Rough rolling short stroke control and self-learning method

A technology of short-stroke control and self-learning method, applied in the field of rough rolling short-stroke control and self-learning, can solve the problems that the control effect cannot fully meet the actual production requirements, and the short-stroke control cannot be adjusted in real time.

Active Publication Date: 2013-06-12
BEIJING ARITIME INTELLIGENT CONTROL +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The traditional short-stroke control is to give a curve or control the broken line, and then manually adjust the shape of the curve or broken line according to the me

Method used

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  • Rough rolling short stroke control and self-learning method
  • Rough rolling short stroke control and self-learning method

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Embodiment Construction

[0096] The present invention will be further described below according to the embodiments and corresponding drawings. A control and self-learning method of a rough rolling short stroke of the present invention comprises the following steps:

[0097] 1) Read slab PDI data (slab width, thickness, steel type, intermediate billet thickness, finished product width, etc.), equipment parameters (roll diameter, rolling mill maximum rolling force, torque, etc.), when the slab reaches the roughing mill The measured value is extracted from the width measuring instrument, and data preparation is made for the self-learning of the short-stroke model. Among them, the equipment parameters are used to check the rolling mill after the calculation is completed.

[0098] 2) According to the slab data (slab width, thickness, steel type, intermediate billet thickness, finished product width, etc.), read the short-stroke model parameters layer by layer to read the short-stroke model parameters, and...

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Abstract

The invention relates to a rough rolling short stroke control and self-learning method and belongs to the technical field of steel rolling process control. A short stroke control curve mode adopts the polynomial, the second stage is adopted for calculating four coefficients Alpha 0, Alpha 1, Alpha 2 and Alpha 3 of a cubic polynomial in the continuous-rolling rough rolling vertical roller short stroke control process, the coefficients are issued to the first stage, and the operation is executed according to the cubic curve when the first stage receives the parameters issued by the second stage, and the self-learning with the rough rolling short stroke curve is obtained by aiming the rough rolling short stroke curve. The head and tail short stroke control is carried out during the rough rolling vertical roller manufacturing, and the short stroke position at the head and tail side pressure is precisely calculated. The method has the advantages that after the method is adopted, the head and tail width is obviously improved, and the width exceeding quantity at the head and tail parts is reduced by about 10mm.

Description

technical field [0001] The invention belongs to the technical field of steel rolling process control, in particular to a rough rolling short stroke control and self-learning method. Background technique [0002] It is an important research topic to improve the yield in strip hot rolling production. During the rolling of the slab in the hot continuous rolling roughing mill, when the slab is subjected to a large lateral pressure, since the head and tail of the slab are not affected by the "rigid end", this part of the metal will flow to the middle after vertical roll rolling. And non-uniform extension, resulting in loss of width. In addition, the "dog-bone" shape in the middle part of the slab is more severe than that at both ends of the slab, and the amount of recovery after flat roll rolling is also greater than that at both ends. Therefore, after the flat rolling pass, the original width loss is further enlarged. Before entering the finishing mill, it is necessary to cut...

Claims

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Application Information

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IPC IPC(8): B21B37/16
Inventor 武凯胡宇宋向荣宋敏李亚锋田华余四清刘新忠
Owner BEIJING ARITIME INTELLIGENT CONTROL
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