Method and device for determining the control range of a cement raw material mine limestone indicator

Abstract

This application discloses a method and apparatus for determining the control range of limestone indicators in cement raw material mines. The method includes: acquiring raw material indicator data and fuel indicator data; receiving pre-configured extreme values ​​of clinker and limestone indicators; constructing a mathematical model for determining the control range of limestone indicators; calculating the values ​​of the objective function corresponding to the values ​​of different decision variables in the mathematical model under the condition of satisfying the constraints; obtaining the values ​​of the objective function as the values ​​of each decision variable under the optimal condition; and using the values ​​of each decision variable under the optimal condition as the solution result of the data model. This application solves the problems existing in the methods for determining the control range of limestone indicators in the prior art, thereby enabling rapid and accurate determination of the control range of limestone indicators in cement raw material mines.

Description

Technical Field

[0001] This application relates to the field of cement raw material mine production and quality control, specifically to a method and apparatus for determining the control range of limestone indicators in cement raw material mines. Background Technology

[0002] In cement manufacturing, it is necessary to calculate the proportions of each raw material based on the limestone indicators provided by the cement raw material mine, as well as the indicators of other raw materials such as fly ash, fly ash, sandstone, and iron powder. This is combined with fuel indicators, clinker heat consumption, and clinker yield, ratios, and proportions to meet the performance requirements of cement manufacturing. Other raw materials such as fly ash, fly ash, sandstone, and iron powder are used in small quantities and have relatively fixed compositions. When the control range of the limestone indicators is strict, it can easily lead to the inability to utilize some mineral resources and a large amount of waste discharge. Conversely, when the control range of the limestone indicators is broad, it can easily lead to difficulties in raw meal batching for cement manufacturing, resulting in cement that does not meet the required performance. Furthermore, when the limestone indicators are adjusted, traditional raw meal batching methods such as the trial-and-error method, the decreasing trial-and-error method, and the loss on ignition method are complex, time-consuming, labor-intensive, and have low calculation accuracy. Summary of the Invention

[0003] This application provides a method and apparatus for determining the control range of limestone indexes in cement raw material mines, so as to at least solve the problems existing in the methods for determining the control range of limestone indexes in the prior art.

[0004] According to one aspect of this application, a method for determining the control range of limestone indicators in cement raw material mines is provided, comprising: acquiring raw material indicator data and fuel indicator data; receiving clinker indicator extreme values ​​and limestone indicator extreme values ​​pre-configured by a user; constructing a mathematical model for determining the control range of limestone indicators, wherein the data model includes: known parameters, calculation parameters, decision variables, constraints, and an objective function; the known parameters include: the raw material indicator data, the fuel indicator data, the clinker indicator extreme values, and the limestone indicator extreme values; the calculation parameters are calculated based on the known parameters; the calculation parameters and the known parameters participate in the calculation of the constraints; the constraints are pre-configured; under the condition of satisfying the constraints, calculating the values ​​of the objective function corresponding to the values ​​of different decision variables in the mathematical model; obtaining the values ​​of the objective function as the values ​​of each decision variable under the optimal condition; and using the values ​​of each decision variable under the optimal condition as the solution result of the data model, wherein the solution result includes the control range of limestone indicators.

[0005] According to another aspect of this application, a device for determining the control range of limestone index in cement raw material mines is also provided, comprising: a first acquisition module for acquiring raw material index data and fuel index data; a receiving module for receiving clinker index extreme values ​​and limestone index extreme values ​​pre-configured by a user; a construction module for constructing a mathematical model for determining the control range of limestone index, wherein the data model includes: known parameters, calculation parameters, decision variables, constraints, and an objective function; the known parameters include: the raw material index data, the fuel index data, the clinker index extreme value, and the limestone index extreme value; the calculation parameters are calculated based on the known parameters; the calculation parameters and the known parameters participate in the calculation of the constraints; the constraints are pre-configured; a calculation module for calculating the values ​​of the objective function corresponding to the values ​​of different decision variables in the mathematical model under the condition of satisfying the constraints; a second acquisition module for acquiring the values ​​of the objective function as the values ​​of each decision variable under the optimal condition; and a determination module for using the values ​​of each decision variable under the optimal condition as the solution result of the data model, wherein the solution result includes the control range of limestone index.

[0006] In this embodiment, the following methods are employed: acquiring raw material index data and fuel index data; receiving pre-configured extreme values ​​of clinker and limestone indices; constructing a mathematical model for determining the control range of limestone indices; wherein the data model includes: known parameters, calculation parameters, decision variables, constraints, and an objective function; the known parameters include: the raw material index data, the fuel index data, the extreme values ​​of clinker and limestone indices; the calculation parameters are calculated based on the known parameters; the calculation parameters and the known parameters participate in the calculation of the constraints; the constraints are pre-configured; under the condition of satisfying the constraints, calculating the values ​​of the objective function corresponding to the values ​​of different decision variables in the mathematical model; obtaining the values ​​of the objective function as the values ​​of each decision variable under the optimal condition; and using the values ​​of each decision variable under the optimal condition as the solution result of the data model, wherein the solution result includes the control range of limestone indices. This application solves the problems existing in the methods for determining the control range of limestone indicators in the prior art, thereby enabling the rapid and accurate determination of the control range of limestone indicators in cement raw material mines, as well as the automatic calculation of raw material batching, guiding the preparation of production plans for cement raw material mines and cement manufacturing, maximizing the utilization of mineral resources, reducing waste rock discharge, and extending the service life of mines. Attached Figure Description

[0007] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0008] Figure 1 This is a flowchart of a method for determining the control range of limestone indexes in cement raw material mines according to an embodiment of this application. Detailed Implementation

[0009] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0010] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0011] In this embodiment, a method for determining the control range of limestone indexes in cement raw material mines is provided. The method includes the following steps:

[0012] Step S1: Obtain raw material index data and fuel index data;

[0013] Step S2: Receive the user-pre-configured extreme values ​​of clinker and limestone indices.

[0014] Step S3: Construct a mathematical model for determining the control range of limestone indicators, wherein the data model includes: known parameters, calculation parameters, decision variables, constraints, and an objective function; the known parameters include: raw material indicator data, fuel indicator data, clinker indicator extreme values, and limestone indicator extreme values; the calculation parameters are calculated based on the known parameters; the calculation parameters and the known parameters participate in the calculation of the constraints; the constraints are pre-configured.

[0015] Step S4: Under the condition that the constraints are met, calculate the value of the objective function corresponding to the values ​​of different decision variables in the mathematical model;

[0016] Step S5: Obtain the values ​​of each decision variable under the optimal condition from the values ​​of the objective function;

[0017] Step S6: The values ​​of each decision variable under the optimal condition are used as the solution results of the data model, wherein the solution results include the control range of the limestone index.

[0018] The above steps solve the problems existing in the methods for determining the control range of limestone indicators in the current technology, thereby enabling the rapid and accurate determination of the control range of limestone indicators in cement raw material mines, as well as the automatic calculation of raw material batching, to guide the preparation of production plans for cement raw material mines and cement manufacturing, maximize the utilization of mineral resources, reduce waste rock discharge, and extend the service life of mines.

[0019] The following description uses an optional embodiment. In this embodiment, a method for determining the control range of limestone indicators in cement raw material mines is provided. Figure 1 This is a flowchart of a method for determining the control range of limestone indexes in cement raw material mines according to an embodiment of this application, such as... Figure 1 As shown, the process includes the following steps:

[0020] Step 101: Obtain raw material and fuel index data from the data server;

[0021] Step 102: The user sets the extreme values ​​for clinker and limestone indices;

[0022] Step 103: Automatically construct a mathematical model for determining the control range of limestone indicators;

[0023] Step 104: Solve the mathematical model to obtain the control range of limestone index.

[0024] In step 101, the raw material index data obtained from the data server includes the loss on ignition of coal ash, fly ash, sandstone and iron powder, the proportion of SiO2, Al2O3, Fe2O3, CaO, MgO and other compounds, and the fuel index data obtained from the data server includes volatile matter, fixed carbon, ash content, moisture content and calorific value.

[0025] In step 102, the user sets the clinker heat consumption, clinker lime saturation coefficient upper limit, clinker lime saturation coefficient lower limit, clinker silicon ratio upper limit, clinker silicon ratio lower limit, clinker aluminum ratio upper limit, clinker aluminum ratio lower limit, limestone SiO2 upper limit, limestone SiO2 upper limit, limestone Al2O3 upper limit, limestone Al2O3 upper limit, limestone Fe2O3 upper limit, limestone Fe2O3 upper limit, limestone CaO upper limit, limestone CaO upper limit, limestone MgO upper limit, and limestone MgO upper limit. Among these, an extreme value of limestone index greater than 0 indicates that it is under control, otherwise it indicates that it is not under control.

[0026] The mathematical model for determining the control range of limestone indicators automatically constructed in step 103 is as follows:

[0027] Known parameters:

[0028] Loss on ignition of coal ash, and the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds.

[0029] Loss on ignition of fly ash, and the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds.

[0030] Loss on ignition of sandstone, and the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds.

[0031] Loss on ignition of iron powder, and the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds.

[0032] Q V Q FC Q A Q W Q: The percentages of volatile matter, fixed carbon, ash, moisture, and calorific value of the fuel.

[0033] Q′: Clinker heat consumption.

[0034] The total percentage of SiO2, Al2O3, Fe2O3, and CaO in the chemical composition of clinker.

[0035] Upper limit of clinker lime saturation coefficient and lower limit of clinker lime saturation coefficient.

[0036] Upper limit of silicon content in clinker, lower limit of silicon content in clinker.

[0037] Upper limit of aluminum content in clinker, lower limit of aluminum content in clinker.

[0038] The upper limit of the proportion of SiO2, Al2O3, Fe2O3, CaO, and MgO in limestone.

[0039] The lower limit of the proportion of SiO2, Al2O3, Fe2O3, CaO, and MgO in limestone.

[0040] Decision variables:

[0041] The loss on ignition of limestone and the percentages of SiO2, Al2O3, Fe2O3, CaO, and MgO.

[0042] y L y F y S y T The ratio of limestone, fly ash, sandstone and iron powder.

[0043] Calculation parameters:

[0044] G: Percentage of coal ash infiltration per 100kg of clinker

[0045] G R The percentage of raw meal in 100kg of clinker.

[0046] The SiO2 content of the design clinker

[0047]

[0048] The Al2O3 content of the design clinker

[0049]

[0050] The Fe2O3 content of the design clinker

[0051]

[0052] The CaO content of the clinker should be designed.

[0053]

[0054] Objective function:

[0055] (1)

[0056] (2)

[0057] constraint:

[0058] (1) Variable logical constraints

[0059]

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066]

[0067]

[0068]

[0069]

[0070] y L ≥0;

[0071] y F ≥0;

[0072] y S ≥0;

[0073] y T ≥0;

[0074] y L +y F +y S +y T =100.

[0075] (2) The total proportion of SiO2, Al2O3, Fe2O3, and CaO in the chemical composition of clinker is constrained.

[0076]

[0077] (3) Clinker ratio value constraint

[0078]

[0079]

[0080]

[0081] In step 104, the mathematical model for determining the control range of limestone index in cement raw material mines described in step 103 is solved by lpSolve, and the control range of the proportion of limestone SiO2, Al2O3, Fe2O3, CaO and MgO, as well as the corresponding proportions of limestone, fly ash, sandstone and iron powder are obtained.

[0082] The following example will illustrate this point.

[0083] A1: When determining the control range of limestone indicators for a certain cement raw material mine, the raw material indicator data obtained from the data server include the loss on ignition of fly ash, fly ash, sandstone, and iron powder, as well as the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds, as follows:

[0084] Loss on ignition <![CDATA[SiO2]]> <![CDATA[Al2O3]]> <![CDATA[Fe2O3]]> CaO MgO other coal ash 0 54.62 32.80 6.00 3.57 3.01 1.23 fly ash 6.00 67.27 14.25 6.05 1.12 5.31 1.26 sandstone 4.89 49.51 26.15 7.32 6.10 6.03 0.30 Iron powder 2.53 33.16 7.08 41.22 7.00 9.02 1.33

[0085] The fuel index data obtained from the data server are as follows: volatile matter content 26.99%, fixed carbon content 61.13%, ash content 22.76%, moisture content 0.9%, and calorific value 23486 kJ / kg.

[0086] A2: The user sets the clinker heat consumption to 3052 kJ / kg, the clinker lime saturation coefficient control range to 0.89±0.02, the clinker silicon content control range to 2.1±0.1, and the clinker aluminum content control range to 1.3±0.1; the limestone index extreme values ​​are set as follows:

[0087] <![CDATA[SiO2]]> <![CDATA[Al2O3]]> <![CDATA[Fe2O3]]> CaO MgO upper limit 18.00 -1 -1 52.00 -1 lower limit 4.00 -1 -1 45.30 -1

[0088] A3: The mathematical model for automatically constructing the control range of limestone indicators is as follows:

[0089] Known parameters:

[0090] Loss on ignition of coal ash, and the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds.

[0091] The percentage of fly ash loss on ignition, SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds. "Percentage" means the percentage calculated using "fly ash loss on ignition, SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds" as the "total". For example: fly ash loss on ignition percentage = fly ash loss on ignition / total amount; SiO2 percentage = SiO2 content / total amount; other compounds percentage = other compounds content / total amount.

[0092] Loss on ignition of sandstone, and the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds.

[0093] Loss on ignition of iron powder, and the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds.

[0094] Q V Q FC Q A Q W Q: The percentages of volatile matter, fixed carbon, ash, moisture, and calorific value of the fuel.

[0095] Q′: Clinker heat consumption.

[0096] The total percentage of SiO2, Al2O3, Fe2O3, and CaO in the chemical composition of clinker.

[0097] Upper limit of clinker lime saturation coefficient and lower limit of clinker lime saturation coefficient.

[0098] Upper limit of silicon content in clinker, lower limit of silicon content in clinker.

[0099] Upper limit of aluminum content in clinker, lower limit of aluminum content in clinker.

[0100] The upper limit of the proportion of SiO2, Al2O3, Fe2O3, CaO, and MgO in limestone.

[0101] The lower limit of the proportion of SiO2, Al2O3, Fe2O3, CaO, and MgO in limestone.

[0102] Decision variables:

[0103] The loss on ignition of limestone and the percentages of SiO2, Al2O3, Fe2O3, CaO, and MgO.

[0104] y L y F y S y T The ratio of limestone, fly ash, sandstone and iron powder.

[0105] Calculation parameters:

[0106] G: Percentage of coal ash infiltration per 100kg of clinker

[0107] G R The percentage of raw meal in 100kg of clinker.

[0108] The SiO2 content of the design clinker

[0109]

[0110] The Al2O3 content of the design clinker

[0111]

[0112] The Fe2O3 content of the design clinker

[0113]

[0114] The CaO content of the clinker should be designed.

[0115]

[0116] Objective function:

[0117] (1)

[0118] (2)

[0119] Among them, the two objective functions are independent of each other. 1. Solve the mathematical model with (1) as the objective function to obtain the lower limit of CaO proportion, as shown in the "lower limit" in Table A4; 2. Solve the mathematical model with (2) as the objective function to obtain the upper limit of CaO proportion, as shown in the "upper limit" in Table A4.

[0120] constraint:

[0121] (1) Variable logical constraints

[0122]

[0123]

[0124]

[0125]

[0126]

[0127]

[0128]

[0129]

[0130]

[0131]

[0132]

[0133] y L ≥0;

[0134] y F ≥0;

[0135] y S ≥0;

[0136] y T ≥0;

[0137] y L +y F +y S +y T=100.

[0138] (2) The total proportion of SiO2, Al2O3, Fe2O3, and CaO in the chemical composition of clinker is constrained.

[0139]

[0140] (3) Clinker ratio value constraint

[0141]

[0142]

[0143]

[0144] A4: By solving the mathematical model of the control range of limestone index in cement raw material mines as described in step A3 using lpSolve, the following control ranges for the proportions of SiO2, Al2O3, Fe2O3, CaO, and MgO in limestone are obtained:

[0145] <![CDATA[SiO2]]> <![CDATA[Al2O3]]> <![CDATA[Fe2O3]]> CaO MgO upper limit 18.00 3.56 0.86 52.00 2.78 lower limit 7.31 2.01 0.45 46.15 1.32 Setting value 11.38 2.01 0.64 46.28 2.21

[0146] Based on the set limestone index, the corresponding ratio of limestone, fly ash, sandstone and iron powder is 93.19:0.95:2.38:3.48.

[0147] In this embodiment, an electronic device is provided, including a memory and a processor. The memory stores a computer program, and the processor is configured to run the computer program to perform the methods described in the above embodiments.

[0148] The aforementioned program can run on a processor or be stored in memory (or computer-readable medium). Computer-readable medium includes both permanent and non-permanent, removable and non-removable media, and information storage can be achieved by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable medium does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0149] These computer programs may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes can be implemented using different modules, and different steps can be implemented using different modules.

[0150] This embodiment provides such an apparatus or system. The apparatus, referred to as a cement raw material mine limestone index control range determination device, includes: a first acquisition module for acquiring raw material index data and fuel index data; a receiving module for receiving user-pre-configured clinker index extreme values ​​and limestone index extreme values; a construction module for constructing a mathematical model for determining the limestone index control range, wherein the data model includes: known parameters, calculation parameters, decision variables, constraints, and an objective function; the known parameters include: the raw material index data, the fuel index data, the clinker index extreme values, and the limestone index extreme values; the calculation parameters are calculated based on the known parameters; the calculation parameters and the known parameters participate in the calculation of the constraints; the constraints are pre-configured; a calculation module for calculating the values ​​of the objective function corresponding to different decision variables in the mathematical model, provided the constraints are met; a second acquisition module for acquiring the values ​​of the objective function as the values ​​of each decision variable under optimal conditions; and a determination module for using the values ​​of each decision variable under optimal conditions as the solution result of the data model, wherein the solution result includes the limestone index control range.

[0151] The above embodiments solve the problems existing in the methods for determining the control range of limestone indicators in the prior art, thereby enabling the rapid and accurate determination of the control range of limestone indicators in cement raw material mines, as well as the automatic calculation of raw material batching, guiding the preparation of production plans for cement raw material mines and cement manufacturing, maximizing the utilization of mineral resources, reducing waste rock discharge, and extending the service life of mines.

[0152] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for determining a control range of an index of a limestone in a cement raw material mine, characterized by, include: Obtain raw material and fuel index data; Receive user-configured extreme values ​​for clinker and limestone indices; A mathematical model is constructed to determine the control range of limestone indicators. The data model includes: known parameters, calculated parameters, decision variables, constraints, and an objective function. The known parameters include: raw material indicator data, fuel indicator data, clinker indicator extreme values, and limestone indicator extreme values. The calculated parameters are obtained based on the known parameters. The calculated parameters and the known parameters participate in the calculation of the constraints. The constraints are pre-configured. The decision variables include: The loss on ignition of limestone, the proportions of SiO2, Al2O3, Fe2O3, CaO, and MgO, and The proportions of limestone, fly ash, sandstone, and iron powder; the objective function includes: (1) ,as well as （2） ； The constraints include: (1) Logical constraints on variables: if ; if ; if ; if ; if ; if ; if ; if ; if ; if ; ； ； ； ； ； ； (2) Constraints on the total proportions of SiO2, Al2O3, Fe2O3, and CaO in the chemical composition of clinker: ； (3) Clinker ratio index constraint ； ； ； Under the condition that the constraints are satisfied, calculate the values ​​of the objective function corresponding to the values ​​of different decision variables in the mathematical model; The value of the objective function is obtained by taking the values ​​of each decision variable under the optimal condition; The values ​​of each decision variable under the optimal condition are used as the solution results of the data model, wherein the solution results include the control range of the limestone index.

2. The method according to claim 1, characterized in that, The known parameters include: The loss on ignition of coal ash, the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds; and, The loss on ignition of fly ash, the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds; and, The loss on ignition, SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds in sandstone; and, The loss on ignition of iron powder, the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds; and, The volatile matter, fixed carbon, ash content, moisture content, and calorific value of fuels; and, : Clinker heat consumption; and, The total percentage of SiO2, Al2O3, Fe2O3, and CaO in the chemical composition of clinker; and, : Upper limit of clinker lime saturation coefficient, lower limit of clinker lime saturation coefficient; and, : Upper limit of clinker silicon content, lower limit of clinker silicon content; and, : Upper limit of aluminum content in clinker, lower limit of aluminum content in clinker; and, The upper limit of the proportions of SiO2, Al2O3, Fe2O3, CaO, and MgO in limestone; and, The lower limit of the proportion of SiO2, Al2O3, Fe2O3, CaO, and MgO in limestone.

3. The method according to claim 2, characterized in that, The calculation parameters include: The percentage of coal ash infiltrating into 100kg of clinker. ; The percentage of raw meal in 100kg of clinker. ; The SiO2 content of the designed clinker, ; The Al2O3 content of the designed clinker, ； The Fe2O3 content of the designed clinker, ;as well as, The CaO content of the designed clinker, .

4. A device for determining the control range of limestone indexes in cement raw material mines, characterized in that, include: The first acquisition module is used to acquire raw material index data and fuel index data; The receiving module is used to receive the extreme values ​​of clinker index and limestone index pre-configured by the user. A construction module is used to build a mathematical model for determining the control range of limestone indicators. The data model includes: known parameters, calculation parameters, decision variables, constraints, and an objective function. The known parameters include: raw material indicator data, fuel indicator data, clinker indicator extreme values, and limestone indicator extreme values. The calculation parameters are calculated based on the known parameters. The calculation parameters and the known parameters participate in the calculation of the constraints. The constraints are pre-configured. The decision variables include: The loss on ignition of limestone, the proportions of SiO2, Al2O3, Fe2O3, CaO, and MgO, and The ratio of limestone, fly ash, sandstone and iron powder; The decision variables include: The loss on ignition of limestone, the proportions of SiO2, Al2O3, Fe2O3, CaO, and MgO, and The ratio of limestone, fly ash, sandstone and iron powder; The objective function includes: (1) ,as well as （2） ； The constraints include: (1) Logical constraints on variables: if ; if ; if ; if ; if ; if ; if ; if ; if ; if ; ； ； ； ； ； ； (2) Constraints on the total proportions of SiO2, Al2O3, Fe2O3, and CaO in the chemical composition of clinker: ； (3) Clinker ratio index constraint ； ； ； The calculation module is used to calculate the values ​​of the objective function corresponding to the values ​​of different decision variables in the mathematical model, under the condition that the constraints are met. The second acquisition module is used to acquire the values ​​of each decision variable under the optimal condition of the objective function; The determination module is used to take the values ​​of each decision variable under the optimal condition as the solution result of the data model, wherein the solution result includes the control range of the limestone index.

5. The apparatus according to claim 4, characterized in that, The known parameters include: The loss on ignition of coal ash, the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds; and, The loss on ignition of fly ash, the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds; and, The loss on ignition, SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds in sandstone; and, The loss on ignition of iron powder, the proportions of SiO2, Al2O3, Fe2O3, CaO, MgO, and other compounds; and, The volatile matter, fixed carbon, ash content, moisture content, and calorific value of fuels; and, : Clinker heat consumption; and, The total percentage of SiO2, Al2O3, Fe2O3, and CaO in the chemical composition of clinker; and, : Upper limit of clinker lime saturation coefficient, lower limit of clinker lime saturation coefficient; and, : Upper limit of clinker silicon content, lower limit of clinker silicon content; and, : Upper limit of aluminum content in clinker, lower limit of aluminum content in clinker; and, The upper limit of the proportions of SiO2, Al2O3, Fe2O3, CaO, and MgO in limestone; and, The lower limit of the proportion of SiO2, Al2O3, Fe2O3, CaO, and MgO in limestone.

6. The apparatus according to claim 5, characterized in that, The calculation parameters include: The percentage of coal ash infiltrating into 100kg of clinker. ; The percentage of raw meal in 100kg of clinker. ; The SiO2 content of the designed clinker, ; The Al2O3 content of the designed clinker, ； The Fe2O3 content of the designed clinker, ;as well as, The CaO content of the designed clinker, .

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