CN108760784B - Quantitative analysis method for metallographic volume fraction gradient distribution of surface layer of cutting processing of dual-phase titanium alloy - Google Patents
Quantitative analysis method for metallographic volume fraction gradient distribution of surface layer of cutting processing of dual-phase titanium alloy Download PDFInfo
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Abstract
The invention discloses a quantitative analysis method for metallographic volume fraction gradient distribution of a surface layer of a dual-phase titanium alloy cutting process. The method comprises the steps of carrying out warp cutting and inlaying on a titanium alloy cutting sample to manufacture a test block, grinding, polishing and corroding the test block to obtain a tested surface, scanning the tested surface by using a scanning electron microscope to obtain an electron microscope image, converting the electron microscope image into a gray image through graying, trimming the electron microscope image to obtain an effective electron microscope image, dividing the effective electron microscope image into an alpha phase region and a beta phase region according to gray levels, and carrying out binarization processing on the effective electron microscope image. And carrying out discrete layering along the cutting depth direction, counting the number of alpha-phase pixels and beta-phase pixels in each layered image, wherein the percentage of the number of the alpha-phase pixels and the number of the beta-phase pixels in the total number of pixels of each layered image is the volume fraction of the alpha phase and the beta phase in the layered image, and then obtaining the volume fraction gradient distribution characteristic of the metallographic phase of the side section of the cutting sample according to the volume fraction of the alpha phase and the beta phase in each layered image.
Description
Technical Field
The invention relates to the technical field of the characterization and evaluation of microstructure distribution characteristics of a surface layer machined by cutting a metal material, in particular to a quantitative analysis method for the volume fraction gradient distribution of a metallographic phase of a surface layer machined by cutting a two-phase titanium alloy.
Background
Titanium alloys can be classified into alpha-type titanium alloys, beta-type titanium alloys and alpha + beta-type titanium alloys according to the type of the contained metallographic phase. The physical and mechanical properties of the α + β type dual phase titanium alloy are influenced by the properties of the α and β phases themselves, and also depend on the volume fractions of the α and β phases, and the like.
The high temperatures, high stresses and high strain rates generated by the cutting process cause phase changes in the machined surface layer material, resulting in a different volume fraction of the alpha and beta phases of the machined surface layer than the volume fraction of the alpha and beta phases in the matrix material.
At present, a method for quantitatively analyzing the volume fraction of a metallographic phase is mainly an X-ray diffraction method (XRD), but the method cannot be used for quantitatively describing the metallographic gradient distribution condition of a side section of a cut sample, on one hand, the focus size of an X-ray diffractometer is large and is generally a long and narrow rectangle (millimeter level), the measured volume fraction of the metallographic phase is the average value of the rectangular area, on the other hand, the depth of an area where the material is subjected to phase change from the surface of a cutting process is small (micron level), and the X-ray diffractometer cannot achieve the high resolution.
Disclosure of Invention
The invention provides a quantitative analysis method for metallographic volume fraction gradient distribution of a surface layer material of a dual-phase titanium alloy cutting process. The method is characterized in that the alpha phase and the beta phase in the electron microscope image are quantitatively counted by digitally processing the side section scanning electron microscope image of the titanium alloy cutting sample.
In order to solve the problems, the invention is realized by the following technical measures: a quantitative analysis method for metallographic volume fraction gradient distribution of a surface layer material of a dual-phase titanium alloy cutting process comprises the following steps:
(1) cutting the cut surface of the titanium alloy material by warps to manufacture cuboid samples with the length, width and height of 10mm, 5mm and 5mm, and inlaying and manufacturing test blocks by taking the side sections of the samples as detection surfaces;
(2) grinding and polishing the test surface of the test block by using 2000-mesh abrasive paper, putting the test block into a corrosive liquid at room temperature for 10 seconds, and taking out the test sample;
(3) scanning the test surface of the test block by using a scanning electron microscope to obtain an electron microscope image simultaneously containing an alpha phase and a beta phase;
(4) in image processing software, converting an electron microscope image into a quantized gray image with 256 levels (namely 0-255) through gray processing, wherein the gray level 255 is displayed as pure white in the electron microscope image, and the gray level 0 is displayed as pure black in the electron microscope image;
(5) pruning the electron microscope image, and pruning information of non-microstructure components in the initial image by identifying an effective electron microscope image area, wherein the information comprises a title bar of the electron microscope image and a non-titanium alloy material part;
(6) dividing the effective electron microscope image into an alpha phase region and a beta phase region according to the gray scale, judging the image region with the gray scale between 0 and 127 as the alpha phase region, and judging the image region with the gray scale between 128 and 255 as the beta phase region;
(7) performing binarization processing on a gray level image, setting a gray level threshold value to divide image data into two parts, normalizing pixel gray values which are greater than or equal to the threshold value 128 into '1', normalizing pixel gray values which are smaller than the threshold value 128 into '0', and converting a scanning electron microscope image into an image consisting of pure white and pure black through image binarization processing;
(8) discretely layering the binary image along the cutting depth direction, counting the number of layers N, and counting the number I of alpha-phase pixels in each layered imageαAnd the number of beta-phase pixels Iβ；
(9) Calculating the percentage of the number of alpha-phase pixels and beta-phase pixels in the layered image in the total number of pixels of the layered image;
(10) the percentage of the number of alpha-phase pixels and beta-phase pixels in the layered images to the total number of pixels in the layered images is the volume fraction of alpha-phase and beta-phase in each layered image;
(11) obtaining the volume fraction gradient distribution characteristics of the metallographic phase of the side section of the cut sample according to the volume fractions of the alpha phase and the beta phase in each layered image;
(12) the method is combined with the metallographic volume fraction gradient distribution characteristics under different cutting process parameters, can be directly used for realizing the change of the metallographic structure of the processed surface of the titanium alloy caused by cutting and the quantitative evaluation of the influence rule of the metallographic structure on the material performance, and feeds back and formulates reasonable titanium alloy cutting process parameters.
In order to further improve the technical scheme, the quantitative analysis method for the metallographic volume fraction gradient distribution of the surface layer of the cutting processing of the biphase titanium alloy is characterized in that the side section of the cutting processing sample refers to a plane of the sample vertical to the surface of the cutting processing.
In order to further improve the technical scheme, the invention discloses a quantitative analysis method for the metallographic volume fraction gradient distribution of a surface layer of the cutting processing of the biphase titanium alloy, wherein the cutting processing refers to turning, milling, grinding and planing.
In order to further improve the technical scheme, the quantitative analysis method for the metallographic volume fraction gradient distribution of the surface layer of the cutting processing of the biphase titanium alloy comprises the step of quantitatively analyzing the metallographic volume fraction gradient distribution of the surface layer of the cutting processing of the biphase titanium alloy, wherein 5ml of 65 percent nitric acid HNO with the concentration of 5ml is used as the corrosive liquid33ml of a liquid obtained by mixing 40% hydrofluoric acid HF and 100ml of water.
In order to further improve the technical scheme, the effective electron microscope image is an electron microscope image only comprising an alpha phase and a beta phase.
In order to further improve the technical scheme, the invention discloses a quantitative analysis method for the metallographic volume fraction gradient distribution of the surface layer of the cutting processing of the biphase titanium alloy, and the effective electron microscope image area judgment method refers to that a pixel lattice set M (x) in an electron microscope image is collectedi，yi) Number of lines xiThe maximum value of (b) represents the total number of rows x of the pixel lattice set Mj,maxNumber of columns yjThe maximum value of (a) represents the total number of columns y of the pixel lattice set Mj,max；
Subset N (x) of pixel lattice set MiAnd 1), among two groups of pixels with the maximum gray value difference of the adjacent pixels, two pixels with larger gray values are marked as p (x)11) and p (x)21), wherein x1<x2；
Subset S (x) of pixel lattice set Mi，yj,max) In the two groups of pixels with the maximum gray value difference between the adjacent pixels, the two pixels with the larger gray value are marked as q (x)3，yj,max) And q (x)4，yj,max) Wherein x is3<x4；
When x is2<x4Then, the pixel point p (x)1，1)，p(x2，1)，q(x3，yj,max) And q (x)2，yj,max) The enclosed quadrilateral area is an effective electron microscope image area;
when x is2>x4Then, the pixel point p (x)1，1)，p(x4，1)，q(x3，yj,max) And q (x)4，yj,max) The enclosed quadrilateral area is an effective electron microscope image area.
In order to further improve the technical scheme, the quantitative analysis method for the metallographic volume fraction gradient distribution of the surface layer of the cutting processing of the biphase titanium alloy, disclosed by the invention, has the advantages that the value range of the discrete layering layer number N of the binary image along the cutting processing depth direction is [1, x%j,max]。
In order to further improve the technical scheme, the image processing software refers to Matlab.
In order to further improve the technical scheme, the quantitative analysis method for the metallographic volume fraction gradient distribution of the surface layer of the cutting processing of the dual-phase titanium alloy comprises the step of carrying out volume fraction f of alpha phase and beta phase in each layered imageαAnd fβRespectively refer to the number I of alpha-phase pixels in the layered imageαAnd the number of beta-phase pixels IβOccupying the total pixel number I of the layered imageα+IβThe calculation formula is as follows:
fα＝Iα/(Iα+Iβ)
fβ＝Iβ/(Iα+Iβ)
the quantitative analysis method for the metallographic volume fraction gradient distribution of the surface layer of the cutting processing of the dual-phase titanium alloy has the advantages that the quantitative analysis of the metallographic gradient distribution of the side section of the cutting sample is realized by adopting an electron microscope image recognition technology and characterizing the metallographic characteristics on a micron scale. The problem of quantitative analysis of volume fraction gradient distribution of a metallographic phase on the surface of a titanium alloy cutting machining surface in the prior art is solved, the number N of discrete layering layers of an electron microscope image along the cutting machining depth direction is controllable, and high-precision identification of the electron microscope image can be realized. Therefore, compared with the prior art, the invention has prominent substantive features and remarkable progress, and the beneficial effects of the implementation are also obvious.
Drawings
FIG. 1 is a schematic diagram illustrating a sampling process of a test block;
FIG. 2 is an initial image of a scanning electron microscope;
FIG. 3 is a cut electron microscope image;
FIG. 4 is a binarized image;
FIG. 5 is a schematic diagram of a discrete layered analysis method for electron microscope images;
FIG. 6 is a two-phase titanium alloy Ti-6Al-4V milling surface layer material beta phase volume fraction gradient distribution curve;
FIG. 7 is an X-ray diffraction pattern of an uncut material;
fig. 8 is an X-ray diffraction pattern of the cut surface material.
Detailed Description
In order to clearly illustrate the technical features of the present solution, the following explains the present solution by a specific embodiment in combination with the accompanying drawings.
Selecting a middle area of the processed surface of the workpiece, performing warp cutting to manufacture a rectangular sample, embedding and manufacturing test blocks by taking side sections as detection surfaces respectively, wherein a schematic diagram of a test block sampling process is shown in fig. 1. In fig. 1, 101 denotes a machined surface, 102 denotes a side cross section, 103 denotes a cutting tool, 104 denotes an insert block, and 105 denotes a titanium alloy material to be machined.
The test surface of the test block was ground (2000 mesh sandpaper) and polished and then placed in a corrosive solution at room temperature for 10 seconds, and the formula and performance parameters of the corrosive solution are listed in the following table.
Scanning the side section of the milling sample of the dual-phase titanium alloy Ti-6Al-4V by using an SH-3000HIROX scanning electron microscope to obtain an electron microscope image simultaneously containing an alpha phase and a beta phase, and scanning an electron microscope initial image as shown in figure 2. The beta phase is denoted by 203 in fig. 2 and is pale white. Designated at 204 in fig. 2 as the alpha phase, is light black.
The scanning electron microscope initial image is an RGB format image, that is, various color images are obtained by the change of three color channels of Red (Red), Green (Green), and Blue (Blue) and their mutual superposition. In order to describe the brightness relationship between the alpha phase and the beta phase in the golden phase diagram, the initial image needs to be converted into a gray scale image. The rgb2gray function is used to convert the original image to a quantized gray scale image with 256 levels (0-255), where "255" represents pure white and "0" represents pure black.
And (3) pruning the electron microscope image, and pruning the information of the non-microstructure components in the initial image by identifying the effective electron microscope image area, wherein the information comprises a title column of the electron microscope image and a non-titanium alloy material part, such as an inlaid material indicated by 201 and an electron microscope image title column indicated by 202 in the figure 2. The cropped electron microscope image is shown in FIG. 3, and the window size of the cropped electron microscope image is 243 μm 170 μm.
And carrying out binarization processing on the gray level image. By setting a threshold value
Dividing the image data into two parts, for values greater than or equal to a threshold value
Is normalized to "1", less than a threshold value
The pixels of (a) are then normalized to "0". After image binarization processing, the scanning electron microscope image is converted into an image composed of pure white and pure black, as shown in fig. 4.
And (3) discretely layering the binary image along the depth direction of cutting processing, wherein the number of layers is 170, and fig. 5 is a schematic diagram of a method for analyzing the discrete layering of the electron microscope image.
Counting the number of alpha-phase pixels and beta-phase pixels in each layered image, and calculating the percentage of the number of the alpha-phase pixels and the number of the beta-phase pixels in the layered images in the total number of pixels of the layered images, wherein the calculation results of the first 25 layers are as follows:
the volume fractions of the alpha and beta phases in each layered image are expressed as the percentage of the number of alpha and beta phase pixels in the layered image to the total number of pixels in the layered image.
According to the volume fractions of the alpha phase and the beta phase in each layered image, a metallographic gradient distribution curve of a side section of the cut sample can be drawn, and as shown in fig. 6, the metallographic gradient distribution curve of the volume fraction of the beta phase of the surface layer material milled by the dual-phase titanium alloy Ti-6Al-4V is obtained.
In order to verify the reliability of the titanium alloy Ti6Al4V metallographic phase content statistical method based on the image recognition technology, samples of the surface of an uncut material and samples of the cut surface are respectively selected and subjected to XRD test to obtain corresponding X-ray spectrums, wherein the X-ray diffraction spectrum of the uncut material is shown in figure 7, and the X-ray diffraction spectrum of the cut surface material is shown in figure 8.
Corresponding X-ray maps are obtained according to uncut material surface and cut surface samples, and the volume fractions of the alpha phase and the beta phase are calculated according to the following formula.
fα＝Qα/(Qα+Qβ)
fβ＝Qβ/(Qα+Qβ)
In the formula Qα，QβThe diffraction peak intensities corresponding to α (101) and β (110), respectively.
The volume fractions of beta phases of the uncut material and the machined surface were calculated to be 13.5% and 31.3%, respectively, and the results were calculated to be 15.4% and 36.7%, respectively, based on the statistics of the image processing technique. Comparing the XRD test result with the statistical result of the image processing method, the test errors of the volume fractions of the uncut material and the beta phase on the cut surface of the titanium alloy Ti6Al4V are respectively 12.3% and 14.7%, which shows that the identification of the volume fractions of the metallographic phase of the titanium alloy Ti6Al4V by the image processing technology has high enough precision.
Claims (1)
1. A quantitative analysis method for metallographic volume fraction gradient distribution of a surface layer of a dual-phase titanium alloy cutting process is characterized by comprising the following steps of: the method comprises the following steps:
step (1), the cut surface of the titanium alloy material is subjected to warp cutting to manufacture cuboid samples with the length, width and height of 10mm, 5mm and 5mm, and the side sections of the samples are used as detection surfaces to be inlaid to manufacture test blocks;
step (2), grinding and polishing the test surface of the test block by using 2000-mesh abrasive paper, putting the test block into a corrosive liquid at room temperature for 10 seconds, and taking out the test sample;
scanning the test surface of the test block by using a scanning electron microscope to obtain an electron microscope image simultaneously containing an alpha phase and a beta phase;
step (4), in image processing software, converting an electron microscope image into a quantized gray image with 256 levels, namely 0-255, through gray processing, wherein the gray level 255 is displayed as pure white in the electron microscope image, and the gray level 0 is displayed as pure black in the electron microscope image;
trimming the electron microscope image, and trimming the information of non-microstructure components in the initial image by identifying an effective electron microscope image area, wherein the information comprises a title bar of the electron microscope image and a non-titanium alloy material part;
dividing the effective electron microscope image into an alpha phase region and a beta phase region according to the gray scale, judging the image region with the gray scale between 0 and 127 as the alpha phase region, and judging the image region with the gray scale between 128 and 255 as the beta phase region;
the effective electron microscope image area judgment method refers to that a pixel dot matrix set M (x) in the electron microscope imagei，yi) Number of lines xiThe maximum value of (b) represents the total number of rows x of the pixel lattice set Mj,maxNumber of columns yjThe maximum value of (a) represents the total number of columns y of the pixel lattice set Mj,max；
Subset N (x) of pixel lattice set MiAnd 1), among two groups of pixels with the maximum gray value difference of the adjacent pixels, two pixels with larger gray values are marked as p (x)11) and p (x)21), wherein x1<x2；
Subset S (x) of pixel lattice set Mi，yj,max) In the two groups of pixels with the maximum gray value difference between the adjacent pixels, the two pixels with the larger gray value are marked as q (x)3，yj,max) And q (x)4，yj,max) Wherein x is3<x4；
When x is2<x4Then, the pixel point p (x)1，1)，p(x2，1)，q(x3，yj,max) And q (x)2，yj,max) The enclosed quadrilateral area is an effective electron microscope image area;
when x is2>x4Then, the pixel point p (x)1，1)，p(x4，1)，q(x3，yj,max) And q (x)4，yj,max) The enclosed quadrilateral area is an effective electron microscope image area;
performing binarization processing on the gray level image, setting a gray level threshold value to divide image data into two parts, normalizing pixel gray level values larger than or equal to the threshold value 128 into '1', normalizing pixel gray level values smaller than the threshold value 128 into '0', and converting the scanning electron microscope image into an image consisting of pure white and pure black through image binarization processing;
step (8) discretely layering the binary image along the cutting processing depth direction, wherein the number of layers is N, and the number I of alpha-phase pixels in each layered image is countedαAnd the number of beta-phase pixels Iβ；
Step (9), calculating the percentage of the number of alpha-phase pixels and beta-phase pixels in the layered image to the total number of pixels in the layered image;
step (10), the percentage of the number of alpha-phase pixels and beta-phase pixels in the layered image to the total number of pixels in the layered image is the volume fraction of alpha-phase and beta-phase in each layered image;
step (11), obtaining the volume fraction gradient distribution characteristics of the metallographic phase of the side section of the cut sample according to the volume fractions of the alpha phase and the beta phase in each layered image;
step (12), the metallographic volume fraction gradient distribution characteristics under different cutting process parameters are combined, the method can be directly used for realizing the change of the metallographic structure of the processed surface of the titanium alloy caused by cutting and the quantitative evaluation of the influence rule of the metallographic structure on the material performance, and reasonable cutting process parameters of the titanium alloy are made in a feedback mode;
the side section of the cutting sample refers to a plane of the sample perpendicular to the cutting surface;
the cutting processing refers to turning, milling, grinding and planing;
the corrosive liquid is 5ml of 65 percent nitric acid HNO33ml of a liquid obtained by mixing 40% hydrofluoric acid (HF) with 100ml of water;
the effective electron microscope image is an electron microscope image only comprising an alpha phase and a beta phase;
the value range of the discrete layering layer number N of the binary image along the cutting processing depth direction is [1, xj,max]；
The volume fraction f of alpha phase and beta phase in each layered imageαAnd fβRespectively refer to the number I of alpha-phase pixels in the layered imageαAnd the number of beta-phase pixels IβOccupying the total pixel number I of the layered imageα+IβThe calculation formula is as follows:
fα＝Iα/(Iα+Iβ)
fβ＝Iβ/(Iα+Iβ)。
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