Method for predicting coarse grain defects on surface of high-strength aluminum alloy extruded profile

Abstract

The invention provides a method for predicting coarse grain defects on the surface of a high-strength aluminum alloy extruded profile, and relates to the field of aluminum alloy image processing. The method for predicting the surface coarse grain defects of the high-strength aluminum alloy extruded profile comprises the following steps: carrying out a hot extrusion experiment and a hot compression experiment; representing an extruded profile and a thermal shrinkage pressure sample to obtain a recrystallization fraction and a recrystallization grain average size; simulating a profile extrusion process and obtaining basic physical quantities of the profile; determining a function relationship between the physical field quantity and the recrystallization fraction and between the physical field quantity and the recrystallization grain average size through data fitting and linear regression, and establishing a prediction mathematical model; establishing a recrystallization grain growth rate model; and realizing surface coarse grain defect prediction of the extruded profile through numerical simulation. According to the method, the distribution position of the coarse grain defects on the surface of the aluminum alloy profile can be accurately predicted, the recrystallization degree, the grain size and the recrystallization grain coarsening rate of each position of the profile are independently quantified, and the coarse grain defects on the surface of the high-strength aluminum alloy extruded profile are accurately evaluated.

Description

Technical Field

[0001] The invention relates to the field of aluminum alloy image processing, and in particular to a method for predicting coarse-grained defects on the surface of a high-strength aluminum alloy extruded profile. Background Art

[0002] High-strength aluminum alloy extruded profiles have excellent properties such as low density, high specific strength, and good damage tolerance. They are widely used structural parts in the fields of marine engineering, marine transportation, rail transportation, and aerospace. However, high-strength aluminum alloy profiles such as Al-Li and Al-Zn are very prone to local coarse-grained defects during hot extrusion and subsequent heat treatment, which usually exist on the surface of aluminum alloy profiles and longitudinal welds. Such coarse-grained defects seriously affect the mechanical properties, fatigue properties, and corrosion resistance of aluminum alloy profiles, and damage the safety, reliability, and service life of aluminum alloy components.

[0003] The formation and evolution of coarse-grained microstructure on the surface of aluminum alloy extruded profiles are jointly affected by the extrusion die and the extrusion process. There are differences in the microstructure of aluminum alloy profiles under different extrusion conditions, and the deformation parameters are diverse and complex. But in essence, the main reason for the formation of coarse-grained defects on the surface of aluminum alloy profiles, welds and other local locations is that the change in deformation conditions causes the temperature, strain rate and strain field of the local material to change, resulting in differences in local deformation storage energy, which in turn triggers different recrystallization and grain growth processes. Therefore, the basic physical quantities such as strain degree, strain rate and temperature of aluminum alloy materials during extrusion deformation are the main factors affecting the local microstructure of aluminum alloy profiles. To this end, technicians have tried to use physical simulation experiments, extrusion experiments and numerical simulation methods to study the influence of basic physical quantities on the grain structure of aluminum alloy profiles and predict the location of defect formation.

[0004] However, there are still some key problems that need to be solved in the existing technology. First, current research tends to explore the influencing rules and the mechanism of coarse grain generation, and a method that can effectively predict the distribution position of coarse grain defects on the surface of extruded profiles has not yet been found; second, it is impossible to achieve quantitative evaluation of recrystallization and grain coarsening under large plastic strain, especially when the surface of the extruded profile undergoes severe plastic deformation. It is difficult to accurately obtain and quantify the degree of recrystallization and grain coarsening under large strain conditions using traditional physical simulation experimental methods such as single hot compression and hot stretching; third, the formation and evolution of surface coarse grains in high-strength aluminum alloy materials such as Al-Li, Al-Cu and Al-Zn during extrusion forming have their own unique characteristics. Generally, a fine recrystallization layer is formed on the surface of the aluminum alloy profile during hot extrusion deformation, and then the fine grains are rapidly coarsened during heat treatment to form surface coarse grain defects. At present, there is a lack of effective prediction methods for surface coarse grain defects based on the above mechanism.

[0005] In summary, due to the above problems, it is currently impossible to accurately establish the quantitative relationship between the basic physical quantities, the degree of recrystallization of the profile surface, and the degree of surface grain coarsening during the extrusion process of high-strength aluminum alloys, and it is also impossible to effectively predict the distribution position of surface coarse grain defects. Therefore, it is necessary to establish a method model that can accurately predict the recrystallization and grain growth behavior of the surface structure during the extrusion process of high-strength aluminum alloys to solve the above problems in the prior art. Summary of the invention

[0006] In order to solve the technical problems existing in the prior art, the present invention provides a method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles, which can accurately predict the distribution positions of coarse-grained defects on the surface of aluminum alloy profiles, and can also individually quantify the degree of recrystallization, grain size and recrystallization grain coarsening rate at each position of the profile, thereby achieving accurate prediction of local coarse-grained defects in high-strength aluminum alloy extruded profiles and reducing the blindness and contingency of coarse-grained defect prediction.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows: A method for predicting coarse-grained defects on the surface of a high-strength aluminum alloy extruded profile comprises the following steps: Step S001, extruding the aluminum alloy profile to obtain an extruded profile; Step S002, performing a solid solution treatment on the extruded profile to obtain a solid solution profile; Step S003, sampling each characteristic position of the extruded profile to obtain the extruded profile sample and then characterizing it to obtain the recrystallization fraction and the average size of the recrystallized grains at each characteristic position of the extruded profile; sampling each characteristic position of the solid solution profile to obtain the solid solution profile sample and then characterizing it to obtain the average size of the grains at each characteristic position of the solid solution profile after coarsening; Step S004, performing a hot compression test on the aluminum alloy profile to obtain a hot compression sample; Step S005, sampling and characterizing the middle position of the hot compression sample to obtain the recrystallization fraction and average size of recrystallized grains at the middle position of the hot compression sample; Step S006, numerically simulating the extrusion process of the aluminum alloy profile to obtain the physical field quantity of each characteristic position of the extruded profile; The physical field quantities include: temperature, strain, and strain rate; Step S007, establishing a quantitative relationship model between the physical field quantity and the recrystallization fraction and a quantitative relationship model between the physical field quantity and the average size of the recrystallized grains respectively through curve fitting and linear regression; Step S008, calculating the driving force of grain boundary migration according to the average size of recrystallized grains at each characteristic position of the extruded profile and the average size of grains at each characteristic position after coarsening after solution treatment, and establishing a recrystallized grain growth rate prediction model; Step S009, embedding the quantitative relationship model of step S007, the recrystallization grain growth rate prediction model and the relevant parameter calculation formulas in the model into the finite element numerical simulation software; Step S010, obtaining numerical values ​​of the extrusion process of the aluminum alloy profile, and performing calculations using finite element numerical simulation software embedded with a quantitative relationship model and a recrystallization grain growth rate prediction model to obtain prediction results of coarse grain defects on the surface of the high-strength aluminum alloy extruded profile.

[0008] Furthermore, the method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles also includes the following steps: step S011, performing metallographic observation and characterization on the solid solution profile sample of step S003 to obtain a metallographic observation and characterization result, and then comparing the metallographic observation and characterization result with the prediction result obtained in step S010 to verify the prediction accuracy of step S010.

[0009] Furthermore, in step S001, the cross section of the extruded profile includes at least: an outer convex rounded corner, an inner concave rounded corner, and a flat surface.

[0010] Preferably, in step S002, the solution treatment temperature is not less than 500° C., and the solution treatment time is not less than 1 hour.

[0011] Preferably, in step S003, the characteristic positions of the extruded profile at least include: an outer convex fillet, an inner concave fillet, and a flat surface; The characteristic positions of the solid solution state profile at least include: external convex fillet, internal concave fillet, and flat surface; The sampling position for the solid solution state profile is the same as the sampling position for the extruded state profile.

[0012] Furthermore, in the step S004, in the test conditions of the thermal compression test, the deformation temperature is one of the following: 400°C, 450°C, 500°C or 550°C; the strain rate is one of the following: 0.01s -1 , 0.1s -1 , 1s -1 or 10s -1 ; The compression amount is 70% of the height of the compressed specimen, corresponding to a true strain of 1.2.

[0013] Furthermore, in step S007, the quantitative relationship model between the physical field quantity and the recrystallization fraction is shown in formula (1): (1); In formula (1), X drx is the recrystallization fraction; ε For strain; γ drx The value is -0.92; α drx The value is 33.47; β drx The value is -1.35×10 10 ; m drx The value is -5.76; n drx The value is 0.90; Z is the Zener-Hollomon parameter; The quantitative relationship model between the physical field quantity and the average size of the recrystallized grains is shown in formula (2): (2); In formula (2), D drx is the average size of recrystallized grains; D0 is the average grain size of the aluminum alloy profile before extrusion treatment; ε For strain; is the strain rate; T is temperature; λ drx The value is 3.77×10 3 ; p drx The value is -0.62; q drx The value is -0.18; r drx The value is -0.03; Q drx The value is -2.36×10 4 .

[0014] In step S008, the recrystallization grain growth rate prediction model is shown in formula (3): (3); In formula (3), v gb is the recrystallization grain growth rate; M is the grain boundary mobility; P It is the driving force for grain boundary migration; P sz is the grain boundary migration resistance; Said M The calculation method is ; Said P The calculation method is ; Said P sz The calculation method is ; in, R c is the average radius of recrystallized grains, calculated by formula (2); R rex is the average radius of the grain after coarsening, obtained by characterizing the solid solution profile in step S003; δ The value is 8.75×10 -14 m 3 / s; b The value is 2.86×10 -10 m; Q diff The value is 100 kJ / mol; R The value is 8.314 J / mol·K; c The value is 1.5; γ b The value is 0.324J / m 2 ; f v The value is 0.052; r The value is 0.165μm.

[0015] Preferably, in step S003, after the extruded profile sample is characterized by electron backscatter diffraction EBSD, HKL-Channel5 software is used for analysis and statistics to obtain the recrystallization fraction and average size of recrystallized grains at each characteristic position of the extruded profile; After the solid solution profile samples were characterized by electron backscatter diffraction EBSD, the HKL-Channel5 software was used for analysis and statistics to obtain the average size of the grains after coarsening at each characteristic position of the solid solution profile; In the step S005, the middle position of the hot compression sample is sampled and characterized by electron backscatter diffraction EBSD, and the HKL-Channel5 software is used for statistical analysis to obtain the recrystallization fraction and average recrystallized grain size of the middle position of the hot compression sample.

[0016] Preferably, in step S006, the extrusion process of the aluminum alloy profile is numerically simulated using QForm forging extrusion heat treatment simulation software; In step S007, 1stOpt software is used to perform curve fitting and linear regression; In the step S009, the finite element numerical simulation software is a subroutine module of QForm.

[0017] Compared with the prior art, the present invention has the following beneficial effects: (1) The method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles of the present invention can accurately predict the distribution position of coarse-grained defects on the surface of aluminum alloy profiles, and can also individually quantify the degree of recrystallization, grain size and recrystallization grain coarsening rate at each position of the profile, thereby realizing accurate prediction of local coarse-grained defects in high-strength aluminum alloy extruded profiles and reducing the blindness and contingency of coarse-grained defect prediction. It has important theoretical guidance and practical significance for local coarse-grained evaluation of high-strength aluminum alloys, selection of extrusion process parameters and die structure design.

[0018] (2) The present invention proposes for the first time a method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles. This method can provide a basis and reference for the selection of extrusion process parameters and die structure design of high-strength aluminum alloy profiles.

[0019] (3) The method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles of the present invention can effectively predict coarse-grained defects in surface and interface regions such as the coarse-grained area on the surface of solid profiles and the longitudinal welding interface area of ​​shunt welding extrusion. It can also calculate specific parameters such as the recrystallization fraction, average size of recrystallized grains, and grain coarsening rate at different positions of the profile, and effectively realize real-time detection of recrystallization and grain coarsening behaviors during profile extrusion.

[0020] (4) The present invention first proposes a prediction method for coarse-grained defects on the profile surface, and then uses software fitting to establish a quantitative relationship between the experimental conditions of the extrusion process, the recrystallization fraction, the average size of the recrystallized grains, and the grain coarsening rate. Not only is the method simple and practical, but the calculation results are accurate, making the evaluation of coarse grains on the surface of high-strength aluminum alloys and coarse grains in the longitudinal welds more precise and targeted, greatly reducing the randomness and blindness of coarse-grained defects during profile extrusion, and having important theoretical guidance and practical significance for the prediction of coarse-grained defects in high-strength aluminum alloys. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. 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.

[0022] Figure 1 The simulation prediction results and experimental results comparison of the recrystallization fraction and average recrystallized grain size at different positions of the extruded profile are shown in the figure. Figure 2 This is a comparison chart between the simulation prediction results and the experimental results of the coarse grain distribution on the surface of the extruded profile; Figure 3 This is a comparison chart between the simulation prediction results and the experimental results of coarse-grained defects on the surface and weld position of the shunt welded extruded plate. DETAILED DESCRIPTION

[0023] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those generally understood by those of ordinary skill in the art to which the present application belongs. It should be noted that the present invention is not limited to the following embodiments, and the embodiments and descriptions are only intended to illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and modifications, which all fall within the scope of the present invention to be protected. The scope of the present invention to be protected is defined by the attached claims and their equivalents.

[0024] Example 1 This embodiment provides a method for predicting coarse-grained defects on the surface of a high-strength aluminum alloy extruded profile, comprising the following steps: (1) A 2195 high-strength aluminum alloy cylinder (Φ68×170 mm) was used as the experimental material. The profile was extruded on a 400-ton horizontal extruder. The preheating temperature of the extrusion die was 450°C, the preheating temperature of the extrusion barrel was 400°C, the preheating temperature of the billet was 460°C, and the extrusion speed was 1.0 mm / s. After extrusion treatment, the extruded profile was obtained.

[0025] Among them, the cross section of the extruded profile controlled by the extrusion die includes: convex fillets, concave fillets, flat surfaces, and different width-to-thickness ratio areas. Specifically, the extruded profile has 3 different width-to-thickness ratio areas, and the width-to-thickness ratios of each area are 1:1 (circular), 1:1 (square), 5.1:1 and 10.5:1 respectively; the extruded profile has 7 convex fillets, one of which has a radius of 3.25mm, two of which have a radius of 1mm, and four of which have a radius of 0.2mm; the extruded profile has 6 concave fillets, two of which have a radius of 0.2mm, two of which have a radius of 0.5mm, and two of which have a radius of 1mm.

[0026] (2) The extruded profile obtained by the extrusion treatment in step (1) is subjected to a solution treatment, the solution temperature is controlled to be 500° C., and the solution treatment time is controlled to be 1 h, to obtain a solution profile.

[0027] (3) Sampling different characteristic positions (i.e., positions with different strains) of the extruded profile of step (1) and the solid solution profile of step (2) to obtain samples; after cold mounting the samples, first metallographic polishing to a mirror surface is performed, and then the samples are removed from the mounting material and electrolytic polishing is performed to remove the surface stress layer to obtain electron backscatter diffraction EBSD characterization samples; then the EBSD characterization samples are placed in a ZEISS Gemini-300 electron microscope equipped with an EBSD accessory for electron backscatter diffraction EBSD characterization to obtain EBSD characterization data; the EBSD characterization data are analyzed and statistically analyzed by HKL-Channel5 software to obtain the recrystallization fraction and average size of recrystallized grains at each characteristic position of the extruded profile; and the average size of the grains after coarsening (i.e., the grain size after full growth) at each characteristic position of the solid solution profile.

[0028] In the metallographic polishing process, diamond polishing agent and silica sol polishing agent are used in turn for polishing; the electrolytic polishing is performed by using a perchloric acid-ethanol mixed solution with a volume ratio of 1:9 as the electrolytic polishing liquid, and electrolyzing at a temperature of 25°C for 10s.

[0029] (4) The extrusion process of step (1) was numerically simulated using QForm forging extrusion heat treatment simulation software. The extrusion deformation process conditions in the numerical simulation were set to be consistent with the actual extrusion conditions of step (1); that is, the extrusion die preheating temperature was set to 450°C, the extrusion barrel preheating temperature was set to 400°C, the billet preheating temperature was set to 460°C, the extrusion speed was set to 1.0 mm / s, and the friction and heat transfer conditions adopted the default hot extrusion conditions of the QForm software.

[0030] (5) After simulation with QForm software, the physical field quantities at different positions of the extruded profile are obtained, and the temperature, strain and strain rate at each of the characterization positions of the extruded profile in step (3) are obtained and recorded.

[0031] (6) The 2195 alloy cylindrical specimen was prepared by machining, with the diameter of the specimen controlled to be 8 mm and the height to be 12 mm, to obtain a compression specimen.

[0032] (7) A thermocouple was welded in the middle of the length direction of the compression specimen, and hot compression tests were carried out under different test conditions on a Gleeble 1500 thermal simulation testing machine to obtain the corresponding hot compression specimens.

[0033] The different test conditions of the hot compression test are: the deformation temperature is one of the following: 400°C, 450°C, 500°C and 550°C; the strain rate is one of the following: 0.01s -1 , 0.1s -1 , 1s -1 and 10s -1; The compression amount is 70% of the height of the compressed specimen, corresponding to a true strain of 1.2.

[0034] (8) The hot compression sample obtained in step (7) is cut open along the axis, and a sample is taken from the middle position, and then processed into an electron backscatter diffraction (EBSD) characterization sample; then, EBSD characterization is performed to obtain the recrystallization fraction and the average size of the recrystallized grains at that position.

[0035] The sample preparation method, EBSD characterization method and data statistics method for electron backscatter diffraction EBSD characterization are consistent with step (3).

[0036] (9) The deformation parameter data and the corresponding recrystallization fraction and average recrystallized grain size described or obtained in steps (3), (4), (7), and (8) are summarized as shown in Table 1 below: Table 1 Summary of deformation parameter data and corresponding recrystallization fraction and average recrystallized grain size

[0037] (10) According to the data in Table 1 above, the dynamic recrystallization fraction X drx and the average size of recrystallized grains D drx Fitting to temperature T , strain rate and strain ε The quantitative relationship between the physical field quantity of extrusion deformation and the degree of recrystallization and the average size of recrystallized grains is established as a function of . The Levenberg-Marquardt algorithm is used to calculate the unknown parameters in the functional relationship. The two functional relationships after fitting are shown in formulas (1) and (2): (1); In formula (1), Z is the Zener-Hollomon parameter, which can be further expressed as a function of strain rate and temperature, as shown in formula (m): (m); In formula (m), is the strain rate; T is the deformation temperature; R is the comprehensive gas constant, which is 8.314 J·(mol·K) -1 ; Q is the deformation activation energy, which can be reasonably taken as 246 kJ·mol according to existing technologies (such as relevant literature). -1 .

[0038] (2);

[0039] In formula (2), D0 is the average grain size of the aluminum alloy profile before extrusion treatment; R is the comprehensive gas constant, which is 8.314 J·(mol·K) -1 .

[0040] In formula (1), γ drx , α drx , β drx , m drx 、n drx And λ in formula (2) drx , p drx , q drx , r drx , Q drx is the material constant to be determined, which is determined by fitting the experimental data in Table 1. The fitting results are shown in Table 2 below: Table 2 Specific parameters of formula (1) and formula (2) (11) The grain growth rate formula is set as shown in formula (3): (3); In formula (3), v gb is the grain growth rate; M is the grain boundary mobility, which can be further expressed as ; P represents the driving force for grain boundary migration, which can be further expressed as ; P sz represents the grain boundary migration resistance, which can be further expressed as ; In the above parameters, R c , R rex Respectively represent the average radius of recrystallized grains and the radius of fully grown grains, where R c Calculated by formula (2), R rex According to experimental characterization (i.e., half of the average size of the solid solution profile grains after coarsening), other parameters are obtained through existing technologies (such as relevant literature, etc.) to obtain corresponding reasonable values. Other specific parameters in the calculation of formula (3) and its related variables are shown in Table 3 below: Table 3 Specific parameters in the calculation of formula (3) and its related variables In Table 3, δ is the grain boundary thickness; D Grain boundary self-diffusion coefficient; b is the Burgers vector; K is the Boltzmann constant; Q diff is the activation energy of grain boundary diffusion, and its value is determined from the literature; γ b is the interfacial energy per unit area between the second phase particles and the aluminum matrix, which was determined from the literature; c is constant, determined from the literature; f v and r represent the volume fraction and average size of the second phase particles in the aluminum alloy profiles, respectively, which are determined by TEM characterization experiments.

[0043] (12) The calculation formulas of equations (1)-(3) and their related parameters were programmed using the Lua language and embedded into the subroutine module of the finite element numerical simulation software QForm. After obtaining the numerical values ​​of the aluminum alloy profile extrusion process (extrusion die preheating temperature, extrusion barrel preheating temperature, billet preheating temperature, extrusion speed), the subroutine calculation was performed to predict the recrystallization fraction and average recrystallized grain size at different positions on the cross section of the extruded profile. The comparison between the predicted results and the experimental results is shown in Figure 2. Figure 1 shown.

[0044] Figure 1 (a) and (b) show the simulated predicted recrystallization fractions and average recrystallized grain size distribution cloud diagrams at each position of the profile; it can be seen that the recrystallization fractions at points 1, 2, and 3 are 66.3%, 27.5%, and 20.2%, respectively, and the average recrystallized grain sizes are 2.85 μm, 4.05 μm, and 4.63 μm, respectively.

[0045] Figure 1 Figures (c) to (e) in the figure show the EBSD recrystallization images at the corresponding positions of points 1, 2, and 3 of the actual extruded profile, and the recrystallization ratio and the average size of the recrystallized grains are statistically analyzed; it can be seen that the predicted values ​​of the numerical simulation at the corresponding positions are relatively close to the experimental results. The above results show that the model established by the method of this embodiment can more accurately predict the position, ratio and average size of the recrystallized grains during the extrusion hot deformation of the 2195 alloy.

[0046] (13) The grain growth rate is calculated using a subroutine. The position with a high grain growth rate on the cross section of the extruded profile corresponds to the area where grain coarsening is likely to occur during the solution treatment, thereby realizing the prediction of the coarse grain defect area on the surface of the extruded profile. The solution-treated profile in step (2) is polished and surface etched, and metallographic observation and characterization are performed to verify the accuracy of the method of this embodiment for the coarse grain distribution position of the extruded profile. The comparison between the predicted results and the experimental observation results is as follows: Figure 2 shown.

[0047] The surface was first etched with a 110 g / L NaOH aqueous solution and then ultrasonically cleaned with a 30% volume concentration HNO3 solution.

[0048] Figure 2 Figure (a) shows the simulated predicted grain growth rate distribution cloud diagram on the profile cross section. The red area represents the location where the grains have a faster growth rate and the risk of forming coarse grain defects in the subsequent solution treatment is higher. Figure 2 Figure (b) shows the low-magnification microstructure of the cross-section of the solid solution profile sample after solution treatment. It can be seen that the surface coarse grain distribution has a high degree of overlap with the predicted coarse grain risk position.

[0049] In order to more clearly show the surface structure characteristics at different characteristic positions of the profile, Figure 2 Figures (c) to (h) in the figure respectively show the high-magnification metallographic photos of the characteristic positions of the solid solution state profile after solution treatment, corresponding to Figure 2 It can be seen that the coarse-grained layer is thicker in the convex corner feature area (1, 4), the coarse-grained layer is thinnest on the surface of the concave corner (2, 5), and the coarse-grained layer formed on the straight surface (3, 6) is of medium thickness. Figure 2 The predicted high-risk distribution position of coarse grains in Figure (a) is consistent.

[0050] The above results show that the model established in this embodiment and the prediction method proposed can more accurately predict the distribution position of coarse-grained defects on the surface of high-strength aluminum profiles.

[0051] Example 2 This embodiment provides a method for predicting surface coarse grain defects and weld coarse grain defects of high-strength aluminum alloy extrusions, comprising the following steps: (1) 2195 aluminum-lithium alloy (Φ120×400mm) was used as the experimental material. The profile was extruded on an 800-ton horizontal extruder. The preheating temperature of the extrusion die was 450℃, the preheating temperature of the extrusion barrel was 400℃, and the preheating temperature of the billet was 450℃. The extrusion speed was 2.0mm / s. After extrusion treatment, aluminum-lithium alloy extruded sheets with longitudinal welds were obtained.

[0052] In the extrusion process, a diversion welding plate extrusion die is used, and a longitudinal weld is formed in the middle of the extruded plate through the diversion hole and diversion bridge structure of the upper die of the extrusion die; the cross-sectional size of the extruded plate is 60.5×4.0mm 2 , the longitudinal weld is located in the middle of the width of the extruded sheet.

[0053] (2) The aluminum-lithium alloy extruded sheet with a longitudinal weld was solution treated at a temperature of 515°C and a time of 1 h to obtain a solution state sheet. Samples were then taken from the longitudinal weld, the flat surface and the end of the solution state sheet. The solution state sheet samples were mechanically polished and corroded with a tri-acid solution, and then metallographic observation and characterization were performed to verify the accuracy of the subsequent prediction of the distribution position of coarse grain defects.

[0054] The specific composition and ratio of the three-acid solution are: 0.5 mL HF, 18 mL HCl, 7 mL HNO3 and 42 mL H2O.

[0055] (3) The QForm forging extrusion heat treatment simulation software is used to perform numerical simulation on the plate extrusion process of step (1), and the extrusion deformation process conditions in the numerical simulation are set to be consistent with the actual extrusion conditions of step (1); and the recrystallization fraction, average recrystallized grain size, grain growth rate mathematical model established in steps (9)-(12) of Example 1 and the subroutine of the finite element numerical simulation software QForm are used to predict the grain coarsening at each position of the plate; and the predicted results are compared with the metallographic observation characterization results in step (2). The results are as follows: Figure 3 shown.

[0056] Figure 3 Figure (a) shows the grain growth rate distribution cloud map on the cross section of the extruded plate obtained by simulation, and the red area is the high-risk area for coarse grain production. Figure 3 Figures (b) to (d) show the longitudinal weld, flat surface and end fillet position of the solid solution plate after solution treatment (corresponding to Figure 3 Metallographic structure photos of the 1, 2, and 3 positions in Figure a. Figure 3 It can be seen that there is a coarsened grain structure at the longitudinal weld, the end of the plate, and the surface of the plate in the extruded plate, while the inside of the extruded plate presents a fine grain structure; at the same time, the thickness of the coarse grain layer at the end of the extruded plate and the longitudinal weld is thicker, while the thickness of the coarse grain layer at the straight surface is relatively thin. The above experimental phenomenon is consistent with the coarse grain risk area predicted by simulation, indicating that the prediction method proposed in this embodiment has good prediction accuracy for the distribution position of surface defects of extruded profiles and coarse grain defects in welds.

[0057] Unless otherwise specified, all percentages used in the present invention are by mass.

[0058] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles, characterized in that: The steps include: Step S001, extruding the aluminum alloy profile to obtain an extruded profile; Step S002, performing a solid solution treatment on the extruded profile to obtain a solid solution profile; Step S003, sampling each characteristic position of the extruded profile to obtain the extruded profile sample and then characterizing it to obtain the recrystallization fraction and the average size of the recrystallized grains at each characteristic position of the extruded profile; sampling each characteristic position of the solid solution profile to obtain the solid solution profile sample and then characterizing it to obtain the average size of the grains at each characteristic position of the solid solution profile after coarsening; Step S004, performing a hot compression test on the aluminum alloy profile to obtain a hot compression sample; Step S005, sampling and characterizing the middle position of the hot compression sample to obtain the recrystallization fraction and average size of recrystallized grains at the middle position of the hot compression sample; Step S006, numerically simulating the extrusion process of the aluminum alloy profile to obtain the physical field quantity of each characteristic position of the extruded profile; The physical field quantities include: temperature, strain, and strain rate; Step S007, establishing a quantitative relationship model between the physical field quantity and the recrystallization fraction and a quantitative relationship model between the physical field quantity and the average size of the recrystallized grains respectively through curve fitting and linear regression; Step S008, calculating the driving force of grain boundary migration according to the average size of recrystallized grains at each characteristic position of the extruded profile and the average size of grains at each characteristic position after coarsening after solution treatment, and establishing a recrystallized grain growth rate prediction model; Step S009, embedding the quantitative relationship model and recrystallization grain growth rate prediction model of step S007 into finite element numerical simulation software; Step S010, obtaining numerical values ​​of the extrusion process of the aluminum alloy profile, and performing calculations using finite element numerical simulation software embedded with a quantitative relationship model and a recrystallization grain growth rate prediction model to obtain prediction results of coarse grain defects on the surface of the high-strength aluminum alloy extruded profile.

2. The method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles according to claim 1, characterized in that: It also includes the following steps: Step S011, perform metallographic observation and characterization on the solid solution profile sample of step S003 to obtain a metallographic observation and characterization result, and then compare the metallographic observation and characterization result with the prediction result obtained in step S010 to verify the prediction accuracy of step S010.

3. The method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles according to claim 1, characterized in that: In step S001, the cross section of the extruded profile includes at least: an outer convex rounded corner, an inner concave rounded corner, and a flat surface.

4. The method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles according to claim 1, characterized in that: In the step S002, the solution treatment temperature is not less than 500° C., and the solution treatment time is not less than 1 hour.

5. The method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles according to claim 1, characterized in that: In the step S003, the characteristic positions of the extruded profile at least include: an outer convex rounded corner, an inner concave rounded corner, and a flat surface; The characteristic positions of the solid solution state profile at least include: external convex fillet, internal concave fillet, and flat surface; The sampling position for the solid solution state profile is the same as the sampling position for the extruded state profile.

6. The method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles according to claim 1, characterized in that: In the step S004, in the test conditions of the thermal compression test, the deformation temperature is one of the following: 400°C, 450°C, 500°C or 550°C; the strain rate is one of the following: 0.01s -1 , 0.1s -1 , 1s -1 or 10s -1 ; The compression amount is 70% of the height of the compressed specimen, corresponding to a true strain of 1.

2.

7. The method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles according to claim 1, characterized in that: In step S007, the quantitative relationship model between the physical field quantity and the recrystallization fraction is shown in formula (1): （1）； In formula (1), X drx is the recrystallization fraction; ε For strain; γ drx The value is -0.92; α drx The value is 33.47; β drx The value is -1.35×10 10 ; m drx The value is -5.76; n drx The value is 0.90; Z is the Zener-Hollomon parameter; The quantitative relationship model between the physical field quantity and the average size of the recrystallized grains is shown in formula (2): （2）； In formula (2), D drx is the average size of recrystallized grains; D0 is the average grain size of the aluminum alloy profile before extrusion treatment; ε For strain; is the strain rate; T is temperature; λ drx The value is 3.77×10 3 ; p drx The value is -0.62; q drx The value is -0.18; r drx The value is -0.03; Q drx The value is -2.36×10 4 .

8. The method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles according to claim 7, characterized in that: In step S008, the recrystallization grain growth rate prediction model is shown in formula (3): （3）； In formula (3), v gb is the recrystallization grain growth rate; M is the grain boundary mobility; P It is the driving force for grain boundary migration; P sz is the grain boundary migration resistance; Said M The calculation method is ; Said P The calculation method is ; Said P sz The calculation method is ; in, R c is the average radius of recrystallized grains, calculated by formula (2); R rex is the average radius of the grain after coarsening, which is obtained by characterizing the solid solution profile in step S003; δ The value is 8.75×10 -14 m 3 / s; b The value is 2.86×10 -10 m; Q diff The value is 100 kJ / mol; R The value is 8.314 J / mol·K; c The value is 1.5; γ b The value is 0.324J / m 2 ; f v The value is 0.052; r The value is 0.165μm.

9. The method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles according to claim 1, characterized in that: In the step S003, after the extruded profile sample is characterized by electron backscatter diffraction EBSD, HKL-Channel5 software is used for statistical analysis to obtain the recrystallization fraction and average recrystallized grain size of each characteristic position of the extruded profile; After the solid solution profile samples were characterized by electron backscatter diffraction EBSD, the HKL-Channel5 software was used for analysis and statistics to obtain the average size of the grains after coarsening at each characteristic position of the solid solution profile; In the step S005, the middle position of the hot compression sample is sampled and characterized by electron backscatter diffraction EBSD, and the HKL-Channel5 software is used for statistical analysis to obtain the recrystallization fraction and average recrystallized grain size of the middle position of the hot compression sample.

10. The method for predicting coarse-grained defects on the surface of high-strength aluminum alloy extruded profiles according to claim 1, characterized in that: In the step S006, the extrusion process of the aluminum alloy profile is numerically simulated using QForm forging extrusion heat treatment simulation software; In step S007, 1stOpt software is used to perform curve fitting and linear regression; In the step S009, the finite element numerical simulation software is a subroutine module of QForm.

Images