CN116855650A - Automatic control system and method for steelmaking alloy feeding amount - Google Patents
Automatic control system and method for steelmaking alloy feeding amount Download PDFInfo
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- 239000000956 alloy Substances 0.000 title claims abstract description 146
- 229910045601 alloy Inorganic materials 0.000 title claims abstract description 146
- 238000009628 steelmaking Methods 0.000 title claims abstract description 41
- 238000000034 method Methods 0.000 title claims description 108
- 229910000831 Steel Inorganic materials 0.000 claims abstract description 164
- 239000010959 steel Substances 0.000 claims abstract description 164
- 238000005457 optimization Methods 0.000 claims abstract description 62
- 238000004364 calculation method Methods 0.000 claims abstract description 58
- 238000012360 testing method Methods 0.000 claims abstract description 25
- 239000013072 incoming material Substances 0.000 claims description 51
- 238000012937 correction Methods 0.000 claims description 30
- 238000003723 Smelting Methods 0.000 claims description 27
- 239000000203 mixture Substances 0.000 claims description 20
- 238000001514 detection method Methods 0.000 claims description 18
- 238000007689 inspection Methods 0.000 claims description 17
- 238000007781 pre-processing Methods 0.000 claims description 10
- 238000004458 analytical method Methods 0.000 claims description 9
- 238000005303 weighing Methods 0.000 claims description 8
- 238000013500 data storage Methods 0.000 claims description 7
- 229910001264 Th alloy Inorganic materials 0.000 claims description 6
- 239000000463 material Substances 0.000 claims description 6
- 238000003860 storage Methods 0.000 claims description 5
- 238000004140 cleaning Methods 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 2
- 230000010354 integration Effects 0.000 claims description 2
- 239000007788 liquid Substances 0.000 claims 1
- 238000004519 manufacturing process Methods 0.000 abstract description 2
- 239000002699 waste material Substances 0.000 abstract description 2
- XKRFYHLGVUSROY-UHFFFAOYSA-N Argon Chemical compound [Ar] XKRFYHLGVUSROY-UHFFFAOYSA-N 0.000 description 12
- 229910052786 argon Inorganic materials 0.000 description 6
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
- 238000013459 approach Methods 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 238000003556 assay Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 229910052742 iron Inorganic materials 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
Classifications
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B5/00—Making pig-iron in the blast furnace
- C21B5/006—Automatically controlling the process
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B5/00—Making pig-iron in the blast furnace
- C21B5/008—Composition or distribution of the charge
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B7/00—Blast furnaces
- C21B7/18—Bell-and-hopper arrangements
- C21B7/20—Bell-and-hopper arrangements with appliances for distributing the burden
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B7/00—Blast furnaces
- C21B7/24—Test rods or other checking devices
Abstract
The invention discloses an automatic control system for steel-making alloy feeding amount, which is characterized in that data acquisition is carried out on production data, secondary data and test data, an element optimization mode is judged by utilizing the acquired data, element optimization types are calculated, pretreatment is carried out on the data, standard data is obtained, compensation calculation is carried out on element set values, the optimization calculation of the feeding amount of scrap steel and alloy is carried out, an optimization calculation result is obtained, and the optimization calculation result is executed, displayed and stored, so that the automatic control of the scrap steel and alloy in the steel-making process is realized, the waste of steelmaking cost due to artificial judgment is reduced, the fluctuation of molten steel components after steelmaking is reduced, and the molten steel hit rate and the automatic control level in the steel-making process are improved.
Description
Technical Field
The invention relates to the technical field of steelmaking control, in particular to an automatic control system and method for steelmaking alloy feeding quantity.
Background
As the country increasingly strictly limits the capacity of molten iron of a steel blast furnace, the steel enterprises in recent ten years obviously increase the use amount of scrap steel in the steel smelting process, so that the carbon emission can be reduced, and the production cost of steel can be obviously reduced; meanwhile, the competition in the steel industry is aggravated, so that the steel enterprises pay more and more attention to the reduction of the process cost, and the alloy cost control of the steelmaking process is particularly critical. Therefore, maintaining high-precision component hit in the steelmaking process while further reducing the alloy cost in the steelmaking process under the condition of high scrap addition becomes a key issue for steel enterprises.
At present, scrap steel and alloy are added in the steelmaking field mainly by means of empirical estimation and manual adjustment by operators based on component test results, and the addition amount of the alloy based on experience is accompanied by obvious systematic deviation, and meanwhile, fluctuation of components and increase of alloy cost are caused. Currently, more research in the steel industry is directed to methods and apparatus for adding scrap steel and alloys.
Therefore, there is a need to further develop an automatic control model of scrap steel and alloy during the steel smelting process, thereby improving the hit rate of the components and further reducing the steelmaking alloy.
Disclosure of Invention
The invention aims to provide an automatic control system for steelmaking alloy feeding quantity, which realizes high precision of component hit under the condition of high scrap steel feeding and low cost control of steelmaking alloy, wherein a control model respectively collects feeding data of scrap steel and alloy, molten steel weighing data, test component data, set value data of steel grade components, fixed compensation data of steel grade components, component set value data of scrap steel and alloy and price data of scrap steel and alloy through a data acquisition module; carrying out incoming material component correction, element type calculation, data preprocessing, self-learning compensation, linkage compensation, comprehensive compensation and optimization calculation on the collected data through an optimization model module, so as to obtain optimized result data of scrap steel and alloy; performing operation execution on the optimized result data through a issuing execution module; the optimization result data is presented to operators and technicians in real time through a terminal display module; and (3) carrying out database storage, analysis and model self-learning on the optimized result data through a data storage module.
The technical problems solved by the invention are as follows: an automatic optimizing control model for scrap steel and alloy in the steelmaking process.
The aim of the invention can be achieved by the following technical scheme:
an automatic control system for the charging amount of steel-making alloy comprises the following steps:
step one: collecting data of a previous steelmaking process and the current process according to the current smelting process and smelting heat;
step two: calculating the data collected in the step one through a mode judging program to obtain incoming material component correction data of the current smelting heat;
step three: according to the incoming material component correction data in the second step, calculating the component elements of the current heat by an element type calculation program to obtain the control types of the elements;
step four: preprocessing the collected data through a data preprocessing program according to the mode and the control type of the element to obtain preprocessed data;
step five: according to the preprocessed data, the control type of the elements, the self-learning compensation program, the linkage compensation program and the comprehensive compensation program, calculating the comprehensive compensation value of each element, and then calculating the compensated data;
step six: according to the preprocessed data, the control type of the element and the compensated data, performing optimization calculation on the alloy addition of the current heat through an optimization calculation program to obtain optimization result data of the alloy addition;
step seven: and according to the optimized result data added by the alloy, issuing, executing, displaying and storing through a secondary system.
As a further scheme of the invention: in the first step, the collected data comprise the addition data of scrap steel and alloy, the weighing data of molten steel, the detection and test component data, the set value data of steel grade components, the fixed compensation data of steel grade components, the component set value data of scrap steel and alloy and the price data of scrap steel and alloy.
As a further scheme of the invention: in the second step, the mode judging program is used for calculating the incoming material component correction data adopted by the current heat, and the modes comprise a checking mode and a theoretical calculation mode;
the inspection mode is that in most scenes, the incoming material inspection and test components in the existing process have higher reliability, and the inspection and test component data are directly adopted to perform the optimization calculation of alloy addition;
the theoretical calculation mode is that the reliability of the detection components of the incoming material in the current working procedure is low in few scenes, and the detection components cannot be directly used for the optimization calculation of alloy addition.
As a further scheme of the invention: the calculation of the incoming material component correction data is performed in a checking mode or a theoretical calculation mode;
in the inspection mode, the incoming material component correction data is incoming material inspection and test component data of the current process;
in the theoretical calculation mode, the incoming material component correction data is an incoming material calculation component of the current process, and is calculated according to the weight of incoming material molten steel of the previous process, the incoming material detection and test component of the previous process, the weight of alloy and scrap steel added in the previous process and the set component of alloy and scrap steel added in the previous process.
As a further scheme of the invention: in the third step, the control types of the elements comprise a non-calculation element, an upper limit value element, a target value element and a non-early warning element.
As a further scheme of the invention: in the fourth step, the data preprocessing is to perform feature extraction, data integration and data cleaning on the collected data to obtain standard data.
As a further scheme of the invention: in the fifth step, the comprehensive compensation value comprises a fixed compensation value, a linkage compensation value and a self-learning compensation value;
the fixed compensation value is the fixed compensation data of the steel grade component of the acquired data;
the linkage compensation value is calculated by a linkage compensation program according to the control type of the preprocessed data and elements;
the self-learning compensation value is calculated by a self-learning compensation program according to the control type of the preprocessed data and the elements.
As a further scheme of the invention: the compensated data compensates different set value types of each element according to the comprehensive compensation value, and the calculation formula is as follows:
wherein i is a set value type comprising a maximum value, a minimum value and a target value; j is the name of the element;an initial value of a set value type i of the element j; />A comprehensive compensation value of a set value type i of the element j; />Is the compensated value of the set value type i of element j.
As a further scheme of the invention: in the sixth step, the boundary conditions of the optimization calculation program include the following 4 kinds;
further, the target value of the element j corresponds to the boundary condition:
X 0 A 0j +X 1 A 1j +…+X m A mj ＝(X 0 +X 1 +…+X m )Y j ；
further, the minimum value of the element j corresponds to the boundary condition that:
X 0 A 0j +X 1 A 1j +…+X m A mj ；
further, the maximum value of the element j corresponds to the boundary condition of min
X 0 A 0j +X 1 A 1j +…+X m A mj ；
Further, the addition amount of the scrap steel and the alloy corresponds to the boundary condition of max
X i ；
Further, the total addition amount of scrap steel and alloy corresponds to the boundary conditions:
X 1 +…+X m ≤w totol ；
wherein j is the name of the element; x is X 0 The weight of the molten steel which is fed in the previous working procedure; a is that 0j The content of the material element j is detected and tested in the previous working procedure; m is the total number of the types of alloy or scrap steel added in the previous working procedure; i is the number of the alloy and the scrap steel added in the previous working procedure; x is X i The weight of the i-th alloy or scrap steel is added; a is that i,j The target value content of the element j in the ith alloy or scrap steel; y is Y min,j Is the minimum value of steel class element j; y is Y max,j Is the maximum value of steel class element j; w (w) totol To allow the upper limit of the weight of scrap steel and alloys added to the steel.
As a further scheme of the invention: an automatic control system for the feed amount of a steelmaking alloy, comprising:
the data acquisition module is used for acquiring data of a previous steelmaking process and the current process according to the current smelting process and smelting heat and sending the acquired data to the optimization model module in an electrical mode;
the optimization model module is used for calculating the collected data through a mode judging program to obtain incoming material component correction data of the current smelting heat;
according to the incoming material component correction data, an optimization model module calculates component elements of the current heat through an element type calculation program to obtain the control type of the elements;
according to the mode and the control type of the element, the optimization model module performs data preprocessing on the collected data through a data preprocessing program to obtain preprocessed data;
according to the preprocessed data, the control type of the elements, the self-learning compensation program, the linkage compensation program and the comprehensive compensation program, calculating the comprehensive compensation value of each element, and then calculating the compensated data;
according to the preprocessed data, the control type of the element and the compensated data, performing optimization calculation on the alloy addition of the current heat through an optimization calculation program to obtain optimization result data of the alloy addition;
the issuing execution module is used for issuing and executing the optimized result data added by the alloy through the secondary system;
the terminal display module is used for displaying the optimized result data added by the alloy to operators and technicians in real time;
and the data storage module is used for carrying out database storage and analysis on the optimization result data added by the alloy.
The invention has the beneficial effects that: the invention respectively collects the adding data of scrap steel and alloy, the weighing data of molten steel, the detecting and testing component data, the set value data of steel grade components, the fixed compensation data of steel grade components, the component set value data of scrap steel and alloy and the price data of scrap steel and alloy through a data acquisition module; carrying out incoming material component correction, element type calculation, data preprocessing, self-learning compensation, linkage compensation, comprehensive compensation and optimization calculation on the collected data through an optimization model module, so as to obtain optimized result data of scrap steel and alloy; performing operation execution on the optimized result data through a issuing execution module; the optimization result data is presented to operators and technicians in real time through a terminal display module; the optimized result data is stored and analyzed in a database through the data storage module, so that automatic control of scrap steel and alloy in the steelmaking process is realized, waste of steelmaking cost due to manual judgment is reduced, fluctuation of molten steel components after steelmaking is reduced, and molten steel hit rate and automatic control level in the steelmaking process are improved.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a process flow diagram of the present invention;
fig. 2 is a flow chart of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to FIG. 1, the invention relates to an automatic control method for steelmaking alloy charging amount, comprising the following steps:
step one: collecting data of a previous steelmaking process and the current process according to the current smelting process and smelting heat;
the data collected in the first step comprises adding data of scrap steel and alloy, weighing data of molten steel, detecting and testing component data, set value data of steel grade components, fixed compensation data of the steel grade components, component set value data of the scrap steel and alloy and price data of the scrap steel and alloy;
further, the adding data of the scrap steel and the alloy comprises, but is not limited to, the prior smelting heat, the process, the grade of steel, the type of adding the scrap steel, the adding weight of various scrap steel, the type of adding the alloy and the adding weight of various alloy;
further, the weighing data includes, but is not limited to, smelting heat, molten steel weight, process;
further, the detection and assay component data comprise smelting heat, working procedures, detection batch and detection values of the content of each element;
further, the steel grade composition set value data comprises, but is not limited to, steel grade marks, working procedures and set values of various elements, wherein the set values of the elements comprise minimum values, target values and maximum values;
further, the fixed compensation data of the steel grade components are compensation values of steel grade containing elements, and are used for compensating and correcting the set values of the elements;
further, the method for obtaining the composition set value data of the scrap steel and the alloy comprises the following two modes, but is not limited to: 1. and secondly, calculating the composition setting data according to the checking composition data of certain period of the type of scrap steel or alloy. The certain period is generally one of the batch, week, half month and month; the calculation method includes, but is not limited to, average, median, weighted average;
further, the method of obtaining price data for scrap and alloys includes, but is not limited to, the following:
1. setting a fixed value according to experience;
2. calculating the composition setting data according to the purchase data of the scrap steel or alloy of the type in a certain period;
wherein the certain period comprises a period of time generally the present batch, week, half month or month; the calculation method includes, but is not limited to, average, median, weighted average;
step two: calculating the data collected in the step one through a mode judging program to obtain incoming material component correction data of the current smelting heat;
wherein, the mode decision program is used for calculating the incoming material composition correction data adopted by the current heat, and the modes comprise but are not limited to the following modes: 1. checking a second theoretical calculation mode;
furthermore, the inspection mode is that in most scenes, the incoming material inspection and test components in the existing process have higher reliability, and the inspection and test component data are directly adopted to perform the optimization calculation of alloy addition;
most of these scenarios include, but are not limited to: argon station procedure, LF procedure after RH, RH procedure after LF, second addition of LF procedure, second addition after RH, LF procedure after argon station adding a small amount of alloy and RH procedure;
in the inspection mode, the incoming material component correction data is incoming material inspection and test component data of the current process;
furthermore, the theoretical calculation mode is that in a few scenes, the reliability of the incoming material detection and analysis components of the existing working procedure is low, and the method cannot be directly used for optimizing and calculating the alloy addition;
among them, a few include, but are not limited to: an LF procedure or an RH procedure after more scrap steel and alloy are added in an argon station;
in the theoretical calculation mode, the incoming material component correction data is the incoming material calculation component Yj of the current process j The method is calculated according to the weight of molten steel fed in the previous step, the test components of the molten steel fed in the previous step, the weight of alloy and scrap steel added in the previous step and the set components of the alloy and the scrap steel added in the previous step, and the calculation formula is as follows:
wherein j is the name of the element; x is X 0 The weight of the molten steel which is fed in the previous working procedure; y is Y 0j The content of the material element j is detected and tested in the previous working procedure; m is the total number of the types of alloy or scrap steel added in the previous working procedure; i is the number of the alloy and the scrap steel added in the previous working procedure; x is X i The weight of the i-th alloy or scrap steel is added; y is Y i,j The content of the element j in the ith alloy or scrap steel;
step three: according to the incoming material component correction data in the second step, calculating the component elements of the current heat by an element type calculation program to obtain the control types of the elements;
the control types of the elements comprise a non-calculation element, an upper limit value element, a target value element and a non-early warning element;
the non-calculation element does not need to perform optimization calculation;
the composition of the upper limit value element is required to be between a set minimum value and a set maximum value;
the composition of the target value element needs to be equal to the set target value;
the non-early warning element is an element which exceeds or approaches the maximum value of the element and does not need early warning;
step four: according to the mode and the control type of the element, carrying out data preprocessing on the collected data through a data preprocessing program to obtain preprocessed data;
the data preprocessing program is used for extracting characteristics, integrating data and cleaning the data to obtain standard data;
step five: according to the preprocessed data, the control type of the elements, the self-learning compensation program, the linkage compensation program and the comprehensive compensation program, calculating the comprehensive compensation value of each element, and then calculating the compensated data;
the comprehensive compensation value comprises a fixed compensation value, a linkage compensation value and a self-learning compensation value;
further, the fixed compensation value is fixed compensation data of steel grade components of the acquired data;
further, the linkage compensation value is calculated through a linkage compensation program according to the preprocessed data and the control type of the element;
further, the self-learning compensation value is calculated by a self-learning compensation program according to the preprocessed data and the control type of the element;
further, the comprehensive compensation program calculates a final compensation value of each element according to the fixed compensation value, the linkage compensation value and the self-learning compensation value of each element, so that compensated data are obtained;
the compensated data compensates different set value types of each element according to the comprehensive compensation value, and the calculation formula is as follows:
wherein i is a set value type comprising a maximum value, a minimum value and a target value; j is the name of the element;an initial value of a set value type i of the element j; />A comprehensive compensation value of a set value type i of the element j; />Set value class for element jCompensated value of type i.
Step six: according to the preprocessed data, the control type of the element and the compensated data, performing optimization calculation on the alloy addition of the current heat through an optimization calculation program to obtain optimization result data of the alloy addition;
the pretreated data comprise alloy price, alloy and scrap steel components, incoming material component correction data, incoming material molten steel weight and steel grade component setting data;
wherein, the boundary conditions of the optimization calculation program comprise the following 4 types;
further, the target value of the element j corresponds to the boundary condition:
X 0 A 0j +X 1 A 1j +…+X m A mj ＝(X 0 +X 1 +…+X m )Y j ；
further, the minimum value of the element j corresponds to the boundary condition that:
X 0 A 0j +X 1 A 1j +…+X m A mj ；
further, the maximum value of the element j corresponds to the boundary condition of min
X 0 A 0j +X 1 A 1j +…+X m A mj ；
Further, the addition amount of the scrap steel and the alloy corresponds to the boundary condition of max
X i ；
Further, the total addition amount of scrap steel and alloy corresponds to the boundary conditions:
X 1 +…+X m ≤w total ；
wherein j is the name of the element; x is X 0 The weight of the molten steel which is fed in the previous working procedure; a is that 0j The content of the material element j is detected and tested in the previous working procedure; m is the total number of the types of alloy or scrap steel added in the previous working procedure; i is the number of the alloy and the scrap steel added in the previous working procedure; x is X i The weight of the i-th alloy or scrap steel is added; a is that i,j The target value content of the element j in the ith alloy or scrap steel; y is Y min,j Is a steel grade elementA minimum value of j; y is Y max,j Is the maximum value of steel class element j; w (w) totol An upper limit for the weight of scrap steel and alloys that are allowed to be added to the molten steel;
step seven: and according to the optimized result data added by the alloy, issuing, executing, displaying and storing through a secondary system.
Example 2
Referring to FIG. 2, the invention relates to an automatic control system for steelmaking alloy charging quantity, which comprises a data acquisition module, an optimization model module, a issuing execution module, a terminal display module and a data storage module;
the data acquisition module is used for acquiring data of a previous steelmaking process and the current process according to the current smelting process and smelting heat and sending the acquired data to the optimization model module in an electrical mode;
the optimization model module is used for calculating the collected data through a mode judging program to obtain incoming material component correction data of the current smelting heat;
according to the incoming material component correction data, an optimization model module calculates component elements of the current heat through an element type calculation program to obtain the control type of the elements;
according to the mode and the control type of the element, the optimization model module performs data preprocessing on the collected data through a data preprocessing program to obtain preprocessed data;
according to the preprocessed data, the control type of the elements, the self-learning compensation program, the linkage compensation program and the comprehensive compensation program, calculating the comprehensive compensation value of each element, and then calculating the compensated data;
according to the preprocessed data, the control type of the element and the compensated data, performing optimization calculation on the alloy addition of the current heat through an optimization calculation program to obtain optimization result data of the alloy addition;
the issuing execution module is used for issuing and executing the optimized result data added by the alloy through the secondary system;
the terminal display module is used for displaying the optimized result data added by the alloy to operators and technicians in real time;
and the data storage module is used for carrying out database storage and analysis on the optimization result data added by the alloy.
The data acquired by the data acquisition module comprises adding data of scrap steel and alloy, weighing data of molten steel, checking and testing component data, set value data of steel grade components, fixed compensation data of steel grade components, component set value data of scrap steel and alloy and price data of scrap steel and alloy;
the adding data of the scrap steel and the alloy comprises, but is not limited to, a previous smelting heat, a current smelting heat, a process, a steel grade number, a type of adding the scrap steel, the adding weight of various scrap steel, the type of adding the alloy and the adding weight of various alloy;
wherein, the weighing data comprises but is not limited to smelting heat, molten steel weight and working procedure;
wherein the detection and test composition data comprise smelting heat, working procedures, detection batch and detection values of the content of each element;
wherein, the steel grade composition set value data comprises but is not limited to steel grade marks, working procedures and set values of various elements. Wherein the set values of the elements comprise a minimum value, a target value and a maximum value;
the fixed compensation data of the steel grade components are compensation values of steel grade containing elements, and are used for compensating and correcting set values of the elements;
the method for acquiring the composition set value data of the scrap steel and the alloy comprises the following two modes: 1. and secondly, calculating the composition setting data according to the checking composition data of certain period of the type of scrap steel or alloy. The certain period is generally one of the batch, week, half month and month; the calculation method includes, but is not limited to, average, median, weighted average;
wherein, the method for acquiring price data of the scrap steel and the alloy comprises the following modes: 1. and setting a fixed value according to experience, and calculating the composition setting data according to purchase data of certain period of the type of scrap steel or alloy. Wherein the certain period comprises a period of time generally the present batch, week, half month or month; the calculation methods include, but are not limited to, average, median, weighted average.
The pattern determination program is used to calculate incoming material composition correction data for the current heat, wherein the pattern includes, but is not limited to, the following: 1. checking a second theoretical calculation mode;
the detection mode is that in most scenes, the incoming material detection and analysis components in the existing process have higher reliability, and the detection and analysis component data can be directly adopted to perform optimization calculation of alloy addition; most of the scenarios include, but are not limited to: argon station procedure, LF procedure after RH, RH procedure after LF, second addition of LF procedure, second addition after RH, LF procedure after argon station adding a small amount of alloy and RH procedure. In the inspection mode, the incoming material component correction data are incoming material inspection and test component data of the current process;
the theoretical calculation mode is that the reliability of the incoming material detection and analysis components of the existing working procedure is low in few scenes, and the method cannot be directly used for optimizing and calculating the alloy addition; the minority scenario includes, but is not limited to: and an LF procedure or an RH procedure after more scrap steel and alloy are added in an argon station. In the theoretical calculation mode, the incoming material component correction data is the incoming material calculation component Y of the current process j The method is calculated according to the weight of molten steel fed in the previous step, the test components of the molten steel fed in the previous step, the weight of alloy and scrap steel added in the previous step and the set components of the alloy and the scrap steel added in the previous step, and the calculation formula is as follows:
wherein j is the name of the element; x is X 0 The weight of the molten steel which is fed in the previous working procedure; y is Y 0j The content of the material element j is detected and tested in the previous working procedure; m is the category of alloy or scrap added in the previous stepA total number; i is the number of the alloy and the scrap steel added in the previous working procedure; x is X i The weight of the i-th alloy or scrap steel is added; y is Y i,j The content of the element j in the ith alloy or scrap steel.
The control types of the elements comprise a non-calculation element, an upper limit value element, a target value element and a non-early warning element;
in the optimization model, the non-calculation element does not need to perform optimization calculation;
in the optimization model, the components of the upper limit value element are required to be between a set minimum value and a set maximum value;
wherein, in the optimization model, the components of the target value elements need to be equal to the set target values;
in the optimization model, the non-early-warning element is an element which exceeds or approaches to the maximum value of the element and does not need early warning;
the comprehensive compensation value comprises a fixed compensation value, a linkage compensation value and a self-learning compensation value;
wherein the fixed compensation value is the fixed compensation data of the steel grade component of the acquired data;
the linkage compensation value is calculated by a linkage compensation program according to the preprocessed data and the control type of the element;
the self-learning compensation value is calculated by a self-learning compensation program according to the preprocessed data and the control type of the element;
the comprehensive compensation program calculates a final compensation value of each element according to the fixed compensation value, the linkage compensation value and the self-learning compensation value of each element, so that compensated data are obtained;
the compensated data compensates different set value types of each element according to the comprehensive compensation value, and the calculation formula is as follows:
wherein i is a set value type comprising a maximum value,Minimum and target values; j is the name of the element;an initial value of a set value type i of the element j; />A comprehensive compensation value of a set value type i of the element j; />A compensated value of the set value type i of the element j;
the preprocessed data includes: alloy price, alloy and scrap steel components, incoming material component correction data, incoming material molten steel weight and steel grade component setting data;
the boundary conditions of the optimization calculation program comprise the following 4 types;
wherein, the target value of the element j corresponds to the boundary condition:
X 0 A 0j +X 1 A 1j +…+X m A mj
the minimum value of the element j corresponds to the boundary condition:
X 0 A 0j +X 1 A 1j +…+X m A mj
wherein, the maximum value of the element j corresponds to the boundary condition: min
X 0 A 0j +X 1 A 1j +…+X m A mj
Wherein, the addition of scrap steel and alloy corresponds to boundary conditions: max
X i
wherein, the total addition amount of scrap steel and alloy corresponds to boundary conditions:
X 1 +…+X m ≤w totol
wherein j is the name of the element; x is X 0 The weight of the molten steel which is fed in the previous working procedure; a is that 0j The content of the material element j is detected and tested in the previous working procedure; m is the total number of the types of alloy or scrap steel added in the previous working procedure; i is added for the previous stepNumbering of alloys and scrap steel; x is X i The weight of the i-th alloy or scrap steel is added; a is that i,j The target value content of the element j in the ith alloy or scrap steel; y is Y min,j Is the minimum value of steel class element j; y is Y max,j Is the maximum value of steel class element j; w (w) totol To allow the upper limit of the weight of scrap steel and alloys added to the steel.
The issuing execution module is used for issuing and executing the optimized result data added by the alloy through the secondary system;
the terminal display module is used for displaying the optimized result data added by the alloy to operators and technicians in real time;
and the data storage module is used for carrying out database storage and analysis on the optimization result data added by the alloy.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (10)
1. An automatic control method for the charging amount of steelmaking alloy is characterized by comprising the following steps:
step one: collecting data of a previous steelmaking process and the current process according to the current smelting process and smelting heat;
step two: calculating the data collected in the step one through a mode judging program to obtain incoming material component correction data of the current smelting heat;
step three: according to the incoming material component correction data in the second step, calculating the component elements of the current heat by an element type calculation program to obtain the control types of the elements;
step four: according to the mode and the control type of the element, carrying out data preprocessing on the collected data through a data preprocessing program to obtain preprocessed data;
step five: according to the preprocessed data, the control type of the elements, the self-learning compensation program, the linkage compensation program and the comprehensive compensation program, calculating the comprehensive compensation value of each element, and then calculating the compensated data;
step six: according to the preprocessed data, the control type of the element and the compensated data, performing optimization calculation on the alloy addition of the current heat through an optimization calculation program to obtain optimization result data of the alloy addition;
step seven: and according to the optimized result data added by the alloy, issuing, executing, displaying and storing through a secondary system.
2. The automatic control method of steel-making alloy feed amount according to claim 1, wherein in the first step, the collected data includes steel scrap and alloy feed data, steel liquid weighing data, test composition data, steel grade composition set value data, steel grade composition fixed compensation data, steel grade composition set value data, steel scrap and alloy price data.
3. The automatic control method of steelmaking alloy charge amount according to claim 1, wherein in the second step, the mode determination program is used for calculating incoming material component correction data adopted by the current heat, and the modes include a test mode and a theoretical calculation mode;
the inspection mode is that in most scenes, the incoming material inspection and test components in the existing process have higher reliability, and the inspection and test component data are directly adopted to perform the optimization calculation of alloy addition;
the theoretical calculation mode is that the reliability of the detection components of the incoming material in the current working procedure is low in few scenes, and the detection components cannot be directly used for the optimization calculation of alloy addition.
4. The automatic control method of steelmaking alloy charge according to claim 3, wherein the calculation of the charge composition correction data is performed in a test mode or a theoretical calculation mode;
in the inspection mode, the incoming material component correction data is incoming material inspection and test component data of the current process;
in the theoretical calculation mode, the incoming material component correction data is an incoming material calculation component of the current process, and is calculated according to the weight of incoming material molten steel of the previous process, the incoming material detection and test component of the previous process, the weight of alloy and scrap steel added in the previous process and the set component of alloy and scrap steel added in the previous process.
5. The automatic control method of steelmaking alloy feed amount according to claim 1, wherein in step three, the control types of the elements include a non-calculation element, an upper limit value element, a target value element, and a non-warning element.
6. The method for automatically controlling the steel-making alloy feeding amount according to claim 1, wherein in the fourth step, the data preprocessing is to perform feature extraction, data integration and data cleaning on the collected data to obtain standard data.
7. The automatic control method of steelmaking alloy feed amount according to claim 1, wherein in step five, the integrated compensation value comprises a fixed compensation value, a linkage compensation value and a self-learning compensation value;
the fixed compensation value is the fixed compensation data of the steel grade component of the acquired data;
the linkage compensation value is calculated by a linkage compensation program according to the control type of the preprocessed data and elements;
the self-learning compensation value is calculated by a self-learning compensation program according to the control type of the preprocessed data and the elements.
8. The automatic control method of steelmaking alloy feed amount according to claim 7, wherein the compensated data compensates for different set value types of each element according to the integrated compensation value, and the calculation formula is as follows:
wherein i is a set value type comprising a maximum value, a minimum value and a target value; j is the name of the element;an initial value of a set value type i of the element j; />A comprehensive compensation value of a set value type i of the element j; />Is the compensated value of the set value type i of element j.
9. The automatic control method of steelmaking alloy feed rate according to claim 8, wherein in step six, the boundary conditions of the optimization calculation program include 4 kinds of;
further, the target value of the element j corresponds to the boundary condition:
X 0 A 0j +X 1 A 1j +…+X m A mj ＝(X 0 +X 1 +...+X m )Y j ；
further, the minimum value of the element j corresponds to the boundary condition that:
X 0 A 0j +X 1 A 1j +…+X m A mj ≥(X 0 +X 1 +…+X m )Y min,j ；
further, the maximum value of the element j corresponds to the boundary condition:
X 0 A 0j +X 1 A 1j +…+X m A mj ≤(X 0 +X 1 +…+X m )Y max,j ；
further, the addition amount of the scrap steel and the alloy corresponds to the boundary conditions that:
X i ≥0；
further, the total addition amount of scrap steel and alloy corresponds to the boundary conditions:
X 1 +…+X m ≤w totol ；
wherein j is the name of the element; x is X 0 The weight of the molten steel which is fed in the previous working procedure; a is that 0j The content of the material element j is detected and tested in the previous working procedure; m is the total number of the types of alloy or scrap steel added in the previous working procedure; i is the number of the alloy and the scrap steel added in the previous working procedure; x is X i The weight of the i-th alloy or scrap steel is added; a is that i,j The target value content of the element j in the ith alloy or scrap steel; y is Y min,j Is the minimum value of steel class element j; y is Y max,j Is the maximum value of steel class element j; w (w) totol To allow the upper limit of the weight of scrap steel and alloys added to the steel.
10. An automatic control system for the feed rate of a steelmaking alloy as claimed in claim 1, comprising:
the data acquisition module is used for acquiring data of a previous steelmaking process and the current process according to the current smelting process and smelting heat and sending the acquired data to the optimization model module in an electrical mode;
the optimization model module is used for calculating the collected data through a mode judging program to obtain incoming material component correction data of the current smelting heat;
according to the incoming material component correction data, an optimization model module calculates component elements of the current heat through an element type calculation program to obtain the control type of the elements;
according to the mode and the control type of the element, the optimization model module performs data preprocessing on the collected data through a data preprocessing program to obtain preprocessed data;
according to the preprocessed data, the control type of the elements, the self-learning compensation program, the linkage compensation program and the comprehensive compensation program, calculating the comprehensive compensation value of each element, and then calculating the compensated data;
according to the preprocessed data, the control type of the element and the compensated data, performing optimization calculation on the alloy addition of the current heat through an optimization calculation program to obtain optimization result data of the alloy addition;
the issuing execution module is used for issuing and executing the optimized result data added by the alloy through the secondary system;
the terminal display module is used for displaying the optimized result data added by the alloy to operators and technicians in real time;
and the data storage module is used for carrying out database storage and analysis on the optimization result data added by the alloy.
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