CN117787066B - Method for predicting roll shape of working roll based on thermal convexity of CVC rolling mill - Google Patents
Method for predicting roll shape of working roll based on thermal convexity of CVC rolling mill Download PDFInfo
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Abstract
The invention discloses a method for predicting a working roll shape based on thermal convexity of a CVC rolling mill, which comprises the following steps: collecting strip steel parameters, rolling process parameters, cooling water parameters, CVC rolling mill parameters and working roll temperature data; establishing a three-dimensional thermal convexity finite element model of the CVC working roll according to the parameters of the CVC rolling mill; calculating the convective heat transfer coefficient of the working roll, strip steel, air and cooling water in the rolling process, applying the convective heat transfer coefficient to a three-dimensional thermal convexity finite element model, and carrying out a finite element simulation experiment; adjusting the temperature boundary condition of the three-dimensional thermal convexity finite element model to enable the temperature data curve of the working roll in the finite element simulation experiment to be consistent with the temperature data curve of the working roll actually measured on site; and carrying out finite element simulation experiments based on the adjusted three-dimensional thermal convexity finite element model, extracting transverse distribution data of the thermal expansion quantity of the surface of the working roll at different time nodes, and fitting with an initial CVC working roll shape curve to obtain a new working roll shape curve.
Description
Technical Field
The invention belongs to the technical field of hot rolling, and relates to a method for predicting a roll shape of a working roll based on thermal convexity of a CVC rolling mill.
Background
At present, a main plate shape control means is realized by axially traversing the working roll of a rolling mill to obtain the convexity of a required roll gap in the process of hot rolling strip steel, a representative rolling mill is a CVC rolling mill, and the CVC rolling mill can achieve the purpose of controlling the flatness and convexity of the strip steel through axially traversing the working roll. The shape of the working roll is the most direct and active factor influencing the strip steel shape control, so the original shape of the working roll of the axially-transversely-moving variable-convexity rolling mill directly influences the shape control capability and effect of the working roll. Taking a working roll of a CVC rolling mill as an example, at present, the working roll of the CVC rolling mill is generally designed by adopting a 3-time curve, and the roll shape of the working roll is directly influenced by different 3-time curve designs, so that the control effect of the CVC rolling mill on the strip steel plate shape is influenced, and a specific method for optimizing and designing the roll shape curve of the working roll is provided by combining on-site process conditions.
In hot rolled strip production, the hot roll shape of the work rolls is one of the important factors affecting the strip shape. The thermal convexity of the working roll must be accurately calculated and predicted to improve the quality of the strip steel. In the hot rolling process, the temperature of the strip steel is continuously input into the working roll, so that the temperature of the middle part and the edge part of the working roll are uneven, the expansion amount of the middle part is larger than that of the edge part, the roll shape curve is changed, the roll gap shape is changed, the thickness of the strip steel is also changed along the transverse distribution, and the plate shape is influenced.
Many related researches have been made by domestic researchers for the problem of hot roll shape existing in the hot rolling production process. The invention relates to a method for analyzing the influence of hot convexity on a plate shape in a cold continuous rolling process, which is disclosed in Chinese patent application No. CN202210448408.X, and the method combines a hot convexity numerical simulation model with a rolling process numerical simulation model, can intuitively reflect the change condition of the hot convexity of a working roller, can influence the plate shape due to the thermal expansion of the working roller, and can further obtain the plate shape condition under different hot convexities. The Chinese journal 'hot continuous rolling mill working roll hot roll shape simulation research' adopts a difference method to establish a two-dimensional transient temperature field of a roll and a forecast model of the hot roll shape, researches the change process of the hot roll shape of the working roll in the rolling process, further analyzes the influence of the width of a rolled piece, a roll shifting system and the like on the hot roll shape, and provides a guiding basis for actual production and theoretical research. The journal paper 1700 hot continuous rolling mill roller temperature field and hot convexity research calculates the working roller temperature field and hot convexity of a certain rolling period by establishing a difference model of the working roller temperature field of a tropical steel rolling mill. For a CVC roll, the roll surface temperature distribution and thermal convexity are affected by roll lateral movement. In the whole rolling process, the thermal deformation change of the roller surface is closely related to the rolling rhythm. The Chinese journal paper "CVC roller thermal convexity model research" researches and analyzes a roller thermal convexity model of a CVC rolling mill, and the problems of the existing model are found by comparing the roller thermal convexity model with a theoretical calculation value of a two-dimensional roller thermal convexity model in a strip shape control system, so that the thermal convexity model is improved on the basis, the calculation precision of the roller thermal convexity model is improved, and the strip steel strip shape control precision is improved.
The deficiencies of the above research mainly have three aspects: (1) The thermal convexity model of the traditional working roll is set as a two-dimensional ideal model, but a complex heat transfer process exists in the actual rolling process, and if the ideal two-dimensional ideal model is used in the simulation process, the ideal two-dimensional ideal model is not matched with the actual rolling process. The two-dimensional ideal model ignores temperature transmission and thermal expansion in the circumferential direction of the roller, and has larger error in the actual production process, so that the thermal convexity simulation model has certain limitation; (2) The differential model and the mathematical model do not consider the heat conduction in the axial direction of the roll shaft, and the calculation process is complicated. (3) The heat transfer condition of the working rolls in the hot rolling process is more complex than that of the cold rolling process, the change of the hot roll shape is more severe, and some schemes only consider the problem of predicting the cold roll shape and do not consider the influence of the hot roll shape, so that the method is not suitable for being applied to the hot rolling.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method for predicting the roll shape of a working roll based on the thermal convexity of a CVC rolling mill.
The invention provides a method for predicting a working roll shape based on thermal convexity of a CVC rolling mill, which comprises the following steps:
Step 1: collecting the strip steel parameters, rolling process parameters, cooling water parameters, CVC rolling mill parameters and working roll temperature data which are actually measured on site;
Step 2: establishing a three-dimensional thermal convexity finite element model of the CVC working roll according to the CVC rolling mill parameters acquired in the step 1;
step 3: calculating convection heat exchange coefficients of a working roll and strip steel, working roll and air and working roll and cooling water in the rolling process according to the strip steel parameters, rolling process parameters and cooling water parameters acquired in the step 1, and applying the convection heat exchange coefficients to a three-dimensional thermal convexity finite element model to perform a finite element simulation experiment;
Step 4: adjusting the temperature boundary condition of the three-dimensional thermal convexity finite element model to enable the temperature data curve of the working roll in the finite element simulation experiment to be consistent with the temperature data curve of the working roll actually measured on site;
Step 5: carrying out a finite element simulation experiment based on the adjusted three-dimensional thermal convexity finite element model, extracting transverse distribution data of the thermal expansion amount of the surface of the working roll at different time points in the finite element simulation experiment, and fitting the transverse distribution data with an initial CVC working roll shape curve to obtain a new working roll shape curve;
step 6: and (5) analyzing the influence of the thermal convexity change of the working rolls at different time nodes on the roller shape curve of the CVC working rolls according to the new roller shape curve of the working rolls obtained in the step (5).
Further, the step 1 specifically includes: obtaining strip steel parameters, rolling process parameters, cooling water parameters, CVC rolling mill parameters and working roll temperature field data from a hot rolling production line;
The strip steel parameters comprise: steel type, width, thickness and temperature of the strip steel;
the rolling process parameters comprise: rolling speed, friction coefficient, rolling gap time and lateral movement of the working rolls;
the cooling water parameters include: cooling water temperature, cooling water flow rate and cooling water injection pressure;
the CVC rolling mill parameters include: work roll diameter, work roll body length, work roll density, work roll elastic modulus, work roll poisson ratio, work roll thermal expansion coefficient, work roll specific heat capacity, work roll heat conductivity coefficient and initial CVC work roll shape curve;
The temperature field data of the working roller is that a reflective adhesive tape is stuck on the working roller after the working roller is arranged in the axial direction, and a temperature field cloud picture of the working roller is shot by a thermal imager.
Further, the initial CVC work roll shape curve equation is a cubic polynomial function, specifically:
；
；
Wherein R U (x) is an upper roll shape function of the working roll, R L (x) is a lower roll shape function of the working roll, and x is a transverse coordinate of the roll; r 0 is the nominal radius of the working roller, and the unit is mm; a 1、a2 and a 3 are roll-shaped coefficients to be determined; l REF is the design length of the working roll, in mm.
Further, the step 2 specifically includes:
step 2.1: establishing modeling dimension parameters of a three-dimensional thermal convexity finite element model of the CVC working roll according to the CVC rolling mill parameters acquired in the step 1;
step 2.2: establishing material parameters of a three-dimensional thermal convexity finite element model of the CVC working roll according to the CVC rolling mill parameters acquired in the step 1;
step 2.3: establishing a three-dimensional thermal convexity finite element model of the CVC working roll, and modeling by taking 1/30 of the circumferential direction of the working roll for shortening the calculation time;
step 2.4: simplifying the boundary conditions.
Further, the step 2.3 specifically includes: selecting a SOLID164 eight-node hexahedral unit for modeling, defining thermal physical parameters of a working roll material, and drawing a roll shape curve of the working roll by adopting a higher B spline curve based on the CVC rolling mill parameters acquired in the step 1; grid refinement is carried out on the surface of the working roll, so that the calculation accuracy is ensured, the calculation time is gradually shortened from outside to inside, and the surface grid size is 10mm in the length direction, 2mm in the width direction and 3mm in the depth direction.
Further, the specific assumption and simplification content of the step 2.4 is:
(1) In the rolling process, the temperature of any node periodically changes, and the boundary condition reversely rotates to simulate the rotation of the working roll under the assumption that the working roll does not rotate;
(2) The temperature fields of the upper working roller and the lower working roller are considered to be consistent, and the working roller is positioned at a 0-leap roller position;
(3) The heat exchange between the working roller and the strip steel, between the working roller and the cooling water and between the working roller and the air is equivalent to convection heat exchange;
(4) Neglecting frictional heating between the work roll and the backup roll;
(5) According to the contact arc length between the strip steel and the working roller, the working roller is divided into 30 equal parts along the axial direction, each part is 12 degrees, and the strip steel is in contact with the working roller.
Further, the step3 specifically includes:
step 3.1: the contact heat transfer and deformation heat between the working roller and the strip steel in the rolling process and the radiation heat exchange process between the working roller and the air are equivalent to convection heat exchange;
step 3.2: determining the convective heat transfer coefficients of the strip steel, the working roller, the cooling water and the air according to a convective heat transfer formula and an empirical value;
Step 3.3: generating a circulation curve of time-heat exchange coefficient through the K file by the convection heat exchange coefficient calculated in the step 3.2;
Step 3.4: and creating an SEGM on the surface of the three-dimensional thermal convexity finite element model of the CVC working roll, and applying a time-heat exchange coefficient curve to the SEGM to realize the heating and cooling processes of the working roll.
Further, the step 3.2 specifically includes:
The expression of the heat transfer coefficient in the contact arc of the working roller and the strip steel is as follows:
；
Wherein: h con is the convective heat transfer coefficient of the strip steel and the working roll; The average unit rolling force is the unit N; v is the rolling speed in m/s;
the heat exchange coefficient expression of the working roll and the cooling water is as follows:
(1) The surface temperature Tr of the working roller is less than 100℃:
；
(2) The surface temperature Tr of the working roller is greater than 200℃:
；
Wherein: h cw is the convective heat transfer coefficient of the working roll and the cooling water; gamma 1、γ2 is the cooling heat transfer correction coefficient; e is the elastic modulus of the working roll; q is water flow density, q=v SP/ASP;PSP is injection pressure, unit MPa; t C is the temperature of cooling water, and is in units of ℃; v SP is the cooling water quantity, unit l/s; a SP is the spray area, unit, m 2; when Q is less than 10000 (l/s/m 2）,B=(Tc/16)-0.17; when Q is more than or equal to 10000 (l/s/m 2), B=1.0;
The heat exchange coefficient expression of the working roll and air is as follows:
；
Wherein: h air is the convective heat transfer coefficient of the working roll and air; delta T is the temperature difference between the work roll and the ambient air in degrees Celsius.
Further, the step5 specifically includes:
Step 5.1: extracting transverse distribution data of the thermal expansion of the surface of the working roll of different time nodes in a finite element simulation experiment;
Step 5.2: adding the thermal expansion amount of the surface of the working roll and the initial CVC working roll shape curve to obtain a plurality of thermal convexity working roll shape curves under different thermal convexities; normalizing the working roll width data of a plurality of thermal convexity working roll shape curves under different thermal convexities, and fitting the obtained normalized thermal convexity working roll shape curves by using a cubic polynomial to obtain a cubic fitting polynomial as follows:
；
Wherein y is a new work roll shape curve; x is dimensionless coordinate of the normalized working roll width direction, x is [ -1,1]; a 1 is a first term fitting coefficient, a 2 is a second term fitting coefficient, and a 3 is a third term fitting coefficient; e (x) is the fitting error;
Step 5.3: based on a 1、A2、A3, a new work roll shape curve is drawn, and indexes of the work roll partial thermal convexity c p and the whole thermal convexity c t are calculated:
；
；
Where h c is the work roll diameter at the work roll center point, h i is the work roll diameter at the work roll operation side portion, h i ' is the work roll diameter at the work roll drive side portion, h j is the work roll diameter corresponding to the strip operation side portion, and h j ' is the work roll diameter corresponding to the strip drive side portion.
Further, the influence of the thermal convexity on the roll shape curve and the strip steel shape in the step 6 is as follows:
At different rolling time nodes, the roll shape curves of the CVC working rolls are distributed in an S shape, but the roll shape curves in the middle of the CVC working rolls are increased upwards along with the increase of the rolling time, which is equivalent to the increase of secondary term, primary term and constant term coefficients on the basis of the initial CVC working roll shape curves.
The method for predicting the roll shape of the working roll based on the thermal convexity of the CVC rolling mill has the following beneficial effects:
according to the method, a three-dimensional thermal convexity simulation model of the CVC working roll is established according to the actually measured temperature boundary conditions, so that the thermal convexity change is more close to reality, and suggestions with practical production significance are provided for process arrangement, a grinding roll system, a roll shifting strategy and the like of hot rolling production; the thermal convexity is fitted with the original roll shape curve, so that the change of the roll shape of the CVC working roll can be predicted more intuitively and accurately, the thermal convexity is taken into consideration when the roll shape is ground, the fact that the actual convexity of the roll is consistent with the target convexity is ensured, meanwhile, different plate-shaped actuating mechanisms can be combined to better regulate and control the strip steel plate shape in actual production, the improvement of the strip steel plate shape quality can be facilitated, the product quality is further improved, and the enterprise benefit is improved; the invention adopts the simulation experiment method based on three-dimensional finite element simulation, and can reduce equipment, time and cost loss caused by actual experiments.
Drawings
FIG. 1 is a flow chart of a method of predicting work roll shape based on CVC mill thermal convexity in accordance with the present invention;
FIG. 2 is an initial CVC work roll shape curve;
FIG. 3 is a boundary condition zone division of a work roll surface;
FIG. 4 is a graph comparing a work roll temperature data curve of a finite element simulation experiment with a work roll temperature data curve measured in the field;
FIG. 5 is a graph comparing the measured thermal expansion of the middle of the work roll with the simulation results;
FIG. 6 is a graph of the amount of thermal expansion of the work roll surface at different time nodes;
FIG. 7 is a graph of overall thermal convexity versus partial thermal convexity distribution for a work roll;
fig. 8 is a graph of a new work roll shape curve versus an initial CVC work roll shape curve at different amounts of thermal expansion.
Detailed Description
In the embodiment, a 1780mm CVC four-roller hot continuous rolling mill set of a certain factory is taken as an example, numerical simulation research analysis is carried out on the continuous rolling mill set, a working roller of a rolling mill is in a CVC roller shape, and a supporting roller is a flat roller.
As shown in fig. 1, a method for predicting a roll shape of a work roll based on thermal convexity of a CVC rolling mill includes:
Step 1: collecting the strip steel parameters, rolling process parameters, cooling water parameters, CVC rolling mill parameters and working roll temperature data which are actually measured on site;
In the concrete implementation, the strip steel parameters, the rolling process parameters, the cooling water parameters, the CVC rolling mill parameters and the working roll temperature field data are obtained from the hot rolling production line.
The strip steel parameters comprise: steel type, width, thickness and temperature of the strip steel.
The rolling process parameters comprise: rolling speed, friction coefficient, rolling gap time and lateral movement of working roller.
The CVC rolling mill parameters include: work roll diameter, work roll body length, work roll density, work roll elastic modulus, work roll poisson ratio, work roll thermal expansion coefficient, work roll specific heat capacity, work roll heat conductivity coefficient and initial CVC work roll shape curve.
The cooling water parameters include: cooling water temperature, cooling water flow rate, cooling water injection pressure.
The temperature field data of the working roller is that a reflective adhesive tape is stuck on the working roller after the working roller is arranged in the axial direction, and a temperature field cloud picture of the working roller is shot by a thermal imager.
In this example, the obtained strip parameters are shown in table 1. The obtained rolling process parameters are shown in table 2. The CVC mill parameters obtained are shown in Table 3. The obtained cooling water parameters are shown in table 4.
Table 1 strip steel parameters.
| Parameters of strip steel | Parameter values |
| Strip steel type | DD11-MD |
| Width of strip steel | 1260mm |
| Thickness of strip steel | 10.7mm |
| Strip steel temperature | 952.03℃ |
Table 2 rolling process parameters.
| Rolling process parameters | Numerical value |
| Rolling speed | 3.42m/s |
| Coefficient of friction | 0.35 |
| Rolling gap time | 60s |
| Range of change in lateral movement of work roll | -120~120mm |
Table 3 CVC mill parameters.
| Parameters (parameters) | Numerical value |
| Diameter of work roll | 778mm |
| Length of working roll body | 2080mm |
| Density of work rolls | 7850kg/m3 |
| Modulus of elasticity of work roll | 210GPa |
| Poisson ratio of working roller | 0.3 |
| Coefficient of thermal expansion of work roll | 1.2e-5 |
| Specific heat capacity of working roll | 590 J·(kg·℃)-1 |
| Coefficient of thermal conductivity of work roll | 60 W·(m·K)-1 |
Table 4 cooling water parameters.
| Parameters (parameters) | Numerical value |
| Cooling water temperature | 30℃ |
| Cooling water flow | 2500l/min |
| Cooling water injection pressure | 1.47MPa |
In this embodiment, the working roll of the CVC rolling mill is a CVC roll shape, and the initial CVC working roll shape curve equation is a cubic polynomial function.
The upper roller of the working roller and the lower roller of the working roller are placed in a plane rectangular coordinate system, and as shown in fig. 2, the roller shape curve functions of the upper roller and the lower roller are respectively as follows:
；
；
wherein R U (x) is an upper roll shape function of the working roll, R L (x) is a lower roll shape function of the working roll, and x is a transverse coordinate of the roll; r 0 is the nominal radius of the working roller, and the unit is mm; a 1、a2 and a 3 are roll-shaped coefficients to be determined; l REF is the design length of the working roll, in mm. The parameters of the work roll profile in this example are shown in table 5.
Table 5 CVC working roll profile parameters.
| Roller shape curve parameter | Numerical value |
| Roll form factor a 1 | -1.850745×10-3 |
| Roll form factor a 2 | 1.830577×10-6 |
| Roll form factor a 3 | -5.260278×10-10 |
| Nominal radius R of roll 0 | 389mm |
| Roll design length L REF | 2080mm |
Step2: establishing a three-dimensional thermal convexity finite element model of the CVC working roll according to the CVC rolling mill parameters acquired in the step 1, wherein the step2 specifically comprises the following steps:
step 2.1: establishing modeling dimension parameters of a three-dimensional thermal convexity finite element model of the CVC working roll according to the CVC rolling mill parameters acquired in the step 1;
step 2.2: establishing material parameters of a three-dimensional thermal convexity finite element model of the CVC working roll according to the CVC rolling mill parameters acquired in the step 1;
Step 2.3: establishing a three-dimensional thermal convexity finite element model of the CVC working roll, and modeling by taking 1/30 of the circumferential direction of the working roll for shortening the calculation time, wherein the step 2.3 specifically comprises the following steps:
Selecting a SOLID164 eight-node hexahedral unit for modeling, defining thermal physical parameters of a working roll material, and drawing a roll shape curve of the working roll by adopting a higher B spline curve based on the CVC rolling mill parameters acquired in the step 1; grid refinement is carried out on the surface of the working roll, so that the calculation accuracy is ensured, the calculation time is gradually shortened from outside to inside, and the surface grid size is 10mm in the length direction, 2mm in the width direction and 3mm in the depth direction.
Step 2.4: the simplified boundary conditions, specific assumptions and simplified contents are:
(1) In the rolling process, the temperature of any node periodically changes, and the boundary condition reversely rotates to simulate the rotation of the working roll under the assumption that the working roll does not rotate;
(2) The temperature fields of the upper working roller and the lower working roller are considered to be consistent, and the working roller is positioned at a 0-leap roller position;
(3) The heat exchange between the working roller and the strip steel, between the working roller and the cooling water and between the working roller and the air is equivalent to convection heat exchange;
(4) The frictional heat generation between the working roller and the supporting roller is small, so that the frictional heat generation between the working roller and the supporting roller is ignored;
(5) According to the contact arc length between the strip steel and the working roll, dividing the working roll into thirty equal parts along the axial direction, wherein each part is 12 degrees, the strip steel is in contact with the working roll, as shown in fig. 3, the surface of the working roll is divided into 10 boundary areas, and the area 2 is a heat exchange area where the working roll is in contact with the strip steel and is a direct source of heat of the working roll; 3. the areas 6, 8 and 1 are areas where the working roller contacts with air, and heat exchange is carried out between the working roller and the air; the 7 area is the direct contact area between the working roller and the supporting roller; 5. the region 9 is a forced convection heat exchange region of cooling water and a working roller; 4. the area 10 is the heat convection between the accumulated water between the water baffles and the working roll.
Step 3: according to the strip steel parameters, rolling process parameters and cooling water parameters acquired in the step 1, calculating convection heat exchange coefficients of a working roll and strip steel, the working roll and air and the working roll and cooling water in the rolling process, and applying the convection heat exchange coefficients to a three-dimensional thermal convexity finite element model of a CVC working roll to perform finite element simulation experiments, wherein the step 3 specifically comprises the following steps:
step 3.1: the contact heat transfer and deformation heat between the working roller and the strip steel in the rolling process and the radiation heat exchange process between the working roller and the air are equivalent to convection heat exchange;
step 3.2: determining the convective heat transfer coefficient of the strip steel, the working roller, the cooling water and the working roller and the air according to a convective heat transfer formula and an empirical value, wherein the step 3.2 specifically comprises the following steps:
The expression of the heat transfer coefficient in the contact arc of the working roller and the strip steel is as follows:
；
Wherein: h con is the convective heat transfer coefficient of the strip steel and the working roll; the average unit rolling force is the unit N; v is the rolling speed in m/s.
The heat exchange coefficient expression of the working roll and the cooling water is as follows:
(1) The surface temperature Tr of the working roller is less than 100℃:
；
(2) The surface temperature Tr of the working roller is greater than 200℃:
；
Wherein: h cw is the convective heat transfer coefficient of the working roll and the cooling water; gamma 1、γ2 is the cooling heat transfer correction coefficient; e is the elastic modulus of the working roll; q is water flow density, q=v SP/ASP;PSP is injection pressure, unit MPa; t C is the temperature of cooling water, and is in units of ℃; v SP is the cooling water quantity, unit l/s; a SP is the spray area, unit, m 2; when Q is less than 10000 (l/s/m 2）,B=(Tc/16)-0.17; when Q is more than or equal to 10000 (l/s/m 2), B=1.0.
The heat exchange coefficient expression of the working roll and air is as follows:
；
Wherein: h air is the convective heat transfer coefficient of the working roll and air; delta T is the temperature difference between the work roll and the ambient air in degrees Celsius.
Step 3.3: generating a circulation curve of time-heat exchange coefficient through the K file by the convection heat exchange coefficient calculated in the step 3.2;
step 3.4: and creating an SEGM on the surface of the three-dimensional thermal convexity finite element model of the CVC working roll, and applying the time-heat exchange coefficient curve time to the SEGM to realize the heating and cooling processes of the working roll.
Step 4: the temperature boundary condition of the three-dimensional thermal convexity finite element model is adjusted to enable the temperature data curve of the working roll in the finite element simulation experiment to be consistent with the temperature field data curve of the working roll actually measured on site, and the step4 is specifically as follows:
And extracting temperature field data of the working rolls distributed along the axial direction in the finite element simulation experiment, comparing the temperature field data with the field actual measurement temperature field data, and enabling the three-dimensional thermal convexity finite element model precision to accord with the field actual measurement precision by adjusting boundary conditions and convection heat transfer coefficients. The temperature data curve of the working roll in the finite element simulation experiment is consistent with the temperature field data curve of the working roll actually measured on site, absolute errors between simulation results and actually measured values are smaller than 0.5 ℃, real-time change data of thermal expansion amount of an F4 frame in a roll changing period is selected according to PFC working logs collected from site, and as shown in a simulation result pair such as a graph shown in fig. 5, the thermal expansion amount of the working roll can be seen to rise along with time and then gradually tend to be stable, and finally the working roll is kept stable at about 250 mu m, because of idle period in rolling, the temperature of the roll body of the working roll is reduced, the thermal expansion is reduced, and therefore individual point fluctuation is large. Fig. 4 is a pair of a work roll temperature data curve of a finite element simulation experiment and a work roll temperature data curve measured in the field. FIG. 5 is a graph showing the comparison of the measured thermal expansion in the middle of the work roll with the simulation results.
Step 5: based on the adjusted three-dimensional thermal convexity finite element model, carrying out finite element experiments, extracting transverse distribution data of thermal expansion amounts of the surfaces of the working rolls at different time nodes in the finite element experiments, and fitting the transverse distribution data with an initial CVC working roll shape curve to obtain a new working roll shape curve, wherein the step 5 specifically comprises the following steps:
Step 5.1: extracting transverse distribution data of the thermal expansion of the surface of the working roll of different time nodes in a finite element simulation experiment;
in specific implementation, the post-processing software is used for extracting the thermal expansion amounts of the working rolls at different time nodes along the axial direction. The graph of the amount of thermal expansion of the work roll surface at different time nodes is shown in fig. 6.
Step 5.2: adding the thermal expansion amount of the surface of the working roll and the initial CVC working roll shape curve to obtain a plurality of working roll shape curves with different thermal convexities at different time nodes; normalizing the working roll width data of a plurality of thermal convexity working roll shape curves under different thermal convexities, and fitting the obtained normalized thermal convexity working roll shape curves by using a cubic polynomial to obtain a cubic fitting polynomial as follows:
；
Wherein y is a new work roll shape distribution curve; x is dimensionless coordinate of the normalized working roll width direction, x is [ -1,1]; a 1 is a first term fitting coefficient, a 2 is a second term fitting coefficient, and a 3 is a third term fitting coefficient; e (x) is the fitting error.
Step 5.3: based on a 1、A2、A3, a new work roll shape curve is drawn, and indexes of the work roll partial thermal convexity c p and the whole thermal convexity c t are calculated:
；
；
Where h c is the work roll diameter at the work roll center point, h i is the work roll diameter at the work roll operation side portion, h i ' is the work roll diameter at the work roll drive side portion, h j is the work roll diameter corresponding to the strip operation side portion, and h j ' is the work roll diameter corresponding to the strip drive side portion. In this example, data extraction was performed according to the above formula, and fig. 7 and 8 are drawn, and fig. 7 is a graph of the overall thermal convexity versus partial thermal convexity distribution of the work rolls. Fig. 8 is a graph of a new work roll shape curve versus an initial CVC work roll shape curve at different amounts of thermal expansion.
Step 6: and (5) analyzing the influence of the thermal convexity change of the working rolls at different time nodes on the CVC working roll shape curve according to the new working roll shape curve data obtained in the step (5).
The working roll is contacted with the strip steel at the initial stage of rolling, the temperature is rapidly increased, the expansion amount is also rapidly increased, when the rolling time is increased from 1000s to 5000s, the diameter of the middle part of the working roll is increased by 139.23 mu m, after 5000s, the diameter of the middle part of the working roll is slowly increased by 3.59 mu m, the temperature is gradually flattened, and the thermal expansion amount of the edge part of the working roll is increased from 1.24 mu m to 26.88 mu m along with the rolling time. The thermal expansion change of the working roll forms the thermal convexity of the working roll, when the rolling time is increased to 5000s, the whole thermal convexity and the local thermal convexity of the working roll are rapidly increased before 5000s, 472.28 mu m and 170.01 mu m are respectively increased, the increase is slow after 5000s, and the thermal convexity of the working roll is stable. When the rolling time is increased from 1000S to 5000S, the roll shape curve in the middle of the CVC working roll is increased upwards along with the increase of the rolling time, which is equivalent to the increase of the coefficients of the quadratic term, the primary term and the constant term on the basis of the original roll shape curve, but all the roll shape curves are distributed in an S shape, the thermal convexity is not changed along with the increase of the time after 5000S, and the roll shape curves are not changed any more, so that the stability is achieved.
According to the method for predicting the plate shape based on the thermal convexity of the CVC rolling mill, provided by the invention, the actual measurement parameters of the hot rolling production line are utilized, a finite element platform is utilized to build a simulation model of the thermal convexity of the CVC rolling mill, and the influence of the thermal convexity on the rolling curve of the rolling mill is analyzed. And a scientific and reasonable verification plan is formulated, and the stability and accuracy of the model are ensured. And analyzing the influence rule according to the obtained post-processing data after determining the transverse movement amount of the working roll by means of the on-site process parameters.
The foregoing description of the preferred embodiments of the invention is not intended to limit the scope of the invention, but rather to enable any modification, equivalent replacement, improvement or the like to be made without departing from the spirit and principles of the invention.
Claims (5)
1. A method for predicting a roll shape of a work roll based on thermal convexity of a CVC rolling mill, comprising:
step 1: collecting field actually measured strip steel parameters, rolling process parameters, cooling water parameters, CVC rolling mill parameters and working roll temperature field data;
Step 2: establishing a three-dimensional thermal convexity finite element model of the CVC working roll according to the CVC rolling mill parameters acquired in the step 1;
step 3: calculating convection heat exchange coefficients of a working roll and strip steel, working roll and air and working roll and cooling water in the rolling process according to the strip steel parameters, rolling process parameters and cooling water parameters acquired in the step 1, and applying the convection heat exchange coefficients to a three-dimensional thermal convexity finite element model to perform a finite element simulation experiment;
Step 4: adjusting the temperature boundary condition of the three-dimensional thermal convexity finite element model to enable the temperature data curve of the working roll in the finite element simulation experiment to be consistent with the temperature data curve of the working roll actually measured on site;
Step 5: carrying out a finite element simulation experiment based on the adjusted three-dimensional thermal convexity finite element model, extracting transverse distribution data of the thermal expansion amount of the surface of the working roll at different time points in the finite element simulation experiment, and fitting the transverse distribution data with an initial CVC working roll shape curve to obtain a new working roll shape curve;
step 6: according to the new working roll shape curve obtained in the step 5, analyzing the influence of the thermal convexity change of the working rolls at different time nodes on the CVC working roll shape curve;
the step 2 specifically comprises the following steps:
step 2.1: establishing modeling dimension parameters of a three-dimensional thermal convexity finite element model of the CVC working roll according to the CVC rolling mill parameters acquired in the step 1;
step 2.2: establishing material parameters of a three-dimensional thermal convexity finite element model of the CVC working roll according to the CVC rolling mill parameters acquired in the step 1;
step 2.3: establishing a three-dimensional thermal convexity finite element model of the CVC working roll, and modeling by taking 1/30 of the circumferential direction of the working roll for shortening the calculation time;
Step 2.4: simplifying boundary conditions;
The step 2.3 specifically comprises the following steps: selecting a SOLID164 eight-node hexahedral unit for modeling, defining thermal physical parameters of a working roll material, and drawing a roll shape curve of the working roll by adopting a higher B spline curve based on the CVC rolling mill parameters acquired in the step 1; grid refinement is carried out on the surface of the working roll, so that the calculation accuracy is ensured, the calculation time is gradually shortened from outside to inside, and the surface grid size is 10mm in the length direction, 2mm in the width direction and 3mm in the depth direction;
the specific assumption and simplification of the step 2.4 is as follows:
(1) In the rolling process, the temperature of any node periodically changes, and the boundary condition reversely rotates to simulate the rotation of the working roll under the assumption that the working roll does not rotate;
(2) The temperature fields of the upper working roller and the lower working roller are considered to be consistent, and the working roller is positioned at a 0-leap roller position;
(3) The heat exchange between the working roller and the strip steel, between the working roller and the cooling water and between the working roller and the air is equivalent to convection heat exchange;
(4) Neglecting frictional heating between the work roll and the backup roll;
(5) Dividing the working roll into 30 equal parts along the axial direction according to the contact arc length between the strip steel and the working roll, wherein each part is 12 degrees, and the strip steel is in contact with the working roll;
The step 5 specifically comprises the following steps:
Step 5.1: extracting transverse distribution data of the thermal expansion of the surface of the working roll of different time nodes in a finite element simulation experiment;
Step 5.2: adding the thermal expansion amount of the surface of the working roll and the initial CVC working roll shape curve to obtain a plurality of thermal convexity working roll shape curves under different thermal convexities; normalizing the working roll width data of a plurality of thermal convexity working roll shape curves under different thermal convexities, and fitting the obtained normalized thermal convexity working roll shape curves by using a cubic polynomial to obtain a cubic fitting polynomial as follows:
y＝A1x+A2x2+A3x3+e(x)；
Wherein y is a new work roll shape curve; x is dimensionless coordinate of the normalized working roll width direction, x is [ -1,1]; a 1 is a first term fitting coefficient, a 2 is a second term fitting coefficient, and a 3 is a third term fitting coefficient; e (x) is the fitting error;
Step 5.3: based on a 1、A2、A3, a new work roll shape curve is drawn, and indexes of the work roll partial thermal convexity c p and the whole thermal convexity c t are calculated:
Wherein h c is the work roll diameter at the work roll center point, h i is the work roll diameter at the work roll operation side edge, h i 'is the work roll diameter at the work roll transmission side edge, h j is the work roll diameter corresponding to the strip steel operation side edge, and h j' is the work roll diameter corresponding to the strip steel transmission side edge;
the influence of the thermal convexity on the roll shape curve and the strip steel shape in the step 6 is as follows:
At different rolling time nodes, the roll shape curves of the CVC working rolls are distributed in an S shape, but the roll shape curves in the middle of the CVC working rolls are increased upwards along with the increase of the rolling time, which is equivalent to the increase of secondary term, primary term and constant term coefficients on the basis of the initial CVC working roll shape curves.
2. The method for predicting the roll shape of a work roll based on the thermal convexity of a CVC rolling mill according to claim 1, wherein the step1 is specifically: obtaining strip steel parameters, rolling process parameters, cooling water parameters, CVC rolling mill parameters and working roll temperature field data from a hot rolling production line;
The strip steel parameters comprise: steel type, width, thickness and temperature of the strip steel;
the rolling process parameters comprise: rolling speed, friction coefficient, rolling gap time and lateral movement of the working rolls;
the cooling water parameters include: cooling water temperature, cooling water flow rate and cooling water injection pressure;
the CVC rolling mill parameters include: work roll diameter, work roll body length, work roll density, work roll elastic modulus, work roll poisson ratio, work roll thermal expansion coefficient, work roll specific heat capacity, work roll heat conductivity coefficient and initial CVC work roll shape curve;
The temperature field data of the working roller is that a reflective adhesive tape is stuck on the working roller after the working roller is arranged in the axial direction, and a temperature field cloud picture of the working roller is shot by a thermal imager.
3. The method for predicting the roll shape of a work roll based on the thermal convexity of a CVC rolling mill according to claim 2, wherein the initial CVC work roll shape curve equation is a cubic polynomial function, specifically:
RU(x)＝R0+a1·x+a2·x2+a3·x3；
RL(x)＝R0+a1·(LREF-x)+a2·(LREF-x)2+a3·(LREF-x)3;
Wherein R U (x) is an upper roll shape function of the working roll, R L (x) is a lower roll shape function of the working roll, and x is a transverse coordinate of the roll; r 0 is the nominal radius of the working roller, and the unit is mm; a 1、a2 and a 3 are roll-shaped coefficients to be determined; l REF is the design length of the working roll, in mm.
4. The method for predicting the roll shape of a work roll based on the thermal convexity of a CVC rolling mill according to claim 1, wherein said step 3 is specifically:
step 3.1: the contact heat transfer and deformation heat between the working roller and the strip steel in the rolling process and the radiation heat exchange process between the working roller and the air are equivalent to convection heat exchange;
Step 3.2: determining the convective heat transfer coefficients of the strip steel and the working roll, the working roll and the cooling water and the working roll and the air according to a convective heat transfer formula;
Step 3.3: generating a circulation curve of time-heat exchange coefficient through the K file by the convection heat exchange coefficient calculated in the step 3.2;
Step 3.4: and creating an SEGM on the surface of the three-dimensional thermal convexity finite element model of the CVC working roll, and applying a time-heat exchange coefficient curve to the SEGM to realize the heating and cooling processes of the working roll.
5. The method for predicting the roll shape of a work roll based on the thermal convexity of a CVC rolling mill according to claim 4, wherein said step 3.2 is specifically:
The expression of the heat transfer coefficient in the contact arc of the working roller and the strip steel is as follows:
Wherein: h con is the convective heat transfer coefficient of the strip steel and the working roll; The average unit rolling force is the unit N; v is the rolling speed in m/s;
the heat exchange coefficient expression of the working roll and the cooling water is as follows:
(1) The surface temperature Tr of the working roller is less than 100℃:
(2) The surface temperature Tr of the working roller is greater than 200℃:
Wherein: h cw is the convective heat transfer coefficient of the working roll and the cooling water; gamma 1、γ2 is the cooling heat transfer correction coefficient; e is the elastic modulus of the working roll; q is water flow density, q=v SP/ASP;PSP is injection pressure, unit MPa; t C is the temperature of cooling water, and is in units of ℃; v SP is the cooling water quantity, unit l/s; a SP is the spray area, unit m 2; when Q is less than 10000 (l/s/m 2),B＝(Tc/16)-0.17; when Q is more than or equal to 10000 (l/s/m 2), B=1.0;
The heat exchange coefficient expression of the working roll and air is as follows:
hair＝1.465ΔT1/3；
Wherein: h air is the convective heat transfer coefficient of the working roll and air; delta T is the temperature difference between the work roll and the ambient air in degrees Celsius.
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