Method, device, medium and electronic equipment for smelting magnesium by kinetic model

Abstract

The present invention provides a method for magnesium smelting by a kinetic model, the method comprising: obtaining process operation parameters during magnesium smelting; calculating the process operation parameters by a kinetic computer statement in a kinetic model to obtain index data at multiple moments, the kinetic model is a model established based on a multiphase system, and the index data includes index data under the multiphase system. The present invention also provides a device, a medium and an electronic device for magnesium smelting by a kinetic model.

Description

Technical Field

[0001] The present invention relates to the technical field of model magnesium smelting, and in particular to a method, device, medium and electronic equipment for smelting magnesium through a kinetic model. Background Art

[0002] The injection method for continuous liquid magnesium smelting is a new magnesium smelting technology. Under certain vacuum conditions, the reducing agent is melted by induction heating to form a liquid molten pool. The magnesium-containing raw materials are pneumatically conveyed into the molten pool to undergo a reduction reaction to produce magnesium vapor, thereby achieving liquid reduction magnesium smelting. The generated magnesium vapor enters the liquid collector to condense liquid magnesium metal, which is then vacuum refined and collected to improve the purity of the magnesium metal. At the same time, impurity alkali metals are collected, and the slag generated by the reduction is continuously discharged by siphoning under vacuum.

[0003] In terms of the kinetic calculation of the magnesium smelting process, the following methods can be used for calculation. For example, the Arrhenius equation is used to analyze the thermal decomposition mechanism of dolomite, and the lnk-1 / T relationship curve is calculated; the Arrhenius equation is used to study the effects of pelletizing pressure, reduction temperature and addition of fluoride salts on the magnesium reduction rate during vacuum thermal reduction of calcined dolomite; the shrinkage unreacted core model is used to calculate the comprehensive rate equation of magnesium pore diffusion and quasi-interface chemical reaction control during the Pijiang method of magnesium smelting; the solid-solid reaction model is used to study the effects of factors such as temperature, gas flow rate and additives on the magnesium vapor generation rate; the solid-solid reaction model is used to study the relationship between the Mg reduction rate and temperature under different heating rates. However, none of the above calculation methods can predict the changes in system components at any time during the reaction process.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present invention, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The purpose of the embodiments of the present invention is to provide a method, device, medium and electronic equipment for smelting magnesium through a kinetic model, so that at least to a certain extent, it is possible to obtain multiple possible indicator data in the model reaction during magnesium smelting, effectively solving the problem in the related art that the reaction components at multiple times during the reaction process cannot be predicted.

[0006] Other features and advantages of the present invention will become apparent from the following detailed description, or may be learned in part by practice of the present invention.

[0007] According to a first aspect of an embodiment of the present invention, a method for smelting magnesium through a kinetic model is provided, the method comprising: obtaining process operating parameters during magnesium smelting; calculating the process operating parameters through kinetic computer statements in the kinetic model to obtain index data at multiple moments, wherein the kinetic model is a model established based on a multiphase system, and the index data includes index data under the multiphase system.

[0008] In some embodiments of the present invention, the multiphase system comprises a quaternary multiphase system, wherein the quaternary multiphase system is ferrosilicon, calcined ash, slag phase, and gas phase, and the indicator data under the quaternary multiphase system are ferrosilicon composition, slag phase composition, gas phase pressure, and condensation amount of magnesium.

[0009] In some embodiments of the present invention, the process operation parameters include: furnace size, molten pool depth, molten pool temperature, nozzle insertion depth, vacuum degree, nozzle rotation speed, and gas injection flow rate.

[0010] In some embodiments of the present invention, the model established based on the multiphase system includes: acquiring kinetic calculation data and historical process operation parameters, the kinetic calculation data including: chemical reactions, mass transfer coefficients, thermodynamic calculation formulas, coupled reactions, reduction period reactions, and condensation processes, the historical process operation parameters including historical furnace dimensions, historical molten pool depths, historical molten pool temperatures, historical nozzle insertion depths, historical vacuum degrees, historical nozzle rotation speeds, and historical gas injection flow rates; generating the kinetic computer statements based on the kinetic calculation data and the historical process operation parameters; and establishing the kinetic calculation model based on the kinetic computer statements.

[0011] In some embodiments of the present invention, after establishing the kinetic calculation model, the method also includes: obtaining initial process operation parameters; calculating the initial process operation parameters through the kinetic computer statements in the kinetic calculation model to obtain initial indicator data at multiple times; obtaining actual detection data at multiple times in industrial experiments; comparing the initial indicator data at the multiple times with the actual detection data at the multiple times; and determining whether the kinetic calculation model is stable based on the comparison results.

[0012] In some embodiments of the present invention, the method also includes: if the initial indicator data at the same time is the same or similar to the actual detection data, it indicates that the dynamic calculation model is stable; or if the difference between the initial indicator data at the same time and the actual detection data is greater than a preset interval, it indicates that the dynamic calculation model is unstable.

[0013] In some embodiments of the present invention, when the difference between the initial indicator data and the actual detection data at the same time is greater than a preset interval, the method includes: obtaining a first process operation parameter, the first process operation parameter being the process operation parameter after modifying the initial working operation parameter and the mass transfer coefficient; calculating the first process operation parameter through the kinetic computer statement in the kinetic calculation model to obtain the first indicator data at multiple times; obtaining the first actual detection data at multiple times in the industrial test; comparing the first indicator data at the multiple times with the first actual detection data at the multiple times; determining whether the kinetic calculation model is stable based on the first comparison result; and repeating the above steps until the kinetic calculation model is stable.

[0014] According to a second aspect of an embodiment of the present invention, there is provided a device for smelting magnesium through a kinetic model, the device comprising: a first acquisition module, used to obtain process operation parameters during magnesium smelting; a first calculation module, used to calculate the process operation parameters through kinetic computer statements in the kinetic model, and obtain index data at multiple moments, the kinetic model is a model established based on a multiphase system, and the index data includes index data under the multiphase system.

[0015] In some embodiments of the present invention, the multiphase system comprises a quaternary multiphase system, wherein the quaternary multiphase system is ferrosilicon, calcined ash, slag phase, and gas phase, and the indicator data under the quaternary multiphase system are ferrosilicon composition, slag phase composition, gas phase pressure, and condensation amount of magnesium.

[0016] In some embodiments of the present invention, the process operation parameters include: furnace size, molten pool depth, molten pool temperature, nozzle insertion depth, vacuum degree, nozzle rotation speed, and gas injection flow rate.

[0017] In some embodiments of the present invention, the model established based on the multiphase system includes: acquiring kinetic calculation data and historical process operation parameters, the kinetic calculation data including: chemical reactions, mass transfer coefficients, thermodynamic calculation formulas, coupled reactions, reduction period reactions, and condensation processes, the historical process operation parameters including historical furnace dimensions, historical molten pool depths, historical molten pool temperatures, historical nozzle insertion depths, historical vacuum degrees, historical nozzle rotation speeds, and historical gas injection flow rates; generating the kinetic computer statements based on the kinetic calculation data and the historical process operation parameters; and establishing the kinetic calculation model based on the kinetic computer statements.

[0018] In some embodiments of the present invention, after establishing the kinetic calculation model, the device also includes: a second acquisition module, used to obtain initial process operation parameters; a second calculation module, used to calculate the initial process operation parameters through the kinetic computer statements in the kinetic calculation model, and obtain initial indicator data at multiple times; a third acquisition module, used to obtain actual detection data at multiple times in industrial experiments; a first comparison module, used to compare the initial indicator data at multiple times and the actual detection data at multiple times; a first determination module, used to determine whether the kinetic calculation model is stable based on the comparison results.

[0019] In some embodiments of the present invention, the device also includes: a first representation module, if the initial indicator data at the same time is the same or similar to the actual detection data, it indicates that the dynamic calculation model is stable; or a second representation module, if the difference between the initial indicator data at the same time and the actual detection data is greater than a preset interval, it indicates that the dynamic calculation model is unstable.

[0020] In some embodiments of the present invention, when the difference between the initial indicator data and the actual detection data at the same time is greater than a preset interval, the device includes: a fourth acquisition module, used to acquire the first process operation parameter, wherein the first process operation parameter is the process operation parameter after modifying the initial process operation parameter and the mass transfer coefficient; a third calculation module, used to calculate the first process operation parameter through the kinetic computer statement in the kinetic calculation model to acquire the first indicator data at multiple times; a fifth acquisition module, used to acquire the first actual detection data at multiple times in the industrial test; a second comparison module, used to compare the first indicator data at the multiple times with the first actual detection data at the multiple times; a second determination module, used to determine whether the kinetic calculation model is stable according to the first comparison result; and a loop module, used to loop the above steps until the kinetic calculation model is stable.

[0021] According to a third aspect of an embodiment of the present invention, there is provided an electronic device, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method for smelting magnesium by a kinetic model as described in the first aspect of the above embodiment.

[0022] According to a fourth aspect of an embodiment of the present invention, a computer-readable medium is provided, on which a computer program is stored. When the program is executed by a processor, the method for smelting magnesium by a kinetic model as described in the first aspect of the above embodiment is implemented.

[0023] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0024] In the technical solutions provided in some embodiments of the present invention, process operation parameters during magnesium smelting are obtained, and the process operation parameters are calculated by kinetic computer statements in a kinetic model to obtain index data at multiple moments. The kinetic model is a model established based on a multiphase system, and the index data includes index data under the multiphase system. In this way, the index data under the multiphase body at multiple moments can be predicted, which makes it easy to make reasonable suggestions based on the index data under the multiphase system.

[0025] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings herein are incorporated into and constitute a part of the specification, showing embodiments consistent with the present invention, and together with the specification, are used to explain the principles of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0027] Figure 1 A schematic diagram showing an exemplary system architecture of a method for smelting magnesium using a kinetic model or an apparatus for smelting magnesium using a kinetic model according to an embodiment of the present invention is applicable;

[0028] Figure 2 A flow chart of a method for magnesium smelting by a kinetic model according to an embodiment of the present invention is schematically shown;

[0029] Figure 3 A flow chart of a method for magnesium smelting by a kinetic model according to another embodiment of the present invention is schematically shown;

[0030] Figure 4 A flow chart of a method for magnesium smelting by a kinetic model according to another embodiment of the present invention is schematically shown;

[0031] Figure 5 A flow chart of a method for magnesium smelting by a kinetic model according to another embodiment of the present invention is schematically shown;

[0032] Figure 6 A flowchart schematically shows the establishment, verification, and application of a novel continuous magnesium smelting process kinetic prediction model according to the present invention;

[0033] Figure 7 A schematic diagram of the reaction process in the novel continuous magnesium smelting process kinetic prediction model according to the present invention is schematically shown;

[0034] Figure 8 A block diagram of a device for smelting magnesium using a kinetic model according to an embodiment of the present invention is schematically shown;

[0035] Fig. 9 A block diagram of a device for smelting magnesium using a kinetic model according to another embodiment of the present invention is schematically shown;

[0036] Fig.10 A block diagram of a device for smelting magnesium using a kinetic model according to another embodiment of the present invention is schematically shown;

[0037] Fig.11 A block diagram of a device for smelting magnesium using a kinetic model according to another embodiment of the present invention is schematically shown;

[0038] Fig.12 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0039] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the present invention will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0040] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present invention. However, those skilled in the art will appreciate that the technical solution of the present invention can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring various aspects of the present invention.

[0041] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0042] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0043] Figure 1 The diagram shows an exemplary system architecture of a method for smelting magnesium using a kinetic model or an apparatus for smelting magnesium using a kinetic model, to which an embodiment of the present invention can be applied.

[0044] like Figure 1 As shown, the system architecture 100 may include one or more of terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0045] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, networks and servers. For example, the server 105 may be a server cluster composed of multiple servers.

[0046] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Terminal devices 101, 102, 103 can be various electronic devices with display screens, including but not limited to smart phones, tablet computers, portable computers, desktop computers, etc.

[0047] The server 105 may be a server that provides various services. For example, the server 105 may obtain the process operation parameters of the terminal device 103 (or the terminal device 101 or 102) during magnesium smelting; the process operation parameters are calculated by the kinetic computer statements in the kinetic model to obtain the index data at multiple moments. The kinetic model is a model established based on a multiphase system, and the index data includes the index data under the multiphase system. In this way, the index data under the multiphase body at multiple moments can be predicted, so that it is convenient to make reasonable suggestions based on the index data under the multiphase system.

[0048] In some embodiments, the method for smelting magnesium by a kinetic model provided in the embodiment of the present invention is generally executed by the server 105, and accordingly, the device for smelting magnesium by a kinetic model is generally disposed in the server 105. In other embodiments, some terminals may have functions similar to those of the server to execute the method. Therefore, the method for smelting magnesium by a kinetic model provided in the embodiment of the present invention is not limited to being executed on the server side.

[0049] Figure 2 A flow chart of a method for smelting magnesium using a kinetic model according to an embodiment of the present invention is schematically shown.

[0050] like Figure 2As shown, the method for smelting magnesium using a kinetic model may include step S210 and step S220.

[0051] In step S210, process operation parameters for magnesium smelting are obtained.

[0052] In step S220, the process operation parameters are calculated by kinetic computer statements in a kinetic model to obtain index data at multiple moments. The kinetic model is a model established based on a multiphase system, and the index data includes index data under the multiphase system.

[0053] The method can obtain the process operation parameters during magnesium smelting, calculate the process operation parameters through the kinetic computer statements in the kinetic model, and obtain index data at multiple moments. The kinetic model is a model established based on a multiphase system, and the index data includes index data under the multiphase system. In this way, the index data under the multiphase body at multiple moments can be predicted, which makes it easy to make reasonable suggestions based on the index data under the multiphase system.

[0054] In one embodiment of the present invention, the process operation parameters include: furnace size, molten pool depth, molten pool temperature, nozzle insertion depth, vacuum degree, nozzle rotation speed, and gas injection flow rate.

[0055] In one embodiment of the present invention, the multiphase system comprises a quaternary multiphase system, wherein the quaternary multiphase system comprises ferrosilicon, calcined slag, slag phase, and gas phase, and the index data under the quaternary multiphase system comprises ferrosilicon composition, slag phase composition, gas phase pressure, and condensation amount of magnesium.

[0056] In one embodiment of the present invention, after calculating the ferrosilicon composition, slag phase composition, gas phase pressure, and magnesium condensation amount through the above-mentioned kinetic computer statements, one or more of the above-mentioned process operation parameters can be selected to change to examine the influence of each process operation parameter on the reaction process in the kinetic model and the final magnesium yield, so as to provide guidance for the production practice of the new continuous magnesium smelting process in a targeted manner. For example, the molten pool temperature and / or nozzle speed in the process operation parameters can be modified, so that based on the modified process operation parameters, the new ferrosilicon composition, new slag phase composition, new gas phase pressure, and new magnesium condensation amount can be calculated through the above-mentioned kinetic computer statements, that is, by changing one or more of the process operation parameters, the system composition changes at any time in the magnesium smelting process can be obtained.

[0057] In one embodiment of the present invention, based on the coupled reaction, combined with the mass transfer process and chemical reaction process between the solid-liquid-gas three phases, through independent programming (for example, writing corresponding computer statements in C++ software. The computer statements are mainly divided into three parts: input part, calculation part, and output part. The input part is various process operation parameters; the calculation part is the detailed process of kinetic calculation, and the various parameters of the input part will be taken into calculation during calculation; the output part is to output the calculation results in a txt file), kinetic calculation is performed for the magnesium smelting process, so that a kinetic model of the "ferrosilicon-calcined white-slag phase-gas phase" quaternary multiphase system can be established, and the system composition changes at any time during the magnesium smelting process can be obtained through the kinetic model. For example, the magnesium yield and quality changes under different reaction conditions (different molten pool temperatures, different nozzle speeds, etc.) can be calculated through the kinetic model. In this embodiment, the kinetic model can be optimized in combination with the actual detection data of industrial experiments, so as to obtain a kinetic model that is consistent with the actual production process.

[0058] In one embodiment of the present invention, the above-mentioned process operation parameters can be calculated by the kinetic computer statements in the kinetic model. For example, the reaction processes that can be considered in the calculation include: the floating of magnesium vapor in ferrosilicon and slag phases, the sublimation of magnesium vapor, the influence of gas powder injection, the chemical reaction between ferrosilicon and slag phases, and the chemical reaction between forging white powder particles and ferrosilicon. Specifically, the nozzle is first inserted into the ferrosilicon, and the forging white powder particles are ejected from the nozzle at a certain speed. Due to the density difference, the forging white powder particles will gradually float from the nozzle to the slag phase, and the forging white powder particles will react with the ferrosilicon during the floating process. After the forging white powder particles float to the slag phase, foamy slag will be formed. At this time, the slag phase will also react with the ferrosilicon. The magnesium vapor generated by the reaction will pass through the slag phase and enter the gas phase, and then be pumped away into the condensation equipment, such as Figure 7 Wherein, the condensing device is not shown in the figure.

[0059] Figure 3 A flow chart of a method for smelting magnesium using a kinetic model according to another embodiment of the present invention is schematically shown.

[0060] like Figure 3 As shown, the model established based on the multiphase system includes steps S310 to S330.

[0061] In step S310, kinetic calculation data and historical process operation parameters are obtained, wherein the kinetic calculation data include: chemical reaction, mass transfer coefficient, thermodynamic calculation formula, coupled reaction, reduction period reaction, and condensation process, and the historical process operation parameters include historical furnace size, historical molten pool depth, historical molten pool temperature, historical nozzle insertion depth, historical vacuum degree, historical nozzle rotation speed, and historical gas injection flow rate.

[0062] In step S320, the kinetic computer statements are generated based on the kinetic calculation data and the historical process operation parameters.

[0063] In step S330, the dynamics calculation model is established based on the dynamics computer statement.

[0064] The method can generate the kinetic computer statement based on the kinetic calculation data and the historical process operation parameters, and establish the kinetic calculation model based on the kinetic computer statement, so that automatic magnesium smelting can be achieved through the kinetic calculation model. For example, the kinetic computer statement in the kinetic model can calculate the index data under the multiphase system.

[0065] In one embodiment of the present invention, the kinetic computer statements are generated based on the kinetic calculation data and the historical process operation parameters, and the kinetic calculation model is established based on the kinetic computer statements. For example, based on the coupled reaction, combined with the mass transfer process and chemical reaction process between the solid-liquid-gas three phases, through autonomous programming, kinetic calculations are performed for the magnesium smelting process, so that a kinetic model of the "ferrosilicon-calcined white-slag phase-gas phase" quaternary multiphase system can be established, and the changes in system components at any time during the magnesium smelting process can be obtained through this kinetic model. For example, the magnesium yield and quality changes under different reaction conditions (different molten pool temperatures, different nozzle speeds, etc.) can be calculated through this kinetic model. In this embodiment, the kinetic model can be optimized in combination with the actual detection data of industrial experiments, so as to obtain a kinetic model that is consistent with the actual production process.

[0066] Figure 4 A flow chart of a method for smelting magnesium using a kinetic model according to another embodiment of the present invention is schematically shown.

[0067] After establishing the dynamic calculation model, the method further includes steps S410 to S450, such as Figure 4 shown.

[0068] In step S410, initial process operation parameters are obtained.

[0069] In step S420, the initial process operation parameters are calculated using the kinetic computer statements in the kinetic calculation model to obtain initial indicator data at multiple moments.

[0070] In step S430, actual detection data at multiple moments in the industrial test is obtained.

[0071] In step S440, the initial indicator data at the multiple moments are compared with the actual detection data at the multiple moments.

[0072] In step S450, it is determined whether the dynamics calculation model is stable according to the comparison result.

[0073] The method can compare the initial indicator data at the multiple moments and the actual detection data at the multiple moments, and determine whether the dynamic calculation model is stable based on the comparison results, which can improve the calculation ability of the dynamic model, that is, improve the accuracy of obtaining indicator data.

[0074] In one embodiment of the present invention, the method further includes: if the initial indicator data at the same time is the same or similar to the actual detection data, it indicates that the dynamic calculation model is stable; or if the difference between the initial indicator data at the same time and the actual detection data is greater than a preset interval, it indicates that the dynamic calculation model is unstable. In this embodiment, the preset interval can be set according to actual conditions.

[0075] In one embodiment of the present invention, the above-mentioned initial process operation parameters can be set by relevant personnel according to their own prior knowledge. For example, the initial process operation parameters may include initial furnace size, initial molten pool depth, initial molten pool temperature, initial nozzle insertion depth, initial vacuum degree, initial nozzle speed, initial mass transfer coefficient, and initial gas injection flow rate.

[0076] In one embodiment of the present invention, the initial index data at multiple moments may be the initial index data of the kinetic model under the multi-phase system at the 400th second, the 800th second, the 1200th second, etc. when magnesium smelting starts.

[0077] In one embodiment of the present invention, the actual detection data at multiple moments in the industrial test may be the actual detection data in a multi-phase system at the 400th second, the 800th second, the 1200th second, etc. when the industry starts smelting magnesium.

[0078] Based on the above embodiment, the initial index data of the kinetic model under the multiphase system at the 400th second when magnesium smelting starts and the actual detection data of the industry under the multiphase system at the 400th second when magnesium smelting starts are compared, and whether the kinetic calculation model is stable is determined according to the comparison results. And / or the initial index data and the actual detection data at other same moments can also be compared to determine whether the kinetic calculation model is stable. For example, the ferrosilicon composition, slag phase composition, gas phase pressure, and / or condensation quality of magnesium at the 400th second when magnesium smelting starts are compared with the ferrosilicon composition, slag phase composition, gas phase pressure, and / or condensation quality of magnesium at the 400th second when magnesium smelting starts in the kinetic model, and the ferrosilicon composition, slag phase composition, gas phase pressure, and / or condensation quality of magnesium at the 400th second when magnesium smelting starts in the industry, so that whether the kinetic calculation model is stable can be determined according to the comparison results.

[0079] Figure 5 A flow chart of a method for smelting magnesium using a kinetic model according to another embodiment of the present invention is schematically shown.

[0080] When the difference between the initial indicator data and the actual detection data at the same time is greater than the preset interval, the method includes steps S510 to S560. Figure 5 shown.

[0081] In step S510, a first process operation parameter is acquired, where the first process operation parameter is a process operation parameter after modifying an initial process operation parameter.

[0082] In step S520, the first process operation parameter is calculated by using the kinetic computer statements in the kinetic calculation model to obtain first indicator data at multiple moments.

[0083] In step S530, first actual detection data at multiple moments in the industrial test is acquired.

[0084] In step S540, the first indicator data at the multiple moments are compared with the first actual detection data at the multiple moments.

[0085] In step S550, it is determined whether the dynamics calculation model is stable according to the first comparison result.

[0086] In step S560, steps S510 to S550 are looped until the dynamics calculation model is stable.

[0087] The method can cycle through steps S510 to S550 to optimize the initial mass transfer coefficient in the initial process operation parameters, that is, the mass transfer coefficient in step S510. When the mass transfer coefficient does not change in two consecutive optimizations or changes very little, it is determined that the kinetic model is stable.

[0088] In one embodiment of the present invention, the first process operating parameter may be a modified process operating parameter of the initial process operating parameter, for example, the first process operating parameter may be a modified mass transfer coefficient based on the initial process operating parameter.

[0089] In one embodiment of the present invention, the first index data at multiple moments may be initial index data of the kinetic model under a multi-phase system at the 400th second, the 800th second, the 1200th second, etc. when magnesium smelting starts.

[0090] In one embodiment of the present invention, the first actual detection data at multiple moments in the industrial test may be actual detection data in a multi-phase system at the 400th second, the 800th second, the 1200th second, etc. when the industry starts smelting magnesium.

[0091] Based on the above embodiment, the first index data of the kinetic model in the multiphase system at the 400th second when magnesium smelting starts and the first actual detection data of the industry in the multiphase system at the 400th second when magnesium smelting starts are compared, and whether the kinetic calculation model is stable is determined according to the comparison result. And / or the first index data and the first actual detection data at other same moments can also be compared to determine whether the kinetic calculation model is stable.

[0092] Figure 6 The flowchart schematically shows the establishment, verification, and application of the novel continuous magnesium smelting process kinetic prediction model according to the present invention. In this embodiment, the novel continuous magnesium smelting process kinetic prediction model is Figure 2 to Figure 5 In addition, the furnace in this embodiment can support continuous addition of magnesium, so the kinetic model also supports the calculation of composition changes in a multiphase system during continuous magnesium smelting.

[0093] like Figure 6 As shown, S1: Establish a new type of continuous magnesium smelting process kinetic prediction model. For example, the parameters in the kinetic calculation and the parameters in the process operation parameters are programmed into computer statements. Then, a new type of continuous magnesium smelting process kinetic prediction model is established based on these computer statements.

[0094] S2: Kinetic response mechanism of the new continuous magnesium smelting process. For example, the above-mentioned process operation parameters can be calculated through the kinetic computer statements in the kinetic model. For example, the reaction processes that can be considered in the calculation include: the floating of magnesium vapor in ferrosilicon and slag phases, the sublimation of magnesium vapor, the influence of gas powder injection, the chemical reaction between ferrosilicon and slag phases, and the chemical reaction between forging white powder particles and ferrosilicon. Specifically, the nozzle is first inserted into the ferrosilicon, and the forging white powder particles are ejected from the nozzle at a certain speed. Due to the density difference, the forging white powder particles will gradually float from the nozzle to the slag phase, and the forging white powder particles will react with the ferrosilicon during the floating process. After the forging white powder particles float to the slag phase, foamy slag will be formed. At this time, the slag phase will also react with the ferrosilicon. The magnesium vapor generated by the reaction will pass through the slag phase into the gas phase, and then be pumped away into the condensation equipment, such as Figure 7 As shown. Wherein, the condensation device is not shown in the figure. In this embodiment, the highest magnesium yield, the best reaction conditions, and the best injection rate can be obtained through this reaction mechanism.

[0095] S3: Verify the new continuous magnesium smelting process kinetic prediction model. For example, by optimizing the mass transfer coefficient in the kinetic calculation to ensure that the new continuous magnesium smelting process kinetic prediction model is stable.

[0096] S4: Applied to the production process of the new continuous magnesium smelting process. For example, after the new continuous magnesium smelting process is stabilized, the new process operation parameters can be calculated using the new continuous magnesium smelting process, so that the changes in the composition of the multi-phase system at multiple times can be obtained.

[0097] Figure 8 A block diagram of a device for smelting magnesium using a kinetic model according to an embodiment of the present invention is schematically shown.

[0098] like Figure 8 As shown, the device 200 for smelting magnesium using a kinetic model includes a first acquisition module 201 and a first calculation module 202 .

[0099] Specifically, the first acquisition module 201 is used to acquire process operation parameters during magnesium smelting.

[0100] The first calculation module 202 is used to calculate the process operation parameters through the kinetic computer statements in the kinetic model to obtain index data at multiple moments. The kinetic model is a model established based on a multiphase system, and the index data includes index data under the multiphase system.

[0101] The device 200 for smelting magnesium by a kinetic model can obtain process operation parameters during magnesium smelting, calculate the process operation parameters by kinetic computer statements in the kinetic model, and obtain index data at multiple moments. The kinetic model is a model established based on a multiphase system, and the index data includes index data under the multiphase system. In this way, the index data under the multiphase body at multiple moments can be predicted, which makes it easy to make reasonable suggestions based on the index data under the multiphase system.

[0102] According to an embodiment of the present invention, the device 200 for smelting magnesium by a kinetic model can be used to achieve Figure 2 The method of magnesium refining by kinetic modeling is described in the embodiment.

[0103] In some embodiments of the present invention, the model established based on the multiphase system includes: acquiring kinetic calculation data and historical process operation parameters, the kinetic calculation data including: chemical reactions, mass transfer coefficients, thermodynamic calculation formulas, coupled reactions, reduction period reactions, and condensation processes, the historical process operation parameters including historical furnace dimensions, historical molten pool depths, historical molten pool temperatures, historical nozzle insertion depths, historical vacuum degrees, historical nozzle rotation speeds, and historical gas injection flow rates; generating the kinetic computer statements based on the kinetic calculation data and the historical process operation parameters; and establishing the kinetic calculation model based on the kinetic computer statements.

[0104] Fig. 9 A block diagram of an apparatus for smelting magnesium using a kinetic model according to another embodiment of the present invention is schematically shown.

[0105] like Fig. 9 As shown, the device 200 for smelting magnesium using a kinetic model further includes a second acquisition module 203 , a second calculation module 204 , a third acquisition module 205 , a first comparison module 206 and a first determination module 207 .

[0106] Specifically, the second acquisition module 203 is used to acquire initial process operation parameters.

[0107] The second calculation module 204 is used to calculate the initial process operation parameters through the kinetic computer statements in the kinetic calculation model to obtain initial indicator data at multiple moments.

[0108] The third acquisition module 205 is used to acquire actual detection data at multiple moments in the industrial test.

[0109] The first comparison module 206 is used to compare the initial indicator data at the multiple moments with the actual detection data at the multiple moments.

[0110] The first determination module 207 is used to determine whether the dynamics calculation model is stable according to the comparison result.

[0111] The device 200 for smelting magnesium using a kinetic model can compare the initial index data at the multiple moments and the actual detection data at the multiple moments, and determine whether the kinetic calculation model is stable based on the comparison results, which can improve the calculation capability of the kinetic model, that is, improve the accuracy of obtaining index data.

[0112] According to an embodiment of the present invention, the device 200 for smelting magnesium by a kinetic model can be used to achieve Figure 4 The embodiment describes an apparatus 200 for smelting magnesium using a kinetic model.

[0113] Fig.10A block diagram of an apparatus for smelting magnesium using a kinetic model according to another embodiment of the present invention is schematically shown.

[0114] like Fig.10 As shown, the device 200 for smelting magnesium using a kinetic model further includes a first representation module 208 or a second representation module 209 .

[0115] Specifically, the first representation module 208 indicates that the dynamics calculation model is stable if the initial indicator data and the actual detection data at the same time are the same or similar.

[0116] The second indicating module 209 indicates that the dynamics calculation model is unstable if the difference between the initial indicator data and the actual detection data at the same time is greater than a preset interval.

[0117] Fig.11 A block diagram of an apparatus for smelting magnesium using a kinetic model according to another embodiment of the present invention is schematically shown.

[0118] like Fig.11 As shown, when the difference between the initial indicator data and the actual detection data at the same time is greater than the preset interval, the device 200 for smelting magnesium through a kinetic model also includes a fourth acquisition module 210, a third calculation module 211, a fifth acquisition module 212, a second comparison module 213, a second determination module 214 and a circulation module 215.

[0119] Specifically, the fourth acquisition module 210 is used to acquire a first process operation parameter, where the first process operation parameter is a process operation parameter after modifying an initial process operation parameter.

[0120] The third calculation module 211 is used to calculate the first process operation parameter through the kinetic computer statement in the kinetic calculation model to obtain the first indicator data at multiple moments.

[0121] The fifth acquisition module 212 is used to acquire first actual detection data at multiple moments in the industrial test.

[0122] The second comparison module 213 is used to compare the first indicator data at the multiple moments with the first actual detection data at the multiple moments.

[0123] The second determination module 214 is used to determine whether the dynamics calculation model is stable according to the first comparison result.

[0124] The loop module 215 is used to loop the above steps until the kinetic calculation model is stable.

[0125] The device 200 for smelting magnesium by a kinetic model can cycle through steps S510 to S550 to optimize the initial mass transfer coefficient in the initial process operation parameters, i.e., the mass transfer coefficient in step S510. When the mass transfer coefficient does not change in two consecutive optimizations, or changes very little, it is determined that the kinetic model is stable.

[0126] According to an embodiment of the present invention, the device 200 for smelting magnesium by a kinetic model can be used to achieve Figure 5 The method of magnesium refining by kinetic modeling is described in the embodiment.

[0127] Since each module of the apparatus 200 for smelting magnesium by a kinetic model according to an exemplary embodiment of the present invention can be used to implement the above 2~ Figure 5 The steps of an exemplary embodiment of the method for smelting magnesium by a kinetic model are described, so for details not disclosed in the embodiment of the apparatus of the present invention, please refer to the embodiment of the method for smelting magnesium by a kinetic model of the present invention described above.

[0128] It can be understood that at least one of the first acquisition module 201, the first calculation module 202, the second acquisition module 203, the second calculation module 204, the third acquisition module 205, the first comparison module 206, the first determination module 207, the first representation module 208, the second representation module 209, the fourth acquisition module 210, the third calculation module 211, the fifth acquisition module 212, the second comparison module 213, the second determination module 214, and the loop module 215 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented in hardware or firmware in any other reasonable way of integrating or packaging circuits, or in an appropriate combination of software, hardware and firmware. Alternatively, at least one of the first acquisition module 201, the first calculation module 202, the second acquisition module 203, the second calculation module 204, the third acquisition module 205, the first comparison module 206, the first determination module 207, the first representation module 208, the second representation module 209, the fourth acquisition module 210, the third calculation module 211, the fifth acquisition module 212, the second comparison module 213, the second determination module 214, and the loop module 215 can be at least partially implemented as a computer program module, and when the program is run by a computer, the functions of the corresponding module can be executed.

[0129] Reference below Fig.12 , which shows a schematic diagram of the structure of a computer system 300 of an electronic device suitable for implementing an embodiment of the present invention. Fig.12The computer system 300 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0130] like Fig.12 As shown, the computer system 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage part 308 into a random access memory (RAM) 303. Various programs and data required for system operation are also stored in the RAM 303. The CPU 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0131] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, a mouse, etc.; an output section 307 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed, so that a computer program read therefrom is installed into the storage section 308 as needed.

[0132] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 309, and / or installed from a removable medium 311. When the computer program is executed by a central processing unit (CPU) 301, the above-mentioned functions defined in the system of the present application are executed.

[0133] It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0134] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0135] The units involved in the embodiments of the present invention may be implemented by software or hardware, and the units described may also be arranged in a processor. The names of these units do not, in some cases, limit the units themselves.

[0136] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method for smelting magnesium by a kinetic model as described in the above embodiment.

[0137] For example, the electronic device can implement Figure 2 As shown in: Obtaining process operation parameters during magnesium smelting. In step S220, the process operation parameters are calculated by the kinetic computer statements in the kinetic model to obtain index data at multiple moments, the kinetic model is a model established based on a multiphase system, and the index data includes index data under the multiphase system.

[0138] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0139] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation of the present invention.

[0140] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the following claims.

[0141] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for smelting magnesium by a kinetic model, characterized in that: The method includes: Obtain the process operation parameters during magnesium smelting; The process operation parameters are calculated by the kinetic computer statements in the kinetic model to obtain index data at multiple moments. The kinetic model is a model established based on a multiphase system. The index data include index data under the multiphase system. The multiphase system includes a quaternary multiphase system. The quaternary multiphase system is ferrosilicon, calcined molten steel, slag phase, and gas phase. The index data under the quaternary multiphase system are ferrosilicon composition, slag phase composition, gas phase pressure, and magnesium condensation amount. The process operation parameters include furnace body size, molten pool depth, molten pool temperature, nozzle insertion depth, vacuum degree, nozzle rotation speed, and gas blowing flow rate.

2. The method according to claim 1, characterized in that The model established based on the multiphase system includes: Acquire kinetic calculation data and historical process operation parameters, wherein the kinetic calculation data includes: chemical reaction, mass transfer coefficient, thermodynamic calculation formula, coupling reaction, reduction period reaction, and condensation process, and the historical process operation parameters include historical furnace size, historical molten pool depth, historical molten pool temperature, historical nozzle insertion depth, historical vacuum degree, historical nozzle rotation speed, and historical gas injection flow rate; generating the kinetic computer statements based on the kinetic calculation data and the historical process operation parameters; A dynamics calculation model is established based on the dynamics computer statements.

3. The method according to claim 2, characterized in that After establishing the dynamics calculation model, the method further comprises: Obtaining initial process operating parameters; Calculating the initial process operation parameters by using the kinetic computer statements in the kinetic calculation model to obtain initial indicator data at multiple moments; Obtain actual test data at multiple times during industrial testing; Comparing the initial indicator data at the multiple moments with the actual detection data at the multiple moments; Whether the dynamics calculation model is stable is determined according to the comparison result.

4. The method according to claim 3, characterized in that The method further includes: If the initial indicator data at the same time is the same as or close to the actual detection data, it means that the dynamic calculation model is stable; or If the difference between the initial indicator data and the actual detection data at the same time is greater than a preset interval, it means that the dynamic calculation model is unstable.

5. The method according to claim 4, characterized in that When the difference between the initial indicator data and the actual detection data at the same time is greater than a preset interval, the method includes: Acquire a first process operation parameter, where the first process operation parameter is a process operation parameter after modifying an initial process operation parameter; Calculating the first process operation parameter by using the kinetic computer statements in the kinetic calculation model to obtain first indicator data at multiple moments; Acquire first actual detection data at multiple moments in the industrial test; Comparing the first indicator data at the multiple moments with the first actual detection data at the multiple moments; Determining whether the dynamics calculation model is stable according to the first comparison result; The above steps are repeated until the kinetic calculation model is stable.

6. A device for smelting magnesium by a kinetic model, characterized in that: The device includes: The first acquisition module is used to obtain the process operation parameters during magnesium smelting; The first calculation module is used to calculate the process operation parameters through the kinetic computer statements in the kinetic model to obtain index data at multiple moments. The kinetic model is a model established based on a multiphase system. The index data include index data under the multiphase system. The multiphase system includes a quaternary multiphase system. The quaternary multiphase system is ferrosilicon, calcined molten steel, slag phase, and gas phase. The index data under the quaternary multiphase system are ferrosilicon composition, slag phase composition, gas phase pressure, and magnesium condensation amount. The process operation parameters include furnace size, molten pool depth, molten pool temperature, nozzle insertion depth, vacuum degree, nozzle rotation speed, and gas blowing flow rate.

7. An electronic device comprising: one or more processors; as well as A storage device, used for storing one or more programs, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the method according to any one of claims 1 to 5.

8. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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