A control method for improving strip width accuracy

Abstract

The application relates to a control method for improving strip steel width precision, which comprises pass mode design, setting a gauge setter input mode judgment item, setting a tail short stroke trigger mode and width expansion self-learning algorithm optimization; each group of short stroke control parameter matrices is set as an independent group, different modes correspond to different short stroke matrix controls, different rolling pass modes are distinguished during short stroke control, thus solving the pass conflict problem, a gauge setter input mode judgment is newly added, a side pressure amount index is introduced, the dog bone influence width expansion calculation problem is effectively solved, a tail short stroke trigger condition is set to solve the problem that the E1 first pass tail short stroke is not executed, the width value used for calculating long-term width self-learning parameters is compromised through width expansion algorithm optimization, after the next strip steel uses the newly generated width value to perform long-term self-learning calculation, the actual production width is closer to the pre-calculated width, and therefore the strip steel width precision is improved.

Description

Technical Field

[0001] This invention relates to the field of hot-rolled strip steel technology, and in particular to a method for improving the control accuracy of strip steel width. Background Technology

[0002] The roughing area of ​​a traditional hot rolling mill consists of two roughing mills, RM1 and RM2. A roughing mill group consists of horizontal rolling mills R1 and R2 that control the thickness and vertical rolling mills E1 and E2 that control the width.

[0003] The width control of strip steel is mainly controlled by the vertical rolling mill. Different control parameters are set in the model system according to different thickness range indices. During production, the corresponding short stroke and width spread parameters are read from the model system according to the entry thickness of the rolled piece in each pass, thereby realizing the width control of the finished strip steel.

[0004] In actual production, different pass patterns are selected for R1 and R2 depending on the equipment status. When rolling 6 passes, there are generally 3+3 and 1+5 patterns, and when rolling 8 passes, there are 3+5 and 1+7 patterns, etc. With different pass patterns, the reduction amount in each pass is different, and the width after rolling by the horizontal roll will vary. In actual production, for products of the same specifications, such as 3.0 mm thickness and 5.0 mm thickness, when the thickness of the workpiece at the roughing entry is in the same thickness range, the short stroke and width parameters will use the same set of parameters. When different passes and different reduction amounts are used, the same set of parameters will be used, resulting in differences in control results. For the same product, using different pass patterns in roughing will result in defects such as excessive width or narrow length.

[0005] Whether or not the width-fixing machine is put into operation will cause changes in the thickness of the slab. When the width-fixing machine is not put into operation, the thickness of the slab is only the thermal expansion of the original slab. However, when the width-fixing machine is put into operation, the thickness of the edge of the slab is thicker than that of the middle when the slab comes out of the width-fixing machine. This is commonly known as "dog bone". Moreover, the height of the dog bone is different for different steel grades and different heating temperatures, which increases the error of the width prediction.

[0006] Inaccurate tail short stroke triggering condition: Through overall analysis of the tail short stroke execution program and strip data, it was found that occasionally the E1 tail short stroke was not executed, resulting in a narrow strip tail length.

[0007] Different passes have different widths. When the long-term width self-learning parameter is calculated using the pre-calculated width of the model, the new self-learning value often results in excessive width or narrowness when used for the calculation of the next strip. Data analysis revealed that this is due to conflicts between passes. Different specifications and different passes have significantly different widths, leading to abnormal finished product widths.

[0008] In summary, due to the mutual influence of factors such as track conflicts, the use of width-fixing machines, short strokes, and strip width extension, the strip width control cannot be precisely adjusted, often resulting in defects such as excessive width and narrow dimensions, which hinders the quality control of strip width. Summary of the Invention

[0009] This invention provides a control method to improve the accuracy of strip width. By designing the pass mode, adding a judgment item for the input mode of the width-fixing machine, setting a short-stroke trigger mode at the tail, and optimizing the width extension self-learning algorithm, the accuracy of hot-rolled strip width control is effectively improved.

[0010] To achieve the above objectives, the present invention employs the following technical solution:

[0011] A method for improving the control accuracy of strip width includes the following:

[0012] 1) Pass pattern design: Each set of short-stroke control parameters is designed as a matrix and matched with the corresponding pass pattern. Specifically, for each pass rolling pattern, control parameters are set separately according to different rolling pass patterns.

[0013] 2) Set the input method judgment item for the fixed width machine: Set the third dimension index variable of the short stroke group number as the side pressure index. It is set as the side pressure index, with a total of 5 index values: 0, 1, 2, 3, and 4. If the slab side pressure is greater than or equal to 40mm, all are put into the fixed width machine. The index of all products put into the fixed width machine is 0. Other indices are the index values ​​of products not put into the fixed width machine. According to the slab side pressure range of -40 to -20mm, -20 to -0mm, 0 to 20mm, and 20 to 40mm, the corresponding pressing amount indices are 1, 2, 3, and 4.

[0014] 3) Set the tail short stroke trigger mode: When the photoelectric tube on the R1 inlet side of the horizontal rolling mill is turned off, the E1 of the vertical rolling mill is in the steel biting state, and the tail short stroke of E1 starts to be executed.

[0015] 4) Width extension self-learning algorithm optimization: Under different rolling pass modes, the pre-calculated set width and the instrument feedback width value are multiplied by the corresponding weight coefficient and then added together.

[0016] Furthermore, the short stroke values ​​at the beginning and end are set independently for different rolling pass modes. The 3+3 mode takes the first set of short stroke values ​​at the beginning and end, the 3+5 mode takes the second set of short stroke values ​​at the beginning and end, and so on for other pass modes.

[0017] Furthermore, the index variables also include family indexes, width indexes, and fixed-width machine input mark indexes.

[0018] Furthermore, the weighting coefficient is 0.3 to 0.7.

[0019] Furthermore, the different rolling modes include 3+3, 3+5, 1+5, and 1+7 modes.

[0020] Compared with the prior art, the beneficial effects of the present invention are:

[0021] 1) Set each group of short-stroke control parameter matrices to be an independent group. When implementing 3+3 mode, 3+5 mode and other different pass modes, use different short-stroke matrix control to distinguish different rolling pass modes when implementing short-stroke control, thereby solving the pass conflict problem.

[0022] 2) Added a new method for determining the input mode of the fixed width machine, introduced a side pressure index, and worked together with the family index and width index to effectively solve the problem of dog bone affecting the width calculation;

[0023] 3) Setting the tail short stroke trigger condition resolved the issue of the tail short stroke not executing in the first pass of E1;

[0024] 4) Through the optimization of the width extension algorithm, the width value used to calculate the long-term width self-learning parameter is compromised. After the next strip steel is calculated using the newly generated width value for long-term self-learning, the actual production width is closer to the pre-calculated width. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the structure of the present invention.

[0026] In the diagram: 1. Different passes correspond to short strokes; 2. Strip steel before entering the width sizing machine; 3. Width sizing machine; 4. Vertical roll. Detailed Implementation

[0027] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings:

[0028] See Figure 1 This is a schematic diagram of the structure of the present invention. The present invention provides a method for improving the control accuracy of strip width, comprising the following:

[0029] 1) Rolling pass pattern design: In the model control program, the rolling pass pattern is used as the judgment condition. Each set of short-stroke control parameters is designed as a matrix. The matrix is ​​configured with dedicated short-stroke control parameters and matched with the corresponding rolling pass pattern. Specifically, each rolling pass pattern is independent and does not affect each other. The different passes correspond to short stroke 1. The 3+3, 3+5, 1+5, and 1+7 patterns correspond to short stroke 1, short stroke 2, short stroke 3, and short stroke 4, respectively. Control parameters are set according to different rolling pass patterns to control the same set of short-stroke parameters, thereby solving the problem of different rolling pass patterns using the same set of short-stroke parameters.

[0030] 2) Setting the input method judgment item for the width-fixing machine 3: Add a third-dimensional index variable to the short-stroke group number based on the original two-dimensional data and set it as the side pressure index. There are 5 index values, namely 0, 1, 2, 3, and 4. The index variable also includes the family index, width index, and width-fixing machine 3 input mark index. The model calculates the width reduction of the slab and the finished product in advance based on the original data of the slab. First, it judges whether to input the width-fixing machine 3 based on the input conditions of the width-fixing machine 3. If the width-fixing machine 3 is input, the width reduction index of the strip 2 before entering the width-fixing machine is forcibly set to 0. The model control parameters will query the parameters according to this index to control the width. When the judgment conditions do not meet the input conditions of the width-fixing machine 3, the model parameter values ​​are retrieved according to the actual pressure measurement, according to the corresponding indexes 1, 2, 3, and 4 in the intervals of -40~-20mm, -20~-0mm, 0~20mm, and 20~40mm, so that the input of the width-fixing machine 3 and the conditions can be independently controlled by parameters, eliminating the influence of whether the width-fixing machine 3 is input or not.

[0031] 3) Set the tail short stroke trigger mode: Through the improvement of the PLC control program, the setting condition is that the photoelectric tube on the R1 entrance side of the horizontal roll mill is off at the same time that E1 of the vertical roll 4 mill is in the steel biting state, and the tail short stroke control of E1 starts to be executed.

[0032] 4) Width self-learning algorithm optimization: Under different rolling pass modes, the pre-calculated set width and the instrument feedback width value are multiplied by the corresponding weight coefficient and added together. The set width weight coefficient is 0.4, and the instrument feedback width weight coefficient is 0.6. Therefore, the self-learning width value used = set width value * 0.4 + instrument width value * 0.6. This makes the width value used to calculate the long-term width self-learning parameter more moderate. After the next strip steel is calculated using the newly generated width value, the actual production width is closer to the pre-calculated width.

[0033] The above embodiments are implemented based on the technical solution of the present invention, providing detailed implementation methods and specific operation processes. However, the scope of protection of the present invention is not limited to the above embodiments. Unless otherwise specified, the methods used in the above embodiments are conventional methods.

Claims

1. A method for improving the control accuracy of strip width, characterized in that, Includes the following: 1) Pass pattern design: Each set of short-stroke control parameters is designed as a matrix and matched with the corresponding pass pattern. Specifically, for each rolling pass pattern, control parameters are set separately according to different rolling pass patterns. 2) Set the input method judgment item for the fixed width machine: Set the third dimension index variable of the short stroke group number as the side pressure index, with a total of 5 index values: 0, 1, 2, 3, and 4. If the slab side pressure is greater than or equal to 40mm, all slabs are put into the fixed width machine. The index of all products put into the fixed width machine is 0. Other indices are the index values ​​of products not put into the fixed width machine. The slab side pressure ranges of -40 to -20mm, -20 to 0mm, 0 to 20mm, and 20 to 40mm correspond to the 1, 2, 3, and 4 pressure indexes. The index variables also include family indexes, width indexes, and fixed-width machine input mark indexes; 3) Set the tail short stroke trigger mode: When the photoelectric tube on the R1 inlet side of the horizontal rolling mill is turned off, the E1 of the vertical rolling mill is in the steel biting state, and the tail short stroke of E1 starts to be executed. 4) Width extension self-learning algorithm optimization: Under different rolling pass modes, the pre-calculated set width and the instrument feedback width value are multiplied by the corresponding weight coefficient and added together; the weight coefficient is 0.3 to 0.

7.

2. The method for improving the control accuracy of strip width according to claim 1, characterized in that, The different rolling pass modes include 3+3, 3+5, 1+5, and 1+7 modes. The short stroke values ​​at the beginning and end are set independently for different rolling pass modes. The 3+3 mode takes the first set of short stroke values ​​at the beginning and end, the 3+5 mode takes the second set of short stroke values ​​at the beginning and end, and so on for other pass modes.

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