A calculation method for optimization coefficient of work roll wear model of hot rolling production line

Abstract

The present invention relates to a method for calculating the optimization coefficient of the wear model of the working roll of a hot rolling production line, and belongs to the technical field of steel rolling control methods. The technical solution of the present invention is: S1: finding the wear model formula before optimization and the secondary model wear value of the working roll during the roll period; S2: calculating the actual wear roll shape value of the working roll and the same roll period; S3: obtaining the various parameter values ​​of the current wear roll shape model formula; S4: calculating the compensation coefficient before optimizing the wear model; S5: defining the compensation coefficient as a function; S6: completing the wear model formula of the working roll, adding all the secondary wear model values ​​within the roll period, and finally comparing them with the actual measured value of the working roll wear model to obtain the compensation coefficient of the wear model formula. The present invention changes the compensation coefficient of the wear model formula according to the production schedule of different steel grades, which can more accurately predict the wear value of the working roll; reducing the gap between the predicted value and the actual measured value of the secondary model, and achieving the effect of improving the target plate shape.

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 hot-rolled strip production, roll wear is a significant factor affecting strip shape. Roll wear includes both backup roll wear and work roll wear. Backup roll wear affects work roll bending, which in turn affects strip shape, while work roll wear affects the mill roll gap shape, directly impacting strip shape quality. The patterns and amount of roll wear are currently difficult to quantitatively control in production. Therefore, in-depth research on roll wear is of great significance to practical production, and developing a work roll wear model formula that can be integrated with field practice to ensure strip shape is particularly important.

[0003] Usually, the optimization of the on-site working roller wear model formula is usually just to compare the wear value results of the measured wear value during the entire roller 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 roller shape value and the measured roller 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 rolls 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, thereby achieving the effect of improving the target plate shape, and effectively solving 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 work 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 work roll during the roll period;

[0007] S2: Calculate the actual wear roll profile value of the same work roll during the above-mentioned period using the on-site work roll wear roll profile curve;

[0008] S3: Obtain the 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 work roll and the above parameter values;

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

[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 ​​within the roll period, and compare them with the measured values ​​of the work roll wear model to obtain the compensation coefficient of the wear model formula.

[0012] In 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 before being put on the rolling mill and the pre-grinding curve value of the cold roll after being cooled after being taken off the 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 profile value during the roll period.

[0015] In step S4, the compensation coefficient y1 of the currently used wear model is obtained based on the quotient of the measured values ​​of all working rolls in all roll periods and 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 species or the carbon equivalents related thereto for all products within the work roll rolling period, and x2 is the target width of all products within the work roll rolling period;

[0018] S52: The specific values ​​of a1 and a2 are calculated using the regression wear model formula, and the compensation coefficient function 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: 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 of the secondary model and the measured value 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 combination 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 work 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 work roll during the roll period;

[0024] S2: Calculate the actual wear roll profile value of the same work roll during the above-mentioned period using the on-site work roll wear roll profile curve;

[0025] S3: Obtain the 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 work roll and the above parameter values;

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

[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 ​​within the roll period, and compare them with the measured values ​​of the work roll wear model to obtain the compensation coefficient of the wear model formula.

[0029] In 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 before being put on the rolling mill and the pre-grinding curve value of the cold roll after being cooled after being taken off the 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 profile value during the roll period.

[0032] In step S4, the compensation coefficient y1 of the currently used wear model is obtained based on the quotient of the measured values ​​of all working rolls in all roll periods and 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 species or the carbon equivalents related thereto for all products within the work roll rolling period, and x2 is the target width of all products within the work roll rolling period;

[0035] S52: The specific values ​​of a1 and a2 are calculated using the regression wear model formula, and the compensation coefficient function 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] The regression equation is based on the seven known data: wear rate of 1.20*10^-7, rolling force per unit width of the working roll when producing each steel, working roll speed u[i] when producing each steel, wear value t during the roll period, number of products produced by the working roll during the roll period, target width of each steel v[i], and steel family number w[i] of each steel:

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

[0045] The values ​​of a1 and a2 are obtained 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]), and 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, and the compensation coefficient is calculated as 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] The working roll of F7 frame is made of high chromium cast iron and the 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] when producing each steel

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

[0053] The wear value of the secondary model 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], 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 work 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 work roll during the roll period; S2: Calculate the actual wear roll profile value of the same work roll during the above-mentioned period using the on-site work roll wear roll profile curve; S3: Obtain the 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 work roll and the above parameter values; S5: defining the compensation coefficient of the current wear model as a function, which is a function defined for each steel during the rolling period of the work roll, and using the function to obtain the compensation coefficient y2 of the optimized wear model; S6: Calculate the secondary model wear value of each steel bar through the specific parameter values ​​in the wear model formula related to each steel bar. Add up all the secondary model wear values ​​within the roll period and compare them with the measured values ​​of the work roll wear model to obtain the compensation coefficient of the wear model formula.

2. The method for calculating the optimization coefficient of the work roll wear model of a hot rolling production line according to claim 1, characterized in that: In step S1, the wear model formula before optimization is wear value = wear rate * rolling force per unit width * rotation speed * compensation coefficient, where 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 work 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 before being put on the rolling mill and the pre-grinding curve value of the cold roll after being cooled after being taken off the mill.

4. The method for calculating the optimization coefficient of the work 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 profile value during the roll period.

5. The method for calculating the optimization coefficient of the work 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 based on the quotient of the measured values ​​of all working rolls in all roll periods and the wear value of the secondary model.

6. The method for calculating the optimization coefficient of the work 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 species or the carbon equivalents related thereto for all products within the work roll rolling period, and x2 is the target width of all products within the work roll rolling period; S52: Calculate the specific values ​​of a1 and a2 using the regression wear model formula, and use the compensation coefficient function of the wear model to calculate the result, which is the compensation coefficient y2 of the optimized wear model.

7. The method for calculating the optimization coefficient of the work roll wear model of a hot rolling production line according to claim 1, 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 by the compensation coefficient y1 of the wear model before optimization, that is, multiplying the original wear model formula by the compensation coefficient y2 / y1.

Images