A quantitative calculation method for mixed microstructure distribution of titanium alloy based on stereology

Abstract

The application provides a quantitative calculation method of titanium alloy mixed structure morphology distribution based on stereology, establishes a calculation model of titanium alloy lamellar alpha interlaced degree and a calculation model of titanium alloy mixed structure morphology probability, and combines with a quantitative calculation method of titanium alloy mixed structure grain morphology distribution considering lamellar interlaced effect of Java language. Through establishing the calculation model of titanium alloy lamellar alpha interlaced degree and the calculation model of grain morphology distribution probability reflecting the influence of equiaxial alpha phase grain size and lamellar alpha angle, the titanium alloy mixed structure can be better identified, the quantitative analysis of the grain morphology distribution probability of the interlaced lamellar alpha can be carried out, the quantitative analysis result can more comprehensively and truly reflect the microstructure characteristics of the titanium alloy mixed structure. In the modeling process of the lamellar alpha interlaced degree, the multi-attribute decision comprehensive evaluation method is used to determine the weight of the microstructure characteristic parameters, and the reliability and the prediction accuracy of the model are improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of stereology microstructure quantitative characterization, and particularly relates to a quantitative calculation method for mixed microstructure morphology distribution of titanium alloy based on stereology. BACKGROUND

[0002] Titanium alloy is a microstructure sensitive material, and the microstructure morphology evolution in the forming manufacturing process is extremely complex. Moreover, the microstructure morphology characteristics of titanium alloy determine its macroscopic mechanical properties, so accurate quantitative analysis of the microstructure morphology distribution of titanium alloy is the key to establishing a microstructure-mechanical property prediction model. In the mixed microstructure of titanium alloy, there are various morphologies of grains such as equiaxed alpha, grain boundary alpha and lamellar alpha, and the lamellar alpha can be in parallel clusters or interweaving. These complex microstructure morphologies bring great challenges to the quantitative analysis of titanium alloy microstructure.

[0003] The prior art discloses a method for quantitatively analyzing the grain morphology distribution probability by using a two-point correlation function method or a linear path function method. The method determines a line segment with a length of r and a direction of θ, 0° is the horizontal direction, and the counterclockwise direction is positive. The left end point of the line segment is the starting point, and the right end point is the terminal point. The pixel points in the image are scanned point by point, and the distribution probability of the line segment starting point and terminal point in the same phase or different phases and different microstructure grains is calculated.

[0004] However, the method cannot realize the quantitative analysis of the interweaving degree of lamellar alpha, nor can it realize the statistical analysis of the lamellar alpha and lamellar alpha grain morphology distribution probability, which makes the quantitative results unable to comprehensively and truly reflect the mixed microstructure characteristics of titanium alloy, and inevitably leads to low calculation accuracy of the microstructure-mechanical property prediction model, resulting in inaccurate control of the mechanical properties of titanium alloy forming manufacturing. SUMMARY

[0005] The technical problem to be solved by the application is to provide a quantitative calculation method for mixed microstructure morphology distribution of titanium alloy based on stereology in view of the deficiencies of the prior art. The method first quantitatively analyzes and comprehensively evaluates the length of lamellar alpha, the uniformity of lamellar alpha angle distribution, the number of intersection points of lamellar alpha per unit area and the uniformity of intersection point distribution of lamellar alpha based on the multi-attribute decision-making comprehensive evaluation method of simple weighted method, so as to describe the interweaving degree of titanium alloy lamellar alpha. On this basis, by considering the equiaxed alpha grain size and the lamellar alpha angle, a quantitative calculation method for mixed microstructure of titanium alloy with multiple phases and multiple morphologies is established based on the nearest neighbor function.

[0006] The application solves the technical problems by adopting the technical scheme of establishing a titanium alloy sheet layer alpha interlacing degree calculation model and a titanium alloy mixed organization form probability calculation model based on a multi-attribute decision comprehensive evaluation method and a nearest neighbor function method, and developing a titanium alloy mixed organization grain form distribution quantitative calculation method considering sheet layer interlacing effect in combination with Java language;

[0007] The method comprises the following steps:

[0008] S1, combining the influences of the titanium alloy sheet layer alpha length, the sheet layer alpha angle distribution uniformity, the intersection number of the sheet layer alpha in unit area and the intersection distribution uniformity of the sheet layer alpha on the sheet layer alpha interlacing degree, a calculation model of the titanium alloy sheet layer alpha interlacing degree is established;

[0009] S2, based on the nearest neighbor function, considering the multi-phase and multi-form organization distribution characteristics of the equiaxed alpha, the sheet layer alpha and the beta matrix in the titanium alloy microstructure, a grain form distribution probability calculation model reflecting the influences of the equiaxed alpha phase grain size and the sheet layer alpha angle is established;

[0010] S3, based on the stereology two-dimensional graph, the sheet layer alpha length, the sheet layer alpha angle distribution variation coefficient, the intersection number of the sheet layer alpha in unit area and the intersection pattern uniformity of the sheet layer alpha under different process parameters are quantitatively counted, the weight coefficients of different microstructure characteristic parameters in S1 are calculated, and on this basis, the interlacing degree of the titanium alloy sheet layer alpha is calculated;

[0011] S4, based on the stereology two-dimensional graph, the equiaxed alpha grain size, the volume fraction, the sheet layer alpha grain number, the length, the thickness, the angle, the volume fraction and the intersection number under different process parameters are quantitatively counted, the grain form distribution probability calculation model reflecting the influences of the equiaxed alpha phase grain size and the sheet layer alpha angle in S2 is combined, and the probability P and the probability density F of the sheet layer alpha distribution around the spherical grain and the other intersection distribution around the sheet layer alpha intersection under different process parameters are calculated.

[0012] Further, the calculation model in S1 is specifically as follows:

[0013]

[0014] In the formula, z i is the sheet layer alpha interlacing degree of the i th process scheme;

[0015] W j (j=1~4) is the weight of different microstructure characteristic parameters, the sheet layer alpha length, the sheet layer alpha angle distribution uniformity, the intersection number of the sheet layer alpha in unit area and the intersection distribution uniformity of the sheet layer alpha;

[0016] r ijis the normalized value of the jth microstructure characteristic parameter in the ith process scheme;

[0017] C.V i , G i and U i are the average length of lamella α in the ith process scheme, the coefficient of variation of the angle distribution of lamella α, the number of intersections of lamella α per unit area and the uniformity of the intersection pattern of lamella α, respectively;

[0018] n is the total number of lamella α, and l is the length of a single lamella α in μm;

[0019] t is the number of angles of lamella α in a single interval;

[0020] is the average number of angles of lamella α in each interval;

[0021] c is the total number of intervals, which can be expressed as:

[0022] g is the number of intersections of lamella α;

[0023] A is the area of the region to be measured (μm 2 );

[0024] a is the exclusive circle area of the intersection (μm 2 ).

[0025] Further, W j can be expressed as:

[0026]

[0027] In the formula, e j is the entropy value of the jth microstructure characteristic parameter, which can be expressed as:

[0028]

[0029] In the formula, m is the total number of process schemes taken.

[0030] Further, in S2, when calculating the distribution probability of lamella α around the spherical grain, lamella α is regarded as an equivalent spherical grain with a radius of R e,i , and the equivalent radius R e,i can be expressed as:

[0031]

[0032] In the formula, a i and b i are the lengths of the major and minor axes of the ith lamella α in μm, respectively;

[0033] li is the distance between the reference point and the geometric center of the lamella grain;

[0034] w i is the angle between the line connecting the reference point and the geometric center of the lamella grain and the long axis of the lamella;

[0035] Therefore, the probability P i (r) that the lamella a is located within a distance r from the center of the equiaxial a with a radius R 12,i (r) can be represented as:

[0036]

[0037] wherein, P i (r) represents the probability that the equivalent spherical grain is located outside a distance r from the reference point when the reference point is the center of the equiaxial a with a radius R

[0038]

[0039] wherein, M is the number of lamellas a;

[0040] A is the area of the region to be measured in μm 2 ;

[0041] φ 2,i represents the volume fraction of the equivalent spherical grain when the reference point is the center of the equiaxial a with a radius R i ;

[0042] represents the average radius of the equivalent spherical grain in μm when the reference point is the center of the equiaxial a with a radius R i ;

[0043] represents the average area of the equivalent spherical grain in μm 2 when the reference point is the center of the equiaxial a with a radius R i ;

[0044] Further, the probability density F i (r) that the lamella a is located within a distance r from the center of the equiaxial a with a radius R 12,i (r) can be represented as:

[0045]

[0046] In addition, the probability P 33 (r) that other intersection points are distributed within a distance r from the intersection point of the lamella a is used to describe the distribution of other lamellas a around the lamella a, the higher the degree of aggregation and uniformity of the distribution of the intersection points of the lamella a, the higher the degree of interweaving of the lamella a, and the probability P33 (r) and its probability density F 33 (r) are respectively represented as:

[0047]

[0048]

[0049] In the formula, represents the probability that the intersection point of the lamellar alpha is located outside the distance r around the reference point;

[0050] K is the total number of intersection points of the lamellar;

[0051] A is the area of the region to be measured μm 2 .

[0052] Further, in S3, Image Pro-plus 6.0 software is used to quantitatively analyze the length of lamellar alpha, the coefficient of variation of the angle distribution of lamellar alpha, the number of intersection points of lamellar alpha per unit area and the uniformity of the intersection point pattern of lamellar alpha under different process parameters.

[0053] In S4, Image Pro-plus 6.0 software is also used to quantitatively analyze the grain size, volume fraction of equiaxed alpha, and the number, length, thickness, angle, volume fraction and intersection point number of lamellar alpha under different process parameters.

[0054] Further, the weight coefficients of different microstructure characteristic parameters are calculated using Java language.

[0055] Compared with the prior art, the present application has the following advantages:

[0056] The present application can better identify the interlaced lamellar alpha in the mixed microstructure of titanium alloy and quantitatively analyze the grain morphology distribution probability of the interlaced lamellar alpha by establishing a calculation model of the interlacing degree of lamellar alpha and a calculation model of the grain morphology distribution probability reflecting the influence of equiaxed alpha grain size and lamellar alpha angle. This makes the quantitative analysis results more comprehensive and true to reflect the microstructure characteristics of the mixed microstructure of titanium alloy. Moreover, in the modeling process of the interlacing degree of lamellar alpha, a multi-attribute decision-making comprehensive evaluation method is used to determine the weight of the microstructure characteristic parameters, which improves the reliability and prediction accuracy of the model. It lays a theoretical foundation for subsequent microstructure-mechanical property modeling and accurate control of the mechanical properties of titanium alloy forming manufacturing. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 is the lamellar microstructure of the titanium alloy in the embodiment of the present application;

[0058] Figure 2 is the dual-state microstructure of the titanium alloy in the embodiment of the present application;

[0059] Figure 3 P is the probability of the distribution of the lamellar alpha around the spherical grain of the dual-state structure of the titanium alloy in the embodiment of the present application 12 ;

[0060] Figure 4 F is the probability density of the distribution of the lamellar alpha around the spherical grain of the dual-state structure of the titanium alloy in the embodiment of the present application 12 ;

[0061] Figure 5 P is the probability of the distribution of the other intersection around the intersection of the lamellar alpha of the dual-state structure of the titanium alloy in the embodiment of the present application 33 ;

[0062] Figure 6 F is the probability density of the distribution of the other intersection around the intersection of the lamellar alpha of the dual-state structure of the titanium alloy in the embodiment of the present application 33 . DETAILED DESCRIPTION

[0063] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0064] In the embodiment 1, the present application provides a technical solution: a quantitative calculation method of the distribution of the mixed microstructure of titanium alloy based on stereology, which comprises the following steps:

[0065] S1, combining the influences of the length of the lamellar alpha, the uniformity of the angle distribution of the lamellar alpha, the number of the intersections of the lamellar alpha in the unit area and the uniformity of the distribution of the intersections of the lamellar alpha on the interweaving degree of the lamellar alpha, a calculation model of the interweaving degree of the lamellar alpha of the titanium alloy is established;

[0066] The calculation model is specifically as follows:

[0067]

[0068] In the formula, z i is the interweaving degree of the lamellar alpha of the i th process scheme;

[0069] W j (j=1~4) are different microstructure characteristic parameters, the weight of the length of the lamellar alpha, the uniformity of the angle distribution of the lamellar alpha, the number of the intersections of the lamellar alpha in the unit area and the uniformity of the distribution of the intersections of the lamellar alpha;

[0070] r ijis the normalized value of the jth microstructure characteristic parameter in the ith process scheme;

[0071] C.V i , G i and U i are the average length of lamella α in the ith process scheme (μm), the coefficient of variation of the angle distribution of lamella α, the number of intersections of lamella α per unit area and the uniformity of the intersection pattern of lamella α, respectively;

[0072] n is the total number of lamella α, and l is the length of a single lamella α (μm);

[0073] t is the number of angles of lamella α in a single interval;

[0074] is the average value of the number of angles of lamella α in each interval;

[0075] c is the total number of intervals, which can be expressed as:

[0076] g is the number of intersections of lamella α;

[0077] A is the area of the region to be measured (μm 2 );

[0078] a is the exclusive circle area of the intersection (μm 2 ).

[0079] W j can be expressed as:

[0080]

[0081] In the formula, e j is the entropy value of the jth microstructure characteristic parameter, which can be expressed as:

[0082]

[0083] In the formula, m is the total number of process schemes taken.

[0084] S2, based on the nearest neighbor function, considering the multi-phase and multi-morphology distribution characteristics of equiaxed α, lamellar α and β matrix in titanium alloy microstructure, a grain morphology distribution probability calculation model reflecting the influence of equiaxed α grain size and lamellar α angle is established; when calculating the distribution probability of lamellar α around spherical grains, lamellar α is regarded as an equivalent spherical grain with a radius of R e,i , and the equivalent radius R e,i can be expressed as:

[0085]

[0086] In the formula, a i and bi respectively the length of the long, short semi-axis of the i-th lamella a in pm;

[0087] l i the distance between the reference point and the geometric center of the lamella grain;

[0088] w i the angle between the line connecting the reference point and the geometric center of the lamella grain and the long axis of the lamella;

[0089] Therefore, the probability P i (r) that the lamella a is located within a distance r from the center of the equivalent sphere a with radius R 12,i can be expressed as:

[0090]

[0091] wherein P (r) denotes the probability that the equivalent spherical grain is located outside a distance r from the reference point when the reference point is the center of the equivalent sphere a with radius R i can be expressed as:

[0092]

[0093] wherein M is the number of lamellas a;

[0094] A is the area of the region to be measured in pm 2 ;

[0095] φ 2,i denotes the volume fraction of the equivalent spherical grain when the reference point is the center of the equivalent sphere a with radius R i ;

[0096] denotes the average radius of the equivalent spherical grain in pm when the reference point is the center of the equivalent sphere a with radius R i ;

[0097] denotes the average area of the equivalent spherical grain in pm 2 when the reference point is the center of the equivalent sphere a with radius R i ;

[0098] The probability density F i (r) that the lamella a is located within a distance r from the center of the equivalent sphere a with radius R 12,i can be expressed as:

[0099]

[0100] In addition, the probability P 33(r) to describe the distribution of other sheet layers α around sheet layer α, the higher the degree of interweaving of sheet layer α, the higher the degree of aggregation and uniformity of the distribution of sheet layer α intersection points, and the probability P of the distribution of other intersection points within a distance r around the sheet layer α intersection point 33 (r) and its probability density F 33 (r) are respectively represented as:

[0101]

[0102]

[0103] In the formula, represents the probability that the sheet layer α intersection point is located outside the distance r around the reference point;

[0104] K is the total number of sheet layer intersection points;

[0105] A is the area of the region to be measured μm 2 .

[0106] S3, based on the two-dimensional graph of stereology, the length of sheet layer α, the coefficient of variation of the angle distribution of sheet layer α, the number of intersection points of sheet layer α per unit area, and the uniformity of the intersection pattern of sheet layer α under different process parameters are quantitatively analyzed using Image Pro-plus 6.0 software, the weight coefficients of different microstructure characteristic parameters in S1 are calculated using Java language, and the interweaving degree of titanium alloy sheet layer α is calculated and obtained on this basis;

[0107] S4, based on the two-dimensional graph of stereology, the grain size, volume fraction of equiaxed α, and the grain number, length, thickness, angle, volume fraction and intersection number of sheet layer α are quantitatively analyzed under different process parameters using Image Pro-plus 6.0 software, and the grain morphology distribution probability calculation model reflecting the influence of equiaxed α grain size and sheet layer α angle is established in S2, the distribution of sheet layer α around spherical grain and the probability P and probability density F of the distribution of other intersection points around the intersection point of sheet layer α under different process parameters are calculated.

[0108] Example 2, quantitative analysis of the interweaving degree of TC17 alloy sheet layer α.

[0109] S1, the calculation model of titanium alloy sheet layer interweaving degree reflecting the influence of microstructure characteristic parameters such as sheet layer α length, sheet layer α angle distribution uniformity, number of sheet layer α intersection points per unit area, and sheet layer α intersection distribution uniformity is established as:

[0110]

[0111] In the formula, z i is the interweaving degree of sheet layer α of the i th process scheme;

[0112] W j (j = 1 ~ 4) are different microstructure characteristic parameters; the length of the lamella α, the uniformity of the angle distribution of the lamella α, the number of intersection points of the lamella α in unit area and the uniformity of the intersection point distribution of the lamella α;

[0113] r ij is the normalized value of the jth microstructure characteristic parameter in the ith process scheme;

[0114] C.V i , G i and U i are the average length of the lamella α in the ith process scheme, the coefficient of variation of the angle distribution of the lamella α, the number of intersection points of the lamella α in unit area and the uniformity of the intersection point pattern of the lamella α, respectively;

[0115] n is the total number of lamella α, and l is the length of a single lamella α in μm;

[0116] t is the number of angles of the lamella α in a single interval;

[0117] is the average value of the number of angles of the lamella α in each interval;

[0118] c is the total number of intervals, which can be represented as:

[0119] g is the number of intersection points of the lamella α; A is the area of the region to be measured in μm 2 ;

[0120] a is the exclusive circle area of the intersection point in μm 2 .

[0121] wherein, W j can be represented as:

[0122]

[0123] In the formula, e j is the entropy value of the jth microstructure characteristic parameter, which can be represented as:

[0124]

[0125] In the formula, m is the total number of process schemes taken.

[0126] S2, carry out high temperature deformation and heat treatment test of TC17 alloy, the high temperature deformation process is: deformation temperature 910℃, deformation degree 40%, strain rate 0.01s -1, after deformation, cooling to 600℃ by 1100s, air cooling, solid solution and aging treatment process is: 800℃ for 4h, water cooling, then 630℃ for 8h, air cooling, to obtain TC17 alloy lamellar structure, as shown in Figure 1 , the lamellar alpha is interlaced.

[0127] S3, based on stereology two-dimensional graphics, using Image Pro-plus 6.0 software to quantitatively analyze the length of lamellar alpha, the coefficient of variation of lamellar alpha angle distribution, the number of intersection points of lamellar alpha per unit area and the uniformity of intersection pattern of lamellar alpha, using Java language to calculate the weight coefficient of different microstructure characteristic parameters in S1, and the calculation results are shown in Table 1 below;

[0128] Table 1 quantitative analysis results and weight coefficients of titanium alloy lamellar structure characteristic parameters

[0129]

[0130] S4, the weight coefficient is brought into the calculation model of the interlacing degree of titanium alloy lamellar alpha in S1, and the interlacing degree z of TC17 alloy lamellar is calculated by Java language i , the greater the value of z i , the better the interlacing degree, z∈[0,1], the calculation results are shown in the table.

[0131] Example 3, quantitative analysis of grain morphology distribution of TC4 alloy duplex structure.

[0132] S1, based on the nearest neighbor function, a grain morphology distribution probability calculation model reflecting the influence of alpha phase grain size and lamellar alpha angle is established, and the lamellar alpha is regarded as an equivalent spherical grain with radius R e,i , the equivalent radius R e,i can be expressed as:

[0133]

[0134] In the formula, a i and b i are the lengths of the long and short half axes of the i-th lamellar alpha, respectively, in μm;

[0135] l i is the distance between the reference point and the geometric center of the lamellar grain;

[0136] w i is the angle between the line connecting the reference point and the geometric center of the lamellar grain and the long axis of the lamellar.

[0137] Therefore, the probability P i (r) that the lamellar alpha is located within a distance r from the isometric alpha with radius R 12,i can be expressed as:

[0138]

[0139] wherein, represents the probability that the equivalent spherical grain is located outside the distance r around the reference point when the reference point is the center of the equiaxed alpha circle with radius R i

[0140]

[0141] wherein, M is the number of lamellae alpha;

[0142] A is the area of the region to be measured μm 2

[0143] φ 2,i represents the volume fraction of the equivalent spherical grain when the reference point is the center of the equiaxed alpha circle with radius R i

[0144] represents the average radius of the equivalent spherical grain μm when the reference point is the center of the equiaxed alpha circle with radius R i

[0145] represents the average area of the equivalent spherical grain μm 2 when the reference point is the center of the equiaxed alpha circle with radius R i

[0146] Similarly, the probability density F 12,i (r) that the lamellae alpha is located within the distance r around the equiaxed alpha circle with radius R i

[0147]

[0148] In addition, the present application uses the probability P 33 (r) that other intersection points are distributed within the distance r around the intersection point of the lamellae alpha to describe the distribution of other lamellae alpha around the lamellae alpha, the higher the degree of aggregation and the degree of uniformity of the distribution of the intersection points of the lamellae alpha, the higher the degree of interweaving of the lamellae alpha, and the probability P 33 (r) and the probability density F 33 (r) thereof respectively are represented as:

[0149]

[0150]

[0151] wherein, represents the probability that the intersection point of the lamellae alpha is located outside the distance r around the reference point; ​​​​​​

[0152] K is the total number of lamellar intersection points;

[0153] A is the area of the region to be measured μm 2 .

[0154] S2, carry out TC4 alloy high temperature deformation and heat treatment test, high temperature deformation process is: deformation temperature 980 DEG C, deformation degree 40%, strain rate 0.1s -1 , argon cooling to room temperature, double annealing and aging treatment process is:

[0155] At 920 DEG C for 1h, water cooling, then 920 DEG C for 1.5h, air cooling, finally 500 DEG C for 6h, air cooling, to obtain TC4 alloy duplex structure, as Figure 2 Indicated.

[0156] Step 3 is based on stereology two-dimensional graphics, using Image Pro-plus 6.0 software to the variable of the model established in step 1, equiaxed alpha grain size, volume fraction and lamellar alpha grain number, length, thickness, angle, volume fraction and intersection number, etc. Quantitative statistics, the statistical results are shown in Table 2 as follows:

[0157] Table 2 the organization characteristic parameters in the probability calculation model of titanium alloy duplex structure grain morphology distribution

[0158]

[0159] S4, using the probability model of S3 to obtain the probability P and the probability density F of the distribution of lamellar alpha around the spherical grain and the distribution of other intersection points around the lamellar alpha intersection in TC4 alloy duplex structure;

[0160] The results are shown in Figure 3 The probability P of the distribution of lamellar alpha around the spherical grain in the titanium alloy duplex structure in the embodiment of the application 12 , Figure 4 The probability density F of the distribution of lamellar alpha around the spherical grain in the titanium alloy duplex structure in the embodiment of the application 12 and Figure 5 The probability P of the distribution of other intersection points around the lamellar alpha intersection in the titanium alloy duplex structure in the embodiment of the application 33 and Figure 6 The probability density F of the distribution of other intersection points around the lamellar alpha intersection in the titanium alloy duplex structure in the embodiment of the application 33 are shown in

[0161] It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting; it is not intended to exclude myriad other embodiments of the present application that other inventors can develop based on the same general inventive concepts embodied by the described embodiments. That is, although the present application is described in terms of particular embodiments and illustrative figures, it should be apparent that the scope of the present application is not limited to these specific embodiments.

[0162] While the embodiments of the application have been shown and described herein, it will be understood by those skilled in the art that many changes, modifications, substitutions and alterations to these embodiments can be made without departing from the principles and spirits of the application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for quantitatively calculating a mixed microstructure distribution of a titanium alloy based on stereology, characterized by, The method comprises the following steps: S1, the influence of the length of titanium alloy sheet layer alpha, the uniformity of sheet layer alpha angle distribution, the number of intersection points of sheet layer alpha in unit area and the uniformity of intersection point distribution of sheet layer alpha on the interweaving degree of sheet layer alpha is combined to establish a calculation model of the interweaving degree of titanium alloy sheet layer alpha; The calculation model is specifically as follows: ； In the formula, is the interlacing degree of the sheet layer α for the i th process scheme; weight for different microstructure characteristic parameters, lamella a length, lamella a angle distribution uniformity, intersection number of lamella a per unit area, and intersection distribution uniformity of lamella a; normalized value of the jth microstructure characteristic parameter in the ith process scheme; and respectively are the average length of the lamellas α in the i-th process variant in μm, the coefficient of variation of the angle distribution of the lamellas α, the number of intersections of the lamellas α per area and the uniformity of the intersection pattern of the lamellas α; n is the total number of sheet layer alpha, l is the length of a single sheet layer alpha in microns; t is the number of sheet layer alpha angles in a single interval; Average number of sheet angles in each interval; c is the total number of intervals, which can be expressed as: ; g is the number of intersection points of sheet layer alpha; A is the area of the region to be measured (pm 2 ) ; Exclusive circle area for intersection (pm 2 ); S2, based on the nearest neighbor function, considering the multi-phase and multi-morphology distribution characteristics of equiaxed alpha, sheet layer alpha and beta matrix in the microstructure of titanium alloy, a grain morphology distribution probability calculation model reflecting the influence of equiaxed alpha grain size and sheet layer alpha angle is established; S3, based on stereology two-dimensional graphics, the length of sheet layer alpha, the coefficient of variation of sheet layer alpha angle distribution, the number of intersection points of sheet layer alpha in unit area and the uniformity of intersection point pattern of sheet layer alpha under different process parameters are quantitatively counted, the weight coefficients of different microstructure characteristic parameters in S1 are calculated, and the interweaving degree of titanium alloy sheet layer alpha is obtained based on this; S4, based on stereology two-dimensional graphics, the grain size, volume fraction of equiaxed alpha, and the number, length, thickness, angle, volume fraction and number of intersection points of sheet layer alpha under different process parameters are quantitatively counted, the grain morphology distribution probability calculation model reflecting the influence of equiaxed alpha grain size and sheet layer alpha angle in S2 is combined, and the probability P and probability density F of sheet layer alpha distribution around spherical grain and other intersection point distribution around sheet layer alpha intersection point under different process parameters are calculated.

2. The method for quantitatively calculating the distribution of mixed microstructure morphology of titanium alloy based on stereology according to claim 1, characterized in that, may be represented as: ； In the formula, is the entropy value of the jth micro-feature parameter, which can be expressed as: ； In the formula, m is the total number of process schemes taken.

3. The method for quantitatively calculating a mixed microstructure distribution of a titanium alloy based on stereology according to claim 2, characterized in that, In S2, when calculating the distribution probability of the lamella a around the spherical grain, the lamella a is regarded as an equivalent spherical grain with a radius of R e,i The equivalent radius R e,i can be expressed as: ； wherein and are the lengths of the long and short semi-axes of the i-th lamella a in pm, respectively. R is the distance of the reference point from the geometric center of the tile grain; is the angle between the line connecting the reference point and the geometric center of the slice layer grain and the long axis of the slice layer; Thus, the probability P 12,i (r) that a lamella α is located within a distance around the equiaxed α grains of radius can be expressed as: ； wherein represents the probability that the equivalent spherical grain is located outside the distance of from the reference point when the reference point is the center of an equilateral α circle with a radius of may be represented as: ； In the formula, M is the number of sheet layer alpha; A is the area of the region under test in μm 2 ; represents the volume fraction of equivalent spherical grains when the reference point is the center of an equiaxed a circle with a radius of r. represents the average radius of the equivalent spherical grains in μm when the reference point is the center of an equiaxed α circle with a radius of represents the average radius of the equivalent spherical grains in μm when the reference point is the center of an equiaxed α circle with a radius of represents the average area of the equivalent spherical grains in μm when the reference point is the center of a circle of radius of an equiaxed α. 2 .

4. The method for quantitatively calculating a mixed microstructure distribution of a titanium alloy based on stereology according to claim 3, characterized in that, The probability density of the lamellae a located within a distance of the equiaxed a with a radius of 0.5 mm can be represented as: P(r) = 1 - exp(-r2 / 2) ； Further, the distance around the intersection point of the sheet layer α the probability of the distribution of other intersection points within the distance to describe the distribution of other sheet layers α around the sheet layer α, the higher the degree of aggregation and the uniformity of the distribution of the intersection points of the sheet layer α, the higher the degree of interweaving of the sheet layer α, and the probability of the distribution of other intersection points within the distance around the intersection point of the sheet layer α and the probability density thereof are respectively represented as: ； ； wherein represents the probability that the sheet layer a intersection point is located at a distance outside the reference point. K is the total number of sheet layer intersection points; A is the area of the region under test in μm 2 .

5. The method for quantitatively calculating a mixed microstructure distribution of a titanium alloy based on stereology according to claim 4, characterized in that, In S3, Image Pro-plus 6.0 software is used to quantitatively count the length of sheet layer alpha, the coefficient of variation of sheet layer alpha angle distribution, the number of intersection points of sheet layer alpha in unit area and the uniformity of intersection point pattern of sheet layer alpha under different process parameters; In S4, Image Pro-plus 6.0 software is also used to quantitatively count the grain size, volume fraction of equiaxed alpha, and the number, length, thickness, angle, volume fraction and number of intersection points of sheet layer alpha under different process parameters.

6. The method for quantitatively calculating a mixed microstructure distribution of a titanium alloy based on stereology according to claim 5, characterized in that, The weight coefficients of different microstructure characteristic parameters are calculated by using Java language.

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