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Cold-rolled sheet shape control self-learning method based on optimum algorithm

A self-learning method and shape control technology, applied in the direction of contour control, etc., can solve problems such as inapplicability and jumping

Inactive Publication Date: 2012-06-27
WISDRI WUHAN AUTOMATION
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] The traditional cold-rolled shape control self-learning algorithm based on the optimization algorithm needs to solve complex equations, and the new optimized efficiency factor may jump compared with the original efficiency factor, which is suitable for L2 level process Off-line self-learning or analysis and calculation of computer, real-time requirements for the calculation of the optimization efficiency factor of each shape control mechanism by the shape control self-learning program in the L1-level basic automation CPU, and the action of each shape control mechanism by the shape control program Calculation of adjustments and execution stability requirements do not apply

Method used

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  • Cold-rolled sheet shape control self-learning method based on optimum algorithm
  • Cold-rolled sheet shape control self-learning method based on optimum algorithm
  • Cold-rolled sheet shape control self-learning method based on optimum algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0071] Example 1: On-line detection method of plate shape

[0072] Plate shape refers to the degree of warpage of the plate, and its essence refers to the distribution of residual stress inside the strip. In cold rolling production, the meaning of plate shape refers to the flatness of the strip, that is, the difference in tensile stress of the strip along the width direction. In fact, the meaning of plate shape also includes the lateral thickness difference of the strip steel. Generally, the plate shape we mentioned only represents the flatness of the plate shape without considering the lateral thickness difference. Commonly used plate shape expression methods include: "relative length difference expression", "tensile stress difference expression", "strip section shape expression", "waveform expression" and so on.

[0073] Representation of relative length difference of flatness: such as image 3 As shown, if a section of tension-free strip is cut from the coil, then this section ...

Embodiment 2

[0103] Example 2: Method for determining edge plate shape measurement area and its coverage

[0104] Such as Figure 5 As shown, if starting from the OS side (operating side) and ending at the DS side (transmission side), number the measurement areas of the plate-shaped measuring roll from z_1 to z_n, then there will be two Measurement areas z_os and z_ds.

[0105] The purpose of determining the edge measurement area is to determine the effective flatness detection and control area.

[0106] Such as Figure 5 As shown, the length of the uncovered area on the OS side and the DS side is calculated by the following formula:

[0107] 1_free_os=(w_zone_sum-w_strip)*0.5-strip_shift+d_axial (Equation 2-1)

[0108] 1_free_ds=(w_zone_sum-w_strip)-1_free_os (Equation 2-2)

[0109] Where: 1_free_ds is the length of the uncovered area on the DS side; 1_free_os is the length of the uncovered area on the OS side; w_zone_sum is the sum of the widths of the measurement zone of the plate roll; w_strip i...

Embodiment 3

[0122] Example 3: Setting method of target shape

[0123] In cold rolling production, most of the cold plates after rolling need to be further processed by subsequent processes, such as hot-dip galvanizing and annealing lines. The shape of the plate will affect the operational stability of these lines, and in the subsequent processes, the plate Therefore, when setting the target curve of the rolling mill flatness, the requirements of the subsequent units must be considered. Usually, the target flatness curve is set to micro waves or micro waves.

[0124] In this embodiment, the plate shape setting curve adopts such as Figure 7 The segmented curve shown, which divides the strip width corresponding to the effective flatness detection and control area into two parts, the middle part and the side part. The expression of the curve is as follows:

[0125] f s ( x ) = B * [ x / ( 0.5 * W ) ] + Cl * [ x / 0.5 * W ] 2 ...

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Abstract

The invention discloses a cold-rolled sheet shape control self-learning method based on an optimum algorithm, which includes the steps: by means of gradually and iteratively computing through iterative formulas to approximate an optimum value, enabling an L1 CPU (central processing unit) sheet shape control self-learning program in online application to timely obtain a precise learning sample; and optimizing efficiency factors Pj<u+1> [i] of all plate shape control mechanisms including a back-up roll inclining mechanism, an intermediate roll bending mechanism, a working roll bending mechanism and an intermediate roll traversing mechanism of a rolling mill according to the learning sample, wherein the efficiency factors gradually tend to the optimum value along with increase of self-learning times, and in the self-learning process, the efficiency factors do not increase sharply, therefore computing precision of action regulating quantity of all the sheet shape control mechanisms is improved. By the aid of the cold-rolled sheet shape control self-learning method, optimized schedule of the efficiency factors of all the sheet shape control mechanisms is accelerated, and the advantage of the method on improving the computing precision of the efficiency factors of all the sheet shape control mechanisms is given full play, so that the sheet shape control program is benefited to improve the computing precision of the action regulating quantity of all the sheet shape control mechanisms in real time.

Description

Technical field [0001] The invention relates to the field of cold-rolled strip steel production, in particular to a cold-rolled flatness control self-learning method based on an optimization algorithm. Background technique [0002] Plate shape accuracy is a major quality index of strip steel and an important factor that determines its market competitiveness. With the continuous improvement of flat quality requirements of industrial users such as automobiles, light industry, home appliances, and electrical manufacturing, flatness control technology has become one of the core and most complex technologies in the field of steel rolling. It is developed and researched by various countries in the world after plate thickness control. Another hot issue in China. [0003] Major domestic cold-rolled strip steel production plants use flatness control technology and control systems on their cold-rolled production lines, and these flatness control systems basically rely on imports. At presen...

Claims

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Application Information

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IPC IPC(8): B21B37/28
Inventor 黄杏往王胜勇卢家斌叶刚桥李传涛李四川李海东
Owner WISDRI WUHAN AUTOMATION
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