Hot rolling production line working roll wear model optimization coefficient calculation method

Abstract

The invention relates to a hot rolling production line working roller wear model optimization coefficient calculation method, and belongs to the technical field of steel rolling control methods. According to the technical scheme, the method comprises the steps that S1, a wear model formula before optimization and a secondary model wear value in a working roll period are found; s2, the actually-measured abrasion roller shape value of the working roller in the same roller period is calculated; s3, obtaining various parameter values of the existing worn roll shape model formula; s4, calculating a compensation coefficient before the wear model is optimized; s5, defining a compensation coefficient as a functional expression; and S6, a wear model formula of the working roll is completed, all the secondary wear model values in the roll period are added, finally, the sum is compared with a measured value of the wear model of the working roll, and a wear model formula compensation coefficient is obtained. The compensation coefficient of the wear model formula is changed according to the production scheduling plans of different steel types, and the wear value of the working roller can be predicted more accurately; the difference between the predicted value and the measured value of the secondary model is reduced, and the effect of improving the target strip shape is achieved.

Description

Technical Field

[0001] The invention relates to a method for calculating an optimization coefficient of a wear model of a working roll of a hot rolling production line, and belongs to the technical field of steel rolling control methods. Background Art

[0002] In the production of hot rolled strip, roll wear is one of the important factors affecting the strip shape. Roll wear includes support roll wear and working roll wear. Support roll wear affects the bending deformation of the working roll, which in turn affects the strip shape, while working roll wear affects the mill roll gap shape, which directly affects the strip shape quality. The wear law and amount of roll wear are factors that are difficult to quantitatively control in current production. Therefore, in-depth research on roll wear is of great significance to actual production, and it is particularly important to develop a set of working roll wear model formulas that are combined with the field to ensure the strip shape.

[0003] Usually, the optimization of the on-site working roll wear model formula is usually just to compare the wear value results of the measured wear value during a whole roll period with the wear value results of the secondary model value, and then add the compensation coefficient for optimization. However, the materials and specifications of the products produced on-site are constantly changing, which usually leads to a large difference between the wear roll shape value and the measured roll shape value. Summary of the invention

[0004] The purpose of the present invention is to provide a method for calculating the optimization coefficient of the wear model of the working roll of a hot rolling production line. By changing the compensation coefficient of the wear model formula according to the production schedule of different steel grades on site, the wear value of the working roll can be predicted more accurately; the gap between the predicted value and the measured value of the secondary model can be reduced, so as to achieve the effect of improving the target plate shape, and effectively solve the above-mentioned problems existing in the background technology.

[0005] The technical solution of the present invention is: a method for calculating the optimization coefficient of the working roll wear model of a hot rolling production line, comprising the following steps:

[0006] S1: Collect the wear model formula before optimization and the secondary model wear value of the working roll during the roll period;

[0007] S2: Calculate the actual measured wear roll shape value of the same working roll during the roll period using the on-site working roll wear roll shape curve;

[0008] S3: Obtain various parameter values ​​of the current wear roller shape model formula by collecting data and calculating relevant data;

[0009] S4: Calculate the compensation coefficient y1 of the current wear model using the secondary model wear value of the working roll and the above-mentioned parameter values;

[0010] S5: defining the compensation coefficient of the current wear roll shape as a function, which is a function defined for each steel during the rolling period of the working roll, and using the function to obtain the compensation coefficient y2 of the optimized wear model;

[0011] S6: Calculate the secondary wear model value of each steel through the specific parameter values ​​in the wear model formula related to each steel, add up all the secondary wear model values ​​in the roll period, compare with the measured value of the working roll wear model, and obtain the compensation coefficient of the wear model formula.

[0012] In the step S1, the wear model formula before optimization is wear value = wear rate * rolling force per unit width * rotation speed * compensation coefficient, wherein the compensation coefficient is the measured wear roller shape value / the secondary model roller shape value.

[0013] In step S2, the measured worn roll shape value is calculated by taking the difference between the post-grinding curve value of the working roll after grinding before the rolling mill and the pre-grinding curve value of the cold roll after cooling after the rolling mill.

[0014] In step S3, the collected data include the wear rate of the working roll, the rolling force per unit width, the rotation speed of the working roll, and the measured wear roll shape value during the roll period.

[0015] In step S4, the compensation coefficient y1 of the current wear model is obtained by dividing the actual measured values ​​of all working rolls in all roll periods by the secondary wear value.

[0016] In the step S5,

[0017] S51: defining the compensation coefficient function of the current wear model as a linear equation a1x1+a2x2, where x1 is the different steel races or carbon equivalents associated with all products in the working roll rolling period, and x2 is the target width of all products in the working roll rolling period;

[0018] S52: The specific values ​​of a1 and a2 are obtained by using the regression wear model formula method, and the compensation coefficient function formula of the wear model is used to calculate the result, which is the optimized wear roller shape compensation coefficient y2.

[0019] In step S6, the compensation coefficient of the wear model formula is obtained by dividing the compensation coefficient y2 of the optimized wear model formula by the compensation coefficient y1 of the wear model formula before optimization, that is, multiplying the original wear model formula by the compensation coefficient y2 / y1.

[0020] The beneficial effects of the present invention are as follows: by changing the compensation coefficient of the wear model formula according to the production schedule of different steel grades on site, the wear value of the working roll can be predicted more accurately; the gap between the predicted value and the measured value of the secondary model is reduced, thereby achieving the effect of improving the target plate shape. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of the invention implementation cases clearer, the technical solutions of the present invention will be clearly and completely described in conjunction with the implementation cases below. Obviously, the implementation cases described are only a small part of the implementation cases of the present invention, rather than all the implementation cases. Based on the implementation cases in the present invention, all other implementation cases obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0022] A method for calculating an optimization coefficient of a working roll wear model of a hot rolling production line comprises the following steps:

[0023] S1: Collect the wear model formula before optimization and the secondary model wear value of the working roll during the roll period;

[0024] S2: Calculate the actual measured wear roll shape value of the same working roll during the roll period using the on-site working roll wear roll shape curve;

[0025] S3: Obtain various parameter values ​​of the current wear roller shape model formula by collecting data and calculating relevant data;

[0026] S4: Calculate the compensation coefficient y1 of the current wear model using the secondary model wear value of the working roll and the above-mentioned parameter values;

[0027] S5: defining the compensation coefficient of the current wear roll shape as a function, which is a function defined for each steel during the rolling period of the working roll, and using the function to obtain the compensation coefficient y2 of the optimized wear model;

[0028] S6: Calculate the secondary wear model value of each steel through the specific parameter values ​​in the wear model formula related to each steel, add up all the secondary wear model values ​​in the roll period, compare with the measured value of the working roll wear model, and obtain the compensation coefficient of the wear model formula.

[0029] In the step S1, the wear model formula before optimization is wear value = wear rate * rolling force per unit width * rotation speed * compensation coefficient, wherein the compensation coefficient is the measured wear roller shape value / the secondary model roller shape value.

[0030] In step S2, the measured worn roll shape value is calculated by taking the difference between the post-grinding curve value of the working roll after grinding before the rolling mill and the pre-grinding curve value of the cold roll after cooling after the rolling mill.

[0031] In step S3, the collected data include the wear rate of the working roll, the rolling force per unit width, the rotation speed of the working roll, and the measured wear roll shape value during the roll period.

[0032] In step S4, the compensation coefficient y1 of the current wear model is obtained by dividing the actual measured values ​​of all working rolls in all roll periods by the secondary wear value.

[0033] In the step S5,

[0034] S51: defining the compensation coefficient function of the current wear model as a linear equation a1x1+a2x2, where x1 is the different steel races or carbon equivalents associated with all products in the working roll rolling period, and x2 is the target width of all products in the working roll rolling period;

[0035] S52: The specific values ​​of a1 and a2 are obtained by using the regression wear model formula method, and the compensation coefficient function formula of the wear model is used to calculate the result, which is the optimized wear roller shape compensation coefficient y2.

[0036] In step S6, the compensation coefficient of the wear model formula is obtained by dividing the compensation coefficient y2 of the optimized wear model formula by the compensation coefficient y1 of the wear model formula before optimization, that is, multiplying the original wear model formula by the compensation coefficient y2 / y1.

[0037] Example:

[0038] Existing wear model formula: Wear value = wear rate * unit width rolling force * speed * compensation coefficient

[0039] The working roll is made of high chromium cast iron with a wear rate of 1.200E-7

[0040] Rolling force per unit width = rolling force of a certain stand / target width

[0041] Speed ​​= working roll rolling kilometers / 3.14 / working roll diameter*1000000 / finishing rolling pure rolling time (min)

[0042] Compensation coefficient = a1*target width + a2*steel type

[0043] Through the known data wear rate of 1.20*10^-7, the unit width rolling force x[i] of the working roll when producing each steel, the working roll speed u[i] when producing each steel, the wear value t during the roll life, the number of products produced by the working roll during the roll life n, the target width v[i] of each steel and the steel family number w[i] of each steel, the regression equation is:

[0044] MinFunction abs(t-Sum(i=1:n)(1.20*10^-7*x[i]*u[i]*(a1*v[i]+a2*w[i])))

[0045] Obtain the values ​​of a1 and a2 through regression

[0046] Then a1*v[i]+a2w[i] is the compensation coefficient value of the working roll wear model when producing each steel. The wear value of the working roll when producing each steel is z=1.20*10^-7*x[i]*u[i]*(a1*v[i]+a2*w[i]). The wear value of n steels in this roll period is h=Sum(i=1:n)(1.20*10^-7*x[i]*u[i]*(a1*v[i]+a2*w[i])). This wear value is the optimized secondary model wear value. The compensation coefficient is calculated to be y2. The compensation coefficient y1 is calculated using the secondary model wear value of the working roll before optimization and the above parameter values. The compensation coefficient result of this optimization is y=y2 / y1.

[0047] Example

[0048] Known parameters:

[0049] F7 frame working roll material high chromium cast iron wear rate is 1.20*10^-7

[0050] The rolling force per unit width of the working roll when producing each steel bar is x[i]

[0051] Working roll speed u[i] for each steel produced

[0052] The measured value of working roll wear during the roll period is 0.08

[0053] The secondary model wear value of the working roll during the roll period is 0.78

[0054] The number of products produced by the working roll during the rolling period is 50

[0055] Target width of each steel bar v[i]

[0056] The steel family number of each steel w[i]

[0057] The specific parameter data of the unit width rolling force x[i], rotation speed u[i], target width v[i], and steel family number w[i] of each steel during the rolling period are as follows:

[0058]

[0059]

[0060] The values ​​of a1 and a2 after regression are a1:-0.0186414213264499, a2:1.38436354888771. After calculation, the wear value of the optimized secondary model is 0.08.

[0061] Compensation coefficient before optimization y1 = 0.078 / 0.08 = 0.975

[0062] The optimized compensation coefficient y2 = 0.08 / 0.08 = 1

[0063] Then the optimization coefficient value is y2 / y1=1 / 0.975=1.02564103.

Claims

1. A method for calculating the optimization coefficient of the working roll wear model of a hot rolling production line, characterized in that The following steps are involved: S1: Collect the wear model formula before optimization and the secondary model wear value of the working roll during the roll period; S2: Calculate the actual measured wear roll shape value of the same working roll during the roll period using the on-site working roll wear roll shape curve; S3: Obtain various parameter values ​​of the current wear roller shape model formula by collecting data and calculating relevant data; S4: Calculate the compensation coefficient y1 of the current wear model using the secondary model wear value of the working roll and the above-mentioned parameter values; S5: defining the compensation coefficient of the current wear roll shape as a function, which is a function defined for each steel during the rolling period of the working roll, and using the function to obtain the compensation coefficient y2 of the optimized wear model; S6: Calculate the secondary wear model value of each steel through the specific parameter values ​​in the wear model formula related to each steel, add up all the secondary wear model values ​​in the roll period, compare with the measured value of the working roll wear model, and obtain the compensation coefficient of the wear model formula.

2. The method for calculating the optimization coefficient of the working roll wear model of a hot rolling production line according to claim 1, characterized in that: In the step S1, the wear model formula before optimization is wear value = wear rate × rolling force per unit width × rotation speed × compensation coefficient, wherein the compensation coefficient is the measured wear roller shape value / the secondary model roller shape value.

3. The method for calculating the optimization coefficient of the working roll wear model of a hot rolling production line according to claim 1, characterized in that: In step S2, the measured worn roll shape value is calculated by taking the difference between the post-grinding curve value of the working roll after grinding before the rolling mill and the pre-grinding curve value of the cold roll after cooling after the rolling mill.

4. The method for calculating the optimization coefficient of the working roll wear model of a hot rolling production line according to claim 1, characterized in that: In step S3, the collected data include the wear rate of the working roll, the rolling force per unit width, the rotation speed of the working roll, and the measured wear roll shape value during the roll period.

5. The method for calculating the optimization coefficient of the working roll wear model of a hot rolling production line according to claim 1, characterized in that: In step S4, the compensation coefficient y1 of the current wear model is obtained by dividing the actual measured values ​​of all working rolls in all roll periods by the secondary wear value.

6. The method for calculating the optimization coefficient of the working roll wear model of a hot rolling production line according to claim 1, characterized in that: In the step S5, S51: defining the compensation coefficient function of the current wear model as a linear equation a1x1+a2x2, where x1 is the different steel races or carbon equivalents associated with all products in the working roll rolling period, and x2 is the target width of all products in the working roll rolling period; S52: The specific values ​​of a1 and a2 are obtained by using the regression wear model formula method, and the compensation coefficient function formula of the wear model is used to calculate the result, which is the optimized wear roller shape compensation coefficient y2.

7. The method for calculating the optimization coefficient of the working roll wear model of a hot rolling production line according to claim 7, characterized in that: In step S6, the compensation coefficient of the wear model formula is obtained by dividing the compensation coefficient y2 of the optimized wear model formula by the compensation coefficient y1 of the wear model formula before optimization, that is, multiplying the original wear model formula by the compensation coefficient y2 / y1.

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