CN1979497A - Optimizing method for preventing and controlling scrab in cold band-steel continuous milling machine - Google Patents

Abstract

The invention discloses an optimization method aimed at preventing scratches in a continuous cold strip rolling mill. The method collects parameters such as equipment, strip steel characteristics, and rolling process of the cold strip continuous rolling mill, and specifies the initial tension and The set value of the reduction amount, and then calculate the slip factor of each stand of the cold tandem rolling mill and the value of the comprehensive judgment index of the scratch of each stand, and obtain the objective function of the optimal setting of the rolling procedure; then judge the objective function Whether Powell's condition is met or not, the optimal tension and reduction setting values are obtained. The method of the present invention introduces the concept of scratch judgment, considers each stand of the tandem cold rolling mill as a whole, and takes scratch prevention as the goal to carry out online optimization setting of the rolling schedule. This method can play a role in ensuring Under the premise of product quality, the rolling speed is greatly improved, the surface quality of the strip is improved, and the huge economic losses caused by the enterprise are greatly reduced.

Description

An optimization method aiming at scratch prevention in cold-strip continuous rolling mill

technical field

The invention relates to forming processing of cold strip steel, in particular to an optimization method aiming at scratch prevention in a cold strip continuous rolling mill.

Background technique

The cold strip continuous rolling process is shown in Figure 1. The strip 1 is uncoiled from the uncoiler 2 and then sent to the stands 31~3i. After being rolled by multiple stands, the strip 1 reaches the specified thickness and is sent to the Coiler rewinds. The rolls of each stand include backup rolls 4 and work rolls 5, wherein the work rolls 5 are in direct contact with the strip surface.

The rolling process generally includes the setting of parameters such as front and rear tension of each stand, pass deformation (characterized by pass reduction or reduction rate). Since these parameters are the key factors of quality control in the cold strip continuous rolling process, a lot of research work has been done in this area. For details on the optimal control or setting methods of these parameters, please refer to "Reduction Regulations for Plate and Strip Mills" Energy optimization design" "Nonferrous Metals" 1998 No. 2, pp. 51-54, "Cold-rolled strip reduction procedure optimization design" "Hebei Metallurgy" 2002 No. 2, pp. 24-27, and "Cold-rolled broadband Optimization of steel rolling procedures" "Shanghai Metal" 1997 No. 11, pp. 49-53) and other references.

The optimization and setting of the rolling schedule involved in the above-mentioned public documents generally only consider factors such as the relative load uniformity of the motors of each stand, thickness control, and plate shape, and never consider the prevention and prevention of scratches. Scratches are produced on the surface of the strip steel and the surface of the roll during the manufacturing process, as shown in Figure 2. In the figure, there are scratches 6 on the strip 1 and the work roll 5. The generation of scratches not only affects the improvement of the rolling speed, but also limits the The output of the rolling mill is reduced, and the surface quality of the strip is affected, resulting in a decline in the product quality level or even being scrapped, causing huge economic losses to the enterprise.

Contents of the invention

The purpose of the present invention is to aim at the above-mentioned defects that exist in the traditional cold strip rolling process, and to provide an optimization method aimed at preventing scratches in the cold strip continuous rolling mill, which can prevent scratches from occurring in the cold continuous rolling process , in order to realize the line control of cold strip rolling.

In order to achieve the above object, the present invention adopts the following technical solutions,

The optimization method aimed at scratch prevention in the cold-strip continuous rolling mill includes the following steps:

a. Collect equipment parameters, strip characteristic parameters, rolling process parameters, and lubrication system parameters of the cold tandem mill;

b. The initial tension and reduction setting values of each stand of the given continuous rolling mill, as well as the initial step length and termination accuracy;

c. Obtain the value of the slip factor of each stand of the cold tandem rolling mill;

d. According to the value of slip factor ψ _i , obtain the value λ _i of the scratch comprehensive judgment index of each rack of the tandem cold rolling mill;

e. Obtain the objective function of rolling schedule optimization setting;

f. Judging whether the objective function satisfies the Powell's condition, if so, obtain the optimized tension and reduction value; if not, repeat the above steps c, d and e until the Powell's condition is met, and obtain the optimal tension and the setting value of the reduction amount;

g. Output the optimized tension and reduction value, and use the optimized tension and reduction setting value as a new rolling schedule to complete the online setting.

In the above-mentioned technical scheme of the present invention, the method first collects the equipment of the cold tandem rolling mill, the characteristics of the strip, the rolling process, and the parameters of the lubrication system, and provides the initial tension and the reduction setting value of each stand of the tandem rolling mill, As well as the initial step size and termination accuracy, the slip factor of each stand of the cold tandem rolling mill and the value of the comprehensive judgment index of the scratch of each stand are obtained respectively, and the objective function of the optimal setting of the rolling procedure is obtained; finally, the judgment Whether the objective function satisfies Powell's condition, the optimal tension and reduction setting values are obtained, and the online setting is completed. Therefore, the method of the present invention not only considers factors such as relative load uniformity, thickness control, and plate shape of each frame motor, but also introduces a new concept of scratch judgment, and considers each frame of the tandem cold rolling mill as a whole, and the scratches The on-line optimization setting of the rolling schedule is carried out with the aim of prevention and control of traces. This method can greatly increase the rolling speed and give full play to the potential of the rolling mill under the premise of ensuring product quality. It improves the surface quality of the strip and greatly reduces the The huge economic loss caused by the enterprise.

Description of drawings

Fig. 1 is the schematic diagram of cold-strip continuous rolling process;

Fig. 2 is the schematic diagram of the scratch defect produced in the continuous rolling production of cold strip steel;

Fig. 3 is a schematic flow chart of the optimization method of the present invention;

Detailed ways

In order to better understand the present invention, the mechanism that scratches are produced is analyzed below first,

As for the mechanism of the scratch defect, at first the site believed that the defect was a thermal slipping problem caused by the local rupture of the lubricating oil film, which was caused by insufficient lubrication. In fact, according to the relevant literature, it can be known that the thermal slip defect is not elongated and penetrating in appearance, but short and thick, so the defect is not a thermal slip at all in terms of morphology. In order to find out what happened, the site started with improving the lubrication system and increasing the flow rate of the emulsion. It was found that the relevant experiments had little effect on the scratch defect, which indicated that the defect was not caused by insufficient lubrication.

In this way, in order to find the real cause of the scratches, we first conducted a follow-up survey on the site, and found that the scratches concentrated on the last two stands of the tandem cold rolling mill, especially the last stand. On this basis, starting from the basic theory of rolling, the rolling process parameters of strips with scratch defects are analyzed, and it is found that all strips with scratch defects have two common characteristics: (1) the occurrence of scratch defects The relevant racks with scratch defects all have a slipping tendency; (2) The rolling speeds of the relevant racks with scratch defects are very high. Therefore, after further analysis and inference, it is believed that the main reason for the scratches is due to the high-speed slipping of the cold tandem mill during the rolling process. Specifically, it can be described as follows: scratches are mainly caused by slipping, but the slipping itself does not necessarily To cause scratches, it must be slipping at high speed to produce scratches. Both are indispensable, which is why the scratches are concentrated in the last two stands of the cold tandem mill, especially the last stand.

Through the above analysis, it can be known that there are two factors that determine whether a certain stand has scratch defects during the rolling process of the cold tandem mill: one is the probability of slipping and the degree of slipping, and the other is the rolling speed.

For the slippage problem in the tandem cold rolling process, a general parameter that characterizes the occurrence probability and degree of slippage—the slip factor ψ—can be introduced to reflect the probability and degree of slippage of a stand in the tandem cold rolling process. Its expression is:

$\mathrm{<span\; class="notranslate">\; \&psi;</span>}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; |</span>\frac{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

In the formula: γ-neutral angle;

α-Bite angle.

The physical meaning of the slip factor ψ is the relative position of the neutral plane in the deformation zone. The smaller the ψ, the closer the neutral plane is to the middle of the deformation zone, the smaller the probability of slipping and the lighter the degree of occurrence; and the larger the slip factor ψ, the farther the neutral plane is from the middle of the deformation zone, the lower the probability of slipping. The larger the degree of occurrence, the more unstable the rolling process will be.

In this way, in order to judge whether there will be scratches on the surface of the rolls and the strip in a certain stand during the tandem cold rolling process, and the extent of the scratches, and also to facilitate the horizontal comparison between the stands of the tandem cold rolling mill, a special proposal is made. A parameter λ representing the probability and degree of scratches is named as the comprehensive judgment index of scratches, and its expression is:

λ＝ψ· ^Vα (2)

In the formula: ψ-slip factor;

V-rolling speed;

  α-speed impact index is closely related to the characteristics of tandem cold rolling mills, generally α = 0.8□1.2, and Baosteel 1220 five-stand tandem cold rolling mill according to statistics and regression, α = 1.15.

Obviously, the smaller the scratch comprehensive judgment index λ, the smaller the probability of scratch occurrence and the lighter the occurrence degree; on the contrary, the larger the scratch comprehensive judgment index λ, the greater the probability of scratch occurrence and the lower the occurrence degree of scratches. serious.

It should be noted that, for a continuous cold rolling process, as long as scratches occur in any pass, it is considered that scratches have occurred in the rolling process. The value of the comprehensive judgment index λ for scratches is ultimately determined by the combined effect of the slip factor ψ and the rolling speed V. For the cold tandem mill, although the rolling speed is always higher and higher, that is, the rolling speed of the downstream stand is always greater than that of the upstream stand, the value of the slip factor of each stand is affected by the rolling speed. Influenced by the regulations (including the tension system and the compression procedure). That is to say, the value of the comprehensive judgment index λ of the scratches of each stand can be changed through the optimization of the rolling schedule, so that the value of the comprehensive judgment index λ of the scratches of each stand in the process of continuous cold rolling is evenly distributed, and neither overall The phenomenon that the λ value is too large, and the phenomenon that the overall λ value is small but the λ value of a certain rack is too large, so as to finally achieve the purpose of preventing scratches.

Please refer to shown in Fig. 3, in the cold-strip continuous rolling mill of the present invention, the optimization method with scratch prevention as the goal can be summarized as the following steps:

The first step is to collect equipment parameters, strip characteristic parameters, rolling process parameters, and lubrication system parameters of the tandem cold rolling mill;

In the second step, the initial tension and reduction setting values of each stand of the continuous rolling mill, as well as the initial step length and termination accuracy are given;

The third step is to obtain the value of the slip factor of each stand of the cold tandem mill;

In the fourth step, according to the value of the slip factor ψ _i , the value λ _i of the comprehensive judgment index of the scratches of each stand of the tandem cold rolling mill is obtained;

The fifth step is to obtain the objective function of rolling schedule optimization setting:

The sixth step is to judge whether the objective function satisfies the Powell condition, and if so, obtain the optimized tension and reduction values; if not, repeat the above steps 3, 4 and 5 until the Powell condition is satisfied, and obtain the optimal Optimum tension and reduction setting values;

The seventh step is to output the optimized tension and reduction value, and use the optimized tension and reduction setting value as a new rolling procedure to complete the online setting.

According to the rolling theory, for a continuous cold rolling process, for any stand, the following equation holds true:

${\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\sqrt{\frac{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}{{{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}^{<span\; class="notranslate">\; \&prime;</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}\sqrt{\frac{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}{{{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}^{<span\; class="notranslate">\; \&prime;</span>}}}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&mu;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; (</span>\sqrt{\frac{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}{{{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}^{<span\; class="notranslate">\; \&prime;</span>}}}<span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}{{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ]</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

${{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 16</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; v</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; \&pi;E</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$

In the formula: h _0i - the inlet thickness of the strip of the i-th rack;

h _1i - outlet thickness of the strip from the i-th rack;

R′ _i - the flattening radius of the work roll of the i-th rack;

R _i - the radius of the work roll of the i-th rack;

p _i - rolling pressure per unit width of stand i;

σ _1i , σ _0i - front and rear tension of the i-th rack;

μ _i - friction coefficient of the i-th frame;

E, v-Young's modulus and Poisson's ratio of the work roll.

In this way, the slip factor ψ _i of the i-th rack can be further expressed by the following formula:

${\mathrm{<span\; class="notranslate">\; \&psi;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{{\mathrm{<span\; class="notranslate">\; 4</span>}\mathrm{<span\; class="notranslate">\; \&mu;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; |</span>\sqrt{\frac{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}{{{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}^{<span\; class="notranslate">\; \&prime;</span>}}}<span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}{{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 7</span>}<span\; class="notranslate">\; )</span>$

At the same time, if emulsion lubrication is used in rolling, the friction coefficient is mainly determined by the thickness of the oil film in the rolling deformation zone ^[4] , which can be expressed by the following formula:

${\mathrm{<span\; class="notranslate">\; \&mu;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; \&mu;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&xi;</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&ap;</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; the\; ri</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&mu;</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="1"\; label="c"\; filenames="A20051011098000131.png"\; state="\{\{state\}\}">c</figure-callout></span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}{{\mathrm{<span\; class="notranslate">\; \&xi;</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}^{{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 8</span>}<span\; class="notranslate">\; )</span>$

In the formula: k _r - influence coefficient of roll roughness, the greater the roll roughness, the smaller k _r .

μ ₀ - dry friction coefficient under the same roll roughness:

c ₁ , c ₂ - fitting coefficients, which can be obtained from experiments;

ξ _0i - Equivalent thickness of oil film in rolling deformation zone, its expression is:

${\mathrm{<span\; class="notranslate">\; \&xi;</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 6</span>}\mathrm{<span\; class="notranslate">\; a\&eta;</span>}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{\sqrt{\frac{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}{{{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}^{<span\; class="notranslate">\; \&prime;</span>}}}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; a</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; K</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 9</span>}<span\; class="notranslate">\; )</span>$

In the formula: $\mathrm{\&eta;}={\mathrm{\&eta;}}_0{e}^{(\mathrm{ap}-{\mathrm{bT}}_m)}$

η ₀ - the room temperature viscosity of the lubricant at one atmospheric pressure;

a- viscosity pressure coefficient of lubricant;

b- viscosity temperature coefficient of lubricant;

_Tm - the average temperature of the lubricating oil film;

V _i - the rolling speed of the i-th stand;

K _i - Deformation resistance of the ith rack strip.

Similarly, according to the principle of equal flow per second, the rolling speed at the exit of each rack can be expressed by the following formula:

${\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; \&CenterDot;</span>{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="1"\; label="h"\; filenames="A20051011098000131.png"\; state="\{\{state\}\}">h</figure-callout></span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; no</span>}}}{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 10</span>}<span\; class="notranslate">\; )</span>$

In the formula: V _n - setting rolling speed, i.e. the rolling speed of the last stand;

h _1n - exit strip thickness of the last rolling mill stand.

If L _i is defined as the relative deformation of the i-th stand, it can be known from formulas (3)-(10) that under the premise that the process lubrication system and roll application process remain unchanged, the comprehensive judgment of the scratches of each stand of the cold tandem mill The value of the index λ _i is mainly determined by the distribution L _i of the reduction amount of each rack, and the tension system σ _0i , σ _1i and can be expressed by the following function:

λ _i =λ(L _i , σ _0i , σ _1i ) i=1, 2, . . . , n (11)

Therefore, the objective function of rolling schedule optimization can be simply defined as:

f(X)＝A·g ₁ (X)+(1-A)·g ₂ (X) (12)

In the formula:

${\mathrm{<span\; class="notranslate">\; g</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\sqrt{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 13</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; g</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 14</span>}<span\; class="notranslate">\; )</span>$

$\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; no</span>}}\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 15</span>}<span\; class="notranslate">\; )</span>$

X={L _i , σ _0i , σ _1i , i=1, 2, 3, . . . , n) (16)

A-weighting factor

n - the number of stands of the continuous rolling mill.

It should be noted that g ₁ (X) in formula (12) represents the uniformity of the λ value of each rack, and g ₂ (X) represents the overall value of λ of each rack. The two are indispensable, because the optimization result neither expects the phenomenon that the overall λ value is too large, nor does it want the phenomenon that the overall λ value is small but the λ value of a certain rack is too large.

In this way, the entire optimization process can be described as looking for a suitable reduction distribution standard and tension system X={L _i , σ _0i , σ _1i =1, 2, 3,...n}, so that f(X) is the smallest, using Powell The (powell) optimization method yields an optimized result.

Example

(1) Collect the required equipment and strip raw data

Equipment parameters of tandem cold rolling mill: work roll diameter D _w1 = 550/500mm; D _w2 = 533.4 (~535)/470mm; D _w3 = 533.4 (~535)/470mm; D _w4 = 533.4 (~535)/470mm; D _w5 ＝533.4(～535)/470mm

Raw roughness of work roll: Ra ₁ =0.60μm; Ra ₂ =0.58μm; Ra ₃ =0.56μm; Ra ₄ =0.43μm; Ra ₅ =0.38μm

Rolling kilometers of work rolls: L _w1 = 80Km; L _w2 = 80Km; L _w3 = 80Km; L _w4 = 80Km; L _w5 = 80Km

Product variety specification range: strip width 1000mm, entrance thickness 1.8mm, exit thickness 0.195mm, steel type is MRT3

(2) Selection of rolling process parameters

The exit rolling speed of the last stand of the cold tandem mill is set at 1600m/min

(3) The room temperature viscosity of the lubricant at one atmospheric pressure is 80, the viscosity pressure coefficient of the lubricant is 50, and the viscosity temperature coefficient of the lubricant is 0.2

(4) Optimization of rolling schedule

1) given each rack initial tension and the setting value X0=[0.2, 0.2, 0.2, 0.2, 0.2, 176, 176, 176, 176, 176, 176, 176, 176, 176, 176], Define the convergence precision as 0.001;

2) Find the value of the slip factor ψ _i =[0.1, 0.21, 0.3, 0.32, 0.4] of each stand of the cold tandem mill;

3), calculate the value λ _i =[6.2, 7.9, 8.4, 9.5, 18.2] of the scratch comprehensive judgment index value of each stand of the cold tandem rolling mill;

4), obtain the objective function f(X)=4.3 of rolling schedule optimization setting;

5) Judging whether Powell's conditions are met, performing repeated iterative calculations, and obtaining the optimal tension and reduction setting values,

The parameter results of each rack are shown in Table 1.

Table 1 Optimization results of rolling schedule for typical products

Optimization Rack   Thickness H/mm Tension T/Mpa Scratch comprehensive judgment index λ before optimization 1.8 49 1 1.26 146.412 3.86 2 0.741869   164.052 5.72 3 0.461207   164.052 6.93 4 0.3 165.816 10.52 5 0.195 68.6 15.31 Optimized 1.8 49 1 1.1952 161.28 5.81 2 0.68225 161.28 6.72 3 0.432461 161.28 7.48 4 0.288987 176 8.22 5 0.195 68.6 9.10

It can be seen from the table that after optimization, the peak value of the scratch judgment index is much lower than that before optimization. For example, before optimization, the peak values of rack 4 and rack 5 are 10.52 and 15.31; , The peak value of rack 5 is only 8.22, 9.10.

As can be seen from the above description, the method of the present invention can indeed greatly improve the rolling speed under the premise of ensuring product quality, reduce the probability of scratches on the strip during the rolling process, and better ensure the surface quality of the strip.

Claims (8)

1. An optimization method targeting scratch prevention in a cold-strip continuous rolling mill, It is characterized in that the method comprises the following steps: a. Collect equipment parameters, strip characteristic parameters, rolling process parameters, and lubrication system parameters of the cold tandem mill; b. The initial tension and reduction setting values of each stand of the given continuous rolling mill, as well as the initial step length and termination accuracy; c. Obtain the value of the slip factor of each stand of the cold tandem rolling mill; d. According to the value of slip factor ψ _i , obtain the value λ _i of the scratch comprehensive judgment index of each rack of the tandem cold rolling mill; e. Obtain the objective function of rolling schedule optimization setting; f. Judging whether the objective function satisfies the Powell's condition, if so, obtain the optimized tension and reduction value; if not, repeat the above steps c, d and e until the Powell's condition is met, and obtain the optimal tension and the setting value of the reduction amount; g. Output the optimized tension and reduction value, and use the optimized tension and reduction setting value as a new rolling schedule to complete the online setting. 2. The optimization method aiming at scratch prevention in the cold-strip continuous rolling mill as claimed in claim 1, It is characterized by: Described equipment parameter comprises the diameter of each frame work roll, the roughness of each frame work roll, the rolling kilometer of each frame work roll, the Young's modulus and Poisson's ratio of each frame work roll; 3. The optimization method aiming at scratch prevention in the cold-strip continuous rolling mill as claimed in claim 1, It is characterized by: The characteristic parameters of the steel strip include the width of the steel strip, the thickness of the steel strip at the entrance of the first rack, the initial yield strength of the steel strip and the work hardening coefficient of the steel strip. 4. The optimization method aiming at scratch prevention in the cold-strip continuous rolling mill as claimed in claim 1, It is characterized by: The rolling process parameters include the exit rolling speed of the last stand of the tandem cold rolling mill. 5. The optimization method aiming at scratch prevention in the cold-strip continuous rolling mill as claimed in claim 1, It is characterized by: The process lubrication system parameters refer to the room temperature viscosity of the lubricant at one atmospheric pressure, the viscosity-pressure coefficient of the lubricant, and the viscosity-temperature coefficient of the lubricant. 6. The optimization method aiming at scratch prevention in the cold-strip continuous rolling mill as claimed in claim 1, It is characterized by: The slip factor in the step c is defined as, $\mathrm{<span\; class="notranslate">\; \&psi;</span>}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; |</span>\frac{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span>$ In the formula, γ—neutral angle α—bite angle. 7. The optimization method aiming at scratch prevention in the cold-strip continuous rolling mill as claimed in claim 1, It is characterized by: In the step d, the scratch comprehensive judgment index is defined as, λ=ψ V ^α In the formula, V—rolling speed; α—speed influence index, which is closely related to the characteristics of the cold rolling mill, generally α=0.8～1.2. 8. The optimization method aiming at scratch prevention in the cold-strip continuous rolling mill as claimed in claim 1, characterized in that: In the described step e, the rolling schedule optimization objective function is defined as: f(X)＝A·g ₁ (X)+(1-A)·g ₂ (X) In the formula: ${\mathrm{<span\; class="notranslate">\; g</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\sqrt{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; -</span>}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}$ ${\mathrm{<span\; class="notranslate">\; g</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\stackrel{<span\; class="notranslate">\; -</span>}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}$ $\stackrel{<span\; class="notranslate">\; -</span>}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; no</span>}}\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}$ X={L _i , σ _0i , σ _1i , i=1, 2, 3,...n} A—weighting coefficient, in general, take A=0.35 n—the number of stands of the continuous rolling mill.

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