JPH0488122A - Temperature control method for continuous type heating furnace - Google Patents

Abstract

PURPOSE:To allow the dealing with the operations of considerably different conditions, such as hot slabs and cold slabs or high-temp. ejection materials and low-temp. ejection materials by predicting the optimum set in-furnace temp. at every control period (for example, 2 minutes intervals) from the present time to the extraction time of all the slabs to be successively charged and ejected. CONSTITUTION:This temp. control method for a continuous heating furnace having plural continuous control zones consists in determining the optimum set in-furnace temp. of the respective control bands in order to satisfy the target ejection temp. and target ejection lower limit temp. at the time of ejection of all the slabs to be successively charged and ejected and to save energy by optimizing fuel consumption. The evaluation functions expressing the evaluation values of the target ejection temp., target ejection lower limit temp. and fuel consumption at the time of ejection of all the slabs to be successively charged and ejected by the change rate of the in-furnace temp. are used at the time of determining the above- mentioned optimum set in-furnace temp. These functions are made zero by the partial differentiation executed by the change rate of the in-furnace temp., by which the change rate of the in-furnace temp. is determined. The change rate of the optimum set in-furnace temp. to minimize the evaluation functions is thus determined.

Description

[Detailed description of the invention] [Industrial application field] The present invention relates to a temperature control method for a continuous heating furnace.

[Prior art]

In the temperature control of a continuous heating furnace having a plurality of continuous control zones, the following technical capabilities have been known so far.

The required furnace temperature is determined for each slab in each zone, and the temperature is controlled using the highest furnace temperature for each zone among the required furnace temperature group as the representative furnace temperature (Japanese Patent Publication No. 51-3052
Publication No. 6).

In the heating furnace, the difference between the predicted temperature at the time of extraction of the slab and the target extraction temperature is included in the evaluation function, and the amount of change in the set furnace temperature that minimizes the evaluation function is determined by linear programming.
-25771).

In a heating furnace, a set furnace temperature is calculated according to the deviation between the predicted temperature of the slab and a predetermined temperature increase pattern (Japanese Patent Publication No. 49-29403).

[Problem to be solved by the invention]

However, in Japanese Patent Publication No. 51-30526, since only the slabs that are difficult to heat are heated, other slabs are overcooked and fuel consumption increases, requiring a large amount of operator intervention. Japanese Patent Publication No. 6]-25771 discloses that in order to actually satisfy the manufacturing conditions of each slab such as target extraction temperature and target extraction minimum temperature, and to perform energy-saving operation, multiple slabs must be considered in the evaluation function. and the target extraction temperature,
It is necessary to have multiple conditions such as the target extraction lower limit temperature and the evaluation value of fuel consumption, and the evaluation function is
Calculating using linear programming (minutes) requires a huge amount of calculations, and the optimum solution may not be found due to calculation errors, which hinders productivity. Furthermore, linear programming does not have flexibility in setting conditions for obtaining an optimal solution, and cannot respond to changes in operating policies, etc. Special Public Service 1977
- In the case of Publication No. 29403.

Because the response of the slab temperature to the furnace temperature is slow,
It is too late to control the temperature after detecting the deviation.

The present invention aims to improve the conventional problems as described above.

[Means to solve the problem]

The present invention has been made in view of these points,
In a temperature control method for a continuous heating furnace having a plurality of continuous control zones: If the target extraction temperature and the target extraction lower limit temperature are satisfied during extraction of all the slabs that are sequentially charged and extracted, the fuel When determining the optimal furnace temperature setting for each control zone to optimize consumption and save energy, the target extraction temperature and target extraction lower limit temperature during extraction are determined for all slabs that are sequentially charged and extracted.

Using an evaluation interval in which the evaluation value of fuel consumption is expressed as the amount of change in the furnace temperature, partial differentiation is performed on the evaluation function by the amount of change in the furnace temperature, and the amount of change in the furnace temperature is determined as zero, and the evaluation function is The method is characterized in that an optimally set furnace temperature change amount to be minimized is determined.

[Effect]

According to the present invention, when determining the optimally set furnace temperature change amount that minimizes the evaluation function, there is no need for repeated calculations to converge the results, and a unique result can be obtained, so the amount of calculation is reduced compared to the conventional method. It is significantly reduced compared to , and the load on the computer is reduced. In addition, the weighting function of the evaluation function can be adjusted and determined for each slab condition and the amount of furnace temperature change for each control zone, and by adjusting and determining it in advance, it can be changed dynamically online. can do. This makes it possible, for example, to optimally operate the heating furnace in response to operational changes such as higher quality and energy saving.

In a preferred embodiment of the present invention, the optimally set furnace temperature is predicted for each control cycle (for example, at 2-minute intervals) from the current time to the extraction time for all slabs that are sequentially charged and extracted. This makes it possible to handle operations with significantly different conditions, such as hot strip material and cold strip material, high temperature extracted material and low temperature extracted material, etc.

In a preferred embodiment, the slap temperature increase influence coefficient of the evaluation function is the product of the coefficients of the ARMA model formula.

Calculate by calculation. Thereby, the slab temperature increase influence coefficient can be easily determined, and the invention can be implemented very effectively when processing with a computer.

Further, according to the present invention, since it is possible to set all the slabs to be sequentially charged and extracted and a plurality of evaluation values, it is possible to optimally operate the heating furnace under various operating conditions and each slab condition. By arbitrarily selecting the weighting function for each slab and each control zone, the heating furnace can be operated optimally in response to operational changes such as quality-oriented or energy-saving-oriented. Furthermore, since the optimally set in-furnace temperature change amount can be uniquely determined without repeated convergence calculations, the control cycle can be subdivided and the computer load can be reduced.

〔Example〕

Hereinafter, an embodiment of the present invention will be described in detail. Here, the evaluation function J for determining the optimum in-furnace temperature change amount is assumed to be a quadratic form with the extraction temperature, extraction lower limit temperature, and fuel flow rate consumption as evaluation values as shown in the following equation.

Evaluation function J Σr・ (extraction temperature/extraction lower limit temperature evaluation value) 2+Σq・
(Fuel flow rate consumption evaluation value) 2 = (A・Δu−B)”R
(A・Δu−B)−PT(A・Δu−B)×ΔuT□Δ
u+W"Δu...(1) Here, A slab temperature increase influence coefficient (constraint condition matrix) (
mXn)Δu: :Optimum furnace temperature change amount
(nXl)A・Δu: ゛Slab extraction temperature change amount
(mXl) B Nislab extraction temperature required change amount (constraint condition vector) (mXl) R weighting function
(mXm)Q weight function
(nXn)P weighting function (non-negative vector) (mXriW
゛Weight function (non-negative vector) (
nXl) m 2 x (number of slabs) n Prediction time (minutes)/control period (minutes) x number of control bands.

In this example, in order to find the optimal amount of change in furnace temperature,
Find the point where the above evaluation function J has the minimum value. That is, the point where the evaluation function J is partially differentiated by Δu: and the result is O is the minimum point of the evaluation function J, and the calculation formula for the optimum furnace temperature change is as shown in equation (2). become.

Δu"=(A"RA+Q)-'(A"RB-W/2+A
”P/2)...(2) Equation (2) allows the optimally set furnace temperature change amount (Δu
t) can be uniquely determined, and by arbitrarily selecting the weighting function of the evaluation function for each slab and each control zone, for example, it is possible to improve quality-oriented and energy-saving-oriented operations as described later. The heating furnace can be operated optimally in response to changes.

Here, the constraint conditions constituting the above evaluation function will be explained. First, the concept of slab temperature increase influence coefficient (A) will be explained. In the control period (Δt) of a certain control band,
The amount of change (Δt) in the slab temperature on the control band exit side when the furnace temperature is changed by Δu can be expressed as in the following equation (3).

A T= a T/ a u −
(3) Therefore, the amount of change in the furnace temperature in each control zone is set at the current time t in increments of Δ. When considering the above equation by expanding it from t to t, the amount of change in the extraction temperature of the slab becomes as shown in the following equation (4).

ΔTk (t,,, x) = -0au1 (1・Δt) -8a+g(1・Δt) -6aU3(]・Δt) ... (4) Here, ΔTk (+,,, x) in the slab thickness direction X point extraction temperature change amount Δu l + Δu2+ Δu3 Amount of furnace temperature change in each control zone (ex pre-preparation zone, heating zone, soaking zone) 11+12+t3 Remaining time in each control zone (ex pre-preparation zone, heating zone, soaking zone) Tropical) k' is the slab number.

Here, the extraction temperature and extraction lower limit temperature are defined as follows.

Extraction temperature = T (t,,,,0) Extraction lower limit temperature = T (tゎ,,,1) T (t,,,,0): Total cross-section average temperature T (t,,,,
, 1): On-skid part cross-sectional average temperature According to this definition, the slab temperature increase influence coefficient (A) is determined based on equation (4) as shown in FIG. 3.

Here, the partial differential term can be easily obtained as shown in Equation (6) from the coefficients (a, b) of the ARMA model equation as shown in Equation (5) below. is very effective.

Tn-ΣaI-T,,,I+ΣbI-uo-,...
(5) However, n Current time J Time T Slab temperature U゛ Furnace temperature Here, 1, -] ・ Δ t Δ t k Nisslab number l Two-handed tropical zone (=1), heating zone (=2), soaking zone (・３)
It is.

Next, the required change in slab extraction temperature The method will be explained below.

(B) Idea θu1 (1・Δ+) aU, (]・Δt)
...(6) Here, Ti (t.., 0): Average temperature of the entire cross section of the Si slab during extraction Ti (t,.l+ 1): Average temperature of the on-skid section of the Si slab during extraction .

As mentioned above, equation (2) can be solved by determining the constraint conditions (A, B), but an example of how to respond to operational changes using weighting coefficients, which is one of the features of the present invention, is shown below. .

For example, when the slab condition is a material with minimum extraction temperature regulation,
By changing the above weights, it is possible to perform optimal operation with priority given to the slab.

Ru.

For example, post-load operation with excellent energy savings is also possible by changing the above-mentioned weights.

Here, the relationship between weights R and P is expressed as follows, and coefficient Kl(I
P is determined by Xm).

When P= and RK are increased, the operation is on the safe side with respect to the extraction temperature and the minimum extraction temperature, and when K1 is decreased, the operation is optimized with respect to the extraction temperature and the minimum extraction temperature.

Also, the relationship between weights Q and W is expressed as follows, and the coefficient is 2(lXn
) determines the weight W.

If you increase 2 for W- and 2 for Q, the set furnace temperature will be lowered actively, and K
If 2 is made small, the operation attempts to keep the set furnace temperature constant.

An example of changing the weight of the evaluation function using the control method described above is shown in FIGS. 1 and 2.

In the example shown in FIG. 1, the weight is set for baking in a safe direction, and as is clear from the figure, all target temperatures are satisfied. In the example shown in FIG. 2, the weights are set for baking with energy saving in mind, and as is clear from the figure, it follows the target temperature well. The fuel consumption rate was better than when the operator intervened more frequently.

〔Effect of the invention〕

As described in detail above, according to the present invention, weighting functions are determined for each slab using evaluation coefficients including target extraction temperature, target extraction lower limit temperature, and evaluation value of fuel consumption for a plurality of slabs. Since it can be selected arbitrarily for each slab and each control zone, it is possible to optimally operate the heating furnace in response to operational changes such as quality-oriented or energy-saving-oriented, reducing the frequency of operator intervention and fuel consumption.

In addition, in the calculation to minimize the evaluation function for determining the amount of change in the optimal furnace temperature, there is no need for repeated calculations for convergence, and the result can be uniquely determined, reducing the amount of calculation compared to conventional methods. It is possible to reduce the computer load significantly compared to the conventional method.

[Brief explanation of drawings]

Figures 1 and 2 are graphs showing extraction temperature characteristics in one embodiment of the present invention, and Figure 3 is a map showing a set of slab temperature increase influence coefficients (A) obtained from equation (4). be. Preheating slab number

Claims (3)

[Claims] (1) In a temperature control method for a continuous heating furnace having a plurality of continuous control zones, the target extraction temperature and the target extraction lower limit temperature are satisfied during extraction of all slabs that are sequentially charged and extracted,
Furthermore, when determining the optimal furnace temperature setting for each control zone in order to optimize fuel consumption and save energy,
Using an evaluation function that expresses the evaluation value of the target extraction temperature, target extraction lower limit temperature, and fuel consumption amount in terms of the amount of furnace temperature change for all slabs that are sequentially charged and extracted,
A continuous heating furnace characterized in that the evaluation function is partially differentiated by the amount of change in the furnace temperature, the amount of change in the furnace temperature is determined as zero, and the optimally set amount of change in the furnace temperature that minimizes the evaluation function is determined. temperature control method. (2) For all slabs that are sequentially charged and extracted,
2. The temperature control method for a continuous heating furnace according to claim 1, wherein the optimally set furnace temperature is predicted for each control cycle from the current time to the extraction time. (3) The continuous heating furnace according to claim 1, wherein the evaluation function is the evaluation function J shown below, and the slab temperature increase influence coefficient (constraint condition matrix A) thereof is obtained by integrating the coefficients of the ARMA model formula. temperature control method. Evaluation function J=Σr・(extraction temperature/extraction lower limit temperature evaluation value)
^2 + Σq・(Fuel flow rate consumption evaluation value) ^2=(A・Δ
u-B)^TR(A・Δu-B)−P^T(A・Δu−
B)+Δu^TQΔu+W^TΔu However, A: Slab temperature increase influence coefficient (constraint condition matrix) (m×n) Δu: Optimal furnace temperature change amount (n×l) A・Δu: Slab extraction temperature change amount (m ×l) B: Necessary change amount of slab extraction temperature (constraint condition vector) (
m×l) R: Weighting function (m×m) Q: Weighting function (n×n) P: Weighting function (non-negative vector) (m×l) W: Weighting function (non-negative vector) (n×l) m: 2×(number of slabs) n: prediction time (minutes)/control period (minutes)×number of control bands.