JPH02179819A - Cooling controller for hot-rolled steel sheet - Google Patents

Abstract

PURPOSE:To obtain the controller capable of keeping the warpage of a hot steel being cooled within control limits by controlling the amt. of cooling water to be sprayed from nozzles provided on the upper and lower faces of the hot steel sheet, and determining the water cooling time in accordance with the obtained water amt. sprayed to the upper and lower faces. CONSTITUTION:The relation between the amt. of cooling water to be sprayed from the nozzles 7c arranged on the upper face and the heat transfer rate of the hot steel sheet 1 is obtained by a first arithmetic means based on the previously given physical properties of the sheet 1 such as its quality, thickness, width, and length. The relation between the amt. of cooling water to be sprayed from the nozzle 7c arranged on the lower face and the heat transfer rate of the hot steel sheet 1 is obtained in the same way by a second arithmetic means. The warpage is calculated by a warpage arithmetic means from the temp. history of the hot steel 1 based on the obtained relations from the 1st and 2nd arithmetic means. Meanwhile, the amts. of water to be sprayed from the nozzles 7c provided of the upper and lower faces are controlled by a cooling water control means so that the obtained warpage is kept within control limits, and the water cooling time is determined in accordance with the obtained amts. of water sprayed to the upper and lower faces.

Description

[Detailed Description of the Invention] [Objective of the Invention] (Industrial Application Field) The present invention provides a method for cooling a hot-rolled steel plate by blowing cooling water from both the upper and lower surfaces, so that the steel plate does not suffer from shape defects. In order to avoid this and obtain the desired material quality,
The present invention relates to a cooling control device for a hot rolled steel plate that optimally controls the amount of cooling water injected from both sides.

(Prior Art and Problems to be Solved by the Invention) In recent years, high-temperature thick steel plates immediately after hot rolling are rapidly cooled (accelerated cooling) with water to obtain a quenching effect, and control to impart high strength properties to the steel plates has been developed. A steel plate manufacturing device is in operation that includes a process called cooling.

This steel plate manufacturing apparatus enables controlled cooling immediately after rolling to produce steel plates with excellent usability.

However, in such conventional steel sheet manufacturing equipment, due to the imbalance of cooling from the top and bottom surfaces of the steel sheet during accelerated cooling, shape defects due to warping in the sheet width direction occur more than with conventional air cooling. It has the disadvantage of being easy. The occurrence of this shape defect is caused by a difference in cooling rate due to a difference in the behavior of cooling water injected from the upper and lower surfaces of the steel plate.

If each part of the steel plate is cooled at different cooling rates in this way, asymmetrical internal stress is generated in the thickness direction of the steel plate, resulting in deterioration of the shape of the product.

Further, in severe cases, there were problems such as not only poor shape but also differences in mechanical properties between the upper and lower surfaces. Conventionally, methods for preventing the occurrence of such shape defects include measuring the temperature of the upper and lower surfaces of the steel plate during water cooling, predicting the amount of deformation from the temperature difference, and controlling the amount of water injected into the upper and lower surfaces of the steel plate to prevent deformation. There is technology to control this.

However, a method for controlling the amount of water injected is not presented, and the effect on the cooling end temperature when changing the amount of water injected into the upper and lower surfaces of the father is not considered.

The present invention has been made in view of such conventional problems, and it is an object of the present invention to ensure a predetermined cooling end temperature due to the material, and to keep the amount of warpage of the hot steel plate within the specified value during water cooling. The present invention aims to provide a cooling control device for a hot rolled steel plate having a function of controlling the amount of cooling water injected from the upper and lower surfaces.

(Means for Solving the Problems) The present invention for achieving the above object includes a finishing rolling mill that rolls a heated steel plate to a predetermined thickness, and a finishing rolling mill that is arranged in a downstream process of the finishing rolling mill and is conveyed. A cooling device that injects cooling water from a plurality of nozzles arranged in the width direction of the heated steel plate from both the upper and lower sides of the heated steel plate to cool the heated steel plate while conveying the steel plate. In the manufacturing device, a first calculation for determining the relationship between the amount of cooling water injected from a nozzle arranged on the upper surface of the cooling device and the heat transfer coefficient of the hot steel sheet based on various physical property values of the hot steel sheet given in advance. means, second calculation means for determining the relationship between the amount of cooling water injected from a nozzle arranged on the lower surface of the cooling device and the heat transfer coefficient of the hot steel plate, and the first calculation means and the second calculation means calculating means for calculating the history of the temperature distribution in the thickness direction of the hot steel plate during the cooling process from the relationship between each heat transfer coefficient and the amount of cooling water; and calculating the amount of warpage in the width direction of the hot steel plate from the temperature distribution history. Based on the total warpage calculation means to be calculated and the amount of warpage determined by the total warpage calculation means, the amount of cooling water injected from each of the nozzles arranged on the upper and lower surfaces is controlled so that the amount of warpage is within a specified value. The cooling water amount control means is characterized in that it has a cooling water amount control means.

(Function) The present invention having the above configuration functions as follows.

The first calculating means calculates the temperature from a nozzle arranged on the upper surface based on various physical property values 1 of the hot steel plate given in advance, such as material, plate thickness, plate width, plate length, cooling start temperature, cooling stop temperature, etc. The relationship between the amount of cooling water to be injected and the heat transfer coefficient of the hot steel plate is determined. Then, the second calculation means as well as the first calculation means,
The relationship between the amount of cooling water injected from the nozzle arranged on the lower surface and the heat transfer coefficient of the hot steel plate is determined. The entire warpage calculation means is
Based on the relationship between the respective cooling water amounts and heat transfer coefficients determined by the first calculation means and the second calculation means, the amount of warpage of the hot steel sheet is calculated from the obtained temperature history of the hot steel sheet, and the cooling water amount control means The system controls the amount of cooling water injected from each nozzle arranged on the upper and lower surfaces so that the amount of warpage calculated by the total warpage calculation means is within the specified value, and also controls the amount of water injected to the upper and lower surfaces. The water cooling time will be adjusted accordingly.

Therefore, the amount of warpage of the hot steel sheet during cooling can be kept within the specified value, and a predetermined cooling end temperature can be ensured, so that it is possible to prevent the occurrence of shape defects due to warping in the width direction of the sheet during cooling. A predetermined material can be obtained.

(Example) FIG. 1 shows a part of a steel sheet production line equipped with a cooling control device for hot rolled steel sheets according to the present invention.

As shown in the figure, the steel plate production line includes a heating furnace 2 that maintains the temperature of the hot steel plate 1 being conveyed, a scale breaker 3 that removes scale formed on the surface of the hot steel plate 1, and a target plate. A rough rolling mill 4 that performs tentering rolling to a width is sequentially installed, and the hot steel plate 1 is scale-removed in the steps up to this point and is assembled to a predetermined width and thickness. The post-process of the rough rolling mill 4 includes a finishing mill 5 that rolls the hot steel plate 1 to the target thickness, a hot straightening machine 6 that straightens the shape of the hot steel plate 1 after finishing rolling, and a hot straightening machine 6 that straightens the shape of the hot steel plate 1 after finishing rolling. Cooling devices 7 for accelerating cooling of the hot steel plate 1 are sequentially arranged, and the hot steel plate 1 after being acceleratedly cooled becomes a product having a desired shape and desired material.

FIG. 2 is a diagram showing the arrangement of measuring instruments for measuring the temperature and shape of the hot steel plate 1 being transported, and the internal structure of the cooling device.

A finishing rear surface thermometer 11 is provided on the rear surface of the finishing rolling mill 5 to measure the temperature of the heated steel sheet 1 to be finish rolled. moreover,
A cooling device front thermometer 13 is provided on the front side of the cooling device 7, and measures the temperature of the hot steel plate 1 just before being conveyed to the cooling device 7. Further, a cooling device rear surface thermometer 14 and a shape meter 15 are provided on the rear surface of the cooling device 7 to measure the temperature and shape of the heated steel plate 1 after being cooled by the cooling device 7.

Further, inside the cooling device 7, as shown in the figure, a large number of nozzle groups 7c, 7c, . The injection of cooling water from these nozzle groups 7c is controlled by flow control valves 8, 8 . 6 of Z1 to Z6 by ...
The cooling process is divided into two cooling zones. In other words, the number of zones to be used differs depending on various conditions such as the thickness and length of the hot steel plate 1 to be cooled, cooling start temperature, cooling stop temperature, etc., so it is divided into six zones and the number of zones is divided into six zones. The number of zones used can be adjusted according to the situation. The amount of water in each cooling zone can be adjusted separately for the top and bottom sides. In addition, optical fibers are used to radiate light on the upper and lower surfaces of the entrance side of the cooling device 7, between the 3rd and 4th zones, between the 4th and 5th zones, and between the 5.6th and 5th zones. Thermometer pair (hereinafter referred to as optical fiber thermometer pair'>20.21,22.
23 is provided to detect the temperature of the upper and lower surfaces of the hot steel plate 1 in the cooling process.

FIG. 3 is a diagram showing the arrangement of thermometers and nozzles in the cooling device 7.

As mentioned above, the optical fiber thermometer pair 20 is located near the entrance of the cooling device 7, and the optical fiber thermometer pair 21 is located near the inlet of the cooling device 7.
Between the zones, a pair of optical fiber thermometers 22 is disposed between zones 4 and 5, and a pair of fiber optic thermometers 23 is disposed between zones 5 and 6, respectively. Nozzle 7 of each zone
Control of the amount of cooling water etc. injected from c is performed by each of the aforementioned flow control valves 8.

FIG. 4 is a schematic configuration diagram of a control system of a cooling control device for hot rolled steel sheets according to the present invention.

The cooling control computer 30 that performs general control of cooling in the cooling device 7 (controls the amount of water from each nozzle arranged on the upper and lower surfaces) includes a rolling control computer 31 that performs general control of the rolling mill. , inputs and displays various data output from the business computer 32 that mainly performs production management and the cooling control computer 30, and also outputs control correction data etc. from the operator to the cooling control computer 30. A data input/output device 33 is connected, and the cooling control computer 30 operates various control devices described below based on data from these computers 31, 32 and the data input/output device 33. Further, a cooling data learning calculation computer 36 is connected to the cooling control computer 30,
When cooling the hot steel sheet 1, the method of setting the amount of cooling water injected from each nozzle and the sheet passing speed is learned, and the results of the learning are output to the cooling control computer 30. The cooling control computer 30 then controls the hot steel plate 1.
a mask control device 37 that corrects the cooling rate that differs between the peripheral edges and the central portion when cooling the hot steel plate 1;
A cooling water flow control device 38 that controls the flow rate control valve 8 disposed in each zone as shown in FIG. The cooling control computer 30 calculates and controls the amount of mask, the amount of cooling water, and the rate of sheet passing per sheet. Further, the shape data processing computer 34 that processes the shape data of the hot steel plate 1 outputted from the shape meter 15 is connected to the cooling data learning calculation computer 36, and the processed shape data is transferred to the cooling data learning calculation computer 36. 36. The shape data processing computer 34 stores each data after shape data processing (curvature in the board width direction (C
amount of warpage in the length direction of the steel plate, the amount of warpage in the length direction of the steel plate (L warp), the wave height and pitch of the side waves that occur in the length direction of the steel plate at the end of the light wave eye, and the center that occurs inside the steel plate in the length direction A display device 35 is connected to display the wave height and pitch of the partial wave shape, and the final shape of the steel sheet to be manufactured is displayed. This cooling data learning calculation computer 36 includes the aforementioned rolling control computer 31. Business computer 32, cooling device front thermometer 13. Cooling device rear thermometer 14. Optical fiber thermometer pair 20 disposed in the cooling device 7
23. Cooling water amount control device 38 and sheet threading speed control device 40
are connected, and learning calculations for performing cooling control are performed based on actual data output from these computers, thermometers, or devices.

FIG. 5 is a diagram showing the overall general operation of the cooling control device for hot rolled steel sheets according to the present invention.

The operation of this device can be roughly divided into two operations.

In order to avoid defects in the shape of hot steel sheets and to obtain the specified material quality, we have improved the accuracy of the settings for the cooling device and the setting operations that are performed before the material to be cooled reaches the cooling device. The purpose is to learn after cooling.

First, the settings of the cooling device will be explained.

The rolling control computer 31 records the rolling results of the hot steel plate 1 to be cooled, that is, the temperature before starting the finishing final rolling (hereinafter abbreviated as finishing temperature) inputted by the post-finishing surface thermometer 11, the sheet thickness, and the sheet width. The cooling control computer 30 performs an estimation calculation to estimate the temperature of each part of the hot steel plate 1 immediately before the cooling device 7. This estimation calculation is performed using the upper surface temperature (finishing temperature) of the heated steel plate 1 immediately before the start of final rolling inputted by the rolling control computer 31 or the target finishing temperature inputted by the business computer 32 (described later) as an initial value. Using 11 points divided into 10 parts of the total thickness at the above representative points as calculation target points, the temperature transition from the finishing final rolling to the entrance side of the cooling device 7 is calculated by solving a one-dimensional heat conduction difference equation. In addition, the representative point is
The calculation is carried out at one point in the flat direction of the plate, but taking the plate length into account, the calculation predicted arrival time of each part is different, and the calculation is performed at the leading edge in the conveyance direction.

Three points are set, one in the center and one in the tail. In addition, when performing this calculation, the temperature change due to heat conduction, the effect of temperature change due to the final finishing rolling of the finishing mill 5, transformation, the effect of temperature change due to the hot straightening machine 6, etc. are taken into consideration.

The business computer 32 also provides instruction information regarding cooling, namely, the amount of water on the lower surface of each zone in the target finish temperature cooling device 7, the target cooling start temperature when the hot steel plate 1 enters the cooling device 7, and the temperature at which the hot steel plate 1 enters the cooling device 7. The target cooling stop temperature when leaving the room, the number of zones used, information on the material composition of the board, and the board thickness.

Data such as plate width and plate length are output, and the cooling control computer 30 inputs these data to determine plate width, cooling stop temperature, average bottom surface age, and operational standard values predetermined for each usage zone. .

This operational standard value consists of an initial value when calculating the appropriate water and wastewater flow ratio to keep the amount of warpage in the width direction of the steel sheet after cooling below the allowable value, and various mask amounts. Incidentally, the water volume ratio is defined by the following formula, and if the bottom surface water volume and the water volume ratio are determined, the top surface water volume can be determined.

This is based on the following idea. Temperature control is necessary to control the material properties of the coolant (tensile strength, yield strength, elongation, etc.), and by predetermining the amount of water on the bottom surface,
Determine the plate temperature drop characteristics within the cooling device. On the other hand, in order to make the plate shape flat, it is desirable to make the temperature distribution in the thickness direction of the plate vertically symmetrical during cooling, and it is necessary to determine the amount of water on the top surface according to the amount of water on the bottom surface. Therefore, the water and wastewater volume ratio was adopted as a parameter.

Then, the cooling control computer 30 performs a temperature estimation calculation on the inlet side of the cooling system, and calculates the initial value of the water/sewage volume ratio given by the calculation result and the determined operational standard value, and the learning obtained by the temperature learning calculation described later. Based on the results, plate temperature estimation calculations are performed.

Then, stress strain estimation calculation is performed based on the calculation result of this plate temperature estimation calculation and the learning result of stress strain learning = 1'' calculation described later. Since this stress strain estimation calculation is complicated, the details of this calculation will be described later. Next, the cooling control computer 30 calculates the optimum vertical ratio of the amount of cooling water to be injected from the nozzles disposed on the upper and lower surfaces of the cooling device 7 based on the results obtained by the stress strain estimation calculation. By determining the optimum vertical ratio, the amount of water to be injected from the nozzle arranged on the top surface of the cooling device 7 is determined,
The calculation result is output to the cooling water amount control device 38. Further, on the basis of the results obtained by the sheet temperature estimation calculation, calculations are performed to set the optimum sheet threading speed when the hot steel sheet 1 is passed through the cooling device 7. The calculation result of this optimum sheet threading speed is output to the sheet threading speed control device 40, and the heated steel sheet 1 is conveyed inside the cooling device 7 at a speed based on this calculation result.

On the other hand, the cooling control computer 30 determines the mask amount for the tip, tail, and side ends of the steel plate based on the operating standard value, and this mask amount is output to the mask control device 37.

This control of the mask amount is performed to correct the difference in cooling conditions between the peripheral part of the hot steel plate 1 and other parts, and by this correction, any part of the hot steel plate 1 can be cooled in the same way. cooling will be performed. Note that since the determination of the mask device and the mask amount is not a control closely related to the present invention, a detailed explanation of the determination will be omitted hereafter.

Next, learning performed after cooling the hot steel plate 1 will be explained.

The cooling data learning computer 36 receives information about the plate such as components from the business computer 32 and the finishing surface thermometer 11, and the rolling control computer 31
The actual temperature of the heated steel plate 1 on the rear surface of the finishing rolling mill 5 manually inputted is input, and the temperature measurement calculation of the inlet side plate of the cooling device 7 is performed. In addition, the cooling data learning calculation computer 36 uses the actual temperature difference between the upper and lower surfaces of the hot steel plate 1 on the side of the cooling device 7, detected by the pair of optical fiber thermometers 20 on the cooling device 7 side, and the temperature difference detected by the cooling device front thermometer 13. Inlet side temperature learning is calculated based on the upper surface temperature of the hot steel plate 1 on the cooling device 7 person side and the measured value of the plate temperature setting calculation described above, and this learning result is used by the cooling control computer 30 at the time of setting. This will be used when calculating the entrance plate temperature setting.

Next, the cooling data learning computer 36 calculates the actual sheet threading speed set by the sheet threading speed control device 40, the actual water amount of the upper and lower surfaces set by the cooling water amount control device, and the cooling data detected by the cooling device front thermometer 13. The actual temperature of the hot steel plate 1 on the 7th person side of the device and the actual temperature difference between the upper and lower surfaces of the hot steel plate 1 on the 7th person side of the cooling device detected by a pair of optical fiber thermometers 20 at the cooling device inlet were manually calculated, and Perform plate temperature estimation calculation.

The cooling data learning calculation computer 36 also calculates the actual temperature of the hot steel plate 1 on the exit side of the cooling device 7 detected by the cooling device rear thermometer 14, and the optical fiber thermometer pair 21 disposed inside the cooling device 7. A temperature learning calculation is performed based on the actual temperature difference between the upper and lower surfaces of the heated steel plate 1 during cooling between zones 1 to 23 and the estimated value of the plate temperature estimation calculation described above. This learning result will be used in the plate temperature estimation calculation at the bottom of the cooling setting, which is performed by the cooling control computer 30. The cooling data learning control computer 36 then
Stress strain estimation calculations are performed based on the temperature estimation results during cooling obtained by temperature learning calculations.

On the other hand, the shape data processing computer 34 uses the shape meter 15
The shape data of the hot steel plate 1 after cooling detected by is input, and the deviation of the shape from the ideal shape is calculated. Cooling data learning control computer 36
performs a learning calculation of stress strain based on the deviation calculated by the shape data processing computer 34 and the stress strain obtained by the stress strain estimation calculation. The learning results obtained by this learning calculation will be used in the stress strain estimation calculation by the cooling control computer 30 during setting. Further, the cooling data learning control computer 36 is
The initial value of the vertical ratio of the standard value is corrected based on the deviation between the actual shape and the ideal shape calculated by the shape data processing computer 34, and this corrected value is used as the operating standard value in the cooling control computer 30 at the time of setting. It will be used when making decisions.

As described above, the hot rolled steel plate cooling control device according to the present invention firstly, before the hot steel plate 1 is conveyed to the cooling device 7,
Estimate the plate temperature and plate shape during cooling, determine the plate passing hardness and upper and lower surface cooling water volume in the cooling device 7, and make sure that the cooling stop temperature is a preset temperature and a predetermined material is obtained. In addition, while controlling the settings of the cooling device so that the shape becomes the ideal shape, learning calculations are performed based on the actual data of the hot steel sheet 1 after cooling, and this learning result is used in the subsequent production of the hot steel sheet 1. Taking actual data into consideration, quality and other matters are managed through closed-loop control.

The hot-rolled steel sheet cooling control device according to the present invention configured as described above operates as follows based on the flowcharts shown in FIGS. 6 and subsequent figures. Incidentally, when explaining this flowchart, the explanation of the matters that have already been explained above will be omitted.

First, the cooling setting calculation calculated before the heated steel plate 1 is transported to the cooling device 7 will be explained with reference to FIG. 6.

The cooling setting calculation starts from the start of finish rolling of the hot steel plate 1 to be cooled (
Finish rolling is normally performed multiple times), and is activated immediately before the end of finish rolling and at the timing when data is corrected from the data input/output device 33. First, the cooling control computer 30
determines whether the finish rolling of the hot steel plate 1 to be set has been performed up to just before the final finishing rolling, and if the timing is earlier than the final finishing rolling, the target finishing temperature sent from the business computer 32 is set as the final finishing temperature. At the timing after the final rolling, the actual finishing temperature detected by the finishing rear surface thermometer 11 and inputted by the rolling control computer 31 is determined as the finishing temperature. Further, this determination is made depending on whether or not the rolling control computer 31 has inputted information to the cooling control computer 30 (step 1). Next, the cooling control computer 30 performs an estimation calculation of the temperature of the hot steel plate 1 on the inlet side of the cooling device 7 (Step 2), based on various data output from the business computer 32 and the corrected standard value. Operational standard value (initial value of water and wastewater volume ratio,
The mask ff1) is determined (step 3). next,
The cooling control computer 30 uses the temperature of the heated steel plate 1 on the input side of the cooling device 7 and the initial value of the upper/lower ratio determined in step 3 to perform a simple plate temperature estimation calculation and calculate the threading speed of the heated steel plate 1. (Step 4). Next, the cooling control computer 30 estimated the sheet passing temperature determined in step 4 and in step 2.

A precise plate is prepared based on the temperature of the heated steel plate 1 on the inlet side of the cooling device 7, the learned temperature value obtained by the learning calculation in step 5 described later, and the operating standard value (initial value of upper/lower ratio) determined in step 3. Temperature estimation calculation is performed, and stress strain estimation calculation is performed based on the calculation result and the learning value obtained as a result of stress strain estimation calculation. Based on the result of the stress strain estimation calculation, the optimal vertical ratio of the amount of cooling water from the upper and lower surfaces that should minimize this stress strain is calculated (step 5).
). Then, the cooling control computer 30 compares the sheet temperature in the final cooling zone calculated in step 5 with the target cooling stop temperature input by the business computer 31 to correct the sheet threading speed (step 6).
), the results of the above calculations are output to the mask control device 371, the sheet threading speed control device 40°, and the cooling water amount control device 38, respectively.Step 7), the heated steel sheet 1 is cooled.

Further, the cooling learning calculation performed after cooling the hot steel plate 1 will be explained with reference to FIG. The cooling data learning system dual-purpose computer 36 corrects the initial value of the -L lower ratio among the operating standard values based on the actual water/sewage ratio and the actual amount of warpage (step 10). Next, the cooling data learning control computer 36 estimates the temperature of the hot steel plate 1 on the inlet side of the cooling device 7, and performs an inlet temperature learning calculation based on the estimated temperature and the actual temperature on the inlet side of the cooling device (step 11). Then, the cooling data learning control computer 36 uses the actual water amount and the actual sheet passing temperature to calculate the estimated sheet temperature during cooling (step 12).
, the temperature learning calculation during cooling is performed from the estimated temperature transition, the actual surface temperature after cooling, and the actual temperature difference between the upper and lower surfaces (step 13).
). Furthermore, the cooling data learning control computer 36
Using the temperature learning value obtained in step 13, temperature and shape are calculated and compared with the actual amount of warpage to perform shape learning calculation (step 14).

Next, the processing of each step of the main routine shown in FIG. 6 will be explained in detail.

FIG. 8 is a subroutine flowchart of step 2 in the main routine.

This subroutine flowchart shows that the hot steel plate 1 is
- This shows a processing procedure for estimating the temperature of each part on the plate surface on the side of the cooling device 7 from before the start of final rolling in the rolling mill 5 to the time when the sheet is transported to the input side of the cooling device 7.

First, the cooling control computer 30 uses the finishing temperature determined in step 1 to determine the initial temperature distribution at 11 points divided into 10 parts in the thickness direction of the hot steel plate 1 by the following method.

■Top surface temperature is finish temperature ■The temperature difference between the top surface and the highest plate temperature point is given by the formula below.

ΔT = 33.8-3.63h (-0,0371+0.
00528h)・TF However, ΔT: Temperature difference between the upper surface and the highest plate temperature point h: Plate thickness TF: Finishing temperature ■ The lower surface temperature is determined from the upper surface temperature and the input side temperature learned value.

However, T: Bottom surface temperature ξ: Temperature conversion coefficient learning value ΔT　Two-person side temperature upper and lower surface temperature difference learned value ξ and ΔT will be described later in the explanation of learning.

K+ + K2: Adjustment element, K+ = 1.0. to 2
A radial temperature distribution that satisfies the conditions (1) to (2) above =00■ is determined, and a temperature distribution in the plate thickness direction is determined.

FIG. 8 shows the determination method (step 20). Then, the cooling control computer 30 resets and starts the time counter t for difference calculation to 0 and starts plate temperature estimation difference calculation.

This plate temperature estimation difference calculation is performed based on the initial temperature distribution state obtained in step 20, using 11 points divided into 10 parts of the total thickness at the representative point on the plate as calculation target points, and calculating the one-dimensional heat conduction difference shown in the following formula. This is done by solving the equation (step 21.22).

Conversion from plate temperature T to heat content Q T >880 Q-3,333+0.16TT≦880
Q-149,05+0.481 ・T-1,68X
to−4・T2 Q(i)t+Δ1−Qi)t”.

At(λ -2λ1+λ1-1), ΔX 2 DI (1-1 to 11) (1-1, 11 only) =0 (1-2 to 10) Q(i)t; of element 1 at time t Heat content T(i)t
; Isothermal display Δt ; Increment time of difference calculation ('const, 15
0m5ec) ρ: Density λ; Thermal conductivity of element 1 Tg; Temperature ΔQ; Boundary condition ΔX; Plate thickness division thickness heat content ff1Q converted to temperature T (heat content; value of specific heat integrated from 0°C to T) Q >144.13 T = -20.8+6.25XQ
O<Q≦144.13 T =1431.5-1.162 xtoe -5,9
Since the method of giving 5X103 XQρ and λ is well known, detailed explanation will be omitted.

Then, when the representative point reaches the finishing rolling mill 5 during final rolling (step 23), the amount of heat generated during rolling is added. This amount of heat is the plastic working heat,
It is the sum of frictional heat and roll heat removal. These heat calculation formulas are also calculated using the following known formulas.

1) Plastic working heat ΔQ = η ・Kfffl・ε/(J-P)p ΔQ, : Plastic working heat (heat content display) ηp; Efficiency (const) and work equivalent (-const) ρ; Specific gravity 2) Friction Heat ΔQf-ηf・μ・P[Il・ΔV/ (J-P)ΔQ
,; Frictional heat (heat content display) ηf; Efficiency (-const) μ; Friction coefficient (-const) P; Average rolling force (finish final reduction) ΔV; Relative speed difference between rolling roll and steel plate 3) Roll heat removal ΔQR : Roll heat removal (heat content display) ηR; Efficiency C1; Specific heat TR; Rolling time ΔT; Amount of temperature drop before and after final rolling Each element is well known, so a detailed explanation will be omitted (Step 24). Cooling control computer 30
When determining that it is the time when the representative point reaches the hot straightening machine 6 based on the cumulative time of the timer started in step 21 (step 25), the hot straightening machine 6
Add the temperature drop heat due to passage of , that is, heat removal (
Step 26). The amount of heat removed is shown below.

HL heat removal addition 1) HL heat removal ΔTIIL = B3 (day!L-B5) ΔTIIL, amount of temperature drop due to passing through HL (amount of heat removed) Next, when the tip of the hot steel plate 1 reaches the cooling device 7, The cooling control computer 30 stores the temperature of the tip of the hot steel plate 1 (Steps 27 and 28), and when the time when the center of the hot steel plate 1 reaches the cooling device 7, the cooling control computer 30 stores the temperature of the tip of the hot steel plate 1. The temperature at the center of the steel plate 1 is stored in steps 29 and 30), and when the tail end of the heated steel plate 1 reaches the cooling device 7, the cooling control computer 3
0 stores the temperature at the tail end of the hot steel plate 1 (step 3
1.32). The arrival time of each part is determined based on the conveyance distance and conveyance speed plate length. Incidentally, the cumulative time of the timer for capturing the moving position of the hot steel plate 1 as time is set so that Δ is the cumulative time of the time (step 3).
3). Δt is 0. The time is approximately 1 sec. Then, the transformation heat generation is added to the temperature of each part of these stored representative points. The addition of this transformation heat generation is the calculated surface temperature at the center and the Ar
This is done by comparing three transformation points.

First, the Ar3 transformation point temperature (Tar3) is calculated using the following formula.

Tar3 = Ba +87 [C] + Ba
[:Si]+h l:Mn]+B+o[Ni Miko31
1 [Cul+812 [V] B6-868°B7 Electric-396°Ba = 24.6°B9-58.7°Boo--50°B+t-35°B12-190° [C, [Si], [Mn ], [Ni],
[:Cul, [V] is 1/100 of each component of rolled steel plate
Weight % (included in the board information from the business controller) Addition of metamorphosis heat generation is performed using the following formula for each part, including the tip, center, and tail, taking into account the learned value (Step 34)
.

T(1)=TC(1)+dTt2. +ΔT (i-1
~11) ΔT; Cooling device inlet temperature learning value T(i); Cooling device inlet plate temperature Tc(1); Inlet plate temperature dT before adding body heat generation
trS: Metamorphosis calorific value (common to the tip, center, and tail end) When central part T c (i) > T ar3 dTtrs
When =0Tc≦Tar3, dTtrs=B+4(Ts Tar3)+B+s.

Table 1 h>18mm 0.56 16h≦18mm O,58 h≦16mn+ 0.55 3ts 9, 09 0, 53 -7. 98 Next, the operation standard value determination in step 3 in the main flowchart of FIG. 6 is performed.

The board width, target cooling start temperature, cooling stop temperature, number of zones used in the cooling device 7, and bottom surface water amount for each zone are input from the business computer 32.

The predetermined operational standard values, that is, the water and wastewater volume ratio for each zone, the side end mask amount, the front end mask amount, and the tail end mask amount are determined. This water and wastewater volume ratio for each zone is determined in step 5.
This is the initial value to be searched for in the calculation of the optimal up/down setting performed in .

Next, FIG. 10 shows a subroutine flowchart of the sheet passing speed setting calculation in step 4 in the main flowchart shown in FIG. This subroutine flowchart is for determining the optimum threading speed of the hot steel plate 1 within the cooling device 7. The cooling control computer 30 calculates the average amount of water used within the cooling device 7 as follows (step 40).

Qlav' Lower surface average cooling water amount (m3/m2 min) Q(i)
;I zone lower surface water amount (m311112 minutes) Lz(i);
i-zone cooling length (m) Nz; Number of zones used. However, Lz (1) is the cooling zone where water does not flow.
1)=0.

(2) Upper and lower surface points (3) Heat load (j-2 to 9) ηo (1); Initial value of water and wastewater amount ratio Next, the cooling control computer 30 calculates the input of the cooling device 7 calculated in step 2. The required cooling time tc and the temperature/time influence coefficient when cooling the hot steel plate 1 to the target cooling stop temperature using this average amount of water with respect to the plate temperature at the center on the side are determined. Temperature calculation is performed using a one-dimensional difference formula. The calculation is shown below.

+82 ・a(T(j)−Tw) (
j-1,11)<5uff1x j is the third element divided in the plate thickness direction.

(4) Heat transfer coefficient (with upper and lower surface divisions) α=(αB”
(W/Ko/ni3) X)'αB=EXP((ao
+al φTs+a2 4s2+ ・+a21IT
s6) /1000) X= bo +l)+ 4s+b2 ・Ts2+-
・・・-・+b611Ts6) W: Water density ([1137
m2IIIln) (1) Inside the plate One-dimensional heat conduction difference equation Ts: Steel plate surface temperature (XIO-2°C) αB: Standard α L: Temperature learning value (before classification of upper and lower surfaces) -Left space- Heat content (Kcal/ kg), Ts: Steel surface temperature.

Specific heat (kg/m2), Tw: water temperature (°C).

Thermal conductivity (Kcal/mhr’c).

:Thermal conductivity at 0°C (Kcal/mhr'C).

: Conversion temperature (°C).

: Calculation division time (hr) = 1.39X10' (50m
sce).

Surface heat load (Kcal/m 2hr).

: Divided length in the thickness direction (m).

Ambient temperature (℃), C: Specific heat (Kcal/kg℃)
.

Heat transfer coefficient (Kcal/m 2hr'C).

, β2: coefficient When water cooling β1=0. β2=1 During air cooling, βl-1, β2 = 0.

(5) Average plate temperature calculation ρ: Kd: Kd.

φj Δ t Q: Δy Tg: α : β1 (6) Required cooling time tc; sum of Δt until Tav reaches the target cooling stop temperature (7) Temperature/time influence coefficient d T/ d t = (Tavo = Ta111 )
/ t CdT/dt; Temperature/time influence coefficient TaVo; Average plate temperature Ta1m at the entrance side of the cooling device
; The target cooling stop temperature temperature/time influence coefficient is the falling temperature per unit time in the cooling calculation, that is, the cooling rate, and the later-described correction calculation of the cooling time is performed using this temperature/time influence coefficient (step 41). Then, the sheet passing speed is calculated based on the cooling time and the total length L zone of the use zone. Vcc-Lzonc/lc
Vcc threading speed (step 42). It should be noted that the plate threading speed obtained by the above calculation is a speed determined assuming a constant amount of water in all zones, so it is a rough determination.

Next, FIG. 9 shows a subroutine flowchart for determining the optimal water and wastewater amount ratio in step 5 in the main flowchart shown in FIG. This subroutine flowchart is a routine that calculates the temperature within the cooling device 7 and changes in the plate shape, and performs processing for determining, for each cooling zone, the water and wastewater volume ratio that minimizes warping in the width direction of the plate. Specifically, warpage in the width direction is caused by the asymmetric distribution of thermal stress in the width direction of the sheet due to the temperature difference between the upper and lower surfaces. The amount of warpage in the board width direction is estimated, and the amount of cooling water to be sprayed on the upper and lower surfaces is determined in order to minimize the warp in the board width direction in the cooling zone, that is, to make the thermal stress symmetrical in the board thickness direction.

First, the cooling control computer 30 calculates the outlet passage time of each central cooling zone using the already determined sheet passing speed (step 50). Then, the cooling control computer 30 sets the time when the calculation target point reaches the entrance side of the cooling device 7 to t=0, and simultaneously sets the value of the counter Z for counting the number of cooling zones to 1 (step 51).
．． 52). Next, the cooling control computer 30 sets input conditions. The input conditions include the inlet side set temperature of the zone, the stress in the board width direction, the board width, and several types of water and sewage volume ratios provided before and after the operational standard water and sewage volume ratio (step 53). Then, plate temperature estimation calculations are performed in the same manner as the inlet temperature estimation process shown in FIG. 7, plate temperature estimation calculations are performed at each representative point in the zone, and plate shape estimation calculations are performed. This shape estimation calculation, which will be explained in detail later, is performed based on a -dimensional thermoelastic-plastic equation. These plate temperature estimation calculations and shape estimation calculations are performed at predetermined time intervals until the representative point leaves the cooling zone (steps 54 to 57). And step 57
The optimum water/sewage volume ratio for the cooling zone obtained up to this point is calculated, the value of the counter Z is incremented by 1, and the process returns to step 53.

Then, when the calculated number of cooling zones becomes equal to the number n of zones determined by the operation standard value determination process, the process returns to the main routine (steps 58 to 60).

In this way, this subroutine estimates the amount of warpage in the board width direction on the inlet side of each zone and the exit side of the zone, and calculates the optimal water and wastewater volume ratio that minimizes the amount of warp in the board width direction in the zone. .

FIG. 12 is a subroutine flowchart of the shape estimation calculation shown in FIG. 11. The calculation is performed for each time step Δ used in the cooling calculation in order to take into account the temperature change over time at each part in the plate thickness direction. Now, suppose that the amount of warpage in the board width direction at a given time is to be determined.

The cooling control computer 30 calculates physical property values such as the coefficient of linear expansion, Young's modulus, and yield stress of the hot steel plate 1 (step 61). Since the stress state at time t-Δt at time t is known, this stress is converted into a point on the stress-strain line. This conversion is caused by the stress -
Since the strain diagram changes, temperature compensation is performed (step 62). Here, the stress-strain relationship is the well-known σ≦E−ε in the elastic range.

σ: Stress ε: Strain E: Young's modulus with respect to temperature at time t σγ1. εγ
: Yield stress with respect to temperature at time t1, yield strain, εγ: (σγ/E) Next, the cooling control computer 30 divides the steel plate into 10 parts in the plate thickness direction, and divides each divided element (i=1 to 10 ), create the following simultaneous equations based on each part obtained in the above steps.

ΔI) (i, t)・(1-k), l)L (1,
7-Δt)A −E(i, t) = PL(i-1, t-Δt)・is +ΔεT(i-i, t
)l・(1+k)−PL(f, −Δt)・11+△
εT(i, t)l・(1-k)...(2) Here, ΔP(i, t): For the i-th element from the top surface,
Internal force A that increased from time 1 Δt to time t: Cross-sectional area E (1, t) of the element: Young's modulus P L (1, at -Δt) of the i-th element from the top surface relative to the temperature at time t : Length Δε1・(i, t) of the i-th element from the top surface at time 1 Δt : Thermal strain (temperature change coefficient of linear expansion) -Δt): If element i is plastic in the above equation of the radius of curvature of the steel plate at time t-Δt, then E (i.

dρ/dε=nσγ・(ε/εγ)・1/εγ obtained from (σ/σγ)=(ε/εγ) instead of t)
Use.

Equation (2) is + -X(1-1)(1+K) -1)L(i-1,t-
Δt) IX(1-1)-X(i-1>)(14K)
・PL(j-1,t-△t)IX(1)C(i,2
) , ・-=C(i,n), and the right side is set as D(1), the equation (2') for i=2 to n is less than or equal to 1 margin 1△1) (i÷1.t) + t) = PL (i-1, t-△t)11+△εT (
1-1,t)l (1+k)-PL(1,-△t)(
1+ΔεT (i, t)l(1-K) ...(
2') In equation (2'), if i = 2 to n, then n-
-One simultaneous equation is obtained.

The coefficient of 8P (1, t) in equation (2') is changed to C(1,1')
).

Regarding the method of solving this simultaneous equation, the simultaneous equations are expressed as a matrix for △P(i, t) as shown below, and below the [K] matrix, the shape matrix, f
Pl is called a stress increment matrix and [F] is called a strain matrix. Then, stress due to thermal strain is calculated based on the shape matrix obtained in step 63. This stress calculation follows Funatsuri's matrix solution method and finds the inverse matrix [K]-1 of [K] (P) = [:lk]
The stress increment (P) is obtained from -1, and the previous stress calculated for each step time is added to this stress increment vector (step 64). Next, it is determined whether each element is elastic or plastic based on the stress, and if it is plastic, the stress value of each element is determined again by using the stress value as the yield stress value. Strictly speaking, convergence calculations are required for the stress strain when changing from elasticity to plasticity, and when changing from plasticity to elasticity, but in the present invention, convergence calculations are omitted by reducing the calculation time increments. The aim is to shorten calculation time.

In addition, while re-determining the stress of each element, the mechanical strain at time t is determined from the stress-strain relational expression, and the length of each element at time t (i.e., the plate width) is determined by combining it with the thermal strain determined previously. seek.

Furthermore, the cooling control computer 30 calculates the amount of warpage of the heated steel sheet 1 in the sheet width direction based on the above calculation result.

The calculation for the amount of warpage is performed on the output side of each zone.

Amount of warp = warp + C (B: board width) 8ρ Here, the amount of warp in the board width direction is determined by the following equation from the direction that cancels out the board asymmetry in the board thickness direction within the board width direction determined above.

1=Σ(Pi-Σ1EA) ρ 2AΣXi2 E FIG. 13 is a subroutine flowchart of the sheet passing speed correction calculation shown in step 6 of the main flowchart explained in FIG. This sheet threading speed correction calculation is
The sheet passing speed roughly determined in step 4 is evaluated and corrected as necessary.

First, the cooling control computer 30 calculates the estimated average plate temperature Tlast at the exit side of the final water cooling zone of the cooling device obtained in step 5 of the main routine, and the target cooling stop temperature Taiim output from the business computer 32.
In step 80), it is determined whether the absolute value of this temperature difference is larger or smaller than the allowable deviation amount ε (step 81), where ε is assumed to be 10°C. If this temperature difference is smaller than the allowable deviation amount, the tip of the hot steel plate 1 with a considerable length.

The acceleration rate is calculated so that the temperatures at the center two tail end portions are the same when they exit the cooling device 7 (step 82). On the other hand, if the temperature difference is greater than or equal to the allowable deviation amount, the required sheet passing speed is corrected and calculated. This corrected calculation is shown in the formula below.

■-Ω zone/ [Kv ・ (Tlast-
'l'aim)/(dT/dt)+tcKv; Coefficient=
0.6 dT/dt; Temperature-time influence coefficient The speed obtained by this corrected calculation is used to perform the optimum upper/lower ratio setting calculation (step 5) again. However, the correction is limited to five times or less, and if the condition is not satisfied even after five corrections, step 82 is performed.

FIG. 13 is a subroutine program at step 82 shown in FIG. 12.

This calculation of the acceleration rate is performed in order to bring the entire surface of the hot steel plate 1 to a negative temperature on the outlet side of the cooling device 7.

First, the cooling control computer 30 calculates the temperature on the inlet side of the cooling device 7 at each part in the longitudinal direction, the tip, the center, and the tail end of the hot steel plate 1 in the inlet side temperature setting calculation in step 2. Then, the cooling control computer 30 calculates the required cooling time in the cooling device 7 for each part of the tip and tail end from the required cooling time of the central part used in step 5 of the hot steel plate 1, and based on this required cooling time. Calculate the threading speed pattern. The formula for calculating the required cooling time is shown below. (Step 90).

t m =D zone/Vccll =1. n+ (φ/Vcc) (Tt −T
m) tb = t, n+(φ/Vcc) (Tb −T
m) φ: coefficient tl; Required time for cooling the tip, tb; Required time for cooling the tail, t, ; Required time for cooling the center, Vcc; Finally determined threading speed j7zonc; Effective cooling IJ scene length ( Water-cooled cooling zone length l [I) Tt ; Tip cooling device entrance side plate temperature < thickness hs tactile initial value) Tm ; tail end cooling device person side plate temperature (thickness direction 1) Tb , center cooling device Human side plate temperature (I
h11D average i) Next, calculate the sheet threading speed pattern that satisfies the required cooling time for each point on the sheet. The plate threading speed is given as a set of data on the position of the plate tip and the conveyance speed.

As shown in Fig. 15, if the position of the tip of the plate is X and the conveyance speed at this time is V (x), then point A on the plate at that point in the cooling device population, in other words, X behind the tip of the plate. Next, the water cooling time at the point at the tip, center, and tail end, 1+, 1□, and t, is determined by the following formula.

L: Plate length V (x) = 1/ (ax2 + bx + c) and substituted into the above three equations to find a, b, and c.

+42zone (tt +tb -2tm)).

The acceleration range (defined area of X) is determined as shown in the formula below.

0 ≦ By substituting into the equation, a set (speed pattern) of the position of the plate tip and the conveyance at that time is created (step 91).

The calculation result is then output to the sheet threading speed control device 40.

The reason why the acceleration rate is determined in this way is because the hot steel plate 1 is cooled while being conveyed, and therefore the time at which the steel plate enters the cooling device 7 is different between the tip and tail ends of the steel plate. In other words, since the cooling start temperature differs along the longitudinal direction of the steel plate, the temperature after cooling differs between the tip and tail ends, and the threading speed must be adjusted to make the product material uniform over the entire length. This is to compensate by increasing the speed toward the tail end.

The following is a cooling setting process performed before the heated steel plate 1, which is the material to be cooled, reaches the cooling device 7. The cooling control device for hot rolled steel plates according to the present invention has a learning function described below. This ensures that controlled cooling is always performed under optimal conditions. In addition, this learning includes two inverse components as error components, that is, a continuous component (continuous term) that changes with the progress of rolling in the finishing rolling mill 5, and an inherent change such as plate thickness characteristics. The table components (stratified classes) that will be used are taken into consideration. In the above explanation of the setting calculation, what is explained as the learning value is the sum of this continuous term and the stratification order.

However, when calculating the learning value, it is actually impossible to accurately separate these two types of terms, so when calculating, the error distribution is fixed and the distribution ratio is an adjustment item. .

FIG. 16 shows a flowchart for correcting the standard value in order to improve the accuracy of the operational standard value (initial value of water and sewage volume ratio) in step 10 of FIG. 7.

The shape data processing computer 34 inputs the plate shape detected by the shape meter 15, and calculates the actual amount of warpage in the width direction of the hot steel plate 1 based on the input plate shape data (steps 100 and 101).

Based on these data, the cooling data learning calculation computer 36 calculates the operating standard value, that is, the new L-inhibit initial value for each zone, and updates the operating standard value. In this update, it is assumed that the amount of warpage in the sheet width direction is proportional to the top-bottom ratio in the vicinity of the optimum value, and the top-bottom ratio is corrected. However, if the actual plate width direction amount is within the reference value (3 mm), this correction is not performed. The calculation formula is shown below (
Step 102).

770 (i) new-y7o (i) old+Δ
77 (i = 1 ~ n use) Δy7 = 1
(Cr −Cair) However, ηo (i) new;
Updated upper/lower ratio initial value ηo (i) old: Upper/lower ratio initial value Δη before update; Up/down correction value ηuse; Actual final use zone number.

Cr: Actual 0 warp amount Ca1r; Target 0 warp amount KI; Correction coefficient (=-0,01) Next, FIG. 17 shows the learning of the inlet temperature of the cooling device 7 in step 11 in the main flowchart of FIG. Explain according to the following.

The inlet temperature learning of the cooling device 7 is performed for the purpose of improving the accuracy of the inlet temperature estimation calculation of the cooling device 7.
A device that calculates an inlet temperature correction value that corrects the absolute value of the inlet temperature of the cooling device 7 and an upper and lower surface temperature difference correction value before the start of finishing final rolling that corrects the temperature distribution in the plate thickness direction at the inlet side of the cooling device. It is.

First, an inlet temperature estimation calculation is performed. This calculation is performed using the same formula as the inlet temperature estimation calculation in the previous step. however,
The learning value is as below.

Temperature conversion coefficient; data used when calculating settings for the material in question.

Learning value of entrance temperature and upper and lower surface temperature difference; data used when calculating settings for the material in question.

Cooling device inlet temperature learning value: Data used when calculating settings for the material in question.

As a result of the calculation, the upper surface temperature Tcal (
1) and the calculated upper and lower surface temperature difference ΔTincal is obtained (step 110).

Next, update the learned value. First, the inlet temperature correction value is updated according to the following formula (step 111).

ΔTu, N=Trcal(1) −Tcal(1)Δ
TueOnN= g I ”ΔTueOn.

+g3 (1-g+)ΔTu+N Δi'uelasN= g 2 'ΔTuclas
.

+ (1-gs) (1-g2) Δ'l"u+N However, ΔTuH,; CLC entrance side upper surface temperature estimation error T rea
l (1); CLC person side hot water side thermometer actual measurement value surface component cal (1); CLC entrance side plate temperature estimated value surface component ΔTueOrlN, ΔT ueono:
New and old CLC human side temperature correction value continuous term (after and before update) ΔTuclas N, ΔTuelaS O; C
New and old LC human side temperature correction value stratification term (after and before update)
s; Coefficient (0≦g≦1) Next, the learning value of the temperature of the upper and lower surfaces of the entrance side of the cooling device is updated according to the following formula (step 106).

Δ'l'5lcon = g5hiroTSICON+g)°(
1-gs) Hiro'CLCre@△'l's'cIas
s = g6"Δ'l'5l class+ (1-g+
)・(1-gg) Hiro T. ,. ,. .

ΔTs−cOn ; Upper and lower surface temperature difference learning term (continuous term) Δ
Ts - class ; Upper and lower surface temperature difference learning term (stratification term) ΔTs CLCreal ; 1 - Lower surface temperature difference on the CLC person side (actual measurement value on the CLC person side) gb, ge, g7: Coefficient 1 - Lower surface temperature difference Defined as lower surface plate temperature - upper surface plate temperature.

Next, update the temperature conversion coefficient (step 113). However, ξ, ξ; New and old N of upper and lower surface temperature difference conversion coefficients.

(Before and after update) ΔT s FM set + Upper and lower surface temperature difference before finishing 1 pressure reduction (set as initial condition in learning calculation) Δ
TSCLCcal Temperature difference between the upper and lower surfaces of the CLC input side (CL
C calculation result on the inlet side) g4: Update gain of upper and lower surface temperature difference conversion coefficient correction value Next, FIG. 18 shows a subroutine flowchart for calculating the plate temperature estimation during cooling in step 12 of the main flowchart of FIG.

First, the plate temperature distribution on the inlet side of the cooling device 7 is determined. That is, the inlet temperature distribution is determined using actual values obtained using the cooling device front thermometer 13 and the pair of fiber end thermometers 20. This determination method is the same as the calculation of the initial temperature distribution in step 20 described above, and is performed assuming that the temperature distribution in the thickness direction is radial, and the surface temperature is the actual value measured by the entrance thermometer 13. .

The temperature difference between the upper surface temperature and the highest plate temperature point is determined by using the calculation formula for the temperature difference between the highest plate temperature point on the entrance side and the upper surface, which was obtained by calculating the initial temperature distribution in step 20 above. Regarding the temperature difference on the lower surface, the plate temperature distribution in the plate thickness direction is determined (radiation is calculated) as the actual temperature difference between the upper and lower surfaces of the pair of optical fiber thermometers 20 (step 120).

Next, plate temperature transition from the inlet side to the outlet side of the cooling device 7 is calculated. This calculates the plate temperature from the inlet side of the cooling device 7 to the outlet thermometer 18 using the model (arithmetic formula) used in the plate temperature estimation calculation in step 54 and the latest learned values. However, shape estimation calculations are not performed. The following data are then saved (step 121).

1. Estimated upper surface plate temperature Tucal (
1);i corresponds to cooling zone.

2. Estimated lower surface plate temperature TLcal at the exit side of each cooling zone (
i); i corresponds to cooling zone.

3. Average value T of the estimated plate temperature of the upper and lower surfaces at the exit side of each cooling zone
aeal(1).

4. Estimated upper surface temperature Tucal under the outlet thermometer 18
(M2) 5. Estimated bottom surface temperature Tlcal under outlet thermometer 18
(Hz) 6. Average value of the estimated plate temperature of the upper and lower surfaces under the outlet thermometer 18
Tacal (Hz) However, Mz = Nusc + 1, N use is the number of zones actually used.

Next, calculate the model error. It is assumed that all plate temperature estimation errors in the model occur in the water-cooled region, and that the plate temperature estimation errors accumulated due to water cooling are equally included in the air-cooled region.

Using the average plate temperature of the upper and lower surfaces as a reference value, a model estimation error is determined (step 122).

1'error=Tmrcal-Taeal(Hz
) - (29) Tmrcal: Actual temperature measured by the cooling device rear surface thermometer Terror: Plate temperature estimation error by the cooling device rear surface thermometer.

Next, distribute model errors. Various methods can be considered for allocating the error, but in this embodiment, the simplest structure is used, and it is regarded as an item for leveling up after confirming model behavior. It is assumed that the model error increases in proportion to the water cooling time, and is given by the following formula. Further, the model estimation error at an arbitrary time t is assumed to be ΔTE (t).

ΔT E (t) = Terrorit/1clcou
t(0≦t≦tclcout) or ΔTE(t) =
Tterror (tclcout <t).

Teleout is the actual final cooling zone time. By substituting the exit side passing time of each zone into the above equation, the model estimation error at the exit side of each zone is calculated. (Step 123
).

ET(1)=ΔT E (tzoi) ET(1); Plate temperature estimation error tzoi on the i-zone exit side
; i-zone exit side passage time teleout; final use zone exit side passage time Next, determine the actual temperature transition. In this process, first, the actual temperature transition on the outlet side of each zone is determined for the upper and lower surface points. The basic idea of determining the actual temperature transition is as follows.

1) The temperature transition profile (time/temperature characteristics) estimated by the model is considered to be correct overall, and the actual temperature transition can be observed from the model estimated value and model error.

2) Since the learning target is the heat transfer coefficient of the upper and lower surfaces, determine the temperature transition of the upper and lower surfaces (note that it is not the center of the plate or the average of the metal plate).

3) Actual upper and lower surface temperature trends are measured using two optical fiber thermometers.
Expresses the temperature difference between the upper and lower surfaces measured in steps 1 to 23.

- Based on the average plate temperature of the lower surface of L, the actual temperature change of the upper surface is (1/2) (average estimated value of upper and lower surfaces + model error -
The lower surface actual temperature transition is determined as (1/2) (upper and lower surface average estimated value + model error 10 upper and lower surface temperature actual values). These are: Actual lower temperature + actual upper temperature = estimated average + model error actual lower temperature -
It is obtained by simultaneously solving two equations: actual temperature = actual temperature difference between upper and lower surfaces.

Tur(i)=(1/2)・[Tacal(1)
+ET(i)-DTr(1)koTlr(i)=(1/2
) ・[Tacal(i)+ET(1)-DTr(
i) ko1'ur(i); Actual temperature on the upper surface of the i-zone outlet side Tlr(i); Actual temperature of the lower surface on the i-zone outlet side Dl'r(i); Actual temperature difference between the upper and lower surfaces of the i-zone outlet side However, DTr (1) and D'l'r (2) are the actual values of the cooling device inlet optical fiber thermometer pair 20 and the 3-zone outlet optical fiber thermometer pair 21, since there is no optical fiber thermometer pair. is obtained by interpolating with respect to time (step 124).

Next, the temperature learning calculation during cooling in step 12 of the main flowchart shown in FIG. 7 will be explained.

First, the actual temperature transition obtained in step 124 is regarded as the true value, and a learning value is determined so that the result of plate temperature estimation calculation matches the actual temperature transition.

The learned value is a correction value for the heat transfer coefficient of the upper and lower surfaces, and is maintained over the entire temperature range for each of the upper and lower surfaces. The learned value is in the form of an index as shown in the temperature calculation formula described above. First, I will explain the basic idea.

1) It is assumed that all errors in plate temperature estimation calculations are due to errors in the upper and lower surface heat transfer coefficient models, and temperature model learning is carried out in the form of heat transfer coefficient correction values. In other words, the horizontal axis is the temperature, the vertical axis is the heat transfer coefficient (logarithmic display), the base heat transfer coefficient curve (upper surface or lower surface) is obtained, the heat transfer coefficient learning value is obtained, and the heat transfer coefficient is the base. Correct the coefficient with the learned value and set this as the heat transfer coefficient for the next heat transfer calculation.

2) The problem of finding the learned value of the heat transfer coefficient is a nonlinear identification problem, and it is impossible to find the optimal value analytically.

Therefore, a computer experiment is conducted to search for a learning value that makes the estimated board temperature and the actual board temperature match by changing the human power conditions.

3) Sequentially search and calculate the above computer experiments to obtain learning values. However, there are two input variable conditions to be identified (upper surface correction method and lower surface correction method), and this becomes a two-dimensional parameter optimization problem.

FIG. 20 shows a subroutine flowchart for this temperature calculation. First, to give an overview, the optimum heat transfer coefficient correction ri[Lud(j), Lid(j)] is determined for each zone. Lud(j) and LId(j) calculate the plate temperature transition in the zone under nine different condition settings, and the upper and lower surface temperatures at the exit side of the zone are determined by the difference between the actual value and the estimated value. Adopt the smallest condition.

When the difference between the actual value and the estimated value is greater than the reference value, search again. Perform this operation across all usage zones.

Further, the temperature learning value is calculated for each cooling zone, but when updating the learning value, the optimum correction value for each cooling zone is converted into a correction for each temperature range, and the learning value is updated. This will be explained according to FIG.

First, initial conditions for correction values are set. Conditions for heat transfer coefficient correction values are set for performing search calculations (step 130).

Lua(i,j)=1.0+Δa u(1) −(
35) Lla(i,j)=1.0+Δα1(t)
-(36) Lua (i, j): Condition i of j zone
Top surface heat transfer coefficient correction value. i=1-9. j≦6゜Lla (i, j): Lower surface heat transfer coefficient correction value for condition i in zone j.

Δαu(i): Added value under condition i (upper surface).

Δα1(i): Added value under condition i (lower surface).

The values of Δαu(i):Δα1(1) are shown in the following table and FIG. 21.

One or less margin one condition (1) Δαu(1> Δα!(1)2
0 Δα3
Δα Δα4 Δα
05 Δα
−Δα6 0 −Δα7
−Δα −Δα8 −Δα
09 −Δα
Δα However, Δα: amount of change in heat transfer coefficient (constant) Next, estimate the plate temperature. For conditions i=1 to 9, the plate temperature estimation calculation for the zone (j) is performed. The calculation formula is calculated for the entire thickness using the same difference formula used in the plate temperature estimation calculation in step 121 described above. However, instead of learning value,
The heat transfer coefficient correction values of Conditions 1 to 9 are used, and no shape estimation calculation is performed.

For condition 1, Lua (i, j), Lla (1, j
) to condition i, Lua(i, j),
Lla(i,j) is manually operated, and the entrance plate temperature and actual water cooling time are used in common for all conditions. As a result, conditions 1~
9 operation result Tucal (1) ~ Tucal (9
), Tlcal(L) to Tlcal(9) are obtained. Tucal (i); Upper surface plate temperature under condition i (j zone outlet side) T 1eaf (i); Condition i
Lower surface plate temperature (zone exit side) at (step 131)
).

Next, it is determined whether there is an optimal solution. For conditions 1 to 9, the lower evaluation function value Ia(i) is calculated, and when there is a value where the evaluation function value is smaller than the reference value, it is determined that there is an optimal solution.

la(i) = [Tur(j) −Tucal
(i) Ko2+ [Tlr(j)-Tlcal(1)]2
=437)la(1) <[st, it is determined that there is an optimal solution.

1st is the temperature error squared reference value (=100).

If it is determined that there is an optimal solution, the distribution of the outlet plate temperature of the zone (initial temperature of the next zone) is determined.

Set the j zone outlet plate temperature under the condition i* that minimizes 1a(i) as the initial temperature distribution of the next zone (step 134)
.

Next, when it is determined that there is no optimal solution, the correction value search range is modified. Search again around the minimum value of 1a(i). Set the heat transfer coefficient correction value again to the conditions of 1 to 9. However, the search range will be narrowed.

Lua (i, J) = Lua (1, J) + Δa u (1)
=・(38)Lla(i,j)=Lla(k,
J)+Δa l (i) −(39)Δαu(i
): Ka・Δαu(i) However, 1 is i that 1a(i) satisfies the minimum (1: quasi-optimal condition). Ka is a search range correction coefficient (0<Ka<1) and is a constant. Figure 22 shows the search process (step 133).
.

When the final zone is reached (step 135), the optimum learning value is updated. The optimal correction value determined in step 134 is converted into an optimal learning value vector, and exponential smoothing is performed on a vector-by-vector basis using this optimal learning value vector and the old learning value vector to determine a new learning value.

b) Shape of learning value vector The top and bottom surfaces are independent. Each component corresponds to a learned value for each surface temperature range. It also has a continuous class and a stratified class.

Ludg = [Ludg (1) , = Ludg (
j), -Ludg(n)] ...(40)L
ldg-[Lldg(L),-Lldg(j),-=L
Idg(n)]・(41) Ludg(j) ; Upper surface learning value for the temperature range of steel plate surface temperature < TS (j), Lldg(j) ; Lower surface learning value for the temperature range of steel plate surface temperature < TS (j) From the above, the learned values are obtained as shown in the following table.

Table j Temperature Top surface learning value Top surface learning value Ludg
Lldg j T S (j-1) L udg (j)
L udg(j)≦T<TS(j) 口) Conversion of optimal correction value to optimal learning vector.

The optimal correction value is calculated for each cooling zone, but this is edited into a vector for each temperature. The relevant area of the surface temperature of each cooling zone is used for learning.

Regarding the temperature range component at the boundary between each cooling zone, the average of both zones is taken as a learned value (the weighted average L udg (j) * for the position of the temperature boundary value is taken).

The area where the optimum correction value does not exist is set to 1.0.

Ludg*(j)−[Lud(k)*X(TS(j+1
)−1'ur(k)]+Lud(k+1)*X(T
ur (k) − TS (j) l Koba TS (j+1) −
1'5(j)] ...(40)
j: For temperature classification parameters: Parameters for cooling zone Perform for each of the upper and lower surfaces. This is done for each continuous class and stratification term. FIG. 23 shows the relationship between the plate temperature transition and the calculated optimal correction value and optimal learned value.

C) Exponential smoothing.

When updating the learned values, exponential smoothing is performed on a vector-by-vector basis.

This is done for each continuous class and stratified class.

Ludgcon (j) = (1-gs) Ludgcon
+gt ILudge(i)*...(41) Ludgclass(i)=(1-H)Ludgec 1
oss+g9・Ludge(j)X...(42) Lldgcon(i)=(1-gt)Ludgecon
+gt ・LIdge (j) bundle... (43) Lldgclass (j) = (1-gy) Ludgc
loss+H・LIdge(i)! ...(42) Ludgeon(j); Top surface heat transfer coefficient learning vector of continuous class Ludgclass(j); Top surface heat transfer coefficient learning vector of stratified class Lldgcon(j); Bottom surface heat transfer coefficient learning vector of continuous class Lldgclass (j) ; Lower surface heat transfer coefficient learning vector for stratification type Note that when calculating the optimal correction value, if a cooling zone occurs where the actual and estimated temperatures do not converge, the optimal correction value for the previous cooling zone is valid, and the subsequent Zones are treated as invalid. Updates are performed only for valid zones.

Next, the stress strain learning calculation in step 14 of the main flow chart FIG. 7 will be explained.

FIG. 24 is a subroutine flowchart of stress strain learning calculation. This process is performed to improve the accuracy of stress strain estimation calculation.

This learning calculation is performed on the assumption that the error in the estimated value of warpage in the sheet width direction is the same in each zone, and the estimated value of warp in the sheet width direction is corrected for each cooling zone.

First, using the optimal learning value calculated in the temperature learning calculation described above and the actual operating parameters, we perform temperature and shape estimation calculations from the cooling device 7 person side to the bottom of the shape meter 15. The amount of warpage in the width direction Ccal is calculated (step 140).

Next, from the actual measured shape (actual value) detected by the shape meter 15 calculated by the shape data processing computer 34, the estimated error ΔCT of the warp amount in the board width direction is calculated from the actual board width direction warp amount area+
is calculated (step 141).

ΔCT=Creal−CCaI Distribute the error ΔC(1) to each zone (step 142
).

ΔC(i)=ΔCT/Nuse−(47
) Nuse; Last used sea number.

Next, set the learned values to the following ΔC(i)con and ΔC(1)e
Update to tasS. The learning value is the continuous term ΔC(i)con
and has a stratification class ΔC(i) class (step 133
).

ΔC(i)con = (1-g +2)ΔC(i)co
n0g, 2・(1g+3)・ΔC(1)...(48
) ΔC(i) class = (1-g 14) ΔC(i
) class 10g14・g13・ΔC(i)・
... (48) B12: Update gain of continuous term B13: Update gain of stratified class B14: Distribution gain of continuous term and stratified class As described above, in the present invention, in the cooling process of hot steel plate 1, material quality is secured. Calculate the amount of cooling water to be injected from the top surface so that the heat transfer coefficients on the top and bottom surfaces of the plate are the same, based on the amount of cooling water injected from the bottom surface that is preset to obtain the cooling speed that can be achieved. , the amount of warpage in the board width direction is controlled to be minimized. Furthermore, since this control includes learning control, it is possible to easily obtain the desired material and shape, and it is possible to manufacture steel plates with always stable quality.

And, Fig. 25A (Results of conventional cooling stop temperature accuracy -
As shown in Fig. 25B (actual results of cooling stop temperature accuracy according to the present invention - target data), according to the present invention, the variation in cooling stop temperature accuracy is extremely reduced compared to the conventional method. I can see that it is. Also, the second
As shown in Figure 6A (conventional sheet width direction warp amount data) and Figure 26B (sheet width direction warp amount data according to the present invention), it can be seen that the sheet width direction warp is improved by the present invention. .

Further, although specific numerical values are not shown, along with this improvement in warpage in the width direction of the sheet, the correction rate, which indicates the degree to which the warp in the sheet width direction must be corrected after cooling, has also decreased significantly.

In addition, Fig. 27A (conventional hardness distribution in the plate thickness direction) and Fig. 2
FIG. 7B (hardness distribution in the thickness direction according to the present invention) shows the test results of the conventional hardness distribution in the thickness direction and the hardness distribution in the thickness direction according to the present invention.

As is clear from this figure, the difference in hardness between the upper and lower surfaces is extremely small, and it can be seen that uniform material quality is obtained on the upper and lower surfaces.

In addition, Fig. 28A (conventional warped state in the board width direction) and Fig. 2
FIG. 8B (board widthwise warped state according to the present invention) shows the test results for the conventional C warped state and the board widthwise warped state according to the present invention.

As is clear from this figure, the conventional C warp amount was about 10 mm at its maximum, but in the present invention, it is suppressed to about 1.5 mm at its maximum. Therefore, a very flat shape can be obtained. Further, Fig. 29A shows the start temperature of water cooling in the longitudinal direction of the steel plate, Fig. 29B shows the end temperature of water cooling in the longitudinal direction according to the conventional method, and Fig. 29C shows the end temperature of water cooling in the longitudinal direction according to the present invention.

As is clear from this figure, according to the present invention, the longitudinal temperature deviation at the start of water cooling is improved, and a uniform water cooling end temperature is obtained.

[Effects of the Invention] As is clear from the above explanation, in the present invention, the amount of cooling water injected from each nozzle arranged on the upper and lower surfaces is controlled so that the amount of warpage is within a specified value, and Since the water cooling time is set according to the amount of water applied to the top and bottom surfaces, it is possible to keep the amount of warpage of the hot steel sheet within the specified value during cooling, and to ensure the specified cooling end temperature. It is possible to prevent the occurrence of shape defects due to warpage in the board width direction, and it is possible to obtain a predetermined material quality.

[Brief explanation of the drawing]

FIG. 1 is a diagram showing a part of a W4 temporary production line equipped with a cooling control device for hot rolled steel sheets according to the present invention, and FIG. 2 is a measuring device for measuring the temperature and shape of hot rolled steel sheets being conveyed. FIG. 3 is a diagram showing the arrangement of thermometers and the internal structure of the cooling device; FIG. 4 is a diagram showing the arrangement of thermometers and nozzles in the cooling device; FIG. A schematic configuration diagram of the control system of the cooling control device. FIG. 5 is a diagram showing the overall general operation of the cooling control device for hot rolled steel sheets according to the present invention. FIG. Main flowchart of the cooling control device for rolled steel plates. Figure 7 is a flowchart for performing cooling learning calculations. Figure 8 is a subroutine flowchart for estimating the inlet temperature of hot steel plates. Figure 9 is for calculating plate temperature estimation. Figure 10 is a subroutine flowchart for setting the optimum threading speed for hot steel plates; Figure 11 is a subroutine flowchart for determining the optimum upper/lower ratio of water volume; Figure 12 is a flowchart for determining the shape Fig. 13 is a subroutine flowchart for correcting the sheet passing speed; Fig. 14 is a subroutine flowchart for calculating the acceleration rate for uniformly cooling a heated steel plate; Fig. 15 is a subroutine flowchart for calculating the acceleration rate. Figure 16 is a subroutine flowchart for correcting standard values; Figure 17 is a subroutine flowchart for inlet temperature learning calculation; Figure 18 is a flowchart for calculating actual cooling temperature. Calculation subroutine flowchart. Figure 19 is a conceptual diagram when calculating actual cooling temperature. Figure 20 is a subroutine flowchart for temperature learning calculation. Figures 21 to 23 are processing when performing temperature learning calculation. 24 is a subroutine flowchart of stress strain learning calculation, 25A and 25B are distribution diagrams of cooling stop temperature accuracy between the conventional method and the present invention, and 26A and 26B are conventional Figures 27A and 27B are diagrams showing the hardness distribution in the thickness direction between the conventional and the present invention, Figures 28A and 28B are the diagrams showing the distribution of the hardness in the thickness direction between the conventional and the present invention. Figures 29A to 29C, which show the deformed state of the hot steel plate with the invention, are comparison diagrams of temperature distributions between the conventional method and the present invention in terms of cooling start temperature and cooling end temperature. DESCRIPTION OF SYMBOLS 1... Hot steel plate, 5... Finishing rolling machine, 6... Hot straightening machine, 7... Cooling device, 7C... Nozzle, 8... Solenoid valve (cooling water amount control means), 20-23...
- Optical fiber thermometer 30...Cooling control computer (first calculation means, second calculation means), 31...Rolling control computer 32...Business computer (first calculation means) 36
... Computer for cooling data learning calculation (warp amount calculation means) 38 ... Cooling water amount control device (cooling water amount control means)

Claims (1)

[Claims] A finishing mill that rolls a hot steel plate to a predetermined thickness;
The hot steel plate is placed in the downstream process of the finishing rolling machine, and cooled water is injected from a plurality of nozzles arranged in the width direction of the hot steel plate from both the top and bottom sides of the hot steel plate being conveyed. In a steel sheet manufacturing apparatus equipped with a cooling device that cools the hot steel sheet while being transported, based on various physical property values of the hot steel sheet given in advance,
a first calculating means for calculating the relationship between the amount of cooling water injected from a nozzle placed on the top surface of the cooling device and the heat transfer coefficient of the hot steel plate; a second calculation means for determining the relationship between the heat transfer coefficient of the steel plate; and a calculation unit that determines the relationship between the heat transfer coefficient and the amount of cooling water obtained by the first calculation means and the second calculation means in the thickness direction of the hot steel plate. a calculation means for calculating the history of temperature distribution during the cooling process; a warpage calculation means for calculating the amount of warpage in the sheet width direction of the heated steel sheet from the temperature distribution history; hand,
A cooling control device for a hot-rolled steel plate, comprising a cooling water amount control means for controlling the amount of cooling water injected from each of the nozzles arranged on the upper and lower surfaces so that the amount of warpage falls within a specified value.