Method, device and equipment for controlling surface waviness of cold-rolled strip steel
By obtaining the target waviness of cold-rolled strip and the waviness, minimum and maximum values of each stand's rolls, defining intermediate variables and error functions, and using optimization step size and increment parameters, the optimal roll waviness is calculated. This solves the problem of inaccurate control of surface waviness of cold-rolled strip in traditional methods and achieves an efficient and stable production process.
Patent Information
- Application Number
- CN202511239340.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-01
- Publication Date
- 2025-11-11
AI Technical Summary
Traditional methods make it difficult to accurately control the surface waviness of cold-rolled strip steel, resulting in high production uncertainty, low efficiency, and poor product quality consistency.
By obtaining the target waviness of cold-rolled strip and the waviness, minimum and maximum values of each stand's rolls, defining intermediate variables and error functions, and using optimization step size and increment parameters, the optimal roll waviness is calculated to achieve precise control.
It enables precise control of the surface waviness of cold-rolled strip steel, improves the predictability and stability of production, reduces human intervention, and improves production efficiency and product quality.
Smart Images
Figure CN120920524A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of strip steel surface technology, and relates to a method, device and equipment for controlling the surface waviness of cold-rolled strip steel. Background Technology
[0002] In the steel manufacturing industry, cold-rolled strip steel is a key material widely used in the automotive, home appliance, and construction industries. Surface waviness, which refers to the irregularity of the minute wave shapes on the surface of the strip steel, is one of the important parameters for evaluating the surface quality of the strip steel. It directly affects the aesthetics of the strip steel and its adaptability to subsequent processing, such as coating and deep drawing performance.
[0003] Controlling the surface waviness of strip steel is often challenging in traditional production processes. Due to the complexity of the cold rolling process, multiple factors can affect the final surface waviness. Even slight variations in these factors can lead to differences in product quality and impact its market competitiveness.
[0004] Furthermore, traditional methods rely primarily on operator experience for control, lacking precise and automated control mechanisms. This not only increases production uncertainty but also limits improvements in production efficiency and consistency. Therefore, developing a model-based method capable of precisely controlling the surface waviness of cold-rolled strip steel is of paramount importance. Summary of the Invention
[0005] To solve the above problems, the technical solution adopted by the present invention is: a method for controlling the surface waviness of cold-rolled strip steel, comprising the following steps:
[0006] S1: Obtain the target waviness Wa of the cold-rolled strip. T ;
[0007] S2: Obtain the minimum value Wa of roll waviness for each stand under the premise of stable rolling. wimin And the maximum value Wa wimax Where: i = 1…5, and the inlet strip corrugation Wa0;
[0008] S3: Define intermediate variables, including the optimal value Wa' of the roll waviness for each stand. wi 'Optimization step size ΔWa for roll waviness' w Roll waviness increment parameter k i Wa of the strip corrugation at the end of the machine frame exit h The error function is F(x).
[0009] S4: Calculate the minimum value of Wa for the roll waviness of each stand. wimin Wa of export strip under certain conditions h and the initial error function F 0(x) ;
[0010] S5: Order
[0011] Let k1 = 1;
[0012] S6: Make Wa w1 =Wa w1min +k1*ΔWa w , judge Wa w1 <Wa w1max Whether it is true or not, when Wa w1 <Wa w1max If not, output the optimal value Wa' for the roll waviness of each stand. wi ', when Wa w1 <Wa w1max Upon establishment, proceed to step S7;
[0013] S7: Let k2 = 1;
[0014] S8: Make Wa w2 =Wa w2min +k2*ΔWa w , judge Wa w2 <Wa w2max Whether it is true or not, when Wa w2 <Wa w2max If not true, k1 = k1 + 1, return to step S6; when Wa w2 <Wa w2max Upon establishment, proceed to step S9;
[0015] S9: Let k3 = 1;
[0016] S10: Ling Wa w3 =Wa w3min +k3*ΔWa w , judge Wa w3 <Wa w3max Whether it is true or not, when Wa w3 <Wa w3max If this condition is not met, k2 = k2 + 1, return to step S8, when Wa w3 <Wa w3max Upon establishment, execute step S11;
[0017] S11: Let k4 = 1;
[0018] S12: Let Wa w4 =Wa w4min +k4*ΔWa w , judge Wa w4 <Wa w4max Whether it is true or not, when Wa w4 <Wa w4max If this condition is not met, k3 = k3 + 1, return to step S10, when Wa w4 <Waw4max When it holds, execute step S13;
[0019] S13: Let k5 = 1;
[0020] S14: Let Wa w5 = Wa w5min + k5 * ΔWa w , and determine whether Wa w5 < Wa w5max holds. When Wa w5 < Wa w5max does not hold, k4 = k4 + 1, and return to step S12. When Wa w5 < Wa w5max holds, execute step S15;
[0021] S15: Calculate the strip waviness Wa h at the exit of the last stand, the error function F(x), and determine whether F(x) < the initial error function F0(x) holds. When F(x) < F0(x) does not hold, let k5 = k5 + 1 and return to S14; when F(x) < F0(x) holds, execute S16;
[0022] S16: Let the optimal value Wa' wi of the roll waviness of each stand be Wa wi , and F0(x) = F(x); determine whether Wa w1 < Wa w1max holds. If it holds, k5 = k5 + 1 and execute S14. If Wa w1 < Wa w1max does not hold, output the optimal value Wa' wi of the roll waviness of each stand to obtain the actual waviness of the final cold-rolled strip.
[0023] Furthermore, the expression of the strip waviness Wa h at the exit is as follows:
[0024]
[0025] where: p i1 , p i2 and p i3 are fitting coefficients. When calculating for the first time, Wa wi = Wa wimin .
[0026] Furthermore, the expression of the error function F(x) is as follows:
[0027] F(x) = (Wa T - Wa h ) 2
[0028] Among them: Wa T The target waviness of cold-rolled strip is given by Wa, the strip waviness at the last stand exit. h .
[0029] Furthermore, the minimum value of Wa for the roll waviness of each stand is... wimin And the maximum value Wa wimax It is determined by the friction coefficient of each stand's rolls.
[0030] A device for controlling the surface waviness of cold-rolled strip steel includes:
[0031] Acquisition Module I: Used to acquire the target waviness Wa of cold-rolled strip steel. T ;
[0032] Module II: Obtain the minimum value Wa of roll waviness for each stand under the premise of stable rolling. wimin And the maximum value Wa wimax Where: i = 1…5, and the inlet strip corrugation Wa0;
[0033] Definition module: Used to define intermediate variables, including the optimal value Wa' for the roll waviness of each stand. wi 'Optimization step size ΔWa for roll waviness' w Roll waviness increment parameter k i Wa of the strip corrugation at the end of the machine frame exit h The error function is F(x).
[0034] Calculation module: Used to calculate the minimum waviness Wa of the rolls for each stand. wimin Wa of export strip under certain conditions h and the initial error function F 0(x) ;
[0035] Judgment Module: S5:
[0036] Let k1 = 1;
[0037] S6: Make Wa w1 =Wa w1min +k1*ΔWa w , judge Wa w1 <Wa w1max Whether it is true or not, when Wa w1 <Wa w1max If not, output the optimal value Wa' for the roll waviness of each stand. wi ', when Wa w1 <Wa w1max Upon establishment, proceed to step S7;
[0038] S7: Let k2 = 1;
[0039] S8: Make Wa w2 =Wa w2min +k2*ΔWa w , judge Wa w2 <Wa w2max Whether it is true or not, when Wa w2 <Wa w2max If not true, k1 = k1 + 1, return to step S6; when Wa w2 <Wa w2max Upon establishment, proceed to step S9;
[0040] S9: Let k3 = 1;
[0041] S10: Ling Wa w3 =Wa w3min +k3*ΔWa w , judge Wa w3 <Wa w3max Whether it is true or not, when Wa w3 <Wa w3max If this condition is not met, k2 = k2 + 1, return to step S8, when Wa w3 <Wa w3max Upon establishment, execute step S11;
[0042] S11: Let k4 = 1;
[0043] S12: Let Wa w4 =Wa w4min +k4*ΔWa w , judge Wa w4 <Wa w4max Whether it is true or not, when Wa w4 <Wa w4max If this condition is not met, k3 = k3 + 1, return to step S10, when Wa w4 <Wa w4max Upon establishment, proceed to step S13;
[0044] S13: Let k5 = 1;
[0045] S14: Ling Wa w5 =Wa w5min +k5*ΔWa w , judge Wa w5 <Wa w5max Whether it is true or not, when Wa w5 <Wa w5max If this condition is not met, k4 = k4 + 1, return to step S12, when Wa w5 <Wa w5max Upon establishment, proceed to step S15;
[0046] S15: Calculate Wa, the strip corrugation at the end frame exit.h The error function F(x) is used to determine whether F(x) < the initial error function F0(x) holds. When F(x) < F0(x) does not hold, let k5 = k5 + 1 and return to S14; when F(x) < F0(x) holds, execute S16;
[0047] S16: Let the optimal value Wa' of the roll waviness of each stand wi = Wa wi , and F0(x) = F(x); determine whether Wa w1 < Wa w1max holds. If it holds, k5 = k5 + 1 and execute S14. If Wa w1 < Wa w1max does not hold, output the optimal value Wa' of the roll waviness of each stand wi , and obtain the actual waviness of the final cold-rolled strip.
[0048] A computer device includes: a processor and a memory. The memory stores program modules. It is characterized in that the program modules run on the processor to implement the method described in any one of the above.
[0049] A control method, device and equipment for the surface waviness of cold-rolled strip provided by the present invention conduct a mechanism analysis on the cold-rolled roll transfer that has a great influence on the surface waviness. On the other hand, by intelligently adjusting the rolling process parameters, the precise control of the strip surface waviness is achieved;
[0050] Through this method, the precise regulation and control of the surface waviness of cold-rolled strip are achieved. This method not only improves the predictability and stability of production, but also improves production efficiency and reduces costs by reducing human intervention. Through real-time data analysis and feedback adjustment, this method can instantly identify and correct factors that may cause surface waviness deviation during the production process, thereby ensuring that the product quality reaches a higher standard. BRIEF DESCRIPTION OF THE DRAWINGS
[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.
[0052] Figure 1 is the flowchart of this method. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0053] 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.
[0054] 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.
[0055] Figure 1 This is a flowchart of the method.
[0056] A method for controlling the surface waviness of cold-rolled strip steel includes the following steps:
[0057] S1: Obtain the target waviness Wa of the cold-rolled strip. T ;
[0058] S2: Obtain the minimum value Wa of roll waviness for each stand under the premise of stable rolling. wimin And the maximum value Wa wimax Where: i = 1…5, and the inlet strip corrugation Wa0;
[0059] S3: Define intermediate variables, including the optimal value Wa' of the roll waviness for each stand. wi 'Optimization step size ΔWa for roll waviness' w Roll waviness increment parameter k i Wa of the strip corrugation at the end of the machine frame exit h The error function is F(x).
[0060] S4: Calculate the minimum value of Wa for the roll waviness of each stand. wimin Wa of export strip under certain conditions h and the initial error function F 0(x) ;
[0061] S5: Order
[0062] Let k1 = 1;
[0063] S6: Make Wa w1 =Wa w1min +k1*ΔWa w , judge Wa w1 <Wa w1max Whether it is true or not, when Waw1 <Wa w1max If not, output the optimal value Wa' for the roll waviness of each stand. wi ', when Wa w1 <Wa w1max Upon establishment, proceed to step S7;
[0064] S7: Let k2 = 1;
[0065] S8: Make Wa w2 =Wa w2min +k2*ΔWa w , judge Wa w2 <Wa w2max Whether it is true or not, when Wa w2 <Wa w2max If not true, k1 = k1 + 1, return to step S6; when Wa w2 <Wa w2max Upon establishment, proceed to step S9;
[0066] S9: Let k3 = 1;
[0067] S10: Ling Wa w3 =Wa w3min +k3*ΔWa w , judge Wa w3 <Wa w3max Whether it is true or not, when Wa w3 <Wa w3max If this condition is not met, k2 = k2 + 1, return to step S8, when Wa w3 <Wa w3max Upon establishment, execute step S11;
[0068] S11: Let k4 = 1;
[0069] S12: Let Wa w4 =Wa w4min +k4*ΔWa w , judge Wa w4 <Wa w4max Whether it is true or not, when Wa w4 <Wa w4max If this condition is not met, k3 = k3 + 1, return to step S10, when Wa w4 <Wa w4max Upon establishment, proceed to step S13;
[0070] S13: Let k5 = 1;
[0071] S14: Ling Wa w5 =Wa w5min +k5*ΔWa w , judge Wa w5 <Waw5max Whether it holds. When Wa w5 <Wa w5max does not hold, k4 = k4 + 1, return to step S12. When Wa w5 <Wa w5max holds, execute step S15;
[0072] S15: Calculate the strip waviness Wa at the exit of the last stand h , the error function F(x), and determine whether F(x) < the initial error function F0(x) holds. When F(x) < F0(x) does not hold, let k5 = k5 + 1 and return to S14; when F(x) < F0(x) holds, execute S16;
[0073] S16: Let the optimal value Wa' of the roll waviness of each stand wi = Wa wi , F0(x) = F(x); determine whether Wa w1 <Wa w1max holds. If it holds, k5 = k5 + 1 and execute S14. If Wa w1 <Wa w1max does not hold, output the optimal value Wa' of the roll waviness of each stand wi , and obtain the actual waviness of the final cold-rolled strip.
[0074] The strip waviness Wa at the exit h has the following expression:
[0075]
[0076] where: p i1 , p i2 and p i3 are fitting coefficients. When calculating for the first time, Wa wi = Wa wimin .
[0077] The error function F(x) has the following expression:
[0078] F(x) = (Wa T - Wa h ) 2
[0079] where: Wa T is the target waviness of the cold-rolled strip, and the strip waviness Wa at the exit of the last stand h .
[0080] The minimum value Wa wimin and the maximum value Wa wimax of the roll waviness of each stand are determined by the friction coefficient of each stand's roll.
[0081] A device for controlling the surface waviness of cold-rolled strip steel includes:
[0082] Acquisition Module I: Used to acquire the target waviness Wa of cold-rolled strip steel. T ;
[0083] Module II: Obtain the minimum value Wa of roll waviness for each stand under the premise of stable rolling. wimin And the maximum value Wa wimax Where: i = 1…5, and the inlet strip corrugation Wa0;
[0084] Definition module: Used to define intermediate variables, including the optimal value Wa' for the roll waviness of each stand. wi 'Optimization step size ΔWa for roll waviness' w Roll waviness increment parameter k i Wa of the strip corrugation at the end of the machine frame exit h The error function is F(x).
[0085] Calculation module: Used to calculate the minimum waviness Wa of the rolls for each stand. wimin Wa of export strip under certain conditions h and the initial error function F 0(x) ;
[0086] Judgment Module: S5:
[0087] Let k1 = 1;
[0088] S6: Make Wa w1 =Wa w1min +k1*ΔWa w , judge Wa w1 <Wa w1max Whether it is true or not, when Wa w1 <Wa w1max If not, output the optimal value Wa' for the roll waviness of each stand. wi ', when Wa w1 <Wa w1max Upon establishment, proceed to step S7;
[0089] S7: Let k2 = 1;
[0090] S8: Make Wa w2 =Wa w2min +k2*ΔWa w , judge Wa w2 <Wa w2max Whether it is true or not, when Wa w2 <Wa w2max If not true, k1 = k1 + 1, return to step S6; when Wa w2 <Waw2max When it holds, execute step S9;
[0091] S9: Let k3 = 1;
[0092] S10: Let Wa w3 = Wa w3min + k3 * ΔWa w , and judge whether Wa w3 < Wa w3max holds. When Wa w3 < Wa w3max does not hold, let k2 = k2 + 1, and return to step S8. When Wa w3 < Wa w3max holds, execute step S11;
[0093] S11: Let k4 = 1;
[0094] S12: Let Wa w4 = Wa w4min + k4 * ΔWa w , and judge whether Wa w4 < Wa w4max holds. When Wa w4 < Wa w4max does not hold, let k3 = k3 + 1, and return to step S10. When Wa w4 < Wa w4max holds, execute step S13;
[0095] S13: Let k5 = 1;
[0096] S14: Let Wa w5 = Wa w5min + k5 * ΔWa w , and judge whether Wa w5 < Wa w5max holds. When Wa w5 < Wa w5max does not hold, let k4 = k4 + 1, and return to step S12. When Wa w5 < Wa w5max holds, execute step S15;
[0097] S15: Calculate the strip waviness Wa at the exit of the last stand h , the error function F(x), and judge whether F(x) < the initial error function F0(x) holds. When F(x) < F0(x) does not hold, let k5 = k5 + 1, and return to S14; when F(x) < F0(x) holds, execute S16;
[0098] S16: Let the optimal value Wa' of the roll waviness of each stand wi = Wa wiF0(x) = F(x); determine Wa w1 <Wa w1max Is it true? If true, k5 = k5 + 1, execute S14. If Wa w1 <Wa w1max If this condition is not met, output the optimal value Wa' for the roll waviness of each stand. wi This yields the actual waviness of the final cold-rolled strip.
[0099] A computer device includes: a processor and a memory, the memory storing a program module that runs on the processor to implement the method as described in any one of the claims.
[0100] Example 1:
[0101] A method for controlling the surface waviness of cold-rolled strip steel includes the following steps:
[0102] (a) Setting the target waviness Wa of the finished product T =0.45μm;
[0103] (b) Collect initial parameters and determine the minimum roll waviness of each stand under the premise of stable rolling.
[0104] Wa wimin ={0.2,0.2,0.2,0.2,0.2}μm, i ={1,2,3,4,5} and the maximum value.
[0105] Wa wimax ={3.5,3.5,3.5,3.5,3.5}μm, i={1,2,3,4,5}, inlet strip corrugation
[0106] Wa0 = 2.4 μm;
[0107] (c) Define intermediate variables, the optimal value of Wa' for the roll waviness of each stand. wi 'Optimization step size ΔWa for roll waviness' w =0.05μm, roll waviness increment parameter k, strip waviness Wa at the last stand exit. h Error function F(x) = (Wa T -Wa h ) 2 ;
[0108] (d) Calculate the strip corrugation Wa at the end of the machine stand. h =G(Wa wi Wa0) = 1.1 μm, and the error function
[0109] F0(x) = 0.4225;
[0110] (e) Let k1 = 1;
[0111] (f) Let Wa w1 =Wa w1min +k1*ΔWa w , judge Wa w1 <Wa w1max If the condition is true, proceed to step (g); if it is false, proceed to step (r).
[0112] (g) Let k2 = 1;
[0113] (h) Let Wa w2 =Wa w2min +k2*ΔWa w , judge Wa w2 <Wa w2max If the condition is true, proceed to step (i); if not, k1 = k1 + 1, proceed to step (f).
[0114] (i) Let k3 = 1;
[0115] (j) Let Wa w3 =Wa w3min +k3*ΔWa w , judge Wa w3 <Wa w3max If the condition is true, proceed to step (k); if not, k2 = k2 + 1, proceed to step (h).
[0116] (k) Let k4 = 1;
[0117] (l) Let Wa w4 =Wa w4min +k4*ΔWa w , judge Wa w4 <Wa w4max If the condition is true, proceed to step (m); if not, k3 = k3 + 1, proceed to step (j).
[0118] (m) Let k5 = 1;
[0119] (n) Let Wa w5 =Wa w5min +k5*ΔWa w , judge Wa w5 <Wa w5max If the condition is true, proceed to step (o); if not, k4 = k4 + 1, proceed to step (l).
[0120] (o) Calculate Wa, the strip corrugation at the outlet of the last frame at this time. h and the error function F(x), determine
[0121] If F(x) < F0(x), if true, proceed to step (p); if not, k5 = k5 + 1 and proceed to step (n).
[0122] (p) Let the optimal value of the roll waviness of each stand be Wa’ wi = Wa wi , and F0(x) = F(x);
[0123] (q) Determine whether Wa w1 < Wa w1max holds. If true, k5 = k5 + 1 and proceed to step (n); if not, proceed to step (r);
[0124] (r) Output the optimal value of the roll waviness of each stand Wa’ wi = {0.59, 0.53, 0.46, 0.40, 2.3}, i = {1, 2, 3, 4, 5}; achieving the control of the surface waviness of cold-rolled strip steel.
[0125] Example 2:
[0126] (a) Set the target waviness of the finished product Wa T = 0.52 μm;
[0127] (b) Collect the initial parameters, the minimum value of the roll waviness of each stand under the premise of stable rolling
[0128] Wa wimin = {0.3, 0.3, 0.3, 0.3, 0.3} μm, i = {1, 2, 3, 4, 5} and the maximum value
[0129] Wa wimax = {3.0, 3.0, 3.0, 3.0, 3.0} μm, i = {1, 2, 3, 4, 5}, the waviness of the incoming strip
[0130] Wa0 = 2.8 μm;
[0131] (c) Define intermediate variables, the optimal value of the roll waviness of each stand Wa’ wi ’, the optimization step of the roll waviness ΔWa w = 0.03 μm, the roll waviness increment parameter k, the waviness of the strip at the exit of the last stand Wa h , and the error function F(x) = (Wa T - Wa h ) 2 ;
[0132] (d) Calculate the waviness of the strip at the exit of the last stand Wa h = G(Wa wi , Wa0) = 1.1 μm, and the error function
[0133] F0(x) = 0.4225;
[0134] (e) Let k1 = 1;
[0135] (g) Let Wa w1 =Wa w1min +k1*ΔWa w , judge Wa w1 <Wa w1max If the condition is true, proceed to step (h); if it is false, proceed to step (s).
[0136] (h) Let k2 = 1;
[0137] (i) Let Wa w2 =Wa w2min +k2*ΔWa w , judge Wa w2 <Wa w2max If the condition is true, proceed to step (j); if not, k1 = k1 + 1, proceed to step (g).
[0138] (j) Let k3 = 1;
[0139] (k) Let Wa w3 =Wa w3min +k3*ΔWa w , judge Wa w3 <Wa w3max If the condition is true, proceed to step (l); if not, k2 = k2 + 1, proceed to step (i).
[0140] (l) Let k4 = 1;
[0141] (m)Let Wa w4 =Wa w4min +k4*ΔWa w , judge Wa w4 <Wa w4max If the condition is true, proceed to step (n); if not, k3 = k3 + 1, proceed to step (k).
[0142] (n) Let k5 = 1;
[0143] (o)Let Wa w5 =Wa w5min +k5*ΔWa w , judge Wa w5 <Wa w5max If the condition is true, proceed to step (p); if not, k4 = k4 + 1, proceed to step (m).
[0144] (p) Calculate Wa, the strip corrugation at the end of the machine frame exit.h and the error function F(x), to judge
[0145] F(x) < F0(x). If it holds, enter step (q). If it does not hold, k5 = k5 + 1, and enter step (o);
[0146] (q) Let the optimal value of the roll waviness of each stand Wa’ wi = Wa wi , F0(x) = F(x);
[0147] (r) Judge whether Wa w1 < Wa w1max holds. If it holds, k5 = k5 + 1, and enter step (o). If it does not hold, enter step (s);
[0148] (s) Output the optimal value of the roll waviness of each stand Wa’ wi {0.70, 0.63, 0.56, 0.47, 2.4}, i = {1, 2, 3, 4, 5}; to achieve the control of the surface waviness of cold-rolled strip steel.
[0149] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for controlling the surface waviness of cold-rolled strip steel, characterized in that: Includes the following steps: S1: Obtain the target waviness Wa of the cold-rolled strip. T ; S2: Obtain the minimum value Wa of roll waviness for each stand under the premise of stable rolling. wimin And the maximum value Wa wimax Where: i = 1…5, and the inlet strip corrugation Wa0; S3: Define intermediate variables, including the optimal value Wa' of the roll waviness for each stand. wi 'Optimization step size ΔWa for roll waviness' w Roll waviness increment parameter k i Wa of the strip corrugation at the end of the machine frame exit h The error function is F(x). S4: Calculate the minimum value of Wa for the roll waviness of each stand. wimin Wa of export strip under certain conditions h and the initial error function F 0(x) ; S5: Let k1 = 1; S6: Make Wa w1 =Wa w1min +k1*ΔWa w , judge Wa w1 <Wa w1max Whether it is true or not, when Wa w1 <Wa w1max If not, output the optimal value Wa' for the roll waviness of each stand. wi ', when Wa w1 <Wa w1max Upon establishment, proceed to step S7; S7: Let k2 = 1; S8: Make Wa w2 =Wa w2min +k2*ΔWa w , judge Wa w2 <Wa w2max Whether it is true or not, when Wa w2 <Wa w2max If not true, k1 = k1 + 1, return to step S6; when Wa w2 <Wa w2max Upon establishment, proceed to step S9; S9: Let k3 = 1; S10: Ling Wa w3 =Wa w3min +k3*ΔWa w , judge Wa w3 <Wa w3max Whether it is true or not, when Wa w3 <Wa w3max If this condition is not met, k2 = k2 + 1, return to step S8, when Wa w3 <Wa w3max Upon establishment, execute step S11; S11: Let k4 = 1; S12: Let Wa w4 =Wa w4min +k4*ΔWa w , judge Wa w4 <Wa w4max Whether it is true or not, when Wa w4 <Wa w4max If this condition is not met, k3 = k3 + 1, return to step S10, when Wa w4 <Wa w4max Upon establishment, proceed to step S13; S13: Let k5 = 1; S14: Ling Wa w5 =Wa w5min +k5*ΔWa w , judge Wa w5 <Wa w5max Whether it is true or not, when Wa w5 <Wa w5max If this condition is not met, k4 = k4 + 1, return to step S12, when Wa w5 <Wa w5max Upon establishment, proceed to step S15; S15: Calculate the strip waviness Wa at the outlet of the last stand h , the error function F(x), and determine whether F(x) < the initial error function F0(x) holds. When F(x) < F0(x) does not hold, let k5 = k5 + 1 and return to S14; when F(x) < F0(x) holds, execute S16; S16: Set the optimal value Wa' for the roll waviness of each stand. wi =Wa wi F0(x) = F(x); determine Wa w1 <Wa w1max If true, k5 = k5 + 1, execute S14. If Wa w1 <Wa w1max If this condition is not met, output the optimal value Wa' for the roll waviness of each stand. wi This yields the actual waviness of the final cold-rolled strip.
2. The method for controlling the surface waviness of cold-rolled strip steel according to claim 1, characterized in that: Export strip corrugation Wa h The expression is as follows: Where: p i1 p i2 and p i3 The fitting coefficients are Wa, calculated in the first iteration. wi =Wa wimin .
3. The method for controlling the surface waviness of cold-rolled strip steel according to claim 1, characterized in that: The expression for the error function F(x) is as follows: F(x)=(Wa T -Wa h ) 2 Among them: Wa T The target waviness of cold-rolled strip is given by Wa, the waviness of the strip exiting the last stand. h .
4. The method for controlling the surface waviness of cold-rolled strip steel according to claim 1, characterized in that: The minimum value of Wa for the roll waviness of each stand wimin And the maximum value Wa wimax The coefficient of friction of each stand's rolls is determined.
5. A device for controlling the surface waviness of cold-rolled strip steel, characterized in that: include: Acquisition Module I: Used to acquire the target waviness Wa of cold-rolled strip steel. T ; Module II: Obtain the minimum value Wa of roll waviness for each stand under the premise of stable rolling. wimin And the maximum value Wa wimax Where: i = 1…5, and the inlet strip corrugation Wa0; Definition module: Used to define intermediate variables, including the optimal value Wa' for the roll waviness of each stand. wi 'Optimization step size ΔWa for roll waviness' w Roll waviness increment parameter k i Wa of the strip corrugation at the end of the machine frame exit h The error function is F(x). Calculation module: Used to calculate the minimum waviness Wa of the rolls for each stand. wimin Wa of export strip under certain conditions h and the initial error function F 0(x) ; Judgment Module: S5: Let k1 = 1; S6: Make Wa w1 =Wa w1min +k1*ΔWa w , judge Wa w1 <Wa w1max Whether it is true or not, when Wa w1 <Wa w1max If not, output the optimal value Wa' for the roll waviness of each stand. wi ', when Wa w1 <Wa w1max Upon establishment, proceed to step S7; S7: Let k2 = 1; S8: Make Wa w2 =Wa w2min +k2*ΔWa w , judge Wa w2 <Wa w2max Whether it is true or not, when Wa w2 <Wa w2max If not true, k1 = k1 + 1, return to step S6; when Wa w2 <Wa w2max Upon establishment, proceed to step S9; S9: Let k3 = 1; S10: Ling Wa w3 =Wa w3min +k3*ΔWa w , judge Wa w3 <Wa w3max Whether it is true or not, when Wa w3 <Wa w3max If this condition is not met, k2 = k2 + 1, return to step S8, when Wa w3 <Wa w3max Upon establishment, execute step S11; S11: Let k4 = 1; S12: Let Wa w4 =Wa w4min +k4*ΔWa w , judge Wa w4 <Wa w4max Whether it is true or not, when Wa w4 <Wa w4max If this condition is not met, k3 = k3 + 1, return to step S10, when Wa w4 <Wa w4max Upon establishment, proceed to step S13; S13: Let k5 = 1; S14: Ling Wa w5 =Wa w5min +k5*ΔWa w , judge Wa w5 <Wa w5max Whether it is true or not, when Wa w5 <Wa w5max If this condition is not met, k4 = k4 + 1, return to step S12, when Wa w5 <Wa w5max Upon establishment, proceed to step S15; S15: Calculate the strip waviness Wa at the outlet of the last stand h , the error function F(x), and determine whether F(x) < the initial error function F0(x) holds. When F(x) < F0(x) does not hold, let k5 = k5 + 1 and return to S14; when F(x) < F0(x) holds, execute S16; S16: Set the optimal value Wa' for the roll waviness of each stand. wi =Wa wi F0(x) = F(x); determine Wa w1 <Wa w1max If true, k5 = k5 + 1, execute S14. If Wa w1 <Wa w1max If this condition is not met, output the optimal value Wa' for the roll waviness of each stand. wi This yields the actual waviness of the final cold-rolled strip.
6. A computer device, comprising: A processor and a memory, the memory storing a program module, characterized in that the program module runs on the processor to implement the method as described in any one of claims 1-4.