JP2002224726A - Temper rolling method for metal strip - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method which enables precise temper rolling of a metal strip under rolling load calculated using an estimation equation of rolling load. SOLUTION: In temper rolling of a metal strip by a temper rolling mill, taking extension ratio and strip width as variables, rolling load is expressed in the equations, p=a.r+b, P=W.p wherein, p is rolling load for a unit width, r is extension ratio, P is rolling load, W is strip width, and a, b are sensitivity coefficients. The temper rolling mill is controlled to roll, based on the rolling load estimated by this mathematical model composed of the equations.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for accurately predicting a rolling load in rolling of a metal strip using a temper rolling mill, and performing a rolling operation so as to obtain a target elongation and a metal strip shape. Things.

[0002]

2. Description of the Related Art In the process of cold rolling a steel strip, a cold-rolled steel sheet finished to a target thickness is often annealed and then temper-rolled to obtain a predetermined elongation to obtain a product. . The temper rolling mill is computer-controlled so that a target elongation rate is obtained. In this computer control, it is necessary to predict a rolling load generated during rolling. Further, since the rolling load has a great effect on the shape of the finished cold-rolled steel strip, it is important to predict the rolling load from the viewpoint of shape preset control.

Conventionally, as a rolling load prediction model, a well-known and commonly used Bland & Ford rolling load equation shown in equation (1) has been used. _{P b & f = f (k} m, t 1, t 2) Q P L P (1) P b & f: rolling load, k _m: Mean deformation resistance, Q _P: rolling force function L _P: Contact arc length, t _1, t ₂ : Inlet / outlet unit tension

However, in the case of rolling with a small rolling reduction such as temper rolling, if the rolling load is estimated using the Bland & Ford rolling load formula, the actual rolling load and the calculated rolling load are significantly different. This is based on the assumption that the roll shape in the rolling direction in the roll tool maintains an arc as shown in FIG. 1 in the rolling load formula of Bland & Ford, but the rolling reduction is similar to that of temper rolling. If it is small, as shown in FIG. 2, the flat deformation amount ΔR of the roll may become almost equal to the rolling reduction amount Δt due to the force received from the plate, and the undulation of the roll shape cannot be ignored.

[0005] Therefore, in order to improve the rolling load prediction system in temper rolling, the literature "The 42nd Lecture on Plasticity, (199)
1), p. 465 ", a rolling load analysis model that considers the undulation of the roll shape has been proposed. In this analysis model, the rolling pressure distribution is calculated assuming the rolling direction distribution of the roll gap, that is, the sheet thickness distribution, and the rolling pressure distribution is calculated repeatedly until the obtained roll gap distribution matches the assumed value. The distribution is determined and the rolling load is calculated.

[0006]

However, these rolling load analysis models calculate the rolling load by performing convergence calculation until a suitable solution of the roll shape and the thickness distribution is obtained. Therefore, it is difficult to use the formula as a mathematical model for calculating the rolling load online. Therefore, the Bland & Ford rolling load equation and the like are still used, and there is a problem that the estimation accuracy of the rolling load is poor, and a target elongation rate and a metal strip shape cannot be obtained in many cases. The present invention has been devised to solve such a problem, and by using a rolling load prediction formula in a high-precision temper rolling that can be used online, the temper rolling of a metal strip can be performed with high accuracy. The aim is to provide a way to do so.

[0007]

SUMMARY OF THE INVENTION In order to achieve the object, a method for temper rolling a metal strip according to the present invention comprises, in rolling a metal strip using a temper rolling mill, rolling by using the elongation percentage and the sheet width as variables. The following expression representing the load: p = ar · b + b P = W · p where p: rolling load per unit width, r: elongation percentage P: rolling load, W: plate width, a, b: influence coefficient The rolling load is predicted by a mathematical model to be performed, and rolling is controlled by controlling a rolling mill based on the predicted rolling load.

[0008]

BEST MODE FOR CARRYING OUT THE INVENTION The present inventors have conducted various investigations and studies on a highly accurate rolling load prediction method which can be used online in temper rolling. As a result, paying attention to the fact that the rolling load per unit width is almost linear with the elongation,
It has been found that the rolling load can be accurately predicted by using a mathematical model incorporating the effect of the elongation on the rolling load.

Hereinafter, the present invention will be described in detail. The inventor of the present invention described in the above-mentioned document "The 42nd Plastic Lending Lecture, (1991),
P. 465 ", a rolling load analysis model in temper rolling in consideration of the roll undulation was prepared. This analysis model is a model in which an elastic deformation analysis of a roll and a plastic deformation analysis of a material are coupled, and is characterized in that a roll shape is calculated by a numerical analysis from a rolling pressure distribution.

Factors affecting the rolling load include the sheet width,
There are plate thickness, material, tension, lubrication state and elongation. Of these, considering the effect of the sheet width, the rolling load is proportional to the sheet width, so other factors that affect the rolling load per unit width may be considered. In addition, regarding the influence of the sheet thickness and the material, an influence coefficient in a mathematical model may be set in a table for each section of the sheet thickness and the material, and the influence coefficient may be expressed as a function of the sheet thickness and the material. is there. Regarding the influence of the tension, since the rolling is performed with almost the same tension in the same sheet thickness and the same material category, it can be taken into the mathematical model as a constant value. As for the lubrication state, the change affects the rolling load as a change in the friction coefficient. It should be taken in.

With respect to the lubricating state, the fluctuation changes the friction coefficient and affects the rolling load. Since the friction coefficient during rolling in the actual machine cannot be determined experimentally, an arbitrary friction coefficient is input to the rolling load analysis model, and the friction coefficient is set so that the rolling load obtained by simulation matches the rolling load in the actual machine. The reverse calculation is performed, and the average value may be taken as the friction coefficient when calculating the rolling load using the rolling load analysis model.

Next, the effect of the elongation on the rolling load was examined. Using the above-mentioned rolling load analysis model, a medium-carbon steel hot-rolled sheet having a sheet thickness of 2.6 mm has an elongation of 0.6 to
As a result of performing a simulation of rolling in the range of 2.0%, as shown in FIG. 3, the elongation and the rolling load per unit width can be arranged in a substantially linear relationship. Therefore, the rolling load prediction formula is expressed as in equations (2) and (3). p = ar · b + (2) P = W · p (3) where p is a rolling load per unit width, r is an elongation, P is a rolling load, W is a sheet width, and a and b are influence coefficients. Show.

The influence coefficients a and b are constants determined by the sheet thickness and the material, and are analysis models obtained by coupling the elastic deformation analysis of the roll and the plastic deformation analysis of the material such as an experiment or the above-mentioned rolling load analysis model. From the simulation by The influence coefficient a is obtained as a gradient in a linear relationship between the elongation rate r and the rolling load p per unit width, and the influence coefficient b is obtained as a constant term in the relation. In FIG. 3, a = 2.608 kN / m
m and b = 5.602 kN / mm. Each influence coefficient is
As shown in Table 1, a table may be set for each sheet thickness and material classification, or a mathematical expression may be made as a function of the sheet thickness and material.

[0014]

The rolling load p per unit width is calculated by substituting the target elongation into equation (2), and the obtained rolling load p per unit width and sheet width W are substituted into equation (3) for rolling. The load is calculated. FIG. 4 shows a comparison between the rolling load calculated by the rolling load prediction formula and the rolling load directly calculated by the rolling load analysis model.
% And the standard deviation are well in agreement with 1.4%. And
Elongation and shape are controlled based on the calculated rolling load.

[0016]

EXAMPLES The present invention was applied to an actual temper rolling mill to verify the accuracy of a rolling load prediction formula. The rolling mill has a roll diameter of 65.
Using a 4-mm rolling mill of 0 mm, plate width 800 to 1200 m
m, a low carbon steel hot rolled sheet having a sheet thickness of 1.4 to 4.5 mm was rolled. When rolling low-carbon steel with a thickness of 2.3 mm and a width of 866 mm at a target elongation of 1.75%, Bland is applied based on the conventional method.
The rolling load predicted by &Ford's rolling load formula is 6804
kN and the actual rolling load measured by a load cell during the actual rolling is 6300 kN. As shown in FIG. 5A, the calculated rolling load tends to be larger than the actual rolling load measured by a load cell during rolling, and the difference is 7.8% in average and the standard deviation is 5%. 0.9%.

On the other hand, in the method of the present invention, the influence coefficient a = 1.921 (kN /
mm) and b = 3.884 (kN / mm), and were calculated by the rolling load prediction formulas of Expressions (2) and (3). Board thickness 2.
3mm, 866mm low carbon steel with target elongation of 1.7
When rolling at 5%, the rolling load is 6275 kN,
This is in good agreement with the actual rolling load of 6300 kN. FIG. 5 (b) shows the calculated and measured values of the rolling load for each sheet thickness, sheet width, and elongation, and plots them. The difference between the calculated rolling load and the actual rolling load is 2.2% on average and the standard deviation is 1.6%, and the prediction accuracy is improved as compared with the conventional method.

[0018]

As described above, according to the present invention, the present invention can be used on-line in consideration of the linear relationship between the elongation percentage and the rolling load obtained from the rolling load analysis model in consideration of the undulation of the roll shape. Since the rolling load is calculated by the rolling load prediction formula, the rolling load can be accurately predicted, and the target elongation and the shape of the metal strip can be obtained.

[Brief description of the drawings]

FIG. 1 is a diagram showing a roll shape on the assumption that an arc is maintained.

FIG. 2 is a diagram showing a roll-shaped undulation

FIG. 3 is an explanatory diagram showing a linear relationship between elongation and rolling load per unit width.

FIG. 4 is a diagram showing a comparison between a rolling load calculated by a rolling load prediction formula according to the present invention and a rolling load directly calculated by a rolling load analysis model.

FIG. 5 is a diagram showing a comparison between a calculated rolling load and an actual rolling load in (a) a conventional method and (b) a method of the present invention.

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Kenji Hara 1 Tsurucho, Amagasaki-shi, Hyogo F-term in Nisshin Steel Co., Ltd. Technical Research Institute 4E024 AA01 BB01 CC02 EE02

Claims (1)

[Claims] 1. In the rolling of a metal strip using a temper rolling mill, the following equation expressing the rolling load with elongation and strip width as variables: p = ar · b P = W · p, where p: unit width Rolling load per unit, r: elongation percentage, P: rolling load, W: plate width, a, b: influence coefficient, and the rolling load is predicted by a mathematical model, and the rolling mill is controlled based on the predicted rolling load. A temper rolling method for a metal strip, characterized by performing rolling.