Method for predicting surface roughness of work rolls of a secondary cold rolling mill

Abstract

The application discloses a kind of secondary cold-rolling unit working roll surface roughness prediction method, including steps: 1, according to steel grade to establish the surface roughness attenuation model of working roll;2, establish the mathematical model of working roll transfer rate;3, according to steel production process to set the minimum threshold of transfer rate;4, set the number of rolled steel coil i, i ∈ [1, M] and initialize i=1;5, the i th coil strip is rolled, and the transfer rate after the next coil strip is rolled is calculated according to formula (3);6, whether the transfer rate in step 5 is ≤ the minimum threshold of transfer rate, if yes, then step 7 is executed;If not, then i=i+1, and return to step 5;7, output the number of steel coil i, stop after the i th coil strip is rolled, and replace the working roll.The application accurately predicts the wear degree of the surface of the working roll by establishing the transfer rate model, thereby greatly reducing the occurrence of surface quality problems of the strip steel product, and achieving the purpose of good strip steel quality control.

Description

TECHNICAL FIELD

[0001] The present application relates to a strip rolling control method, in particular to a surface roughness prediction method of a work roll of a secondary cold rolling mill. BACKGROUND

[0002] In the cold and hot rolling process of the strip, the wear of the work roll is inevitable. Improper control of the wear of the work roll will reduce the product quality, increase the surface contact pressure between the end surfaces of the work roll, and even cause the work roll to break or flake off. Therefore, during the service of the work roll, the work roll needs to be replaced and re-grounded again to restore the roll shape required by the process when the wear (i.e. the reduction of the radius) reaches a certain amount. When the diameter of the work roll is reduced to a certain amount, the entire work roll needs to be scrapped.

[0003] The wear of the work roll can be divided into macro-scale wear and micro-scale wear. Macro-scale wear changes the size and shape of the work roll, which affects the thickness control quality and the shape of the strip. Micro-scale wear does not significantly change the shape and size of the work roll, but only shows the attenuation of the surface roughness of the work roll, which affects the rolling transfer and reduces the micro-surface quality of the strip. In the cold rolling process, the wear of the work roll is one of the main factors affecting the surface of the strip, the shape of the strip and the roll changing period. When the wear of the work roll reaches the order of 10 microns, it will significantly affect the shape of the strip, and the softer the material of the strip, the greater the impact. In terms of the ratio of the change in the crown of the strip, the ordinary material of the strip can reach 50%. At the same time, when the wear of the work roll reaches the order of 10 microns, it also significantly affects the thickness of the strip, and the softer the material of the strip, the greater the impact. In terms of the ratio of the average thickness change, the ordinary material of the strip can reach 30%. For cold-rolled strips with high surface roughness requirements (surface roughness Ra is 0.3-1.5um) such as tinplate, when the wear of the work roll reaches the order of sub-microns, it will affect the rolling transfer of the micro-morphology of the strip surface, resulting in the surface roughness of the rolled strip not meeting the requirements and reducing the micro-surface quality of the strip.

[0004] Chinese invention patent ZL201810010679.0 discloses a prediction method for the surface roughness of a roughened work roll in a cold rolling process. The prediction method tracks the test industrial production site data, conducts laboratory tests on the simulated cold rolling process under different conditions of the initial roughness of the sample, the test force and the test mileage, uses the regression analysis module of the SPSS software to regress the test data to obtain model parameters, and then obtains the prediction model for the surface roughness of the roughened work roll in the cold rolling process. The prediction method determines the experimental parameters through a group of data, and establishes a regression model according to the test results. The error of the data is large, and the replacement parameters of the work roll cannot be set, so that the downtime of the work roll cannot be determined, and the practicability is poor. SUMMARY

[0005] The application aims to provide a surface roughness prediction method for a work roll of a secondary cold rolling mill set, which can accurately predict the wear degree of the surface of the work roll by establishing a transfer rate model, thereby greatly reducing the occurrence of surface quality problems of the strip steel product, and achieving the purpose of good strip steel product control.

[0006] The application is implemented as follows:

[0007] A surface roughness prediction method for a work roll of a secondary cold rolling mill set, comprising the following steps:

[0008] Step 1: establishing a surface roughness attenuation model of the work roll according to the steel production process, and the model formula is:

[0009] Formula (1)

[0010] wherein i is the number of steel coils of the strip steel, i=1, 2, …, M;

[0011] M is the total number of rolled steel coils of the work roll in a service period;

[0012] is the surface roughness of the work roll after rolling the i-th coil of strip steel;

[0013] is the length of the i-th coil of strip steel;

[0014] is a first coefficient, is a second coefficient, is a third coefficient, is a fourth coefficient, is a fifth coefficient, and the first to fifth coefficients are obtained by linear regression calculation;

[0015] is the ratio of the unit width rolling pressure to the yield strength in the rolling process of the i-th coil of strip steel, and the calculation formula is:

[0016] Formula (2)

[0017] wherein, is the total rolling force of the i-th coil of strip steel;

[0018] is the strip steel width of the i-th coil of strip steel;

[0019] is the yield strength of the i-th coil of strip steel;

[0020] Step 2: establishing a mathematical model of the transfer rate of the work roll, and the mathematical model formula of the transfer rate is:

[0021] λ(i+1) = α1+ α2h(i) - α3 3 - α4[1000 / ] 3 - α5 Formula (3)

[0022] wherein λ(i+1) is the transfer rate of the i+1th coiled strip after rolling;

[0023] α1 is the first influence coefficient, α2 is the second influence coefficient, α3 is the third influence coefficient, α4 is the fourth influence coefficient, and α5 is the fifth influence coefficient, which are calculated by linear regression;

[0024] h(i) is the reduction of the i th coiled strip;

[0025] is the length of the i th coiled strip;

[0026] Ra(i) is the surface roughness of the i th coiled strip; S (i) is the surface roughness of the work roll after rolling the i th coiled strip The relationship is:

[0027] Ra S (i) = η(i) Ra S0 + λ(i) Formula (7)

[0028] wherein Ra S (i) is the surface roughness of the i th coiled strip;

[0029] η(i) is the surface roughness heredity rate of the i th coiled strip;

[0030] Ra S0 is the surface roughness of the i th coiled strip;

[0031] λ(i) is the transfer rate of the i th coiled strip after rolling;

[0032] Step 3: Set the minimum threshold value λ0 of the transfer rate according to the steel production process;

[0033] Step 4: Set the number of rolled coiled strips i, i ∈ [1, M] and initialize i = 1;

[0034] Step 5: Roll the i th coiled strip, and calculate the transfer rate λ(i+1) of the next coiled strip after rolling according to Formula (3);

[0035] Step 6: Determine whether the transfer rate λ(i+1) calculated in Step 5 is ≤ the minimum threshold value λ0 of the transfer rate, if yes, execute Step 7; if no, let i = i + 1 and return to Step 5;

[0036] Step 7: output the number of steel coil i, and stop after the i th coil of strip steel is rolled, and replace the work roll.

[0037] In the step 2, the mathematical model of the transfer rate is established by:

[0038] Step 2.1: calculate the additional surface roughness Ra of the i th coil of strip steel in rolling ad (i), and the calculation formula is:

[0039] Ra ad (i)=λ(i) Formula (4) ;

[0040] Step 2.2: calculate the surface roughness Ra of the outlet strip steel S (i), the surface roughness Ra of the outlet strip steel is determined by the genetic roughness of the strip steel and the additional surface roughness in rolling, that is: S

[0041] Ra S (i)=η(i)Ra S0 +Ra ad (i) Formula (5)

[0042] Wherein, Ra S (i) is the surface roughness of the i th coil of strip steel at the outlet of the strip steel;

[0043] η(i) is the genetic rate of the surface roughness of the i th coil of strip steel, η(i) is related to the reduction h(i), the ratio of the unit width rolling force to the yield strength , the yield strength of the strip steel , the length of the strip steel .

[0044] The mathematical model of the genetic rate of the surface roughness is established as follows:

[0045] η(i+1) =β1+e β2h(i) -β3[ / ] 3 -β4[1000 / ] 3 -β5 Formula (6)

[0046] Wherein, β1 is the sixth influence coefficient, β2 is the seventh influence coefficient, β3 is the eighth influence coefficient, β4 is the ninth influence coefficient, β5 is the tenth influence coefficient, and the sixth influence coefficient~the tenth influence coefficient is calculated by linear regression;

[0047] Ra S0 is the surface roughness of the i th coil of strip steel at the inlet of the strip steel;​

[0048] Ra ad (i) is the additional surface roughness of the i-th volume of strip steel rolling;

[0049] Step 2.3: formula (4) is brought into formula (5), and the following formula (6) is obtained:

[0050] Ra S (i)=η(i)Ra S0 +λ(i) Formula (7);

[0051] Step 2.4: according to formula (7), when the work roll and the strip steel material are determined, the transfer rate λ is related to the reduction h(i), the ratio of the unit width rolling force to the yield strength , the yield strength of the strip steel , the length of the strip steel , and a mathematical model of the transfer rate is established: λ(i+1) =α1+α2h(i)-α3 3 -α4[1000 / ] 3 -α5 .

[0052] In the step 3, the minimum threshold value λ0 of the transfer rate is set as the minimum value of the surface roughness of the current steel strip.

[0053] Compared with the prior art, the present application has the following beneficial effects:

[0054] 1、The present application introduces the transfer rate, which is the ratio of the rack rolling additional surface roughness to the surface roughness of the work roll, can quantitatively analyze the ability of the surface roughness of the work roll to transfer to the surface of the strip steel, so as to realize the behavior and efficiency control of the surface micro-morphology of the work roll in the secondary cold rolling process, avoid the surface quality problem of the strip steel product caused by the too low surface roughness of the work roll, and achieve the purpose of controlling the production quality of the strip steel.

[0055] 2、The present application establishes the roughness decay model of the surface of the work roll, predicts the change of the surface roughness of the work roll through the measurement of the surface roughness of the work roll during the service period, and uses the roughness decay model to constrain the mathematical model of the transfer rate, so that the prediction of the transfer rate can be used to accurately predict the replacement time of the work roll, the prediction accuracy is high, unnecessary time cost and technical cost are avoided, and economic benefit is improved.

[0056] The present application establishes a transfer rate mathematical model, quantifies the ability of the work roll surface roughness to be transferred to the surface of the strip steel, accurately predicts the wear degree of the work roll surface in the micro scale (sub-micron order), and controls according to the change of the transfer rate, so that the occurrence of the surface quality problem of the strip steel product caused by the too low surface roughness of the work roll is greatly reduced, and the good strip steel product control purpose is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 is a flow chart of the surface roughness prediction method of the work roll of the secondary cold rolling mill set. DETAILED DESCRIPTION

[0058] The present application will be further described below in combination with the drawings and specific embodiments.

[0059] Please refer to the accompanying Figure 1 A surface roughness prediction method of a work roll of a secondary cold rolling mill set, comprising the following methods:

[0060] By a large number of tracking tests on the surface roughness attenuation law of the work roll in large industrial production, and combining the theoretical analysis of the influence of the intermediate roll (or backup roll) and the strip steel on the surface roughness attenuation of the work roll from the perspective of rough surface contact causing plastic deformation of the rough peak, the influencing factors of the roll surface roughness attenuation are determined, the measured data is analyzed by using mathematical method, and a semi-theoretical and semi-empirical work roll surface roughness prediction model is established to study the attenuation law of the work roll surface roughness value R a roll .

[0061] There are many influencing factors of the surface roughness of the strip steel, and the relationship between various influencing factors and the surface roughness is not a simple linear superposition relationship, but a very complex nonlinear mapping relationship. If the nonlinear function expression reflecting the relationship between various components and the surface roughness is to be found out, a large number of experiments need to be done, which cannot be realized in actual research. The stepwise regression analysis method in mathematical statistics is used to establish the relationship model function.

[0062] In the temper rolling production, the contact part of the roll and the strip steel edge is severely worn, which will cause a sharp change of the roll roughness and bring surface quality defects of the strip steel. In order to avoid this situation, the production plan is arranged from wide to narrow during the service life of the work roll. Therefore, it is assumed that the surface roughness of the work roll is uniformly distributed along the width direction of the strip steel in the contact area of the work roll and the strip steel during the production process, and the work roll attenuation model is established.

[0063] Step 1: Establish the surface roughness attenuation model of the work roll according to the steel production process, and the model formula is:

[0064] Formula (1)

[0065] wherein, is the surface roughness of the work roll when the work roll is put into service, in um, is obtained by on-site testing of a roughness tester.

[0066] i is the number of steel coils of the strip steel, i = 1, 2, …, M, M is the total number of rolled steel coils of the work roll in a service period.

[0067] is the surface roughness of the work roll after rolling the i-th coil of the strip steel, in um, is obtained by on-site testing of a roughness tester.

[0068] is the length of the i-th coil of the strip steel, in km, is obtained from a production process control system.

[0069] is a first coefficient, is a second coefficient, is a third coefficient, is a fourth coefficient, is a fifth coefficient, the first to fifth coefficients are calculated by linear regression.

[0070] is the ratio of the unit width rolling pressure to the yield strength during rolling of the i-th coil of the strip steel, The calculation formula of is:

[0071] Equation (2);

[0072] wherein, is the total rolling force of the i-th coil of the strip steel, in N, is obtained from a production process control system.

[0073] is the strip steel width of the i-th coil of the strip steel, in mm, is obtained from a production process control system.

[0074] is the yield strength of the i-th coil of the strip steel, in Mpa, is obtained from a production process control system.

[0075] Step 2: Establish a mathematical model of the transfer rate of the work roll, and the mathematical model formula of the transfer rate is:

[0076] λ(i+1)=α1+α2h(i)-α3 3 -α4[1000 / ]3 -α5 Formula (3)

[0077] Wherein, λ(i+1) is the transfer rate of the i+1 coiled strip after rolling.

[0078] α1 is the first influence coefficient, α2 is the second influence coefficient, α3 is the third influence coefficient, α4 is the fourth influence coefficient, and α5 is the fifth influence coefficient. The first influence coefficient to the fifth influence coefficient are calculated by linear regression.

[0079] h(i) is the reduction of the i coiled strip, with the unit of um, and h(i) is obtained from the production process control system.

[0080] is the ratio of the unit width rolling force to the yield strength of the i coiled strip during rolling, with the unit of 10 kN / mm, calculated by formula (2).

[0081] is the yield strength of the i coiled strip, with the unit of Mpa, obtained from the production process control system.

[0082] is the length of the i coiled strip, with the unit of km, obtained from the production process control system.

[0083] The mathematical model of the transfer rate is:

[0084] Step 2.1: Calculate the rolling additional surface roughness Ra ad (i) of the i coiled strip, and the calculation formula is:

[0085] Ra ad (i)=λ(i-1)· Formula (4).

[0086] The work roll directly contacts with the surface of the strip, which is the key component to determine the surface quality of the strip and affect the rolling process. The surface roughness of the work roll is a key process parameter for the micro-surface quality control of the steel plate, and has an extremely important influence on the micro-surface quality of the rolled strip.

[0087] The transfer rate λ is defined as the ratio of the rolling additional surface roughness Ra ad to the surface roughness of the work roll , which can quantitatively analyze the ability of the surface roughness of the work roll to transfer to the surface of the strip, i.e. the influence of the surface roughness of the work roll on the surface roughness of the strip.

[0088] Step 2.2: Calculate the surface roughness Ra S(i), exit strip surface roughness Ra S (i) is determined by the inherited roughness of the strip and the additional surface roughness during rolling, that is:

[0089] Ra S (i)=η(i)Ra S0 +Ra ad (i) Formula (5)

[0090] wherein Ra S (i) is the exit strip surface roughness of the i-th coiled strip, in um, which can be measured on the surface of the strip after rolling by a handheld roughness meter.

[0091] η(i) is the surface roughness inheritance rate of the i-th coiled strip, η(i) is mainly related to the reduction h(i), the ratio of the unit width rolling force to the yield strength , the yield strength of the strip , the length of the strip , that is, η(i)=F(h(i), , , ).

[0092] A mathematical model of the surface roughness inheritance rate is established:

[0093] η(i+1) =β1+e β2h(i) -β3[ / ] 3 -β4[1000 / ] 3 -β5 Formula (6)

[0094] wherein β1 is the sixth influence coefficient, β2 is the seventh influence coefficient, β3 is the eighth influence coefficient, β4 is the ninth influence coefficient, and β5 is the tenth influence coefficient. The sixth to tenth influence coefficients are calculated by linear regression.

[0095] Ra S0 is the entrance strip surface roughness of the i-th coiled strip, in um, which can be measured on the surface of the strip before rolling by a handheld roughness meter.

[0096] Ra ad (i) is the rolling additional surface roughness of the i-th coiled strip.

[0097] Step 2.3: Substitute formula (4) into formula (5) to obtain:

[0098] Ra S (i)=η(i)Ra S0 +λ(i-1) Formula (7).

[0099] Step 2.4: As can be seen from Formula (7), under the condition that the work roll and the strip steel material are determined, the transfer rate λ is mainly related to the reduction h(i), the ratio of the unit width rolling force to the yield strength , the yield strength of the strip steel , and the length of the strip steel , and thus a mathematical model of the transfer rate λ is established based on the reduction, the ratio of the unit width rolling force to the yield strength, the yield strength of the strip steel, and the length of the strip steel.

[0100] Step 3: Set the minimum threshold value λ0of the transfer rate according to the steel production process.

[0101] The transfer rate is the degree of transfer of the surface morphology of the work roll to the surface morphology of the strip steel, and it is generally considered that the greater the transfer rate value is, the better, and thus the minimum threshold value λ0of the transfer rate can be preferably set as the minimum value of the surface roughness of the strip steel of the current production steel grade. For example, the surface roughness requirement of a certain steel grade is 1-1.1 um, and the minimum threshold value λ0of the transfer rate can be set as 1 um. Alternatively, in the actual rolling procedure, when the surface roughness of the rolled strip steel reaches the minimum requirement, the transfer rate at this time is calculated, and the transfer rate is taken as the minimum threshold value λ0of the transfer rate of the strip steel of this steel grade.

[0102] Step 4: Set the number i of the rolled strip steel, i∈[1, M] and initialize i=1.

[0103] Step 5: Roll the i-th strip steel, and calculate the transfer rate λ(i+1) of the next rolled strip steel according to Formula (3).

[0104] Step 6: Determine whether the transfer rate λ(i+1) is ≤ the minimum threshold value λ0of the transfer rate, if yes, execute Step 7; if no, let i=i+1 and return to Step 5.

[0105] Step 7: Output the number i of the strip steel, and stop rolling after the i-th strip steel is rolled and replace the work roll.

[0106] Example 1:

[0107] In the production of a certain steel grade strip steel, the parameters of the first 10 rolls of strip steel are collected, mainly including:

[0108] The surface roughness of the work roll before and after rolling of the 10 rolls of strip steel is tested by a handheld roughness meter on site ~ (10), parameter values are {0.7955 μm, 0.6948 μm, 0.6298 μm, 0.6068 μm, 0.5836 μm, 0.5756 μm, 0.5548 μm, 0.5487 μm, 0.5247 μm, 0.5168 μm, 0.5014 μm}.

[0109] The length L(1)~L(10) of the 10 coils of strip steel is obtained from the production process control system, parameter values are {10.820 km, 10.542 km, 11.258 km, 10.269 km, 12.632 km, 10.032 km, 9.865 km, 10.846 km, 10.326 km, 10.625 km}.

[0110] The unit width rolling pressure of the 10 coils of strip steel is obtained from the production process control system (1)~ (10), parameter values are {428 t, 452 t, 397 t, 408 t, 383 t, 356 t, 432 t, 412 t, 397 t, 457 t}.

[0111] The width B(1)~B(10) of the 10 coils of strip steel is obtained from the production process control system, parameter values are {976 mm, 950 mm, 976 mm, 985 mm, 965 mm, 970 mm, 960 mm, 967 mm, 979 mm, 965 mm}.

[0112] The yield strength of the 10 coils of strip steel is obtained from the production process control system (1)~ (10), parameter values are {520 MPa, 480 MPa, 536 MPa, 495 MPa, 560 MPa, 480 MPa, 542 MPa, 465 MPa, 576 MPa, 565 MPa}.

[0113] The reduction h(1)~h(10) of the 10 coils of strip steel is obtained from the production process control system, parameter values are {0.25 mm, 0.24 mm, 0.23 mm, 0.23 mm, 0.24 mm, 0.23 mm, 0.25 mm, 0.22 mm, 0.21 mm, 0.22 mm}.

[0114] The above parameters are substituted into formula (1) and formula (2) respectively, and the first coefficient~the fifth coefficient are calculated by linear regression: b0=0.3202, b1=0.231434, b2=0.04008, b3=0.40565, b4=0.010534. The correlation index R of the work roll attenuation model 2 is 0.8604.

[0115] Substitute the above parameters into formula (6), and calculate the sixth to tenth influence coefficients by linear regression: β1=0.9562, β2=0.01086, β3=0.0325, β4=0.0053, β5=0.00015.

[0116] The mathematical model of the surface roughness heritability is represented as:

[0117] η(i+1)=0.9562+e 0.01086h(i) -0.0325[ / ] 3 -0.0053[1000 / ] 3 -0.00015 .

[0118] The correlation index R 2 of the mathematical model of the surface roughness heritability is 0.4652. It can be seen from the correlation index R 2 that R 2 is quite different from 1, indicating that the heritability has a low correlation with the reduction, the strip length, the rolling force, the strip width, and the yield strength. The model cannot accurately predict the heritability. Therefore, the heritability is not taken as the work roll off-machine setting index.

[0119] Substitute the above parameters into formula (3), and calculate the first to fifth influence coefficients by linear regression: α1=1.0122, α2=0.0206, α3=0.0444, α4=0.0026, α5=0.00032.

[0120] The mathematical model of the transfer rate is represented as:

[0121] λ(i+1)=1.0122+0.0206h(i)-0.0444 3 -0.0026[1000 / ] 3 -0.00032 formula (8).

[0122] The correlation index R 2 of the mathematical model of the transfer rate is 0.8505. It can be seen from the correlation index R 2 that R 2 is close to 1, indicating that the transfer rate has a high correlation with the reduction, the strip length, the rolling force, the strip width, and the yield strength. The model can accurately predict the transfer rate, and therefore the transfer rate is taken as the work roll off-machine setting index.

[0123] R is a statistic reflecting the closeness of the correlation between two variables, the closer to 1 the closer the relationship, the closer to 0 the linear relationship does not exist, the correlation index R 2 Reflecting the relationship of multiple linear regression, the closer to 1 the more linearly correlated, the closer to 0 the more linearly uncorrelated.

[0124] In this embodiment, the minimum threshold of the transfer rate λ0=0.2 is set.

[0125] Initialize the number of steel coils i=1, start rolling the strip steel, and calculate the transfer rate according to formula (8) after rolling each coil of strip steel, and the calculation results are shown in Table 1.

[0126] Table 1 Roughness value and transfer rate value of the working roll surface after rolling each coil of strip steel

[0127] Steel coil number i Rolling distance (km) Work roll surface roughness (um) Transfer rate 1 10 0.7965 0.5972 2 20 0.6954 0.5848 3 30 0.6234 0.5753 4 40 0.6067 0.5655 5 50 0.5866 0.5559 6 60 0.5655 0.5471 7 70 0.5543 0.5373 8 80 0.5432 0.5278 9 90 0.5281 0.5182 10 100 0.5193 0.5086 11 110 0.5062 0.4991 12 120 0.4885 0.4901 13 130 0.4768 0.4802 14 140 0.4760 0.4707 15 150 0.4715 0.4617 16 160 0.4670 0.4523 17 170 0.4626 0.4424 18 180 0.4581 0.4325 19 190 0.4536 0.4236 20 200 0.4491 0.4139 21 210 0.4446 0.4048 22 220 0.4401 0.3947 23 230 0.4357 0.3858 24 240 0.4312 0.3760 25 250 0.4267 0.3663 26 260 0.4222 0.3567 27 270 0.4177 0.3471 28 280 0.4132 0.3380 29 290 0.4088 0.3290 30 300 0.4043 0.3195 31 310 0.3998 0.3099 32 320 0.3953 0.2998 33 330 0.3908 0.2909 34 340 0.3863 0.2809 35 350 0.3819 0.2719 36 360 0.3774 0.2618 37 370 0.3729 0.2529 38 380 0.3684 0.2435 39 390 0.3639 0.2340 40 400 0.3594 0.2241 41 410 0.3550 0.2148 42 420 0.3505 0.2054 43 430 0.3495 0.2001 44 440 0.3490 0.1988

[0128] From Table 1, it can be seen that during the rolling of the first to the 43rd coil of strip steel, the transfer rate is greater than 0.2; after rolling the 43rd coil of strip steel, according to formula (8), it is calculated that after rolling the 44th coil of strip steel, i.e. after rolling 440km, the transfer rate will decrease to 0.1988<0.2, then the output steel coil number i=43, after rolling the 43rd coil of strip steel, stop rolling and replace the working roll.

[0129] At this time, the roughness of the working roll surface is 0.3490um, and after the working roll is replaced, the actual measurement of the roughness of the working roll surface is 0.32um, and the prediction error is within 10%.

[0130] The above is only a preferred embodiment of the present application, and is not used to limit the protection scope of the present application, therefore, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method of predicting surface roughness of work rolls of a secondary cold rolling mill train, characterized by: The method comprises the following steps: Step 1: establishing a surface roughness attenuation model of the work roll according to a steel grade production process, and the model formula is: Equation (1) Wherein, i is the number of steel coils of the strip steel, i=1, 2, …, M; M is the total number of rolled steel coils of the work roll in a service period; Rf is the roughness of the work roll surface after rolling the i coiled strip; Li is the length of the i-th coil of strip steel; is a first coefficient, is a second coefficient, is a third coefficient, is a fourth coefficient, is a fifth coefficient, the first coefficient to the fifth coefficient being calculated by linear regression. is the ratio of the rolling pressure per unit width to the yield strength in the i-th coil, and the calculation formula is: Equation (2) wherein, is the total rolling force for the i-th coil of strip steel; Wj is the strip width for the i-th coil; Yi is the yield strength of the i-th coil of strip steel; Step 2: establishing a mathematical model of the transfer rate of the work roll, and the mathematical model formula of the transfer rate is: λ(i+1) = α1+ α2h(i) - α3 3 - α4[1000 / ] 3 - α5 Equation (3) Wherein, λ(i+1) is the transfer rate after rolling of the i+1th coil of strip steel; α1 is a first influence coefficient, α2 is a second influence coefficient, α3 is a third influence coefficient, α4 is a fourth influence coefficient, and α5 is a fifth influence coefficient, and the first influence coefficient to the fifth influence coefficient are calculated by linear regression; h(i) is the reduction of the i th coil of strip steel; L is the length of the i-th coil of strip steel; The relationship between the surface roughness Ra of the exit strip of the i-th coil and the surface roughness of the work roll after rolling the i-th coil is given by: S The relationship between the surface roughness Ra of the exit strip of the i-th coil and the surface roughness of the work roll after rolling the i-th coil is given by: The relationship between the surface roughness Ra of the exit strip of the i-th coil and the surface roughness of the work roll Ra S (i)=η(i)Ra S0 +λ(i) Equation (7) wherein Ra S (i) is the exit strip surface roughness of the i-th coil of strip steel; η(i) is the surface roughness inheritance rate of the i th coil of strip steel; Ra S0 Ri is the surface roughness of the incoming strip surface for the i-th coil; λ(i) is the transfer rate after rolling of the i th coil of strip steel; Step 3: setting a minimum threshold λ0 of the transfer rate according to the steel grade production process; Step 4: setting the number of rolled steel coils i, i∈[1, M] and initializing i=1; Step 5: rolling the i th coil of strip steel, and calculating the transfer rate λ(i+1) after rolling of the next coil of strip steel according to formula (3); Step 6: judging whether the transfer rate λ(i+1) calculated in step 5 is ≤ the minimum threshold λ0 of the transfer rate, if yes, executing step 7; if not, letting i=i+1 and returning to step 5; Step 7: outputting the number of steel coils i, and stopping rolling and replacing the work roll after rolling of the i th coil of strip steel is completed.

2. The method of claim 1, wherein the method is characterized by: In the step 2, the mathematical model of the transfer rate is established by: Step 2.1 : Calculate the rolling additional surface roughness Ra of the i-th coil ad (i) with the formula: Ra ad (i)=λ(i) Equation (4); Step 2.2: Calculate the exit strip surface roughness Ra S (i) the exit strip surface roughness Ra S (i) is determined by the strip inherited roughness and the additional surface roughness at rolling, i.e.: Ra S (i) = η(i) Ra S0 + Ra ad (i) Equation (5) wherein Ra S (i) is the exit strip surface roughness of the i-th coil of strip steel; η(i) is the surface roughness heritability of the i-th coiled steel, η(i) is correlated with the reduction h(i), the ratio of the rolling force per unit width to the yield strength , the yield strength of the steel strip , the length of the steel strip ; Establishing a mathematical model of the surface roughness inheritance rate: η(i+1) = β1+ e β2h(i) - β3[1000 / ] 3 - β4[1000 ] 3 - β5 Equation (6) Wherein, β1 is a sixth influence coefficient, β2 is a seventh influence coefficient, β3 is an eighth influence coefficient, β4 is a ninth influence coefficient, and β5 is a tenth influence coefficient, and the sixth influence coefficient to the tenth influence coefficient are calculated by linear regression; Ra S0 Ri is the surface roughness of the incoming strip surface for the i-th coil; Ra ad (i) is the additional surface roughness for the i-th coil of steel; Step 2.3: bringing formula (4) into formula (5) to obtain: Ra S (i)=η(i)Ra S0 +λ(i) Equation (7); Step 2.4: From equation (7), when the work roll and strip material are determined, the transfer ratio λ is related to the reduction h(i), the ratio of the rolling force per unit width to the yield strength , the yield strength of the strip , the length of the strip , and the mathematical model of the transfer ratio is established: λ(i+1) =α1+α2h(i)-α3 3 -α4[1000 / ] 3 -α5 .

3. The method of claim 1, wherein the method is characterized by: In the step 3, the minimum threshold λ0 of the transfer rate is set as the minimum value of the surface roughness of the strip steel of the current steel grade.

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