CN114692434B - Grading method and device for preheating scrap steel, electronic equipment and storage medium - Google Patents

Grading method and device for preheating scrap steel, electronic equipment and storage medium Download PDF

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CN114692434B
CN114692434B CN202210618119.XA CN202210618119A CN114692434B CN 114692434 B CN114692434 B CN 114692434B CN 202210618119 A CN202210618119 A CN 202210618119A CN 114692434 B CN114692434 B CN 114692434B
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scrap
grade
preheating
steel raw
raw materials
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CN114692434A (en
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朱立光
鲁素玲
郭志红
杨春牛
郑亚旭
韩宝臣
王旗
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Hebei University of Science and Technology
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Hebei University of Science and Technology
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Priority to PCT/CN2023/096783 priority patent/WO2023231951A1/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • C—CHEMISTRY; METALLURGY
    • C21—METALLURGY OF IRON
    • C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
    • C21C5/00—Manufacture of carbon-steel, e.g. plain mild steel, medium carbon steel or cast steel or stainless steel
    • C21C5/28—Manufacture of steel in the converter
    • C—CHEMISTRY; METALLURGY
    • C21—METALLURGY OF IRON
    • C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
    • C21C5/00—Manufacture of carbon-steel, e.g. plain mild steel, medium carbon steel or cast steel or stainless steel
    • C21C5/56—Manufacture of steel by other methods
    • C21C5/562—Manufacture of steel by other methods starting from scrap
    • C21C5/565—Preheating of scrap
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06313—Resource planning in a project environment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • C—CHEMISTRY; METALLURGY
    • C21—METALLURGY OF IRON
    • C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
    • C21C2300/00—Process aspects
    • C21C2300/06—Modeling of the process, e.g. for control purposes; CII
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/04—Constraint-based CAD
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P10/00—Technologies related to metal processing
    • Y02P10/20—Recycling
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Abstract

The invention provides a grading method and device for scrap steel preheating, electronic equipment and a storage medium. The method comprises the following steps: dividing the waste steel raw material to be processed into M grades based on predetermined waste steel grading standards; determining the addition amount of each grade of waste steel raw material according to a preset objective function based on the preset constraint condition of each grade of waste steel raw material; the preset constraint condition is constructed according to the attribute parameters of the waste steel raw materials of all levels, and the preset objective function is determined according to the specific surface area coefficient of the waste steel raw materials of all levels; determining N distribution modes of the waste steel raw materials of all levels in the waste steel preheating device according to the adding amount of the waste steel raw materials of all levels; and calculating the preheating temperature of the waste steel raw materials of each grade under various distribution formulas, and determining the optimal distribution mode according to the preheating temperature of the waste steel raw materials of each grade under various distribution formulas. The invention can improve the efficiency of scrap steel preheating and reduce the power consumption.

Description

Grading method and device for preheating scrap steel, electronic equipment and storage medium
Technical Field
The invention relates to the technical field of scrap steel metallurgy, in particular to a scrap steel preheating grading method, a scrap steel preheating grading device, electronic equipment and a storage medium.
Background
As an important strategic resource, the steel reserves in the world are continuously increased, and the release amount of steel scrap raw materials is continuously increased. The treatment method of the scrap steel during steelmaking mainly uses a converter or an electric furnace for smelting and recycling, and the electric furnace steelmaking has the advantages of short flow, energy conservation, environmental protection and the like compared with the traditional converter long flow, so that the electric furnace steelmaking is inevitably the development trend of the industry in the future. Electric furnaces are divided into intermediate frequency furnaces, electric arc furnaces, resistance furnaces and the like, scrap steel is heated and melted by adopting modes of electromagnetism, electric arc, conductor impedance and the like, and the main energy consumption is electric energy. At present, in a converter smelting process, compared with molten iron, scrap steel has the advantages of low cost and environmental protection, so that in the converter steelmaking process, the addition ratio of the scrap steel is improved, the cost is reduced, the energy is saved, and the environmental pollution is reduced.
The conventional steel making method generally adds the steel scrap at normal temperature, the heat generated in the smelting process of the converter is limited, a large amount of steel scrap at normal temperature is difficult to melt rapidly, the energy consumption is increased, and the production efficiency is reduced. Because of the defects of the traditional steelmaking, the technical means of scrap steel preheating is generated to make up the defects of high energy consumption and frequent smelting period. However, in the prior art, when scrap steel is used for preheating, a reasonable distribution mode is not considered, and the problems of energy waste and low efficiency are still caused.
Disclosure of Invention
The embodiment of the invention provides a grading method and device for scrap steel preheating, electronic equipment and a storage medium, and aims to solve the problems that in the prior art, when scrap steel preheating is adopted, a reasonable distribution mode is not considered, energy waste and low efficiency are still caused.
In a first aspect, the invention provides a grading method for scrap steel preheating, comprising the following steps:
dividing the waste steel raw material to be processed into M grades based on predetermined waste steel grading standards;
determining the addition amount of each grade of waste steel raw material according to a preset objective function based on the preset constraint condition of each grade of waste steel raw material; the preset constraint condition is constructed according to the attribute parameters of the waste steel raw materials of all levels, and the preset objective function is determined according to the specific surface area coefficient of the waste steel raw materials of all levels;
determining N distribution modes of the waste steel raw materials of all levels in the waste steel preheating device according to the adding amount of the waste steel raw materials of all levels;
and calculating the preheating temperature of each grade of waste steel raw material under various distribution formulas, and determining the optimal distribution mode according to the preheating temperature of each grade of waste steel raw material under various distribution formulas.
In one possible implementation, the attribute parameters of each grade of steel scrap raw material include the added amount of each grade of steel scrap raw material, the bulk density of each grade of steel scrap raw material, the cost of each grade of steel scrap raw material, and the inventory amount of each grade of steel scrap raw material.
In one possible implementation, the preset constraint condition includes: a first constraint, a second constraint, a third constraint and a fourth constraint;
the first constraint is:
Figure DEST_PATH_IMAGE001
(ii) a Wherein the content of the first and second substances,x i is as followsiThe addition amount of the raw material of the scrap steel of each grade,p i is as followsiThe bulk density of the individual grades of scrap steel feedstock,V max is the maximum capacity of the scrap preheating device,V min the minimum allowable capacity of the scrap steel preheating device under the nominal capacity;
the second constraint is:
Figure 997323DEST_PATH_IMAGE002
(ii) a Wherein, the first and the second end of the pipe are connected with each other,C i is as followsiThe unit price of each grade of scrap steel raw material,C min a lower threshold for a preset total cost,C max an upper threshold value for a preset total cost;
the third constraint is:
Figure DEST_PATH_IMAGE003
；
wherein the content of the first and second substances,ω i is as followsiThe ratio of the stock of the individual-grade steel scrap raw materials to the number of the preset steel-making furnace times;
the fourth constraint condition is as follows:
Figure 195086DEST_PATH_IMAGE004
；
wherein the content of the first and second substances,wfor the maximum containment quality of the scrap preheating device,y 1 in order to lay the bottom material in a certain quantity,y 1min the minimum value of the bottom material paving amount required by the scrap steel preheating device.
In one possible implementation, the preset objective function is:
Figure DEST_PATH_IMAGE005
wherein the content of the first and second substances,x i is as followsiThe addition amount of the raw material of the scrap steel of each grade,a i is as followsiSpecific surface area coefficient of individual grade scrap material.
In one possible implementation, the formula for calculating the preheating temperature of each grade of scrap steel raw material under each cloth formula is:
Figure 742742DEST_PATH_IMAGE006
wherein the content of the first and second substances,T ij is as followsiThe individual grade of scrap steel raw material isjThe preheating temperature under the formula of the seed cloth,s i is as followsiThe specific surface area of the individual grades of scrap steel feedstock,μin order to obtain a convective heat transfer coefficient,p i is as followsiThe bulk density of the individual grade scrap material,cthe specific heat capacity is the specific heat capacity,tin order to achieve the pre-heating time of the preset temperature,k 1ij is as followsiIn the first step of individual grades of scrapjThe mass coefficient under the formula of the seed cloth,k 2i is as followsiThe shape comprehensive coefficient of the individual grade of the scrap steel raw material,T gij is as followsiIn the first step of individual grades of scrapjThe temperature of the flue gas under the formula of the seed cloth,T s is the initial temperature.
In one possible implementation manner, the determining of the optimal distribution manner according to the preheating temperature of each grade of the scrap steel raw material under various distribution manners comprises the following steps: for each distribution mode, calculating the difference value of the highest temperature and the lowest temperature in the preheating temperatures of all grades of scrap steel raw materials in the distribution mode as the temperature difference value in the distribution mode; selecting a cloth formula corresponding to the minimum temperature difference value as an optimal cloth formula; or, for each distribution mode, calculating the average temperature value of the preheating temperatures of all grades of scrap steel raw materials in the distribution mode; selecting a distribution formula corresponding to the highest average temperature value as an optimal distribution formula; or, for each cloth distribution mode, acquiring the highest temperature value of the preheating temperatures of all grades of waste steel raw materials under the cloth distribution mode; selecting a distribution formula corresponding to the maximum temperature value lower than a preset threshold value as an optimal distribution formula; wherein the preset threshold is determined according to the solidus line of the scrap steel raw material.
In one possible implementation manner, determining the addition amount of each grade of waste steel raw material according to a preset objective function based on a preset constraint condition of each grade of waste steel raw material includes:
and solving the preset objective function by using a planning algorithm based on the preset constraint conditions of the waste steel raw materials of all levels, and taking the solved result as the adding amount of the waste steel raw materials of all levels.
In a second aspect, the present invention provides a grading apparatus for scrap preheating, comprising:
the dividing module is used for dividing the waste steel raw materials to be processed into M grades based on predetermined waste steel grading standards;
the first calculation module is used for determining the adding amount of each grade of waste steel raw material according to a preset target function based on the preset constraint condition of each grade of waste steel raw material; the preset constraint condition is constructed according to the attribute parameters of the waste steel raw materials of all levels, and the preset objective function is determined according to the specific surface area of the waste steel raw materials of all levels;
the second calculation module is used for determining N distribution modes of the waste steel raw materials of all levels in the waste steel preheating device according to the adding amount of the waste steel raw materials of all levels;
and the selection module is used for calculating the preheating temperature of each grade of waste steel raw material under various distribution formulas and determining the optimal distribution mode according to the preheating temperature of each grade of waste steel raw material under various distribution formulas.
In a third aspect, the present invention provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program operable on the processor, and the processor executes the computer program to implement the steps of the grading method for scrap preheating according to the first aspect or any one of the possible implementations of the first aspect.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program for implementing the steps of the grading method for scrap preheating as described in the first aspect or any one of the possible implementations of the first aspect.
The invention provides a grading method and device for scrap steel preheating, electronic equipment and a storage medium. Then, the distribution mode of the scrap steel raw materials of each grade is determined according to the addition amount, and the scrap steel preheating efficiency is improved. And finally, determining an optimal distribution mode according to the preheating temperatures in various distribution modes, and preheating the scrap steel according to the optimal distribution mode, so that the integral power consumption can be reduced while the scrap steel preheating efficiency is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a flow chart of the implementation of a grading method for scrap preheating provided by an embodiment of the invention;
FIG. 2 is a schematic structural diagram of a grading device for scrap preheating provided by an embodiment of the invention;
fig. 3 is a schematic diagram of an electronic device provided in an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following description is made by way of specific embodiments with reference to the accompanying drawings. Referring to fig. 1, it shows a flow chart for implementing a grading method for scrap preheating according to an embodiment of the present invention. As shown in fig. 1, a grading method for scrap preheating may include:
s101, dividing the waste steel raw material to be processed into M grades based on a predetermined waste steel grading standard. Where M is a positive integer, for example, M may be 4.
Optionally, the waste steel raw material to be treated is waste steel which needs to be preheated. Before the waste steel raw materials are treated, grading can be carried out according to specification parameters of the waste steel raw materials, and the grading standard of the waste steel is determined. The specification parameters may include feature size, bulk density, class, specific surface area, and the like. The waste steel raw materials are graded, so that the treatment efficiency of the waste steel can be improved.
Optionally, the optical image processing method may be adopted to collect specification parameters of the scrap steel raw material, and the length and thickness of the scrap steel raw material may be obtained. For example, the AI intelligent recognition method may be used to identify and read parameters such as the size and type of the scrap, and obtain specification parameters of the scrap.
Illustratively, the scrap steel raw material may be specifically classified into four major grades according to specification parameters, i.e., the scrap steel classification standard may be as shown in table 1, as follows:
TABLE 1 scrap grading Standard
Figure 506298DEST_PATH_IMAGE007
S102, determining the adding amount of each grade of waste steel raw material according to a preset objective function based on the preset constraint condition of each grade of waste steel raw material; the preset constraint condition is constructed according to the attribute parameters of the waste steel raw materials of all levels, and the preset objective function is determined according to the specific surface area coefficient of the waste steel raw materials of all levels.
Optionally, the attribute parameters of each grade of steel scrap raw material may include the addition amount of each grade of steel scrap raw material, the bulk density of each grade of steel scrap raw material, the cost of each grade of steel scrap raw material, the stock of each grade of steel scrap raw material, the nominal weight of the steel scrap preheating device, and other parameters.
Optionally, the preset objective function may be solved by using a planning algorithm based on the preset constraint condition of each grade of the steel scrap raw material, and the solved result is used as the addition amount of each grade of the steel scrap raw material. The reasonable adding amount of the waste steel raw materials of each grade is calculated through the constraint conditions, so that the treatment preheating efficiency of the waste steel raw materials can be improved.
Specifically, the constraint function is used for solving the problem of solving the optimal solution of variables in the planning; limiting the value range of the variable by setting a constraint condition on the variable; and calculating the optimal solution of the constraint function through a planning algorithm. For example, the planning algorithm includes an interval approximation algorithm.
S103, determining N distribution modes of the waste steel raw materials of all levels in the waste steel preheating device according to the adding amount of the waste steel raw materials of all levels. Wherein N can be calculated from M, i.e. N is
Figure 481208DEST_PATH_IMAGE008
A positive integer, for example, when M is 4, N is 24.
Optionally, the scrap steel raw material needs to be preheated in a scrap steel preheating device, and the distribution mode of the scrap steel raw material needs to be determined. After the reasonable adding amount of the waste steel raw materials of each grade is determined, N distribution modes of the waste steel raw materials of each grade in the waste steel preheating device are determined in a permutation and combination mode.
And S104, calculating the preheating temperature of the waste steel raw materials of each grade under various distribution formulas, and determining the optimal distribution mode according to the preheating temperature of the waste steel raw materials of each grade under various distribution formulas.
Optionally, different cloth formulas may correspond to different preheating temperatures, that is, to different heating power consumptions.
Specifically, the constraint parameters of the formula of the preheating temperature of each grade of the scrap steel raw material can comprise the addition amount, the bulk density, the specific surface area, the height in the preheating device and the like of each grade of the scrap steel raw material.
The formula for calculating the preheating temperature of the scrap steel raw materials of each grade under various cloth formula formulas is as follows:
Figure 697425DEST_PATH_IMAGE006
T ij is a firstiThe individual grade of scrap steel raw material isjThe preheating temperature under the formula of the seed cloth,s i is as followsiThe specific surface area of the individual grades of scrap steel feedstock,μin order to obtain a convective heat transfer coefficient,p i is as followsiThe bulk density of the individual grades of scrap steel feedstock,cthe specific heat capacity is the specific heat capacity,tin order to achieve the pre-heating time of the preset temperature,k 1ij is as followsiIn the first step of individual grade of scrapjThe mass coefficient under the formula of the seed cloth,k 2i is as followsiThe shape comprehensive coefficient of the individual grade of the scrap steel raw material,T gij is as followsiIn the first step of individual grades of scrapjThe temperature of the flue gas under the formula of the seed cloth,T s is the initial temperature.
Wherein, each parameter difference between the waste steel raw materials of each grade is not large.
Therefore, different scrap steel raw materials correspond to different specific heat capacities, the specific heat capacities of the scrap steel raw materials are close to each other, the specific heat capacity in the formula can be the average specific heat capacity of each scrap steel raw material, and the specific heat capacity can be specifically selected according to actual conditions. The convective heat transfer coefficient can also be of each wasteAverage convective heat transfer coefficient of the steel feedstock. The preset temperature between different steel scrap raw materials can be the same and can be T. The preheating time may be the same between different scrap materials. Initial temperature of scrap Material of respective gradesT s The difference is not large and can be the same, so that the complexity of calculation is reduced. The flue gas temperature generally refers to the average temperature of flue gas in the scrap steel preheating device, namely the flue gas temperature is the flue gas temperature after the scrap steel preheating device is stable, and can be obtained according to actual conditions.
k 1ij The mass coefficient is the coefficient of influence of the addition amount of the waste steel raw materials of different grades on preheating, the more the addition mass is, the smaller the coefficient is, the lower the average preheating temperature is, and meanwhile, the coefficient is also related to the type and arrangement mode of the waste steel. Coefficient of massk 1ij The method is characterized in that the scrap steel raw materials with different cloth formula modes correspond to different mass coefficients under the influence of the cloth formula modes.
k 2i Is a shape synthesis factor. And counting the shapes and sizes of the waste steel raw materials of different grades, and obtaining the shape comprehensive coefficient of the waste steel raw materials of each grade based on the influence of the shapes and sizes on the preheating temperature. The preheating temperature of each steel scrap raw material is different under the condition of the same specific surface area due to different shapes and sizes. Coefficient of integration of shapek 2i The method is determined according to a simulation test, each steel scrap raw material corresponds to a shape comprehensive coefficient, and the shape comprehensive coefficient is not influenced by a distribution mode.
According to the embodiment of the invention, through calculating the reasonable adding amount of the scrap steel raw materials of each grade and the optimal distribution mode, the convenience of primary preheating is kept, and the phenomenon of uneven preheating temperature caused by increasing the preheating temperature is improved.
In some embodiments of the present invention, the preset constraint condition in S102 may include: a first constraint, a second constraint, a third constraint and a fourth constraint;
the first constraint is:
Figure 579931DEST_PATH_IMAGE001
；
wherein the content of the first and second substances,x i is as followsiThe addition amount of the raw material of the scrap steel of each grade,p i is as followsiThe bulk density of the individual grades of scrap steel feedstock,V max is the maximum capacity of the scrap preheating device,V min the minimum allowable capacity of the scrap steel preheating device under the nominal capacity;
the second constraint is:
Figure 135677DEST_PATH_IMAGE002
；
wherein the content of the first and second substances,C i is as followsiThe unit price of each grade of scrap steel raw material,C min a lower threshold for a preset total cost,C max an upper threshold value for a preset total cost; for example, the unit of unit price may be expressed as "yuan/ton", and the unit of addition amount of the scrap raw material may be "ton".
The third constraint is:
Figure 343804DEST_PATH_IMAGE003
；
wherein the content of the first and second substances,ω i is as followsiThe ratio of the stock of the individual-grade steel scrap raw materials to the number of the preset steel-making furnace times;
the fourth constraint is:
Figure 985001DEST_PATH_IMAGE004
；
wherein the content of the first and second substances,wfor the maximum containment quality of the scrap preheating device,y 1 in order to lay the bottom material in a certain quantity,y 1min the minimum value of the bottom material paving amount required by the scrap steel preheating device. The quantity of bedding material being bedding scrap material, e.g. inx 1 When the bottom is paved,y 1 =x 1 (ii) a In thatx 2 When the bottom is paved, the water is paved,y 1 =x 2 and so on. Namely atx i When the bottom is paved, the water is paved,y 1 =x i . In general, the bottom layer material is light and thin, so that the preheating efficiency can be improved.
The first constraint condition is used for constraining the adding amount of the waste steel raw materials of each level through a bulk density function, the second constraint condition is used for constraining the adding amount of the waste steel raw materials of each level through cost, the third constraint condition is used for constraining the adding amount of the waste steel raw materials of each level through the stock of the waste steel raw materials of each level, and the fourth constraint condition is used for constraining the adding amount of the waste steel raw materials of each level through the weight of a waste steel preheating device.
Optionally, the preset objective function in S102 is:
Figure 671198DEST_PATH_IMAGE005
wherein, the first and the second end of the pipe are connected with each other,x i is as followsiThe addition amount of the raw material of the scrap steel of each grade,a i is a firstiSpecific surface area coefficient of individual grade scrap material. The specific surface area coefficient is a coefficient given by sorting based on data of specific surface areas of the scrap at each level.
In some embodiments of the invention, different distribution modes are obtained by permutation and combination based on the addition amount of the waste steel raw materials of each level, the temperature of the waste steel raw materials of each level under different distribution modes is obtained by calculation, and the optimal distribution mode is obtained by comparing the temperature difference, the average temperature and the maximum temperature.
Specifically, the "determining the optimal distribution mode according to the preheating temperature of the scrap steel raw materials of each grade under each distribution formula" in S104 may include:
for each distribution mode, calculating the difference value between the highest temperature and the lowest temperature in the preheating temperatures of all levels of the scrap steel raw materials in the distribution mode as the temperature difference value in the distribution mode; selecting a cloth formula corresponding to the minimum temperature difference value as an optimal cloth formula; alternatively, the first and second electrodes may be,
for each distribution mode, calculating the average temperature value of the preheating temperatures of all levels of the scrap steel raw materials in the distribution mode; selecting a distribution formula corresponding to the highest average temperature value as an optimal distribution formula; alternatively, the first and second liquid crystal display panels may be,
for each cloth distribution mode, acquiring the highest temperature value of the preheating temperatures of all grades of scrap steel raw materials under the cloth distribution mode; selecting a distribution formula corresponding to the maximum temperature value lower than a preset threshold value as an optimal distribution formula; wherein the preset threshold is determined according to the solidus of the scrap steel raw material, and the preset threshold can be a value lower than the solidus of the scrap steel by 100 ℃.
Illustratively, a 130 ton electric arc furnace scrap is preheated, the weight of the preheated scrap in a single smelting is 70 tons, and the grade standard of the scrap is M = 4.
The preset objective function is:
Figure 347030DEST_PATH_IMAGE009
。
the preset constraint conditions include:
Figure 460479DEST_PATH_IMAGE010
；
Figure 651289DEST_PATH_IMAGE011
；
Figure 78859DEST_PATH_IMAGE012
；
Figure 405935DEST_PATH_IMAGE013
；
wherein the content of the first and second substances,y 1min =5t，V max =55m 3 ，V min =45m 3 the cost of the first-level to fourth-level waste steel raw materials is 2600 yuan/ton, 2500 yuan/ton, 2700 yuan/ton and 2800 yuan/ton respectively, C +3000 is an upper limit threshold of preset cost, C-3000 is a lower limit threshold of preset cost, C is an average value of total cost of each ton of waste steel raw materials in long-term production, 3000 is a maximum cost variable preset by YuanAnd (5) changing the amplitude.
Through planning calculation, the reasonable addition amounts of the first-stage to fourth-stage waste steel raw materials are respectively as follows: 17.2 tons, 20.2 tons, 10 tons and 22.6 tons.
Further, the preheating temperature of the 70 ton steel scrap was calculated and shown in Table 2. Wherein, the first and the second end of the pipe are connected with each other,
Figure 690286DEST_PATH_IMAGE014
the first type of scrap, except for the bedding layer, is shown in the following table:
table 2 preheating thermometer for calculating 70 ton steel scrap
Figure 804611DEST_PATH_IMAGE015
The cloth recipe corresponding to the minimum temperature difference value is selected as the optimal cloth recipe, and the cloth recipe 18 is selected. Compared with the traditional distribution scheme, the distribution mode selected by the scrap steel preheating grading method provided by the embodiment of the invention reduces the consumption of electric energy in the smelting process by 5kwh/t, saves the electrode consumption by 0.3-0.5 kg/t, and shortens the smelting period of 3 minutes.
Illustratively, the method provided by the embodiment of the invention is applied to preheating of 300 tons of converter steel scraps, 4105kg of steel scraps can be increased under the condition of not influencing the heat balance of the converter, and the steel scrap ratio is improved by nearly 1%.
According to the embodiment of the invention, the optimal addition amount of each grade of scrap steel is obtained by constructing a constraint equation and an objective function of the scrap steel raw material; and (3) carrying out permutation and combination based on the addition amount of each grade of the waste steel raw materials to obtain different distribution modes, calculating the temperature of each grade of the waste steel raw materials under different distribution modes, and comparing the temperature difference, the average temperature and the maximum temperature to obtain the optimal distribution mode. The overall preheating temperature and the preheating uniformity are improved, the energy consumption is reduced, the smelting period is shortened, and the effects of low carbon and high efficiency are achieved.
The embodiment of the invention achieves the aim of optimizing distribution by a linear programming mathematical model and a preheating temperature function, not only maintains the convenience of primary preheating, but also improves the phenomenon of uneven preheating temperature caused by increasing the preheating temperature.
According to the embodiment provided by the invention, through the constructed mathematical model, the quick computer operation can be realized, the calculation result is accurate, the production efficiency is improved, the stability of process smelting is favorably kept, the smelting period is effectively reduced, the operability is strong, and the popularization is easy.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
The following are embodiments of the apparatus of the invention, reference being made to the corresponding method embodiments described above for details which are not described in detail therein.
Fig. 2 is a schematic structural diagram of a grading apparatus for preheating scrap according to an embodiment of the present invention, and for convenience of description, only the parts related to the embodiment of the present invention are shown, and the details are as follows:
as shown in fig. 2, the grading apparatus 20 for scrap preheating may include:
a dividing module 201, configured to divide the steel scrap raw material to be processed into M grades based on a predetermined steel scrap classification standard;
the first calculation module 202 is used for determining the adding amount of each grade of waste steel raw material according to a preset objective function based on the preset constraint condition of each grade of waste steel raw material; the preset constraint condition is constructed according to the attribute parameters of the waste steel raw materials of all levels, and the preset objective function is determined according to the specific surface area of the waste steel raw materials of all levels;
the second calculation module 203 is used for determining N distribution modes of the waste steel raw materials of all levels in the waste steel preheating device according to the adding amount of the waste steel raw materials of all levels;
and the selection module 204 is used for calculating the preheating temperature of each grade of the waste steel raw materials under various distribution formulas and determining the optimal distribution mode according to the preheating temperature of each grade of the waste steel raw materials under various distribution formulas.
In some embodiments of the present invention, the attribute parameters of each grade of scrap material include an amount of each grade of scrap material added, a bulk density of each grade of scrap material, a cost of each grade of scrap material, and an inventory amount of each grade of scrap material.
In some embodiments of the present invention, the preset constraint condition may include: a first constraint, a second constraint, a third constraint and a fourth constraint;
the first constraint is:
Figure 98189DEST_PATH_IMAGE001
；
wherein the content of the first and second substances,x i is as followsiThe adding amount of the raw material of the individual grade steel scrap,p i is as followsiThe bulk density of the individual grades of scrap steel feedstock,V max is the maximum capacity of the scrap preheating device,V min the minimum allowable capacity of the scrap steel preheating device under the nominal capacity;
the second constraint is:
Figure 483034DEST_PATH_IMAGE002
；
wherein, the first and the second end of the pipe are connected with each other,C i is a firstiThe unit price of each grade of scrap steel raw material,C min a lower threshold for a preset total cost,C max an upper threshold value for a preset total cost;
the third constraint is:
Figure 938286DEST_PATH_IMAGE003
；
wherein the content of the first and second substances,ω i is as followsiThe ratio of the stock of the individual-grade steel scrap raw materials to the number of preset steel-making furnace times;
the fourth constraint is:
Figure 41371DEST_PATH_IMAGE004
；
wherein the content of the first and second substances,was maximum as scrap preheating meansThe mass is contained in the container body,y 1 in order to lay the bottom material in a certain quantity,y 1min the minimum value of the amount of the bottom material required by the scrap preheating device.
In some embodiments of the invention, the preset objective function is:
Figure 873061DEST_PATH_IMAGE005
wherein the content of the first and second substances,x i is as followsiThe addition amount of the raw material of the scrap steel of each grade,a i is a firstiSpecific surface area coefficient of individual grade scrap material.
In some embodiments of the present invention, the preheating temperature for each grade of scrap feedstock for each distribution formula is calculated as:
Figure 174729DEST_PATH_IMAGE006
wherein the content of the first and second substances,T ij is as followsiThe scrap steel of the first grade isjThe preheating temperature under the formula of the seed cloth,s i is as followsiThe specific surface area of the individual grades of scrap steel feedstock,μin order to obtain the heat convection coefficient,p i is a firstiThe bulk density of the individual grade scrap material,cthe specific heat capacity is the specific heat capacity,tin order to achieve the pre-heating time of the preset temperature,k 1ij is as followsiIn the first step of individual grades of scrapjThe mass coefficient under the formula of the seed cloth,k 2i is as followsiThe shape comprehensive coefficient of the individual grade of the scrap steel raw material,T gij is as followsiIn the first step of individual grades of scrapjThe temperature of the flue gas under the formula of the seed cloth,T s is the initial temperature.
In some embodiments of the present invention, the selection module 204 may include a first calculation unit, a second calculation unit, or a third calculation unit:
the first calculation unit is used for calculating the difference value between the highest temperature and the lowest temperature in the preheating temperatures of all levels of the scrap steel raw materials in the distribution mode as the temperature difference value in the distribution mode for each distribution mode; selecting a cloth formula corresponding to the minimum temperature difference value as an optimal cloth formula;
the second calculation unit is used for calculating the average temperature value of the preheating temperatures of all levels of the scrap steel raw materials in each distribution mode; selecting a distribution formula corresponding to the highest average temperature value as an optimal distribution formula;
the third calculation unit is used for acquiring the highest temperature value of the preheating temperatures of all levels of the scrap steel raw materials in each distribution mode; selecting a distribution formula corresponding to the maximum temperature value lower than a preset threshold value as an optimal distribution formula; wherein the preset threshold is determined according to the solidus line of the scrap steel raw material.
In some embodiments of the invention, the first calculation module 202 may include:
and the fourth calculating unit is used for solving the preset objective function by using a planning algorithm based on the preset constraint conditions of the waste steel raw materials of all levels, and taking the solved result as the adding amount of the waste steel raw materials of all levels.
Fig. 3 is a schematic diagram of an electronic device provided in an embodiment of the present invention. As shown in fig. 3, the electronic apparatus 30 of this embodiment includes: a processor 300 and a memory 301, the memory 301 comprising a computer program 302 operable on the processor 300. The processor 300, when executing the computer program 302, implements the steps in the various steel scrap preheating grading method embodiments described above, such as S101-S104 shown in fig. 1. Alternatively, the processor 300, when executing the computer program 302, implements the functions of the modules/units in the above-described device embodiments, such as the modules/units 201 to 204 shown in fig. 2.
Illustratively, the computer program 302 may be partitioned into one or more modules/units, which are stored in the memory 301 and executed by the processor 300 to implement the present invention. One or more modules/units may be a series of computer program instruction segments capable of performing certain functions, the instruction segments being used to describe the execution of the computer program 302 in the electronic device 30. For example, the computer program 302 may be divided into the modules/units 201 to 204 shown in fig. 2.
The electronic device 30 may be a desktop computer, a notebook, a palm top computer, a cloud server, or other computing devices. The electronic device 30 may include, but is not limited to, a processor 300, a memory 301. Those skilled in the art will appreciate that fig. 3 is merely an example of the electronic device 30, and does not constitute a limitation of the electronic device 30, and may include more or fewer components than shown, or combine certain components, or different components, e.g., the electronic device may also include input-output devices, network access devices, buses, etc.
The Processor 300 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 301 may be an internal storage unit of the electronic device 30, such as a hard disk or a memory of the electronic device 30. The memory 301 may also be an external storage device of the electronic device 30, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the electronic device 30. Further, the memory 301 may also include both an internal storage unit and an external storage device of the electronic device 30. The memory 301 is used to store computer programs and other programs and data required by the electronic device. The memory 301 may also be used to temporarily store data that has been output or is to be output.
It should be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional units and modules is only used for illustration, and in practical applications, the above function distribution may be performed by different functional units and modules as needed, that is, the internal structure of the device is divided into different functional units or modules, so as to perform all or part of the above described functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only used for distinguishing one functional unit from another, and are not used for limiting the protection scope of the present application. For the specific working processes of the units and modules in the system, reference may be made to the corresponding processes in the foregoing method embodiments, which are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/electronic device and method may be implemented in other ways. For example, the above-described apparatus/electronic device embodiments are merely illustrative, and for example, a module or a unit may be divided into only one logic function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method according to the above embodiments may be realized by a computer program, which may be stored in a computer readable storage medium and used by a processor to realize the steps of the grading method embodiments for preheating scrap steel. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.

Claims (10)

1. A grading method for scrap steel preheating is characterized by comprising the following steps:
dividing the waste steel raw material to be processed into M grades based on predetermined waste steel grading standards;
determining the addition amount of each grade of waste steel raw material according to a preset objective function based on the preset constraint condition of each grade of waste steel raw material; the preset constraint condition is constructed according to the attribute parameters of the waste steel raw materials of all levels, and the preset objective function is determined according to the specific surface area coefficient of the waste steel raw materials of all levels;
determining N distribution modes of the waste steel raw materials of each grade in the waste steel preheating device in a permutation and combination mode according to the adding amount of the waste steel raw materials of each grade, wherein N =
Figure 570427DEST_PATH_IMAGE001
；
And calculating the preheating temperature of the waste steel raw materials of each grade under various distribution formulas, and determining the optimal distribution mode according to the preheating temperature of the waste steel raw materials of each grade under various distribution formulas.
2. The grading method for scrap preheating according to claim 1, wherein the property parameters of each grade of scrap material include an amount of each grade of scrap material added, a bulk density of each grade of scrap material, a cost of each grade of scrap material, and an inventory amount of each grade of scrap material.
3. A grading method according to claim 2, characterized in that said preset constraints comprise: a first constraint, a second constraint, a third constraint and a fourth constraint;
the first constraint condition is as follows:
Figure 507421DEST_PATH_IMAGE002
；
wherein the content of the first and second substances,x i is as followsiThe addition amount of the raw material of the scrap steel of each grade,p i is as followsiThe bulk density of the individual grade scrap material,V max is the maximum capacity of the scrap preheating apparatus,V min the minimum allowable capacity under the nominal capacity of the scrap steel preheating device;
the second constraint condition is as follows:
Figure 637051DEST_PATH_IMAGE003
；
wherein the content of the first and second substances,C i is as followsiThe unit price of each grade of scrap steel raw material,C min is a preset total cost lower limit threshold value,C max a preset total cost upper limit threshold value is set;
the third constraint condition is as follows:
Figure 248161DEST_PATH_IMAGE004
；
wherein the content of the first and second substances,ω i is as followsiThe ratio of the stock of the individual-grade steel scrap raw materials to the number of the preset steel-making furnace times;
the fourth constraint condition is:
Figure 805044DEST_PATH_IMAGE005
；
wherein the content of the first and second substances,wfor the maximum containment mass of the scrap preheating device,y 1 in order to lay the bottom material in a certain quantity,y 1min the minimum value of the bottom material laying amount required by the scrap steel preheating device.
4. A grading method according to claim 1, characterized in that said preset objective function is:
Figure 72077DEST_PATH_IMAGE006
wherein the content of the first and second substances,x i is as followsiThe addition amount of the raw material of the scrap steel of each grade,a i is as followsiSpecific surface area coefficient of individual grade scrap material.
5. The grading method for scrap preheating according to claim 1, wherein the preheating temperature of each grade of scrap feedstock under each distribution formula is calculated by the formula:
Figure 943081DEST_PATH_IMAGE007
wherein the content of the first and second substances,T ij is as followsiThe individual grade of scrap steel raw material isjThe preheating temperature under the formula of the seed cloth,s i is as followsiThe specific surface area of the individual grades of scrap steel feedstock,μin order to obtain a convective heat transfer coefficient,p i is as followsiThe bulk density of the individual grade scrap material,cthe specific heat capacity is the specific heat capacity,tin order to achieve the pre-heating time of the preset temperature,k 1ij is a firstiIn the first step of individual grades of scrapjThe mass coefficient under the formula of the seed cloth,k 2i is as followsiThe shape comprehensive coefficient of the individual grade of the scrap steel raw material,T gij is a firstiIn the first step of individual grades of scrapjThe temperature of the flue gas under the formula of the seed cloth,T s is the initial temperature of the scrap.
6. The grading method for scrap preheating according to any of claims 1-5, wherein the determining of the optimal distribution according to the preheating temperature of each grade of scrap feedstock under each distribution formula comprises:
for each distribution mode, calculating the difference value of the highest temperature and the lowest temperature in the preheating temperatures of all grades of scrap steel raw materials in the distribution mode as the temperature difference value in the distribution mode; selecting a distribution formula corresponding to the minimum temperature difference value as an optimal distribution formula; alternatively, the first and second liquid crystal display panels may be,
for each distribution mode, calculating the average temperature value of the preheating temperatures of all grades of scrap steel raw materials in the distribution mode; selecting a distribution formula corresponding to the highest average temperature value as an optimal distribution formula; alternatively, the first and second electrodes may be,
for each cloth distribution mode, acquiring the highest temperature value of the preheating temperatures of all grades of scrap steel raw materials under the cloth distribution mode; selecting a distribution formula corresponding to the maximum temperature value lower than a preset threshold value as an optimal distribution formula; wherein the preset threshold is determined according to the solidus line of the scrap steel raw material.
7. The grading method for scrap preheating according to any of claims 1-5, wherein the determining the addition of each grade of scrap stock according to a preset objective function based on preset constraints for each grade of scrap stock comprises:
and solving the preset objective function by using a planning algorithm based on the preset constraint conditions of the waste steel raw materials of all levels, and taking the solved result as the adding amount of the waste steel raw materials of all levels.
8. A grading device for scrap steel preheating is characterized by comprising:
the dividing module is used for dividing the waste steel raw materials to be processed into M grades based on predetermined waste steel grading standards;
the first calculation module is used for determining the adding amount of each grade of waste steel raw material according to a preset target function based on the preset constraint condition of each grade of waste steel raw material; the preset constraint condition is constructed according to the attribute parameters of the waste steel raw materials of all levels, and the preset objective function is determined according to the specific surface area of the waste steel raw materials of all levels;
a second calculation module for adopting the arrangement group according to the adding amount of the scrap steel raw materials of each gradeDetermining N distribution modes of the waste steel raw materials of all levels in the waste steel preheating device in a combined mode, wherein N =
Figure 346381DEST_PATH_IMAGE008
；
And the selection module is used for calculating the preheating temperature of each grade of waste steel raw material under various distribution formulas and determining the optimal distribution mode according to the preheating temperature of each grade of waste steel raw material under various distribution formulas.
9. An electronic device comprising a memory and a processor, the memory having stored therein a computer program operable on the processor, wherein the processor, when executing the computer program, implements the steps of the grading method for scrap preheating according to any of claims 1 to 7 above.
10. A computer-readable storage medium, storing a computer program, characterized in that the computer program, when being executed by a processor, carries out the steps of the grading method of scrap preheating according to any of the claims 1 to 7 above.
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