JP2002035908A - Breakout detection method in continuous casting equipment - Google Patents

Abstract

(57) [Summary] [PROBLEMS] To provide a method for accurately detecting a breakout occurring in a slab in a mold in continuous casting of molten steel. SOLUTION: In a method of measuring a mold temperature by a plurality of temperature measuring means embedded in a mold and detecting a mold casting abnormality based on a measured value of the mold temperature, a temperature embedded in a plurality of portions of the mold at intervals in a mold direction. The mold temperature is measured by the measuring means, and the heat flux on the inner surface of the mold at each measurement point is estimated using the heat transfer inverse problem method based on the measured mold temperature value, and the change in the heat flux value is determined as the change starting point. From the first order delay value,
From the calculated upper heat flux value and the first order lag value, a difference in heat flux is determined for each casting direction, and the distance between the heat flux difference and the downstream thermocouple position at the upstream thermocouple position and Calculate the downstream thermocouple difference integrated value after the moving time of the slab obtained from the drawing speed of the slab, and when the integrated value is equal to or more than a predetermined value, it is assumed that breakout due to solidified shell fracture occurs. Breakout detection method in continuous casting equipment.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for accurately detecting a breakout occurring in a slab in a mold in continuous casting of molten steel.

[0002]

2. Description of the Related Art In continuous casting of molten steel, detection of breakout occurring in a slab in a mold is important in continuous casting operation and quality control, and various means have been conventionally proposed. For example, the invention disclosed in Japanese Patent Application Laid-Open No. Hei 9-108891 filed by the applicant of the present application measures a mold temperature by installing a plurality of temperature measuring elements in the casting direction of a mold of a continuous casting machine, When the measured value rises, a first-order lag temperature from the rising start point is obtained, and a temperature difference is obtained from the measured mold temperature and the first-order lag temperature for each temperature measuring element in the casting direction. The temperature difference at the temperature measuring element position, the distance between the upstream temperature measuring element position and the downstream temperature measuring element position and the temperature at the downstream temperature measuring element position after the slab moving time determined from the drawing speed. A method of predicting breakout in continuous casting, wherein an integrated value with the difference is calculated, and when the integrated value is equal to or greater than a predetermined value, a breakout due to solidification shell fracture is generated. Integrating the temperature difference directly from the detected temperature by installing the thermocouple, a method of determining a breakout.

In this method, the temperature is merely a temperature index at a certain position, and varies greatly depending on conditions (particularly, the remaining mold thickness), and it is difficult to quantitatively determine the temporal change of the remaining mold thickness. However, since it is uniquely determined as a function of time, there is a problem that an error occurs in the evaluation of the heat transfer behavior particularly in an unsteady state. In addition, the occurrence of undetected or overdetected data may increase due to the setting of the predetermined value.

[0004] Similarly to the above, the invention disclosed in Japanese Patent Application Laid-Open No. 6-320245 filed by the present applicant is disclosed in
In continuous casting, a plurality of heat flux meters capable of measuring heat removal in a mold are buried in a copper plate, and using a casting speed Vc obtained from the heat flux meter, a surface flaw generation area / appropriate area / break is obtained based on the following equation. An out-of-mold heat removal control device that determines whether the area is an out-of-mold occurrence area, reduces the amount of cooling water in the mold in the area where the surface flaw occurs, and increases the amount of cooling water in the mold in the area of break-out. 0.44Vc ² -0.592Vc + 1.567 ≦ Q ≦
0.43Vc ² -0.556Vc + 2.029 Q: Heat flux (Kcal / m ² · hr) Vc: Casting speed (m / min)

In the present invention, two thermocouples are arranged in a thickness direction in a mold, and a heat flux q is detected from the temperature difference as the following equation (1). q = λ / d × ΔT (Kcal / m ² · hr) (1) where λ: thermal conductivity of the mold (Kcal / m ² · hr /
° C) d: Thermocouple distance (m) ΔT: Thermocouple temperature difference (° C)

[0006] However, the above assumption is an equation in a steady state, and there is a problem in applying it to an unsteady heat transfer phenomenon in which the heat flux varies greatly with time. As for the heat transfer phenomenon in the casting mold during the casting, the values in the formula change because the powder inflow condition always changes the operating conditions such as the casting speed and the amount of powder inflow. However, λ in the formula is a physical property value of the copper plate and is constant, and there is a problem that a large estimation error is generated in the above formula in order to evaluate the heat transfer phenomenon in the mold in which the heat transfer condition constantly changes.

Recently, in a method disclosed in Japanese Patent Application Laid-Open No. 9-108891, it has been proposed to detect a heat flux on the inner surface of a mold extremely accurately by using a heat transfer inverse problem technique. Have been. This method
It is extremely effective in detecting breakout of a slab in a mold in an unsteady heat transfer phenomenon.

[0008]

SUMMARY OF THE INVENTION The present invention prevents the occurrence of a breakout by accurately detecting the breakout of a slab in a mold, particularly in the unsteady heat transfer phenomenon, as described above. It is an object of the present invention to improve the detection accuracy of breakouts and to suppress the generation of unsteady materials due to a reduction in casting speed performed when avoiding breakouts.

[0009]

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems in the conventional method, and its gist lies in the following means. (1) In a method of measuring a mold temperature by a plurality of temperature measuring means embedded in a mold and detecting an abnormality in mold casting based on the measured value of the mold temperature, the temperature measurement embedded in a plurality of locations of the mold at intervals in the mold direction. Means for measuring the mold temperature, estimating the heat flux on the inner surface of the mold at each measurement point using the heat transfer inverse problem method based on the measured mold temperature value, and calculating the change in the heat flux value from the change start point by 1 point. A second delay value is obtained, and a difference in heat flux is determined for each casting direction from the calculated upper heat flux value and the first-order delay value. The difference between the heat flux difference at the thermocouple position on the upstream side of the casting and the downstream thermocouple is obtained. Calculate the downstream thermocouple difference integrated value after the moving time of the slab obtained from the distance between the paired positions and the slab drawing speed, and when the integrated value becomes a predetermined value or more, due to solidification shell fracture. Continuous casting equipment with breakout Breakout detection methods definitive.

(2) In a method of measuring a mold temperature by a plurality of temperature measuring means embedded in a mold and detecting a mold casting abnormality based on a measured value of the mold temperature, the mold is embedded in a plurality of locations of the mold at intervals in the mold direction. The mold temperature is measured by the temperature measuring means, and the heat flux on the inner surface of the mold at each measurement point is estimated using the heat transfer inverse problem method based on the measured mold temperature, and the change in the heat flux value is started. Find the moving average from the points,
From the calculated upper heat flux value and the moving average value, a difference in heat flux is determined for each casting direction, and the distance between the heat flux difference and the downstream thermocouple position at the thermocouple position on the upstream side of the casting and the casting distance are determined. Calculate the downstream thermocouple difference integrated value after the slab moving time obtained from the slab drawing speed, and when the integrated value is equal to or greater than a predetermined value, determine the occurrence of breakout due to solidified shell fracture as a continuous Breakout detection method for casting equipment. (3) Estimate a heat flux value from temperature information obtained from a plurality of thermocouples installed in a casting direction in a casting mold, and apply a frequency decomposition method to the time series change to remove disturbances (1) or (2). A method for detecting breakout in the continuous casting facility as described in the above.

[0011]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below with reference to the accompanying drawings. FIG. 1 is a diagram showing temperature detection points installed on a mold, and FIG. 2 is a conceptual diagram showing heat transfer between an inner surface of a mold and a mold water cooling groove. In FIG. 1, a mold 1 has a temperature detection line 2, and a plurality of thermocouples 3a (upper temperature detection points) and 3b (lower temperature detection points) are arranged at appropriate intervals in the casting direction. It is connected to a computer (not shown) in which the heat conductivity of the mold material, the distance of the temperature measurement point from the inner surface of the mold, other heat flux values, temperature distribution, convection heat transfer amount, and other data and programs required for calculation are input. ing.

At this time, in order to obtain a heat flux value, a mold temperature distribution, and the like with high accuracy, a thermocouple 3 disposed upstream is used.
a is desirably installed near the liquid phase portion of the molten slag or near the solidification start point, and the thermocouple 3b disposed downstream is installed at the solidified shell portion. The thermocouples 3a and 3b may be arranged in the width direction in accordance with the width of the slab. In the mold 1, a mold water cooling mechanism and a cooling water temperature measurement mechanism are provided, and the measurement result of the temperature measurement mechanism is input to the computer.

As described above, the breakout is detected by measuring the heat flux on the inner surface of the mold from the mold temperature measured by the temperature measuring means embedded between the inner surface of the mold and the water cooling mechanism. Hereinafter, a method for obtaining these heat fluxes will be described. The heat flux in the mold was determined by James. V. Beck's method of nonlinear inverse heat transfer problem [Int. J. Mass. Tran
sfer, vol. 13, pp. 703-716], and a heat flux that can best explain the measured value of the temperature of the mold at one point embedded between the inner surface of the mold and the water cooling mechanism is sequentially obtained from the numerical solution of the unsteady heat transfer equation. In addition, the heat flux and the inner surface temperature of the mold obtained as a solution of the unsteady heat transfer difference equation are simultaneously determined.

In FIG. 2, considering only the one-dimensional heat transfer in the thickness direction of the mold, the equation governing the heat transfer from the inner surface of the mold to the mold water cooling mechanism is expressed by the following equation. ρCp∂T / ∂t = −∂ (λ∂T / ∂x) / ∂x (2) T (E, t) = Y (t) (3) λ∂T (F , T) / ∂x = hw (T (E, t) −Tw) (4) T (x, 0) = T0 (x) (5) where ρ is a mold material Density, Cp is the specific heat of the mold material,
x represents a vertical distance from the inner surface of the mold to the water cooling mechanism at an arbitrary position, E represents a vertical distance from the inner surface of the mold to the installation of the mold thermocouple, and Y represents a measured value of. F is the vertical distance from the mold inner surface 12 to the water cooling mechanism 13, and hw and Tw are
Shows the overall heat transfer coefficient and water temperature of water side cooling. T0 (x) indicates the initial temperature distribution in the vertical direction between the mold inner surface 12 and the mold water cooling mechanism 13, and is all set to room temperature immediately before the start of casting.

The square error between the mold temperature T (E, t) and the measured temperature Y (t) at the thermocouple measurement point calculated by the equations (2), (4) and (5) is expressed by the following equation (6). The heat flux q (t, 0) ≡λ∂T / ∂X _{X = 0} that minimizes this is determined from equation (6). F (q) = (T (E, t) −Y (T)) ² (6) ∂F (q) / ∂q = 0 (7) In the above description, FIG. Although the heat flux is obtained for the upper temperature measurement point, the heat flux at the measurement point can be obtained in the same manner even when there are three or more lower temperature measurement points or measurement points. The heat flux distribution in the mold direction is obtained by extrapolation using the obtained heat flux. The heat flux is a function of the position in the casting direction and of time, but is simply represented by qm.

The calculation for obtaining the heat flux is executed by a computer in accordance with the instructions in the flowchart shown in FIG. In step S31, the time t is set to zero, and in step S32, a minute time interval Δt is added to the time t to update the time. The heat flux qm on the mold surface and the mold inner surface temperature T (0, t) are calculated based on the measured values of the thermocouple read in step (1). The noise is removed by the frequency decomposition method of the output calculated in S35, and the reason will be described later.

Specifically, the above equation (5) is used as an initial condition,
Equation (2) is discretized and solved using equations (3) and (4) as boundary conditions. The mold temperature T (E, t) and the measured temperature Y at the thermocouple measurement point calculated by the equations (2) to (5)
The square error of (t) is calculated by the above equation (6). Partial differential coefficient for the heat flux of the aforementioned (7) the square as shown in equation error F (q) is modified according to the procedures of the following heat flow flux value q ₀ which is assumed to be close to zero. The calculated mold temperature at the mold temperature measurement point calculated using the assumed heat flux q ₀ as a boundary condition is T (E, t) 0, and the corrected heat flux q ₁
Let T (E, t) 1 be the calculated mold temperature value at the mold temperature measurement point calculated with the boundary condition as T (E, t) 1
Is Taylor-expanded about Δq≡q ₁ −q _{0 as} follows. T (E, t) 1 = T (E, t) 0+ (∂T (E, t) 0 / ∂q 0) · (q 1 -q 0) ···· (8)

Here, the sensitivity coefficient β0 is defined as follows. β0≡∂T (E, t) 0 / ∂q 0 = (T (E, t) 1-T (E, t) 0) / εq 0 ···· (9) where, epsilon is the q optimal This is a minute value set for searching for a value, for example, 0.001. Equation (8) and (9)
Substituting the equation into (7) and rearranging q ₁ gives the following. q ₁ = q ₀ + (T (E, t) 0−Y (t)) / β ₀ (10) By comparing q ₁ with q ₀ , if the following convergence judgment formula is satisfied, q
₁ is the desired heat flux. (Q ₁ −q ₀ ) / q ₀ <0.001 (11) In the case where the expression (11) is not satisfied, q is calculated according to the following expression (12) in the same procedure as above based on q _1. Perform the calculation of ₁ ,
The calculation is repeated until the expression (13) is satisfied, the heat flux q is determined, and at the same time, the mold inner surface temperature T (0, t) is calculated. q _i = q _i−1 + (T (E, t) _i−1 −Y (t)) / β _i−1 (12) i = 1,2,3 (q _i −q _{i -1} ) / q _i-1 <0.001 (13) i = 1, 2, 3,.

According to the above method, the heat flux distribution q in the mold direction is obtained.
m, the heat flux estimate calculated from the upper thermocouple fluctuates beyond the limit value a, and the heat flux estimate calculated from the lower thermocouple within the delay time caused by the progress of casting is subsequently limited. It can be determined that a breakout occurs when the value f2 or more fluctuates. It is effective to apply covariance, which is the product of the deviation of two heat fluxes, as a method for more clearly capturing this variation. Furthermore, since this covariance value is a value obtained by integrating two calculated values, the number of determination constants can be reduced, and the load of adjusting the constants can be reduced.

The following description will be made using an example of a constraint breakout caused by an increase in the value of the heat flux. Constraint breakout will be described with reference to FIGS. 1 and 4 by detecting a solidification break occurring during initial solidification in a mold. FIG. 4 shows an example of a heat flux detection sequence in the mold direction estimated from a plurality of temperature detection point sequences in the casting direction shown in FIG. Since molten steel directly contacts the mold at the solidification fracture part, when it passes near the temperature detection line, the time-series change of the heat flux estimated from the temperature detection is shown in FIG.
As shown in (a), the heat flux change patterns similar to each other, ie, a large rise from the normal heat flux and a return to the original heat flux, appear sequentially as the judgment position is passed. With respect to this time change pattern, when the time series change of the heat flux at the temperature detection point is translated in the future direction on the time axis so that the time delay due to the drawing becomes zero, as shown in FIG. Heat flux changes appear at the same timing, and this heat flux change is increased from the normal heat fluxes A (t) and B (T), that is, the deviation Δ
Supplement with qmA (t) and ΔqmB (t). And calculated by the product of the deviations ΔqmA (t) and ΔqmB (t),
As shown in FIG. 4C, the so-called covariance value N (t)
It becomes a large value only when the solidified shell breaks through.

A detailed method of the determination will be described below with reference to FIG. If the covariance value at time t is N (t),
When expressed by a mathematical expression, it can be expressed as the following expression (14). Tv (t) in the equation indicates that the time is v (t) seconds before t, which corresponds to a parallel movement on the time axis. Then, the heat flux time delay between the temperature detection points due to the drawing speed is expressed, and it is expressed by the following equation (17). The normal heat flux is set to the lower of the heat flux at that time and the first-order lag heat flux so that the above-mentioned ΔqmA (t) and ΔqmB (t) become large only when abruptly increasing.

When this is expressed by a mathematical formula, the following (18) and (1)
Equation 9) is obtained. The first-order lag heat flux in the equation is the sampling heat flux A (t), B estimated this time at the temperature detection point.
(T) and the heat flux C (t−
Δt), D (t−Δt) and the first-order lag coefficient, the following (2)
0) and (21). If this time constant is made longer than the duration of the portion where the heat flux rises at the temperature detection point, it is possible to easily capture the change in the heat flux due to the passage through the broken portion of the solidified shell. The constant that needs to be adjusted by the above equation is 1
With only the next transfer time constant, this value can be easily determined from the heat flux change pattern.

N (t) = ΔqmA (t−v (t)) × ΔqmB (t) (14) ΔqmA (t) = A (t) −C (t) (15) ΔqmB (t) = B (t) −D (t) (16) v (t) = L / W (t) (17) where ΔqmA (t): upper side at time t Heat flux deviation at the temperature detection point ΔqmB (t): Heat flux deviation at the lower temperature detection point at time t A (t): Heat flux at the upper temperature detection point at time t B (t): At time t Heat flux at lower temperature detection point v (t): Time delay of heat flux between temperature detection points due to drawing speed at time t L: Distance between temperature detection points (heat flux estimation point) W (t): Time Slab drawing speed at t

C (t) = min (A (t), E (t)) (18) D (t) = min (B (t), F (t)) (19) ) Is calculated. Here, C (t): normal heat flux at the upper temperature detection point at time t D (t): normal heat flux at the lower temperature detection point at time t The first-order lag heat flux in the equation is expressed by the following equation. E (t) = ALFA × A (t) + (1−ALFA) × C (t−Δt) (20) F (t) = ALFA × B (t) + (1−ALFA) × D (T−Δt) (21) ALFA (t) = 1 / (1 + TAU / Δt) (22) where E (t) is a first-order lag heat flow at the upper temperature detection point at time t. Flux F (t): First-order lag heat flux at the lower temperature detection point at time t ALFA: First-order lag constant at time t Δt: Sampling period TAU: First-order lag constant at time t

The first-order lag heat flux E (t) (or F (t)) and the detected heat flux A obtained by the above equations (20) and (21)
From the relationship with (t) (or B (t)), the heat flux C (t) (or D (t) in the normal state is changed to the above (18) and (1).
The first-order lag heat flux calculated from the equation (9) and defined by the equations (20) and (21) is given by the following equations (20-2) and (21-).
The determination can be made even if the normal heat flux is calculated from the moving average heat flux defined by the equation (2).

[0026]

(Equation 1)

E '(t): Moving average heat flux at the upper temperature detection point at time t F' (t): Moving average heat flux at the lower temperature detection point at time t n: Calculation of moving average Number of samples going back to time

The reason will be described with reference to FIG. Figure 1
FIG. 8 shows an example in which a change in the heat flux in a normal state is calculated from a time-series change in a certain heat flux. (A) in the figure is (2)
Normal heat flux value C (t) (or D (t)) calculated from first-order lag heat flux E (t) (or F (t)) calculated from equations (0) and (21). And the heat flux A (t) (or B (t)) at the temperature detection point, and (b) is calculated from the moving heat flux calculated from the equations (20-2) and (21-2). The heat flux value C (t) (or D (t)) at normal temperature and the heat flux A (t) (or B (t)) at the temperature detection point. The solid line in the figure indicates the heat flux A (t) (or B (t)) at the temperature detection point.
Is the heat flux value C (t) (or D
(T)). From this figure, it is confirmed that the change of the heat flux can be similarly captured by using the first-order lag value and the moving average value. Moving average heat flux E '
When predicting the occurrence of a breakout using (t) (or F ′ (t)), the above equations (14) to (19) can be used as they are, and the first-order lag heat flux is calculated. Equations (20) and (21)
By changing to the expressions 0-2) and (21-2), it is possible to predict the occurrence of a breakout. If the time series transition of the covariance value obtained by the method described above is larger than the preset limit value of restrictive breakout, it is recognized as restrictive breakout. By predicting that a part will break out immediately after passing the mold, it is possible to predict the occurrence in advance.

A processing flow for predicting and preventing occurrence of restrictive breakout will be described with reference to FIG. In the figure, reference numeral 100 denotes the heat fluxes A (t) and B (t) detected by the temperature detection sequence in the mold and the casting pulling speed W (t) detected by the pinch roll of the continuous casting machine. The covariance unit 101 calculates the instantaneous covariance value N (t). 101 operates the operator by outputting the covariance value N (t) calculated by the covariance unit 100 to the operation monitoring screen as an index of solidification fracture. In addition to prompting the user to recognize the situation, when the covariance value N (t) is larger than the restrictive breakout occurrence limit value T0 when compared with a preset restrictive breakout occurrence limit value,
Upon receiving the covariance value N (t) from the restrictive breakout occurrence predicting unit 101, the restrictive breakout occurrence predicting determination unit 102 for predicting the occurrence of the restrictive breakout, decelerates and stops the drawing as necessary. To prevent the occurrence of the breakout of the restrictive breakout beforehand.

The processing flow of the covariance value N (t) 100 will be described with reference to the flow charts shown in FIGS.
FIG. 6 is a processing flow of the covariance value N (t) 100 when the first-order lag heat flux E (t) (or F (t)) obtained by the equation (20-2) or (21-2) is used. is there. First, the mold heat fluxes A (t) and B (t) detected at the temperature detection points 3a and 3b of the mold 1 and the drawing speed of the slab measured by the pinch roll are read (S61). The time delay between the temperature detection points due to the drawing speed W (t) at the read time t, that is, the time v (t) in which the position of the slab passes through the temperature detection point 3a and reaches the temperature detection point 3b.
Is calculated by the equation (17) (S62). And
Based on the preset sampling period Δt of the temperature detection points 3a and 3b and the first-order lag constant TAU at the time t, the first-order lag coefficient ALFA is calculated by the equation (22) (S63). The normal heat flux (C (t−Δt), D (t−Δt)) obtained at the previous sampling, and the heat flux A (t) · at the temperature detection points 3a and 3b at the current sampling. B (t), the primary delay constant AL calculated above
Based on the FA, the time t is calculated according to the equations (20) and (21).
First order heat flux E (t) F (t) at the temperature detection point at
Is calculated (S64, S65). The two primary lag heat fluxes E (t) and F (t) and the mold heat fluxes A (t) and B (t) at the temperature detection points read in S41 are used to calculate the equations (18) and (19). The normal value of the heat flux C (t),
D (t) is obtained (S66). The normal heat flux obtained in this way is stored (S67) and used for S64 at the next sampling.

Then, the covariance N
(T) is calculated (S68, S69), and this schematic diagram is shown in (a) and (b) of FIG. That is, from the time t, the mold heat flux A (tv) measured at the temperature detection point before the time delay v (t) between the temperature detection points.
The deviation ΔqmA (t−v (t)) between (t)) and the normal heat flux C (t−v (t)) is obtained by the above equation (15) (S68). Next, the deviation ΔqmA (t−v (t))
And ΔqmB (t) are integrated, that is, the covariance N (t) is calculated by the above equation (14) (S69), stored and output to the operation status monitoring screen to prompt the operator to recognize the operation status, It outputs to the restrictive breakout occurrence prediction unit 101 and the restrictive breakout prevention control unit 102.

On the other hand, FIG. 19 shows (20-2) or (2)
1-2) Moving average heat flux E '(t) obtained by equation (1)
(Or F ′ (t)) using the covariance value N
It is a processing flow of (t) 100. First, the mold heat flux A (t) detected at the temperature detection points 3a and 3b of the mold 1
Read the drawing speed of the mold measured with B (t) and the pinch roll (S181). The time delay between the temperature detection points due to the drawing speed W (t) at the read time t, that is, the time v (t) at which the position of the slab passes through the temperature detection point 3a and reaches the temperature detection point 3b is defined as the above-mentioned value. It is calculated by equation (17) (S182).

Then, the normal heat flux (C (t−Δt), D (t−Δt)) obtained at the previous sampling, and the heat flux A (t) at the temperature detection points 3a, 3b at the current sampling. ), B (t), the formula (20-2) and (21-
The moving average heat flux E '(t) at the temperature detection point is obtained by the equation 2)
(Or F ′ (t)) is calculated (S183). Then, the moving average heat fluxes E '(t) and F' (t), and the mold heat fluxes A (t) at the temperature detection points read in S41,
At B (t), heat fluxes C (t) and D (t) having normal values are obtained from the above equations (18) and (19) (S184, S18).
5). The normal heat flux obtained in this way is stored (S186), and used in S184 at the next sampling.

Then, the covariance N
(T) is calculated (S187, S188).
This schematic diagram is shown in FIGS. That is,
The time delay v (t) between the temperature detection points from the time t
The mold heat flux A (tv) measured at the temperature detection point before
The deviation ΔqmA (t−v (t)) between (t)) and the normal heat flux C (t−v (t)) is obtained by the above equation (15) (S187). Next, the deviation ΔqmA (t−v
(T)) and ΔqmB (t), that is, (14)
The covariance N (t) is calculated by the formula (S188), stored and output to the operation status monitoring screen to prompt the operator to recognize the operation status, and to restrict the breakout occurrence prediction unit 10
1 and the restrictive breakout prevention control unit 102.

Next, the processing flow of the restrictive breakout occurrence prediction judging section 101 will be described with reference to the flowchart shown in FIG. This schematic diagram is shown in FIG. First, the covariance value N (t) calculated by the covariance value calculation unit 100 is read and recognized as an index of solidification shell fracture (S71), and the value is determined to be within a preset limit value of restrictive breakout occurrence. Is determined (S72), and if it is within the constraint breakout occurrence limit, no constraint breakout occurrence prediction is set (S73). If the constraint breakout occurrence limit is exceeded, constraint breakout occurrence prediction is performed. The presence is set (S74). Then, as shown in FIG. 5, the prediction result of the occurrence of the restrictive breakout is output to the operation status monitoring screen to prompt the operator to recognize the operation status, and is output to the restrictive breakout prevention control unit 102.

Further, the processing flow of the restrictive breakout prevention control unit 102 will be described with reference to the flowchart shown in FIG. First, the restraint breakout occurrence prediction determination result stored in the restraint breakout occurrence prediction determination unit 101 is read (S81), and it is determined whether there is no restraint breakout occurrence prediction or restraint breakout occurrence prediction (S82). If the information is the prediction of occurrence of restrictive breakout, the covariance value set in the covariance value calculation unit 100 is read (S83), and the drawing speed set in advance according to the value of the numerical value is determined. Is selected to instruct deceleration or stop to the above-mentioned drawing speed (S84). That is, when a solidification fracture is detected, a time is secured so that the solidification fracture recovers in the mold and suppresses occurrence of restrictive breakout.

[0037] In addition, in this determination method, in the initial solidification in the mold, when the powder abnormally flows between the mold and the molten steel, or when a large inclusion is caught in the surface of the solidified shell, only that portion is used. Heat is not sufficiently removed by cooling the mold, and as a result, the growth of the solidified shell is insufficient. After the thin part of this solidified shell has come out of the mold by drawing the slab,
Without being able to withstand the static pressure of the molten steel in the unsolidified portion inside, the large inclusions fall off and at the same time, the solidified shell of the slab surface breaks, causing a breakout of inclusions in which the molten steel flows out. 3a, 3b for the inclusion breakout
The change also appears in the mold heat fluxes A (t) and B (t) detected at (2) (the heat flux is reduced due to insufficient heat removal), so that application is possible. When the inclusion breakout occurs, the heat flux value is reduced due to the above-mentioned poor heat removal.

As shown in FIG. 12, in the case of the inclusion breakout, the change of the heat flux estimated from the thermopile train in the mold significantly changes in the negative direction as compared with the case of the constraint breakout. Therefore, in order to judge and predict the inclusion property breakout there, the above-mentioned (14)
(18-2) and (19-2) are used in place of (17) and the equations (18) and (19), and the above (20) to (22) are applicable. Become. In the case of the inclusion breakout, the process flow has only a negative change in the heat flux change, and as shown in FIGS. C (t) = max (A (t), E (t)) (18-2) D (t) = max (B (t), F (t)) (19- 2) The moving average heat flux E '(t) (or F')
When predicting the occurrence of a breakout using (t)), the above-described equations (14) to (17) and (18-1) and (18-2) are used as they are, and the first-order lag heat flux is calculated. Expressions (20) and (21) are directly used as (20-
By changing the equations (2) and (21-2), it is possible to predict the occurrence of breakout (this covariance unit 1
00 is shown in FIG. 20).

Further, in the present invention, a short period heat flux fluctuation is removed by a frequency decomposition method such as a wavelet transform, and a breakout is detected to further improve the detection accuracy. The reason will be described with reference to FIGS. As mentioned earlier, breakouts occur when the crack depth exceeds a certain critical depth, making it impossible to ensure a sound solidified portion thickness. Further, when the cracks become deeper, the thickness of the solidified shell, which becomes the heat transfer resistance, changes greatly, so that the heat flux in the mold direction changes greatly. FIG. 9 shows the distribution of the length of the vertical crack when a breakout occurs. It can be seen from FIG. 9 that when the breakout occurs, a vertical crack of 10 cm or more always occurs. Since the drawing speed of the slab is about 2.5 cm / sec, in this verification, even if a short cycle of 4 seconds or less is removed, deep cracks that cause breakout can be prevented by changing the heat flux. The evaluation enables detection.

FIG. 17 shows a covariance value N representing a change in heat flux when noise filtering is performed.
The relationship between (t) and the crack depth is shown by evaluating the accuracy of predicting the crack depth index by performing noise filtering by the frequency decomposition method. The vertical axis in the figure is a crack depth index, which is defined as a dimensionless depth when the critical depth at which breakout occurs is set to 1. The horizontal axis indicates the covariance value N (t) of the heat flux when casting. (A) in the figure is a comparison of the covariance value calculated from the data of the sampled heat flux in a 1-second cycle on the horizontal axis, and (b) in the figure is a high-frequency of 4 seconds or less by the frequency decomposition method. The horizontal axis represents the covariance value N (t) calculated when filtering the frequency domain and removing noise.

Although there is no correlation between the covariance value N (t) and the crack depth index in (a), the covariance value N (t) and the crack depth under the condition (b). There is a positive correlation with the index. The reason for this is that the change in the covariance value N (t) in (a) is affected not only by the deepening of the cracks but also by the change in the heat transfer resistance due to the powder film thickness and air gap generation. Since t) changes, it is estimated that there is no correlation with the crack depth index.

On the other hand, as for (b) in the figure, the change of the heat transfer resistance due to the powder film thickness and the air gap generation is a change of about one second, and the change of the heat transfer resistance is governed by the influence of the crack depth. Therefore, it is considered that there is a correlation. In the present invention, the covariance value N
By setting the threshold of (t) as shown in FIG. 12, breakout occurrence prediction judgment can be performed.
That is, 4 is not caused by the crack depth shown in FIG.
By filtering out high-period noises within seconds, the accuracy of breakout determination is further improved. on the other hand,
If this threshold value is set low, the chance of determining a breakout increases, and the determination accuracy decreases. Further, the embodiment can be implemented by providing a step of removing noise in S35 of the flow of FIG.

An embodiment will be described with reference to FIGS. 10 and 11 show the heat transfer behavior when a breakout occurs. FIG. 10 shows the heat transfer behavior at the time of occurrence of the constraining breakout, and FIG. 11 shows the heat transfer behavior at the time of occurrence of the inclusion breakout. In both figures, the upper part (a) shows the temperature change at the temperature detection point, the middle part (b) shows the time series change of the heat flux at the temperature detection point calculated by S31 to S34 in the flow of FIG. 3, and the lower part (c) ) Is S in the flow of FIG.
35 shows a time-series change of the heat flux when the noise calculated by 35 is removed. Rather than evaluating from the temperature at the temperature detection point from these figures, it is possible to improve the detection accuracy of breakout occurrence by capturing the change in the heat flux when the noise is further removed from the change in the heat flux You can say that.

FIG. 12 is a diagram for evaluating the detection accuracy of the detection of the restrictive breakout according to the present invention. The left side of FIG. 12 shows the covariance value calculated according to the flow of FIG. 6 when no breakout occurs. The right-hand side shows the time-series change of N (t), while the right-hand side shows the time-series change of the covariance value N (t) at the time of the breakout calculated by the above method. The upper part (a) of FIG. 12 shows the time series change of the covariance N (t) value calculated using the temperature change at the temperature detection point calculated by the technique disclosed in Japanese Patent Application Laid-Open No. 9-108801. The middle part (b) shows a time series change of the heat flux covariance value N (t) at the temperature detection point calculated without removing the short cycle of 4 seconds or less by the treatment of S35 shown by the broken line in FIG. Further, the lower row (c) shows the time when the covariance value N (t) of the heat flux at the temperature detection point calculated by performing the removal of the short cycle of 4 seconds or less by the treatment of S35 shown by the broken line in FIG. Indicates a series change. It should be noted that (a) to (c) on the left and (a) to (c) on the right in FIG.
Are based on the measurement data at the same location and at the same timing, respectively, and in FIGS. 3A to 3C in the right-hand side, a crack at which the starting point of the restrictive breakout occurs at a time of -32 seconds is shown. It is.

If the constraint breakout is to be predicted using the covariance value of the temperature as in the prior art shown in FIG.
As shown in the figure, the maximum covariance value of the temperature in the case where the restrictive breakout in the left diagram did not occur (70 at time-78 seconds).
0) may be larger than the covariance value (370 when the time is −32 seconds) when the right constraint breakout occurs, so that the constraint breakout as shown in the right diagram of FIG. In order to detect, the detection threshold is set to 37
It must be set to 0 or less (for example, the threshold value 1 shown in (a)), and (a) excessive detection may occur even when no breakout occurs as shown in the left diagram.

On the other hand, as in the present invention, when a constrained breakout is detected based on a time-series change in heat flux at a temperature detection point as shown in FIG. Since the covariance value of the heat flux is smaller than when the constraint breakout did not occur, it is larger than when the constraint breakout did not occur, and smaller than when the constraint breakout occurred. If a threshold value is set for the value (for example, threshold value 2 in (b)), it is possible to normally detect the occurrence of restrictive breakout.

Further, S35 shown by the broken line in FIG.
In the case where the short period of the heat flux of 4 seconds or less is removed by the above treatment, as shown in FIG. 12C, the difference between when the restraint breakout occurs and when it does not occur appears more remarkably. Therefore, it is possible to detect the restrictive breakout with higher accuracy. FIGS. 12A to 12C are diagrams showing the case of the restrictive breakout. However, even in the case of the inclusion breakout as described above, FIGS.
As shown in (c), it was confirmed that the direction of change of the heat flux waveform was only reversed, and the covariance value N (t) had the same tendency.

[0048]

As described above, according to the present invention, in the continuous casting operation, the occurrence of breakout caused by the outflow of molten steel from the broken solidified shell can be predicted, and the occurrence can be prevented. The detection accuracy can be significantly improved as compared with the conventional method.

[Brief description of the drawings]

FIG. 1 is a diagram showing temperature detection points installed on a mold.

FIG. 2 is a view showing a concept of heat transfer between a mold inner surface and a mold water cooling mechanism.

FIG. 3 is a flowchart showing application of a heat transfer inverse problem method;

4A is a diagram showing a change in heat flux at the time of passing through a fractured portion of a solidified shell; FIG. 4B is a diagram showing a correction of a time delay of a heat flux of a mold; and FIG. 4C is a diagram showing a change in heat flux as a covariance value. Figure

FIG. 5 is a block diagram of an example of a restrictive breakout prediction device.

FIG. 6 is an operation flow diagram of a constrained breakout covariance value calculation unit when a first-order lag heat flux is used.

FIG. 7 is an operation flowchart of a restrictive breakout occurrence prediction determining unit.

FIG. 8 is an operation flowchart of a restrictive breakout prevention control unit.

FIG. 9 is a diagram showing a crack length distribution when restrictive breakout occurs.

FIG. 10 shows (a) a time-series change in temperature for restraint breakout; (b) a diagram showing the time delay of the mold heat flux corrected; (c) a short-period noise of 4 seconds or less removed. Showing time-series changes of heat flux

11A and 11B are diagrams showing a time series change in temperature, and FIG. 11B is a diagram showing the time delay of the heat flux of the mold corrected. Showing time-series changes of heat flux

FIG. 12 is a diagram showing a time-series change of a covariance value of temperature during normal casting (left) and a time of occurrence of a breakout (right); and (b) a diagram showing a time-series change of covariance value of heat flux. (C) A diagram showing a time series change of the covariance value of the heat flux when the short-period noise of 4 seconds or less is removed.

13A is a diagram showing a change in heat flux when passing through an inclusion biting portion. FIG. 13B is a diagram showing a correction of a time delay of a mold heat flux. FIG. 13C is a diagram showing a change in heat flux as a covariance value. Figure

FIG. 14 is an operation flowchart of the inclusion property breakout covariance value calculation unit when the first-order lag heat flux is used.

FIG. 15 is an operation flowchart of the inclusion property breakout occurrence prediction judgment unit.

FIG. 16 is an operation flowchart of the inclusion property breakout prevention control unit.

FIG. 17 shows a relationship between a crack depth and a covariance value N (t). (A) A diagram showing a case where the frequency decomposition method is not applied. (B) A high period noise within 4 seconds by applying the frequency decomposition method. Diagram showing the result of removing

FIG. 18 is a diagram showing time-series changes at a normal time and at a temperature detection point when (a) a first-order lag value and (b) a moving average value are used.

FIG. 19 is an operation flow diagram of a restrictive breakout covariance value calculation unit when a moving average heat flux is used.

FIG. 20 is an operation flowchart of the inclusion property breakout covariance value calculation unit when the moving average heat flux is used.

[Explanation of symbols]

 1 Mold 2 Molten metal 2a Mold temperature detection row (center of short side of mold) 2b Mold temperature detection row (center of long side of mold) 2c Mold temperature detection row (center of long side of mold) 2d Mold temperature detection row (long side of mold) Edge) 3a Mold upper temperature detection point 3b Mold lower temperature detection point 4 Solidification break 5 Solidification shell 11 Cast piece 12 Mold inner surface 13 Water cooling mechanism 16 Upper temperature detection point

Continuing from the front page (72) Inventor Koichi Hirai 1 Nishinosu, Oita, Oita City, Oita Prefecture Nippon Steel Corporation Oita Works (72) Inventor Masayoshi Ono 1 Nishinosu, Oita, Oita City, Oita Prefecture Nippon Steel Corporation F-term in Oita Works (reference) 4E004 MC12 PA07

Claims (3)

[Claims] 1. A method for measuring a mold temperature by a plurality of temperature measuring means embedded in a mold and detecting an abnormality in a mold casting based on a measured value of the mold temperature. The mold temperature is measured by the temperature measuring means, and the heat flux on the inner surface of the mold at each measurement point is estimated using the heat transfer inverse problem method based on the measured mold temperature value, and the change in the heat flux value is determined as the change starting point. From the calculated upper heat flux value and the first-order lag value to determine the difference in heat flux for each casting direction. The difference between the heat flux difference at the thermocouple position on the upstream side of casting and the downstream The downstream thermocouple difference integrated value after the slab moving time obtained from the distance between the side thermocouple positions and the slab drawing speed determined from the slab drawing speed is calculated, and when the integrated value is equal to or greater than a predetermined value, the solidified shell breakage occurs. That a breakout caused by A method for detecting breakout in continuous casting equipment. 2. A method for measuring a mold temperature by a plurality of temperature measuring means embedded in a mold and detecting an abnormality in a mold casting based on a measured value of the mold temperature. The mold temperature is measured by the temperature measuring means, and the heat flux on the inner surface of the mold at each measurement point is estimated using the heat transfer inverse problem method based on the measured mold temperature value, and the change in the heat flux value is determined as the change starting point. From the calculated upper heat flux value and the moving average value to determine the difference in heat flux for each casting direction, the heat flux difference at the upstream thermocouple position and the downstream thermoelectric value. Calculate the downstream thermocouple difference integrated value after the moving time of the slab obtained from the distance between the paired positions and the slab drawing speed, and when the integrated value becomes a predetermined value or more, due to solidification shell fracture. What happens when a breakout occurs A method for detecting breakout in continuous casting equipment. 3. The method according to claim 1, wherein a heat flux value is estimated from temperature information obtained from a plurality of thermocouples arranged in a casting direction in the mold, and a time-series change is subjected to a frequency decomposition method to remove disturbance. Item 3. A method for detecting breakout in a continuous casting facility according to item 1 or 2.