Rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling

Abstract

The present invention discloses a rolling process optimization method based on the prediction of precipitation strengthening during the microalloyed steel finishing rolling process, comprising: constructing a microalloyed steel cross-sectional temperature field based on on-site microalloyed steel production data; predicting the precipitation strengthening effect based on the temperature detection of the finishing mill; measuring the stress-strain curve through a high-temperature compression test, combining the constructed microalloyed steel cross-sectional temperature field and the precipitation strengthening effect prediction results, performing finite element simulation, and obtaining the secondary convexity with and without considering the precipitation strengthening effect during the microalloyed steel finishing rolling process; based on the above two secondary convexities, determining the influence coefficient of the precipitation strengthening effect on the rolling force, realizing the optimization of the bending and shifting roller control strategy, and then achieving plate shape optimization. The present invention can provide a reference for process control and process improvement, reduce plate shape quality objections, and improve product qualification rate, and has significant application prospects.

Description

Technical Field

[0001] The present invention relates to the technical field of metallurgical rolling control, and in particular to a rolling process optimization method based on precipitation strengthening prediction during the finishing rolling process of micro-alloyed steel. Background Art

[0002] Microalloyed steels possess high strength, toughness, and durability. These improvements stem from the matrix-strengthening mechanism of trace alloying elements (such as Nb, Ti, and V). During high-temperature rolling, these microalloying elements combine with base elements like carbon and nitrogen to precipitate microalloying compounds within the austenite matrix. This, in turn, alters the strip's microstructure and affects the uniformity of its mechanical properties during finish rolling.

[0003] As an important strengthening method for microalloyed high-strength steel, precipitation strengthening is easily affected by temperature and changes in precipitation density and precipitation degree occur, that is, it shows temperature-sensitive characteristics. Combined with the non-uniform distribution phenomenon of hot finishing temperature, the non-uniform characteristics of precipitation strengthening exhibited by microalloyed steel during the finishing rolling process will further induce the non-uniform distribution of rolling deformation resistance, forcing the rolling stability to decrease. As far as the current hot finishing rolling control system is concerned, this non-uniform distribution problem of mechanical properties of microalloyed steel has not yet been incorporated into the control logic, so the cross-section control effect of microalloyed steel is not good, and it is difficult to construct a rectangular cross-section control mechanism. In addition to being prone to causing production accidents such as rolling breakage and steel piling in the finishing rolling unit, this problem will be further inherited to downstream cold rolling, continuous annealing and other process units, affecting downstream production stability. It is a key issue that needs to be solved urgently at this stage.

[0004] Currently, steel companies and researchers at home and abroad have conducted extensive research on the precipitation phenomenon in microalloyed steels. However, most of this research focuses on the influence of different microstructures and precipitates on strip properties at room temperature. However, the detection of such precipitation phenomena and their impact on subsequent processes remain relatively unresolved. In the field of plate and strip rolling, in particular, microalloyed steels with non-uniform precipitation strengthening are more difficult to roll in subsequent processes, further increasing the difficulty of controlling the cross-section quality of the strip in subsequent processes. Therefore, a method is urgently needed to predict precipitation strengthening in microalloyed steels, diagnose it, and propose subsequent rolling strategies. Summary of the Invention

[0005] The present invention provides a rolling process optimization method based on the prediction of precipitation strengthening in the finish rolling process of microalloyed steel, so as to predict the precipitation strengthening of microalloyed steel, perform diagnosis and propose subsequent rolling strategies.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] A rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling process, comprising:

[0008] The cross-sectional temperature field of microalloyed steel is constructed based on the field production data of microalloyed steel;

[0009] Prediction of precipitation strengthening effect based on finishing mill temperature detection;

[0010] The stress-strain curves were measured through high-temperature compression tests. Combined with the constructed cross-sectional temperature field of the microalloyed steel and the prediction results of the precipitation strengthening effect, finite element simulation was performed to obtain the secondary crown of the microalloyed steel during the finish rolling process with and without considering the precipitation strengthening effect.

[0011] Based on the secondary crown with and without considering the precipitation strengthening effect, the influence coefficient of precipitation strengthening effect on rolling force is determined, and the bending and shifting roll control strategy is optimized.

[0012] Furthermore, the cross-sectional temperature field of microalloyed steel is constructed based on the field production data of microalloyed steel, including:

[0013] The cross section of the microalloyed steel is divided into multiple rectangular grids along the x-direction and y-direction according to the preset x-direction spacing Δx and y-direction spacing Δy, respectively, to complete the spatial coordinate discretization of the cross section of the microalloyed steel;

[0014] The following two equations are used to obtain the temperature value of each node at each moment in the microalloyed steel cross section after the spatial coordinates are discretized, and the temperature field of the microalloyed steel cross section is constructed:

[0015]

[0016]

[0017] in, represents the temperature of the control volume corresponding to the node with coordinates (i, j) after Δt / 2 time, i = 0, 1, 2, ..., n B , n B Indicates the number of grids in the x direction; represents the temperature of the node with coordinates (i, j) at time k+Δt, where k represents the time, Δt represents the preset time interval, and j = 0, 1, 2, ..., n H , n H Indicates the number of grids in the y direction; a j 、b j 、c j d j All are coefficients; the calculation formulas of each coefficient are as follows:

[0018]

[0019] in, represents the temperature of the node with coordinates (i, j-1) at time k; represents the temperature of the node with coordinates (i, j) at time k; represents the temperature of the node with coordinates (i, j+1) at time k; q in represents the heat flux density of the internal heat source; λ represents thermal conductivity; c represents specific heat capacity; ρ represents density.

[0020] Furthermore, based on the temperature detection of the finishing mill, the precipitation strengthening effect is predicted, including:

[0021] Calculate the size radius of the precipitates and the volume fraction of the precipitates respectively;

[0022] The size radius and volume fraction of the precipitates are fitted with the precipitation strengthening theoretical model to simulate the precipitation strengthening process of microalloyed steel and predict the precipitation strengthening effect.

[0023] Furthermore, the calculation formula for the size radius of the precipitate is as follows:

[0024]

[0025]

[0026]

[0027] Where r represents the size radius of the precipitate; t represents time; D M represents the diffusion coefficient of microalloying elements; α pre Indicates the growth rate of the precipitated phase; represents the volume concentration of the solute in the matrix at a preset distance from the precipitated phase; represents the equilibrium volume concentration of solute elements on the austenite side; It represents the equilibrium volume concentration of the solute element on the precipitated phase side; represents the equilibrium molar concentration of microalloying elements on the precipitate side and the austenite side at the precipitate / austenite interface; represents the molar concentration of the microalloying element in the matrix at a preset distance from the precipitated phase; V γ represents the molar volume of austenite; V p represents the molar volume of the precipitated phase.

[0028] Furthermore, the calculation formula for the volume fraction of precipitates is as follows:

[0029]

[0030]

[0031]

[0032] Where Y represents the volume fraction of microalloy precipitates; I pre represents the steady-state nucleation rate; a represents the lattice constant of austenite; b l represents the Boltzmann constant; ρ represents density; x M is the concentration of microalloying elements; T represents the temperature; ΔG V represents the chemical driving force for the nucleation of the precipitation phase per unit volume; σ represents the energy density, which is 0.19 to 0.55 J / m 2 .

[0033] Furthermore, the precipitation strengthening theoretical model is expressed as:

[0034]

[0035] Among them, σ Orowan represents the precipitation strengthening effect calculated by the precipitation strengthening theoretical model; f p is the volume fraction of the precipitated phase; d p is the average diameter of the precipitated phase; k pc is the proportional constant; k d is the correction parameter for the size of the precipitated phase; μ is the shear coefficient; b is the Burgers vector.

[0036] Furthermore, in order to clarify the ultimate influence of precipitation strengthening on plate shape, the obtained precipitation strengthening theoretical model can be combined, the control group is set to not consider the precipitation strengthening effect, and its constitutive model is constructed separately. Finally, it is substituted into the plate shape simulation model to compare the influence of the contribution of precipitation strengthening to stress on the plate shape σ'=σ-σ Orowan ; where σ is the total yield strength.

[0037] Furthermore, the method further comprises:

[0038] The material stress relaxation curve was measured experimentally and the precipitation strengthening theoretical model was verified.

[0039] Furthermore, the experimental measurement of the material stress relaxation curve and verification of the precipitation strengthening theoretical model include:

[0040] Stress relaxation experiments were conducted using a Gleeble 3500 thermal simulator to measure the PTT curve and precipitation kinetics curve of the microalloyed steel, and the relationship between the precipitation and temperature of the microalloyed steel was obtained.

[0041] The prediction results of the precipitation strengthening theoretical model are compared with the experimental results. If the prediction accuracy of the precipitation strengthening theoretical model exceeds a preset threshold, the coupling relationship between the effects of temperature and precipitation strengthening on deformation resistance is determined.

[0042] Furthermore, the optimization of the bending and shifting roller control strategy is achieved, including:

[0043] Working roll shifting setting, including:

[0044] When the rolling mileage of the last stand after the work roll is changed is less than the critical mileage at which the roll shifting stroke changes, if the set roll shifting frequency is 1, the roll shifting amount is:

[0045] S(i)=S(i-1)+ΔS

[0046] Where S(i) represents the roll shifting amount when rolling the i-th piece of steel; S(i-1) represents the roll shifting amount when rolling the i-1-th piece of steel; ΔS represents the preset roll shifting step length;

[0047] When the rolling mileage of the last stand after the work rolls are changed is greater than the critical mileage at which the roll shifting stroke changes, the work roll shifting amount is:

[0048] P(i)=S m -ΔD(L c -L s )

[0049] Where P(i) represents the calculated value of the working roll travel when rolling the i-th piece of steel; S m Indicates the preset initial roller shifting stroke; L c Indicates the rolling kilometers of the current working roll; L s It represents the critical rolling mileage of the working roll when the roll shifting stroke begins to change; ΔD represents the coefficient of change of the roll shifting stroke, which is obtained by the following formula:

[0050]

[0051] Among them, P m Indicates the preset roller shifting stroke at the end of the rolling unit; L m Indicates the rolling mileage when the roll shifting stroke changes to the final roll shifting stroke of the rolling unit;

[0052] The working roll bending setting formula is as follows:

[0053]

[0054] Among them, B F 、R F Respectively represent the setting values ​​of bending roll force and rolling force; k BF 、k RF Respectively represent the influence coefficients of bending roll force and rolling force; k P Indicates the coefficient of influence of precipitation on rolling force; C m Indicates the mechanical crown of the strip; C WC 、C WERespectively represent the comprehensive roll shape of the middle and edge of the working roll body; k WC 、k WE Respectively represent the roll shape influence coefficients of the middle and edge of the working roll; C BC 、C BE Respectively represent the comprehensive roll shape of the middle and edge of the support roll body; k BC 、k BE Respectively represent the roller shape influence coefficients of the middle and edge of the support roller; C WR 、k WR They represent the initial roll shape and influence coefficient of the working roll respectively; k cst represents the constant coefficient.

[0055] Furthermore, the coefficient considering the influence of precipitation on rolling force is obtained as follows:

[0056] Calculate the ratio of plate shape crown to rolling force under different working conditions, considering the precipitation strengthening effect, and ignoring the precipitation strengthening effect;

[0057] Under each working condition, the ratio of the plate shape crown to the rolling force with the precipitation strengthening effect considered is compared with the ratio of the plate shape crown to the rolling force without the precipitation strengthening effect considered;

[0058] The average value of the calculation results under different working conditions is taken as the coefficient considering the influence of precipitation on rolling force.

[0059] On the other hand, the present invention further provides an electronic device, comprising a processor and a memory; wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the above method.

[0060] In yet another aspect, the present invention further provides a computer-readable storage medium, wherein the storage medium stores at least one instruction, and the instruction is loaded and executed by a processor to implement the above method.

[0061] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0062] The present invention establishes a cross-sectional temperature field of micro-alloyed steel finishing rolling, and realizes the prediction of precipitation strengthening and plate shape defects in the micro-alloyed steel finishing rolling process through theoretical calculation and experimental verification of the micro-alloyed steel finishing rolling process. It can significantly improve the accuracy of plate shape prediction in the micro-alloyed steel finishing rolling process, provide a reference for process control and process improvement, reduce plate shape quality objections, and improve product qualification rate, and has great application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0064] Figure 1 1 is a schematic diagram of an execution flow of a rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling provided by an embodiment of the present invention;

[0065] Figure 2 Schematic diagram of grid division during temperature field calculation provided by an embodiment of the present invention;

[0066] Figure 3 is a PTT curve diagram of the microalloyed steel provided in an embodiment of the present invention;

[0067] Figure 4 is a stress relaxation curve diagram of the microalloyed steel provided in an embodiment of the present invention;

[0068] Figure 5 is a temperature distribution diagram of the microalloyed steel provided by an embodiment of the present invention;

[0069] Figure 6 1 is a graph showing the relationship between the radius of microalloyed steel precipitates and temperature according to an embodiment of the present invention;

[0070] Figure 7 1 is a graph showing the relationship between the volume fraction of precipitates in microalloyed steel and temperature according to an embodiment of the present invention;

[0071] Figure 8 This is a diagram showing the effect of precipitation strengthening on stress at different temperatures for microalloyed steel provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0072] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0073] First embodiment

[0074] This embodiment provides a rolling process optimization method based on the prediction of precipitation strengthening during the finishing rolling process of microalloyed steel. The method can be implemented by an electronic device, which can be a terminal or a server. The method includes three parts: ① Construction of the temperature field of the finishing mill based on microalloyed steel; ② Precipitation strengthening prediction based on temperature detection of the finishing mill; ③ Microalloyed steel strip rolling process optimization strategy for non-uniform precipitation strengthening. Figure 1As shown in the figure, the method first constructs the cross-sectional temperature field based on the field production data of microalloyed steel, then predicts the precipitation strengthening of the strip cross section, determines the coupling relationship between the influence of temperature and precipitation strengthening on deformation resistance, and finally measures the stress-strain curve through high-temperature compression test. Finite element simulation is performed to optimize the bending roller control strategy and realize dynamic control of plate shape.

[0075] Specifically, the execution process of the method includes the following steps:

[0076] S1, constructs the cross-sectional temperature field of microalloyed steel based on the field production data of microalloyed steel;

[0077] Specifically, in this embodiment, the implementation process of the above S1 is as follows:

[0078] S11, discretize the spatial coordinates of the microalloyed steel cross section, and the grid division method is as follows Figure 2 As shown in the figure, where B is the strip width and H is the strip thickness, the cross section of the microalloyed steel with an area of ​​B×H is divided into multiple rectangular grids along the x-direction and y-direction according to the preset x-direction spacing Δx and y-direction spacing Δy respectively; n grids are generated in the width direction (x direction) and length direction (y direction) respectively. B 、n H grids; where i is the node number in the x-direction and j is the node number in the y-direction;

[0079] Among them, it should be noted that since the length of the rolled piece is much larger than its width and thickness, the heat transfer in the length direction is small, and the temperature control technology in the length direction is becoming mature, and the temperature difference can be controlled within 10°C. Therefore, when studying the temperature field of the strip, the heat transfer in the length direction can be ignored, and the three-dimensional problem can be converted into a two-dimensional problem.

[0080] S12, assuming that the temperature of the internal node (i, j) changes from time k to time k+Δt. Change to The following two equations can be used to obtain the temperature before and after the Δt / 2 time step, respectively. The catch-up method can be used to quickly solve the temperature value of each node in the microalloyed steel cross section after the spatial coordinates are discretized, and the temperature field of the microalloyed steel cross section can be constructed:

[0081]

[0082]

[0083] in, represents the temperature of the control volume corresponding to the node with coordinates (i, j) after Δt / 2 time, i = 0, 1, 2, ..., n B , n B Indicates the number of grids in the x direction; represents the temperature of the node with coordinates (i, j) at time k+Δt, where k represents the time, Δt represents the preset time interval, and j = 0, 1, 2, ..., n H , n H Indicates the number of grids in the y direction; a j 、b j 、c j d j All are coefficients; the calculation formulas of each coefficient are as follows:

[0084]

[0085] in, represents the temperature of the node with coordinates (i, j-1) at time k; represents the temperature of the node with coordinates (i, j) at time k; represents the temperature of the node with coordinates (i, j+1) at time k; q in represents the heat flux density of the internal heat source; λ represents thermal conductivity; c represents specific heat capacity; ρ represents density.

[0086] S2, prediction of precipitation strengthening effect based on temperature detection of finishing mill;

[0087] Specifically, in this embodiment, the implementation process of the above S2 is as follows:

[0088] S21, respectively calculates the size radius and volume fraction of the precipitates, fits them with the precipitation strengthening theoretical model, and simulates the precipitation strengthening process of microalloyed steel; the specific process is as follows:

[0089] S211, the relationship between the size radius of the precipitate and time can be obtained by calculation, and the calculation formula is as follows:

[0090]

[0091]

[0092]

[0093]

[0094] Where r represents the size radius of the precipitate; t represents time; D M represents the diffusion coefficient of microalloying elements; α pre Indicates the growth rate of the precipitated phase; It represents the volume concentration of solute in the matrix at a preset distance (far enough) from the precipitated phase; represents the equilibrium volume concentration of solute elements on the austenite side; It represents the equilibrium volume concentration of the solute element on the precipitated phase side; represents the equilibrium molar concentration of microalloying elements on the precipitate side and the austenite side at the precipitate / austenite interface; V represents the molar concentration of the microalloying element in the matrix at a preset distance (far enough) from the precipitated phase; γ represents the molar volume of austenite (6.68×10 -6 m 3 / mol); V p represents the molar volume of the precipitated phase.

[0095] S212, the relationship between the volume fraction of the precipitate and time can be obtained by calculation. The calculation formula is as follows:

[0096]

[0097]

[0098]

[0099] Where Y represents the volume fraction of microalloy precipitates; I pre represents the steady-state nucleation rate; a represents the lattice constant of austenite, which is 3.646×10 -10 m; b l represents the Boltzmann constant, which is 1.380649×10 -23 J / K; ρ represents dislocation density; x M is the concentration of microalloying elements (mole fraction); T represents the temperature value; ΔG V represents the chemical driving force for the nucleation of the precipitation phase per unit volume; σ represents the energy density, which is 0.19 to 0.55 J / m 2 .

[0100] S213, the relationship between the size and volume fraction of precipitates and the contribution of precipitation strengthening to deformation resistance is calculated using the precipitation strengthening theoretical model, ultimately obtaining a coupling relationship between the temperature during the microalloyed steel finish rolling process and the effect of precipitation strengthening on deformation resistance. The precipitation strengthening theoretical model uses the Orowan mechanism, and the calculated precipitation strengthening effect can be described as:

[0101]

[0102] Among them, σ Orowan represents the precipitation strengthening effect calculated by the precipitation strengthening theoretical model; f p is the volume fraction of the precipitated phase; d p is the average diameter of the precipitated phase (nm); k pc is the proportional constant, which can be 0.8; k dis the correction parameter for the precipitate phase size, which can be taken as 1.1; μ is the shear coefficient, which can be taken as 80260 MPa for steel; b is the Burgers vector, which can be taken as 0.248 nm.

[0103] S124, in order to clarify the final effect of precipitation strengthening on plate shape, we can combine the obtained precipitation strengthening theoretical model, set the control group to not consider the precipitation strengthening effect, and construct its constitutive model separately. Finally, substitute it into the plate shape simulation model to compare the effect of the contribution of precipitation strengthening to stress on the plate shape. σ'=σ-σ Orowan ; where σ is the total yield strength.

[0104] S22, the material stress relaxation curve is measured experimentally and the precipitation strengthening theoretical model is verified:

[0105] S221, stress relaxation experiments were conducted using a Gleeble 3500 thermal simulator to measure the PTT curve and precipitation kinetics curve of the microalloyed steel, and the relationship between the precipitates and temperature of the microalloyed steel was obtained;

[0106] Among them, the precipitation kinetics PTT curve represents the precipitation-time-temperature curve under isothermal conditions, such as Figure 3 The curve is obtained from the true stress-true strain curve obtained from the stress relaxation experiment. In the true stress-true strain diagram, the point where the true stress slope increases significantly and the point where the true stress slope decreases significantly are called the precipitation starting point Ps and precipitation ending point Pf, respectively. Figure 4 As shown, a PTT curve can be drawn according to the Ps and Pf values ​​at different temperatures, and the start and end time of precipitation at different temperatures can be observed, and then the precipitation kinetics curve can be drawn.

[0107] S222, comparing the predicted results of the precipitation strengthening theoretical model with the experimental results. If the theoretical model has high accuracy, the coupling relationship between the effects of temperature and precipitation strengthening on deformation resistance can be determined.

[0108] S3, stress-strain curves were measured through high-temperature compression tests. Finite element simulation was performed based on the constructed cross-sectional temperature field of the microalloyed steel and the prediction results of the precipitation strengthening effect. The secondary convexity of the microalloyed steel during the finish rolling process was obtained with and without considering the precipitation strengthening effect. Among them, the precipitation strengthening effect was calculated using the above-mentioned precipitation strengthening theoretical model.

[0109] Specifically, in this embodiment, the implementation process of the above S3 is as follows:

[0110] S31, high-temperature compression tests were conducted using a Gleeble 3500 thermal simulator to obtain stress-strain curves of the specimens under different working conditions. The effects of different factors on the deformation resistance of the specimens under high-temperature conditions were analyzed, and the mechanical properties of the microalloyed steel were measured to provide basic thermal parameters for finite element simulations.

[0111] S32, using finite element software to simulate and analyze microalloyed steel finishing rolling, such as Figure 8 As shown in Figure 3, by comparing the two types of secondary convexity with and without precipitation strengthening effects, we can obtain the effects of considering precipitation and not considering precipitation on the secondary convexity under different temperature drops.

[0112] S4, based on the secondary crown with and without precipitation strengthening effects, determines the influence coefficient of precipitation strengthening effect on rolling force, and optimizes the bending and shifting roll control strategy;

[0113] Specifically, in this embodiment, the implementation process of the above S4 is as follows:

[0114] S41, work roll shifting setting, wherein the work roll shifting setting is mainly based on the incoming material parameters and the crown distribution of each stand, and the work roll shifting position of each stand is set and calculated; the specific setting method is:

[0115] S411: When the rolling mileage of the last stand after the work roll change is less than the critical mileage at which the roll shifting stroke changes, if the set roll shifting frequency is 1, the roll shifting amount is:

[0116] S(i)=S(i-1)+ΔS

[0117] Where S(i) represents the roll shifting amount when rolling the i-th piece of steel; S(i-1) represents the roll shifting amount when rolling the i-1-th piece of steel; ΔS represents the preset roll shifting step length;

[0118] S412: When the rolling mileage of the last stand after the work rolls are changed is greater than the critical mileage at which the roll shifting stroke changes, the work roll shifting amount is:

[0119] P(i)=S m -ΔD(L c -L s )

[0120] Where P(i) represents the calculated value of the working roll travel when rolling the i-th piece of steel; S m Indicates the preset initial roller shifting stroke; L c Indicates the rolling kilometers of the current working roll; L s It represents the critical rolling mileage of the working roll when the roll shifting stroke begins to change; ΔD represents the coefficient of change of the roll shifting stroke, which can be obtained by the following formula:

[0121]

[0122] Among them, P m Indicates the preset roller shifting stroke at the end of the rolling unit; L m Indicates the rolling mileage when the roll shifting stroke changes to the final roll shifting stroke of the rolling unit;

[0123] S42, work roll bending setting, wherein the setting calculation of the work roll bending force requires that, under the premise of determining the rolling force and roll shape, according to the target crown and flatness of the strip at the exit of each stand, the bending force required for each stand is solved from the first stand onwards according to the bending setting strategy; the specific setting process is as follows:

[0124] Using the crown calculation results from the previous step, the linearized model for the bending roll force setting calculation in the existing plate shape setting control system is optimized:

[0125]

[0126] Among them, B F 、R F Respectively represent the setting values ​​of bending roll force and rolling force; k BF 、k RF Respectively represent the influence coefficients of bending roll force and rolling force; k P Indicates the coefficient of influence of precipitation on rolling force; C m Indicates the mechanical crown of the strip; C WC 、C WE Respectively represent the comprehensive roll shape of the middle and edge of the working roll body; k WC 、k WE Respectively represent the roll shape influence coefficients of the middle and edge of the working roll; C BC 、C BE Respectively represent the comprehensive roll shape of the middle and edge of the support roll body; k BC 、k BE Respectively represent the roller shape influence coefficients of the middle and edge of the support roller; C WR 、k WR They represent the initial roll shape and influence coefficient of the working roll respectively; k cst represents the constant coefficient.

[0127] Among them, the influence coefficient k P The method of obtaining is: comparing the ratio of plate shape crown to rolling force under different working conditions, and finally obtaining the coefficient k considering the influence of precipitation on rolling force P ; The details are as follows:

[0128] Calculate the ratio of plate shape crown to rolling force under different working conditions, considering the precipitation strengthening effect, and ignoring the precipitation strengthening effect;

[0129] Under each working condition, the ratio of the plate shape crown to the rolling force with the precipitation strengthening effect considered is compared with the ratio of the plate shape crown to the rolling force without the precipitation strengthening effect considered;

[0130] The average value of the calculation results under different working conditions is taken as the coefficient considering the influence of precipitation on rolling force.

[0131] In summary, this embodiment provides a rolling process optimization method based on the prediction of precipitation strengthening during the finishing rolling process of microalloyed steel. This method can combine the constructed hot finishing temperature field to predict the non-uniform microalloying element precipitation strengthening phenomenon existing in the hot rolling-cold rolling process of microalloyed steel plates and strips, and perform mechanical property heterogeneity diagnosis based on this, and finally propose a rolling strategy for secondary control to the hot finishing rolling unit.

[0132] Next, we will apply this method to an actual microalloyed steel production site. The implementation process is as follows:

[0133] Step 1: construct the cross-sectional temperature field based on the field production data of microalloyed steel;

[0134] Among them, the chemical composition of the steel used in this case is shown in Table 1.

[0135] Table 1 Chemical composition of steel grades used

[0136]

[0137] According to the following two formulas, the cross-sectional temperature field of microalloyed steel under a working condition is calculated. The calculation results are shown in Table 2, which correspond to the temperatures at different positions and are plotted as follows: Figure 5 The temperature distribution diagram is shown.

[0138]

[0139]

[0140] Table 2 Cross-sectional temperature field of microalloyed steel

[0141]

[0142]

[0143] Step 2, performing precipitation strengthening prediction based on finishing mill temperature detection;

[0144] In this case, the changes of the precipitate radius and the volume fraction of the microalloyed steel with temperature are as follows: Figure 6 and Figure 7 As shown in the figure, the comparison between the theoretical calculation and experimental results of the PTT curve is shown in the figure. Figure 3As shown in the figure, the relationship between the effect of precipitation strengthening on stress and temperature is as follows Figure 8 As shown, it can be seen that during the finishing rolling process, precipitation strengthening has a greater impact on stress and should be taken into consideration as a cause of defect diagnosis.

[0145] Step 3, optimizing the rolling process of microalloyed steel strip with heterogeneous precipitation strengthening;

[0146] Among them, the influence coefficient k of the current steel grade precipitation on rolling force calculated in this case is P , as shown in Table 3.

[0147] Table 3 Effect coefficient of precipitation on rolling force

[0148]

[0149] Based on the above data, k in this case P The final average value is 1.04.

[0150] Data and defects of 1,000 rolls of microalloyed steel were collected at a steel mill before and after the application of this method. The comparison is shown in Table 4. It can be seen that after the application of this method, the number of rolls with medium wave defects per 1,000 rolls was reduced by 16 rolls, and the medium wave defect rate was reduced by 50%.

[0151] Table 4 Comparison of defects before and after application of this method

[0152]

[0153] It can be seen that this method can significantly reduce the plate shape defects during the finish rolling process of microalloyed steel, provide a reference for process control and process improvement, reduce plate shape quality objections, and improve product qualification rate.

[0154] Second embodiment

[0155] This embodiment provides an electronic device, which includes a processor and a memory; wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the method of the first embodiment.

[0156] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) and one or more memories, wherein the memory stores at least one instruction, which is loaded by the processor to execute the above method.

[0157] Third embodiment

[0158] This embodiment provides a computer-readable storage medium storing at least one instruction, which is loaded and executed by a processor to implement the method of the first embodiment described above. The computer-readable storage medium may be a ROM, random access memory, CD-ROM, magnetic tape, floppy disk, or optical data storage device. The instructions stored therein can be loaded by a processor in a terminal to execute the method described above.

[0159] Furthermore, it should be noted that the present invention may be provided as a method, apparatus, or computer program product. Thus, embodiments of the present invention may take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media containing computer-usable program code.

[0160] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the process in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0161] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for implementing the process in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0162] It should also be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. The terms "comprises," "includes," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further restrictions, an element defined by the phrase "comprises a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0163] Finally, it should be noted that the above is a preferred embodiment of the present invention. It should be noted that although the preferred embodiment of the present invention has been described, it is clear that those skilled in the art, once they understand the basic inventive concept of the present invention, can make various improvements and modifications without departing from the principles of the present invention. Such improvements and modifications should also be considered as within the scope of protection of the present invention. Therefore, the appended claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. A rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling, characterized in that: The rolling process optimization method based on the prediction of precipitation strengthening during the microalloyed steel finish rolling process includes: The cross-sectional temperature field of microalloyed steel is constructed based on the field production data of microalloyed steel; Prediction of precipitation strengthening effect based on finishing mill temperature detection; The stress-strain curves were measured through high-temperature compression tests. Combined with the constructed cross-sectional temperature field of the microalloyed steel and the prediction results of the precipitation strengthening effect, finite element simulation was performed to obtain the secondary crown of the microalloyed steel during the finish rolling process with and without considering the precipitation strengthening effect. Based on the secondary crown with and without considering the precipitation strengthening effect, the influence coefficient of precipitation strengthening effect on rolling force is determined, and the bending and shifting roll control strategy is optimized.

2. The rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling process according to claim 1, characterized in that: The method of constructing a microalloyed steel cross-sectional temperature field based on microalloyed steel on-site production data includes: The cross section of the microalloyed steel is divided into multiple rectangular grids along the x-direction and y-direction according to the preset x-direction spacing Δx and y-direction spacing Δy, respectively, to complete the spatial coordinate discretization of the cross section of the microalloyed steel; The following two equations are used to obtain the temperature value of each node at each moment in the microalloyed steel cross section after the spatial coordinates are discretized, and the temperature field of the microalloyed steel cross section is constructed: in, represents the temperature of the control volume corresponding to the node with coordinates (i, j) after Δt / 2 time, i = 0, 1, 2, …, nB, nB represents the number of grids in the x direction; represents the temperature of the node with coordinates (i, j) at time k+Δt, where k represents the time, Δt represents the preset time interval, j = 0, 1, 2, ..., nH, and nH represents the number of grids in the y direction; aj, b j 、c j d j All are coefficients; the calculation formulas of each coefficient are as follows: in, represents the temperature of the node with coordinates (i, j-1) at time k; represents the temperature of the node with coordinates (i, j) at time k; represents the temperature of the node with coordinates (i, j+1) at time k; q in represents the heat flux density of the internal heat source; λ represents thermal conductivity; c represents specific heat capacity; ρ represents density.

3. The rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling process according to claim 1, characterized in that: Prediction of precipitation strengthening effect based on finishing mill temperature detection, including: Calculate the size radius of the precipitates and the volume fraction of the precipitates respectively; The size radius and volume fraction of the precipitates are fitted with the precipitation strengthening theoretical model to simulate the precipitation strengthening process of microalloyed steel and predict the precipitation strengthening effect.

4. The rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling process according to claim 3, characterized in that: The calculation formula of the size radius of the precipitate is as follows: Where r represents the size radius of the precipitate; t represents time; D M represents the diffusion coefficient of microalloying elements; α pre Indicates the growth rate of the precipitated phase; represents the volume concentration of the solute in the matrix at a preset distance from the precipitated phase; represents the equilibrium volume concentration of solute elements on the austenite side; It represents the equilibrium volume concentration of the solute element on the precipitated phase side; represents the equilibrium molar concentration of microalloying elements on the precipitate side and the austenite side at the precipitate / austenite interface; represents the molar concentration of the microalloying element in the matrix at a preset distance from the precipitated phase; V γ represents the molar volume of austenite; V p represents the molar volume of the precipitated phase.

5. The rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling process according to claim 4, characterized in that: The calculation formula of the volume fraction of precipitates is as follows: Where Y represents the volume fraction of microalloy precipitates; I pre represents the steady-state nucleation rate; a represents the lattice constant of austenite, which is 3.646×10 -10 m; b l represents the Boltzmann constant, which is 1.380649×10 -23 J / K; ρ represents dislocation density; x M is the concentration of microalloying elements; T represents the temperature; ΔG V represents the chemical driving force for the nucleation of the precipitation phase per unit volume; σ represents the energy density, which is 0.19 to 0.55 J / m 2 .

6. The rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling process according to claim 5, characterized in that: The precipitation strengthening theoretical model is expressed as: Among them, σ Orowan represents the precipitation strengthening effect calculated by the precipitation strengthening theoretical model; f p is the volume fraction of the precipitated phase; d p is the average diameter of the precipitated phase; k pc is the proportional constant; k d is the correction parameter for the size of the precipitated phase; μ is the shear coefficient; b is the Burgers vector.

7. The rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling process according to claim 3, characterized in that: The method further comprises: The material stress relaxation curve was measured experimentally and the precipitation strengthening theoretical model was verified.

8. The rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling according to claim 7, characterized in that: The material stress relaxation curve is measured experimentally and the precipitation strengthening theoretical model is verified, including: Stress relaxation experiments were conducted using a Gleeble 3500 thermal simulator to measure the PTT curve and precipitation kinetics curve of the microalloyed steel, and the relationship between the precipitation and temperature of the microalloyed steel was obtained. The prediction results of the precipitation strengthening theoretical model are compared with the experimental results. If the prediction accuracy of the precipitation strengthening theoretical model exceeds a preset threshold, the coupling relationship between the effects of temperature and precipitation strengthening on deformation resistance is determined.

9. The rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling process according to claim 1, characterized in that: The optimization of the bending and shifting roller control strategy includes: Working roll shifting setting, including: When the rolling mileage of the last stand after the work roll is changed is less than the critical mileage at which the roll shifting stroke changes, if the set roll shifting frequency is 1, the roll shifting amount is: S(i)=S(i-1)+ΔS Where S(i) represents the roll shifting amount when rolling the i-th piece of steel; S(i-1) represents the roll shifting amount when rolling the i-1-th piece of steel; ΔS represents the preset roll shifting step length; When the rolling mileage of the last stand after the work rolls are changed is greater than the critical mileage at which the roll shifting stroke changes, the work roll shifting amount is: P(i)=S m -ΔD(L c -L s ) Where P(i) represents the calculated value of the working roll travel when rolling the i-th piece of steel; S m Indicates the preset initial roller shifting stroke; L c Indicates the rolling kilometers of the current working roll; L s It represents the critical rolling mileage of the working roll when the roll shifting stroke begins to change; ΔD represents the coefficient of change of the roll shifting stroke, which is obtained by the following formula: Among them, P m Indicates the preset roller shifting stroke at the end of the rolling unit; L m Indicates the rolling mileage when the roll shifting stroke changes to the final roll shifting stroke of the rolling unit; The working roll bending setting formula is as follows: Among them, B F 、R F Respectively represent the setting values ​​of bending roll force and rolling force; k BF 、k RF Respectively represent the influence coefficients of bending roll force and rolling force; k P Indicates the coefficient of influence of precipitation on rolling force; C m Indicates the mechanical crown of the strip; C WC 、C WE Respectively represent the comprehensive roll shape of the middle and edge of the working roll body; k WC 、k WE Respectively represent the roll shape influence coefficients of the middle and edge of the working roll; C BC 、C BE Respectively represent the comprehensive roll shape of the middle and edge of the support roll body; k BC 、k BE Respectively represent the roller shape influence coefficients of the middle and edge of the support roller; C WR 、k WR They represent the initial roll shape and influence coefficient of the working roll respectively; k cst represents the constant coefficient.

10. The rolling process optimization method based on precipitation strengthening prediction during microalloyed steel finish rolling according to claim 9, characterized in that: The method for obtaining the coefficient considering the influence of precipitation on rolling force is: Calculate the ratio of plate shape crown to rolling force under different working conditions, considering the precipitation strengthening effect, and ignoring the precipitation strengthening effect; Under each working condition, the ratio of the plate shape crown to the rolling force with the precipitation strengthening effect considered is compared with the ratio of the plate shape crown to the rolling force without the precipitation strengthening effect considered; The average value of the calculation results under different working conditions is taken as the coefficient considering the influence of precipitation on rolling force.

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