CN117852317A - Digital twinning technology-based ultra-large high-temperature furnace temperature simulation method - Google Patents
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Abstract
The invention discloses a digital twin technology-based ultra-large high-temperature furnace temperature simulation method, which comprises the following steps: co-arrangement in ultra-large high temperature furnacesNThe temperature sensors start to record the indication values of the temperature sensors after the temperature of the high-temperature furnace is stable, and the indication values are recorded togetherNGroup temperature data; based onNDeviation between each group average value in the group temperature data and the set value of the high-temperature furnace is weighted and averagedNThe group of temperature data are fused into a group of data, and the uniformity, the temperature deviation and the fluctuation of the high-temperature furnace are calculated; combining physical parameters of high temperature furnaceThe digital information is used for establishing a simulation model of the high-temperature furnace based on a digital twin technology, and carrying out theoretical reasoning analysis on a simulation cloud picture of the internal temperature of the high-temperature furnace and the temperature change conditions in the length, width and height directions. Practice proves that the temperature change condition of each layer in the ultra-large high-temperature furnace can be simulated by the method, and the technical problem that the traditional temperature calibration needs to be carried out under a stable condition is solved.
Description
Technical Field
The invention relates to the technical field of metering calibration, in particular to a temperature simulation method of an ultra-large high-temperature furnace based on a digital twin technology.
Background
The high-temperature furnace is a device for heating and heat treatment in industrial and mining enterprises, scientific research institutions and laboratories, and is widely applied to various fields. For example: the high-temperature furnace can be used for researching the characteristics of the material such as thermal property, thermal expansion coefficient, thermal conductivity and the like, and the behavior and performance of the material at high temperature; in the field of metal processing, a high-temperature furnace can be used for the processes of heat treatment, annealing, smelting, casting and the like of metal so as to improve the performance and quality of the metal; in the field of semiconductor manufacturing, high temperature furnaces may be used for growth, annealing and heat treatment of semiconductor materials to improve the performance and reliability of semiconductor devices; in the field of glass manufacturing, high temperature furnaces can be used for glass melting and forming, and glass product sintering and annealing; in the field of ceramic manufacturing, high temperature furnaces can be used for sintering, heat treatment and forming of ceramic materials to improve the performance and quality of ceramic products; in the field of chemical reactions, high temperature furnaces can provide a high temperature environment for various chemical reactions, such as catalyst activation, organic synthesis, catalytic reactions, and the like.
The design scale of the ultra-large high-temperature furnace is obviously larger than that of a common high-temperature furnace, the hearth volume and the processing capacity of the ultra-large high-temperature furnace are obviously enhanced, and the energy consumption is relatively high. At present, no proper calibration standard can be referred to for the detection work of the ultra-large high-temperature furnace, and although JJF1376-2012 'calibration standard for the box-type resistance furnace' and a specific test method are issued, the method is only aimed at the traditional box-type resistance furnace, and conventional temperature sensor distribution cannot be carried out on the ultra-large high-temperature furnace, such as a lifting-type resistance furnace and the like; because the volume of the ultra-large high-temperature furnace is large, even if the temperature sensor is distributed according to the requirements of regulations, the temperature change condition inside the ultra-large high-temperature furnace cannot be known in an image.
Disclosure of Invention
Aiming at the problem that the ultra-large high-temperature furnace cannot be accurately detected, the invention provides the ultra-large high-temperature furnace temperature simulation method based on the digital twin technology, which combines the analog simulation technology on the basis of the traditional temperature detection technology, adopts an artificial intelligence mode to carry out the accurate test of the ultra-large high-temperature furnace, so that the internal temperature change condition of the ultra-large high-temperature furnace can be more vividly known, and the accuracy of the temperature measurement of the ultra-large high-temperature furnace can be improved.
In order to achieve the above object, the present invention is realized by the following technical scheme:
a digital twinning technology-based ultra-large high temperature furnace temperature simulation method, comprising:
co-arrangement in ultra-large high temperature furnacesNAt least one temperature sensor is respectively arranged at four corners of the bottom plane of the high-temperature furnace and the center point of the bottom plane;
after the temperature of the high-temperature furnace is stable, the indication values of the temperature sensors are recorded one by one every preset time period, and each temperature sensor recordsMThe data of the respective temperatures are provided for,Mnot less than 20; then together recordNTemperature data of groups, each group includingMA plurality of temperature data;
separately calculateNAverage value of each group in the group temperature data is weighted and averaged based on deviation between the average value and the set value of the high temperature furnaceNThe group temperature data are fused into a group of data;
according toNThe uniformity of the high-temperature furnace is calculated by transverse comparison among the temperature data, and the temperature deviation and fluctuation of the high-temperature furnace are calculated by using the fused data;
by detection ofNTemperature combinationThe degree data and the average value of the fused group of data are combined with the physical parameter information of the high-temperature furnace, and a simulation model of the high-temperature furnace is established based on a digital twin technology; the physical parameter information comprises the space size, the air heat transfer coefficient, the specific heat capacity, the material density and the heat conductivity of the high-temperature furnace;
and according to the simulation model, carrying out theoretical reasoning analysis on a simulation cloud picture of the internal temperature of the high-temperature furnace and the temperature change conditions in the length, width and height directions.
As a preferred embodiment of the present invention, the temperature sensor is specifically a thermocouple sensor.
As a preferred embodiment of the present invention, the method of using bias weighted averageNThe group temperature data are fused into a group of data, and the formula is:
（1）
（2）
in the method, in the process of the invention,representation ofNThe average value of each of the sets of temperature data,irepresenting each groupMThe first of the temperature dataiThe number of the two-dimensional space-saving type,i∈[1,M]and is also provided withiIs an integer;pindicating the setting value of the blast furnace; />Mean>And the set value of the high-temperature furnacepAbsolute value of deviation between; />Represent the firstjThe temperature data of the group is set,j∈[1,N]and is also provided withjIs an integer; />Representing the fused set of data.
As a preferred embodiment of the present invention, the said methodNThe uniformity of the high-temperature furnace is calculated by transverse comparison among the group temperature data, and the method specifically comprises the following steps:
one by one calculateNThe deviation of the maximum value and the minimum value recorded in the same preset time period in the group temperature data is taken as the uniformity of the high-temperature furnaceThe formula is:
（3）
in the method, in the process of the invention,represent the firstjGroup temperature data;
the fused data are used for calculating the temperature deviation and fluctuation of the high-temperature furnace, and the temperature deviationThe calculation formula of (2) is as follows:
（4）
in the method, in the process of the invention,represents a fused set of data +.>Is used for the average value of (a),pindicating the setting value of the blast furnace;
from a fused set of dataMaximum value of +.>And minimum->The difference is taken as a half and half principle to calculate the volatility +.>The formula is:
（5）。
as a preferable scheme of the invention, when a simulation model of the high-temperature furnace is established based on a digital twin technology, the digital twin technology is adopted to simulate the temperature inside the high-temperature furnace, and the energy satisfies the following formula:
（6）
in the method, in the process of the invention,in the case of a heat storage item,Cis specific heat capacity->For the current temperature +.>As a function of the current temperature vector,Kfor the current temperature correction term, +.>For the moment of timetIs a heat source of the heat engine;
under the condition that the current temperature is detected, calculating a temperature vector of the next time period, wherein the formula is as follows:
（7）
in the method, in the process of the invention,for the next time periodnTemperature value of +1, ">For the current time periodnTemperature value of (2); />The Euler parameters are 0.5-1; />Is a time period; />For the next time periodnA temperature vector of +1;
the equation obtained after taking the time parameter on the basis of equation (6) is as follows:
（8）
the equations for solving the next time period obtained by the simultaneous equation (7) and equation (8) are:
（9）
in the method, in the process of the invention,for the current time periodnIs a temperature vector of (a); />For the moment of timetIs>Modulus of (c).
As a preferable scheme of the invention, the method for establishing the simulation model of the high-temperature furnace based on the digital twin technology specifically comprises the following steps:
inputting physical parameter information of the high-temperature furnace;
establishing a simulation model of the high-temperature furnace according to the physical parameter information of the high-temperature furnace, and performing grid division;
applying a convective heat transfer load and an initial temperature to the established simulation model, and carrying out solution by using a formula (9);
and analyzing the solved simulation model, and establishing a simulation cloud picture of the internal temperature of the high-temperature furnace and a temperature change curve of the high-temperature furnace in the length, width and height directions.
Compared with the prior art, the invention has the beneficial effects that: by arranging a plurality of temperature sensors and recording a large amount of temperature data, the temperature distribution condition inside the ultra-large high-temperature furnace is more comprehensively known, and a plurality of groups of temperature data are fused into a group of data in a deviation weighted average mode, so that errors can be reduced, and the accuracy of temperature measurement can be improved; based on the traditional temperature detection technology, a digital twin technology is combined to establish a simulation model of the high-temperature furnace, an artificial intelligence mode is adopted to conduct accurate test of the ultra-large high-temperature furnace, the internal temperature change condition of the ultra-large high-temperature furnace is more vividly known, potential problems can be found and solved in time, and the stability and reliability of the ultra-large high-temperature furnace are improved; according to the simulation model, a simulation cloud image of the internal temperature of the high-temperature furnace and the temperature change conditions in the length, width and height directions can be analyzed in a reasoning manner, so that the production operation is guided, such as adjustment of the placement mode of materials in the furnace, optimization of a heating strategy and the like, and the production efficiency and the product quality are improved; through accurate test and optimization furnace temperature distribution, can reduce energy consumption and material waste, reduce manufacturing cost, reduce fault and down time and reduce maintenance cost and production loss.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic view of a high Wen Lujie structure in an embodiment of the invention;
FIG. 3 is a schematic diagram of temperature distribution in an embodiment of the present invention;
FIG. 4 is a graph showing a temperature distribution after data fusion in an embodiment of the present invention;
FIG. 5 is a graph showing temperature variation in the X-axis direction in an embodiment of the present invention;
FIG. 6 is a graph showing temperature variation in the Y-axis direction in an embodiment of the present invention;
fig. 7 is a graph showing a temperature change in the Z-axis direction in the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which are obtained by a person skilled in the art based on the described embodiments of the invention, fall within the scope of protection of the invention.
As shown in fig. 1, in one embodiment of the present invention, the embodiment provides a temperature simulation method for an ultra-large high temperature furnace based on digital twin technology, which includes the following steps:
s1: co-arrangement in ultra-large high temperature furnacesNAt least one temperature sensor is respectively arranged at four corners of the bottom plane of the high-temperature furnace and the center point of the bottom plane;
preferably, the temperature sensor is in particular a thermocouple sensor.
S2: after the temperature of the high-temperature furnace is stable, the indication values of the temperature sensors are recorded one by one every preset time period, and each temperature sensor recordsMThe data of the respective temperatures are provided for,Mnot less than 20; then together recordNTemperature data of groups, each group includingMA plurality of temperature data;
s3: separately calculateNThe average value of each group in the group temperature data is weighted and averaged based on the deviation between the average value and the set value of the high temperature furnaceNThe group temperature data are fused into a group of data;
in one embodiment, the deviation is weighted and averagedNThe group temperature data are fused into a group of data, and the formula is:
（1）
（2）
in the method, in the process of the invention,representation ofNThe average value of each of the sets of temperature data,irepresenting each groupMThe first of the temperature dataiThe number of the two-dimensional space-saving type,i∈[1,M]and is also provided withiIs an integer;pindicating the setting value of the blast furnace; />Mean>And the set value of the high-temperature furnacepAbsolute value of deviation between; />Represent the firstjThe temperature data of the group is set,j∈[1,N]and is also provided withjIs an integer; />Representing the fused set of data.
S4: according toNThe uniformity of the high-temperature furnace is calculated by transverse comparison among the temperature data, and the temperature deviation and fluctuation of the high-temperature furnace are calculated by using the fused data;
in a specific embodiment, according toNThe uniformity of the high-temperature furnace is calculated by transverse comparison among the group temperature data, and the method specifically comprises the following steps:
one by one calculateNThe deviation of the maximum value and the minimum value recorded in the same preset time period in the group temperature data is taken as the uniformity of the high-temperature furnaceThe formula is:
（3）
calculating the temperature deviation and fluctuation of the high-temperature furnace by using the fused set of data, wherein the temperature deviationThe calculation formula of (2) is as follows:
（4）
in the method, in the process of the invention,represents a fused set of data +.>Is used for the average value of (a),pindicating the setting value of the blast furnace;
from a fused set of dataMaximum value of +.>And minimum->The difference is taken as a half and half principle to calculate the volatility +.>The formula is:
（5）。
s5: by detection ofNThe group temperature data and the average value of the fused group of data are combined with the physical parameter information of the high-temperature furnace, and a simulation model of the high-temperature furnace is established based on a digital twin technology; the physical parameter information comprises the space size, the air heat transfer coefficient, the specific heat capacity, the material density and the heat conductivity of the high-temperature furnace;
when a simulation model of the high-temperature furnace is established based on a digital twin technology, the digital twin technology is adopted to simulate the temperature inside the high-temperature furnace, and the energy meets the following formula:
（6）
in the method, in the process of the invention,in the case of a heat storage item,Cis specific heat capacity->For the current temperature +.>As a function of the current temperature vector,Kfor the current temperature correction term, +.>For the moment of timetIs a heat source of the heat engine;
under the condition that the current temperature is detected, calculating a temperature vector of the next time period, wherein the formula is as follows:
（7）
in the method, in the process of the invention,for the next time periodnTemperature value of +1, ">For the current time periodnTemperature value of (2); />The Euler parameters are 0.5-1; />Is a time period; />For the next time periodn+1A temperature vector;
the equation obtained after taking the time parameter on the basis of equation (6) is as follows:
（8）
the equations for solving the next time period obtained by the simultaneous equation (7) and equation (8) are:
（9）
in the method, in the process of the invention,for the current time periodnIs a temperature vector of (a); />For the moment of timetIs>Modulus of (c).
In a specific embodiment, step S5 specifically includes:
s51: inputting physical parameter information of the high-temperature furnace;
s52: establishing a simulation model of the high-temperature furnace according to the physical parameter information of the high-temperature furnace, and performing grid division;
s53: applying a convective heat transfer load and an initial temperature to the established simulation model, and carrying out solution by using a formula (9);
s54: and analyzing the solved simulation model, and establishing a simulation cloud picture of the internal temperature of the high-temperature furnace and a temperature change curve of the high-temperature furnace in the length, width and height directions.
S6: according to the simulation model, theoretical reasoning analysis is carried out on the simulation cloud picture of the internal temperature of the high-temperature furnace and the temperature change conditions in the length, width and height directions.
As shown in fig. 2-7, another embodiment of the present invention is taken as an example of a lifting type resistance furnace, and the temperature set value of the high temperature furnace is set to 500 ℃, so that the implementation process of the present invention is further described.
S1: one thermocouple sensor is respectively arranged at four corners of the bottom plane of the lifting type resistance furnace and the center point of the bottom plane, namely 5 thermocouple sensors are arranged in total and are respectively marked as A, B, C, D, O, as shown in fig. 3;
s2: after the temperature of the high-temperature furnace is stable, recording the indication values of the thermocouple sensors one by one every 1min, and recording for 20min; a total of 5 sets of temperature data are recorded, each set including 20 temperature data (i.eN=5，M=20), as shown in table 1:
table 1 5 sets of data (. Degree. C.) recorded within 20min
S3: respectively calculating the average value of each group in the 5 groups of temperature data, and fusing the 5 groups of temperature data into one group of data by adopting a deviation weighted average mode based on the deviation between the average value and the set value of the high-temperature furnace;
average of 5 sets of temperature dataAs shown in table 1, 496.0, 495.8, 496.0, 497.2, 497.6, respectively;
calculating the average value according to the formula (1)Absolute value of deviation from the set value of 500 DEG C>The method comprises the following steps of: 4.0, 4.2, 4.0, 2.8, 2.4;
（1）
according to absolute value of deviationCalculated weight value +.>The method comprises the following steps of: 0.23, 0.24, 0.23, 0.16, 0.14;
according to the formula (2), adopting a deviation weighted average mode to integrate 5 groups of temperature data into one group of data;
（2）
for example: data of the first line in Table 1The method comprises the following steps of: 496.8, 494.5, 495.5, 498.2, 494.8, the first fused data +.>=496.8×0.23+494.5×0.24+495.5×0.23+498.2×0.16+494.8×0.14=495.893≈495.9℃；
The temperature distribution after data fusion is shown in FIG. 4, and a group of data after fusionAs shown in table 2:
TABLE 2 set of fused data (. Degree. C.)
S4: calculating the uniformity of the high-temperature furnace according to the transverse comparison among 5 groups of temperature data, and calculating the temperature deviation and the fluctuation of the high-temperature furnace by using one group of fused data;
calculating the deviation of the maximum value and the minimum value recorded in the same time period in 5 groups of temperature data one by one, wherein the maximum deviation of 5.0 is taken as the uniformity of the high temperature furnace according to the formula (3) as shown in the last column of the table 1；
（3）
Calculate a fused set of data in Table 2Mean value of>496.4, and calculating to obtain the temperature deviation of the high-temperature furnace to be-3.6 ℃ according to a formula (4);
（4）
maximum value 497.3 and minimum value 495.4 in Table 2, the volatility is determined according to equation (5)Is + -1.0deg.C (here one decimal place is reserved);
（5）。
s5: establishing a simulation model of the high-temperature furnace based on a digital twin technology by combining the detected 5 groups of temperature data and the average value of the fused group of data with the physical parameter information of the high-temperature furnace; the physical parameter information comprises the space size, the air heat transfer coefficient, the specific heat capacity, the material density and the heat conductivity of the high-temperature furnace;
s51: inputting physical parameter information of the high-temperature furnace;
the space size of the high temperature furnace is as follows: 2.5 m long, 3 m wide and 1.5 m high; the air heat transfer coefficient isSpecific heat capacity of +.>The density of the material is +.>The heat conductivity is->；
S52: establishing a simulation model of the high-temperature furnace according to the physical parameter information of the high-temperature furnace, and performing grid division;
because of the symmetry of the space model, the invention adopts a 1/4 model for research, and finally, expansion and completion are carried out;
when a simulation model of the high-temperature furnace is established based on a digital twin technology, the digital twin technology is adopted to simulate the temperature inside the high-temperature furnace, and the energy meets the following formula:
（6）
in the method, in the process of the invention,in the case of a heat storage item,Cis specific heat capacity->For the current temperature +.>As a function of the current temperature vector,Kfor the current temperature correction term, +.>For the moment of timetIs a heat source of the heat engine;
under the condition that the current temperature is detected, calculating a temperature vector of the next time period, wherein the formula is as follows:
（7）
in the method, in the process of the invention,for the next time periodnTemperature value of +1, ">For the current time periodnTemperature value of (2); />The Euler parameters are 0.5-1; />Is a time period; />For the next time periodnA temperature vector of +1;
the equation obtained after taking the time parameter on the basis of equation (6) is as follows:
（8）
the equations for solving the next time period obtained by the simultaneous equation (7) and equation (8) are:
（9）
in the method, in the process of the invention,for the current time periodnIs a temperature vector of (a); />For the moment of timetIs>Modulus of (d);
s53: applying a convective heat transfer load and an initial temperature to the established simulation model, and carrying out solution by using a formula (9);
the initial temperature of the air in the high-temperature furnace is 20 ℃, except one surface at the top is not heated, the other 5 surfaces are all provided with heated resistance wires, the set value of the temperature is 500 ℃, and the temperature is stable after 25 min; setting Euler parametersThe value of (2) is 0.5;
s54: analyzing the solved simulation model, and establishing a simulation cloud picture of the internal temperature of the high-temperature furnace; and temperature change curves of the high-temperature furnace in the length, width and height directions, as shown in fig. 5-7.
S6: according to the simulation model, theoretical reasoning analysis is carried out on a simulation cloud picture of the internal temperature of the high-temperature furnace and the temperature change conditions in the length, width and height directions;
according to the simulation cloud picture, after the temperature reaches the set value of 500 ℃ and is stabilized for 5min, the temperature of the innermost four corners of the high-temperature furnace can reach 499.4 ℃, and the temperature of the middle area of the space is lower and is 498.6 ℃, so that the middle area needs to be avoided as much as possible when the metal material workpiece is subjected to heat treatment.
The method comprises the following steps: fig. 5-7, partially illustrated in english:
NODAL SOLUTION: post-processing operation of simulation software;
STEP: step length; SUB: step number sequence; TIM: time; PATH PLOT: a path diagram; NOD1: a point sequence number; NOD2: a point sequence number; DIST: distance.
In summary, the invention can more comprehensively understand the temperature distribution condition in the ultra-large high temperature furnace by arranging a plurality of temperature sensors and recording a large amount of temperature data, and integrate a plurality of groups of temperature data into one group of data by using a deviation weighted average mode, thereby reducing errors and improving the accuracy of temperature measurement; based on the traditional temperature detection technology, a digital twin technology is combined to establish a simulation model of the high-temperature furnace, an artificial intelligence mode is adopted to conduct accurate test of the ultra-large high-temperature furnace, the internal temperature change condition of the ultra-large high-temperature furnace is more vividly known, potential problems can be found and solved in time, and the stability and reliability of the ultra-large high-temperature furnace are improved; according to the simulation model, a simulation cloud image of the internal temperature of the high-temperature furnace and the temperature change conditions in the length, width and height directions can be analyzed in a reasoning manner, so that the production operation is guided, such as adjustment of the placement mode of materials in the furnace, optimization of a heating strategy and the like, and the production efficiency and the product quality are improved; through accurate test and optimization furnace temperature distribution, can reduce energy consumption and material waste, reduce manufacturing cost, reduce fault and down time and reduce maintenance cost and production loss.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think of various changes or substitutions within the technical scope of the present application, and these should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (6)
1. The ultra-large high-temperature furnace temperature simulation method based on the digital twin technology is characterized by comprising the following steps of:
co-arrangement in ultra-large high temperature furnacesNAt least one temperature sensor is respectively arranged at four corners of the bottom plane of the high-temperature furnace and the center point of the bottom plane;
after the temperature of the high-temperature furnace is stable, the indication values of the temperature sensors are recorded one by one every preset time period, and each temperature sensor recordsMThe data of the respective temperatures are provided for,Mnot less than 20; then together recordNTemperature data of groups, each group includingMA plurality of temperature data;
separately calculateNAverage value of each group in the group temperature data is weighted and averaged based on deviation between the average value and the set value of the high temperature furnaceNThe group temperature data are fused into a group of data;
according toNThe uniformity of the high-temperature furnace is calculated by transverse comparison among the temperature data, and the temperature deviation and fluctuation of the high-temperature furnace are calculated by using the fused data;
by detection ofNThe group temperature data and the average value of the fused group of data are combined with the physical parameter information of the high-temperature furnace, and a simulation model of the high-temperature furnace is established based on a digital twin technology; the physical parameter information comprises the space size, the air heat transfer coefficient, the specific heat capacity, the material density and the heat conductivity of the high-temperature furnace;
and according to the simulation model, carrying out theoretical reasoning analysis on a simulation cloud picture of the internal temperature of the high-temperature furnace and the temperature change conditions in the length, width and height directions.
2. The ultra-large high-temperature furnace temperature simulation method based on the digital twin technology according to claim 1, wherein the temperature sensor is specifically a thermocouple sensor.
3. The ultra-large high-temperature furnace temperature simulation method based on the digital twin technology as claimed in claim 1, wherein the deviation weighted average mode is adopted for the simulationNThe group temperature data are fused into a group of data, and the formula is:
（1）
（2）
in the method, in the process of the invention,representation ofNThe average value of each of the sets of temperature data,irepresenting each groupMThe first of the temperature dataiThe number of the two-dimensional space-saving type,i∈[1,M]and is also provided withiIs an integer;pindicating the setting value of the blast furnace; />Mean>And the set value of the high-temperature furnacepAbsolute value of deviation between; />Represent the firstjThe temperature data of the group is set,j∈[1,N]and is also provided withjIs an integer; />Representing the fused set of data.
4. The digital twinning technology-based ultra-large high-temperature furnace temperature simulation method of claim 1Characterized in that the said method is based onNThe uniformity of the high-temperature furnace is calculated by transverse comparison among the group temperature data, and the method specifically comprises the following steps:
one by one calculateNThe deviation of the maximum value and the minimum value recorded in the same preset time period in the group temperature data is taken as the uniformity of the high-temperature furnaceThe formula is:
（3）
in the method, in the process of the invention,represent the firstjGroup temperature data;
the fused data are used for calculating the temperature deviation and fluctuation of the high-temperature furnace, and the temperature deviationThe calculation formula of (2) is as follows:
（4）
in the method, in the process of the invention,represents a fused set of data +.>Is used for the average value of (a),pindicating the setting value of the blast furnace;
from a fused set of dataMaximum value of +.>And minimum->The difference is taken as a half and half principle to calculate the volatility +.>The formula is:
（5）。
5. the ultra-large high-temperature furnace temperature simulation method based on the digital twin technology according to claim 1, wherein when a simulation model of the high-temperature furnace is established based on the digital twin technology, the digital twin technology is adopted to simulate the temperature inside the high-temperature furnace, and the energy satisfies the following formula:
（6）
in the method, in the process of the invention,in the case of a heat storage item,Cis specific heat capacity->For the current temperature +.>As a function of the current temperature vector,Kfor the current temperature correction term, +.>For the moment of timetIs a heat source of the heat engine;
under the condition that the current temperature is detected, calculating a temperature vector of the next time period, wherein the formula is as follows:
（7）
in the method, in the process of the invention,for the next time periodnTemperature value of +1, ">For the current time periodnTemperature value of (2); />The Euler parameters are 0.5-1; />Is a time period; />For the next time periodnA temperature vector of +1;
the equation obtained after taking the time parameter on the basis of equation (6) is as follows:
（8）
the equations for solving the next time period obtained by the simultaneous equation (7) and equation (8) are:
（9）
in the method, in the process of the invention,for the current time periodnIs a temperature vector of (a); />For the moment of timetIs>Modulus of (c).
6. The digital twinning technology-based ultra-large high-temperature furnace temperature simulation method is characterized by comprising the following steps of:
inputting physical parameter information of the high-temperature furnace;
establishing a simulation model of the high-temperature furnace according to the physical parameter information of the high-temperature furnace, and performing grid division;
applying a convective heat transfer load and an initial temperature to the established simulation model, and carrying out solution by using a formula (9);
and analyzing the solved simulation model, and establishing a simulation cloud picture of the internal temperature of the high-temperature furnace and a temperature change curve of the high-temperature furnace in the length, width and height directions.
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