Method for controlling surface roughness of cold-rolled strip steel

Abstract

The invention discloses a method for controlling the surface roughness of cold-rolled strip steel, and belongs to the technical field of strip steel surfaces. The method comprises the following steps that the target roughness of the surface of the cold-rolled strip steel of each cold-rolling mill rack and an error allowable value are obtained; initial parameters of the cold rolling mill are obtained, specifically, the roller roughness Rawi, i = {1, 2, 3, 4 and 5} represents 1-5 racks, the original roughness Ra0 after strip steel acid pickling is conducted, and the strip steel roughness Rai of an outlet of each rack is calculated based on the obtained initial parameters of the cold rolling mill; and on the basis of the calculated roughness of the strip steel at the outlet of each rack and the target roughness and error allowable value of the surface of the cold-rolled strip steel of each cold-rolling mill rack, parameter optimization is carried out on the roughness of the roller of each rack, the optimized roughness of the roller of each rack is obtained, and then control over the surface roughness of the cold-rolled strip steel is achieved. The control method for the surface roughness of the cold-rolled strip steel is based on an advanced data analysis and processing technology, the production stability can be improved, and the production fluctuation and quality problems caused by human factors can be reduced.

Description

Technical Field

[0001] This invention belongs to the field of strip steel surface technology and relates to a method for controlling the surface roughness of cold-rolled strip steel. Background Technology

[0002] With the rapid development of modern industry, cold-rolled strip steel, as an important metallic material, has been widely used in many industries such as automobiles, home appliances, and construction. Especially in high-end manufacturing, increasingly higher requirements are being placed on the surface quality of cold-rolled strip steel. Surface roughness is one of the key indicators for measuring the surface quality of cold-rolled strip steel; it not only relates to the appearance of the product but also directly affects its performance and service life. Traditional methods for controlling the surface roughness of cold-rolled strip steel mainly rely on the experience and technical level of operators, achieved by adjusting rolling process parameters. However, this method has many shortcomings, such as long adjustment cycles, low precision, and poor stability. Therefore, developing an intelligent method for controlling the surface roughness of high-grade cold-rolled strip steel has become an urgent problem to be solved in the current cold-rolled strip steel production field. Summary of the Invention

[0003] To solve the above problems, the technical solution adopted by the present invention is: a method for controlling the surface roughness of cold-rolled strip steel, comprising the following steps:

[0004] S1: Obtain the target roughness and allowable error value of the surface of the cold-rolled strip steel for each cold rolling mill stand;

[0005] S2: Obtain the initial parameters of the cold rolling mill: roll roughness Ra wi , i={1,2,3,4,5} represents the original roughness Ra0 of the strip steel after pickling for frames 1-5;

[0006] S3: Based on the acquired initial parameters of the cold rolling mill, calculate the strip roughness Ra at the exit of each stand. i ;

[0007] S4: Based on the calculated surface roughness of the strip at the exit of each stand, as well as the target surface roughness and allowable error of the cold-rolled strip surface of each cold rolling mill stand, the parameters of the roll roughness of each stand are optimized to obtain the optimized roll roughness of each stand, thereby achieving the control of the surface roughness of the cold-rolled strip.

[0008] Furthermore, the process of optimizing the parameters of the roll roughness of each stand is as follows:

[0009] S41: Define the intermediate variable ΔRa i =Ra Ti -Ra i ΔRa w The optimal step size for roll roughness;

[0010] S42: Let i = 1;

[0011] S43: Determine whether i≤5 is true. If true, proceed to step S44; otherwise, proceed to step S47.

[0012] S44: Let k = 0;

[0013] S45: Let Ra wi =Ra wi +kΔRa w Calculate Ra i and ΔRa i ;

[0014] S46: Determine ΔRa i ≤ΔRa max If the condition is true, let i = i + 1 and proceed to step S43; if the condition is false, let k = k + 1 and proceed to step S45.

[0015] S47: Output the optimized roll roughness Rawi, i = {1, 2, 3, 4, 5}.

[0016] Furthermore, the surface roughness R of the strip at the outlet of each frame... ai The calculation formula is as follows:

[0017] Ra i =a0+a1Ra wi +a2Ra wi 2 +a3Ra i-1

[0018] Among them, Ra i It represents the surface roughness of the strip steel at the current rack exit, and a0…a3 are the coefficients of the polynomial regression.

[0019] A device for controlling the surface roughness of cold-rolled strip steel includes:

[0020] Acquisition Module I: Used to acquire the target roughness and allowable error value of the surface of cold-rolled strip steel for each cold rolling mill stand;

[0021] Acquisition Module II: Used to acquire the initial parameters of the cold rolling mill: roll roughness Ra wi , i={1,2,3,4,5} represents the original roughness Ra0 of the strip steel after pickling for frames 1-5;

[0022] Calculation module: Used to calculate the strip roughness Ra at the exit of each stand based on the acquired initial parameters of the cold rolling mill. i ;

[0023] The optimization module is used to optimize the parameters of the roll roughness of each stand based on the calculated roughness of the strip at the exit of each stand, as well as the target roughness and allowable error value of the cold-rolled strip surface of each cold rolling mill stand, so as to obtain the optimized roll roughness of each stand and thus realize the control of the surface roughness of the cold-rolled strip.

[0024] A readable storage medium that stores a program module, which, when executed in a processor, can implement the method as described in any one of the claims.

[0025] This invention provides a method for controlling the surface roughness of cold-rolled strip steel, which is of great significance for improving the product quality and production efficiency of surface-grade cold-rolled strip steel. The method of this application can monitor and adjust rolling process parameters in real time to ensure that the surface roughness of the cold-rolled strip steel reaches the preset target. This not only improves the appearance quality of the product but also enhances its performance and service life, meeting the high quality requirements of high-end manufacturing. Compared with traditional manual adjustment methods, the intelligent control method can quickly respond to changes in the production process, shorten the adjustment cycle, and reduce waste in production. Simultaneously, by optimizing rolling process parameters, it can also improve the operating efficiency of the production line and reduce production costs.

[0026] This application presents a method for controlling the surface roughness of cold-rolled strip steel based on advanced data analysis and processing technology, enabling precise control of the surface roughness of cold-rolled strip steel. This not only improves production stability but also reduces production fluctuations and quality problems caused by human factors.

[0027] Based on this need, this invention combines artificial intelligence technology, automated control technology, and optimized rolling process to achieve intelligent control of the surface roughness of high-grade cold-rolled strip steel. By introducing advanced intelligent technology, it can promote the development of cold-rolled strip steel production towards a more efficient, environmentally friendly, and intelligent direction, thereby enhancing the competitiveness of the entire industry.

[0028] (1) The surface roughness control scheme of high-grade cold-rolled strip steel described in this invention is different from the previous control methods. By analyzing the mechanism of roughness transfer during cold rolling, the process parameters such as rolling force and roll roughness of each stand are optimized based on the optimization algorithm. Effective control of surface roughness can be achieved without other auxiliary equipment and a lot of modifications.

[0029] (2) The method described in this invention can be directly imported into the rolling control model for online parameter optimization, and can be directly applied to the production of cold continuous rolling mills, promoting the transformation of enterprises towards intelligence and improving control accuracy and stability. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a flowchart of the method; Detailed Implementation

[0032] It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0033] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] A method for controlling the surface roughness of cold-rolled strip steel includes the following steps:

[0035] S1: Obtain the target roughness and allowable error value of the surface of the cold-rolled strip steel for each cold rolling mill stand;

[0036] S2: Obtain the initial parameters of the cold rolling mill: roll roughness Ra wi i = {1, 2, 3, 4, 5} represents frames 1-5, and the original roughness R of the strip steel after pickling. a0 ;

[0037] S3: Based on the acquired initial parameters of the cold rolling mill, calculate the strip roughness R at the exit of each stand. ai ;

[0038] S4: Based on the calculated surface roughness of the strip at the exit of each stand, as well as the target surface roughness and allowable error of the cold-rolled strip surface of each cold rolling mill stand, the parameters of the roll roughness of each stand are optimized to obtain the optimized roll roughness of each stand, thereby achieving the control of the surface roughness of the cold-rolled strip.

[0039] Furthermore, the process of optimizing the parameters of the roll roughness of each stand is as follows:

[0040] S41: Define the intermediate variable ΔRa i =Ra Ti -Ra i ΔRa w The optimal step size for roll roughness;

[0041] S42: Let i = 1;

[0042] S43: Determine whether i≤5 is true. If true, proceed to step S44; otherwise, proceed to step S47.

[0043] S44: Let k = 0;

[0044] S45: Let Ra wi =Ra wi +kΔRa w Calculate Ra i and ΔRa i ;

[0045] S46: Determine ΔRa i ≤ΔRa max If the condition is true, let i = i + 1 and proceed to step S43; if the condition is false, let k = k + 1 and proceed to step S45.

[0046] S47: Output the optimized roll roughness Ra wi , i = {1, 2, 3, 4, 5}.

[0047] Furthermore, the surface roughness Ra of the strip at the outlet of each frame... i The calculation formula is as follows:

[0048] Ra i =a0+a1Ra wi +a2Ra wi 2 +a3Ra i-1

[0049] Among them, Ra i It represents the surface roughness of the strip steel at the current rack exit, and a0…a3 are the coefficients of the polynomial regression.

[0050] A device for controlling the surface roughness of cold-rolled strip steel includes:

[0051] Acquisition Module I: Used to acquire the target roughness and allowable error value of the surface of cold-rolled strip steel for each cold rolling mill stand;

[0052] Acquisition Module II: Used to acquire the initial parameters of the cold rolling mill: roll roughness Ra wi , i={1,2,3,4,5} represents the original roughness Ra0 of the strip steel after pickling for frames 1-5;

[0053] Calculation module: Used to calculate the strip roughness Ra at the exit of each stand based on the acquired initial parameters of the cold rolling mill. i ;

[0054] The optimization module is used to optimize the parameters of the roll roughness of each stand based on the calculated roughness of the strip at the exit of each stand, as well as the target roughness and allowable error value of the cold-rolled strip surface of each cold rolling mill stand, so as to obtain the optimized roll roughness of each stand and thus realize the control of the surface roughness of the cold-rolled strip.

[0055] A readable storage medium that stores a program module, which, when executed in a processor, can implement the method as described in any one of the claims.

[0056] Example 1:

[0057] (a) Setting the target roughness Ra Ti ={0.70,0.65,0.60,0.57,0.60}, i ={1,2,3,4,5}, allowable error value ΔRa max =0.05;

[0058] (b) Collect initial parameters: roll roughness Ra wi0 ={0.20,0.20,0.20,0.20,2.0}, i ={1,2,3,4,5}, the original roughness of the strip inlet Ra0 = 2.0;

[0059] (c) Calculate the roughness Ra of the strip at the exit of each frame. i Ra i ={0.83,0.80,0.75,0.72,0.73}, i={1,2,3,4,5};

[0060] (d) Define intermediate variable ΔRa i =Ra Ti -Ra i ΔRa w =0.01;

[0061] (e) Let i=1;

[0062] (f) Determine whether i≤5 is true. If true, proceed to step (g); if false, proceed to step (j).

[0063] (g) Let k = 0;

[0064] (h) Let Ra wi =Ra wi +kΔRa w Calculate Ra i and ΔRa i ;

[0065] (i) Determine ΔRa i ≤ΔRa max If the condition is true, let i = i + 1 and proceed to step (f); if the condition is false, let k = k + 1 and proceed to step (h).

[0066] (j) Output the optimized roll roughness Ra wi ={0.83,0.56,0.40,0.36,3.1}, i ={1,2,3,4,5}, thereby achieving control over the surface roughness of cold-rolled strip steel.

[0067] Example 2:

[0068] (a) Setting the target roughness Ra Ti ={0.75,0.70,0.65,0.60,0.67}, i ={1,2,3,4,5}, allowable error value ΔRa max =0.05;

[0069] (b) Collect initial parameters: roll roughness Ra wi ={0.20,0.20,0.20,0.20,2.5}, i={1,2,3,4,5}, Ra0=2.3;

[0070] (c) Calculate the roughness Ra of the strip at the exit of each frame. i : Rai={0.86,0.83,0.80,0.78,0.83}, i={1,2,3,4,5};

[0071] (d) Define intermediate variable ΔRa i =Ra Ti -Ra i ΔRa w =0.01;

[0072] (e) Let i=1;

[0073] (f) Determine whether i≤5 is true. If true, proceed to step (g); if false, proceed to step (j).

[0074] (g) Let k = 0;

[0075] (h) Let Ra wi =Ra wi +kΔRa w Calculate Ra i and ΔRa i ;

[0076] (i) Determine ΔRa i ≤ΔRa maxIf the condition is true, let i = i + 1 and proceed to step (f); if the condition is false, let k = k + 1 and proceed to step (h).

[0077] (j) Output the optimized roll roughness Ra wi ={0.84,0.61,0.49,0.41,3.25}, i ={1,2,3,4,5}, thereby achieving control over the surface roughness of cold-rolled strip steel.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the surface roughness of cold-rolled strip steel, characterized in that: Includes the following steps: S1: Obtain the target roughness and allowable error value of the surface of the cold-rolled strip steel for each cold rolling mill stand; S2: Obtain the initial parameters of the cold rolling mill: roll roughness Ra wi , i={1,2,3,4,5} represents the original roughness Ra0 of the strip steel after pickling for frames 1-5; S3: Based on the acquired initial parameters of the cold rolling mill, calculate the strip roughness Ra at the exit of each stand. i ; S4: Based on the calculated surface roughness of the strip at the exit of each stand, as well as the target surface roughness and allowable error of the cold-rolled strip surface of each cold rolling mill stand, the parameters of the roll roughness of each stand are optimized to obtain the optimized roll roughness of each stand, thereby achieving the control of the surface roughness of the cold-rolled strip.

2. The method for controlling the surface roughness of cold-rolled strip steel according to claim 1, characterized in that: The process of optimizing the parameters of the roll roughness of each stand is as follows: S41: Define the intermediate variable ΔRa i =Ra Ti -Ra i ΔRa w The optimal step size for roll roughness; S42: Let i = 1; S43: Determine whether i≤5 is true. If true, proceed to step S44; otherwise, proceed to step S47. S44: Let k = 0; S45: Let Ra wi =Ra wi +kΔRa w Calculate Ra i and ΔRa i ; S46: Determine whether ΔRai ≤ ΔRa max If the condition is true, let i = i + 1 and proceed to step S43; if the condition is false, let k = k + 1 and proceed to step S45. S47: Output the optimized roll roughness Ra wi , i = {1, 2, 3, 4, 5}.

3. The method for controlling the surface roughness of cold-rolled strip steel according to claim 1, characterized in that: The roughness Ra of the strip steel at the outlet of each frame i The calculation formula is as follows: Sun i =a0+a1Ra wi +a2Ra wi 2 +a3Ra i-1 Among them, Ra i It represents the surface roughness of the strip steel at the current rack exit, and a0…a3 are the coefficients of the polynomial regression.

4. A device for controlling the surface roughness of cold-rolled strip steel, characterized in that: include: Acquisition Module I: Used to acquire the target roughness and allowable error value of the surface of cold-rolled strip steel for each cold rolling mill stand; Acquisition Module II: Used to acquire the initial parameters of the cold rolling mill: roll roughness Ra wi , i={1,2,3,4,5} represents the original roughness Ra0 of the strip steel after pickling for frames 1-5; Calculation module: Used to calculate the strip roughness Ra at the exit of each stand based on the acquired initial parameters of the cold rolling mill. i ; The optimization module is used to optimize the parameters of the roll roughness of each stand based on the calculated roughness of the strip at the exit of each stand, as well as the target roughness and allowable error value of the cold-rolled strip surface of each cold rolling mill stand, so as to obtain the optimized roll roughness of each stand and thus realize the control of the surface roughness of the cold-rolled strip.

5. A readable storage medium storing a program module, characterized in that, The program module, when run in a processor, can implement the method as described in any one of claims 1-3.

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