Target strip shape dynamic feedback adjustment method

Abstract

The invention discloses a target plate shape dynamic feedback adjustment method, which comprises the following steps of: firstly, establishing a target plate shape classification database, and forming a rolling mill target plate shape curve of classified strip steel; the coefficient a1 of the target strip shape curve is subjected to iterative calculation according to the control period, a1 in the period is equal to a1 + delta a1 in the last period, delta a1 is a deviation correction coefficient, and a new target strip shape curve is formed and issued to a rolling mill strip shape control system for production; and then the deviation condition of the period is obtained according to the through plate stability data of the batch of classified strip steel produced by the subsequent unit, the deviation correction coefficient delta a1 of the classified strip steel is calculated, the step starting from the target strip shape curve coefficient a1 is repeated and iterated, and dynamic feedback adjustment of the target strip shape is completed. The target plate shape of the rolling mill is changed from static setting to dynamic setting and can be dynamically adjusted in a targeted manner according to the actual plate passing condition of a subsequent unit, so that the plate passing stability is improved; and target plate shape adjustment work is carried out in a classified manner, so that the efficiency is improved, and the safety and the feasibility are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of strip cold rolling technology, in particular to a method for dynamic feedback adjustment of target plate shape. BACKGROUND

[0002] In a plate shape control system of a cold rolling strip, system measurement errors and plate shape requirements of the next process on the present process can be included in the target plate shape, and its application reflects the progress of plate shape measurement technology and plate shape control process, and has extremely important significance for plate shape control.

[0003] The plate shape control flow of a strip cold rolling process is shown in Figure 2 .

[0004] The measured plate shape curve obtained by the plate shape roller is subtracted from the pre-set target curve to obtain a plate shape deviation curve, and the automatic plate shape control system or the main operator identifies plate shape defects according to the plate shape deviation and adjusts the plate shape control mechanism accordingly, and the ultimate goal is to control the plate shape to meet the requirements of the target curve.

[0005] The setting of the target plate shape generally has the following methods: Directly issued from the L2 system (process control automation) in the three-electricity control system to the L1 system (basic automation); Directly set by the L1 system; Part of the parameters are issued by L2 and part of the parameters are set by L1; Set by a special plate shape computer. In addition, the operator can also set the target plate shape.

[0006] The mathematical expression F(x) of the target plate shape model is generally composed of a 4th order or 6th order polynomial, that is: (1) ; (2) ; The formula (1) is the target plate shape expressed by a 4th order polynomial, and the formula (2) is the plate shape expressed by a 6th order polynomial. The target curve is generally expressed by the formula (1), and if the target plate shape wants to express the local plate shape of the edge, the target plate shape (2) is required. Since the 6th order polynomial contains the 4th order polynomial, the following describes the target curve by the 6th order polynomial.

[0007] In general, a 6th order curve can express a relatively complex plate shape curve, in which the 1st order term expresses the overall inclination of the plate shape, the 2nd order term expresses the overall convexity (i.e. large edge wave or large center wave), the 4th order term expresses the plate shape at 1 / 4 of the strip (1 / 4 wave or 1 / 4 tension), and the 6th order term expresses the local plate shape of the edge of the strip (micro edge wave or micro center wave). A typical target plate shape curve is shown in Figure 3The middle wave, the edge wave, the edge-middle composite wave and the 1 / 4 wave are shown respectively.

[0008] wherein, x is the normalized width direction of the horizontal coordinate (-1, 1); x=X / B, X is the width direction of the coordinate, B is the strip width; a0-a6 is each factor coefficient in the target plate shape curve polynomial function; g is the gain amplification factor of the target plate shape; and (1) and (2) should satisfy (3); The above (1) and (2) can be called the basic target plate shape curve, and the actual target plate shape curve is formed by superimposing various compensation curves on the basic target plate shape curve, and these compensation curves are also system measurement errors. The compensation curve is mainly to eliminate the influence of the plate shape roll surface axial temperature distribution, the strip transverse temperature distribution, the plate shape roll deflection deformation, the plate shape roll or coiler geometric installation error, the strip coil profile shape change and other factors on the plate shape measurement.

[0009] In the strip rolling process, due to the existence of large deformation and the possible non-uniformity of cooling, the strip has a large temperature difference in the width, which affects the accuracy of the plate shape roll measurement and will affect the final plate shape control effect. In order to eliminate the influence of the transverse temperature difference of the strip on the plate shape after rolling, according to the temperature field distribution curve of the strip width direction obtained by the temperature measurement device, the method of setting the temperature compensation curve is used to compensate the measurement error. Foreign patent US2010236310 designs a method of using a thermal imager to monitor the flatness of the edge of the strip. This method focuses on measuring the temperature field distribution and temperature change of the edge of the strip and giving the corresponding control to improve the flatness of the edge of the strip. Its core principle is also to consider that the outermost part of the edge of the strip has no plate shape measurement signal, and the temperature gradient of the edge of the strip is measured for compensation. Both are control methods for the plate shape of the edge of the strip. The technical principles of the two methods are not consistent, and the method provided by the present patent does not need to add an additional temperature measurement device.

[0010] The domestic patent CN104001730A designs a target plate shape dynamic setting method, which is used in the rolling force fluctuation stage of the plate strip rolling process. According to the edge target plate shape compensation formula related to the process parameters such as rolling force, rolling speed, coverage rate and outlet thickness, the target plate shape is dynamically set and used in the automatic plate shape control system to realize the automatic plate shape control in the rolling force fluctuation stage or for manual control by the operator. The technical principles of the two methods are not consistent.

[0011] In the cold rolling process, the target plate shape is generally not adjusted after being determined. As described above, the prior art compensates and corrects the target plate shape in real time according to the changes of process parameters such as rolling force fluctuation and temperature fluctuation during the rolling process. In fact, there is still a problem that the target plate shape determined in the early stage is gradually unsuitable for continuous use due to the changes in the state of production process equipment, and needs to be automatically adjusted dynamically according to user requirements in a timely manner. The dynamic adjustment is a long-term process. Through the analysis of the search of domestic and foreign public literature and patents, there is still no effective measure to deal with such problems. SUMMARY

[0012] The purpose of the present application is to overcome the shortcomings of the prior art, and to provide a target plate shape dynamic feedback adjustment method.

[0013] In the actual production process of strip cold rolling, the target plate shape can be dynamically adjusted to improve the stability of the plate passing through the subsequent unit. The present application is used for cold rolling mills and corresponding subsequent continuous annealing and hot plating units. The cold rolling mill unit is linked with the subsequent process units (including continuous annealing and hot plating units). According to the plate passing situation, the recent strip deviation overall situation is calculated and obtained by the subsequent process, and is automatically fed back to the rolling mill process. The rolling mill process automatically adjusts the target plate shape according to the deviation situation. The next batch of strip after adjustment continues to pass through the subsequent unit and feeds back the deviation situation and corrects the target plate shape, forming a continuous dynamic adjustment to improve the stability of the plate passing.

[0014] In order to achieve the above purpose, the technical scheme adopted by the present application is: A target plate shape dynamic feedback adjustment method, comprising the following steps: Step 1: Establish a target plate shape classification database to form a rolling mill target plate shape curve of classified strip; Each coil of strip is classified according to the cold rolling production unit, steel grade, strength level, inlet thickness, outlet thickness, outlet width and subsequent unit, and is numbered by numbers; different classification numbers correspond to different target plate shapes; the target plate shape curve of the classified strip is represented by a polynomial function, and each factor coefficient a0-a6; Step 2: The coefficient a1 of the target plate shape curve is iteratively calculated according to the control period, and the coefficient a1 of the present period is a1 of the last period+Δa1, wherein Δa1 is a deviation correction coefficient, and a new target plate shape curve is formed; Step 3: The new target plate shape curve is issued to the rolling mill plate shape control system and is produced; Step 4: The classified strip of this batch is produced in the subsequent unit, and the plate passing stability data of each coil of classified strip is collected; The classification strip steel is passed through the rear unit, the travel percentage data of the deviation rectifying roller installed at the inlet of the heating furnace and the actual out-roller data generated by the strip steel deviation after the deviation rectifying roller reaches 100% travel are counted, and the passing condition is described according to the counting data; Step 5: The overall passing condition of the classification strip steel in the current period is counted according to the passing condition of each volume of the classification strip steel, and the deviation condition of the classification strip steel in the current period is obtained; Step 6: The deviation correction coefficient Δa1 of the classification strip steel is calculated, and the positive and negative values of the deviation correction coefficient Δa1 are separately set according to the classification condition, the strip steel deviates to the operation side in the rear unit, and the direction corresponding to the rolling mill is the transmission side, so that Δa1 is less than 0; the strip steel deviates to the operation side in the rear unit, and the direction corresponding to the rolling mill is the operation side, so that Δa1 is greater than 0; Steps 2 to 6 are repeatedly executed to complete the dynamic feedback adjustment of the target plate shape.

[0015] Further, the step 4 passing condition description is described by quantitative calculation or according to the deviation severity classification.

[0016] Further, the statistical period of the step 5 is one day or one week.

[0017] Further, the rear unit includes a continuous annealing unit and a hot dipping unit.

[0018] The beneficial effects of the present application are that the target plate shape of the rolling mill is changed from static setting to dynamic setting, the actual passing condition of the rear unit can be dynamically adjusted, the passing stability is improved, the classification statistics work is carried out, the passing condition of the strip steel of different steel grades and different rear units is classified and counted, the target plate shape adjustment work is classified, the efficiency is improved, and the safety and implementability are improved. The present application can be applied to cold rolling mills and rear process units including continuous annealing and hot dipping units, and has wide application prospect and economic benefit. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is the plate shape control flowchart of the present application; Figure 2 is the conventional plate shape control flowchart of the embodiment of the present application; Figure 3 is the schematic diagram of several typical target plate shape curves of the embodiment of the present application; Figure 4 is the schematic diagram of the target plate shape curve set by the classification number 02070605040402 of the embodiment of the present application; Figure 5 is the schematic diagram of the target plate shape curve set by the classification number 02070605040401 of the embodiment of the present application; Figure 6is the target plate shape change schematic diagram of the embodiment of the present application classified as 02070605040402; Figure 7 is the target plate shape change schematic diagram of the embodiment of the present application classified as 02070605040401. DETAILED DESCRIPTION

[0020] The present application will be further described in detail below in combination with embodiments, such as Figure 1 shown, the steps are as follows: (1) Establish a target plate shape classification database to form a rolling mill target plate shape curve of classified strip steel First, according to the cold rolling production unit, steel grade, strength level, inlet thickness, outlet thickness, outlet width, and subsequent (continuous annealing or hot dipping) production unit, the classification is as shown in Table 1.

[0021] Table 1: Target plate shape classification definition example (classification method is optimized according to actual situation) , Suppose a coil of strip steel is produced by cold rolling unit 2, the steel grade is DP steel, the tensile strength is 590 MPa, the rolling mill inlet thickness is 3.5 mm, the outlet thickness is 1.2 mm, the outlet width is 1150 mm, and the subsequent unit is No. 2 continuous annealing. The classification number of the coil of strip steel is 02070605040402, as shown in the last row of Table 1.

[0022] According to the already established classification number, define the target plate shape for each classification number, and express it in accordance with a 6th order polynomial, as shown in Table 2 below.

[0023] Table 2: Definition of target plate shape curve of different classifications (optimized according to actual situation) .

[0024] (2) The coefficient a1 of the target plate shape curve is iteratively calculated according to the control period, and the coefficient a1 of this period is a1 of the last period + Δa1; a new target plate shape curve is formed.

[0025] The initial value of Δa1 is zero, and the feedback value of each control period is obtained according to the subsequent steps.

[0026] The coefficients of each term of the target curve set for classification number 02070605040402 are shown in the first row of Table 2; the target curve is as shown in Figure 4 .

[0027] The coefficients of each term of the target curve set for classification number 02070605040401 are shown in the second row of Table 2; the target curve is as shown in Figure 5 .

[0028] (3) The new target strip shape curve is sent to the rolling mill strip shape control system and production is carried out.

[0029] (4) The batch of hard-rolled coils is produced in the subsequent unit, and the strip passing stability data of each coil is collected.

[0030] The strip passing stability data of each coil in the subsequent unit is collected, the travel percentage data of the correction roller of the correction device installed at the inlet of the heating furnace and the actual out-of-coil data generated by the strip deviation after the correction roller reaches 100% travel are taken as the deviation statistical data, and the severity of the deviation is defined and judged.

[0031] As shown in Table 3, assuming that the control period is calculated by day, on 20250101, batch 2 of the continuous annealing line produced DP steel products produced by No. 2 cold rolling mill (the tensile limit of the products in this batch is 590 MPa, the rolling mill inlet thickness is 3.5 mm, the outlet is 1.2 mm, the outlet width is 1150 mm, and all are a classification number 02070605040402) a total of 10 coils. Each coil of strip steel is judged for deviation.

[0032] Table 3 shows only data for classification number 02070605040402, and all strip steels collect strip passing data and can be filtered and summarized according to classification number to analyze strip passing conditions.

[0033] Table 3 shows the classification strip deviation statistical example , Deviation severity definition (can be adjusted according to actual situation or defined separately for each classification): Normal: Maximum travel percentage of correction roller ≤80%; Mild deviation: Maximum travel percentage of correction roller > 80% and ≤100%; Severe deviation: Maximum travel percentage of correction roller ≥100% and strip out-of-coil width ≥10 mm.

[0034] (5) The overall strip passing conditions of the classification strip steels in the current control period are summarized to obtain the deviation conditions of the classification strip steels in the current control period.

[0035] The strip passing conditions of each coil of strip steel under a certain classification number in the current control period are summarized to obtain the overall strip passing conditions of the classification number, and the statistical method is shown in the following example, which can be modified according to the actual situation: Normal: Deviation and severe deviation coil ratio <10%; Batch mild deviation: Deviation and severe deviation coil ratio ≥10%; Batch severe deviation: Severe deviation coil ratio ≥10%.

[0036] The classification number 02070605040402 corresponds to 10 volumes of strip steel, and a total of 5 volumes of strip steel have slight and serious deviation, 2 volumes have serious deviation, and the deviation direction is the operation side of No. 2 continuous annealing. It is judged that the deviation of the classification number strip steel in this period is: batch serious deviation to the operation side.

[0037] (6) Calculate the deviation correction coefficient Δa1 of the classification strip steel Δa1 deviation correction coefficient calculation method (can be adjusted or defined separately for each classification according to actual situation): Suppose that the classification number 02070605040402 strip steel corresponds to the drive side of the rolling mill on the operation side of the continuous annealing, so as to reduce the deviation of the continuous annealing to the operation side, the operation side of the rolling mill needs to be waved, that is, the operation side is loose and the drive side is tight.

[0038] Suppose that the classification number 02070605040401 strip steel corresponds to the operation side of the rolling mill on the operation side of the continuous annealing, and suppose that the classification number strip steel in this period also has: batch serious deviation to the operation side. Therefore, in order to reduce the deviation of the continuous annealing to the operation side, the drive side of the rolling mill needs to be waved, that is, the drive side is loose and the operation side is tight.

[0039] According to the defined Δa1 deviation correction coefficient of the classification strip steel, as shown in Table 4.

[0040] The classification number 02070605040402, Δa1 is -1; The classification number 02070605040401, Δa1 is 1.

[0041] Table 4: Δa1 deviation correction coefficient of classification strip steel .

[0042] (7) After the deviation correction coefficient Δa1 of this period is obtained, the coefficient a1 of the target plate shape curve is iteratively calculated according to the control period, and this period a1 = last period a1 + Δa1; form a new target plate shape curve and issue for execution.

[0043] The classification number 02070605040402 this period a1 = last period a1 + Δa1 = 0-1 =-1; the target plate shape changes as shown in Figure 6 , the operation side is loose and the drive side is tight.

[0044] The classification number 02070605040401 this period a1 = last period a1 + Δa1 = 0+1 =1; the target plate shape changes as shown in Figure 7 , the operation side is tight and the drive side is loose.

[0045] Considering the production stability of rolling process and other factors, a1 is set to an upper limit, such as ±5.

[0046] The above is only used to illustrate the technical solutions of the present application, and the simple modification or equivalent replacement of the technical solutions of the present application by those skilled in the art does not deviate from the essence and scope of the technical solutions of the present application.

Claims

1. A method of target plate shape dynamic feedback adjustment, characterized by: The method comprises the following steps: Step 1: Establishing a target plate shape classification database to form a rolling mill target plate shape curve of classified strip steel; Each roll of strip steel is classified according to a cold rolling production unit, a steel type, a strength level, an inlet thickness, an outlet thickness, an outlet width and a subsequent unit, and is numbered by a number; different classification numbers correspond to different target plate shapes; a classified strip steel target plate shape curve is expressed by a polynomial function, and each factor coefficient a0-a6; Step 2: The coefficient a1 of the target plate shape curve is iteratively calculated according to a control period, and the current period a1 = last period a1 + Δa1, wherein Δa1 is a deviation correction coefficient, and a new target plate shape curve is formed; Step 3: The new target plate shape curve is issued to a rolling mill plate shape control system and is produced; Step 4: The classified strip steel in the batch is produced in a subsequent unit, and pass stability data of each roll of classified strip steel is collected; When the classified strip steel passes through the subsequent unit, the travel percentage data of a deviation correction roller installed at the inlet of a heating furnace and actual out-roller data of strip steel deviation generated after the deviation correction roller reaches 100% travel are counted, and pass condition description is performed according to the counted data; Step 5: The overall pass condition of the classified strip steel in the current period is counted according to the pass condition of each roll of classified strip steel, and the deviation condition of the classified strip steel in the current period is obtained; Step 6: The deviation correction coefficient Δa1 of the classified strip steel is calculated, and the positive and negative values of the deviation correction coefficient Δa1 are separately set according to the classification condition; if the strip steel deviates to the operation side in the subsequent unit, the corresponding direction of the rolling mill is the transmission side, and then Δa1 is less than 0; if the strip steel deviates to the operation side in the subsequent unit, the corresponding direction of the rolling mill is the operation side, and then Δa1 is greater than 0; Steps 2-6 are repeatedly executed to complete dynamic feedback adjustment of the target plate shape.

2. The method of target plate shape dynamic feedback adjustment of claim 1, wherein: The pass condition description in step 4 is described by quantitative calculation or according to the severity of deviation.

3. The method of target plate shape dynamic feedback adjustment of claim 1, wherein: The statistical period in step 5 is one day or one week.

4. The method of target plate shape dynamic feedback adjustment of claim 1, wherein: The subsequent unit comprises a continuous annealing unit and a hot-dip unit.

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