CN106906351B - A kind of board briquette forecasting model and optimum furnace method - Google Patents
A kind of board briquette forecasting model and optimum furnace method Download PDFInfo
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- CN106906351B CN106906351B CN201710075219.1A CN201710075219A CN106906351B CN 106906351 B CN106906351 B CN 106906351B CN 201710075219 A CN201710075219 A CN 201710075219A CN 106906351 B CN106906351 B CN 106906351B
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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
- C21D9/70—Furnaces for ingots, i.e. soaking pits
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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 a kind of board briquette forecasting model and optimum furnace methods, belong to metallurgical automation process control field.The optimum furnace method includes: using Preform surface temperature and the minimum objective function as optimum furnace control of furnace superintendent institute's envelope surface product, using the maximum difference of the maximum section temperature difference of blank, maximum heating rate, blank tapping temperature and target tapping temperature and furnace temperature bound as constraint condition, optimizing is carried out using heuristic power genetic algorithm, furnace temperature Optimal Distribution curve is exported, so that the energy consumption of heating furnace reaches minimum.The board briquette forecasting model, the influence that water beam exchanges heat to slab is taken into account, so that the slab heating curve that model is calculated is more nearly with measured value, can play accurate temperature forecast, improve the heating quality of slab.
Description
Technical field
The present invention relates to metallurgical automation process control fields, specifically, in particular to a kind of board briquette forecasting model
And optimum furnace method.
Background technique
With China market expanding economy, iron and steel enterprise is in the national economic development in occupation of more and more important position
It sets.Steel and iron industry is the rich and influential family of energy consumption, therefore the energy-saving and emission-reduction work being unfolded to steel and iron industry becomes more and more important.Add
Hot stove is one of production line key equipment in steel and iron industry steel rolling mill, is main energy consumption equipment in steel and iron industry, improves heating
Furnace thermal efficiency reduces the energy consumption that steel and iron industry can be greatly reduced in furnace energy consumption.
The main target of Heating Furnace Control is the real-time control to furnace temperature, mainly according to slab in heating furnace heated
Profiling temperatures in journey are controlled.It is with reasonable heating cycle heating plate to the purpose that furnace temperature optimizes control
Base reaches the required Temperature Distribution of rolling, to improve steel product quality after so that it is come out of the stove.But due in actual production
It cannot achieve the real-time detection of board briquette in journey, therefore establish accurate board briquette forecasting model for the furnace temperature of heating furnace
Real-time control seems particularly important.With the innovation of technology, the theoretical research about slab heating temperature control emerges one after another, furnace
The effect that the theoretical research that temperature automatically controls also has reached quite high degree, but applied in actual production process is not very
It is ideal.Many stoves have second control system, but since the result that second level mathematical model calculates is inaccurate, lead to very great Cheng
Degree is still to carry out Control for Kiln Temperature manually by operative employee.
Currently, to the research method of slab temperature prediction model in heating furnace, mainly including the use of computational fluid dynamics
CFD in heating furnace temperature field carry out analogue simulation method and by the basic mathematical physical equation to Slab Heat into
The method of row numerical solution.CFD approach is mainly used for the steady-state process of description heating temperature field in furnace, velocity field, and numerical value side
Method can be used for predicting the heating process of slab in heating furnace.The existing temperature forecast mould to slab heating process in heating furnace
The research of type usually has ignored the influence that water beam is distributed board briquette, so that the slab that temperature prediction model obtains is heating
Heating curve and measured value in furnace have relatively large deviation.
Summary of the invention
In view of the foregoing, it is an object to a kind of board briquette forecasting model and optimum furnace method are provided, it is right
Furnace temperature optimizes control in heating furnace, obtains optimal furnace curve, improves operation efficiency, reduces energy consumption, and in plate
In base temperature prediction model, it is contemplated that influence of the water beam to heating of plate blank, to solve obtained heating of plate blank process heating curve
And the larger problem of measured value deviation.
To achieve the goals above, the following technical solution is employed by the present invention:
Optimum furnace method of the present invention, comprising: input blank and heating furnace relevant parameter are minimum as furnace using energy consumption
The objective function of warm optimal control, and determine constraint condition, optimizing is carried out using heuristic power genetic algorithm, exports optimal furnace
Warm distribution curve.
Preferably, objective function is minimum for Preform surface temperature and heating furnace furnace superintendent institute's envelope surface product,
In formula, J is objective function；L is heating furnace furnace superintendent, m；TsIt (l) is surface temperature of the blank at a length of l of heating-furnace
Degree, DEG C；
Wherein, constraint condition includes: the maximum section temperature difference, the blank tapping temperature of the maximum heating rate of blank, blank
With the maximum difference and furnace temperature upper and lower limit of target tapping temperature；
Blank and heating furnace relevant parameter include: blank material specification, charging temperature, tapping temperature, rhythm of production, heating
Furnace furnace superintendent, the position Shui Liang, thermocouple location, heating time.
Preferably, heuristic power genetic algorithm the following steps are included:
(1) initial population is generated at random；
(2) judge whether to meet iteration stopping condition, if satisfied, then exporting furnace；If not satisfied, then carrying out step
(3)；
(3) stochastical sampling chooses two parents；
(4) heuristic intersection generates two filial generations；
(5) furnace curve is calculated；
(6) blank heat flow density and temperature field are calculated；
(7) evaluation, father and son compete sequence and generate new population；
(8) new individual is generated based on fitness difference duplicate checking；
(9) judge whether the number of iterations for reaching setting, if not up to setting the number of iterations, is back to step (2), if
Reach setting the number of iterations, then directly exports.
A kind of board briquette forecasting model based on above-mentioned optimum furnace method of the present invention, including,
Walking beam is distributed in heating furnace, and is provided with water beam in walking beam,
Computational domain is chosen, and water beam is included in by computational domain, it is contemplated that the influence that water beam heats up to slab in furnace；
Establish the two-dimension unsteady heat conduction differential equation thermally conductive inside slab；
Boundary condition is set:
Slab upper surface uses comprehensive heat flow density boundary condition,
Third boundary condition is used at slab lower surface and water beam shoe contact position,
Slab lower surface other positions use comprehensive heat flow density boundary condition,
In formula,For heat flow density, W/m2；σ is Boltzmann constant, 5.67 × 10-8W/(m2·K4)；φCFFor blanket heat
Absorptivity；H is the coefficient of heat transfer, W/ (m2·K)；TfFor furnace temperature, K；TsFor steel slab surface temperature, K；TwFor the water temperature in water beam, K；
Adiabatic boundary condition is used at left and right sides of computational domain；
Solve equation.
Further, when carrying out grid dividing to computational domain, to net at slab lower surface and water beam shoe contact position
Lattice are encrypted, the proportional loose grid of other positions.
Further, the above fictitious emissivity method of lower hearth and slab is measured by black box experiment to contact with water beam
When the coefficient of heat transfer.
Compared with prior art, the present invention has the following advantages and beneficial effects:
One, the present invention is using Preform surface temperature and the minimum target letter as optimum furnace control of furnace superintendent institute's envelope surface product
Number, with the maximum difference of the maximum section temperature difference of blank, maximum heating rate, blank tapping temperature and target tapping temperature and
Furnace temperature bound carries out optimizing as constraint condition, using heuristic power genetic algorithm, and it is bent finally to obtain optimal furnace
Line, so that the energy consumption of heating furnace reaches minimum.
Two, the present invention is based on the board briquette forecasting model of optimum furnace method, the influence that water beam exchanges heat to slab is examined
Including worry, so that the slab heating curve that model is calculated is more nearly with measured value, accurate temperature forecast can be played,
Improve the heating quality of slab.
Detailed description of the invention
Fig. 1 is optimum furnace method of the present invention；
Fig. 2 is the flow diagram of heuristic power genetic algorithm of the present invention；
Fig. 3 is board briquette forecasting model schematic diagram of the present invention.
Specific embodiment
Now in conjunction with attached drawing, the present invention is described further, in order to which the present invention is more clear and should be readily appreciated that.
Fig. 1 is optimum furnace method of the present invention.As shown in Figure 1, optimum furnace method includes:
Blank and heating furnace relevant parameter are inputted, using the minimum objective function controlled as optimum furnace of energy consumption, and is determined
Constraint condition carries out optimizing using heuristic power genetic algorithm, exports optimal furnace curve.
Wherein, blank and heating furnace relevant parameter include: blank material specification, charging temperature, tapping temperature, production section
It plays, heating furnace furnace superintendent, the position Shui Liang, thermocouple location, heating time；Objective function is Preform surface temperature and heating furnace furnace superintendent
Institute's envelope surface product is minimum；Constraint condition includes: the maximum section temperature difference, the blank tapping temperature of the maximum heating rate of blank, blank
With the maximum difference and furnace temperature upper and lower limit of target tapping temperature；
Specific statement are as follows:
In formula, J is objective function；L is heating furnace furnace superintendent, unit m；TsIt (l) is table of the blank at a length of l of heating-furnace
Face temperature, unit DEG C；
Constraint condition statement are as follows:
a)
b)Ts(t)-Tc(t)≤ΔTs(max)
c)|Ts(tn)-Ta|≤ΔT
d)Tfmin(ti)≤Tf(ti)≤Tfmax(ti)
In formula, TsFor Preform surface temperature, unit DEG C；TcFor blank central temperature, unit DEG C；TfFor furnace temperature, unit DEG C；t
The heating time for being blank in furnace, unit s；For the maximum heating rate of blank, unit DEG C/s；ΔTs(max)For base
The maximum section temperature difference of material, unit DEG C；TaFor blank target tapping temperature, unit DEG C；TfminAnd TfmaxThe respectively lower limit of furnace temperature
And ceiling temperature, unit DEG C；Δ T is the maximum difference of blank tapping temperature and target tapping temperature, unit DEG C；
Wherein, the surface temperature of blank at this moment is calculated by the Preform surface temperature and the furnace temperature at this moment of previous moment
It obtains, it is specific to state are as follows:
Ts(t+ Δ t)=F (Ts(t),Tf(t+Δt))
Fig. 2 is the flow diagram of heuristic power genetic algorithm of the present invention.As shown in Fig. 2, heuristic power genetic algorithm
The following steps are included:
(1) initial population is generated at random；
(2) judge whether to meet iteration stopping condition, if satisfied, then exporting furnace；If not satisfied, then carrying out step
(3)；
(3) stochastical sampling chooses two parents；
(4) heuristic intersection generates two filial generations；
(5) furnace curve is calculated；
(6) blank heat flow density and temperature field are calculated；
(7) evaluation, father and son compete sequence and generate new population；
(8) new individual is generated based on fitness difference duplicate checking；
(9) judge whether the number of iterations for reaching setting, if not up to setting the number of iterations, is back to step (2), if
Reach setting the number of iterations, then directly exports.
Embodiment one
In conjunction with certain domestic 2250 rolling line 2# bar plate heating stove case history of steel mill, optimum furnace method of the present invention is done
It further illustrates.Wherein, 2250 rolling line 2# bar plate heating stoves are five sections of walking beam reheating furnaces, are divided into heat-recovery section, preheating section, add
One section of heat, heating two sections and soaking zone.
The parameters such as material, specification, charging temperature, the rhythm of production of slab according to heating furnace production are as optimum furnace
Input item, optimum furnace curve is as output item.The area minimum that furnace superintendent and steel slab surface temperature are surrounded is as target
Function, by the maximum section temperature difference, maximum heating rate, tapping temperature and target tapping temperature maximum difference and furnace temperature bound
As constraint condition, oven temperature profile is optimized using heuristic power operator.
For heating the slab of two kinds of different-thickness, slab thickness is respectively 180mm and 230mm, and identical plate is arranged
Base charging temperature is 20 DEG C, and slab tapping temperature is 1250 DEG C, and it is as follows to obtain each heating furnace section Temperature Distribution:
The heat exchanging process of slab in heating furnace is the factors such as furnace gases flowing towa taud and combustion heat release, radiant heat exchange
Coupling, since furnace flame temperature and furnace gas temperature are very high, radiant heat exchange is occupied an leading position.For being heated in furnace
Slab, for temperature-rise period in addition to being influenced by furnace temperature, water beam can also have an impact it.Therefore, in plate of the present invention
In base temperature prediction model, also water beam and the heat exchange at slab contact position are taken into account.Fig. 3 is slab temperature of the present invention
Spend forecasting model schematic diagram.Walking beam is distributed in heating furnace, and is provided with water beam 1 in walking beam, the computational domain of selection will
Water beam 1 is included in, it is contemplated that the influence that water beam heats up to slab in furnace.
Shown in Fig. 3, slab upper and lower surfaces are heated in furnace, and at 1 position of water beam in walking beam, slab is by two
The transmitting of aspect heat.A part from contacted with water beam 1 when, the heat exchange between slab and water beam 1.Another part is slab
When being detached from water beam 1, the heat convection between slab and air.
The board briquette forecasting model makes simplification to model, it is assumed that item using the mathematical model of two-dimension unsteady state
Part are as follows:
A) furnace temperature is distributed in piecewise linearity, is the function along furnace superintendent directional spreding；
B) furnace gas and slab heat convection and radiation heat transfer are comprehensive heat flow density boundary condition；
C) in heat exchanging process, ignore the influence of slab iron scale；
D) slab uniform motion in furnace in heating process.
The two-dimension unsteady heat conduction differential equation thermally conductive inside slab is established, it is specific to state are as follows:
In formula, ρ indicates the density of slab, unit K g/m3；Cp indicates the specific heat of slab, unit J/ (kg DEG C)；T is indicated
Board briquette, unit DEG C；T indicates time, unit s；λ indicates slab thermal coefficient, unit W/ (m DEG C).
It is as follows that boundary condition is set:
A) assume that upper and lower burner hearth fictitious emissivity method is identical in same furnace section；
B) slab upper surface uses comprehensive heat flow density boundary condition,
C) third boundary condition is used at slab lower surface and water beam shoe contact position,
Slab lower surface other positions use comprehensive heat flow density boundary condition,
In formula,For heat flow density, unit W/m2；σ is Boltzmann constant, 5.67 × 10-8W/(m2·K4)；φCFIt is total
Include thermal absorptivity；H is the coefficient of heat transfer, unit W/ (m2·K)；TfFor furnace temperature, unit K；TsFor steel slab surface temperature, unit K；Tw
For the water temperature in water beam, unit K；
D) adiabatic boundary condition is used at left and right sides of computational domain.
When carrying out grid dividing to computational domain, grid is added at slab lower surface and water beam shoe contact position
It is close, the proportional loose grid of other positions.
The two-dimentional Heat Conduction Differential Equations established to mesh point are become using Iterative alternate differential reduced equation to three
Angular moment battle array is simultaneously solved with chasing method.
The heat exchange when fictitious emissivity method and slab for measuring upper lower hearth by black box experiment are contacted with water beam 1
Coefficient h.
Embodiment two
In conjunction with the country, certain 2250 rolling line 2# heating furnace case history of steel mill does board briquette forecasting model of the present invention
It further illustrates.2250 rolling line 2# heating furnaces be five-part form walking beam reheating furnace, be divided into heat-recovery section, preheating section, heating one section,
Heat two sections and soaking zone.
Heating furnace effective length is 59m, is distributed 6 fixed beams in preheating section and bringing-up section and 4 walking beams, soaking zone are solid
Determine beam invariable number, but dislocation 42cm occurs for the position Shui Liang.When choosing computational domain, fully takes into account water beam and slab is added
The influence of heat has selected all to include the position of water beam before and after soaking zone as computational domain.
In computational domain grid dividing, closeer grid dividing is all made of at the position for having water beam 1, other positions use
Proportional density divides.Two-dimentional Heat Conduction Differential Equations are established to each control volume using volume control technique, using alternately implicit
The method of difference simplifies the differential equation, it is made to meet positive triangle matrix, is solved using TDMA method.
When handling boundary condition, slab upper surface is using comprehensive heat flow density boundary condition, slab lower surface and Shui Liang
Third boundary condition is used at shoe contact position, slab lower surface other positions use comprehensive heat flow density boundary condition,
The left and right sides uses adiabatic boundary condition.Due to being walking beam furnace, it is all that walking beam and slab time of contact account for entire stepping
The 1/4 of phase, so the heat flow density in walking beam position is to consist of two parts, a part is plate when slab and walking beam contact
Heat exchange between base and water beam, heat exchange when another part is slab disengaging walking beam between furnace gas.
Black box is installed in milling train side, obtains the blanket heat of upper and lower burner hearth using black box experiment and by data processing
Coefficient of heat transfer when absorptivity and slab and water beam contact.In order to obtain accurate parameter value, when experimental designs, root
According to the position distribution of water beam and the position distribution of thermocouple, take 21 points as testing site on slab.
The above description is only a preferred embodiment of the present invention, is not intended to restrict the invention, for those skilled in the art
For member, the invention may be variously modified and varied.All within the spirits and principles of the present invention, it is made it is any modification,
Equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.
Claims (6)
1. a kind of optimum furnace method characterized by comprising input blank and heating furnace relevant parameter, with the minimum work of energy consumption
For the objective function of optimum furnace control, the objective function is minimum for Preform surface temperature and heating furnace furnace superintendent institute's envelope surface product,
In formula, J is objective function；L is heating furnace furnace superintendent, m；TsIt (l) is surface temperature of the blank at a length of l of heating-furnace,
DEG C,
And determine constraint condition, and optimizing is carried out using weighting heuristic genetic algorithms, exports optimal furnace curve, it is described
Weight heuristic genetic algorithms the following steps are included:
(1) initial population is generated at random；
(2) judge whether to meet iteration stopping condition, if satisfied, then exporting furnace；If not satisfied, then carrying out step (3)；
(3) stochastical sampling chooses two parents；
(4) heuristic intersection generates two filial generations；
(5) furnace curve is calculated；
(6) blank heat flow density and temperature field are calculated；
(7) evaluation, father and son compete sequence and generate new population；
(8) new individual is generated based on fitness difference duplicate checking；
(9) judge whether the number of iterations for reaching setting, if not up to setting the number of iterations, is back to the step (2), if
Reach setting the number of iterations, then directly exports.
2. optimum furnace method according to claim 1, which is characterized in that the constraint condition includes: the maximum of blank
Heating rate, the maximum section temperature difference of blank, blank tapping temperature and the maximum difference and furnace temperature of target tapping temperature are upper and lower
Limit.
3. optimum furnace method according to claim 1, which is characterized in that the blank and heating furnace relevant parameter packet
Include: blank material specification, tapping temperature, rhythm of production, heating furnace furnace superintendent, the position Shui Liang, thermocouple location, adds charging temperature
The hot time.
4. a kind of board briquette forecasting procedure based on optimum furnace method described in claim 1, is distributed with work in heating furnace
Beam is moved, is provided with water beam in the walking beam, which is characterized in that
Computational domain is chosen, the water beam is included in by the computational domain；
Establish the two-dimension unsteady heat conduction differential equation thermally conductive inside slab；
Boundary condition is set:
Slab upper surface uses comprehensive heat flow density boundary condition,
Third boundary condition is used at slab lower surface and water beam shoe contact position,
Slab lower surface other positions use comprehensive heat flow density boundary condition,
In formula,For heat flow density, W/m2；σ is Boltzmann constant, 5.67 × 10-8W/(m2·K4)；φCFTo sum up heat absorption
Rate；H is the coefficient of heat transfer, W/ (m2·K)；TfFor furnace temperature, K；TsFor steel slab surface temperature, K；TwFor the water temperature in water beam, K；
Adiabatic boundary condition is used at left and right sides of computational domain；
Solve equation.
5. board briquette forecasting procedure according to claim 4, which is characterized in that carry out grid dividing to the computational domain
When, grid is encrypted at slab lower surface and water beam shoe contact position, the proportional loose grid of other positions.
6. board briquette forecasting procedure according to claim 4, which is characterized in that measure furnace up and down by black box experiment
The coefficient of heat transfer when fictitious emissivity method and slab and water beam of thorax contact.
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| CN110231840B (en) * | 2019-06-05 | 2020-12-01 | 重庆赛迪热工环保工程技术有限公司 | Control method for black print temperature difference of water beam of steel billet in walking beam type heating furnace |
| CN110438318B (en) * | 2019-07-22 | 2020-11-24 | 中南大学 | Low-energy-consumption fastest heating control method and system for large vertical quenching furnace |
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| CN113191080B (en) * | 2021-04-26 | 2024-02-09 | 辽宁省交通高等专科学校 | Heating furnace billet temperature field prediction model optimization method based on HMPSO algorithm |
| CN115011786A (en) * | 2022-04-19 | 2022-09-06 | 北京科技大学 | Furnace temperature optimization method and device for dynamically sensing working condition of heating furnace |
| CN115065710B (en) * | 2022-04-29 | 2023-07-25 | 燕山大学 | Intelligent temperature control PC end and mobile end remote cloud measurement and control system of heating furnace |
| CN115109918B (en) * | 2022-05-13 | 2023-06-13 | 燕山大学 | Furnace temperature regulation and control method based on double-coupling target heating curve of heating furnace |
| CN115121631B (en) * | 2022-05-13 | 2023-05-12 | 燕山大学 | Temperature control method based on heating furnace blank temperature and furnace temperature cooperative pre-control partition decoupling |
| CN115096106B (en) * | 2022-07-01 | 2023-04-18 | 燕山大学 | Multi-target progressive optimization and early warning method for heating furnace |
| CN115828624B (en) * | 2022-12-21 | 2023-06-27 | 北京科技大学 | Slab heating temperature accurate forecasting method based on black box experiment tuning |
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