CN110257577A - A kind of pebble stove burns furnace course control method for use and system - Google Patents
A kind of pebble stove burns furnace course control method for use and system Download PDFInfo
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- CN110257577A CN110257577A CN201910642705.6A CN201910642705A CN110257577A CN 110257577 A CN110257577 A CN 110257577A CN 201910642705 A CN201910642705 A CN 201910642705A CN 110257577 A CN110257577 A CN 110257577A
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B9/00—Stoves for heating the blast in blast furnaces
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B2300/00—Process aspects
- C21B2300/04—Modeling of the process, e.g. for control purposes; CII
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Abstract
The invention discloses a kind of pebble stoves to burn furnace course control method for use and system, by being based on hot blast stove burning historical data, matching obtains optimal air-fuel ratio, according to gas-particle two-phase heat transfer and process structure in furnace, establish chamber of hot-blast stove diesel engine, based on chamber of hot-blast stove diesel engine, establish temperature prediction model, temperature prediction model includes dome temperature prediction model and exhaust gas temperature prediction model and based on temperature prediction model, the optimal control parameter of control hot blast stove burning process is obtained in real time, it solves the prior art and is difficult to the technical issues of real-time and precise control is carried out to hot blast stove burning process, furnace process is burnt by analysis pebble stove, air-fuel ratio is controlled from data Angle according to site technique, gas flow is controlled from mechanistic point, make the two while being optimal, and combine matched optimal air-fuel ratio To the real-time optimizing of best gas flow, it can be achieved that the real-time and precise to hot blast stove burning process controls.
Description
Technical field
The present invention relates to converter steeling technology field, in particular to a kind of pebble stove burns furnace course control method for use and is
System.
Background technique
Hot-blast stove is the key equipment in blast fumance technique, and it is raw that the hot blast temperature and duration provided directly affects blast furnace
It produces.The work of pebble stove cycle period, within a duty cycle, is broadly divided into combustion phases and air-supply stage.Burning rank
By a certain percentage in combustion chambers burn, the flue gas for generation of burning flows through regenerative chamber for heat-storing sphere for section, blast furnace gas and combustion air
Heating makes its accumulation of heat, is then flowed out by flue, until the amount of stored heat of heat-storing sphere meets accumulation of heat requirement.The air-supply stage, by cold wind from
Cool air hose is sent into hot-blast stove, and cold wind flows through regenerative chamber and is heated into hot wind by heat-storing sphere, is sent to blast furnace by hot-air mouth outflow.Air-supply rank
The wind-warm syndrome and duration of section are directly determined by combustion phases, therefore are the bases for guaranteeing blast furnace and normally producing to burning furnace process and being precisely controlled
Plinth.Pebble stove working principle is the heat that blast furnace gas combustion generates to be sent to blast furnace by medium of heat-storing sphere, but existing
Detection means can not directly measure furnace heat, therefore reflect combustion efficiency by monitoring dome temperature and exhaust gas temperature, into
And estimate amount of stored heat in furnace.Hot wind furnace technology requires dome temperature to maintain 1350 DEG C, and exhaust gas outlet temperature reaches 350 DEG C, but
Furnace inner environment is complicated, it is difficult to be optimal the two.Therefore need to provide a kind of burning furnace course control method for use, it improves and burns heater stage
Amount of stored heat, to meet supply air temperature and duration.Now both at home and abroad mainly based on manually controlling, a small number of Large Steel ironworks are adopted
With expert system control or fuzzy control.
Blast furnace normally produces the requirement to air-supply, pulsation-free air-supply duration and hot blast temperature, therefore needs to gas flow
Reasonable set is carried out with air-fuel ratio.But gas-particle heat transfer is complicated in furnace, and calorific value of gas is frequent with pressure oscillation, and existing means are difficult to reality
It is precisely controlled when real.Hot blast stove burning process control based on manually controlling, existing intelligent control method mainly with
Based on data model, adjusting air-fuel ratio and gas flow, and then dome temperature and exhaust gas temperature are controlled, but data model precision
It is low and heat-transfer mechanism can not be described, it is difficult to dome temperature and exhaust gas temperature be made to reach requirement simultaneously.
CN101881463A hot-blast stove automatic optimal intelligent control method
Application number CN201010206032.9 applying date 2010.06.09
Application publication number CN101881463A data of publication of application 2010.11.10
The patent provides a kind of hot blast stove burning process autocontrol methods.Based on total amount of stored heat, dome temperature is set
With exhaust gas temperature, optimizing is carried out to air-fuel ratio, gas flow by fuzzy control；Pass through exhaust gas temperature adjuster, heating load tune
The flow for saving device and combustion air adjuster control combustion air, is adjusted air-fuel ratio by air-fuel ratio fuzzy controller.
But only dome temperature climbing speed difference and air-fuel ratio change direction are blurred, information is relatively simple, and dome temperature
Variation influenced by calorific value of gas and pressure change, fuzzy result can be made inaccurate.
CN105157057A Combustion of Hot Air Furnace control method and system
Application number CN201510540857.7 applying date 2015.08.28
Application publication number CN105157057A data of publication of application 2015.12.16
The patent provides a kind of Combustion of Hot Air Furnace control method and systems.Dome temperature, valve when obtaining main combustion period first
Door aperture and control parameter etc. are adjusted valve opening according to whether current each parameter meets optimum combustion control parameter.
But hot-blast stove belongs to Large-lag System, and the dome temperature and exhaust gas temperature at current time are straight by gas flow of upper a moment and air-fuel ratio
Influence is connect, this method can not accomplish accurate in real time adjust.
CN105423334A Combustion of Hot Air Furnace control method and system
Application number CN201511028734.1 applying date 2015.12.31
Application publication number CN105423334A data of publication of application 2016.03.23
The patent provides a kind of Combustion of Hot Air Furnace Process Control Systems.It is first depending on the current burning oven-like of expert system identification
State, selects different fuzzy controllers to different combustion phases, including rapid burning period optimizing ratio of air to fuel fuzzy controller and
Dome temperature manages phase optimizing ratio of air to fuel fuzzy controller；Flow gives computing module, calculates gas flow setting value and air
Flow setting value；Household's controller is obscured by flow, and feedforward compensation is carried out to interference.But expert system can not be to all burnings
State is precisely controlled, and leaks solution when there are problems that will appear when burning furnace parameters exception.
CN205803521U Combustion of Hot Air Furnace control method and system
Application number CN201620784658.0 applying date 2016.07.25
Application publication number CN205803521U data of publication of application 2016.12.14
The patent provides a kind of blast funnace hot blast stove gas flow Optimal Control Systems.Equipped with basic gas flow model,
Single producer gas flow correction model, preferential producer gas flow correction model, gas flow adjuster and the dome temperature of burning protect mould
Type adjusts gas valve aperture according to present combustion state.But hot blast stove burning process have it is apparent interim, the patent without
Method realizes that dome temperature conflagration and terminal exhaust gas temperature reach setting value, and fuzzy quantity is simple, and control precision is low.
In conclusion existing technology all has corresponding defect, therefore propose the present invention.
Summary of the invention
A kind of pebble stove provided by the invention burns furnace course control method for use and system, solves the prior art and is difficult to pair
Hot blast stove burning process carries out the technical issues of real-time and precise control.
In order to solve the above technical problems, a kind of pebble stove burning furnace course control method for use proposed by the present invention includes:
Based on hot blast stove burning historical data, matching obtains optimal air-fuel ratio；
According to gas-particle two-phase heat transfer and process structure in furnace, chamber of hot-blast stove diesel engine is established；
Based on chamber of hot-blast stove diesel engine, temperature prediction model is established, temperature prediction model includes vault temperature
Spend prediction model and exhaust gas temperature prediction model；
Based on temperature prediction model, the optimal control parameter of control hot blast stove burning process is obtained in real time.
Further, it is based on hot blast stove burning historical data, matching obtains optimal air-fuel ratio and includes:
The hot blast stove burning historical data of acquisition is pre-processed；
By finite time window, state parameter vector sum operating parameter vector is redescribed, meets work to obtain
The operation mode of skill；
Based on operation mode and customized evaluation index, superior operational pattern base is obtained, and to superior operational pattern base
Two-stage classification is carried out, wherein first-level class is classified according to exhaust gas temperature, and secondary classification is clustered using density peaks；
Oven-like state will currently be burnt and superior operational pattern base carries out three-level matching, to obtain optimal air-fuel ratio.
Further, it will currently burn oven-like state and superior operational pattern base carries out three-level matching, to obtain best air-fuel
Than including:
Current exhaust gas temperature and superior operational pattern base are subjected to level-one matching, obtain optimal operation mode subset；
It is slightly matched in first-level class using Euclidean distance, obtains maximum similar cluster subclass center；
Smart matching is carried out using the polymerization approximation based on linear statistical feature, and best air-fuel is obtained according to matching similarity
Than.
Further, obtaining optimal air-fuel ratio according to matching similarity includes:
When matching similarity is greater than or equal to preset threshold, optimal air-fuel ratio is set as the air-fuel ratio that is matched to；
When matching similarity is less than preset threshold, fuzzy reasoning is carried out according to most like predetermined number operation mode,
Obtain optimal air-fuel ratio.
Further, chamber of hot-blast stove diesel engine, the dome temperature prediction model of foundation are based on specifically:
Tvt(t)=Tr(0,0, t)=(1- φ3+φ4+φ6-ζ2)Tr(0,0,t-Δt)+φ4Tr(0,Δz,t-Δt)
+φ5Tr(Δr,0,t-Δt)+(φ2+ζ1)Ts(0,0,t-Δt)
Wherein, Tvt(t) dome temperature of t moment, T are indicatedr(0,0, t) it indicates in t moment regenerative chamber top layer heat-storing sphere
Temperature at heart point, Tr(0,0, t- Δ t) indicates the temperature of t- time Δt regenerative chamber top layer heat-storing sphere center, Tr(0,
Δ z, t- Δ t) indicates the temperature of heat-storing sphere center at t- time Δt regenerative chamber Δ z, φ2Indicate replacement variable 2, φ3Table
Show replacement variable 3, φ4Indicate replacement variable 4, φ5Indicate replacement variable 5, φ6Indicate replacement variable 6, ζ2Indicate linearisation ginseng
Number 2, Tr(Δ r, 0, t- Δ t) indicate the temperature at t- time Δt regenerative chamber top layer heat-storing sphere Δ r, ζ1Indicate linear parameter
1, Ts(the temperature of 0,0, t- Δ t) expression t- time Δt regenerative chamber top layer exhaust gas center；
And the exhaust gas temperature prediction model established specifically:
Wherein, Twt(t) exhaust gas temperature of t moment, T are indicateds(0, L, t) indicates t moment regenerative chamber bottom exhaust gas center
Temperature at point, Ts(0, L- Δ z, t) indicates the temperature of exhaust gas center at t moment regenerative chamber L- Δ z, Tr(0,L-Δz,t)
Indicate the temperature of heat-storing sphere center at t moment regenerative chamber L- Δ z, mgIndicate flue gas mass flow, φ1Indicate replacement variable
1, ξ1Indicate linear parameter 1, ζ2Indicate linear parameter 2.
Further, it is based on temperature prediction model, obtains the optimal control parameter packet of control hot blast stove burning process in real time
It includes:
Dome temperature setting value and exhaust gas temperature setting value are set；
According to the real output value of dome temperature and exhaust gas temperature and the calculated model output value of temperature prediction model it
Between deviation, feedback modifiers are carried out to temperature prediction model, and revised temperature prediction model is as follows:
T* vtp(τ+Δ t)=Tvtp(τ+Δt)+evt(τ)
T* wtp(τ+Δ t)=Twtp(τ+Δt)+ewt(τ)
Wherein, T* vtp(τ+Δ t) indicates the dome temperature setting value of revised t+ time Δt, Tvtp(τ+Δ t) indicates t
The dome temperature setting value of+time Δt, evt(τ) indicates the difference of the dome temperature of τ moment outputting measurement value and model calculation value
Value, T* wtp(τ+Δ t) indicates the exhaust gas temperature setting value of revised t+ time Δt, Twtp(τ+Δ t) indicates t+ time Δt
Exhaust gas temperature setting value, ewt(τ) indicates the difference of the exhaust gas temperature of τ moment outputting measurement value and model calculation value；
Based on revised temperature prediction model, optimal control target letter is set separately to rapid burning period and accumulation of heat phase
Number, is solved by the optimal control objective function to each stage, to obtain control hot blast stove burning process in real time
Optimal control parameter.
Further, the optimal control parameter for controlling hot blast stove burning process is specially gas flow.
A kind of pebble stove proposed by the present invention burns furnace Process Control System
Memory, processor and storage on a memory and the computer program that can run on a processor, processor
The step of pebble stove of the invention burns furnace course control method for use is realized when executing computer program.
Compared with the prior art, the advantages of the present invention are as follows:
Pebble stove provided by the invention burns furnace course control method for use and system, by being based on hot blast stove burning history number
According to matching obtains optimal air-fuel ratio, according to gas-particle two-phase heat transfer and process structure in furnace, establishes chamber of hot-blast stove Transient Heat Transfer
Model is based on chamber of hot-blast stove diesel engine, establishes temperature prediction model, temperature prediction model includes that dome temperature is pre-
It surveys model and exhaust gas temperature prediction model and is based on temperature prediction model, obtain the optimal of control hot blast stove burning process in real time
Control parameter solves the prior art and is difficult to the technical issues of carrying out real-time and precise control to hot blast stove burning process, by dividing
It analyses pebble stove and burns furnace process, control air-fuel ratio from data Angle according to site technique, control gas flow from mechanistic point,
Make the two while being optimal, and combines matched optimal air-fuel ratio to the real-time optimizing of best gas flow, it can be achieved that hot wind
Furnace burns the real-time and precise control of furnace process.
Detailed description of the invention
Fig. 1 is that the pebble stove of the embodiment of the present invention one burns the flow chart of furnace course control method for use；
Fig. 2 is that the pebble stove of the embodiment of the present invention two burns the flow chart of furnace course control method for use；
Fig. 3 is the hot blast stove burning process optimal air-fuel ratio setting process of the embodiment of the present invention two；
Fig. 4 is the hot blast stove burning process optimal air-fuel ratio multistage matching strategy of the embodiment of the present invention two；
Fig. 5 is the distributed parameter model PREDICTIVE CONTROL functional block diagram of the embodiment of the present invention two；
Fig. 6 is that the pebble stove of the embodiment of the present invention burns furnace Process Control System block diagram.
Appended drawing reference:
10, memory；20, processor.
Specific embodiment
To facilitate the understanding of the present invention, the present invention is made below in conjunction with Figure of description and preferred embodiment more complete
Face meticulously describes, but the protection scope of the present invention is not limited to the following specific embodiments.
The embodiment of the present invention is described in detail below in conjunction with attached drawing, but the present invention can be defined by the claims
Implement with the multitude of different ways of covering.
Embodiment one
Referring to Fig.1, the pebble stove that the embodiment of the present invention one provides burns furnace course control method for use, comprising:
Step S101, is based on hot blast stove burning historical data, and matching obtains optimal air-fuel ratio；
Step S102 establishes chamber of hot-blast stove diesel engine according to gas-particle two-phase heat transfer and process structure in furnace；
Step S103 is based on chamber of hot-blast stove diesel engine, establishes temperature prediction model, temperature prediction model packet
Include dome temperature prediction model and exhaust gas temperature prediction model；
Step S104 is based on temperature prediction model, obtains the optimal control parameter of control hot blast stove burning process in real time.
Pebble stove provided in an embodiment of the present invention burns furnace course control method for use, by being based on hot blast stove burning history number
According to matching obtains optimal air-fuel ratio, according to gas-particle two-phase heat transfer and process structure in furnace, establishes chamber of hot-blast stove Transient Heat Transfer
Model is based on chamber of hot-blast stove diesel engine, establishes temperature prediction model, temperature prediction model includes that dome temperature is pre-
It surveys model and exhaust gas temperature prediction model and is based on temperature prediction model, obtain the optimal of control hot blast stove burning process in real time
Control parameter solves the prior art and is difficult to the technical issues of carrying out real-time and precise control to hot blast stove burning process, by dividing
It analyses pebble stove and burns furnace process, control air-fuel ratio from data Angle according to site technique, control gas flow from mechanistic point,
Make the two while being optimal, and combines matched optimal air-fuel ratio to the real-time optimizing of best gas flow, it can be achieved that hot wind
Furnace burns the real-time and precise control of furnace process.
The purpose of the present invention is to propose to a kind of pebble stoves to burn furnace course control method for use, first to historical data processing, build
Vertical superior operational pattern base, and optimal air-fuel ratio is matched according to current oven-like state of burning, it is pushed away for leakage solution problem using fuzzy rule
Manage out optimal air-fuel ratio；Then and site technique and furnace heat transfer principle establish regenerative chamber diesel engine, and as
Foundation temperature prediction model；Distributed parameter system model predictive control strategy is finally used, gas flow is carried out accurate
Control realizes that vault stablizes conflagration, exhaust gas outlet temperature reaches setting value, to increase amount of stored heat in furnace.
Embodiment two
Referring to Fig. 2, pebble stove provided by Embodiment 2 of the present invention burns furnace course control method for use, comprising:
Step S201 pre-processes the hot blast stove burning historical data of acquisition.
Due to the presence of interference, there are imperfect or inaccurate phenomenons for the data of the present embodiment acquisition, thus using drawing
Ge Lang interpolation method is to missing values processing；For the shape and width for retaining data, filtered using Savitzky-Golay；To eliminate
Influence of the variable dimension to calculating, is normalized each variable.
Step S202 redescribes state parameter vector sum operating parameter vector, by finite time window to obtain
The operation mode of technique must be met.
Data in complex industrial production process mainly include operating parameter and state parameter.The operating parameter at τ moment can
It indicates are as follows:
P (τ)=[p1(τ),p2(τ),...,pm(τ)] (1)
Wherein, m is the number of operating parameter.The state parameter at τ moment may be expressed as:
S (τ)=[s1(τ),s2(τ),...,sn(τ)] (2)
Wherein, n is the number of state parameter.
During hot blast stove burning, the pressure and calorific value frequent fluctuation of coal gas, it is difficult to the operation mode pair at a certain moment
The variation tendency of hot-blast stove operating condition is described, for this purpose, proposing that a kind of operation mode suitable for hot-blast stove describes method.Pass through
Finite time window redescribes state parameter vector S and operating parameter vector Q, and value is-n in time windowT~nT, altogether
2nT+ 1 value, the size of time window is by time step nTIt determines.I-th of state parameter for indicating the τ moment, by limited
Time window description are as follows:
Wherein, s (- nT)~s (nT) be finite time window in status parameter values.Indicate i-th of the behaviour at τ moment
Make parameter, described by finite time window are as follows:
Wherein, p (- nT)~p (nT) be finite time window in operational parameter value.
The state parameter of n dimension and corresponding m dimension operating parameter are defined as operation mode, it may be assumed that
The present embodiment, as state parameter, is used as using air-fuel ratio and is grasped using dome temperature, exhaust gas temperature and gas flow
Make parameter.
Step S203 is based on operation mode and customized evaluation index, obtains superior operational pattern base, and to excellent behaviour
Operation mode library carries out two-stage classification, and wherein first-level class is classified according to exhaust gas temperature, and secondary classification is poly- using density peaks
Class.
Specifically, the present embodiment selects vault outlet temperature, exhaust gas outlet temperature, air-supply wind-warm syndrome, air-supply duration and coal gas
Total dosage sets weight to each evaluation index as evaluation index, by Information Entropy, and then establishes comprehensive evaluation index.It is equipped with
M heats (passing through data prediction) to be evaluated, n evaluation index, the specific steps are as follows:
Step1 calculates the specific gravity p of the i-th heat index value under jth item evaluation indexij:
The entropy e of steo2 calculating jth item indexj:
Wherein k > 0, ln are natural logrithm, 0≤ej≤1。
The difference property coefficient g of step3 calculating jth item indexj:
gj=1-ej (8)
Step4 defines flexible strategy:
Step5 calculates comprehensive index vi:
Wherein, viFor the comprehensive evaluation value of i-th of heat.
The present embodiment carries out two-stage classification to superior operational pattern base, and first-level class is classified according to exhaust gas temperature, and two
Grade classification method is clustered using density peaks.The hot blast stove burning process optimal air-fuel ratio setting process of the embodiment of the present invention is specific
It can refer to Fig. 3, as seen from Figure 3, the embodiment of the present invention passes through finite time window first, operates to state parameter vector sum
Parameter vector is redescribed, to obtain the operation mode for meeting technique, is then based on operation mode and customized evaluation refers to
Mark obtains superior operational pattern base, finally will currently burn oven-like state and superior operational pattern base carries out three-level matching, to obtain
Optimal air-fuel ratio.
Step S204, will currently burn oven-like state and superior operational pattern base carries out three-level matching, to obtain best air-fuel
Than.
Referring to Fig. 4, Fig. 4 is the hot blast stove burning process optimal air-fuel ratio multistage matching strategy of the embodiment of the present invention, from Fig. 4
As can be seen that the present embodiment realizes the matched process of three-level specifically: it is first depending on current exhaust gas temperature and carries out level-one matching,
It is secondary slightly to be matched in first-level class using Euclidean distance, finally use the polymerization approximation (LSF_ based on linear statistical feature
PAA smart matching) is carried out.When final matching result is successful, optimal air-fuel ratio is set；When matching result failure, take most like
5 operation modes carry out fuzzy reasoning, and then obtain optimal air-fuel ratio.Specific step is as follows:
Step1 obtains current time operation mode Qn=[s1,s2,...,sn,p1,p2,...,pm], wherein each parameter ui(τ)
=[ui(-nT),...,ui(-1),ui(0)], 0 current time is indicated.
Step2 is designated as-n under according to exhaust gas temperatureT~-1 waste gas state parameter is matched, and optimum operation is obtained
Mode subset.
Step3 uses Euclidean distance, is designated as-n underT~-1 operation mode carries out Rapid matching, obtains maximum similar
Cluster subclass center.
Step4 is based on LSF_PAA, is designated as-n underT~-1 operation mode carries out smart matching in subclass, obtains matching
As a result
Step5 matching similarity is higher than 0.9, as successful match, sets air-fuel ratio and is matched toIf it fails to match, fuzzy reasoning is carried out according to 5 most like operation modes, obtains best air-fuel
Than.
The present embodiment can not only precisely obtain optimal air-fuel ratio by matching with superior operational pattern base progress three-level, moreover it is possible to
Leakage solution problem is efficiently solved, so that the optimal air-fuel ratio based on acquisition, is precisely controlled hot blast stove burning process.
Step S205 establishes chamber of hot-blast stove diesel engine according to gas-particle two-phase heat transfer and process structure in furnace.
Specifically, it is assumed that axial temperature is identical in regenerative chamber, establishes the two-dimensional transient heat transfer model of flue gas and heat-storing sphere.By
Law of conservation of energy knows in the unit time that the heat of flue gas reduction is equal to the heat of its release in micro unit, increases in heat-storing sphere
Heat be equal to its absorb heat, such as formula (11), (12).
Qs=Qd+Qf (11)
Qr=Qc+Qd+Qf (12)
Q in formulas、QrThe heat that the heat and heat-storing sphere that flue gas discharges in single micro unit respectively in the unit time absorb,
Qd、QfFlue gas and the heat flow of heat-storing sphere heat convection heat flow and gas radiation to heat-storing sphere, Q in respectively single micro unitc
For heat-storing sphere heat transfer net heat flow in single micro unit.
The boundary condition and primary condition of this model are as follows:
In formula, TsFor flue-gas temperature, TrFor heat-storing sphere temperature, Ts0、Tr0The respectively each position flue gas of regenerative chamber and accumulation of heat
The initial temperature of ball, TsinFor vault flue-gas temperature.
In regenerative chamber at (z, r) micro unit smoke delivery are as follows:
Wherein, ms=(1+ η) mgFor flue gas mass flow, η is air-fuel ratio, mgFor the mass flow of coal gas, csFor flue gas ratio
Thermal capacitance.
Known by specific heat capacity formula, the heat that single micro unit heat-storing sphere absorbs in the unit time are as follows:
V in formular=(1- μ) (π (Δ r)2+ 2 π Δ r) Δ z are heat storage volume in single micro unit, and μ is regenerative chamber hole
Rate, ρrFor heat-storing sphere density, crFor heat-storing sphere specific heat capacity.
Known by Fourier law, heat-storing sphere heat transfer net heat flow in unit micro unit are as follows:
In formula, λrFor the thermal coefficient of heat-storing sphere.
Known by Newtonian Cooling formula, the heat convection heat flow of flue gas and heat-storing sphere in single micro unit are as follows:
Qd=hA (Ts-Tr) (17)
In formula,For heat convection area,For convection transfer rate,
Nu=2.0 is nusselt number.
Known by Si Te Winnow-basket-Boltzmann law, the heat flow of flue gas and heat-storing sphere heat radiation in single micro unit are as follows:
In formula, εrFor the radiant emissivity of heat-storing sphere, σ is heat radiation constant, αsFor gas radiation absorptivity, εsFor flue gas
Radiant emissivity.
Step S206 is based on chamber of hot-blast stove diesel engine, establishes temperature prediction model, temperature prediction model packet
Include dome temperature prediction model and exhaust gas temperature prediction model.
Specifically, regenerative chamber transient model formula (11) and formula are realized using finite difference calculus in convolution (14)~(18)
(12) discretization:
For convenience of model inference, the variable in formula (19), (20) is replaced, is enabled:
Linearization process is carried out to radiation term, guarantees that numerical value is equal before and after the processing.It enables:
Wherein, ξ1、ξ2、ζ1And ζ2To linearize coefficient, therefore formula (19), (20) can indicate are as follows:
Exhaust gas temperature prediction model is established according to formula (23):
Wherein, Twt(t) exhaust gas temperature of t moment, T are indicateds(0, L, t) indicates t moment regenerative chamber bottom exhaust gas center
Temperature at point, Ts(0, L- Δ z, t) indicates the temperature of exhaust gas center at t moment regenerative chamber L- Δ z, Tr(0,L-Δz,t)
Indicate the temperature of heat-storing sphere center at t moment regenerative chamber L- Δ z, mgIndicate flue gas mass flow, φ1Indicate replacement variable
1, ξ1Indicate linear parameter 1, ζ2Indicate linear parameter 2.
Dome temperature prediction model is established according to formula (24):
Wherein, Tvt(t) dome temperature of t moment, T are indicatedr(0,0, t) it indicates in t moment regenerative chamber top layer heat-storing sphere
Temperature at heart point, Tr(0,0, t- Δ t) indicates the temperature of t- time Δt regenerative chamber top layer heat-storing sphere center, Tr(0,
Δ z, t- Δ t) indicates the temperature of heat-storing sphere center at t- time Δt regenerative chamber Δ z, φ2Indicate replacement variable 2, φ3Table
Show replacement variable 3, φ4Indicate replacement variable 4, φ5Indicate replacement variable 5, φ6Indicate replacement variable 6, ζ2Indicate linearisation ginseng
Number 2, Tr(Δ r, 0, t- Δ t) indicate the temperature at t- time Δt regenerative chamber top layer heat-storing sphere Δ r, ζ1Indicate linear parameter
1, Ts(the temperature of 0,0, t- Δ t) expression t- time Δt regenerative chamber top layer exhaust gas center.
Dome temperature setting value and exhaust gas temperature setting value is arranged in step S207, specific as follows:
T at the time of dome temperature reaches 1300 DEG C earliest is found from historical data base1, according to t1Divide furnace two stages are burnt
It Ji Suan not setting value.Desired temperature is made of dome temperature setting value and exhaust gas temperature setting value, is expressed as follows:
Tr(τ+Δ t)=[Tvtr(τ+Δt)Twtr(τ+Δt)]T (27)
Dome temperature setting value is as follows:
Exhaust gas temperature setting value is as follows:
Step S208, according to the real output value of dome temperature and exhaust gas temperature and the calculated model of temperature prediction model
Deviation between output valve carries out feedback modifiers to temperature prediction model:
Feedback modifiers are carried out to prediction model with the difference of current outputting measurement value and model calculation value.
E (τ)=[evt(τ)ewt(τ)]T (30)
Dome temperature and exhaust temperature model correction value are as follows:
evt(τ)=Tvt(τ)-Tvtp(τ) (31)
ewt(τ)=Twt(τ)-Twtp(τ) (32)
Revised dome temperature and exhaust gas temperature prediction model are as follows:
T* vtp(τ+Δ t)=Tvtp(τ+Δt)+evt(τ) (33)
T* wtp(τ+Δ t)=Twtp(τ+Δt)+ewt(τ) (34)
Wherein, T* vtp(τ+Δ t) indicates the dome temperature setting value of revised t+ time Δt, Tvtp(τ+Δ t) indicates t
The dome temperature setting value of+time Δt, evt(τ) indicates the difference of the dome temperature of τ moment outputting measurement value and model calculation value
Value, T* wtp(τ+Δ t) indicates the exhaust gas temperature setting value of revised t+ time Δt, Twtp(τ+Δ t) indicates t+ time Δt
Exhaust gas temperature setting value, ewt(τ) indicates the difference of the exhaust gas temperature of τ moment outputting measurement value and model calculation value.
Step S209 is based on revised temperature prediction model, and optimization control is set separately to rapid burning period and accumulation of heat phase
Objective function processed is solved by the optimal control objective function to each stage, to obtain control hot stove in real time
The optimal control parameter of furnace process.
Specifically, optimization control is set separately to rapid burning period and accumulation of heat phase according to hot blast stove burning characteristic in the present embodiment
The objective function of system.Rapid burning period, i.e. τ < t1When optimal control target it is as follows:
Min J=| Tvtr(τ+Δt)-T* vtp(τ+Δt)| (35)
Accumulation of heat phase, i.e. τ > t1When optimal control target it is as follows:
It is solved by the control target to each stage, to obtain the mass flow of best coal gas, and then is calculated
Best coal gas volume flow out.The principle that the embodiment of the present invention uses distributed parameter model to control hot blast stove burning course prediction
Block diagram specifically can refer to shown in Fig. 5.
The present embodiment proposes the control strategy for combining historical data with heat-transfer mechanism.It is first depending on historical data,
Allot optimal air-fuel ratio；Secondly, diesel engine is established, for describing furnace heat transfer mechanism, and on the basis of heat transfer model
On establish dome temperature prediction model and exhaust gas temperature prediction model；Finally by distributed parameter model PREDICTIVE CONTROL, sky is selected
Combustion carries out optimizing than the optimal air-fuel ratio to match, to best gas flow.
Specifically, the embodiment of the present invention analyzes pebble stove and burns furnace process, according to site technique from data Angle control
Air-fuel ratio processed controls gas flow from mechanistic point, makes the two while being optimal.It is real according to the current operation mode for burning furnace
When match optimal air-fuel ratio from superior operational pattern base, best air-fuel is gone out using fuzzy rule inference for leakage solution problem
Than.According to gas-particle two-phase heat transfer in furnace, considers the non-linear physical parameter of flue gas and heat-storing sphere, establish regenerative chamber Transient Heat Transfer mould
Type, for describing furnace heat transfer mechanism.According to heat transfer model, the prediction model of dome temperature and exhaust gas temperature is established, by dividing
Cloth parameter system model PREDICTIVE CONTROL is realized in conjunction with matched optimal air-fuel ratio to the real-time optimizing of best gas flow to hot wind
Furnace burns the control of furnace process real-time and precise.
Key inventive point of the invention is:
(1) optimal air-fuel ratio is matched by historical data, proposes new evaluation index, to improve matching speed and essence
Degree carries out two-stage classification to superior operational pattern base, carries out multistage matching to the current furnace parameters that burn；
(2) consider the heat transfer types such as hot-blast stove heat conduction, thermal convection and heat radiation, establish regenerative chamber Transient Heat Transfer mould
Type, and dome temperature prediction model and exhaust gas temperature prediction model are established based on heat transfer model；
(3) present invention combines site technique requirement, corresponding dome temperature and exhaust gas temperature is set, using distribution parameter system
System Model Predictive Control, adjusts gas flow in real time, is optimal dome temperature simultaneously with exhaust gas temperature.
Referring to Fig. 6, the pebble stove that the embodiment of the present invention proposes burns furnace Process Control System, comprising:
Memory 10, processor 20 and it is stored in the computer journey that can be run on memory 10 and on processor 20
Sequence, wherein processor 20 realizes that the pebble stove that the present embodiment proposes burns furnace course control method for use when executing computer program
The step of.
The pebble stove of the present embodiment burns the specific work process of furnace Process Control System and working principle can refer to this
Pebble stove in embodiment burns the course of work and working principle of furnace course control method for use.
These are only the 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 (8)
1. a kind of pebble stove burns furnace course control method for use, which is characterized in that the described method includes:
Based on hot blast stove burning historical data, matching obtains optimal air-fuel ratio；
According to gas-particle two-phase heat transfer and process structure in furnace, chamber of hot-blast stove diesel engine is established；
Based on the chamber of hot-blast stove diesel engine, temperature prediction model is established, the temperature prediction model includes arch
Push up temperature prediction model and exhaust gas temperature prediction model；
Based on the temperature prediction model, the optimal control parameter of control hot blast stove burning process is obtained in real time.
2. pebble stove according to claim 1 burns furnace course control method for use, which is characterized in that be based on hot blast stove burning
Historical data, matching obtain optimal air-fuel ratio and include:
The hot blast stove burning historical data of acquisition is pre-processed；
By finite time window, state parameter vector sum operating parameter vector is redescribed, meets technique to obtain
Operation mode；
Based on the operation mode and customized evaluation index, superior operational pattern base is obtained, and to the superior operational mould
Formula library carries out two-stage classification, and wherein first-level class is classified according to exhaust gas temperature, and secondary classification is clustered using density peaks；
Oven-like state will currently be burnt and the superior operational pattern base carries out three-level matching, to obtain optimal air-fuel ratio.
3. pebble stove according to claim 2 burns furnace course control method for use, which is characterized in that will currently burn oven-like state
Three-level matching is carried out with the superior operational pattern base, to obtain optimal air-fuel ratio and include:
Current exhaust gas temperature and the superior operational pattern base are subjected to level-one matching, obtain optimal operation mode subset；
It is slightly matched in the first-level class using Euclidean distance, obtains maximum similar cluster subclass center；
Smart matching is carried out using the polymerization approximation based on linear statistical feature, and optimal air-fuel ratio is obtained according to matching similarity.
4. pebble stove according to claim 3 burns furnace course control method for use, which is characterized in that according to matching similarity
Obtaining optimal air-fuel ratio includes:
When matching similarity is greater than or equal to preset threshold, optimal air-fuel ratio is set as the air-fuel ratio that is matched to；
When matching similarity is less than preset threshold, fuzzy reasoning is carried out according to most like predetermined number operation mode, is obtained
Optimal air-fuel ratio.
5. pebble stove according to claim 1 to 4 burns furnace course control method for use, which is characterized in that based on described
Chamber of hot-blast stove diesel engine, the dome temperature prediction model of foundation specifically:
Tvt(t)=Tr(0,0, t)=(1- φ3+φ4+φ6-ζ2)Tr(0,0,t-Δt)+φ4Tr(0,Δz,t-Δt)+φ5Tr
(Δr,0,t-Δt)+(φ2+ζ1)Ts(0,0,t-Δt)
Wherein, Tvt(t) dome temperature of t moment, T are indicatedr(0,0, t) t moment regenerative chamber top layer accumulation of heat ball's dead center is indicated
The temperature at place, Tr(0,0, t- Δ t) indicates the temperature of t- time Δt regenerative chamber top layer heat-storing sphere center, Tr(0,Δz,
T- Δ t) indicates the temperature of heat-storing sphere center at t- time Δt regenerative chamber Δ z, φ2Indicate replacement variable 2, φ3Expression is replaced
Transformation amount 3, φ4Indicate replacement variable 4, φ5Indicate replacement variable 5, φ6Indicate replacement variable 6, ζ2Indicate linear parameter 2, Tr
(Δ r, 0, t- Δ t) indicate the temperature at t- time Δt regenerative chamber top layer heat-storing sphere Δ r, ζ1Indicate linear parameter 1, Ts
(the temperature of 0,0, t- Δ t) expression t- time Δt regenerative chamber top layer exhaust gas center；
And the exhaust gas temperature prediction model established specifically:
Wherein, Twt(t) exhaust gas temperature of t moment, T are indicateds(0, L, t) indicates t moment regenerative chamber bottom exhaust gas center
Temperature, Ts(0, L- Δ z, t) indicates the temperature of exhaust gas center at t moment regenerative chamber L- Δ z, Tr(0, L- Δ z, t) is indicated
The temperature of heat-storing sphere center, m at t moment regenerative chamber L- Δ zgIndicate flue gas mass flow, φ1Indicate replacement variable 1, ξ1
Indicate linear parameter 1, ζ2Indicate linear parameter 2.
6. pebble stove according to claim 5 burns furnace course control method for use, which is characterized in that pre- based on the temperature
Model is surveyed, the optimal control parameter for obtaining control hot blast stove burning process in real time includes:
Dome temperature setting value and exhaust gas temperature setting value are set；
According to the real output value of dome temperature and exhaust gas temperature and the calculated model output value of temperature prediction model it
Between deviation, feedback modifiers are carried out to the temperature prediction model, and revised temperature prediction model is as follows:
T* vtp(τ+Δ t)=Tvtp(τ+Δt)+evt(τ)
T* wtp(τ+Δ t)=Twtp(τ+Δt)+ewt(τ)
Wherein, T* vtp(τ+Δ t) indicates the dome temperature setting value of revised t+ time Δt, Tvtp(τ+Δ t) indicates t+ Δ t
The dome temperature setting value at moment, evt(τ) indicates the difference of the dome temperature of τ moment outputting measurement value and model calculation value,
T* wtp(τ+Δ t) indicates the exhaust gas temperature setting value of revised t+ time Δt, Twtp(τ+Δ t) indicates the useless of t+ time Δt
Gas desired temperature, ewt(τ) indicates the difference of the exhaust gas temperature of τ moment outputting measurement value and model calculation value；
Based on revised temperature prediction model, optimal control objective function is set separately to rapid burning period and accumulation of heat phase, is led to
It crosses and the optimal control objective function in each stage is solved, to obtain the optimal control of control hot blast stove burning process in real time
Parameter processed.
7. pebble stove according to claim 6 burns furnace course control method for use, which is characterized in that the control hot-blast stove
The optimal control parameter for burning furnace process is specially gas flow.
8. a kind of pebble stove burns furnace Process Control System, the system comprises:
Memory (10), processor (20) and it is stored in the computer that can be run on memory (10) and on processor (20)
Program, which is characterized in that the processor (20) realizes any institute of the claims 1 to 7 when executing the computer program
The step of stating method.
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