KR100437637B1 - Shape control method for cold rolling mill with As-U roll - Google Patents

Abstract

The present invention provides a shape control method for a stainless cold rolled steel sheet in a method for controlling the shape of a stainless steel cold rolled sheet, which recognizes the shape of the steel sheet in a multi-stage rolling mill such as a ZRM (Sendzimir mill) and controls the shape of the stainless steel cold rolled sheet with a plurality of drivers. Its purpose is to.

According to the present invention, a shape of a stainless steel plate using a stainless cold rolling mill 200 having an AZ-roll (B, C), which is composed of a plurality of saddles 205 in the axial direction, provides a rolling force. In the control method, receiving the shape of the stainless steel sheet 201 to obtain a shape error in consideration of the reference value of the shape, recognizing the shape of the stainless steel sheet 201, the recognized shape, the thickness of the entry and exit side, the rolling speed And obtaining and controlling a control amount of the plurality of saddles 205 of the egg-roll (B, C) from the position measurement of the egg-roll (B, C), the steel grade, and the width of the plate. A shape control method for a steel sheet is provided.

Description

Shape control method for cold rolling mill with As-U roll

The present invention relates to a shape control method of a stainless steel sheet using a multi-stage rolling mill, and more particularly, to a shape control method of a stainless cold rolled steel sheet capable of stabilizing and automating the shape control of the stainless steel sheet in the cold rolling of the stainless steel sheet.

1 is a schematic view showing a general multi-stage rolling mill.

As shown in FIG. 1, ZRM (Sendzimir mill) 1, which is one of the multi-stage rolling mills, is a total 20-stage rolling mill having 10 rolls formed at the upper and lower parts thereof, and a stainless cold rolled steel sheet 3 through the ZRM 1. ) To control the shape.

On the other hand, in order to control the shape of the stainless cold rolled steel sheet 3, the driver provided in the ZRM 1 is operated. The actuator is an As-U Roll (B, C), and in a multi-stage mill, the A-U Roll (B, C) is a roll composed of eight saddles in the axial direction. By the pressure by the top and bottom of the saddle, the amount of reduction applied to the work roll of the ZRM 1 is controlled to control the formation of the stainless cold rolled steel sheet (3).

However, according to the operation of the hydraulic system has a disadvantage that the speed of the process is reduced. And, in order to control this shape, the operator must manually adjust the driver of the ZRM (1).

On the other hand, with the shape control method described in "Japanese Patent Laid-Open No. 4-127908 (name of the invention: shape control method and apparatus of Senji Miru)", the shape of the steel sheet is detected to recognize the shape pattern of the steel sheet, and the shape It is a method of controlling the multi-stage rolling machine by previously defining the operation method of the driver corresponding to a pattern. The shape recognition uses hierarchical neural network, and fuzzy reasoning is used to obtain the reduction operation of pattern recognition.

However, the neural network used in such a shape control method is not reliable to use the output value for fuzzy inference because the shape recognition result changes greatly with learning. In addition, in fuzzy reasoning, the influence coefficient is forcibly set, and thus the reliability of the accuracy is low.

In addition, as the shape control method introduced in Japanese Patent Laid-Open No. 4-238614 (name of the invention: shape control method for strip rolling), shape parameters are determined and their values are calculated, and based on the calculated parameters. It is a control method for determining the operation amount of the driver.

However, in setting the shape parameters corresponding to the shape recognition sensors, it is difficult to accurately obtain each influence coefficient, and there is a disadvantage in that the use of the evaluation function of the shape becomes inadequate if the influence coefficient is in error.

On the other hand, the shape control method of the conventional stainless steel cold rolled steel sheet classified the symmetric component and the asymmetrical component of the current cold rolled stainless steel sheet by using a formula or model, but this method is reliable in the shape recognition in the width direction of the steel sheet Apart from this, there is a problem in that only a specific part in the width direction of the steel sheet is used, and in addition, in determining the control amount of the driver, there is a disadvantage in that it is difficult to control the mutual relationship between the drivers.

The present invention is provided to solve the problems of the prior art as described above, a stainless steel using a rolling mill equipped with an ed-yu-roll to control the shape of the steel sheet with a control logic made using the fuzzy control and the actual experience of the field It is an object of the present invention to provide a method for controlling the shape of a steel sheet.

1 is a schematic view showing a general multi-stage rolling mill,

FIG. 2 is a front sectional view of a stainless cold rolling mill with an egg-roll in accordance with an embodiment of the present invention.

FIG. 3 is a side view showing an ed-yu roll of the stainless cold rolling mill shown in FIG. 2;

4 is a block diagram of a fuzzy shape control method for shape control according to an embodiment of the present invention;

5 is a flowchart illustrating a fuzzy shape control method for shape control according to an embodiment of the present invention;

6 is an exemplary performance diagram illustrating a steel sheet controlled according to the shape control method illustrated in FIG. 5.

♠ Explanation of symbols on the main parts of the drawing ♠

1, 200: ZRM (Sendzimir mill) 201: Stainless steel sheet

203: measuring roll 207: solenoid switching valve

209: hydraulic cylinder 230: input / output board

250: Shape controller 270: MMI (Man-Machine Interface)

According to the present invention for achieving the object as described above, the shape control method of a stainless steel sheet using a stainless cold rolling mill having an ed-yu-roll is composed of a plurality of saddle (Saddle) in the axial direction to provide a reduction force Obtaining a shape error in consideration of the reference value of the shape by receiving the shape of the stainless steel sheet, recognizing the shape of the steel sheet, measuring the recognized shape and the entry-side thickness, the rolling speed, and the position of the E-roll A shape control method of a stainless steel sheet is provided, comprising the step of obtaining and controlling a control amount of a plurality of birds of an egg-roll from a value, a steel grade, and a width of a plate.

Further, according to the present invention, after classifying the shape of the stainless steel sheet into a plurality of patterns in the shape recognition step of the steel sheet, by combining the plurality of patterns to recognize the original shape of the steel sheet, purge from the recognized value The controller controls the shape of the stainless steel sheet by calculating the control amount of the egg-roll by inputting it into the rolling mill.

In addition, according to the present invention, after calculating the control amount of the ed-yu-roll, the DC level of the driver is obtained by Equation 1, and according to Equation 3, the control amount according to the rolling speed acceleration and deceleration is compensated, and according to the exit thickness of the steel grade and the steel sheet. There is provided a shape control method for a steel sheet which compensates for the control amount and determines the compensation amount based on the control amount according to Equation 2.

In the following, with reference to the accompanying drawings, a preferred embodiment of the shape control method of a stainless steel sheet using a rolling mill equipped with an egg-yu-roll according to the present invention will be described in detail.

In the drawings, FIG. 2 is a front sectional view of a stainless cold rolling mill with an egg-roll according to an embodiment of the present invention, and FIG. 3 is a side view showing an egg-roll of the stainless cold rolling mill shown in FIG. 4 is a configuration diagram of a fuzzy shape control method for shape control according to an embodiment of the present invention, and FIG. 5 is a flowchart illustrating a fuzzy shape control method for shape control according to an embodiment of the present invention. 6 is an exemplary performance diagram illustrating a steel sheet controlled according to the shape control method illustrated in FIG. 5.

As shown in Figures 2 and 3, the stainless steel cold rolling mill comprises a ZRM 200 consisting of a total of 20 rolls, and a measuring roll 203 for measuring the shape of the stainless cold rolled steel sheet (hereinafter referred to as "steel plate"). do.

On the other hand, the driver used for shape control among twenty rolls A-T of the ZRM 200 is an E-roll (B, C). These saddle rolls (B, C) are provided with eight saddles (205) on one axis, and are solenoid operated valves (hereinafter referred to as "solenoid valves"). The rack 211 is moved by the expansion and contraction of the stroke of the hydraulic cylinder 209 is installed, the rack 211 is moved while the E-roll (B, C) eccentricity, the pressure reduction force is lower Is transmitted to the second intermediate roll (J, K) of. The control variable thus represents the up-and-down position of the eight saddles 205 installed on the E-roll (B, C).

In addition, the shape input of the steel plate 201 is input from the measuring roll 203 provided in front and back of the ZRM200. 32 load cells (not shown) are installed in the measuring roll 203, and the steel sheet 201 is pushed by the force to press the load cell of the measuring roll 203. Recognize the shape of.

On the other hand, as shown in Figure 4, the operation flow chart of the shape control device is 32 shape data measured on the measuring roll 203 from the ZRM 200, the thickness of the steel sheet on the entry and exit side of the ZRM 200, the rolling speed , The current position of the E-roll (B, C), the steel grade, the width of the steel sheet, the tension of the steel sheet is measured and input to the sensor signal input and output board 230.

The signal input to the input / output board 230 is input to the shape controller 250 again to determine the reduction control amount and then output to the input / output board 230 again.

The shape controller 250 includes two CPUs, three analog input / output boards, and five digital input / output boards. Here, the reason for the two central processors is that one is responsible for input / output of various signals and operation of the driver, and the other is for operating the shape control logic. The shape controller 250 uses a Versa Module Eurocard (VME) system. The operation state of the shape controller 250 and the control state of the rolling mill are provided to the user through a Man-Machine Interface (MMI) 270. The MMI 270 is a personal computer (PC) dedicated to the VME. Information between the MMI system and the VME system is achieved by accessing the shared memory.

Meanwhile, in the flowchart of the fuzzy shape control method illustrated in FIG. 5, the initialization processing step S1 has an initial value by receiving the current positions of the E-rolls B and C. FIG. At this time, the DC level is calculated from the position values of the eight saddles 205 of the E-roll (B, C), and variables such as a gap limit and a scale are initialized.

Herein, the DC level means eight saddles 205 positions (Top Crown 1, Top Crown 2, ..., Top Crown 8) of Eze-U-Roll (B, C); TC 8 ") is to control while maintaining the average value. For example, if the DC level is 55, the mean value is 55 no matter what each TC has. The method of calculating the DC level is shown in Equation 1.

Here, n = 1,2, ..., 8.

On the other hand, (a) of Equation 1 is an expression showing the initialization of the variable, (b) is a formula obtained by the sum of the current position of the eight TC, (c) is a formula of calculating the average value of the current position of the eight TC Here, TCNum is 8, (d) is an expression which subtracts the DC level value initially set from the average value.

In the gap limit, eight TCs are connected to one axis, and when the position between neighboring TCs increases, the axes are stressed, and in severe cases, the axes are damaged. Thus, it indicates the position value allowed between neighboring TCs.

In addition, the scale element is an element that is multiplied by the control amount in consideration of the output thickness of the steel sheet, the steel type, the rolling speed acceleration and deceleration interval, and the like.

In this manner, after the variable initialization is executed, it is determined whether manual intervention is performed (S2). Here, if there is manual intervention, the manual intervention amount is output (S3), and if there is no manual intervention, the rolling speed is checked (S4). At this time, if the rolling speed is 30mpm or more, the TC purge control routine is executed (S5), and if so, the TC current position is output as it is (S10).

In the TC fuzzy control process, a shape error obtained by subtracting a target profile for each pass from the measured shape is input to the fuzzy controller. The TC fuzzy controller is a 4-input * 1 output controller, and each TC consists of one, that is, eight in total. Shape data obtained from 32 load cells has various patterns. For simplicity, the shape data is divided into four cells and then classified into five patterns for each cell.

The patterns of the five patterns are classified into a first pattern (/), a second pattern (iii), a third pattern (iii), a fourth pattern (iii), and a fifth pattern (-). The combination of the five patterns of can be inferred from the original shape of the steel sheet. After recognizing the shape by the combination of the patterns, the conditional part of the fuzzy rule is constituted. There are eight purge controllers for each of the eight TCs, and the input variable selection of the controller is determined according to the width of the steel plate 201.

In the case of 4 feet (832 mm ≤ width ≤ 1352 mm), for example, shape data is input from 13, 14, 15, and 16 load cells to TC # 4, and shape from 20, 19, 18 and 17 load cells to TC # 5. Data is input, and in TC 3, shape data is input from load cells 9, 10, 11 and 12, and in TC 6, shape data is input from 24, 23, 22 and 21 load cells.

In TC 2, the shape data is input from three load cells, namely, start load cell, start load cell + 1, start load cell + 2, and start load cell + third load cell, in order from the load cell started on the working side. Shape data is input from three load cells, that is, the last load cell, the last load cell-1, the last load cell-2, and the last load cell-3 th load cell, in order from the side to the end of the load cell. TC 1 is inputted from the start load cell, the start load cell + 1, the start load cell + 2, the start load cell + the third load cell regardless of the plate width, TC 8 is also the last load cell, regardless of the width of the steel sheet, Shape data is input from the last load cell-1, the last load cell-2, and the last load cell-3rd load cell.

If the shape error has a large value of ± 40 N / mm ² or more on the basis of the width end, TC 2, 7, 1, and 8 are driven to prevent the meandering fuzzy control unit. The fuzzy controller uses the trigonometric method of fuzzy, the inference was made by the min-MAX method, and the fuzzy by the Center of Gravity (COG) method. The rule used was 555. In the process, the output of the fuzzy controller is ΔU. When the previous input value U [k-1] is added to it, eight control amounts U [k] are calculated.

Where k = 1,2, ..., n; n is an integer and n = 1, 2, ..., 8 is the number of executions of the controller.

The scale value of the control amount is determined by the acceleration and deceleration of the rolling speed and the steel type and exit thickness.

The method of calculating the scale value of the control amount according to the rolling speed is shown in Equation (3).

Herein, Equation 3 is applied to DelSpd ≥ 90mpm, and scale TC = 1 in other cases.

On the other hand, the steel grades are set to 0.5 to 0.9 and 0.8 to 0.9, respectively, according to the stainless steel 300 series and the 400 series. The scale amount according to the exit thickness of the steel sheet is 0.9 in the thickness of 1.0 to 1.1 mm, and 0.5 to 0.8 in the thickness of 1.0 mm or less.

In the next process, it is checked whether the eight control amounts u [k] calculated by the fuzzy controller are in the respective driving ranges of the TC (S6).

For example, after checking whether TC 4 is between 20 mm and 82 mm, the DC level is calculated from the next 8 TC values (S7). The DC level is calculated to prevent the overall pattern of the TC from falling down (i.e., pointing downward). The average value of the TC is obtained to have a vertical movement range based on this value.

Regardless of the value of TC, the absolute value of the upward value and the downward value based on the DC level is the same. The DC level is always recalculated when there is manual intervention.

In the next process, the control compensation process of the width end, if the shape of both ends of the working side and the driving side is ± 20 N / mm ² or more, the TC output amount is compensated according to the width (S8).

After the above process, the gap limit between adjacent TCs is finally checked. This is to protect the equipment because TC is connected to one axis, a large gap limit between neighboring birds puts a lot of stress on the axis. In the case of manual control, there is no gap limit, and only 25 mm is set in the case of automatic control (S9). If the gap limit is set, the reference TC is required (S10).

For example, if TC 4 becomes the reference and the position difference from TC 5 exceeds the gap limit of the reference, TC 5 moves along TC 4. TC 1 and TC 8 are the criteria for the importance of controlling the width end of steel plate.

For example, if TC 1 is 30 mm, TC 2 is 50 mm, and the gap limit is 15 mm, TC 1 maintains 30 mm, but TC 2 has 45 mm.

After the above steps, the final eight control quantities of TC are output.

The embodiment described above will be described with the graph of FIG. 6.

The thickness of the steel sheet used was 2.93 mm, the product thickness was 0.498 mm, the steel grade was STS 304, the plate width was 1242 mm, and a total of 13 passes were tested.

Fig. 6A is a typical shape in two passes. Symmetry is good and shape error is very good. On the other hand, Fig. 6 (b) shows that the phenomenon is good and increases in the last pass until 10 passes of I-units (a typical value showing the flatness of the shape). The average of all I-units is 19.2.

6 (c) shows the maximum speed for each pass. You can see that it was the fastest in 4 passes. This indicates that the shape was very stable in 4 passes. One pass is manual control of the shape controller according to the present invention, and automatic control is performed until the last pass in two passes.

As described in detail above, the shape control method of the stainless steel sheet using the rolling mill equipped with the ed-yu-roll of the present invention is product quality by the operation stabilization through the automation of the shape control by the ed-yu-roll and the improvement of the shape degree There is an advantage that can be improved.

The technical idea of the shape control method of the stainless steel sheet using the rolling mill equipped with the EZ-roll of the present invention has been described above with the accompanying drawings, but this is by way of example to illustrate the best embodiment of the present invention. It is not intended to limit. In addition, it is obvious that any person skilled in the art can make various modifications and imitations without departing from the scope of the technical idea of the present invention.

Claims (3)

In the shape control method of a stainless steel sheet using a stainless cold rolling mill having an As-U Roll composed of a plurality of saddles in the axial direction to provide a rolling force, Obtaining shape error data considering the reference value of the shape by receiving the shape of the stainless steel sheet measured from a measuring roll composed of a plurality of load cells arranged in the width direction of the stainless steel sheet in front and rear of the cold rolling mill, respectively; Inputting the shape error data into a fuzzy controller and classifying the pattern into a plurality of patterns and combining the plurality of sorted patterns to recognize the original shape of the stainless steel sheet, and The control amount of a plurality of birds of the E-roll is calculated from the recognized shape of the stainless steel sheet, the thickness of the entry side, the rolling speed, the position measurement of the Eze-roll, the width of the steel grade and the plate, and then the And controlling the shape of the stainless steel plate by inputting it into a cold rolling mill. The method of claim 1, The shape error data is classified into five patterns, and the five patterns include the first pattern (/), the second pattern (＼), the third pattern (∧), the fourth pattern (∨), and the fifth pattern (−). Shape control method of the stainless steel sheet, characterized in that the classification. The method according to claim 1 or 2, After calculating the control amount of the ed-you-roll, the DC level of the driver is obtained by Equation 1, the control amount according to rolling speed acceleration and deceleration is compensated by Equation 3, and the control amount according to the exit thickness of steel grade and steel sheet is compensated by Equation 2 Shape control method of the stainless steel sheet, characterized in that for determining the compensation amount by the control amount. Equation 1 is (a), (b), (c), (d), where n = 1,2, -8 Equation 2 is Where k = 1,2, ..., n is an integer, n = 1, 2, ..., 8 is the number of executions of the controller, Equation 3 is the scale TC = (100-DelSpd) / 100.0, where DelSpd ≥ 90 mpm.