten steel measured by the auxiliary gun at the end of blowing.

[0085] S6. Based on the information from steps S1-S2, the constraints of the desulfurization process in the refining period are obtained; the specific contents are:

[0086] Sulfur is a harmful element for most types of steel, and the lower the content, the better. However, when calculating the optimized alloy ratio, it is necessary to take into account the sulfur content brought in by various alloys to ensure that the sulfur composition after alloying is within the range. So there is also a problem of determining the value of the sulfur recovery rate. The desulfurization process during the refining period includes the initial sulfur content of the molten steel, the sulfur content expected to be removed during the refining process, and the sulfur content expected to be removed during the refining process. The specific formula is:

[0087]

[0088] Where, [%S] TSO Indicates the sulfur content of the sample at the time of the secondary gun TSO measurement, W i Indicates the weight of the i-th alloying element added, in tons; [% S] i represents the content of sulfur in the i-th alloy element; W molten-steel Indicates the weight of molten steel in tons; delta_[%S] LF-DeS Indicates the sulfur content removed during the refining process, in wt%; [%S] SPEC-UPPER It indicates the upper limit of sulfur content in finished molten steel; n indicates the total number of alloying elements.

[0089] S7, based on the information of steps S1-S2, calculate the chemical composition of the molten steel during the refining period; the specific content is:

[0090] Due to the fast production pace and many changes, the sampling time when the ladle arrives at the refining station varies greatly, the success rate of sampling is difficult to guarantee, and the representativeness of the sampling is not strong, so the composition of the sample at the refining station is not suitable for direct use. In order to overcome this problem, based on the dynamic mean of the alloy element recovery rate, combined with the initial content of a certain element at the time of steelmaking and the amount of alloy containing the element added, the content of the element at the refining station is obtained. The specific formula is:

[0091] [%E i ] ARR =[%E i ] TAP +delta_[%E i ] ALLOY

[0092] Among them, [%E i ] ARR represents the final composition of the ith alloy element at the refining station, [%E i ] TAP Indicates the composition of the i-th alloy element in the molten steel when the converter is tapped, delta_[%E i ] ALLOY It represents the composition change of the i-th alloying element in the molten steel after alloying in the converter.

[0093] S8. Based on the calculation results of steps S3-S7, in combination with the alloy price management system and the alloy inventory management system, the optimal alloy ratio is obtained according to the full-caliber price, storage price and current market price defined within the enterprise; the specific contents are:

[0094] By solving the minimum value of the optimization function, the optimal alloy ratio is obtained; the specific formula of the optimization function and its constraints is:

[0095]

[0096] [%E i ] SPEC-LOWER <[%E i ] OPT <[%E i ] SPEC-UPPER

[0097] W ij >0

[0098] Where, f represents the optimization function; W ij It represents the weight of the jth alloy type added to the i-th alloy element, in tons; P j Indicates the price of the jth alloy type, in yuan / ton; [%E i ] SPEC-LOWERIndicates the lower limit of the finished product specification of the i-th alloy element, in wt%; [%E i ] OPT represents the content of the i-th alloy element under the alloy cost optimization condition, in wt%; <[%E i ] SPEC-UPPER It represents the upper limit of the finished product specification of the i-th alloy element, in wt%; m represents the total number of alloy types.

[0099] S9, such as Figure 2 As shown, the optimal alloy ratio is transmitted to the primary control system, and the primary control system continuously reads the latest results in the database at set time intervals, and issues operation instructions after being reviewed by the alloying operator.

[0100] S10, recording the actual amount of alloy added by the operator in front of the furnace and the recommended value of the amount of alloy added obtained by calculation, and comparing and analyzing the two sets of data. On the one hand, the actual operation of the operator can be known, providing timely information for production management; on the other hand, the difference in the effects of the two sets of data can be compared according to the alloy element composition of the finished molten steel, and the calculation process of steps S3-S7 can be optimized.

[0101] S11, such as Figure 3 As shown, the rules for component control warning, component deviation warning and alloy addition warning are established. When the alloy element composition and the amount of a single alloy added exceed the set upper and lower limits, an abnormal trend warning and abnormal data alarm are generated, and an analysis report is obtained.

[0102] like Figure 4 As shown in Table 1, the method proposed by the present invention significantly reduces the alloy cost consumed by alloying by 4-25%.

[0103] Table 1 Steel types and respective statistical furnace numbers for cost optimization benefits

[0104] Steel grade code Grade_1 Grade_2 Grade_3 Grade_4 Grade_5 Grade_6 Grade_7 Grade_8 Grade_9 Statistical furnace number 155 94 156 7 74 52 13 10 33

[0105] The method proposed in the present invention provides a very valuable tool for alloying operation in the refining process of molten steel in a steelmaking workshop, so that the alloy ratio in the alloying process can be continuously and dynamically optimized and adjusted according to the actual production situation at that time, and the recommended values ​​of various alloy addition amounts are directly given and automatically transmitted to the operation interface of the first-level operating system in front of the furnace for use by operators. The use of this system not only standardizes and simplifies the alloying operation, but also facilitates production management and process quality management, and stabilizes the process.

[0106] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A real-time cost optimization control method for ladle refining alloying, characterized in that: include: S1. Get the current steelmaking furnace number through dynamic query and rapid analysis result reporting system; determine the steel grade and chemical composition requirements of finished molten steel through process card management system; Determine the alloy type during steel refining through the system parameter configuration module; S2. Obtain the converter smelting endpoint information through the secondary control system; obtain the material addition information during the converter steelmaking process through the production lean management system; S3, calculating the amount of molten steel based on the information of steps S1-S2; S4, based on the information of steps S1-S2, calculating the dynamic mean of the alloy element recovery rate during the refining period; S5. Calculate the apparent yield of aluminum alloy during refining based on the information of steps S1-S2; S6. Based on the information from steps S1-S2, obtain the constraints of the desulfurization process during the refining period; S7, calculating the chemical composition of the molten steel during the refining period based on the information from steps S1-S2; S8. Based on the calculation results of steps S3-S7, in combination with the alloy price management system and the alloy inventory management system, the optimal alloy ratio is obtained according to the full-caliber price, storage price and current market price defined within the enterprise; S9. Establish rules for component control warning, component deviation warning and alloy addition warning. When the alloy element composition and the amount of a single alloy added exceed the set upper and lower limits, abnormal trend warnings and abnormal data alarms are generated, and analysis reports are obtained.

2. The real-time cost optimization control method for ladle refining alloying according to claim 1, characterized in that: In step S2, the converter smelting endpoint information includes temperature, oxygen content and chemical composition; the material addition information during the converter steelmaking process includes metallic aluminum, other types of alloys, lime and tempering agents.

3. The real-time cost optimization control method for ladle refining alloying according to claim 1, characterized in that: In step S3, calculating the amount of molten steel includes the following: The total amount of ingots produced in the workshop is obtained by using the rolling average method, converted into the total amount of molten steel, the total amount of molten iron added and the amount of scrap steel added are obtained, the metal recovery rates of molten iron and scrap steel are calculated, and the amount of molten steel is obtained.

4. The real-time cost optimization control method for ladle refining alloying according to claim 1, characterized in that: In step S4, calculating the dynamic mean of alloy element yield includes the following contents: Select the data range, and calculate the average R1av of the alloy element recovery rate with a rolling time length of one period; perform multivariate linear regression on the alloy element data with a time length of two periods, and calculate its rolling average R2av of the recovery rate; calculate the multivariate linear regression average R3av of the alloy element recovery rate with a time length of three periods; Calculate the absolute value of the mean difference respectively. The specific formula is: delta_R1=|R1av-Rav| delta_R2=|R2av-Rav| delta_R3=|R3av-Rav| Among them, delta_R1, delta_R2 and delta_R3 represent the absolute values ​​of the mean differences of the first, second and third phases, respectively, and Rav represents the actual amount of alloy added and the average of the actual alloy element recovery rate obtained by sampling and analyzing the finished molten steel; The weight coefficient is allocated according to the absolute value of the mean difference. The specific formula is: Among them, W1, W2 and W3 represent the weight coefficients of the absolute values ​​of the mean differences of the first, second and third periods respectively; The calculation formula of the dynamic mean R of alloy element recovery rate is: R=W1*R1av+W2*R2av+W3*R3av.

5. The real-time cost optimization control method for ladle refining alloying according to claim 1, characterized in that: In step S5, the apparent yield of aluminum alloy R AL The calculation formula is: Among them, W hotmetal Indicates the weight of molten iron added; W scrap Indicates the weight of scrap steel added; R metal-BOF Indicates the metal recovery rate of converter smelting; [%AL] LF-ARR Indicates the aluminum content of molten steel when the ladle arrives at the LF refining station; W AL[0] It indicates the amount of aluminum consumed by all the oxygen dissolved in the molten steel at the end of the converter. [% O] TSO Indicates the oxygen content of molten steel measured by the auxiliary gun at the end of blowing; W AL Indicates the weight of aluminum added to the steel.

6. The real-time cost optimization control method for ladle refining alloying according to claim 1, characterized in that: In step S6, the desulfurization process during the refining period includes the initial sulfur content of the molten steel during refining, the sulfur content expected to be removed during the refining process, and the sulfur content expected to be removed during the refining process. The corresponding constraints are: Where, [%S] TSO Indicates the sulfur content of the sample at the time of the secondary gun TSO measurement, W i Indicates the weight of the i-th alloying element added, [%S] i represents the sulfur content in the i-th alloy element, W molten-steel Indicates the weight of molten steel, delta_[%S] LF-DeS Indicates the sulfur content removed during the refining process, [%S] SPEC-UPPER It indicates the upper limit of sulfur content in finished molten steel, and n indicates the total number of alloying elements.

7. The real-time cost optimization control method for ladle refining alloying according to claim 1, characterized in that: In step S7, calculating the chemical composition of molten steel includes the following contents: Based on the dynamic mean of alloy element recovery rate, combined with the initial content of an element at steel tapping and the amount of alloy containing the element added, the content of the element at the refining station is obtained. The specific formula is: [%AND i ] ARR =[%And i ] TAP +delta_[%E i ] ALLOY Among them, [%E i ] ARR represents the final composition of the ith alloy element at the refining station, [%E i ] TAP Indicates the composition of the i-th alloy element in the molten steel when the converter is tapped, delta_[%E i ] ALLOY It represents the composition change of the i-th alloying element in the molten steel after alloying in the converter.

8. The real-time cost optimization control method for ladle refining alloying according to claim 1, characterized in that: In step S8, obtaining the optimal alloy ratio includes the following: By solving the minimum value of the optimization function, the optimal alloy ratio is obtained; the specific formula of the optimization function and its constraints is: [%AND i ] SPEC-LOWER <[%And i ] OPT <[%And i ] SPEC-UPPER W ij >0 Where f represents the optimization function; W ij P represents the weight of the jth alloy element added to the i-th alloy element; j represents the price of the jth alloy type; [%E i ] SPEC-LOWER Indicates the lower limit of the finished product specification of the i-th alloy element; [%E i ] OPT represents the content of the ith alloy element under the alloy cost optimization condition; [%E i ] SPEC-UPPER It represents the upper limit of the finished product specification of the i-th alloy element; n represents the total number of alloy elements; m represents the total number of alloy types.

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