JPH09296229A - Method for controlling combustion of continuous heating furnace - Google Patents

Abstract

PROBLEM TO BE SOLVED: To suitably execute the combustion control of a continuous heating furnace for a steel material having the projecting and the recessing shapes, such as a beam blank. SOLUTION: At the time of predicting a steel material temp. with a steel material temp. distribution model representing the internal temp. variation of the steel material in a minute time with a non-linear strict equation, a heat load correcting factor as a shape factor for correcting the influence of shadow from the atmosphere on each surface of the steel material having the projecting and the recessing shapes, is calculated (Step S3). The steel material temp. distribution model is calculated by using the heat load corrected with this heat load correcting factor as a boundary condition to predict the steel material temp. having the projecting and the recessing shapes at the high accuracy (Step S6). Then, a centralized constant system flat plate temp. model as a non-linear simple model from this predicted result is used to set a target temp. raising pattern, and the calculation load is reduced while securing the calculation accuracy to execute the combustion control.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a combustion control method for a continuous heating furnace for continuously heating a steel material having an uneven shape such as a beam blank.

[0002]

2. Description of the Related Art As a conventional combustion control method for a continuous heating furnace, Japanese Patent Application Laid-Open No. 61-199016 (hereinafter referred to as a first conventional example) and Japanese Patent Application Laid-Open No. 2-156017 (hereinafter
The second conventional example) and JP-A-3-140415 (hereinafter, referred to as the third conventional example).

In the first conventional example, when determining a target temperature rise pattern, the average temperature during material extraction, the soaking degree, and each furnace temperature during material passage when the fuel flow rate is kept at the current flow rate and heating is continued. Calculate and calculate the average temperature at the time of material extraction when the fuel flow rate is changed, the soaking degree and each furnace temperature during material passage, and based on the results, calculate the linear coefficient around the current fuel flow rate, and at the time of material extraction The optimum fuel flow rate that minimizes the fuel flow rate is obtained by using linear programming method under the constraint conditions of average temperature and soaking degree. The set furnace temperature of each material is obtained from this fuel flow rate, and each zone set furnace temperature is determined as a weighted average value for each material.

In the second conventional example, the heating furnace operation during the period until the material is extracted is simulated while changing the fuel flow rate set value of each zone every moment, and the heating furnace operation is set according to the operation purpose such as quality assurance and energy saving. The value of the predetermined evaluation function obtained is obtained, and the fuel flow rate is set so as to approach the obtained target temperature rise pattern using a model expressing the dynamic relationship between the fuel flow rate and the material temperature.

The third conventional example expresses that the steel material is heated by the convective heat transfer in the heating furnace represented by the following equations (1) and (2) for the purpose of reducing the computer load on-line. The temperature model of the lumped constant system is used to determine the target temperature rise pattern such that the temperature and the soaking degree at the time of extraction are exactly the target values.

Θo = θg− (θg−θi) · exp (−α · t / D) (1) α = a · σ / (ρ · Cp) · (θg ² + θo ² ) · (θg + θo) (2) Here, θo is the steel material temperature after t hours, θi is the initial steel material temperature, θg is the furnace temperature, t is the heating time, D is the steel material thickness, a is the correction coefficient, σ is the Stefan-Boltzmann constant, ρ is the specific gravity of the steel material, and Cp is the specific heat.

[0007]

However, the first conventional example has the following unsolved problems. It is necessary to calculate the temperature both when the fuel flow rate is kept at the current flow rate and when the heating is continued, and when the fuel flow rate is changed, the calculation amount for obtaining the target temperature rise pattern becomes enormous. As a result, even if it becomes necessary to recalculate the target heating pattern in response to changes in the planned heating time due to changes in various operating conditions such as changes in the heating furnace extraction order and changes in rolling time, computer resources are required. The frequency of re-obtaining the target temperature rise pattern is limited due to the saving of. Since the optimum condition is currently obtained by the linear coefficient around the fuel flow rate, the optimality can be obtained only when the difference between the time when the optimum target heating pattern is obtained and the time when the material is actually heated is small. Since the heat transfer phenomenon in the heating furnace, which is not compensated and originally has a non-linear relationship, is approximated by a linear first-order equation, the approximation error becomes large as the amount of change increases.

In order to solve these unsolved problems, all of the above can be solved by executing the optimization while keeping the nonlinearity, but there is a new problem that the amount of calculation becomes enormous and it cannot be executed by the online control. is there.

Further, in the second conventional example, the optimization can be executed in a non-linear manner, but it is a technique utilizing generalized predictive control and is optimized while changing the fuel flow rate every moment. A linearized dynamic model is used instead of a nonlinear physical phenomenon model that expresses the relationship between heating time, furnace temperature, and steel temperature in the temperature model. A large amount of calculation is required with the square method, and in order to respond to changes in the remaining in-reactor time (heating time), the temperature rise target is defined as a function of time. Needs to recalculate the target temperature rising curve, but there is an unsolved problem that the target temperature rising curve cannot be sufficiently calculated due to the restriction of the calculation amount.

Further, in the third conventional example, only the average temperature of the skid portion and the portion between skids can be optimized, and it is not a method that can satisfy various constraint conditions. The nonlinear model is a lumped-constant temperature model obtained by integrating the following equation (3) assuming that the steel material is heated by convection heat transfer. However, the actual heat transfer in the heating furnace is radiant. Since it is governed by heat transfer, the phenomenon in the heating furnace cannot be expressed only by the above equation (1). Therefore, the heat transfer coefficient α in the equation (1) is considered in the form of the equation (2). Since the temperature dependence of steel material is ignored when the heating time becomes long, the correction coefficient a
There is an unsolved problem that the control accuracy greatly changes depending on the estimation accuracy and the setting accuracy.

Cp · ρ · D (∂θ / ∂t) = 2 · α · (θg−θ) (3) In addition, in any of the above first to third conventional examples, a steel plate is used. This is an object, and there is an unsolved problem that it cannot be applied to a steel material having an uneven shape such as a beam blank.

Therefore, the present invention has been made by paying attention to the unsolved problems of the above-mentioned conventional example, and improves the temperature calculation accuracy of a steel material having a concavo-convex shape such as a beam blank, and the calculation accuracy. An object of the present invention is to provide a fuel control method and apparatus for a continuous heating furnace, which can reduce the calculation load while ensuring the fuel consumption.

[0013]

In order to achieve the above object, a fuel control method for a continuous heating furnace according to a first aspect of the present invention uses a steel material having a plurality of combustion zones and an uneven shape such as a beam blank. In the combustion control method of a continuous heating furnace to continuously heat, by calculating the steel material temperature distribution model expressing the internal temperature change of the steel material in the boundary condition of the heat load considering the form factor of the surface shape of the steel material, It is characterized in that the internal temperature of a steel material having an uneven shape is calculated, and a target temperature rise pattern is set based on the calculated internal temperature of the steel material.

A combustion control method for a continuous heating furnace according to a second aspect of the present invention is a combustion control method for a continuous heating furnace for continuously heating a steel material having a plurality of combustion zones and having an uneven shape such as a beam blank. In the method, by calculating the steel material temperature distribution model expressing the internal temperature change of the steel material under the boundary condition of the heat load in consideration of the view factor of the surface shape of the steel material, the internal temperature of the steel material having the uneven shape is calculated, It is assumed that the temperature rise characteristics of the average temperature in the cross section of the steel material match the temperature rise characteristics of the flat plate assumed to be a lumped constant system, and the target temperature rise pattern is set using the lumped constant plate temperature model. It is characterized by doing so.

Further, in the combustion control method for a continuous heating furnace according to claim 3, in the invention of claim 2, the representative position temperature model is the furnace temperature θg, the representative position steel material temperature after a specific time is θo, and Representative position Steel temperature is θi, specific time range is t, steel representative thickness is D, total heat absorption rate is Φcg, Stefan Boltzmann constant is σ, specific heat is Cp, specific gravity is ρ, heating time, furnace temperature and steel material Relational expression expressing the relationship with temperature

[0016]

[Equation 2]

Is characterized in that

[0018]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a schematic configuration diagram showing an embodiment of the present invention, in which 1 is a bloom BM _{1 to} BM continuously conveyed by a walking beam, for example.
_11. A continuous heating furnace that conveys steel materials 4 such as beam blanks BB _{1 to} BB ₁₇ at predetermined intervals and continuously heats them. The steel material 4 which has been heated by passing through the heating zone 6, the second heating zone 7 and the soaking zone 8 in sequence, and which has finished heating is extracted from the right side and conveyed to the next step.

First heating zone 6, second heating zone 7 and soaking zone 8
Combustion burners are provided in each of the combustion burners, and the fuel supplied to these combustion burners is controlled by the control means 11 composed of a controller connected to a process computer that controls the entire continuous heating furnace 1.

The control means 11 reads the actual furnace temperatures of the pre-tropical zone 5, the first heating zone 6, the second heating zone 7 and the soaking zone 8, and at the same time, the remaining in-reacting time of the target steel material (remaining heating time). , The representative position based on the furnace temperature and the steel material temperature, the total heat absorption rate Φ _cg as a heat transfer parameter is represented according to the steel material temperature change model. The representative position of each of the first heating zone 6, the second heating zone 7 and the soaking zone 8 And the heat transfer parameter calculation means 12 for calculating between the skids respectively, and the cast steel material temperature θo is calculated from the overall heat absorption rate Φ _cg calculated by the heat transfer parameter calculation means 12 and the initial value of the furnace temperature, and the steady fuel flow rate is calculated. The objective function z (= ΣVgi) is expressed as a linear combination of the decision variables consisting of the relevant zone furnace temperature and the relevant zoned average temperature using the model, and the prescribed constraint conditions are defined to satisfy the constraint conditions. And evaluation The furnace temperature and the discharge temperature that minimize the number z are calculated by the linear programming method, and the convergence judgment of the calculated furnace temperature and the discharge temperature is performed. When the calculation is completed, the optimum furnace temperature and the optimum discharge target temperature are determined. Based on the optimum heat-up target calculation means 13 that is determined to be the one and the optimum discharge target temperature that is determined by the optimum heat-up target calculation means 13, the necessary furnace temperature that satisfies the optimum discharge target temperature for each steel material for each combustion zone Is set in accordance with the representative position steel material temperature change model, and a set furnace temperature calculation means 14 for setting the maximum value of the obtained minimum required furnace temperature for each steel material as the set furnace temperature is provided and set by the set furnace temperature calculation means 14. The fuel supplied to the combustion burner is controlled so that the set furnace temperature is set as described above.

Specifically, in this embodiment, the following three heat transfer models are used: a steel material temperature change model, a representative position steel material temperature change model, and a fuel flow rate model. The steel material temperature change model is a model expressing the internal temperature θ [K] of the steel material and is represented by the following equation (4).

[0022]

(Equation 3)

Here, k is thermal conductivity [kcal / mhrK], t is heating time [hr], Cp is specific heat [kcal / kg · K], and ρ is specific gravity [kg /
m]. By calculating the above equation (4) under the boundary condition of the heat load from the surface of the steel material, it is possible to know the temporal change of the steel material temperature. As the boundary condition of the heat load, the radiative heat transfer equation represented by the following equation (5) is used.

Q = F · Φcg ′ · σ (θg ⁴ −θs ⁴ ) ... (5) where F is the view factor of the surface point with respect to the heating furnace temperature θg, and Q is the surface heat load [kcal / m ² hr], Φcg ′ is the overall heat absorption rate (differential calculation parameter), σ is the Stefan Boltzmann constant [kcal / m ² hrK ⁴ ], θg is the furnace temperature [K], and θs is the steel surface temperature [K]. is there.

The equations (4) and (5) can be calculated by the heat transfer difference calculation method, and the calculation efficiency can be improved by the known ADI method.

In the representative position steel material temperature change model, in the steel material temperature change model, assuming that the heating of the steel material is only heat transfer from the upper and lower two directions and the heat transfer is a lumped constant system of the flat plate, the above (4) The formula and the formula (5) can be expressed by Cp · ρ · D · (∂θ / ∂t) = 2 · Φcg · σ · (θg ⁴ −θ ⁴ ) ... (6), and this (6) By integrating the equation with the heating time t, the following equation (7) expressing the relationship between the heating time, the furnace temperature and the steel material temperature can be obtained.

[0027]

(Equation 4)

Where θg is the furnace temperature [K], θo is the representative position steel material temperature [K] after a specific time, and θi is the current representative position steel material temperature.
[K], t is a specific time range [hr], D is a steel material representative thickness [m],
Φ _cg is the overall heat absorption rate, σ is the Stefan Boltzmann constant [k
cal / m ² hrK ⁴ ], Cp is specific heat [kcal / kg · K], ρ is specific gravity [kg /
m].

By using this equation (7), the furnace temperature θg
It is possible to calculate the change in the steel material temperature when heating is performed for the heating time t. Further, the fuel flow rate model is expressed by the fuel flow rate, the furnace temperature, the material temperature, etc. of the corresponding combustion zone in the steady state and the combustion zone on the extraction side thereof.

The heat balance of the corresponding combustion zone in the steady state can be expressed by the following equation (8). Qai + Qgi + Qei + 1 = Qei + Qsi + Qpi (8) Qai = Ca (θai−θrm) μi A ₀ Vgi Qgi = Hg Vgi Qei = Ce (θei−θrm) {G ₀ + (μi-1) A ₀ } Vgi Qsi = SsiΦcgi σ (θfi ⁴ −θsmi ⁴ ) Qpi = αp (θfi−θrm) where Qai is the sensible heat of air [kcal / hr] and Qgi is the calorific value of fuel.
[kcal / hr], Qei + 1 is the inflowing waste gas flow rate [kcal / hr], Qei
Is the flow rate of discharged waste gas [kcal / hr], Qsi is the heat input to steel [k]
cal / hr], Qpi is heat loss from furnace zone [kcal / hr], Ca is air specific heat, θai is preheated air temperature, θrm is room temperature, μ is combustion air ratio, A ₀ is theoretical air amount, Vgi is fuel flow rate, Hg is the calorific value of the fuel gas, Ce is the specific heat of the exhaust gas, θei is the exhaust gas temperature, G ₀
Is the theoretical amount of waste gas, Ssi is the steel surface area, Φcgi is the overall heat absorption rate, θfi is the furnace temperature, θsmi is the strip representative steel temperature, and αp is the heat transfer coefficient outside the furnace.

Then, the heat transfer parameter calculation means 12 executes the heat transfer parameter calculation processing shown in FIG. In this heat transfer parameter calculation process, first, in step S1, a target steel material search is performed. This target steel material search is a process of determining the target steel material of the heat transfer parameter calculation according to the start timing, and includes the first heating zone 6, the second heating zone 7, and the soaking zone 8
All steels immediately before entering each zone are subject steels, and steels staying in each zone are steels with remaining time (remaining heating time) within the set time X 2 minutes or more. Every time the previous calculation time is read out, the steel material with the difference from the current time being the set time X1 minute or more is determined as the target steel material.

Next, in step S2, the shape data of the target steel material is read from the process computer, and the representative thickness D [m] of each target steel material is calculated according to the following equation (9).

D = G / (ρ · S) (9) where G is unit weight [kg / m] and ρ is specific gravity (= 7860) [kg /
m ³ ], S is a converted 1/2 circumference [m].

The converted 1/2 circumference S is as shown in FIG.
In the case of the beam blank BB as shown in (a), the web thickness a, the flange width b, the web height c, the flange tip thickness d, the flanged root thickness e, and the adjacent beam blank BB are input from the process computer. It is determined by reading the interval, that is, the steel material charging interval w, and calculating the following equation (10) based on these values.

S = α · b + 2d + {(b−a) ² +4 (e−d) ² } ^1/2 + (c−2e) (10) Further, the steel material is shown in FIG. 4 (a). In the case of bloom BM, flat bar, and Z, the steel piece thickness b, the steel piece width c, and the steel material charging interval w are read from the process computer,
Based on these, the converted 1/2 circumference S is calculated by performing the calculation of the following formula (11).

S = αb + c (11) Here, α in the equations (10) and (11) is given by the following equation. α = 1- {1+ (w / b) ² } ^1/2 + (w / b) (12) Then, for the beam blank BB, the above formula (9),
By performing the calculations of the equations (10) and (12), the slab shape as shown in FIG. 3 (b) is converted. Similarly, regarding the bloom BM, flat bar, and Z, the above equation (9),
By performing the calculations of the equations (11) and (12), the slab shape as shown in FIG. 4B is converted.

Next, in step S3, the heat load in consideration of the view factor is calculated. The calculation of this heat load is
When the target steel material is the beam blank BB, an arbitrary point (i, j,
k) The heat loads QUAijk and QLijk are calculated.

Since the thermal load QUIijk of the upper surface side recess is affected by the shadow from the atmosphere, the following (1
It is calculated according to the equation 3).

[0039]

(Equation 5)

Here, Fw is the heat load correction coefficient of the beam blank concave portion, Φcgu is the upper overall heat absorption coefficient, θgu is the upper atmosphere temperature [° C.] of the steel material retention zone, and θi, j, k are points (i,
j, k) steel material temperature [° C].

Then, the heat load correction coefficient Fw is calculated for each node of the concave portion, and the respective values are based on the angular relationship, and as shown in FIG. 5 for the bottom portion, that is, the web surface, the width of the flange inclined portion is B, The web surface length is C, the division lengths at arbitrary points P1 on the web surface are C1 and C2, the length from the flange tip to the web is E, and the web surfaces of lines L1 and L2 connecting the flange tip and the point P When the angles formed by and are β1 and β2, Fw = (cosβ1 + cosβ2) / 2 (14) cosβ1 = (C1 + B) / {(C1 + B) ² + E ² )}
^1/2 cos β2 = (C2 + B) / {(C2 + B) ² + E ² )}
It is represented by ^1/2 , and as for the flange inclined surface, as shown in FIG. 6, the horizontal length b between the arbitrary point P2 of the flange inclined surface and the intersection of the web and the flange inclined surface is e, and the vertical length is e. , Fw = {(1 + cosβ) / 2} × [{(B ² + E ² ) ^1/2 } /, where β is the angle formed by the line connecting the other flange tip and the point P and the flange inclined surface (B + E)] ………… (15) cos β = {B (B + C + b) -E (Ee)} / {(B + C + b) ² + (Ee) ² }
It is represented by ^1/2 (B ² + E ² ) ^1/2 . In addition, {(B ² + E ² ) in the above equation (14)
^1/2 } / (B + E) is a term for correcting an increase in surface area due to the rectangular element.

On the other hand, the thermal load QLijk of the lower surface side recess is also affected by the shadow from the atmosphere, and is therefore calculated according to the following equation (16) in consideration of coefficient correction.

[0043]

(Equation 6)

Here, Fw is a heat load correction coefficient of the beam blank concave portion, Φcgl is a lower overall heat absorption rate, θgl is a lower atmosphere temperature [° C] of the steel material retention zone, and θi, j, k are points (i,
j, k) steel material temperature [° C].

Then, the heat load correction coefficient Fw is calculated for each node of the concave portion, and the respective values are based on the angular relationship, and as shown in FIG. 7 for the bottom portion, that is, the web surface, the width of the flange inclined portion is B, The web surface length is C, the division lengths at arbitrary points P1 on the web surface are C1 and C2, the length from the flange tip to the web is E, and the web surfaces of lines L1 and L2 connecting the flange tip and the point P When the angles formed by and are β1 and β2, Fw = (cosβ1 + cosβ2) / 2 ………… (17) cosβ1 = (C1 + B) / {(C1 + B) ² + E ² )}
^1/2 cos β2 = (C2 + B) / {(C2 + B) ² + E ² )}
^As shown in FIG. 8, the flange inclined surface is represented by ^1/2 . The horizontal length b between the arbitrary point P2 of the flange inclined surface and the intersection of the web and the flange inclined surface is b, and the vertical length is e. , Fw = {(1 + cosβ) / 2} × [{(B ² + E ² ) ^1/2 } /, where β is the angle formed by the line connecting the other flange tip and the point P and the flange inclined surface (B + E)] ………… (18) cos β = {B (B + C + b) -E (Ee)} / {(B + C + b) ² + (Ee) ² }
It is represented by ^1/2 (B ² + E ² ) ^1/2 . In addition, in the above formula (18), {(B ² + E ² ).
^1/2 } / (B + E) is a term for correcting an increase in surface area due to the rectangular element.

Further, the heat loads QUAijk and QLijk on the upper and lower surfaces other than the concave portion of the flange are expressed by the equations (13) and (16).
In the equation, the heat load correction coefficient Fw may be calculated as 1.0.

Further, since shadows are also influenced between adjacent steel materials, as shown in FIG. 9, in the upper half of the steel material, the point P3 (i, j, k) on the surface facing the adjacent steel material and the vertical direction The lengths with the ends are a1 and a2, respectively, and the angles formed by the facing surfaces and the lines L1 and L2 connecting the upper and lower ends of the steel material facing the point P3 are β1 and β2, and the distance between the adjacent steel materials is b. Then the heat load correction factors Fsu and Fsl of the upper and lower halves
Can be expressed by the following equations (19) and (20).

Fsu = (1-cosβ1) / 2 (19) Fsl = (1-cosβ2) / 2 (20) where cosβ1 = a1 / (a1 ² + b ² ) ^{1 / 2} cos β2 = a2 / (a2 ² + b ² ) ^1/2 Then, the process proceeds to step S4, and the first heating zone 6 and the second heating zone 6 for the one of the target steel materials determined in step S1 are used.
The remaining in-reactor time ti for each heating zone 7 and each zone i of the soaking zone 8 is predicted as future in-reactor time.

Next, in step S5, assuming that the current actual furnace temperature will continue in the future, n zones i of the first heating zone 6, the second heating zone 7 and the soaking zone 8 are set. Calculate the difference calculation furnace temperature θgn for each zone divided into.

Next, the process proceeds to step S6, and the difference calculation furnace temperature θ calculated in step S3 is calculated from the current furnace temperature calculation result as the starting point and the in-reactor time ti calculated in step S2.
The steel material temperature when heated by gn and the heat load QU calculated in step S3 and the steel material converted thickness D calculated in step S2
ijk, QLijk and heat load correction factors Fsu and Fsl of the facing surface
Based on equation (4) and equation (5), the representative position steel material temperature θoij for each band i is calculated. At this time, the overall heat absorption rate (difference calculation parameter) Φcg ′ in the equation (5) is also changed according to the divided zones.

Here, as the representative position steel material temperature θoi,
Average skid steel material temperature, average skid steel material temperature,
It is preferable to select the steel material center temperature of the skid portion and the steel material center temperature between the skids.

Next, the process proceeds to step S7, and based on the in-zone furnace time ti calculated in each of steps S2 to S4, the difference calculation furnace temperature θgn, and the representative position steel material temperature θoij, the representative of the equation (6) is represented. By calculating the position steel material temperature change model, the overall heat absorption coefficient Φcgij which is a heat transfer parameter at each representative position j of each steel material in each band i is calculated.

Next, in step S8, it is determined whether or not the processes of steps S2 to S7 have been completed for all target steel products. If there is a target steel product that has not been processed, the process returns to step S2. When the processing is completed for all the target steel materials, the heat transfer parameter calculation processing is ended.

The optimum heat-up target calculation means 13 uses the overall heat absorption rate Φcgij as the heat-transfer parameter calculated by the heat-transfer parameter calculation means 12 to perform the optimum heat-up target calculation processing shown in FIG. Execute for each target steel.

In this optimum heat-up target calculation process, first, in step S11, the initial value of the furnace temperature θg is determined from the actual furnace operation results to date. Next, in step S12, the furnace temperature θg determined in step S11, the planned heating time in each zone i (reacting time ti), and the overall heat absorption rate Φcgij determined in the heat transfer parameter processing are set. Based on the above, the equation (7) is calculated to calculate the representative position steel material temperature θoij after the elapse of the scheduled heating time in each zone.

Then, the process proceeds to step S13 to perform the parameter calculation of the objective function. This parameter calculation is
Using the steady-state fuel flow rate model of the above equation (8), the sum of the fuel flow rates Vgi of each zone is defined as the objective function z (= ΣVgi).

Here, the objective function z is expressed as the following equation (21) as a linear combination of the relevant zone furnace temperature and the relevant zone discharge average temperature. z = ΣCfi · θfi + ΣCsi · θoi (21) where Cfi is the relevant zone furnace temperature cost coefficient, θfi is the furnace temperature, and C is
si is the corresponding strip steel temperature cost coefficient, θoi is the corresponding strip steel temperature, and the corresponding strip furnace temperature cost coefficient Cfi and the corresponding strip steel temperature cost coefficient Csi are organized by the above equation (8) and the fuel flow rate, , It can be calculated as an explicit function by finding the partial derivative with respect to the average temperature of the zone. However, although the strip representative steel temperature θsmi is undefined, the above step S
It may be determined by calculating the following formula (22) based on the representative position steel material temperature θoij after the scheduled heating time calculated in 12.

Θsmi = (θo + θi) / 2 (22) Next, in step S14, the parameters of the predefined constraint condition function are calculated.

This constraint condition function is a constraint condition function expressed by the following equation (23) from the temperature model relational expression based on the relation between the steel material temperature, the condition of the extraction target temperature and the condition between the furnace temperature and the steel material temperature. The following (24) based on target temperature and soaking degree
There are constraint condition functions represented by the formulas and constraint condition functions represented by the following formulas (25) and (26) based on the furnace temperature constraint.

Pijθgi + qijθoji = rij (23) Here, θoji is the temperature at which the j-th representative position of the i band is taken out and is defined by the equation (7), and pij, qij, and rij are j of the i band. The derivative of the equation (7) with respect to the th representative position, θgi
Is the furnace temperature in the i band.

ΘoUj ^* >θonj> θoLj ^* (24) where θonj is the temperature of the jth representative position in the final zone, θoUj ^* is the target upper limit temperature of the jth representative position during extraction, and θoLj ^* Is the target lower limit temperature of the j-th representative position during extraction.

Θgi> θoji + βoij (25) θgi> θiji + βiij (26) Here, θoji is the temperature at which the j-th representative position of the i band is taken out and is defined by the formula (7). .Beta.oij is a correction coefficient for the temperature of the j-th representative position of the i-band, .theta.iji is a current temperature of the j-th representative position of the i-band, and .beta.iij is a correction coefficient of the current temperature of the j-th representative position of the i-band.

The representative positions defined by the subscript j in the above equations (23) to (26) are the average temperature of the steel material in the skid portion, the average temperature of the steel material in the skid portion, the central temperature of the steel material in the skid portion, the central temperature of the steel material in the skid portion. Is preferably selected.

Next, the routine proceeds to step S15, where the furnace temperature and the discharge temperature which satisfy the constraint conditions of the above expressions (23) to (26) and minimize the evaluation function z of the above expression (21) are known. Calculated by linear programming.

Then, the process shifts to step S16 to make a convergence judgment. In this convergence determination, the initial value of the furnace temperature defined in step S11 or the calculated value of the furnace temperature at the previous calculation is compared with the result calculated by the linear programming method this time, and if the difference is small, the optimum furnace temperature and the optimum discharge target temperature are obtained. Is determined to end the optimum heat-up target calculation process, and when the difference is large, the process returns to step S12 and steps S12 to S1.
The process of 5 is repeated, but if the process does not converge even if the process is repeated a predetermined number of times or more, the process is terminated, and the corresponding steel product is processed as a steel product not subject to furnace temperature calculation.

In this way, when the optimum furnace temperature and the optimum discharge target temperature are determined for all the target steel materials, the set furnace temperature calculation means 14 calculates the set furnace temperature. In this set furnace temperature calculation, the necessary furnace temperature that satisfies the optimum discharge target temperature for each steel material for each combustion zone is calculated by calculating the above equation (7). In this formula (7), the remaining heating time, the current steel material temperature, and the optimum stripping target temperature can be given to obtain the furnace temperature by convergent calculation, and the maximum value of the required minimum furnace temperature for each steel material obtained is set as the set furnace temperature. And the fuel flow rate in each combustion zone is controlled by this set furnace temperature.

Next, the operation of the above embodiment will be described.
Assuming that, as shown in FIG. 1, the beam blank BB is sequentially charged into the continuous heating furnace 1 and then the room bm is sequentially heated to perform the heat treatment, the heat transfer parameter calculation of the control means 11 is performed. When the heat transfer parameter calculation process of FIG. 2 is executed by the means 12, the bloom BM ₂ entering the first heating zone 6 and the beam blank BB ₁₄ entering the second heating zone 7 at the present moment.
And the beam blank BB ₇ entering the soaking zone 8 is determined as the target steel material, and the beam blanks BB _{3 to} BB ₁₇ and the bloom BM ₁ staying in each zone except the beam blanks BB ₁ and BB ₂ with a short remaining heating time are The target steel material is determined to have the difference between the previous calculation time of the heat transfer parameter and the current time being the set time X1 or more. (Step S1).

In this state, the heat transfer parameter calculating means 12
Then, for each beam blank BB and bloom BM determined as the target steel material, the steel material converted thickness D is calculated and the heat load correction coefficient Fw is calculated, and the heat loads QUAijk and QLijk are calculated based on this (step S2 , S
3) Obtain the remaining in-furnace time ti of each steel material for each of the zones 6 to 8 (step S4), and assume that the current actual furnace temperature will continue in the future and the difference calculation furnace temperature θgn Obtained for each combustion zone (step S5), and using the current temperature calculation result as a starting point, the steel position temperature change model of each zone i is calculated by calculating the steel temperature change model of the above formulas (4) and (5).
oij is obtained (step S6). Here, as the representative position temperature of the steel material, four locations of the skid portion steel material average temperature, the skid portion steel material average temperature, the skid portion steel material central temperature, and the skid portion steel material central temperature are selected.

In this way, the representative position steel material temperature θoij
Then, the representative position steel temperature θoij and in-reactor time t
Based on i and the furnace temperature θgi, the calculation of the equation (7) is performed, and the general heat as a heat transfer parameter from the current position to the current time of the representative position j of the target steel material for each band i at the time of charging or at the current position. The absorption rate Φcgij is calculated (step S7). As a result, the target steel temperature at the time of stripping of each target steel sheet, which is calculated when the representative position steel sheet temperature change model of the above equation (7) is calculated, is calculated by the above equations (4) and (5). The steel material temperature can be matched.

Next, the optimum heat-up target calculating means 13 determines the initial value θgi of the furnace temperature of each zone i from the actual operation results up to the present, and based on this initial value θgi and the planned heating time t ( 7)
By calculating the equation, the representative position steel material temperature θoij at the time of discharging of each zone i is calculated (step S12), and then, using the steady fuel flow rate model, as a linear combination of the relevant zone furnace temperature and the corresponding zone average temperature. The objective function z of equation (21) is defined, the strip representative steel temperature θsmi is calculated, and the constraint conditions are defined. The furnace temperature θgi and the strip temperature that satisfy the constraint conditions and minimize the objective function are known. (Step S15), the optimum furnace temperature and the optimum discharge target temperature were determined when the difference between the calculated furnace temperature and the initial value of the furnace temperature or the calculated value of the furnace temperature at the previous calculation was small. Judge that.

Then, the set furnace temperature calculation means 14 obtains the necessary furnace temperature satisfying the optimum discharge target temperature of each target steel material from the relation of the equation (7), and sets the maximum value of the minimum required furnace temperature of each target steel material. It is set as a furnace temperature, and the fuel flow rate of each zone i is controlled so as to maintain this set furnace temperature.

Therefore, according to the above-described embodiment, for the beam blank BB having the concavo-convex shape, the steel material converted thickness D is calculated by converting the thickness thereof into the rectangular thickness similar to that of the slab, and the heat load according to the shape of the recess is calculated. Since the correction coefficient Fw is calculated and the steel material temperature of the beam blank BB is predicted based on the steel material temperature change model formed by the non-linear exact equation based on the correction coefficient Fw, even if the steel material has an uneven shape such as a beam blank. The steel material temperature can be predicted with high accuracy, and good combustion control can be performed.

Further, the relationship between the heating time, the furnace temperature and the steel material temperature represented by the equation (7) as a non-linear simple model is calculated by using the steel material temperature predicted with high accuracy in the heat transfer parameter calculation processing. It is possible to determine the heat transfer parameter of the representative position steel material temperature change model to be expressed, and to obtain the derivative as an explicit function from the above representative position steel material temperature change model in the optimum heat-up target calculation process, and to raise the temperature by nonlinear programming. Since the target value can be determined, highly accurate operation optimization can be performed with a calculation amount of 1/2 of the conventional example represented by the first conventional example described above.

As described above, since the calculation amount can be reduced, the operation optimization process can be performed in a shorter time cycle than the conventional example, and as a result, the operating conditions such as the change of the heating furnace extraction order and the change of the rolling time can be reduced. The optimum discharge target temperature can be calculated at any time in response to changes, and high optimization can be realized. As a result, the material extraction temperature can be secured, the uneven heat distribution in the material can be prevented, and the fuel consumption rate can be reduced to about 10% of the fuel consumption rate. Reduction, reduction of scale loss due to prevention of overheating, labor saving of heating furnace operating personnel, etc. can be achieved.

Moreover, since the optimization is performed while remaining nonlinear, no error is caused by approximating with a linear expression as in the conventional example, and the sequential linear programming method is used to calculate the optimum output target temperature. Optimization errors can be reduced by using non-linear programming.

In the above embodiment, the case where the first and second heating zones 6 and 7 are provided has been described.
The present invention is not limited to this, and even when the number of heating zones is one or three or more, optimal combustion control is performed by performing heat transfer parameter calculation and optimum heat-up target calculation for each zone. You can

Further, in the above-mentioned embodiment, the case where the expression (7) is applied as the representative steel material temperature model has been described, but the present invention is not limited to this, and Japanese Patent Application No. 61-19 is used.
As described in Japanese Patent No. 9016, an optimum temperature rise curve that minimizes the fuel flow rate for each material is determined based on the fuel flow rate and in consideration of each element of the furnace temperature, the furnace wall temperature, and the material temperature. To determine the average of various materials in the furnace along with this temperature rise curve or preferentially bake a certain material along this temperature rising curve, multiply the set furnace temperature of each material by the weight coefficient for setting the furnace temperature Combustion control method in which the furnace temperature set value of each control zone is used, and the extraction average which is a simple model based on the steel material temperature calculated in the above embodiment as described in JP-A-3-140415. Obtain the sensitivity to the furnace temperature of each zone using the temperature sensitivity formula, find the corrected furnace temperature using the corrected furnace temperature calculation formula, and use the average temperature sensitivity formula during slab extraction so that the uniform temperature becomes the target temperature. Find the sensitivity, and finally by the corrected furnace temperature calculation formula Any furnace temperature setting method for such a combustion control method for determining a final specific each band control furnace temperature can be applied.

[0078]

As described above, according to the invention of claim 1, when the steel material having the uneven shape is continuously heated, the steel material temperature distribution model expressing the internal temperature change of the steel material By calculating the temperature of the steel material having the uneven shape by calculating the boundary conditions of the heat load in consideration of the view factor of the surface shape, the target temperature rising pattern is set based on the calculated temperature of the steel material. It is possible to predict with high accuracy the internal temperature of a steel material having an uneven shape that is not a rectangular cross section, and as a result, conventional heating furnace computer control can be applied to steel materials with complex shapes such as beam blanks. As a result, the effect that the continuous heating control of the steel material having the uneven shape can be performed well can be obtained.

According to the second aspect of the invention, when continuously heating the steel material having the uneven shape, the steel material temperature distribution model expressing the internal temperature change of the steel material is calculated by using the form factor of the surface shape of the steel material. By calculating with the boundary conditions of the heat load considered, the internal temperature of the steel material having the uneven shape is calculated,
It is assumed that the temperature rise characteristics of the average temperature in the cross section of the steel material match the temperature rise characteristics of the flat plate assumed to be a lumped constant system, and the target temperature rise pattern is set using the lumped constant plate temperature model. Since this is done, it has the effect that it is possible to optimize the operation with high accuracy without generating errors while securing the nonlinearity with a smaller calculation amount than the conventional example, and with the reduction of the calculation amount, the conventional example It is possible to optimize the operation in a shorter time cycle, and as a result, it is possible to calculate the optimized temperature increase target value at any time in response to changes in the operating conditions such as changes in the heating furnace extraction order and changes in rolling time. The effect that high optimization can be realized is obtained.

As a result, it is possible to secure the material extraction temperature, prevent uneven heating in the material, reduce the fuel consumption rate, reduce scale loss by preventing overheating, and save labor of the furnace operating personnel.

According to the third aspect of the present invention, since a non-linear model equation expressing the heat transfer phenomenon in the continuous heating furnace is applied as the lumped constant system flat plate temperature model, the transmission corresponding to the temperature change of the steel material is applied. The effect that the change in the thermal coefficient can be taken into consideration and the more accurate optimized temperature increase target value can be calculated is obtained.

[Brief description of drawings]

FIG. 1 is a schematic configuration diagram showing an embodiment of the present invention.

FIG. 2 is a flowchart showing an example of a processing procedure of a heat transfer parameter calculation means.

FIG. 3 is an explanatory diagram for calculating a steel material equivalent thickness of a beam blank.

FIG. 4 is an explanatory diagram for calculating a converted steel material thickness of a bloom.

FIG. 5 is an explanatory diagram in the case of calculating a heat load correction coefficient at the bottom of the upper surface side recess of the beam blank.

FIG. 6 is an explanatory diagram in the case of calculating a heat load correction coefficient in an inclined portion of a concave portion on the upper surface side of the beam blank.

FIG. 7 is an explanatory diagram in the case of calculating a heat load correction coefficient at the bottom of the lower surface side recess of the beam blank.

FIG. 8 is an explanatory diagram in the case of calculating a heat load correction coefficient in the inclined portion of the concave portion on the lower surface side of the beam blank.

FIG. 9 is an explanatory diagram in the case of calculating a heat load correction coefficient on the facing surface of an adjacent steel material.

FIG. 10 is a flowchart showing an example of a processing procedure of an optimum heat-up target calculation means.

[Explanation of symbols]

1 Continuous heating furnace BB _{1 to} BB ₁₇ Beam blank BM _{1 to} BM ₁₁ Bloom 5 Pre-tropical zone 6 First heating zone 7 Second heating zone 8 Soaking zone 11 Control means 12 Heat transfer parameter calculation means 13 Optimal heat-up target calculation means 14 set furnace temperature calculation means 15 furnace temperature control device

Claims (3)

[Claims] 1. A steel material temperature distribution model for expressing internal temperature change of a steel material in a combustion control method for a continuous heating furnace which continuously heats steel material having a plurality of combustion zones and having an uneven shape such as a beam blank. By calculating the boundary conditions of the heat load considering the form factor of the surface shape of the steel,
A combustion control method for a continuous heating furnace, comprising: calculating an internal temperature of a steel material having an uneven shape, and setting a target heating pattern based on the calculated internal temperature of the steel material. 2. A steel material temperature distribution model that represents an internal temperature change of a steel material in a combustion control method for a continuous heating furnace that continuously heats steel material having a plurality of combustion zones and having an uneven shape such as a beam blank. By calculating the boundary conditions of the heat load considering the form factor of the surface shape of the steel,
It is assumed that the internal temperature of the steel material having the uneven shape is calculated, and that the temperature rise characteristics of the average temperature in the cross section of the steel material match the temperature rise characteristics of the flat plate assumed to be the lumped constant system. A combustion control method for a continuous heating furnace, characterized in that a target heating pattern is set using a temperature model. 3. The lumped constant flat plate temperature model includes a furnace temperature θg, a representative position steel material temperature after a specific time θo, a current representative position steel material temperature θi, a specific time range t, a steel material representative thickness D, and a summary. When the heat absorption rate is Φcg, the Stefan Boltzmann constant is σ, the specific heat is Cp, and the specific gravity is ρ, the following relational expression expressing the relationship between the heating time, the furnace temperature, and the steel material temperature is obtained. 3. The combustion control method for a continuous heating furnace according to claim 2, wherein: