CN115232955B - Optimization control method for strip steel temperature in dynamic heating process of continuous annealing furnace - Google Patents
Optimization control method for strip steel temperature in dynamic heating process of continuous annealing furnace Download PDFInfo
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- CN115232955B CN115232955B CN202210873135.3A CN202210873135A CN115232955B CN 115232955 B CN115232955 B CN 115232955B CN 202210873135 A CN202210873135 A CN 202210873135A CN 115232955 B CN115232955 B CN 115232955B
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21D—MODIFYING THE PHYSICAL STRUCTURE OF FERROUS METALS; GENERAL DEVICES FOR HEAT TREATMENT OF FERROUS OR NON-FERROUS METALS OR ALLOYS; MAKING METAL MALLEABLE, e.g. BY DECARBURISATION OR TEMPERING
- C21D9/00—Heat treatment, e.g. annealing, hardening, quenching or tempering, adapted for particular articles; Furnaces therefor
- C21D9/52—Heat treatment, e.g. annealing, hardening, quenching or tempering, adapted for particular articles; Furnaces therefor for wires; for strips ; for rods of unlimited length
- C21D9/54—Furnaces for treating strips or wire
- C21D9/56—Continuous furnaces for strip or wire
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21D—MODIFYING THE PHYSICAL STRUCTURE OF FERROUS METALS; GENERAL DEVICES FOR HEAT TREATMENT OF FERROUS OR NON-FERROUS METALS OR ALLOYS; MAKING METAL MALLEABLE, e.g. BY DECARBURISATION OR TEMPERING
- C21D11/00—Process control or regulation for heat treatments
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Abstract
The invention discloses an optimization control method for strip steel temperature in a dynamic heating process of a continuous annealing furnace, which belongs to the technical field of intelligent steel manufacturing, and realizes accurate temperature control of a heating section, active optimization and dynamic customization of a strip steel heating mode by constructing a full-furnace strip steel temperature distribution calculation model of the heating section of the annealing furnace and a dynamic optimization setting model of the temperature of each row of radiant tubes of the heating section.
Description
Technical Field
The invention relates to the technical field of intelligent steel manufacturing, in particular to an optimization control method for strip steel temperature in a dynamic heating process of a continuous annealing furnace.
Background
The continuous annealing furnace is an important heat treatment procedure in the production of cold-rolled strip steel, and the strip steel recrystallization device is used for annealing, so that the work hardening and residual stress in the cold rolling process can be eliminated, the plastic deformation capability of the steel can be recovered, and the performance of the steel can be improved. Many high-grade strip steel products must be subjected to continuous annealing treatment, such as automotive, household and electrical panels, to improve product quality and market competitiveness. The continuous annealing furnace generally comprises a preheating section, a radiant tube heating section, a soaking section, a slow cooling section, a flash cooling section, an overaging section, a final cooling section and other working procedures. Cold strip steel is run at high speed (current process speed is over 350 m/min) from furnace in to furnace out to complete such a long continuous heat treatment process, and the length of the strip steel in the furnace is even more than 2000 m. Wherein, the dynamic heating process of the continuous annealing furnace is mainly in the heating section of the radiant tube. In a vertical annealing furnace, the temperature control of the strip steel is the core of the heat treatment process. The heating section of the radiant tube is the furnace section with the largest thermal inertia, the thermal inertia time of the furnace is far longer than the residence time of the strip steel in the furnace, and the structure is complex, the distance is long, the high temperature and the heat transfer characteristic are complex, so that the strip steel temperature control of the heating section of the radiant tube has the characteristics of nonlinearity and large hysteresis, and the disturbance factors of the strip steel temperature control of the heating section are increased due to the frequent changes of the technical parameters such as strip steel specification, speed and the like.
The structure and the process of the radiant tube heating section of the continuous annealing furnace lead the radiant tube heating section to present complex thermal behavior and dynamic characteristics, so that the temperature control of the strip steel has the characteristics of nonlinearity, large hysteresis, time variability and multiple interferences, and meanwhile, the effect of the temperature control of the radiant tube heating section can directly influence the quality and the performance of the annealed strip steel product, so the radiant tube heating section becomes the most difficult but also most important furnace section with the steel temperature in the whole continuous annealing furnace. The accurate control of the temperature of the strip steel in the heating section is important, the temperature of the strip steel in the annealing furnace is not easy to continuously and accurately measure at present, the accurate prediction of the temperature distribution of the strip steel in the furnace is carried out by means of an accurate strip steel temperature calculation model to realize the control of the strip temperature, and the method has important significance for the design, offline analysis and online control of the strip steel continuous annealing furnace. Therefore, how to accurately calculate and dynamically track the temperature distribution of the strip steel in the heating process of the continuous annealing furnace and realize accurate temperature control is a technical problem to be solved urgently at present. Therefore, an optimized control method for the temperature of the strip steel in the dynamic heating process of the continuous annealing furnace is provided.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: how to accurately calculate and dynamically track the strip steel temperature distribution in the continuous annealing furnace heating process, and realize accurate temperature control, and provides an optimization control method for the strip steel temperature in the continuous annealing furnace dynamic heating process.
The invention solves the technical problems through the following technical proposal, and the invention comprises the following steps:
the method comprises the following steps:
s1: constructing a heating section full-furnace band steel temperature distribution calculation model, determining basic parameters and solution conditions of model design, and adopting a heat transfer inverse problem method to correct the heating section full-furnace band steel temperature distribution calculation model on line;
s2: and constructing a dynamic optimizing setting model of the temperature of each row of radiant tubes of the heating section, and optimizing and selecting different heating modes meeting the requirements of a heat treatment process.
Still further, the step S1 includes the sub-steps of:
s11: aiming at the structure, process, equipment and automatic control system of the dynamic heating process of the actual continuous strip steel annealing furnace, the arrangement and structure size of radiant tubes in the heating section, the length and quantity of the strip channels, the specification and steel grade of strip steel products, the process speed, the internal material of furnace walls and the heat transfer characteristics are determined;
s12: setting relevant basic parameters of a heating section strip steel temperature distribution calculation model, wherein the relevant basic parameters comprise strip steel, radiant tube and furnace wall blackness, strip steel density and strip steel specific heat capacity;
s13: dividing the heating section into a plurality of closed calculation areas and strip steel units according to the arrangement of the radiant tubes of the heating section and the hearth structure;
S14: an initial temperature profile X is assumed along the length of the strip p Initializing the temperature distribution of the full-furnace band steel of the heating section, namely T p '＝X p Wherein p=0, 1,2,..，T p ' is the initialized temperature distribution of the full furnace band steel of the heating section;
s15: for each strip unit i, a heat flux density calculation is performed, where i=1, 2;
s16: based on theory of heat transfer, carrying out heat balance relation calculation on each strip steel unit in turn, wherein the heat received by the strip steel unit is equal to the heat required by the strip steel unit to heat, and calculating to obtain the endpoint temperature T of the strip steel unit i+1 The following formula is shown:
wherein T is i And T i+1 The temperatures of the starting point and the end point of the ith strip steel unit are respectively, wherein the starting point of the ith strip steel unit is i point, and the end point is i+1 point; q i The total received heat flux density of the left and right side surfaces of the ith strip steel unit is the sum of the radiation heat flux density and the convection heat flux density of the left and right side surfaces of the ith strip steel unit; ΔL i,i+1 The distance from the point i to the point i+1 on the ith strip steel unit; ρ s Is the density of the strip steel; c (C) s,i Taking the average temperature of the ith strip steel unit as the specific heat capacity of the ith strip steel unit to obtain the specific heat capacity; delta s For the thickness of the ith strip unit, u s The speed of the strip steel is the speed of the strip steel;
s17: the method comprises the steps of measuring strip steel temperatures of high-speed operation at an inlet and an outlet of a heating section in real time through infrared radiation pyrometers, measuring hot spot temperatures and hearth temperatures of all rows of radiant tubes in real time through thermocouples to obtain actual measurement data of the inlet and outlet strip temperatures, all rows of radiant tube temperatures, furnace temperatures, strip steel speeds and strip steel specifications, correcting a heating section full-furnace strip steel temperature distribution calculation model in real time on line through a heat transfer inverse problem method, and performing self-learning correction on model parameters to adapt to the change of actual furnace conditions, wherein the heat transfer inverse problem method refers to comparing the calculated outlet strip temperatures according to the heating section full-furnace strip steel temperature distribution calculation model with the actual measured strip temperatures, so as to inversely calculate model parameter correction.
S18: according to the model input parameters measured in real time, including the width, thickness and speed of the strip steel, the temperature of the inlet strip steel of the heating section, the temperature of each row of radiant tubes and the temperature of each region, the temperature distribution of the whole-furnace strip steel is predicted in real time in a certain time period, and the dynamic tracking of the temperature distribution change of the strip steel is realized.
Further, in the step S13, the closed calculation regions are divided into two types, the first type is a region containing radiant tubes and the second type is a region not containing radiant tubes, and each closed calculation region is composed of a left-side strip surface, a right-side strip surface, a radiant tube surface, a furnace wall, and a plurality of imaginary planes.
Still further, in the step S14, the initialized temperature distribution of the full-furnace steel in the heating section uses temperature data of corresponding positions on a theoretical annealing temperature curve, the theoretical annealing temperature curve refers to a linear heating curve from the in-furnace temperature to the desired out-furnace temperature of the steel strip.
Further, in the step S15, the heat flux density received by each strip steel unit includes a radiant heat flux density, that is, the net radiant heat exchange amount of the left and right surfaces of the strip steel unit, and a convective heat exchange amount between the furnace gas and the strip steel unit;
the radiation heat flow density calculation needs to be carried out according to the divided closed calculation areas on the left side and the right side of the strip steel unit, and the radiation heat exchange calculation of each closed calculation area is carried out, wherein the calculation process is as follows:
s1501: determining how many surfaces the closed computing area shares to form a closed radiation heat exchange system, and recording the number of the surfaces as n;
s1502: calculating the radiation heat exchange angle coefficient f between every two surfaces in the closed calculation area by Monte Carlo method ik Then the effective radiation J of the i surface i Represented by the formula:
wherein sigma is Stefan-Boltzmann constant, epsilon i I surface darkness, T i I surface temperature, f ik An angular coefficient from i surface to k surface;
the above equation is n equations and n unknown effective radiations J i The effective radiation J of any i surface can be obtained by adopting an iterative method i ；
S1503: calculating the net radiant heat flux density q according to i And then the radiant heat flux density of the left surface and the right surface of each strip steel unit can be obtained:
the calculation process of the convection heat flux density is as follows:
s1511: calculating the forced convection heat exchange coefficient of the strip steel unit and the furnace gas according to the condition that the fluid is sweeped outside the flat plate, and calculating the forced convection heat exchange coefficient of the furnace gas and the strip steel according to the Noevent standard number, wherein the forced convection heat exchange coefficient is shown in the following formula:
wherein h is a convective heat transfer coefficient; nu is the nuceltel number; lambda (lambda) f Is the heat conductivity coefficient; l is the characteristic dimension, which refers to the length of fluid flowing through the plate;
s1512: and (3) obtaining the convection heat flux density of the surface of the strip steel unit according to a Newton cooling formula:
q c ＝2h c (T g -T s )
wherein q is c The heat flux density is the heat convection between the left and right surfaces of the strip steel unit and the furnace gas; h is a c Is the forced convection heat exchange coefficient between furnace gas and strip steel unit, T g And T s The furnace temperature and the strip steel unit temperature of the region are respectively indicated.
Further, in said step S16, the latest calculated value T is calculated i+1 If the difference is large, i.e. the difference exceeds the maximum temperature error e, compared to the previously assumed temperature value, this new temperature T is used i+1 Re-proceedingThe radiation heat exchange calculation of the closed areas at the two sides of the strip steel unit is repeatedly iterated until the calculated temperatures of the two adjacent times are close enough, namely, the difference value is within the range of the maximum temperature error e; meanwhile, considering that the downstream strip steel temperature used in the radiation heat exchange calculation adopts an assumed value, after the calculation of the temperature distribution of the whole-furnace strip steel is carried out once, all the calculation is carried out again by using the latest calculated value, the calculation of the temperature distribution of the whole-furnace strip steel is repeatedly iterated until the temperature distribution of the whole-furnace strip steel calculated in two adjacent times is close enough, and the convergence standard of the iterative process is the allowable maximum temperature error e.
Still further, the step S2 includes the sub-steps of:
s21: analyzing the limit speeds of the strip steel with different specifications of different steel grades of the heating section, namely calculating the limit speed by adopting a heating section strip steel temperature distribution calculation model according to the strip steel grade, specification and strip steel temperature heat treatment process requirements of a discharging furnace on the premise of the limit heating capacity of a specified strip steel continuous heat treatment unit and a radiant tube;
S22: constructing a dynamic optimizing setting model of the temperature of each row of radiant tubes of the heating section;
s23: and when the temperature of the strip steel at the outlet of the heating section meets the heat treatment process requirement, a plurality of different strip steel heating temperature rising modes exist, and different strip steel heating modes are selected for calculation and optimization according to actual needs.
Further, in the step S21, the limit speed of the strip is calculated as follows:
s211: giving an initial value u to the speed u of the strip steel 0 And sets a termination error epsilon;
s212: taking the maximum value according to the steel grade, width and thickness of the strip steel and the temperature of all the radiant tubes, and obtaining the temperature T of the furnace strip steel by using a heating section strip steel temperature distribution calculation model 1 ；
S213: will T 1 And the lower limit T of the temperature treatment process required range of the tapping zone 2 Comparing, if 0.ltoreq.DeltaT=T is satisfied 1 -T 2 Less than epsilon, the limit belt speed u of the heating section of the radiant tube max Otherwise, increase or decrease the current strip speed by a small amountThe quantity Deltau, i.e. u=u+ -Deltau, is then brought into the heating section strip steel temperature distribution calculation model to re-calculate the temperature T of the strip steel 1 Until the condition 0.ltoreq.DeltaT=T is satisfied 1 -T 2 Less than or equal to epsilon, and further solving the limit speed of the strip steel;
s214: the limit speed of the strip steel of the whole continuous annealing unit is limited by the requirements of other furnace sections, including the minimum overaging time required by the overaging section process, and the limit speed of the strip steel of the overaging section is the ratio of the expansion length of the furnace section to the minimum overaging time; the strip steel limit speed of the final unit is the minimum value of the strip steel limit speeds of the heating section and the overaging section of the radiant tube.
Further, in the step S22, a specific process of constructing a dynamic optimization setting model of the temperature of each row of radiant tubes of the heating section is as follows:
s221: setting relevant basic parameters of a dynamic optimization setting model of the temperature of each row of radiant tubes of the heating section, wherein the relevant basic parameters comprise strip steel, blackness of radiant tubes and furnace walls, strip steel density and strip steel specific heat capacity;
s222: generating the desired strip temperature T of the outlet of the heating section according to the theoretical annealing temperature profile of the known steel grade exp Setting a group of radiant tube temperature heuristic values of each row;
s223: inputting the temperature heuristic values of each row of radiant tubes into a heating section full-furnace strip steel temperature distribution calculation model, and calculating a heating section outlet strip steel temperature predicted value T under the radiant tube heuristic values p ；
S224: according to the objective function Δt=t p -T exp <eps, judging whether the temperature of each row of radiant tubes needs to be adjusted, and if the temperature of each row of radiant tubes does not reach the objective function condition, adjusting the temperature of each row of radiant tubes by adopting the following steps:
T i,tube ＝T i,tube -f*△T
wherein T is i,tube The temperature of the radiant tube in the ith row is f, the temperature adjustment coefficient of the radiant tube is f, and DeltaT is the difference between the predicted value and the expected value of the temperature of the strip steel at the outlet of the heating section;
and if the objective function reaches the condition, obtaining the temperature optimized value of the radiant tube, wherein eps is a temperature error convergence standard.
Further, in the step S23, the heating mode of the strip steel includes a mode in which the temperatures of the radiant tubes in each row are the same and a mode in which the temperatures of the radiant tubes in each row are increased, wherein the mode in which the temperatures of the radiant tubes in each row are the same, i.e., the radiant tubes in each row are heated at the same temperature, the mode in which the temperatures of the radiant tubes in each row are increased, i.e., the first radiant tube temperature in each row is started, the temperature increases of the radiant tubes in each row are the same, and the temperatures of the radiant tubes in each subsequent row are all the maximum until the temperature of the radiant tube in each row reaches the maximum value.
Compared with the prior art, the invention has the following advantages:
the invention aims at the heating section which is the most important to the quality and performance of strip steel products in the whole continuous annealing furnace and is also the section which is the most difficult to control the temperature of the strip steel in the whole annealing furnace (the characteristics of nonlinear control, large hysteresis, time variability and multiple interferences of the strip temperature caused by complex thermal behavior and dynamic characteristics), the method comprises the steps of constructing an accurate calculation model of the temperature distribution of the whole furnace steel of the heating section of the annealing furnace and a dynamic optimization setting model of the temperature of each row of radiant tubes of the heating section, and realizing accurate temperature control of the heating section, active optimization of a strip steel heating mode and dynamic customization.
The method is reliable in theory, practical, accurate in calculation and high in applicability, can be popularized to accurate prediction, dynamic heat tracking and real-time visualization of the temperature of the strip steel under any continuous annealing furnace and various different working conditions, and optimal setting of heat treatment operation parameters, and has important significance for optimizing the process and operation in the actual production process, improving the hit rate of the temperature of the strip steel at the outlet of the heating section within the annealing temperature requirement range, saving energy, reducing cost, enhancing efficiency and the like.
Drawings
FIG. 1 is a flow chart of an optimized control method for the temperature of strip steel in the dynamic heating process of a continuous annealing furnace in the embodiment of the invention;
FIG. 2 is a schematic diagram of a radiant tube heating section of a continuous annealing furnace in an embodiment of the invention;
FIG. 3 is a flow chart of a calculation model of the temperature distribution of the radiant tube heating section full-furnace band steel in the embodiment of the invention;
FIG. 4 is a schematic view of the i-th strip unit and the closed calculation area on both sides in an embodiment of the present invention;
FIG. 5 is a schematic diagram of the temperature distribution of the heating section full-furnace steel under a specific working condition in an embodiment of the invention;
FIG. 6 is a flow chart of calculating the limit belt speed of the heating section of the radiant tube in the embodiment of the invention;
FIG. 7 is a flow chart illustrating the calculation of the temperature set point for each row of radiant tubes in the heating section according to an embodiment of the present invention;
FIG. 8 is a graph showing the temperature rise of a strip steel with different heating modes meeting the heat treatment process requirements of a heating section in an embodiment of the invention.
Detailed Description
The following describes in detail the examples of the present invention, which are implemented on the premise of the technical solution of the present invention, and detailed embodiments and specific operation procedures are given, but the scope of protection of the present invention is not limited to the following examples.
In the embodiment of the invention, as shown in fig. 1, the optimization control method for the strip steel temperature in the dynamic heating process of the continuous annealing furnace comprises two parts, wherein the first part is used for constructing a calculation model of the temperature distribution of the whole strip steel in the heating section of the annealing furnace, and the second part is used for constructing a dynamic optimization setting model of the temperature of each row of radiant tubes in the heating section, and the method is specifically described as follows:
the first part, construct the whole furnace belt steel temperature distribution calculation model of the heating section of the annealing furnace, as shown in figure 3, mainly comprises the following sub-steps:
step 1.1, determining the arrangement and structure size of radiant tubes in a heating section, the length and quantity of a strip channel, the specification and steel grade of strip steel products, the process speed, the internal material of a furnace wall and the like according to the structure, the process, the equipment and the automatic control system of the dynamic heating process of the actual strip steel continuous annealing furnace.
The strip steel continuous annealing furnace of the embodiment is a vertical continuous annealing furnace, products are positioned into automobile plates, household appliance plates and the like, and the specification of the products is (0.25-2.50) × (900-2000) mm 2 The maximum process speed reaches 420m/min. The dynamic heating process (radiant tube heating section) of the annealing furnace is shown in FIG. 2, and the furnace is provided with a heating chamberThe strip steel is driven by a furnace roller under the action of certain tension, and moves back and forth up and down around the furnace roller, and indirectly heats the strip steel through radiant tubes (W type) on two sides of the surface of the strip steel. At the same time, the furnace was filled with a protective gas (about 95% N 2 +5％H 2 ) Can be regarded as a transparent medium. Therefore, dynamic heat exchange occurs among the strip steel, the radiant tube, the furnace wall, the furnace roller and the like in the radiant tube heating section, and meanwhile, the radiation heat exchange exists due to the fact that the temperature difference of the strip steel between adjacent strokes is large, and mutual influence is needed to be considered. In addition, the convective heat transfer between the strip steel and the furnace gas during the movement process is also considered. The radiant tube heating section comprises 29 strip steel passes, the length of each strip steel pass is about 21m, the total length of the strip steel in the heating section is about 650m, 31 rows of radiant tubes are arranged at the same time, the radiant tubes are marked as AA, AB, AC, … and BH in sequence according to the running direction of the strip steel, a plurality of rows of radiant tubes are arranged in each row, and 346W-shaped radiant tubes are arranged in total in the heating section. In addition, a plurality of K-type thermocouples are arranged in the heating section to detect the hearth temperature of different areas and the hot spot temperature of different rows of radiant tubes, wherein the different areas in the furnace are marked as Zone1, zone2, zone3, … and Zone15 in sequence according to the furnace temperature detection points and the strip steel running direction.
And 1.2, setting relevant basic parameters of a heating section strip steel temperature distribution calculation model, wherein the basic parameters comprise strip steel, radiant tube and furnace wall blackness, strip steel density, strip steel specific heat capacity and the like.
The values in this embodiment are as follows: the blackness of the strip steel is 0.3, the calculation influence on the temperature of the strip steel is large, and verification can be carried out according to measured data. The blackness of the radiant tube was taken to be 0.9. The furnace wall is close to the heavy radiation surface because the inner surface of the furnace wall is a bright stainless steel plate, and the blackness of the furnace wall is 0.075. The density of the strip steel is regarded as a constant, 7800kg/m is taken 3 Specific heat capacity C of strip steel p The following formula was used for calculation.
C p ＝0.0019T 2 -1.5263T+791.65 (1)
Step 1.3, dividing the heating section into a plurality of closed radiation heat exchange calculation areas and strip steel units according to the arrangement of the heating section radiant tubes and the hearth structure, such as closed calculation areas E11, E12, …, en1 and the like formed by dotted lines in FIG. 2, a strip steel unit S11 formed from P1 point to P2 point, a strip steel unit S12 formed from P2 point to P3 point and the like. There are two types of closed computing areas: the closed calculation area is constructed mainly for calculating the radiation heat exchange between the strip steel and the radiant tube and between the strip steel and the furnace wall. It should be noted here that the construction of closed computing areas on the left and right sides of the strip is critical, each closed area being made up of n surfaces, the left strip surface, the right strip surface, the radiant tube surface, the furnace wall and a plurality of imaginary surfaces.
Step 1.4, assuming an initial temperature distribution X along the strip length direction p (p=0, 1,2,) heating section full-furnace band steel temperature profile initialization, i.e., T p '＝X p P=0, 1,2, wherein the total discretization on the heating section full furnace strip is p+1 points, T p ' the (p=0, 1,2,) is an initialized heating section full furnace band steel temperature profile. The temperature distribution of the full-furnace band steel of the heating section which is just initialized adopts the temperature data of the corresponding position on a theoretical annealing temperature curve, wherein the theoretical annealing temperature curve refers to a linear heating curve from the feeding temperature of the band steel to the expected discharging temperature.
Step 1.5, for each strip unit i=1, 2. The heat flux density received by each strip steel unit mainly comprises the net radiation heat exchange quantity (namely radiation heat flux density) of the left surface and the right surface of the strip steel unit, and the convection heat exchange quantity (namely convection heat flux density) of furnace gas and the strip steel unit.
To calculate the radiant heat flux densities of the left and right surfaces of each strip unit, a part of the radiant heat flux density is taken as an example according to the above divided radiant heat exchange closed calculation areas, for example, the i-th strip unit in fig. 4 is calculated by radiant heat exchange of the closed areas E1 and E2 on both sides, and the radiant heat flux densities of the surfaces on both sides of the strip unit are obtained. The radiation heat exchange calculation of the closed areas E1 and E2 is to know the temperature, blackness and angular coefficient between every two objects in the closed system, wherein the blackness is known, the angular coefficient between every two objects can be determined, so that the temperature of the radiant tube, the temperatures of the ith, j and k strip steel units and the temperature of the furnace wall (taking the furnace chamber temperature Degree). From the strip trend, the temperature of the kth strip unit is calculated first, and the average temperature of the section of strip is taken, namely (T) k +T k+1 )/2. The temperatures of the ith and j strip steel units are assumed, and the invention takes the strip steel temperature of the theoretical annealing temperature curve at the position.
The radiation heat exchange calculation of each closed calculation area E1 or E2 adopts the following method: if the closed computing area has n surfaces in total, forming the radiation heat exchange system; next, the Monte Carlo method is first used to accurately calculate the angle coefficient f between every two surfaces within the closed system ik Then the effective radiation J of the i surface i Can be represented by formula (2), wherein formula (2) is n equations and n unknown effective radiations J i The effective radiation J of any i surface can be obtained by adopting an iterative method i Then the net radiant heat flux density q can be calculated according to equation (3) i The radiant heat flux density of the left and right surfaces of each strip steel unit can be obtained.
Wherein: sigma is Stefan-Boltzmann constant, ε i I surface darkness, T i I surface temperature, f ik Is the angular coefficient from i surface to k surface.
For the convection heat exchange of the strip steel and the furnace gas, the strip steel moves at a high speed in the furnace, belongs to forced convection heat exchange, the forced convection heat exchange coefficient of the strip steel and the furnace gas can be calculated according to the condition that the fluid is swept out of the flat plate, and then the convection heat exchange heat flow density of the surface of the strip steel unit can be obtained according to a Newton cooling formula, as shown in the formula (4).
q c ＝2h c (T g -T s ) (4)
Wherein q is c Heat flow density for convective heat exchange between the left and right surfaces of the strip steel unit and furnace gas is singleBit is W/m 2 ；h c The unit is W/(m) of the forced convection heat exchange coefficient between the furnace gas and the strip steel unit 2 ·K)，T g And T s Respectively representing the hearth temperature and the strip steel unit temperature of the region; and calculating the forced convection heat exchange coefficient of the furnace gas and the strip steel according to the Noevent standard number, wherein the forced convection heat exchange coefficient is shown in the following formula:
wherein h is the convective heat transfer coefficient in W/(m) 2 K); nu is the nuceltel number; lambda (lambda) f The heat conductivity coefficient is W/(m.K); l is the characteristic dimension, which refers to the length of the fluid flowing through the plate in m.
The calculation of the nucelal number in the formula (5) adopts an unused calculation formula according to different flow forms of the fluid in the boundary layer, and the calculation formula is as follows:
laminar flow region: nu=0.664 Re 1/2 Pr 1/3 Re<5×10 5 (6)
Turbulence zone: nu= (0.037 Re) 4/5 -850)Pr 1/3 5×10 5 ≤Re<10 7 (7)
Wherein Re is the Reynolds number,where u is the fluid velocity and v is the kinematic viscosity; pr is the Planet number. In addition, the qualitative temperature is the average value of the hearth area temperature of the area and the calculated strip steel unit temperature, and the shaping size L is the calculated strip steel unit length.
Step 1.6, based on the theory of heat transfer, carrying out heat balance relation calculation on each strip steel unit in turn, wherein the heat received by the strip steel unit is equal to the heat (the increment of self enthalpy) required by the temperature rise of the strip steel unit, and the endpoint temperature T of the strip steel unit can be calculated i+1 As shown in equation (8). Will calculate the latest value T i+1 If the difference is large compared to the previously assumed temperature value, this new temperature T is used i+1 Re-proceedingThe radiation heat exchange calculation of the closed areas at the two sides of the strip steel unit is repeated and iterated until the calculated temperatures of the two adjacent times are close enough (the allowable maximum temperature error is e). Meanwhile, considering that the downstream strip steel temperature used in the radiation heat exchange calculation is an assumed value, in the embodiment, after the total strip steel temperature distribution is calculated once, all the calculation is performed again by using the latest calculated value, the total strip steel temperature distribution is repeatedly and iteratively calculated until the total strip steel temperature distribution calculated twice is close enough, and the convergence standard of the iterative process is that the allowable maximum temperature error is e.
In this example, the maximum temperature error e is 0.1 ℃.
Wherein T is i And T i+1 The temperatures of the start point (i point) and the end point (i+1 point) of the ith strip steel unit respectively; q i The total received heat flux density of the left and right side surfaces of the ith strip steel unit is the sum of the radiation heat flux density and the convection heat flux density of the left and right side surfaces of the ith strip steel unit; ΔL i,i+1 The distance from the point i to the point i+1 on the ith strip steel unit; ρ s Is the density of the strip steel; c (C) s,i Taking the average temperature of the ith strip steel unit as the specific heat capacity of the ith strip steel unit to obtain the specific heat capacity; delta s For the thickness of the ith strip unit, u s Is the speed of the strip steel.
And 1.7, real-time measuring the temperature of strip steel running at high speed at the inlet and outlet of the heating section by installing infrared radiation pyrometers with quick response, real-time measuring the hot spot temperature of each row of radiant tubes, the temperature of a hearth and the like by adopting thermocouples to obtain actual measurement data of the temperature of the strip steel entering and exiting the furnace, the temperature of each row of radiant tubes, the temperature of the furnace, the speed of the strip steel (namely the speed of the strip steel), the specification of the strip steel and the like, and online correcting a calculation model of the temperature distribution of the whole strip steel of the heating section in real time by adopting a heat transfer inverse problem method, wherein the model parameters (such as blackness and the like of the strip steel) are subjected to self-learning correction so as to adapt to the change of actual furnace conditions. The heat transfer inverse problem method is to calculate the temperature of the furnace outlet according to the temperature distribution calculation model of the whole furnace strip steel of the heating section and compare the calculated temperature with the actual temperature of the furnace outlet so as to inversely calculate the parameter correction of the model.
And 1.8, realizing dynamic thermal process tracking based on an accurate heating section full-furnace belt steel temperature distribution calculation model. The method is characterized in that according to model input parameters measured in real time, including strip steel width, thickness and speed, strip steel temperature at the inlet of a heating section, radiant tube temperature of each row and furnace temperature of each region, the temperature distribution of the whole-furnace strip steel is predicted in real time in a certain time period, and the dynamic tracking of the strip steel temperature distribution change is realized.
By adopting the method, the embodiment aims at specific working conditions: steel grade: DC04, strip speed: 190m/min, strip width: 1470mm, strip thickness: 1.004mm, heating section inlet zone temperature 191 ℃, radiant tube AA row: 746 ℃, column AB: 797.5 ℃, AC column: 777 ℃, AD column: 748 ℃, AE column: 755 ℃, AF column: 691.5 ℃, AG column: 743.5 ℃, AH column: 808 ℃, column AJ: 814.5 ℃, AK column: 835.5 ℃, AL column: 811 ℃, AM column: 792.5 ℃, AN column: 707 ℃, AP column: 729.5 ℃, AQ columns: 770 ℃, AR column: 833 ℃, AS column: 790 ℃, AT column: 757.5 ℃, AV column: 903 ℃, AW column: 865 ℃, AX columns: 862 ℃, AY column: 870.5 ℃, AZ column: 918 ℃, BA column: 937 ℃, BB column: 851.5 ℃, BC column: 951 ℃, BD column: 951.5 ℃, BE column: 914.5 ℃, column BF: 935 ℃, BG column: 947 ℃, BH column: 809 ℃, furnace temperature Zone1:703 ℃, zone2:737 ℃, zone3:733 ℃, zone4:672 ℃, zone5:705 ℃, zone6:744 ℃, zone7:722 ℃, zone8:715 ℃, zone9:732 ℃, zone10:852 ℃, zone11:872 ℃, zone12:927 ℃, zone13:768 ℃, zone14:891 ℃, zone15:847 ℃; the calculated temperature of the strip steel at the outlet of the heating section is 837.65 ℃, and the temperature distribution of the whole furnace strip steel is shown in fig. 5.
And setting models for dynamic optimization of the temperatures of the radiant tubes in the second part and each row of the heating section. The model is established based on a heating section full-furnace band steel temperature distribution calculation and tracking model of the first part, and the on-site radiant tube temperature and furnace temperature set value parameters can be optimized through calculation of the model so as to improve the hit rate of the heating section outlet band steel temperature in the annealing temperature requirement range. In the calculation optimization of the normal working condition of the heating section, the most main types are as follows: and determining the speed of the strip steel, the temperature set value of the radiant tube and the furnace temperature set value by knowing the steel grade, the heat treatment process requirement and the strip steel specification, so that the unit yield is maximum. The essence of the model is that the strip steel temperature at the outlet of the heating section is dynamically optimized in the heat treatment temperature requirement range to the strip speed, the radiant tube temperature set value and the furnace temperature set value, namely the dynamic optimizing set model of the radiant tube temperature of each row of the heating section, and the model comprises the following sub-steps:
step 2.1, the radiant tube heating section is often a key furnace section for limiting the output of the whole continuous annealing unit, and the limit speeds of the strip steel with different specifications and different steel types in the furnace section are needed to be analyzed. Under the premise of specific band steel continuous heat treatment unit and radiant tube limit heating capacity, according to the band steel type, specification and the requirements of the heat treatment process of the temperature of the discharged band steel, calculating the limit speed (the highest speed allowed by the unit) by adopting a heating section band steel temperature distribution calculation model, as shown in figure 6, firstly assigning an initial value u to the band speed u 0 Setting a termination error epsilon, taking the maximum value according to the steel grade, width and thickness of the strip steel and the temperature of all the radiant tubes, and obtaining the temperature T of the strip steel from the furnace by using a heating section strip steel temperature distribution calculation model 1 Will T 1 And the lower limit T of the temperature treatment process required range of the tapping zone 2 Comparing, if 0.ltoreq.DeltaT=T is satisfied 1 -T 2 Less than epsilon, the limit belt speed u of the heating section of the radiant tube max Otherwise, the current strip speed needs to be increased or decreased by a small amount deltau, namely u=u±deltau, and then the current strip speed is brought into a heating section strip temperature distribution calculation model to calculate the temperature T of the discharged strip again 1 Until the condition 0.ltoreq.DeltaT=T is satisfied 1 -T 2 And (5) less than or equal to epsilon, calculating the limit belt speed, and stopping the program. In the embodiment of the invention, epsilon is 0.1 ℃, deltau is 1.0m/min
However, the limiting belt speed of the whole continuous annealing unit is limited by the requirements of other furnace sections, such as minimum overaging time required by overaging section process, so the limiting belt speed of the furnace section is the ratio of the expanding length of the furnace section to the minimum overaging time. The ultimate belt speed of the final unit should take the minimum value of the ultimate belt speeds of the heating section and other furnace sections of the radiant tube. The invention adopts the limit belt speed of the unit as the belt speed with maximized yield.
And 2.2, constructing a dynamic optimization setting model of the temperature of each row of radiant tubes of the heating section on the basis, as shown in fig. 7. The method comprises the following steps: first, the basic parameters of the model are set (step 1.2) and the desired strip temperature T of the outlet of the heating section is generated according to the theoretical annealing temperature profile of the known steel grade exp A set of radiant tube temperature probes is set. Then, all the temperature values are input into a heating section full-furnace band steel temperature distribution calculation model to calculate a heating section outlet band steel temperature predicted value T under the radiant tube heuristic value p . Second, according to the objective function Δt=t p -T exp <And eps, judging whether the temperature of each row of radiant tubes needs to be adjusted, if the temperature of each row of radiant tubes does not reach the condition of the objective function, adjusting the temperature of each row of radiant tubes by adopting the following formula, and if the objective function reaches the condition, obtaining the optimized value of the temperature of the radiant tubes. Where eps is the temperature error convergence criterion.
T i,tube ＝T i,tube -f*△T i＝1,2,...,31 (9)
Wherein T is i,tube And f is the temperature adjustment coefficient of the radiant tube, and DeltaT is the difference between the predicted value and the expected value of the temperature of the strip steel at the outlet of the heating section.
In this example, eps takes 0.5℃and the radiant tube temperature adjustment factor f takes 0.1, and the furnace temperature set point values for each zone are the radiant tube temperature set points in the row minus 50 ℃.
And 2.3, optimizing and selecting different strip steel heating modes meeting the requirements of the heat treatment process.
According to the dynamic optimization setting model of the temperature of each row of radiant tubes of the heating section, the outlet of the heating section is required to obtain the expected strip steel temperature, and various combinations of the set values of the temperature of each row of radiant tubes in the hearth of the heating section can meet the requirements, and the different combinations correspond to different strip steel heating modes. That is, to ensure that the temperature of the strip steel at the outlet of the heating section meets the requirement of the heat treatment process, a plurality of different strip steel heating modes exist, and different strip steel heating modes can be selected for calculation and optimization according to actual needs. The invention provides two typical strip steel heating modes meeting the requirements of a heat treatment process, and two modes exist in the combination of temperature set values of radiant tubes in each row of corresponding heating sections: the same pattern for each row of radiant tubes (heating pattern one) and the incremental pattern for each row of radiant tubes (heating pattern two). For the heating mode two, namely the temperature increment mode of each row of radiant tubes, the invention starts from the temperature of the radiant tubes of the first row, the temperature increment of each row is 15 ℃, until the temperature of one row of radiant tubes reaches the maximum value, and the temperature of the radiant tubes of the subsequent row is the maximum value.
In this embodiment, for a specific working condition: the steel grade is DC04, the annealing temperature of the outlet of the heating section is required to be 840 ℃, the actual measured temperature of the inlet of the heating section is 151 ℃, the width of the strip steel is 1800mm, the thickness of the strip steel is 1.0mm, the speed of the strip steel is 180m/min, the average wall temperature of the radiant tube can be heated to 950 ℃ at the highest, and the like. Under such conditions, the two strip heating modes proposed by the present invention, as shown in FIG. 8, correspond to the radiant tube and furnace temperature settings as shown in Table 1 below. The result shows that the temperature set value of each row of radiant tubes in the first heating mode is the same, the temperature is higher, the energy loss is larger compared with that of the radiant tubes in the second heating mode, and the production cost is obviously increased, but the method has the advantages that the time for the strip steel in the furnace to reach the recrystallization temperature is longer, so that the grain size of the annealed strip steel is larger than that of the strip steel in the second heating mode; and the heating mode II is very close to the theoretical annealing process curve, and the biggest advantage is energy saving and consumption reduction. Under the condition that the annealing structure and performance of the strip steel can meet the requirements, the heating mode II is more economical from the aspect of cost minimization. In the optimization, if the unit yield is to be maximized, the speed of the strip steel is calculated by taking the limit speed obtained in the step 2.1 to calculate the temperature set values of the radiant tube and the hearth.
Table 1 calculates optimized heating mode one and heating mode two corresponding radiant tube and furnace temperature setpoints
In summary, the optimization control method of the strip steel temperature in the dynamic heating process of the continuous annealing furnace can be popularized to accurate prediction, dynamic heat tracking and real-time visualization of the strip steel temperature in any continuous annealing furnace and various different working conditions, so that the accurate temperature control of a heating section, active optimization and dynamic customization of a strip steel heating mode are realized, and the optimization control method has important significance for optimizing the process and operation in the actual production process, improving the hit rate of the strip steel temperature at the outlet of the heating section in the annealing temperature requirement range, saving energy, reducing cost, enhancing efficiency and the like.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (8)
1. An optimization control method for the temperature of strip steel in the dynamic heating process of a continuous annealing furnace is characterized by comprising the following steps:
s1: constructing a heating section full-furnace band steel temperature distribution calculation model, determining basic parameters and solution conditions of model design, and adopting a heat transfer inverse problem method to correct the heating section full-furnace band steel temperature distribution calculation model on line;
Said step S1 comprises the sub-steps of:
s11: aiming at the structure, process, equipment and automatic control system of the dynamic heating process of the actual continuous strip steel annealing furnace, the arrangement and structure size of radiant tubes in the heating section, the length and quantity of the strip channels, the specification and steel grade of strip steel products, the process speed, the internal material of furnace walls and the heat transfer characteristics are determined;
s12: setting relevant basic parameters of a heating section strip steel temperature distribution calculation model, wherein the relevant basic parameters comprise strip steel, radiant tube and furnace wall blackness, strip steel density and strip steel specific heat capacity;
s13: dividing the heating section into a plurality of closed calculation areas and strip steel units according to the arrangement of the radiant tubes of the heating section and the hearth structure;
s14: an initial temperature profile X is assumed along the length of the strip p Initializing the temperature distribution of the full-furnace band steel of the heating section, namely T p '＝X p Wherein p=0,1, 2..p+1 points, T were co-discrete on the heating section full furnace strip steel p ' is the initialized temperature distribution of the full furnace band steel of the heating section;
s15: for each strip unit i, a heat flux density calculation is performed, where i=1, 2;
s16: based on theory of heat transfer, carrying out heat balance relation calculation on each strip steel unit in turn, wherein the heat received by the strip steel unit is equal to the heat required by the strip steel unit to heat, and calculating to obtain the endpoint temperature T of the strip steel unit i+1 The following formula is shown:
wherein T is i And T i+1 The temperatures of the starting point and the end point of the ith strip steel unit are respectively, wherein the starting point of the ith strip steel unit is i point, and the end point is i+1 point; q i The total received heat flux density of the left and right side surfaces of the ith strip steel unit is the sum of the radiation heat flux density and the convection heat flux density of the left and right side surfaces of the ith strip steel unit; ΔL i,i+1 The distance from the point i to the point i+1 on the ith strip steel unit; ρ s Is the density of the strip steel; c (C) s,i Taking the average temperature of the ith strip steel unit as the specific heat capacity of the ith strip steel unit to obtain the specific heat capacity; delta s For the thickness of the ith strip unit, u s The speed of the strip steel is the speed of the strip steel;
s17: the method comprises the steps of measuring strip steel temperatures of high-speed operation at an inlet and an outlet of a heating section in real time through infrared radiation pyrometers, measuring hot spot temperatures and hearth temperatures of all rows of radiant tubes in real time through thermocouples to obtain actual measurement data of the inlet and outlet strip temperatures, the temperatures of all rows of radiant tubes, the furnace temperatures, the strip steel speeds and strip steel specifications, correcting a heating section full-furnace strip steel temperature distribution calculation model on line in real time through a heat transfer inverse problem method, and performing self-learning correction on model parameters to adapt to the change of actual furnace conditions, wherein the heat transfer inverse problem method refers to comparing the calculated outlet strip temperatures according to the heating section full-furnace strip steel temperature distribution calculation model with the actual measured strip temperatures so as to inversely calculate model parameter correction;
S18: according to the model input parameters measured in real time, including the width, thickness and speed of the strip steel, the temperature of the strip steel at the inlet of the heating section, the temperature of each row of radiant tubes and the temperature of each region, the temperature distribution of the whole-furnace strip steel is predicted in real time in a certain time period, and the dynamic tracking of the temperature distribution change of the strip steel is realized;
s2: constructing a dynamic optimizing setting model of the temperature of each row of radiant tubes of the heating section, optimizing and selecting different heating modes meeting the requirements of a heat treatment process;
said step S2 comprises the sub-steps of:
s21: analyzing the limit speeds of the strip steel with different specifications of different steel grades of the heating section, namely calculating the limit speed by adopting a heating section strip steel temperature distribution calculation model according to the strip steel grade, specification and strip steel temperature heat treatment process requirements of a discharging furnace on the premise of the limit heating capacity of a specified strip steel continuous heat treatment unit and a radiant tube;
s22: constructing a dynamic optimizing setting model of the temperature of each row of radiant tubes of the heating section;
s23: and when the temperature of the strip steel at the outlet of the heating section meets the heat treatment process requirement, a plurality of different strip steel heating temperature rising modes exist, and different strip steel heating modes are selected for calculation and optimization according to actual needs.
2. The method for optimally controlling the temperature of strip steel in the dynamic heating process of a continuous annealing furnace according to claim 1, wherein the method comprises the following steps: in the step S13, the closed calculation areas are divided into two types, the first is an area containing the radiant tube and the second is an area not containing the radiant tube, and each closed calculation area is composed of a left-side strip surface, a right-side strip surface, a radiant tube surface, a furnace wall and a plurality of imaginary planes.
3. The method for optimally controlling the temperature of strip steel in the dynamic heating process of a continuous annealing furnace according to claim 2, wherein the method comprises the following steps: in the step S14, the initialized temperature distribution of the full-furnace band steel in the heating section uses temperature data of the corresponding position on a theoretical annealing temperature curve, wherein the theoretical annealing temperature curve refers to a linear heating curve from the entering temperature to the expected exiting temperature of the band steel.
4. The optimization control method for the strip steel temperature in the dynamic heating process of the continuous annealing furnace according to claim 3, wherein the optimization control method comprises the following steps: in the step S15, the heat flux density received by each strip steel unit includes a radiant heat flux density, that is, the net radiant heat exchange amount of the left and right surfaces of the strip steel unit, and a convection heat flux density, that is, the convection heat exchange amount between the furnace gas and the strip steel unit;
the radiation heat flow density calculation needs to be carried out according to the divided closed calculation areas on the left side and the right side of the strip steel unit, and the radiation heat exchange calculation of each closed calculation area is carried out, wherein the calculation process is as follows:
s1501: determining how many surfaces the closed computing area shares to form a closed radiation heat exchange system, and recording the number of the surfaces as n;
S1502: calculating the radiation heat exchange angle coefficient f between every two surfaces in the closed calculation area by Monte Carlo method ik Then the effective radiation J of the i surface i Represented by the formula:
wherein sigma is Stefan-Boltzmann constant, epsilon i I surface darkness, T i I surface temperature, f ik An angular coefficient from i surface to k surface;
the above equation is n equations and n unknown effective radiations J i The effective radiation J of any i surface can be obtained by adopting an iterative method i ；
S1503: calculating the net radiant heat flux density q according to i And then the radiant heat flux density of the left surface and the right surface of each strip steel unit can be obtained:
the calculation process of the convection heat flux density is as follows:
s1511: calculating the forced convection heat exchange coefficient of the strip steel unit and the furnace gas according to the condition that the fluid is sweeped outside the flat plate, and calculating the forced convection heat exchange coefficient of the furnace gas and the strip steel according to the Noevent standard number, wherein the forced convection heat exchange coefficient is shown in the following formula:
wherein h is a convective heat transfer coefficient; nu is the nuceltel number; lambda (lambda) f Is the heat conductivity coefficient; l is the characteristic dimension, which refers to the length of fluid flowing through the plate;
s1512: and (3) obtaining the convection heat flux density of the surface of the strip steel unit according to a Newton cooling formula:
q c ＝2h c (T g -T s )
wherein q is c The heat flux density is the heat convection between the left and right surfaces of the strip steel unit and the furnace gas; h is a c Is the forced convection heat exchange coefficient between furnace gas and strip steel unit, T g And T s The furnace temperature and the strip steel unit temperature of the region are respectively indicated.
5. The method for optimally controlling the temperature of strip steel in the dynamic heating process of a continuous annealing furnace according to claim 4, wherein the method comprises the following steps: in said step S16, the latest calculated value T i+1 If the difference is large, i.e. the difference exceeds the maximum temperature error e, compared to the previously assumed temperature value, this new temperature T is used i+1 Carrying out radiation heat exchange calculation on the closed areas at two sides of the strip steel unit again, and repeating iterative calculation until the calculated temperatures of two adjacent times are close enough, namely, the difference value is within the range of the maximum temperature error e; meanwhile, taking into consideration that the downstream strip steel temperature used in the radiation heat exchange calculation adopts an assumed value, after the temperature distribution of the whole strip steel is calculated once, carrying out all the calculation again by using the latest calculated value, and repeatedly and iteratively calculating the whole stripThe steel temperature profile, until the two adjacent calculated full-band steel temperature profiles are close enough, is the allowable maximum temperature error e.
6. The method for optimally controlling the temperature of the strip steel in the dynamic heating process of the continuous annealing furnace according to claim 5, wherein the method comprises the following steps: in the step S21, the limit speed of the strip is calculated as follows:
S211: giving an initial value u to the speed u of the strip steel 0 And sets a termination error epsilon;
s212: taking the maximum value according to the steel grade, width and thickness of the strip steel and the temperature of all the radiant tubes, and obtaining the temperature T of the furnace strip steel by using a heating section strip steel temperature distribution calculation model 1 ；
S213: will T 1 And the lower limit T of the temperature treatment process required range of the tapping zone 2 Comparing, if 0.ltoreq.DeltaT=T is satisfied 1 -T 2 Less than epsilon, the limit belt speed u of the heating section of the radiant tube max Otherwise, the current strip speed is increased by a small amount deltau, namely u=u+/-deltau, and then the current strip speed is brought into a heating section strip temperature distribution calculation model to calculate the temperature T of the furnace strip again 1 Until the condition 0.ltoreq.DeltaT=T is satisfied 1 -T 2 Less than or equal to epsilon, and further solving the limit speed of the strip steel;
s214: the limit speed of the strip steel of the whole continuous annealing unit is limited by the requirements of other furnace sections, including the minimum overaging time required by the overaging section process, and the limit speed of the strip steel of the overaging section is the ratio of the expansion length of the furnace section to the minimum overaging time; the strip steel limit speed of the final unit is the minimum value of the strip steel limit speeds of the heating section and the overaging section of the radiant tube.
7. The method for optimally controlling the temperature of strip steel in the dynamic heating process of a continuous annealing furnace according to claim 6, wherein the method comprises the following steps: in the step S22, the specific process of constructing the dynamic optimization setting model of the temperature of each row of radiant tubes in the heating section is as follows:
S221: setting relevant basic parameters of a dynamic optimization setting model of the temperature of each row of radiant tubes of the heating section, wherein the relevant basic parameters comprise strip steel, blackness of radiant tubes and furnace walls, strip steel density and strip steel specific heat capacity;
s222: generating the desired strip temperature T of the outlet of the heating section according to the theoretical annealing temperature profile of the known steel grade exp Setting a group of radiant tube temperature heuristic values of each row;
s223: inputting the temperature heuristic values of each row of radiant tubes into a heating section full-furnace strip steel temperature distribution calculation model, and calculating a heating section outlet strip steel temperature predicted value T under the radiant tube heuristic values p ；
S224: according to the objective function Δt=t p -T exp <eps, judging whether the temperature of each row of radiant tubes needs to be adjusted, and if the temperature of each row of radiant tubes does not reach the objective function condition, adjusting the temperature of each row of radiant tubes by adopting the following steps:
T i,tube ＝T i,tube -f*△T
wherein T is i,tube The temperature of the radiant tube in the ith row is f, the temperature adjustment coefficient of the radiant tube is f, and DeltaT is the difference between the predicted value and the expected value of the temperature of the strip steel at the outlet of the heating section;
and if the objective function reaches the condition, obtaining the temperature optimized value of the radiant tube, wherein eps is a temperature error convergence standard.
8. The method for optimally controlling the temperature of strip steel in the dynamic heating process of a continuous annealing furnace according to claim 7, wherein the method comprises the following steps: in the step S23, the strip steel heating and heating mode includes a mode in which the temperatures of the radiant tubes in each row are the same and a mode in which the temperatures of the radiant tubes in each row are increased, wherein the mode in which the temperatures of the radiant tubes in each row are the same, i.e., the radiant tubes in each row are heated at the same temperature, the mode in which the temperatures of the radiant tubes in each row are increased, i.e., the first radiant tube temperature in each row is started, and the temperature increases of the radiant tubes in each row are the same until the temperature of the radiant tubes in a certain row reaches a maximum value, and the temperatures of the radiant tubes in the subsequent rows are all the maximum value.
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