CN114580780A - Sinter quality prediction method and system - Google Patents
Sinter quality prediction method and system Download PDFInfo
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- C—CHEMISTRY; METALLURGY
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- C21B—MANUFACTURE OF IRON OR STEEL
- C21B5/00—Making pig-iron in the blast furnace
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Abstract
The invention discloses a method and a system for predicting the quality of a sinter, wherein the method comprises the following steps: acquiring historical data of sintering production, and constructing a sintering database; building a sinter quality prediction model by using the sintering production historical data in the sintering database; respectively setting a target variable of the quality of the sintered ore to be predicted and a dependent variable influencing the quality of the sintered ore, and determining the quality index of the sintered ore meeting the production requirement of a blast furnace; setting a material proportioning structure and technological parameters to be used in sintering production, and calculating theoretical chemical components of the sinter according to the set material proportioning structure to be used in sintering production; inputting the material mixing structure, the process parameters and the theoretical chemical components to be used in sintering production into the sintered mineral quality prediction model, and predicting to obtain a sintered mineral quality index; judging whether the quality index of the sintering ore meets the production requirement of the blast furnace, and determining the material distribution structure and the technological parameters which are actually used in the sintering production.
Description
Technical Field
The invention relates to the technical field of data mining, in particular to a method and a system for predicting the quality of a sinter based on a sinter production data mining technology.
Background
The sinter is the main component of the blast furnace burden structure, and the quality stability and optimization of the sinter have important influence on the technical and economic indexes of the whole iron-making process. The improvement and the stability of the quality of the sinter are the precondition of high-efficiency and low-consumption production of the blast furnace. Blast furnace iron making has strict requirements on the quality of sinter, and the fluctuation of blast furnace production is inevitably caused when the sinter quality cannot meet the blast furnace requirements.
Because the raw materials of the sintering ore have wide sources, various varieties and complex components, the sintering process is a complex dynamic process with lag, nonlinearity and strong interference, the quality detection of the sintering ore and the adjustment of process parameters have large lag, and the testing and inspection data are not completely consistent with the process parameters at the current moment, so that the sintering production cannot be guided in real time. The prior method for controlling the sintered mineral content is completed by the following processes: firstly, a technical worker preliminarily determines a batching scheme of sintering production according to conditions such as iron ore resource conditions, blast furnace production requirements, current sintering production process and the like; secondly, carrying out experimental study on the control of the batching scheme and the sintering process parameters through a sintering cup test, and determining various process parameters of sintering production meeting production requirements; and carrying out industrial tests according to the process parameters determined in the last step, further optimizing the process parameters through the industrial tests, and determining the process parameters of actual sintering production. This process is a long cycle and the technician is heavy.
The prior Chinese patent CN101339177A, namely a sintering ore FeO forecasting system based on a neural network, Chinese patent CN202351625U, namely a sintering ore chemical component forecasting and intelligent control system under the poor information of small samples, Chinese patent CN103258310A, namely a sintering ore rotary drum strength forecasting method and the like, discloses forecasting methods for sintering ore FeO and rotary drum strength under different information sample conditions, and although the advantages are achieved, the forecasting of the metallurgical performance and quality indexes of the sintering ore is not considered, and the optimization of sintering process parameters can be only realized by applying a forecasting result. Therefore, how to relate to a method capable of comprehensively predicting various quality indexes of the sinter mineral quality still remains a technical problem to be solved in the field.
Disclosure of Invention
In view of the above, the invention provides a method and a system for predicting the quality of a sinter based on a sinter production data mining technology, and the method can comprehensively predict all quality indexes of the sinter quality, determine a sintering material preparation scheme and sintering production process control parameters according to the quality indexes, and realize the optimization and adjustment of the whole sintering production process.
In a first aspect, the present invention provides a method for predicting the amount of sinter in a sample, the method comprising: acquiring historical data of sintering production, and constructing a sintering database; building a sinter quality prediction model by using the sintering production historical data in the sintering database; respectively setting a target variable of the quality of the sintered ore to be predicted and a dependent variable influencing the quality of the sintered ore, and determining the quality index of the sintered ore meeting the production requirement of a blast furnace; setting a material proportioning structure and technological parameters to be used in sintering production, and calculating theoretical chemical components of the sinter according to the set material proportioning structure to be used in sintering production; inputting the material mixing structure, the process parameters and the theoretical chemical components to be used in sintering production into the sintered mineral quality prediction model, and predicting to obtain a sintered mineral quality index; judging whether the quality index of the sintering ore meets the production requirement of the blast furnace, and determining the material distribution structure and the technological parameters which are actually used in the sintering production.
Furthermore, the sintering production historical data at least comprises sintering raw material data, sintering fuel flux data, sintering production process parameter data and sinter quality data.
Further, the target variables at least comprise a sinter tumbler index, an average grain diameter, a molten drop interval, a molten drop maximum pressure difference, a melting end temperature, a low-temperature reduction degradation index and a reduction degree; the dependent variables at least comprise physical and chemical indexes of various iron ores of the sinter, a sintering burdening structure and sintering production process parameters.
Furthermore, the quality indexes of the sintered ore at least comprise the reduction degree, the low-temperature reduction degradation index, the average grain diameter, the molten drop interval, the melting temperature, the pressure difference and the sintered ore barrate index of the sintered ore.
Further, the step of judging whether the quality index of the sintered ore meets the production requirement of the blast furnace and determining the material proportioning structure and the process parameters actually used in the sintering production comprises the following steps: judging whether the predicted quality index of the sintering ore meets the production requirement of the blast furnace, and if so, taking the set material proportioning structure and process parameters to be used in the sintering production as the material proportioning structure and process parameters actually used in the sintering production; if the quality index does not meet the production requirement, adjusting the material mixing structure and the process parameters which are planned to be used in the sintering production, inputting the adjusted material mixing structure, the adjusted process parameters and the adjusted theoretical chemical components which are planned to be used in the sintering production into a sintering ore quality prediction model, and predicting again to obtain the sintering ore quality index until the predicted sintering ore quality index meets the production requirement.
Further comprising: carrying out industrial tests by using the determined batching structure and process parameters actually used in the sintering production, acquiring sintering actual production data of the industrial tests, and storing the sintering actual production data in a sintering database; and correcting the sintered mineral quality prediction model by using the actual sintering production data of the industrial test.
Further comprising: secondarily predicting the quality index of the sintering ore by using the corrected sintering ore quality prediction model; judging whether the sintered mineral quality index obtained by secondary prediction meets the production requirement of the blast furnace, and determining the material mixing structure and the technological parameters which are actually used in the sintering production again.
A second aspect of the present invention provides a system for predicting sinter quality, the system comprising: a memory for storing a computer program; a processor for performing the steps of the sinter quality prediction method as described above.
A third aspect of the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the method for predicting the amount of sinter mineral as described above.
According to the method for predicting the quality of the sintered ore, various indexes of the quality of the sintered ore are predicted timely and accurately in an all-around manner by analyzing and mining the data of historical production data of the sintered ore, so that a sintering material distribution scheme and production process technological parameters meeting the production requirements of a blast furnace are found, and the whole sintering production process is optimized and adjusted.
Drawings
For purposes of illustration and not limitation, the present invention will now be described in accordance with its preferred embodiments, particularly with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of a method for predicting the amount of sinter minerals provided in accordance with an embodiment of the present invention;
FIG. 2 is a flow chart of another method for predicting the amount of sinter minerals provided in accordance with an embodiment of the invention;
fig. 3 is a schematic structural diagram of a system for predicting the quality of a sintered ore according to another embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a detailed description of the present invention will be given below with reference to the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and features of the embodiments may be combined with each other without conflict.
In the following description, numerous specific details are set forth to provide a thorough understanding of the present invention, and the described embodiments are merely a subset of the embodiments of the present invention, rather than a complete embodiment. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
Fig. 1 is a flowchart of a method for predicting quality of a sinter based on a sinter production data mining technique according to an embodiment of the present invention. By the method for predicting the quality of the sintered ore, various indexes of the quality of the sintered ore can be timely and accurately predicted in an all-around manner, so that a sintering batching scheme and production process technological parameters meeting the production requirements of a blast furnace are found.
Referring to fig. 1, the method for predicting the quality of a sinter includes the following steps:
and S100, acquiring historical sintering production data and constructing a sintering database.
In this embodiment, the sintering production history data includes raw material data for sintering, fuel flux data for sintering, sintering production process parameter data, and sintered ore quality data; wherein, the raw material data for sintering comprises the data of physicochemical property, sintering property, balling property, market price and the like of each sintering ore species. For example, the sintering production historical data can be historical data of two 500m2 sintering machine production lines of a certain iron and steel enterprise in last three years, 2420 groups are provided, and a sintering database is established based on the 2420 groups of data.
In this embodiment, the sintering database includes a raw material database for sintering, a fuel flux database for sintering, a sintering production process parameter database, and a sintered ore quality database.
The specific implementation manner of the step S100 is as follows:
after raw material data for sintering, fuel flux data for sintering, parameter data of sintering production process and quality data of sintering ores are obtained, a raw material database for sintering is constructed based on the raw material data for sintering; constructing a fuel flux database for sintering based on the data of the fuel flux for sintering; constructing a sintering production process parameter database based on the sintering production process parameter data; and constructing a sinter quality database based on the sinter quality data.
And S200, constructing a sinter quality prediction model by using the sintering production historical data in the sintering database.
In this embodiment, the sintering production historical data in the sintering database is imported into data statistics predictive analysis software, and a neural network model for predicting the quality of the sintered ore is established through the data statistics predictive analysis software, so as to obtain a sintered ore quality prediction model. Wherein, the input variables of the neural network model comprise raw material data for sintering, fuel flux data for sintering and production process parameters. The output variable is the predicted sinter quality.
In some embodiments, the data statistics predictive analytics software may be implemented in the IBM SPSS Modeller 18.0 software. And establishing a neural network-like model for predicting the quality of the sinter by IBM SPSS Modeler 18.0 software, and taking the neural network-like model for predicting the quality of the sinter as a prediction model for the quality of the sinter.
S300, respectively setting target variables of the quality of the sintered ore to be predicted and dependent variables influencing the quality of the sintered ore, and determining the quality index of the sintered ore meeting the production requirement of the blast furnace.
In this embodiment, the target variables of the quality of the sintered ore to be predicted include the sintered ore drum index, the average particle diameter, the droplet interval, the droplet maximum pressure difference, the melting end temperature, the low-temperature reduction degradation index, the reduction degree, and the like.
In the embodiment, the dependent variables influencing the quality of the sintered ore comprise various iron ore physical and chemical indexes of the sintered ore, a sintering burden structure, sintering production process parameters and the like.
In this example, the quality indexes of the sintered ore satisfying the blast furnace production requirements include the chemical composition of the sintered ore, the drum index of the sintered ore, the average particle size, the droplet interval, the maximum pressure difference of the droplets, the melting end temperature, the low-temperature reduction degradation index, the reduction degree, and the like, as shown in table 1.
TABLE 1 quality index of sinter satisfying blast furnace production requirements
S400, setting a material distribution structure and technological parameters to be used in sintering production, and calculating theoretical chemical components of the sinter according to the set material distribution structure to be used in sintering production.
Firstly, preliminarily setting a material proportioning structure and technological parameters to be used in sintering production, and calculating theoretical chemical components of the sintering ore according to the preliminarily set material proportioning structure to be used in sintering production. The batch structure to be used for the preliminary set sintering production is shown in table 2. The theoretical chemical composition of the sintered ore is shown in table 3.
Table 2 batch structure to be used in sintering production
| Self-producing concentrates | FMG | WPF | Brazil powder | Mike powder |
| 37.00％ | 15.00％ | 10.00％ | 8.00％ | 30.00％ |
TABLE 3 theoretical chemical composition of sinter
And S500, inputting the material mixing structure, the process parameters and the theoretical chemical components to be used in the sintering production into a sinter quality prediction model, and predicting to obtain the sinter quality index.
And inputting the set material mixing structure, process parameters and theoretical chemical components to be used in sintering production into a sinter quality prediction model, and predicting to obtain a sinter quality index. The predicted quality indexes of the sinter comprise the reduction degree, the low-temperature reduction degradation index, the average grain diameter, the molten drop interval, the melting temperature, the pressure difference and the sinter tumbler index of the sinter.
S600, determining the material structure and the process parameters actually used in sintering production based on the predicted sinter mineral content index.
In this embodiment, the specific implementation manner of step S600 is:
judging whether the predicted sinter mineral quality index meets the production requirement of the blast furnace, and if so, taking the set material proportioning structure and process parameters to be used in the sintering production as the material proportioning structure and process parameters actually used in the sintering production; if not, adjusting the material mixing structure and the process parameters to be used in the sintering production, inputting the adjusted material mixing structure, the adjusted process parameters and the adjusted theoretical chemical components to the sinter quality prediction model, and predicting the quality of the obtained sinter until the predicted sinter quality meets the production requirement. The adjusted predicted agglomerate quality index is shown in table 4.
TABLE 4 prediction of sinter quality index
The specific implementation mode for judging whether the predicted sintered mineral quality index meets the production requirement of the blast furnace is as follows:
comparing the preliminarily predicted quality index of the sintering ore with the determined quality index of the sintering ore meeting the production requirement of the blast furnace, judging whether the quality index of the sintering ore is in the production requirement range of the blast furnace, and if the quality index of the sintering ore is in the production requirement range of the blast furnace, meeting the production requirement of the blast furnace; otherwise, the production requirement of the blast furnace is not met, and the material mixing structure and the process parameters to be used in the sintering production need to be adjusted to ensure that the predicted sintered mineral quality index meets the production requirement of the blast furnace.
Fig. 2 is a flowchart of another method for predicting quality of sintered ore based on mining technology of production data of sintered ore according to an embodiment of the present invention. The method for predicting the amount of the sintered minerals further comprises the following steps:
s700, carrying out an industrial test by using the determined batching structure and the process parameters actually used in the sintering production, acquiring sintering actual production data of the industrial test, and storing the sintering actual production data into a sintering database so as to update the sintering database; and correcting the sintered mineral quality prediction model by using the actual sintering production data of the industrial test in the updated sintering database.
And after the material proportioning structure and the technological parameters which are actually used in the sintering production are determined, carrying out industrial tests by using the determined material proportioning structure and the technological parameters which are actually used in the sintering production. The actual production data statistics for the industrial trials are shown in tables 5 and 6.
TABLE 5 sinter chemistry
| Fe | SiO2 | CaO | MgO | F | R | AL2O3 |
| 56.21 | 5.02 | 10.48 | 2.01 | 0.13 | 2.04 | 0.91 |
TABLE 6 metallurgical properties and mechanical Strength of the sinter
And verifying the accuracy of the prediction model through sintering actual production data of industrial tests. The sintering actual production data of the industrial test is imported into a sintering database, the sintering database is updated, a sintered mineral quality prediction model is corrected by using the updated sintering actual production data of the industrial test of the sintering database, the sintering production adjustment time can be shortened, and the quality fluctuation of sintered minerals is reduced; has better practicability and popularization value.
And S800, secondarily predicting the quality index of the sintered ore by using the corrected sintered ore quality prediction model.
And inputting the set material mixing structure and process parameter data to be used in sintering production into the corrected sinter quality prediction model again, and performing secondary prediction to obtain the sinter quality index.
And S900, determining the material proportioning structure and the technological parameters which are actually used in the sintering production again based on the sintered mineral quality index obtained by secondary prediction.
In this embodiment, the specific implementation manner of step S900 is:
judging whether the indexes of the mineral content of the sintered material obtained by secondary prediction meet the production requirements of the blast furnace, and if so, taking the material mixing structure and the technological parameters which are planned to be used in the sintering production as the material mixing structure and the technological parameters which are actually used in the sintering production; if the predicted sintered mineral quality index does not meet the production requirement of the blast furnace, adjusting the material mixing structure and the process parameters to be used in the sintering production, inputting the adjusted material mixing structure and the adjusted process parameters to the sintered mineral quality prediction model, and predicting again to obtain the sintered mineral quality index until the predicted sintered mineral quality index meets the production requirement of the blast furnace.
In this example, the production requirements are blast furnace burden requirements. When the quality index of the sintering ore obtained by secondary prediction can meet the requirement of the blast furnace material, presenting the material proportioning structure and the process parameters to be used by sintering production to sintering production engineering technicians to guide production organization; otherwise, the material distribution structure and the process parameters to be used in the sintering production are adjusted, and then the sintering ore quality index is predicted again until the predicted sintering ore quality index meets the production requirement.
According to the method for predicting the quality of the sintered ore, a sintered ore quality prediction model is constructed by using historical data of sintering production; and the material proportioning structure and the process parameters used in sintering production are determined by using the sinter quality prediction model, so that the complicated manual calculation and laboratory test process of engineering technicians can be omitted.
According to the method for predicting the quality of the sintered ore, the quality index of the sintered ore can be continuously predicted and corrected through the accumulative analysis of sintering production data, and the determined material mixing structure and process parameter data used in sintering production are more accurate.
According to the method for predicting the quality of the sintered ore, the quality of the sintered ore is predicted by adopting the sintered ore quality prediction model, the adjustment time of sintering process parameters can be shortened, and the fluctuation of the quality of the sintered ore is reduced.
In correspondence to the above method embodiment, referring to fig. 3, fig. 3 is a schematic structural diagram of a system for predicting quality of sintered ore according to another embodiment of the present invention, where the system 100 may include:
a memory 101 for storing a computer program;
the processor 102, when executing the computer program stored in the memory 101, may implement the following steps:
acquiring historical data of sintering production, and constructing a sintering database; building a sinter quality prediction model by using the sintering production historical data in the sintering database; respectively setting a target variable of the quality of the sintered ore to be predicted and a dependent variable influencing the quality of the sintered ore, and determining the quality index of the sintered ore meeting the production requirement of a blast furnace; setting a material proportioning structure and technological parameters to be used in sintering production, and calculating theoretical chemical components of the sinter according to the set material proportioning structure to be used in sintering production; inputting the material mixing structure, the process parameters and the theoretical chemical components to be used in sintering production into the sintered mineral quality prediction model, and predicting to obtain a sintered mineral quality index; judging whether the quality index of the sintering ore meets the production requirement of the blast furnace, and determining the material distribution structure and the technological parameters which are actually used in the sintering production.
For the introduction of the device provided by the present invention, please refer to the above method embodiment, which is not described herein again.
Corresponding to the above method embodiment, the present invention further provides a computer-readable storage medium having a computer program stored thereon, the computer program, when executed by a processor, implementing the steps of:
acquiring historical data of sintering production, and constructing a sinter quality prediction model; respectively setting a target variable of the quality of the sintered ore to be predicted and a dependent variable influencing the quality of the sintered ore, and determining the quality index of the sintered ore meeting the production requirement of a blast furnace; setting a material proportioning structure and technological parameters to be used in sintering production, and calculating theoretical chemical components of the sinter according to the set material proportioning structure to be used in sintering production; inputting the material mixing structure, the process parameters and the theoretical chemical components to be used in sintering production into the sintered mineral quality prediction model, and predicting to obtain a sintered mineral quality index; judging whether the quality index of the sintering ore meets the production requirement of the blast furnace, and determining the material distribution structure and the technological parameters which are actually used in the sintering production.
The computer-readable storage medium may include: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
For the introduction of the computer-readable storage medium provided by the present invention, please refer to the above method embodiments, which are not described herein again.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other. The device, the apparatus and the computer-readable storage medium disclosed in the embodiments correspond to the method disclosed in the embodiments, so that the description is simple, and the relevant points can be referred to the description of the method.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for predicting the amount of sinter minerals, comprising:
acquiring historical data of sintering production, and constructing a sintering database;
building a sinter quality prediction model by using historical sintering production data in a sintering database;
respectively setting a target variable of the quality of the sintered ore to be predicted and a dependent variable influencing the quality of the sintered ore, and determining the quality index of the sintered ore meeting the production requirement of a blast furnace;
setting a material proportioning structure and technological parameters to be used in sintering production, and calculating theoretical chemical components of the sinter according to the set material proportioning structure to be used in sintering production;
inputting the material mixing structure, the process parameters and the theoretical chemical components to be used in sintering production into the sintered mineral quality prediction model, and predicting to obtain a sintered mineral quality index;
judging whether the quality index of the sintering ore meets the production requirement of the blast furnace, and determining the material distribution structure and the technological parameters which are actually used in the sintering production.
2. The method according to claim 1, wherein the sintering production history data includes at least raw material data for sintering, fuel flux data for sintering, sintering production process parameter data, and sintered ore quality data.
3. The method for predicting the quality of the sinter as claimed in claim 1, wherein the target variables at least include a sinter tumbler index, an average particle size, a droplet interval, a droplet maximum pressure difference, a melting end temperature, a low-temperature reduction degradation index, and a reduction degree; the dependent variables at least comprise physical and chemical indexes of various iron ores of the sinter, a sintering burdening structure and sintering production process parameters.
4. The method according to claim 1, wherein the quality index of the sintered ore includes at least a reduction degree, a low-temperature reduction degradation index, an average particle diameter, a droplet interval, a melting temperature, a pressure difference, and a sintered ore drum index of the sintered ore.
5. The method for predicting the quality of the sinter as claimed in claim 1, wherein the step of judging whether the quality index of the sinter meets the production requirement of the blast furnace and determining the burden structure and the process parameters actually used in the sintering production comprises:
judging whether the predicted quality index of the sintering ore meets the production requirement of the blast furnace, and if so, taking the set material proportioning structure and process parameters to be used in the sintering production as the material proportioning structure and process parameters actually used in the sintering production; if the quality index does not meet the production requirement, adjusting the material mixing structure and the process parameters which are planned to be used in the sintering production, inputting the adjusted material mixing structure, the adjusted process parameters and the adjusted theoretical chemical components which are planned to be used in the sintering production into a sintering ore quality prediction model, and predicting again to obtain the sintering ore quality index until the predicted sintering ore quality index meets the production requirement.
6. The method for predicting the quality of the sintered ore according to claim 1, wherein the quality indexes of the sintered ore meeting the production requirement of the blast furnace are as follows:
7. the method of predicting the quality of a sinter as claimed in claim 1, further comprising:
carrying out industrial tests by using the determined batching structure and process parameters actually used in the sintering production, acquiring sintering actual production data of the industrial tests, and storing the sintering actual production data in a sintering database; and correcting the sintered mineral quality prediction model by using the actual sintering production data of the industrial test.
8. The method of predicting agglomerate mineralization according to claim 7, further comprising:
secondarily predicting the quality index of the sintering ore by using the corrected sintering ore quality prediction model;
judging whether the sintered mineral quality index obtained by secondary prediction meets the production requirement of the blast furnace, and determining the material mixing structure and the technological parameters which are actually used in the sintering production again.
9. A system for predicting sinter mineralization, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the method of predicting sinter mineralization as claimed in any one of claims 1 to 8 when said computer program is executed.
10. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method for predicting sinter quality as claimed in any one of claims 1 to 8.
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| CN114882961A (en) * | 2022-06-09 | 2022-08-09 | 佛山众陶联供应链服务有限公司 | Firing curve prediction method based on raw material weight as model parameter selection condition |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114882961A (en) * | 2022-06-09 | 2022-08-09 | 佛山众陶联供应链服务有限公司 | Firing curve prediction method based on raw material weight as model parameter selection condition |
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