Prediction method for phosphorus content in dry quenching chemical coke, electronic equipment and storage medium

Abstract

The invention discloses a method for predicting the content of phosphorus in dry quenching chemical coke, electronic equipment and a storage medium, and the method comprises the steps: obtaining coal ash component data of at least one single coal, and calculating the total phosphorus content of each single coal according to the content of phosphorus pentoxide in the coal ash component; industrial analysis ash content data of each single coal is obtained, coal ash content of each single coal is obtained, and a coking ash content coefficient model of the single coal is established to predict coke ash content of the single coal; based on the total phosphorus content of the single coal and the coke ash content of the single coal, calculating to obtain the total phosphorus of the coking coke of the single coal; and according to the blending proportion of each single coal in the target coal blending scheme and the total phosphorus content in the coke ash after the corresponding single coal is coked, calculating the total phosphorus content in the dry quenching coke after the coal blending scheme is coked by weighting calculation and combining the calibration coefficient. According to the scheme, the phosphorus content of different coal blending schemes after coking can be accurately predicted in advance, and the problems that detection data is lagged, and the chemical pyrophosphorus content is high and unstable are solved.

Description

Technical Field

[0001] This application generally relates to the field of coking process technology. More specifically, this application relates to a method, electronic device, and storage medium for predicting the phosphorus content in dry-quenched coke. Background Technology

[0002] Dry-quenched coke is an important carbonaceous reducing agent and exothermic agent in the production of high-end ferroalloys such as high-carbon ferrochrome, high-silicon ferroalloys, and high-carbon ferromanganese. These downstream smelting processes have extremely stringent requirements for the phosphorus (P) content in the coke, because phosphorus, as a harmful impurity, is easily reduced into the alloy during smelting, severely affecting the cold brittleness and processing properties of the final steel. For example, in the smelting of high-silicon ferroalloys, phosphorus pentoxide in the coke ash is reduced into ferrosilicon, reducing product purity; in the blast furnace smelting of high-carbon ferromanganese, due to the large amount of coke added and the relatively low furnace temperature, little phosphorus volatilizes, and most of it is transferred into the alloy, thus the phosphorus content of the coke fed into the furnace is particularly strictly limited.

[0003] Currently, the industry mainly relies on two methods to control the phosphorus content of dry-quenched coke: First, it uses manual experience to formulate so-called low-phosphorus coal blending schemes, lacking systematic scientific basis, resulting in poor predictive accuracy and an inability to quantify and assess the content. Second, it obtains actual phosphorus content data through chemical testing methods after coke production. The former is limited and unstable due to the limitations of experience, making it difficult to guarantee consistent product quality and find the optimal balance between phosphorus content compliance and raw material costs. The latter suffers from significant lag; when test results are unqualified, the entire batch of coke has already been produced and can only be treated as substandard or sold at a reduced price, causing huge economic losses and resource waste.

[0004] In view of this, there is an urgent need to provide a method, electronic equipment and storage medium for predicting the phosphorus content in dry-quenched coke, so as to accurately predict the phosphorus content of coke before coal blending, thereby guiding the optimization of coal blending scheme. Summary of the Invention

[0005] In order to at least solve one or more of the technical problems mentioned above, this application proposes a method, electronic equipment and storage medium scheme for predicting the phosphorus content in dry-quenched chemical coke before coal blending in several aspects.

[0006] In a first aspect, this application provides a method for predicting the phosphorus content in dry-quenched coke, comprising the following steps: obtaining ash composition data of at least one type of coal, and calculating the total phosphorus content P of each type of coal based on the phosphorus pentoxide content in the ash composition; obtaining industrial analysis ash content data of each type of coal, and obtaining the ash content Ad of each type of coal through coking tests, and establishing a coking ash content coefficient model for each type of coal based on this to predict the coke ash content Adi of the single coal; calculating the total phosphorus content Pi of the coke from the single coal based on the total phosphorus content P and the coke ash content Adi of the single coal; and calculating the total phosphorus content Pi of the coke from the single coal based on the blending ratio W of each type of coal in the target coal blending scheme. i The total phosphorus content Pi in the coke ash after coking from the single type of coal is calculated by weighted calculation and combined with calibration coefficient A, and the total phosphorus content P in the dry-quenched coke after coking from the coal blending scheme is obtained. 总 .

[0007] In some embodiments, the total phosphorus content P of the single type of coal is obtained by the following formula: P = phosphorus pentoxide content 0.437; where 0.437 is the mass percentage of phosphorus in phosphorus pentoxide.

[0008] In some embodiments, the ash content Adi of a single type of coal coke is obtained by the following formula: Adi = Adi K; where K is the coking ash coefficient of the single type of coal determined by fitting through coking experiments.

[0009] In some embodiments, the coking ash coefficient K is obtained by testing multiple single coal samples through a 40Kg load small coke oven test and by fitting the correspondence between the industrial analysis ash content of each single coal and its coking ash content.

[0010] In some embodiments, the coking ash content coefficient K is obtained by the following formula:

[0011] Vdaf is the volatile matter of a single type of coal.

[0012] In some embodiments, the total phosphorus Pi of the single-type coal coke is obtained by the following formula: Pi = P Adi.

[0013] In some embodiments, the total phosphorus content P in the dry-quenched coke after coking 总 It is obtained through the following formula: Where A is the calibration coefficient obtained through calibration using actual production data.

[0014] In some embodiments, the calibration coefficient A is determined through the following steps: collecting actual production data from multiple historical coal blending schemes, obtaining the actual total phosphorus content detection value of coke corresponding to each scheme; and predicting and calculating the total phosphorus content P in dry-quenched coke for each historical coal blending scheme. 总 Linear regression analysis is performed on the actual detected value and the predicted calculated value to determine the best fitting coefficient between them as the calibration coefficient A.

[0015] In a second aspect, this application provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the program, implements the method for predicting the phosphorus content in dry-quenched coke as described above.

[0016] In a third aspect, this application provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the program is executed by a processor, it implements the method for predicting the phosphorus content in dry-quenched coke as described above.

[0017] This application's solution obtains ash composition data for a single type of coal and calculates the total phosphorus content based on its phosphorus pentoxide content. It achieves accurate calculation based on the fixed mass percentage of phosphorus in phosphorus pentoxide, providing a reliable foundation for subsequent predictions. This avoids the data lag problem of traditional post-coking testing from the source. By acquiring industrial analysis ash content data for a single type of coal, it quantifies the ash content change pattern from coal to coke, achieving accurate prediction of coke ash content for that single type of coal. This replaces the crude method of traditional manual experience-based judgment, improving the maturity and reliability of predictions. Furthermore, based on the total phosphorus content and coke ash content of a single type of coal, it calculates the total phosphorus in the coke produced from that coal, clarifying the intrinsic relationship between the two and quantifying the actual phosphorus content after coking, providing solid data support for predicting total phosphorus in coal blending. On this basis, by combining the blending ratio of each single type of coal in the target coal blending scheme and its corresponding total phosphorus in the coke produced, a weighted calculation is performed and a calibration coefficient is incorporated to finally obtain the total phosphorus content of the dry-quenched chemical coke after coking in the coal blending scheme. This supports flexible blending of different priced coal types while ensuring phosphorus content meets standards, achieving optimal cost. Attached Figure Description

[0018] The above and other objects, features, and advantages of exemplary embodiments of this application will become readily understood by reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of this application are illustrated by way of example and not limitation, and the same or corresponding reference numerals denote the same or corresponding parts, wherein: Figure 1 A flowchart illustrating the method for predicting phosphorus content in dry-quenched coke according to an embodiment of this application is shown. Figure 2 An exemplary structural block diagram of an electronic device according to some embodiments of this application is shown. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] It should be understood that the terms "comprising" and "including" used in the specification and claims of this application indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0021] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application. As used in this specification and claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this specification and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0022] As used in this specification and claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0023] The specific embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0024] like Figure 1As shown, in some embodiments, this application provides a method for predicting the phosphorus content in dry-quenched coke, comprising the following steps: obtaining ash composition data of at least one type of coal, and calculating the total phosphorus content P of each type of coal based on the phosphorus pentoxide content in the ash composition; obtaining industrial analysis ash content data of each type of coal, and obtaining the ash content Ad of each type of coal through coking tests, and establishing a coking ash content coefficient model for each type of coal based on this to predict the coke ash content Adi of the single coal; calculating the total phosphorus content Pi of the coke from the single coal based on the total phosphorus content P and the coke ash content Adi of the single coal; and calculating the total phosphorus content Pi of the coke from the single coal based on the blending ratio W of each type of coal in the target coal blending scheme. i The total phosphorus content Pi in the coke ash after coking from the single type of coal is calculated by weighted calculation and combined with calibration coefficient A, and the total phosphorus content P in the dry-quenched coke after coking from the coal blending scheme is obtained. 总 .

[0025] In this application, the specific steps of the method for predicting the phosphorus content in dry-quenched coke are as follows: First, obtain the ash composition data of at least one type of coal, and calculate the total phosphorus content P of each type of coal based on the phosphorus pentoxide content in the ash composition. It is worth noting that this calculation logic is based on the fixed mass ratio of phosphorus in phosphorus pentoxide. Second, obtain the industrial analysis ash content data of each type of coal, and obtain the ash content Ad after coking of each type of coal through coking experiments. Based on the coefficient relationship between the industrial analysis ash content and the ash content after coking, establish a coking ash content coefficient model for each type of coal, and then predict the coke ash content Adi of each type of coal using this model. Next, based on the obtained total phosphorus content P of each type of coal and the predicted coke ash content Adi of each type of coal, calculate the total phosphorus content Pi of the coke after coking of each type of coal, thereby quantifying the actual phosphorus content in the coke ash after coking of each type of coal. Finally, for the target coal blending scheme, combining the blending ratio Wi of each type of coal in the scheme, and the total phosphorus content Pi of the coke ash after coking corresponding to each type of coal, a weighted calculation is first performed based on the blending ratio, and then combined with the calibration coefficient A (which reflects the relationship between the predicted data of total phosphorus in coke ash after coking and the actual test data of the coal blending scheme), the total phosphorus content in the dry-quenched coke after coking of the coal blending scheme is finally calculated, providing a reliable basis for the optimization and adjustment of the coal blending scheme.

[0026] This application's solution achieves accurate prediction of phosphorus content in dry quenching chemical coke through a four-step sequential system. It constructs a comprehensive optimization mechanism from basic data acquisition to phosphorus content prediction in coal blending schemes, bringing multiple core benefits. First, by acquiring ash composition data for individual coal types and calculating the total phosphorus content based on phosphorus pentoxide content, accurate calculation is completed based on the fixed mass percentage of phosphorus in phosphorus pentoxide, providing a reliable foundation for subsequent predictions and avoiding the data lag problem of traditional post-coke testing. Second, by acquiring industrial analysis ash content data for individual coal types, the ash content change pattern from coal to coke is quantified, achieving accurate prediction of coke ash content for individual coal types. This replaces the extensive mode of traditional manual experience-based judgment, improving the maturity and reliability of prediction. Furthermore, based on the total phosphorus content and coke ash content of individual coal types, the total phosphorus in the coke formed from individual coal types is calculated, clarifying the intrinsic relationship between the two and quantifying the actual phosphorus content after coking, providing solid data support for predicting total phosphorus in coal blending. Based on this, by combining the proportion Wi of each type of coal in the target coal blending scheme and its corresponding total phosphorus in coking Pi, and by weighting and incorporating the calibration coefficient A, the total phosphorus content of the dry-quenched coke after coking in the coal blending scheme is finally obtained. This supports the flexible combination of different coal types with different prices under the premise that the phosphorus content meets the standard, so as to achieve the optimal cost.

[0027] This solution accurately predicts the phosphorus content of coke after different coal blending schemes in advance, solving the problems of lack of systematic prediction methods before coal blending, lagging detection data, and high and unstable phosphorus content in chemical coke in existing technologies. This solution fully meets the stringent requirements of high-carbon ferrochrome, high-silicon ferroalloy, and high-carbon ferromanganese alloy plants.

[0028] In one specific implementation, the total phosphorus content P of the single type of coal is obtained by the following formula: P = phosphorus pentoxide content 0.437; where 0.437 is the mass percentage of phosphorus in phosphorus pentoxide.

[0029] In the scheme of this application, the total phosphorus content P of a single type of coal is calculated through a clear quantitative formula. The specific calculation formula is P = content of phosphorus pentoxide × 0.437, where the coefficient 0.437 comes from the mass ratio of phosphorus element in phosphorus pentoxide. The calculation logic is based on the fixed relationship between the atomic weight of elements and the molecular weight of compounds: the atomic weight of phosphorus (P) is 31, the atomic weight of oxygen (O) is 16, and the molecular weight of phosphorus pentoxide is 31×2 + 16×5 = 142. Therefore, the mass ratio of phosphorus element in phosphorus pentoxide is (31×2) / 142 = 0.437. Through this formula, the total phosphorus content of the corresponding single type of coal can be accurately deduced directly from the phosphorus pentoxide content obtained by detecting the coal ash composition of the single type of coal.

[0030] In one specific implementation, the ash content Adi of the single type of coal coke is obtained by the following formula: Adi = Ad K; where K is the coking ash coefficient of the single type of coal determined by fitting through coking tests. The coking ash coefficient K was obtained by testing multiple single-type coal samples through a 40kg load small coke oven test, and by fitting the correspondence between the industrial analysis ash content of each single type of coal and its ash content after coking. The coking ash coefficient K is obtained by the following formula: Vdaf is the volatile matter of a single type of coal.

[0031] In the scheme of this application, the ash content Adi of a single type of coal coke is calculated using a specific quantitative formula, namely Adi=Ad K, where Ad represents the ash content value obtained from industrial analysis of the single type of coal, and K is the coking ash coefficient corresponding to the single type of coal. The determination of this coking ash coefficient K is based on a 40kg load small coke oven test. Multiple single-type coal samples were tested separately, and the industrial analysis ash content data and the ash content data after coking were obtained for each sample. Then, the correspondence between these two sets of data was fitted to finally obtain the coking ash coefficient K, which reflects the ash content change law of this type of single coal during the coal-to-coke process. Specifically, the coking ash coefficient K is obtained through the following formula: It is worth noting that the volatile matter Vdaf, like Ad, is obtained from industrial analysis of a single type of coal.

[0032] In one specific implementation scheme, the total phosphorus Pi of the single-type coal coke is obtained by the following formula: Pi = P Adi.

[0033] In this application, the total phosphorus content (Pi) of coke from a single type of coal is calculated using a specific quantitative formula: Pi = P × Adi. Each parameter is based on core data obtained from the aforementioned calculation model. Here, P represents the total phosphorus content of the single type of coal, calculated using the first calculation model. This is achieved by detecting the phosphorus pentoxide content in the coal ash of the single type of coal and then extrapolating it based on the mass percentage of phosphorus in phosphorus pentoxide (0.437). Adi represents the ash content of the coke from the single type of coal, obtained by multiplying the industrial analysis ash content data of the single type of coal by the coking ash coefficient K determined through fitting experiments on a 40kg load small coke oven. This formula establishes a correlation between the total phosphorus content of a single type of coal and the ash content of the coke after coking, accurately quantifying the actual total phosphorus content in the coke ash of the coke after coking from a single type of coal. This provides crucial single-coal data support for the calculation of total phosphorus in coke for subsequent coal blending schemes.

[0034] In one specific implementation, the total phosphorus content P in the dry-quenched coke after coking is... 总 It is obtained through the following formula: Wherein, A is the calibration coefficient obtained through calibration using actual production data. The calibration coefficient A is determined through the following steps: collecting actual production data from multiple historical coal blending schemes, obtaining the actual total phosphorus content detection value of the coke corresponding to each scheme; for each historical coal blending scheme, predicting and calculating the total phosphorus content P in the dry-quenched coke. 总 Linear regression analysis is performed on the actual detected value and the predicted calculated value to determine the best fitting coefficient between them as the calibration coefficient A.

[0035] In this application, the total phosphorus content P_total in the dry-quenched coke after coking is calculated using a specific quantitative formula, namely P = (ΣW_total) / (ΣW_total) i ×P i ) / ΣW i + A. Where P represents the total phosphorus in the coke ash after coking according to the coal blending scheme, and W... i P represents the proportion of each type of coal in the target coal blending scheme. i The total phosphorus in coke ash represents the total phosphorus in coke produced from each type of coal. A is a calibration coefficient, which is a numerical value reflecting the relationship between the predicted total phosphorus in coke ash after coking by the coal blending scheme and the actual measured total phosphorus in coke after coking by the coal blending scheme. This coefficient is obtained by calibration through actual production data.

[0036] The determination process for calibration coefficient A is as follows: First, actual production data from multiple historical coal blending schemes are collected to obtain the actual total phosphorus content detection value of the coke corresponding to each historical scheme. Then, for each historical coal blending scheme, the predicted total phosphorus content of the dry-quenched coke is calculated. Finally, linear regression analysis is performed on the collected actual detection values ​​and corresponding predicted values ​​of each historical scheme to determine the best fitting coefficient that accurately reflects the correlation between the two; this coefficient is the calibration coefficient A. By integrating the blending ratio of each type of coal with the coke phosphorus content data using this formula, and combining it with the coefficient A calibrated from actual production data, the total phosphorus content in the dry-quenched coke after coking by the coal blending scheme can be accurately calculated.

[0037] To illustrate the above solution more clearly, the following example will be used: Suppose a coking plant needs to develop a coal blending scheme for dry-quenched coke, selecting three single coal types (coal type 1, coal type 2, and coal type 3) for blending. The specific application of the above formula to calculate the total phosphorus content of the dry-quenched coke is as follows: Step 1: Determine the values ​​of each parameter in the coal blending scheme. The proportion of single coal type (Wi): According to the production plan, the proportions of the three single coal types are as follows: coal type 1 (W1) = 30% (0.3), coal type 2 (W2) = 40% (0.4), and coal type 3 (W3) = 30% (0.3). Therefore, ΣWi = 0.3 + 0.4 + 0.3 = 1.0.

[0038] Total phosphorus (Pi) in coke from a single type of coal: Calculated using the third calculation model of this patent (Pi=P×Adi): Coal type 1 (P1) = 0.08%, Coal type 2 (P2) = 0.06%, Coal type 3 (P3) = 0.07% (where P is the total phosphorus content of a single type of coal, and Adi is the ash content of coke from a single type of coal, both obtained through the previous model).

[0039] Step 2: Calculate the baseline forecast value (ΣW) i ×P i ) / ΣWi Substitute the above parameters into the first part of the formula to calculate the uncalibrated baseline prediction: ΣW i ×P i = (0.3 × 0.08%) + (0.4 × 0.06%) + (0.3 × 0.07%) = 0.024% + 0.024% + 0.021% = 0.069% Basic forecast value = (ΣW) i ×P i ) / ΣWi =0.069% / 1.0=0.069% Step 3: Determine the calibration coefficients: The calibration coefficient A was obtained through linear regression analysis of historical production data, as follows: Historical data collection: Five historical coal blending schemes that have been completed in production were selected, and the basic predicted values ​​and actual measured values ​​for each scheme were recorded. The data is shown in the table below:

[0040] Linear regression analysis: A linear regression was performed on the baseline predicted value and the actual detected value, and the relationship between the two was found to be: actual detected value = baseline predicted value + 0.001%. Therefore, the best fit coefficient reflecting the relationship between the predicted data and the actual detected data is the calibration coefficient A = 0.001% (this coefficient has been verified through multiple sets of historical data to ensure stability and accuracy).

[0041] Step 4: Calculate the final P 总 : Substitute the base prediction value and the calibration coefficient A into the complete formula: P 总 =(ΣW i ×P i) / ΣWi + A =0.069% + 0.001%=0.070% In summary, the predicted total phosphorus content of the dry-quenched coke produced by this coal blending scheme is 0.070%.

[0042] Correspondingly, embodiments of this application also provide hardware structure diagrams, specifically as follows: Figure 2 As shown, the electronic device 200 can be an apparatus for implementing the above-described method 100 for predicting the phosphorus content in dry-quenched coke. Figure 2 As shown, the electronic device 200 includes a processor 210 and a memory 220. The memory 220 is configured to store program instructions; the processor 210 is configured to load and execute the program instructions stored in the memory 220 to implement an embodiment of the method 100 for predicting the phosphorus content in dry-quenched coke as shown above.

[0043] As one embodiment, memory 220 can be any electronic, magnetic, optical, or other physical storage device that can contain or store information such as program instructions, data, etc. For example, memory 220 can be volatile memory, non-volatile memory, or similar storage media. Specifically, memory 220 can be RAM (Random Access Memory), flash memory, storage drives (such as hard disk drives), solid-state drives, any type of storage disk (such as optical discs, DVDs, etc.), or similar storage media, or combinations thereof.

[0044] This concludes the process. Figure 2 Description of the electronic device shown.

[0045] While numerous embodiments of this application have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will arise for those skilled in the art without departing from the spirit and intent of this application. It should be understood that various alternatives to the embodiments of this application described herein may be employed in the practice of this application. The appended claims are intended to define the scope of protection of this application and therefore cover equivalents or alternatives within the scope of these claims.

Claims

1. A method for predicting the phosphorus content in dry-quenched chemical coke, characterized in that, Includes the following steps: Obtain the ash composition data of at least one type of coal, and calculate the total phosphorus content P of each type of coal based on the phosphorus pentoxide content in the ash composition. Industrial analysis ash content data of each type of coal were obtained, and the ash content Ad of each type of coal was obtained through coking tests. Based on this, a coking ash content coefficient model for each type of coal was established to predict the coke ash content Adi of each type of coal. Based on the total phosphorus content P of the single type of coal and the ash content Adi of the single type of coal coke, the total phosphorus Pi of the coke of the single type of coal is calculated. According to the proportion of each type of coal in the target coal blending scheme W i The total phosphorus content Pi in the coke ash after coking from the single type of coal is calculated by weighted calculation and combined with calibration coefficient A, and the total phosphorus content P in the dry-quenched coke after coking from the coal blending scheme is obtained. 总 .

2. The prediction method according to claim 1, characterized in that, The total phosphorus content P of the single type of coal is obtained by the following formula: P = Phosphorus pentoxide content 0.437; Where 0.437 represents the mass percentage of phosphorus in phosphorus pentoxide.

3. The prediction method according to claim 2, characterized in that, The ash content Adi of a single type of coal coke is obtained by the following formula: Ash content of a single type of coal (Adi) = Ash content of a single type of coal (Ad) K; Wherein, K is the coking ash coefficient of the single type of coal determined by fitting through coking experiments.

4. The prediction method according to claim 3, characterized in that, The coking ash content coefficient K was obtained by testing multiple single coal samples through a 40Kg load small coke oven test, and by fitting the correspondence between the industrial analysis ash content of each single coal and its coking ash content.

5. The prediction method according to claim 4, characterized in that, The coking ash content coefficient K is obtained by the following formula: ； Vdaf is the volatile matter of a single type of coal.

6. The prediction method according to claim 3 or 4, characterized in that, The total phosphorus Pi in the coke from a single type of coal is obtained by the following formula: Pi=P Adi.

7. The prediction method according to claim 1, characterized in that, The total phosphorus content (P) in the dry-quenched coke after coking 总 It is obtained through the following formula: ； Where A is the calibration coefficient obtained through calibration using actual production data.

8. The prediction method according to claim 7, characterized in that, The calibration coefficient A is determined through the following steps: Collect actual production data from multiple historical coal blending schemes and obtain the actual total phosphorus content of coke corresponding to each scheme. For each historical coal blending scheme, the total phosphorus content (P) in the dry-quenched coke is predicted and calculated. 总 ; Linear regression analysis is performed on the actual detected value and the predicted calculated value to determine the best fitting coefficient between them as the calibration coefficient A.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for predicting the phosphorus content in dry-quenched coke as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method for predicting the phosphorus content in dry-quenched coke as described in any one of claims 1 to 8.

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