Strip steel cold rolling pickling parameter optimization method

An optimization method and pickling technology, which is applied in the field of cold rolling, can solve the problems that the pickling parameters cannot achieve the best strip pickling effect, and achieve the effect of improving production efficiency

Pending Publication Date: 2022-07-26
唐山扬邦钢铁技术研究院有限公司 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the deficiencies of the prior art, the present invention provides a strip steel cold rolling pickling parameter optimization method, which solves the problem that the pickling parameters cannot achieve the best strip pickling effect

Method used

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  • Strip steel cold rolling pickling parameter optimization method

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Effect test

Embodiment 1

[0028] like figure 1 As shown, the embodiment of the present invention provides a method for optimizing the pickling parameters of strip cold rolling, including the following steps executed by a computer:

[0029] (a) Collect incoming process parameters;

[0030] (b) Calculate the thickness h of the incoming oxide layer: because there is a functional relationship between the thickness of the incoming iron oxide scale and the incoming process parameters, h=f(P, C, Si, Mn, T j ), where P is the strip steel grade, T j is the coiling temperature; the incoming iron oxide scale is calculated according to the collected incoming process parameters;

[0031] (c) Define the optimization function F(X)=f(h,X);

[0032] (d) Given initialization parameter X;

[0033] (e) define the search direction;

[0034] (f) Perform a one-dimensional search in the search direction: let y0=X(k), perform a one-dimensional search along d0, d1, d2, d3 in turn, for all j=1, 2, 3, 4, denote f(y (j-1)+λ(...

Embodiment 2

[0045] like figure 1 As shown, the embodiment of the present invention provides a method for optimizing the pickling parameters of strip cold rolling, including the following steps executed by a computer:

[0046] (a) Collection of incoming process parameters: randomly collect a group of incoming process parameters of a certain grade of strip steel, mainly including incoming grade A510L, C content of 0.155%, Si content of 0.9%, Mn content of 1.85% and coiling temperature of 500°C;

[0047] Subsequently, in step (b), the thickness h of the incoming oxide layer is calculated: because there is a functional relationship between the thickness of the incoming iron oxide scale and the incoming process parameters, h=f(P,C,Si,Mn,T j ), where P is the strip steel grade, T j is the coiling temperature. According to the collected incoming process parameters, the incoming iron oxide scale is calculated, and the calculated result is 22 μm;

[0048] Then, in step (c), define an optimizati...

Embodiment 3

[0057] like figure 1 As shown, the embodiment of the present invention provides a method for optimizing the pickling parameters of strip cold rolling, including the following steps executed by a computer:

[0058] (a) Collection of incoming process parameters: randomly collect a group of incoming process parameters of a certain grade of strip steel, mainly including incoming grade JSH440W, C content 0.17%, Si content 1.35%, Mn content 2.1% and coiling temperature 500 ℃;

[0059] Subsequently, in step (b), the thickness h of the incoming oxide layer is calculated. Since there is a functional relationship between the thickness of the incoming iron oxide scale and the incoming process parameters, h=f(P,C,Si,Mn,T j ), where P is the strip steel grade, T j is the coiling temperature. According to the collected process parameters, the incoming iron oxide scale is calculated, and the calculated result is 24 μm;

[0060] Then, in step (c), define an optimization function F(X)=f(h,...

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Abstract

The invention provides a strip steel cold rolling pickling parameter optimization method, and relates to the field of cold rolling. The strip steel cold rolling pickling parameter optimization method comprises the following steps executed by a computer: (a) collecting incoming material process parameters; (b) calculating the thickness h of an oxide layer of the supplied material; (c) defining an optimization function F (X) = f (h, X); (d) giving an initialization parameter X; (e) defining a search direction; (f) sequentially performing one-dimensional search on the search direction; (g) checking whether a termination condition is satisfied; (h) determining a search direction; (i) adjusting a search direction; (j) not adjusting the search direction; and (k) finally outputting an optimal pickling speed v meeting constraint conditions and a corresponding pickling process parameter combination Xzy at the moment, and completing optimization of the parameter model. By summarizing production parameters of the cold rolling pickling unit, the optimal pickling speed of the unit is calculated by integrating pickling influence parameters in multiple aspects, and the production efficiency is further improved.

Description

technical field [0001] The invention relates to the technical field of cold rolling, in particular to a method for optimizing the pickling parameters of strip steel cold rolling. Background technique [0002] In the pickling process of strip cold rolling, the optimal control of pickling parameters is an important link to ensure the surface quality of strip steel. At the same time, by adjusting the ratio of various pickling parameters, the pickling speed can be improved on the premise of ensuring the quality of pickling. Therefore, the research on the optimization control of pickling parameters is also an important means to improve the output of the unit. [0003] The optimization control of pickling parameters is mainly to combine the key model of pickling, namely the pickling speed prediction model and the finite element simulation model of the turbulent process of the pickling unit. , run at the maximum pickling speed to ensure the output of the unit. [0004] At present...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/20
CPCG06F30/20
Inventor 张岩岩崔熙颖白晓帅顾清白振华
Owner 唐山扬邦钢铁技术研究院有限公司
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