CN110257577B - Burning process control method and system for ball type hot blast stove - Google Patents
Burning process control method and system for ball type hot blast stove Download PDFInfo
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Abstract
The invention discloses a method and a system for controlling the burning process of a ball type hot blast stove, which are characterized in that the optimal air-fuel ratio is obtained by matching based on the historical data of the burning of the hot blast stove, a transient heat transfer model of a regenerative chamber of the hot blast stove is established according to the gas-solid two-phase heat transfer and process structure in the stove, a temperature prediction model is established based on the transient heat transfer model of the regenerative chamber of the hot blast stove, the temperature prediction model comprises a vault temperature prediction model, a waste gas temperature prediction model and a temperature prediction model, and optimal control parameters for controlling the burning process of the hot blast stove are obtained in real time, the technical problem that the burning process of the hot blast stove is difficult to carry out real-time accurate control in the prior art is solved, the air-fuel ratio is controlled from the data angle by analyzing the burning process of the ball type hot blast stove, the gas flow, the real-time accurate control of the burning process of the hot blast stove can be realized.
Description
Technical Field
The invention relates to the technical field of converter steelmaking, in particular to a method and a system for controlling a burning process of a ball type hot blast stove.
Background
The hot blast stove is a key device in the production process of the blast furnace, and the temperature and the time of the hot blast provided by the hot blast stove directly influence the production of the blast furnace. The ball type hot blast stove works in a cycle, and is mainly divided into a combustion stage and an air supply stage in one working cycle. In the combustion stage, blast furnace gas and combustion-supporting air are combusted in a combustion chamber according to a certain proportion, flue gas generated by combustion flows through a heat storage chamber to heat a heat storage ball so as to store heat, and then flows out of a flue until the heat storage amount of the heat storage ball meets the heat storage requirement. And in the air supply stage, cold air is sent into the hot blast stove from a cold air pipe, flows through the heat storage chamber, is heated by the heat storage balls into hot air, and flows out of the hot air port to be sent to the blast furnace. The air temperature and the time of the air supply stage are directly determined by the combustion stage, so that the accurate control of the furnace burning process is the basis for ensuring the normal production of the blast furnace. The working principle of the ball type hot blast stove is that heat generated by combustion of blast furnace gas is sent to a blast furnace by taking a heat storage ball as a medium, but the heat in the furnace cannot be directly measured by the existing detection means, so that the combustion effect is reflected by monitoring the temperature of the vault and the temperature of waste gas, and further the heat storage capacity in the furnace is estimated. The hot blast stove process requires that the vault temperature is maintained at 1350 ℃, the waste gas end point temperature reaches 350 ℃, but the environment in the stove is complex, and the two are difficult to achieve the optimal. Therefore, it is necessary to provide a method for controlling the furnace burning process, which can increase the heat storage capacity in the furnace burning stage to meet the requirements of the air supply temperature and time. At present, manual control is mainly used at home and abroad, and an expert system control or fuzzy control is adopted in a few large-scale steel plants.
The blast furnace has the requirements on air supply in normal production, and has no fluctuation of air supply time and hot air temperature, so that the gas flow and the air-fuel ratio need to be reasonably set. However, the gas-solid heat transfer in the furnace is complex, the gas calorific value and the pressure fluctuation are frequent, and the real-time accurate control is difficult to realize by the existing means. The burning process of the hot blast stove is mainly controlled manually, the existing intelligent control method is mainly based on a data model and used for adjusting the air-fuel ratio and the gas flow so as to control the vault temperature and the waste gas temperature, but the data model has low precision and cannot describe a heat transfer mechanism, so that the vault temperature and the waste gas temperature are difficult to meet the requirements at the same time.
Automatic optimization intelligent control method for CN101881463A hot blast stove
Application No. CN201010206032.9 application No. 2010.06.09
Application publication No. CN101881463A application publication No. 2010.11.10
The patent provides an automatic control method for the burning process of a hot blast stove. Setting the vault temperature and the waste gas temperature based on the total heat storage amount, and optimizing the air-fuel ratio and the gas flow through fuzzy control; the flow of combustion air is controlled by an exhaust gas temperature regulator, a heat supply regulator and a combustion air regulator, and the air-fuel ratio is regulated by an air-fuel ratio fuzzy controller. However, only the arch crown temperature rise rate difference and the air-fuel ratio change direction are fuzzified, the information is simple, and the change of the arch crown temperature is influenced by the gas heat value and the pressure change, so that the fuzzy result is inaccurate.
CN105157057A hot blast stove combustion control method and system
Application No. CN201510540857.7 application No. 2015.08.28
Application publication No. CN105157057A application publication No. 2015.12.16
The patent provides a method and a system for controlling combustion of a hot blast stove. The method comprises the steps of firstly obtaining the vault temperature, the valve opening, control parameters and the like in a combustion period, and adjusting the valve opening according to whether the current parameters meet the optimal combustion control parameters. However, the hot blast stove belongs to a large hysteresis system, the vault temperature and the waste gas temperature at the current moment are directly influenced by the gas flow and the air-fuel ratio at the last moment, and the method cannot achieve real-time accurate adjustment.
CN105423334A hot blast stove combustion control method and system
Application No. CN201511028734.1 application No. 2015.12.31
Application publication No. CN105423334A application publication No. 2016.03.23
This patent provides a hot blast stove combustion process control system. Firstly, identifying the current furnace burning state according to an expert system, and selecting different fuzzy controllers for different combustion stages, wherein the fuzzy controllers comprise an air-fuel ratio optimizing fuzzy controller in a rapid combustion period and an air-fuel ratio optimizing fuzzy controller in a vault temperature management period; the flow given calculation module is used for calculating a coal gas flow set value and an air flow set value; the disturbance is feed forward compensated by a flow fuzzy home controller. However, the expert system cannot accurately control all combustion states, and the problem of missing solution can occur when the furnace burning parameters are abnormal.
CN205803521U hot blast stove combustion control method and system
Application No. CN201620784658.0 application No. 2016.07.25
Application publication No. CN205803521U application publication No. 2016.12.14
This patent provides a blast furnace hot blast stove gas flow optimal control system. The device is provided with a basic gas flow model, a single-furnace gas flow correction model, a preferential burning furnace gas flow correction model, a gas flow regulator and a vault temperature protection model, and the opening of a gas valve is regulated according to the current combustion state. However, the burning process of the hot blast stove has obvious stage, the patent can not realize the rapid burning of the vault temperature and the end point waste gas temperature reaching a set value, the fuzzy quantity is simple, and the control precision is low.
In summary, the prior art has corresponding drawbacks, and the present invention is therefore proposed.
Disclosure of Invention
The invention provides a method and a system for controlling a burning process of a spherical hot blast stove, which solve the technical problem that the burning process of the hot blast stove is difficult to control accurately in real time in the prior art.
In order to solve the technical problem, the burning process control method of the ball type hot blast stove provided by the invention comprises the following steps:
based on the historical data of the hot blast stove, the optimal air-fuel ratio is obtained through matching;
establishing a transient heat transfer model of a regenerative chamber of the hot blast stove according to gas-solid two-phase heat transfer and a process structure in the stove;
establishing a temperature prediction model based on a transient heat transfer model of a regenerative chamber of the hot blast stove, wherein the temperature prediction model comprises a vault temperature prediction model and a waste gas temperature prediction model;
and obtaining the optimal control parameters for controlling the burning process of the hot blast stove in real time based on the temperature prediction model.
Further, based on the historical data of the hot blast stove burning, the matching and obtaining of the optimal air-fuel ratio comprises the following steps:
preprocessing collected burning history data of the hot blast stove;
re-describing the state parameter vector and the operation parameter vector through a limited time window so as to obtain an operation mode which accords with the process;
obtaining a good operation mode library based on the operation mode and a self-defined evaluation index, and performing two-stage classification on the good operation mode library, wherein the first-stage classification is classified according to the temperature of the waste gas, and the second-stage classification adopts density peak value clustering;
and performing three-level matching on the current furnace burning state and the excellent operation mode library so as to obtain the optimal air-fuel ratio.
Further, performing three-level matching of the current furnace status with the library of good operation modes to obtain the optimal air-fuel ratio comprises:
performing primary matching on the current exhaust gas temperature and a good operation mode library to obtain an optimal operation mode subset;
performing rough matching in the first-level classification by adopting the Euclidean distance to obtain the clustering subclass center with the maximum similarity;
and performing fine matching by adopting aggregation approximation based on linear statistical characteristics, and obtaining the optimal air-fuel ratio according to matching similarity.
Further, obtaining the optimum air-fuel ratio according to the matching similarity includes:
when the matching similarity is larger than or equal to a preset threshold value, setting the optimal air-fuel ratio as the matched air-fuel ratio;
and when the matching similarity is smaller than a preset threshold value, carrying out fuzzy reasoning according to the most similar preset number of operation modes to obtain the optimal air-fuel ratio.
Further, based on the transient heat transfer model of the regenerative chamber of the hot blast stove, the built vault temperature prediction model is specifically as follows:
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) denotes the dome temperature at time T, Tr(0,0, T) represents the temperature at the center of the uppermost ball of the regenerator at time T, Tr(0,0, T- Δ T) represents the temperature at the center point of the uppermost thermal ball of the thermal storage chamber at time T- Δ T, Tr(0, Δ z, t- Δ t) represents the temperature at the center point of the regenerative ball at Δ z in the regenerative chamber at time t- Δ t, φ2Represents the replacement variable 2, phi3Represents the replacement variable 3, phi4Represents the replacement variable 4, phi5Represents the replacement variable 5, phi6Representing the alternative variable 6, ζ2Representing the linearization parameters 2, Tr(Δ r,0, t- Δ t) represents the temperature at Δ r of the uppermost thermal storage ball of the thermal storage chamber at time t- Δ t, ζ1Representing the linearization parameters 1, Ts(0,0, t- Δ t) represents the temperature at the center point of the exhaust gas in the uppermost layer of the regenerator at time t- Δ t;
the established exhaust gas temperature prediction model specifically comprises the following steps:
wherein, Twt(T) represents the exhaust gas temperature at time T, Ts(0, L, T) represents the temperature at the center of the bottommost exhaust gas in the regenerator at time T, Ts(0, L- Δ z, T) represents the temperature at the center point of the exhaust gas at regenerator L- Δ z at time T, Tr(0, L- Δ z, t) represents the temperature at the center point of the regenerative ball at L- Δ z in the regenerative chamber at time t, mgDenotes the mass flow of the flue gas, phi1Representing the alternative variable 1, ξ1Represents the linearization parameter 1, ξ2The linearization parameter 2 is indicated.
Further, based on the temperature prediction model, obtaining the optimal control parameters for controlling the burning process of the hot blast stove in real time comprises:
setting a vault temperature set value and an exhaust gas temperature set value;
and performing feedback correction on the temperature prediction model according to the deviation between the actual output values of the vault temperature and the exhaust gas temperature and the model output value calculated by the temperature prediction model, wherein the corrected temperature prediction model is as follows:
T* vtp(τ+Δt)＝Tvtp(τ+Δt)+evt(τ)
T* wtp(τ+Δt)＝Twtp(τ+Δt)+ewt(τ)
wherein, T* vtp(τ+ Δ T) represents the dome temperature set point at time τ + Δ T after correction, Tvtp(τ + Δ t) represents the dome temperature set point at time τ + Δ t, evt(τ) represents the difference between the output measurement at time τ and the dome temperature of the model calculation, T* wtp(τ + Δ T) represents the exhaust gas temperature set point at the corrected time τ + Δ T, Twtp(τ + Δ t) represents the exhaust gas temperature set point at time τ + Δ t, ewt(τ) represents the difference between the output measurement at time τ and the exhaust temperature calculated by the model;
and respectively setting an optimal control objective function for the rapid combustion period and the heat storage period based on the corrected temperature prediction model, and solving the optimal control objective function of each stage to obtain optimal control parameters for controlling the burning process of the hot blast stove in real time.
Further, the optimal control parameter for controlling the burning process of the hot blast stove is specifically the gas flow.
The invention provides a burning process control system of a ball type hot blast stove, which comprises the following steps:
the control method comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the steps of the ball type hot blast stove burning process control method are realized when the processor executes the computer program.
Compared with the prior art, the invention has the advantages that:
the invention provides a ball type hot blast stove burning process control method and a system, which are characterized in that the optimal air-fuel ratio is obtained by matching based on the historical data of the hot blast stove burning, the transient heat transfer model of a regenerative chamber of the hot blast stove is established according to the gas-solid two-phase heat transfer and process structure in the stove, the temperature prediction model is established based on the transient heat transfer model of the regenerative chamber of the hot blast stove, the temperature prediction model comprises a vault temperature prediction model, a waste gas temperature prediction model and a temperature prediction model, the optimal control parameters for controlling the burning process of the hot blast stove are obtained in real time, the technical problem that the burning process of the hot blast stove is difficult to be accurately controlled in real time in the prior art is solved, the air-fuel ratio is controlled from the data angle by analyzing the burning process of the ball type hot blast stove, the gas flow is controlled from the mechanism, the real-time accurate control of the burning process of the hot blast stove can be realized.
Drawings
FIG. 1 is a flow chart of a ball type hot blast stove burning process control method according to a first embodiment of the invention;
FIG. 2 is a flow chart of a ball type hot blast stove burning process control method according to a second embodiment of the invention;
FIG. 3 is a process for setting the optimum air-fuel ratio in the burning process of the hot-blast stove according to the second embodiment of the present invention;
FIG. 4 is a multi-stage matching strategy for the optimal air-fuel ratio in the burning process of the hot-blast stove in the second embodiment of the invention;
FIG. 5 is a schematic block diagram of a distributed parameter model predictive control according to a second embodiment of the present invention;
FIG. 6 is a block diagram of a ball type hot blast stove burning process control system according to an embodiment of the present invention.
Reference numerals:
10. a memory; 20. a processor.
Detailed Description
In order to facilitate an understanding of the invention, the invention will be described more fully and in detail below with reference to the accompanying drawings and preferred embodiments, but the scope of the invention is not limited to the specific embodiments below.
The embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways as defined and covered by the claims.
Example one
Referring to fig. 1, a method for controlling a burning process of a ball-type hot blast stove provided by an embodiment of the present invention includes:
step S101, matching to obtain an optimal air-fuel ratio based on the historical data of the hot blast stove;
step S102, establishing a transient heat transfer model of a regenerative chamber of the hot blast stove according to gas-solid two-phase heat transfer and a process structure in the stove;
step S103, establishing a temperature prediction model based on a transient heat transfer model of a regenerative chamber of the hot blast stove, wherein the temperature prediction model comprises a vault temperature prediction model and a waste gas temperature prediction model;
and step S104, obtaining the optimal control parameters for controlling the burning process of the hot blast stove in real time based on the temperature prediction model.
The ball type hot blast stove burning process control method provided by the embodiment of the invention obtains the optimal air-fuel ratio through matching based on the historical data of the hot blast stove burning, establishes a hot blast stove regenerative chamber transient heat transfer model according to the gas-solid two-phase heat transfer and process structure in the stove, establishes a temperature prediction model based on the transient heat transfer model of the hot blast stove regenerative chamber, and obtains the optimal control parameter for controlling the hot blast stove burning process in real time based on the temperature prediction model, thereby solving the technical problem that the prior art is difficult to carry out real-time accurate control on the hot blast stove burning process, controlling the air-fuel ratio from a data angle according to a field process by analyzing the ball type hot blast stove burning process, controlling the gas flow from a mechanism angle, enabling the air-fuel ratio and the gas flow to be optimal simultaneously, and searching the optimal gas flow in real time by combining the matched optimal air-, the real-time accurate control of the burning process of the hot blast stove can be realized.
The invention aims to provide a burning process control method of a ball type hot blast stove, which comprises the steps of processing historical data, establishing an excellent operation mode library, matching an optimal air-fuel ratio according to the current burning state, and reasoning the optimal air-fuel ratio by adopting a fuzzy rule aiming at the problem of missed solution; then establishing a transient heat transfer model of the regenerator by using an on-site process and a furnace heat transfer principle, and establishing a temperature prediction model on the basis of the transient heat transfer model; and finally, a distribution parameter system model prediction control strategy is adopted to accurately control the gas flow, stable and rapid vault combustion is realized, and the end point temperature of waste gas reaches a set value, so that the heat storage capacity in the furnace is increased.
Example two
Referring to fig. 2, a method for controlling a burning process of a ball-type hot blast stove provided by the second embodiment of the present invention includes:
and step S201, preprocessing the collected historical burning data of the hot blast stove.
Due to the existence of interference, the data acquired by the embodiment has incomplete or inaccurate phenomenon, and therefore, a Lagrange interpolation method is adopted to process missing values; in order to preserve the shape and width of the data, Savitzky-Golay filtering is used; in order to eliminate the influence of the variable dimension on the calculation, normalization processing is carried out on each variable.
Step S202, the state parameter vector and the operation parameter vector are described again through a limited time window, and therefore an operation mode conforming to the process is obtained.
Data in complex industrial processes mainly include operating parameters and state parameters. The operating parameter at time τ may be expressed as:
P(τ)＝[p1(τ),p2(τ),...,pm(τ)](1)
wherein m is the number of operating parameters. The state parameter at time τ can be expressed as:
S(τ)＝[s1(τ),s2(τ),...,sn(τ)](2)
wherein n is the number of state parameters.
In the burning process of the hot blast stove, the pressure and the heat value of coal gas frequently fluctuate, and the change trend of the working condition of the hot blast stove is difficult to describe by an operation mode at a certain moment. Re-describing the state parameter vector S and the operation parameter vector Q through a finite time window, wherein the value in the time window is-nT～nTTotal 2n ofT+1 value, the size of the time window being defined by the time step nTAnd (6) determining.
The ith state parameter, representing time instant τ, is described by a finite time window as:
wherein, s (-n)T)～s(nT) Are values of state parameters within a finite time window.
The ith operating parameter, representing time τ, is described by a finite time window as:
wherein, p (-n)T)～p(nT) Are values of operating parameters within a finite time window.
Defining the state parameter of n dimension and the operation parameter of m dimension corresponding to the state parameter as operation mode, namely:
the present embodiment employs the dome temperature, the exhaust gas temperature, and the gas flow rate as the state parameters, and the air-fuel ratio as the operation parameter.
And S203, obtaining a good operation mode library based on the operation mode and the self-defined evaluation index, and performing two-stage classification on the good operation mode library, wherein the first-stage classification is classified according to the exhaust gas temperature, and the second-stage classification adopts density peak value clustering.
Specifically, in the embodiment, the vault end temperature, the waste gas end temperature, the air supply air temperature, the air supply duration and the total coal gas consumption are used as evaluation indexes, and the weights are set for the evaluation indexes through an entropy method, so that a comprehensive evaluation index is established. The method is characterized by comprising the following steps of setting m furnaces to be evaluated (subjected to data preprocessing) and n evaluation indexes:
step1 calculates the proportion p of the ith heat index value under the jth evaluation indexij：
steo2 calculates entropy e of j indexj：
Whereink is more than 0, ln is natural logarithm, e is more than or equal to 0j≤1。
step3 calculates the difference coefficient g of the j indexj：
gj＝1-ej(8)
step4 defines the weight:
step5 calculating comprehensive economic benefit index vi：
Wherein v isiAnd the evaluation value is the comprehensive evaluation value of the ith heat.
In the embodiment, the excellent operation mode library is classified in two stages, wherein the first-stage classification is classified according to the temperature of the exhaust gas, and the second-stage classification method adopts density peak value clustering. Referring to fig. 3, it can be seen from fig. 3 that the optimal air-fuel ratio setting process in the hot blast stove burning process according to the embodiment of the present invention first describes the state parameter vector and the operation parameter vector again through a limited time window to obtain an operation mode according with the process, then obtains a good operation mode library based on the operation mode and a self-defined evaluation index, and finally performs three-level matching between the current burning state and the good operation mode library to obtain the optimal air-fuel ratio.
And step S204, carrying out three-level matching on the current furnace burning state and the excellent operation mode library so as to obtain the optimal air-fuel ratio.
Referring to fig. 4, fig. 4 is a multi-stage matching strategy for the optimal air-fuel ratio in the burning process of the hot-blast stove according to the embodiment of the present invention, and as can be seen from fig. 4, the process for realizing the three-stage matching in the embodiment specifically includes: firstly, primary matching is carried out according to the current exhaust gas temperature, secondly, rough matching is carried out in primary classification by adopting an Euclidean distance, and finally, fine matching is carried out by adopting polymerization approximation (LSF _ PAA) based on linear statistical characteristics. When the final matching result is successful, setting the optimal air-fuel ratio; and when the matching result fails, carrying out fuzzy reasoning by taking the most similar 5 operation modes so as to obtain the optimal air-fuel ratio. The method comprises the following specific steps:
step1 obtains the current time operation mode Qn＝[s1,s2,...,sn,p1,p2,...,pm]Wherein each parameter ui(τ)＝[ui(-nT),...,ui(-1),ui(0)]And 0 denotes the current time.
step2 subscripts-n depending on exhaust gas temperatureTAnd matching the exhaust gas state parameters of-1 to obtain the optimal operation mode subset.
step3 uses the Euclidean distance, with subscript of-nTAnd (4) rapidly matching the operation modes of the step-1 to obtain the clustering subclass center with the maximum similarity.
step4 is based on LSF _ PAA, with a pair index of-nTThe operation mode of- < 1 > is precisely matched in the subclass to obtain the matching result
step5 matching similarity is higher than 0.9, namely matching is successful, and the air-fuel ratio is set to be matched
And if the matching fails, carrying out fuzzy reasoning according to the 5 most similar operation modes to obtain the optimal air-fuel ratio.
The embodiment can not only accurately obtain the optimal air-fuel ratio through carrying out tertiary matching with the excellent operation mode library, but also can effectively solve the problem of solution leakage, thereby enabling to accurately control the burning process of the hot blast stove based on the obtained optimal air-fuel ratio.
And S205, establishing a transient heat transfer model of a regenerator of the hot blast stove according to gas-solid two-phase heat transfer and a process structure in the stove.
Specifically, a two-dimensional transient heat transfer model of the flue gas and the heat storage ball is established on the assumption that the axial temperature in the heat storage chamber is the same. The heat quantity reduced by the smoke in the infinitesimal body is equal to the heat quantity released by the infinitesimal body in unit time according to the law of conservation of energy, and the heat quantity increased in the heat storage ball is equal to the heat quantity absorbed by the infinitesimal body, as shown in the formulas (11) and (12).
Qs＝Qd+Qf(11)
Qr＝Qc+Qd+Qf(12)
In the formula Qs、QrRespectively the heat released by the smoke in a single micro element in unit time and the heat absorbed by the heat storage ball, Qd、QfRespectively the heat flow of the convection heat exchange between the flue gas in the single micro-element and the heat storage ball and the heat flow of the flue gas radiated to the heat storage ball, QcThe net heat flow is conducted by the heat storage balls in the single micro-element.
The boundary conditions and initial conditions of this model are:
in the formula, TsIs the temperature of the flue gas, TrFor temperature of the heat-accumulating ball, Ts0、Tr0The initial temperatures T of the flue gas and the heat storage balls at all positions of the heat storage chamber respectivelysinIs the vault flue gas temperature.
The smoke release amount of the micro-element body at the position (z, r) in the heat storage chamber is as follows:
wherein m iss＝(1+η)mgFor the flue gas mass flow, η is the air-fuel ratio, mgIs the mass flow rate of the gas, csIs the specific heat capacity of the flue gas.
According to the specific heat capacity formula, the heat absorbed by a single micro-element heat storage ball in unit time is as follows:
in the formula Vr＝(1-μ)(π(Δr)2+2 π Δ r) Δ z is the volume of the regenerator in a single microelement, μ is the porosity of the regenerator, ρrIs the density of the heat storage ball crAs heat-accumulating ballsSpecific heat capacity.
Known from Fourier law, the heat conduction net heat flow of the heat storage ball in the unit micro element is as follows:
in the formula, λrThe heat conductivity coefficient of the heat storage ball.
According to the Newton cooling formula, the convection heat transfer heat flow of the flue gas and the heat storage ball in a single micro element is as follows:
Qd＝hA(Ts-Tr) (17)
in the formula (I), the compound is shown in the specification,
in order to provide a heat convection area,
nu 2.0 is the Nussel number for the convective heat transfer coefficient.
Known from Steer -Boltzmann's law, the heat flow of the heat radiation between the smoke in a single neuron and the heat storage ball is as follows:
in the formula, epsilonrThe radiation emissivity of the heat storage ball, sigma is the thermal radiation constant, αsIs the absorption rate of flue gas radiation, epsilonsIs the emissivity of the flue gas radiation.
And S206, establishing a temperature prediction model based on the transient heat transfer model of the regenerative chamber of the hot blast stove, wherein the temperature prediction model comprises a vault temperature prediction model and a waste gas temperature prediction model.
Specifically, with reference to equations (14) to (18), discretization of regenerator transient model equations (11) and (12) is realized by a finite difference method:
to facilitate model derivation, the variables in equations (19), (20) are replaced by:
and carrying out linearization treatment on the radiation item to ensure that the numerical values before and after treatment are equal. Order:
wherein, ξ1、ξ2、ζ1And ζ2For the linearization coefficients, equations (19), (20) can be expressed as:
an exhaust gas temperature prediction model is established according to equation (23):
wherein, Twt(T) represents the exhaust gas temperature at time T, Ts(0, L, T) represents the temperature at the center of the bottommost exhaust gas in the regenerator at time T, Ts(0, L- Δ z, T) represents the temperature at the center point of the exhaust gas at regenerator L- Δ z at time T, Tr(0, L- Δ z, t) represents the temperature at the center point of the regenerative ball at L- Δ z in the regenerative chamber at time t, mgDenotes the mass flow of the flue gas, phi1Representing the alternative variable 1, ξ1Represents the linearization parameter 1, ξ2The linearization parameter 2 is indicated.
A vault temperature prediction model is established according to equation (24):
wherein, Tvt(T) denotes the dome temperature at time T, Tr(0,0, T) represents the temperature at the center of the uppermost ball of the regenerator at time T, Tr(0,0, T- Δ T) represents the temperature at the center point of the uppermost thermal ball of the thermal storage chamber at time T- Δ T, Tr(0, Δ z, t- Δ t) represents the temperature at the center point of the regenerative ball at Δ z in the regenerative chamber at time t- Δ t, φ2Represents the replacement variable 2, phi3Represents the replacement variable 3, phi4Represents the replacement variable 4, phi5Represents the replacement variable 5, phi6Representing the alternative variable 6, ζ2Representing the linearization parameters 2, Tr(Δ r,0, t- Δ t) represents the temperature at Δ r of the uppermost thermal storage ball of the thermal storage chamber at time t- Δ t, ζ1Representing the linearization parameters 1, Ts(0,0, t- Δ t) represents the temperature at the center point of the exhaust gas in the uppermost layer of the regenerator at time t- Δ t.
Step S207, setting the dome temperature setting value and the exhaust gas temperature setting value as follows:
searching the historical database for the moment t when the vault temperature reaches 1300 ℃ at the earliest1According to t1And respectively calculating set values for two stages of the furnace. The temperature set point consists of the dome temperature set point and the exhaust gas temperature set point, and is expressed as follows:
Tr(τ+Δt)＝[Tvtr(τ+Δt) Twtr(τ+Δt)]T(27)
the dome temperature set point is as follows:
the exhaust gas temperature set point is as follows:
step S208, according to the deviation between the actual output values of the vault temperature and the exhaust gas temperature and the model output value calculated by the temperature prediction model, carrying out feedback correction on the temperature prediction model:
and performing feedback correction on the prediction model according to the difference between the current output measurement value and the model calculation value.
e(τ)＝[evt(τ) ewt(τ)]T(30)
The dome and exhaust temperature model correction values are as follows:
evt(τ)＝Tvt(τ)-Tvtp(τ) (31)
ewt(τ)＝Twt(τ)-Twtp(τ) (32)
the corrected dome and exhaust gas temperature prediction models are as follows:
T* vtp(τ+Δt)＝Tvtp(τ+Δt)+evt(τ) (33)
T* wtp(τ+Δt)＝Twtp(τ+Δt)+ewt(τ) (34)
wherein, T* vtp(τ + Δ T) represents the dome temperature set point at time τ + Δ T after correction, Tvtp(τ + Δ t) represents the dome temperature set point at time τ + Δ t, evt(τ) represents the difference between the output measurement at time τ and the dome temperature of the model calculation, T* wtp(τ + Δ T) represents the exhaust gas temperature set point at the corrected time τ + Δ T, Twtp(τ + Δ t) represents the exhaust gas temperature set point at time τ + Δ t, ewt(τ) represents the difference in exhaust gas temperature between the output measurement at time τ and the model calculation.
And S209, respectively setting an optimal control objective function for the rapid combustion period and the heat storage period based on the corrected temperature prediction model, and solving the optimal control objective function of each stage to obtain optimal control parameters for controlling the burning process of the hot blast stove in real time.
Specifically, in the present embodiment, the objective functions of the optimization control are respectively set for the fast combustion period and the heat accumulation period according to the burning characteristics of the hot blast stove. Fast burning period, i.e. τ < t1The optimal control objective of the time is as follows:
minJ＝|Tvtr(τ+Δt)-T* vtp(τ+Δt)| (35)
heat accumulation period, i.e. τ > t1The optimal control objective of the time is as follows:
and solving the control target of each stage to obtain the optimal mass flow of the coal gas, and further calculating the optimal volume flow of the coal gas. The schematic block diagram of the predictive control of the burning process of the hot blast stove by adopting the distributed parameter model in the embodiment of the invention can be specifically referred to as fig. 5.
The present embodiment proposes a control strategy that combines historical data with heat transfer mechanisms. Firstly, matching an optimal air-fuel ratio according to historical data; secondly, establishing a transient heat transfer model for describing a heat transfer mechanism in the furnace, and establishing a vault temperature prediction model and an exhaust gas temperature prediction model on the basis of the heat transfer model; and finally, selecting the air-fuel ratio as the matched optimal air-fuel ratio through the predictive control of the distribution parameter model, and optimizing the optimal gas flow.
Specifically, the embodiment of the invention analyzes the burning process of the ball type hot blast stove, controls the air-fuel ratio from the data perspective according to the field process, and controls the gas flow from the mechanism perspective, so that the air-fuel ratio and the gas flow are optimal simultaneously. And matching the optimal air-fuel ratio from the excellent operation mode library in real time according to the current operation mode of the furnace, and reasoning the optimal air-fuel ratio by adopting a fuzzy rule aiming at the problem of solution leakage. According to gas-solid two-phase heat transfer in the furnace, nonlinear physical parameters of flue gas and the heat storage balls are considered, and a transient heat transfer model of the heat storage chamber is established and used for describing a heat transfer mechanism in the furnace. According to the heat transfer model, a prediction model of the vault temperature and the exhaust gas temperature is established, the optimal gas flow is optimized in real time by combining the matched optimal air-fuel ratio through the prediction control of the distributed parameter system model, and the real-time accurate control of the burning process of the hot blast stove is realized.
The key points of the invention are as follows:
(1) matching out the optimal air-fuel ratio through historical data, providing a new evaluation index, carrying out two-stage classification on an excellent operation mode library for improving the matching speed and precision, and carrying out multi-stage matching on the current furnace burning parameters;
(2) a transient heat transfer model of a regenerator is established by considering heat transfer modes such as heat conduction, heat convection and heat radiation in the hot blast stove, and a vault temperature prediction model and an exhaust gas temperature prediction model are established on the basis of the heat transfer model;
(3) the method combines the field process requirements, sets the corresponding vault temperature and the waste gas temperature, adopts the predictive control of a distributed parameter system model, and adjusts the gas flow in real time, so that the vault temperature and the waste gas temperature are optimal simultaneously.
Referring to fig. 6, a ball-type hot blast stove burning process control system provided by the embodiment of the present invention includes:
the control method comprises a memory 10, a processor 20 and a computer program stored on the memory 10 and capable of running on the processor 20, wherein the processor 20 realizes the steps of the ball type hot blast stove burning process control method proposed by the embodiment when executing the computer program.
The specific working process and working principle of the ball type hot blast stove burning process control system in the embodiment can refer to the working process and working principle of the ball type hot blast stove burning process control method in the embodiment.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. A burning process control method for a ball type hot blast stove is characterized by comprising the following steps:
based on the historical data of the hot blast stove, the optimal air-fuel ratio is obtained through matching;
establishing a transient heat transfer model of a regenerative chamber of the hot blast stove according to gas-solid two-phase heat transfer and a process structure in the stove;
establishing a temperature prediction model based on the transient heat transfer model of the heat storage chamber of the hot blast stove, wherein the temperature prediction model comprises a vault temperature prediction model and a waste gas temperature prediction model, and the vault temperature prediction model established based on the transient heat transfer model of the heat storage chamber of the hot blast stove is specifically as follows:
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) denotes the dome temperature at time T, Tr(0,0, T) represents the temperature at the center of the uppermost ball of the regenerator at time T, Tr(0,0, T- Δ T) represents the temperature at the center point of the uppermost thermal ball of the thermal storage chamber at time T- Δ T, Tr(0, Δ z, t- Δ t) represents the temperature at the center point of the regenerative ball at Δ z in the regenerative chamber at time t- Δ t, φ2Represents the replacement variable 2, phi3Represents the replacement variable 3, phi4Represents the replacement variable 4, phi5Represents the replacement variable 5, phi6Representing the alternative variable 6, ζ2Representing the linearization parameters 2, Tr(Δ r,0, t- Δ t) represents the temperature at Δ r of the uppermost thermal storage ball of the thermal storage chamber at time t- Δ t, ζ1Representing the linearization parameters 1, Ts(0,0, t- Δ t) represents the temperature at the center point of the exhaust gas in the uppermost layer of the regenerator at time t- Δ t;
the established exhaust gas temperature prediction model specifically comprises the following steps:
wherein, Twt(T) represents the exhaust gas temperature at time T, Ts(0, L, T) represents the temperature at the center of the bottommost exhaust gas in the regenerator at time T, Ts(0, L- Δ z, T) represents the temperature at the center point of the exhaust gas at regenerator L- Δ z at time T, Tr(0, L- Δ z, t) represents the temperature at the center point of the regenerative ball at L- Δ z in the regenerative chamber at time t, mgDenotes the mass flow of the flue gas, phi1Representing the alternative variable 1, ξ1Represents the linearization parameter 1, ξ2Represents the linearization parameter 2;
and obtaining the optimal control parameters for controlling the burning process of the hot blast stove in real time based on the temperature prediction model.
2. The ball type hot blast stove burning process control method according to claim 1, wherein matching to obtain an optimal air-fuel ratio based on the hot blast stove burning history data comprises:
preprocessing collected burning history data of the hot blast stove;
re-describing the state parameter vector and the operation parameter vector through a limited time window so as to obtain an operation mode which accords with the process;
obtaining a good operation mode library based on the operation mode and a self-defined evaluation index, and performing two-stage classification on the good operation mode library, wherein the first-stage classification is classified according to the temperature of the waste gas, and the second-stage classification adopts density peak value clustering;
and carrying out three-level matching on the current furnace burning state and the excellent operation mode library so as to obtain the optimal air-fuel ratio.
3. The ball stove burning process control method according to claim 2, wherein the performing of the three-level matching of the current burning state with the good operation mode library so as to obtain the optimal air-fuel ratio comprises:
performing primary matching on the current exhaust gas temperature and the excellent operation mode library to obtain an optimal operation mode subset;
performing rough matching in the first-class classification by adopting the Euclidean distance to obtain the clustering subclass center with the maximum similarity;
and performing fine matching by adopting aggregation approximation based on linear statistical characteristics, and obtaining the optimal air-fuel ratio according to matching similarity.
4. The burning process control method of the ball type hot blast stove according to claim 3, wherein obtaining the optimal air-fuel ratio according to the matching similarity comprises:
when the matching similarity is larger than or equal to a preset threshold value, setting the optimal air-fuel ratio as the matched air-fuel ratio;
and when the matching similarity is smaller than a preset threshold value, carrying out fuzzy reasoning according to the most similar preset number of operation modes to obtain the optimal air-fuel ratio.
5. The ball type hot blast stove burning process control method according to any one of claims 1 to 4, wherein obtaining in real time optimal control parameters for controlling the hot blast stove burning process based on the temperature prediction model comprises:
setting a vault temperature set value and an exhaust gas temperature set value;
and performing feedback correction on the temperature prediction model according to the deviation between the actual output values of the vault temperature and the exhaust gas temperature and the model output value calculated by the temperature prediction model, wherein the corrected temperature prediction model is as follows:
T* vtp(τ+Δt)＝Tvtp(τ+Δt)+evt(τ)
T* wtp(τ+Δt)＝Twtp(τ+Δt)+ewt(τ)
wherein, T* vtp(τ + Δ T) represents the dome temperature set point at time τ + Δ T after correction, Tvtp(τ + Δ t) represents the dome temperature set point at time τ + Δ t, evt(τ) represents the difference between the output measurement at time τ and the dome temperature of the model calculation, T* wtp(τ + Δ T) represents the exhaust gas temperature set point at the corrected time τ + Δ T, Twtp(τ + Δ t) represents the exhaust gas temperature set point at time τ + Δ t, ewt(τ) represents the difference between the output measurement at time τ and the exhaust temperature calculated by the model;
and respectively setting an optimal control objective function for the rapid combustion period and the heat storage period based on the corrected temperature prediction model, and solving the optimal control objective function of each stage to obtain optimal control parameters for controlling the burning process of the hot blast stove in real time.
6. The method for controlling the burning process of the ball type hot blast stove according to claim 5, wherein the optimal control parameter for controlling the burning process of the hot blast stove is specifically a gas flow.
7. A burning process control system of a ball type hot blast stove, the system comprises:
memory (10), processor (20) and computer program stored on the memory (10) and executable on the processor (20), characterized in that the steps of the method according to any of the preceding claims 1 to 6 are implemented when the computer program is executed by the processor (20).
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| CN110938453B (en) * | 2019-12-16 | 2021-04-02 | 中冶南方工程技术有限公司 | Temperature control method for iron coke production shaft furnace for blast furnace |
| CN113251670B (en) * | 2021-05-28 | 2021-10-26 | 江苏永联慧科物联技术有限公司 | Hot blast stove control and training method, device, equipment, hot blast stove system and medium |
| CN113987404B (en) * | 2021-10-27 | 2022-06-03 | 杭州丹纳计量科技有限公司 | Flow valve opening degree adjusting method and system based on parameter updating correction |
| CN114117852B (en) * | 2021-11-18 | 2022-10-21 | 华北电力大学 | Regional heat load rolling prediction method based on finite difference working domain division |
| CN114622048B (en) * | 2022-03-15 | 2023-12-01 | 恒创数字科技(江苏)有限公司 | Hot blast stove combustion optimization system and method |
| CN114661075B (en) * | 2022-03-21 | 2023-03-14 | 湖南华菱涟源钢铁有限公司 | Fuzzy control method for waste gas temperature of blast furnace hot blast stove |
| CN114675543B (en) * | 2022-04-08 | 2023-01-10 | 攀枝花学院 | Hot blast stove intelligent combustion control method based on optimized learning algorithm |
| CN114875189B (en) * | 2022-05-12 | 2024-02-02 | 南京科远智慧科技集团股份有限公司 | Hot-blast stove flowmeter-free control method based on data analysis |
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