Method and device for measuring permeability during metal solidification process, electronic equipment, and storage medium

Abstract

The present application provides a method and apparatus, electronic device, and computer-readable storage medium for measuring the permeability of a metal during solidification. The method comprises: obtaining a microstructure image of a metal sample during solidification and a binary image corresponding to the microstructure image; determining a pure liquid phase image of the microstructure image based on the pure liquid phase region indicated by the binary image; determining the solid phase thickness corresponding to each pixel in the solid-liquid mixed region of the microstructure image based on the pure liquid phase image, a preset reference frame, and the property parameters of the metal sample; determining the solid phase fraction and specific surface area of ​​the solidified structure in the microstructure image based on the solid phase thickness and property parameters corresponding to each pixel in the solid-liquid mixed region of the microstructure image; and calculating the permeability of the solidified structure based on the solid phase fraction and specific surface area. This solution enables in-situ measurement of permeability during solidification using a two-dimensional solidification structure image.

Description

Technical Field

[0001] The present application relates to the technical field of characterization of metal materials, and in particular to a method and device for determining the permeability of a metal solidification process, an electronic device, and a computer-readable storage medium. Background Art

[0002] During metal solidification, controlling the microstructure of the solidified structure is crucial for improving casting performance. Permeability is a key parameter controlling fluid flow within the solidified structure within the mushy zone. It significantly influences heat and mass transfer in the liquid phase, thus affecting the formation of the solidified structure. Therefore, in situ determination of dynamic permeability during solidification is crucial.

[0003] In the related art, a numerical method of simplified solid network modeling can be used to predict the permeability of the mushy zone, and the simulated three-dimensional microstructure of the solidified structure improves the accuracy of permeability determination to a certain extent.

[0004] However, these methods have two significant problems. First, the numerical modeling methods used, such as the 3D cellular automaton finite difference method, the phase field-lattice Boltzmann method, and the Navier-Stokes equations, typically consume a large amount of computing resources and are quite time-consuming. Second, when simulating the solid microstructure, these methods all assume that uniformly distributed static atomic nuclei solidify to form an array of cubic grains of the same size. However, in general, the actual solid microstructure results during the solidification process are much more complex than the simplified solid microstructure results of the simulation. Therefore, the simulation results cannot determine the actual permeability. Summary of the Invention

[0005] The purpose of the embodiments of the present application is to provide a method and device for measuring the permeability of a metal solidification process, an electronic device, and a computer-readable storage medium, so as to measure the permeability during the solidification process in situ from a two-dimensional solidification structure image.

[0006] In one aspect, the present application provides a method for determining the permeability of a metal solidification process, comprising:

[0007] Acquire a microstructure image of the metal sample during solidification and a binary image corresponding to the microstructure image; wherein the binary image is an image segmentation result of a solid-liquid phase mixed region and a pure liquid phase region in the microstructure image;

[0008] determining a pure liquid phase image of the microstructure image according to the pure liquid phase region indicated by the binary image;

[0009] Determining the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image based on the pure liquid phase image, a preset reference frame, and the property parameters of the metal sample;

[0010] determining a solid phase fraction and a specific surface area of ​​the solidified tissue in the microstructure image according to the solid phase thickness corresponding to each pixel in the microstructure image and the attribute parameter;

[0011] The permeability of the solidified structure is calculated based on the solid phase fraction and the specific surface area.

[0012] In one embodiment, the step of obtaining a microstructure image of a metal sample during solidification and a binary image corresponding to the microstructure image includes:

[0013] Obtain X-ray imaging images of the solidification process of metal samples;

[0014] performing image enhancement processing on the X-ray imaging image to obtain the microscopic tissue image;

[0015] Perform image segmentation on the microscopic tissue image to obtain the binary image.

[0016] In one embodiment, determining the solid phase thickness corresponding to each pixel in the microstructure image based on the pure liquid phase image, a preset reference frame, and the property parameters of the metal sample includes:

[0017] determining a liquid phase solute concentration distribution map corresponding to the microscopic tissue image based on the pure liquid phase image, the reference frame, and the attribute parameters;

[0018] The solid phase thickness corresponding to each pixel in the microscopic tissue image is determined based on the reference frame, the liquid phase solute concentration distribution map and the attribute parameter.

[0019] In one embodiment, the property parameters include the thickness of the metal sample, the density of the main element and the solute element in the metal sample, and the X-ray mass attenuation coefficient of the main element and the solute element in the metal sample;

[0020] The determining of the liquid phase solute concentration distribution map corresponding to the microscopic tissue image based on the pure liquid phase image, the reference frame, and the attribute parameters includes:

[0021] Calculating the concentration of each element in the pure liquid phase image based on the pixel average value of the reference frame, the concentration of the solute element corresponding to the reference frame, the attribute parameters including the thickness of the metal sample, the density of the main element and the solute element in the metal sample, the X-ray mass attenuation coefficient of the main element and the solute element in the metal sample, and the pixel value of each pixel in the pure liquid phase image to obtain a solute concentration distribution map corresponding to the pure liquid phase image;

[0022] The solute concentration distribution map corresponding to the pure liquid phase image is interpolated to obtain the liquid phase solute concentration distribution map corresponding to the microstructure image.

[0023] In one embodiment, the property parameters include the thickness of the metal sample, and the X-ray mass attenuation coefficients of the main elements and solute elements in the metal sample;

[0024] The determining of the solid phase thickness corresponding to each pixel in the microscopic tissue image based on the reference frame, the liquid phase solute concentration distribution map, and the attribute parameter includes:

[0025] For each pixel in the microstructure image, determining the liquid mass fraction of the solute element according to the liquid concentration distribution map;

[0026] For each pixel in the solid-liquid mixed area in the microstructure image, the solid phase thickness of the solute element corresponding to the pixel is calculated based on the pixel average value of the reference frame, the solid phase mass branch and liquid phase mass fraction corresponding to the pixel, and the X-ray mass attenuation coefficient of the main element and solute element in the metal sample.

[0027] In one embodiment, the property parameters include the thickness of the metal sample and the width of the mushy area in the metal sample;

[0028] Determining the solid phase fraction and specific surface area of ​​the solidified tissue in the microscopic tissue image according to the solid phase thickness corresponding to each pixel in the microscopic tissue image and the attribute parameter includes:

[0029] Determining the solid phase fraction in the mushy region and the height of the mushy region in the metal sample based on the solid phase thickness corresponding to each pixel in the microstructure image, the thickness of the metal sample, and the width of the mushy region in the metal sample;

[0030] The specific surface area of ​​the solidified structure is determined according to the solid phase thickness corresponding to each pixel of the solid-liquid phase mixed area in the microstructure image and the width and height of the mushy area in the metal sample.

[0031] In one embodiment, determining the specific surface area of ​​the solidified structure based on the solid phase thickness corresponding to each pixel in the microstructure image and the width and height of the mushy region in the metal sample includes:

[0032] Calculating the solid phase volume of the solidified structure according to the solid phase thickness corresponding to each pixel in the microstructure image and the width and height of the mushy area in the metal sample;

[0033] determining the gradients of the solid phase thickness in the vertical and horizontal directions according to the solid phase thickness corresponding to each pixel in the microstructure image;

[0034] determining the surface area of ​​the solidified tissue based on the gradients in the vertical direction and the horizontal direction;

[0035] The specific surface area is calculated based on the solid phase volume and surface area of ​​the solidified structure.

[0036] On the other hand, the present application also provides a device for measuring the permeability of a metal solidification process, comprising:

[0037] An acquisition module, configured to acquire a microstructure image of a metal sample during solidification and a binary image corresponding to the microstructure image; wherein the binary image is an image segmentation result of a solid-liquid mixed region and a pure liquid region in the microstructure image;

[0038] a first calculation module, configured to determine a pure liquid phase image of the microstructure image according to the pure liquid phase region indicated by the binary image;

[0039] a second calculation module, configured to determine the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image based on the pure liquid phase image, a preset reference frame, and the property parameters of the metal sample;

[0040] a third calculation module, configured to determine the solid phase fraction and specific surface area of ​​the solidified tissue in the microscopic tissue image according to the solid phase thickness corresponding to each pixel in the microscopic tissue image and the attribute parameter;

[0041] A fourth calculation module is configured to calculate the permeability of the solidified structure based on the solid phase fraction and the specific surface area.

[0042] Furthermore, the present application also provides an electronic device, comprising:

[0043] processor;

[0044] a memory for storing processor-executable instructions;

[0045] Wherein, the processor is configured to execute the above-mentioned method for determining the permeability of the metal solidification process.

[0046] In addition, the present application also provides a computer-readable storage medium, which stores a computer program. The computer program can be executed by a processor to complete the above-mentioned method for determining the permeability of the metal solidification process.

[0047] This application scheme obtains a microstructure image and a corresponding binary image of the metal sample during solidification. The pure liquid phase image of the microstructure image is determined based on the binary image. The solid phase thickness corresponding to each pixel in the solid-liquid mixed region of the microstructure image is determined based on the pure liquid phase image reference frame and the property parameters of the metal sample. The solid phase fraction and specific surface area of ​​the solidified structure in the microstructure image are determined based on the solid phase thickness and property parameters corresponding to each pixel in the solid-liquid mixed region of the microstructure image. The permeability of the solidified structure is calculated based on the solid phase fraction and the specific surface area. This application scheme enables in-situ measurement of permeability during solidification from a two-dimensional solidified structure image, which is more accurate than simulation modeling methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments of the present application.

[0049] Figure 1 A schematic diagram of an application scenario of a method for measuring permeability during a metal solidification process provided in one embodiment of the present application;

[0050] Figure 2 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application;

[0051] Figure 3 A schematic flow chart of a method for measuring permeability during metal solidification provided in one embodiment of the present application;

[0052] Figure 4 A schematic diagram of a process for obtaining a microscopic tissue image and a binary image according to an embodiment of the present application;

[0053] Figure 5 A schematic diagram of image enhancement processing provided in one embodiment of the present application;

[0054] Figure 6 A schematic diagram of image segmentation provided in one embodiment of the present application;

[0055] Figure 7 A schematic diagram of a process for determining a liquid phase solute concentration distribution diagram provided in one embodiment of the present application;

[0056] Figure 8 A schematic flow chart of a method for calculating solid phase thickness provided in one embodiment of the present application;

[0057] Figure 9 A schematic diagram of a three-dimensional microstructure provided in one embodiment of the present application;

[0058] Figure 10 A schematic diagram of a process for calculating solid fraction and specific surface area provided in one embodiment of the present application;

[0059] Figure 11 A schematic diagram of a process for calculating specific surface area provided in one embodiment of the present application;

[0060] Figure 12 This is a block diagram of a device for measuring the permeability of a metal solidification process provided by one embodiment of the present application. DETAILED DESCRIPTION

[0061] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0062] Similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0063] Figure 1 Schematic diagram of the application scenario of the method for measuring the permeability of the metal solidification process provided in the embodiment of the present application. Figure 1 As shown, the application scenario includes a client 20 and a server 30; the client 20 can be a synchrotron radiation X-ray imaging device, which is used to perform in-situ X-ray imaging of metal samples during the solidification process and transmit the acquired X-ray imaging images to the server 30; the server 30 can be a server, a server cluster or a cloud computing center, which can process the acquired X-ray imaging images to obtain the permeability of the metal sample during the solidification process.

[0064] like Figure 2 As shown, this embodiment provides an electronic device 1, including: at least one processor 11 and a memory 12, Figure 2 In the example, a processor 11 is used. Processor 11 and memory 12 are connected via bus 10. Memory 12 stores instructions executable by processor 11. These instructions are executed by processor 11, enabling electronic device 1 to perform all or part of the method described in the following embodiments. In one embodiment, electronic device 1 may be the aforementioned server 30, configured to perform the method for determining the permeability of a metal solidification process.

[0065] The memory 12 can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0066] The present application also provides a computer-readable storage medium, which stores a computer program. The computer program can be executed by the processor 11 to complete the method for determining the permeability of the metal solidification process provided in the present application.

[0067] See also Figure 3 , is a flow chart of a method for determining the permeability of a metal solidification process provided by an embodiment of the present application, such as Figure 3 As shown, the method may include the following steps 310 to 350.

[0068] Step 310: Acquire a microstructure image of the metal sample during solidification and a binary image corresponding to the microstructure image; wherein the binary image is an image segmentation result of the solid-liquid phase mixed region and the pure liquid phase region in the microstructure image.

[0069] Here, the metal sample is a binary alloy, including a main element with a high mass percentage and a solute element with a low mass percentage. For example, the metal sample can be an Al-15wt.%Cu alloy, in which the main element is aluminum and the solute element is copper.

[0070] Microstructure images can show the formation of dendrites during the solidification process of metal samples. In microstructure images, dendrites are present in the solid-liquid mixed region, but not in the pure liquid region.

[0071] Step 320 : Determine a pure liquid phase image of the microstructure image according to the pure liquid phase region indicated by the binary image.

[0072] The binary image has the same width and height as the microstructure image. Each pixel in the binary image indicates whether the corresponding pixel (the pixel at the same position) in the microstructure image is a solid-liquid mixed region or a pure liquid region. For example, a pixel value of 1 in the binary image indicates that the corresponding pixel in the microstructure image belongs to the solid-liquid mixed region; a pixel value of 0 in the binary image indicates that the corresponding pixel in the microstructure image belongs to the pure liquid region.

[0073] The server can process the microstructure image based on the binary image to obtain a pure liquid phase image, in which the pixel values ​​​​except the pure liquid phase area are 0.

[0074] The server can obtain the pure liquid phase image through the following formula (1):

[0075] I l =(EM)*I (1)

[0076] Where, I represents the microscopic tissue image; I l Represents a pure liquid phase image; M represents a binary image, in which the area with a pixel value of 1 represents a solid-liquid mixed area, and the area with a pixel value of 0 represents a pure liquid phase area; E represents an image of the same size as M, in which each pixel value is 1.

[0077] By using the above formula (1), the pixel value of the solid-liquid mixed area in the microstructure image can be changed to 0, and the pixel value of the pure liquid phase area can be retained, thereby obtaining a pure liquid phase image.

[0078] Step 330: Determine the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image based on the pure liquid phase image, the preset reference frame, and the property parameters of the metal sample.

[0079] The reference frame is a microstructure image of the metal sample in a completely molten state (no dendrites appear) with uniform distribution of liquid solute.

[0080] The property parameters of the metal sample may include the thickness of the metal sample, the density of the main element and solute elements in the metal sample, and the X-ray mass attenuation coefficient of the main element and solute elements in the metal sample. Here, the X-ray mass attenuation coefficient may include the attenuation coefficient of the solid phase state and the liquid phase state.

[0081] The solid phase thickness corresponding to each pixel in the microscopic tissue image represents the thickness of the solidified tissue at the position of the pixel in the microscopic tissue image.

[0082] Step 340: Determine the solid phase fraction and specific surface area of ​​the solidified tissue in the microscopic tissue image based on the solid phase thickness and property parameters corresponding to each pixel in the microscopic tissue image.

[0083] Step 350: Calculate the permeability of the solidified structure based on the solid fraction and the specific surface area.

[0084] After calculating the solid fraction and specific surface area, the server can calculate the permeability of the solidified structure using the KC (Kozeny-Carman) equation. The calculation method can be expressed as follows:

[0085]

[0086] Among them, f s is the solid fraction; S v is the specific surface area; k c It is a preset constant and can be configured based on empirical values.

[0087] In one embodiment, see Figure 4 , is a schematic diagram of a process for obtaining a microscopic tissue image and a binary image according to an embodiment of the present application, such as Figure 4 As shown, when the server executes step 310, it can execute the following steps 311 to 313.

[0088] Step 311: Acquire an X-ray imaging image of the metal sample during the solidification process.

[0089] The server can obtain X-ray imaging images of the metal sample during the solidification process in real time from the client providing the X-ray imaging images. The server can obtain an image sequence consisting of multiple X-ray imaging images from the client.

[0090] Step 312: Perform image enhancement processing on the X-ray imaging image to obtain a microscopic tissue image.

[0091] The server can perform flat-field correction on the X-ray imaging image. The server can process the X-ray imaging image in the image sequence by using the X-ray imaging image corresponding to the reference frame and the preset dark field frame. Here, the dark field frame refers to the image obtained when no exposure is performed. The processing method can be expressed by the following formula (3):

[0092]

[0093] Among them, I img Represents the original X-ray imaging image; I B Indicates dark field frame; I R I represents an X-ray imaging image of a reference frame; out represents the image after flat-field correction.

[0094] The server can perform contrast adjustment on the flat-field corrected X-ray imaging image, thereby improving the contrast of the X-ray imaging image.

[0095] The server can perform noise reduction on the contrast-adjusted image to obtain an enhanced microscopic tissue image. For example, the server can perform noise reduction on the image using a Block-Matching and 3D filtering (BM3D) algorithm.

[0096] To illustrate the effects of image enhancement processing, see Figure 5 , is a schematic diagram of image enhancement processing provided by an embodiment of the present application, Figure 5 In the figure, Figure a shows the original X-ray imaging image, Figure b shows the image after flat field correction and contrast enhancement, and Figure c shows the microscopic tissue image after noise reduction processing.

[0097] Step 313: performing image segmentation on the microscopic tissue image to obtain a binary image.

[0098] The server can segment the microscopic tissue image using the trained image segmentation model to obtain a binary image. Figure 6 , is a schematic diagram of image segmentation provided by an embodiment of the present application, Figure 6 In the figure, b is a microstructure image; c is a binary image, in which the white area represents the solid-liquid mixed area, and the black area represents the pure liquid area.

[0099] In one embodiment, when calculating the solid phase thickness corresponding to each pixel in the microstructure image, the server can determine a liquid phase solute concentration profile corresponding to the microstructure image based on the pure liquid phase image, the reference frame, and the attribute parameters. The liquid phase solute concentration profile represents the solute element concentration corresponding to each pixel in the microstructure image.

[0100] The server can determine the solid phase thickness corresponding to each pixel in the solid-liquid mixed area in the microstructure image based on the reference frame, liquid solute concentration distribution map and attribute parameters.

[0101] In one embodiment, see Figure 7 , is a schematic diagram of a process for determining a liquid phase solute concentration distribution diagram provided by an embodiment of the present application, such as Figure 7 As shown, the method may include the following steps 331-332.

[0102] Step 331: Based on the pixel average value of the reference frame, the concentration of the solute element corresponding to the reference frame, attribute parameters including the thickness of the metal sample, the density of the main elements and solute elements in the metal sample, the X-ray mass attenuation coefficient of the main elements and solute elements in the metal sample, and the pixel value of each pixel in the pure liquid phase image, the concentration corresponding to each pixel in the pure liquid phase image is calculated to obtain a solute concentration distribution map corresponding to the pure liquid phase image.

[0103] For each pixel in the pure liquid phase image, the server can calculate the solute concentration difference between the pixel and the corresponding pixel in the reference frame (the pixel at the same position) using the following formula (4):

[0104]

[0105] Where, δ represents the thickness of the metal sample; I ij Represents the pixel value of a pixel in a pure liquid phase image; I w0 represents the average pixel value of the reference frame; μ a,l Represents the X-ray mass attenuation coefficient of the main elements in the metal sample in the liquid phase; ρ a Indicates the density of the main elements in the metal sample; μ b,l Represents the X-ray mass attenuation coefficient of the solute element in the metal sample in the liquid phase; ρ b Indicates the density of the solute element in the metal sample.

[0106] After calculating the solute concentration difference, the concentration of the solute element corresponding to the reference frame can be added to obtain the solute concentration of the above pixel. After calculating the solute concentration of all pixels in the pure liquid phase image, a solute concentration distribution map can be constructed based on the solute concentration of all pixels.

[0107] Step 332: performing interpolation processing on the solute concentration distribution map corresponding to the pure liquid phase image to obtain a liquid phase solute concentration distribution map corresponding to the microscopic tissue image.

[0108] After obtaining the solute concentration distribution map, based on the distribution characteristics of the solute concentration during the metal solidification process, the solute concentration distribution of the liquid phase in the solid-liquid phase mixing area can be supplemented by an interpolation method, thereby obtaining the liquid phase solute concentration distribution map of the entire field of view of the microstructure image.

[0109] The server can interpolate the solute concentration distribution map corresponding to the pure liquid phase image based on the two-line interpolation method of coefficient linear algebra and partial differential equation discretization, thereby obtaining the liquid phase solute concentration distribution map corresponding to the microscopic tissue image.

[0110] In one embodiment, see Figure 8 , is a flow chart of a method for calculating the solid phase thickness provided in one embodiment of the present application, such as Figure 8 As shown, the method may include the following steps 333 and 334.

[0111] Step 333: For each pixel in the microstructure image, determine the liquid mass fraction of the solute element according to the liquid concentration distribution map.

[0112] After the liquid concentration distribution map is obtained, the liquid mass fraction of each pixel in the microstructure image can be determined according to the pixel value of each pixel in the liquid concentration distribution map.

[0113] Step 334: For each pixel in the solid-liquid mixed region in the microstructure image, the solid phase thickness of the solute element corresponding to the pixel is calculated based on the pixel average value of the reference frame, the solid phase mass fraction and liquid phase mass fraction corresponding to the pixel, and the X-ray mass attenuation coefficients of the main elements and solute elements in the metal sample.

[0114] Here, the X-ray mass attenuation coefficient of the main element includes: the X-ray mass attenuation coefficient of the main element in the solid phase state, and the X-ray mass attenuation coefficient of the main element in the liquid phase state; the X-ray mass attenuation coefficient of the solute element includes: the X-ray mass attenuation coefficient of the solute element in the solid phase state, and the X-ray mass attenuation coefficient of the solute element in the liquid phase state.

[0115] The solid phase mass fraction does not change much during the metal solidification process and can be considered as a preset fixed value.

[0116] The server can calculate the solid phase thickness corresponding to each pixel in the solid-liquid mixing area using the following formula (5):

[0117]

[0118] Among them, I sl Represents the pixel value of any pixel in the solid-liquid phase mixing area; I w0 represents the average pixel value of the reference frame; δ represents the thickness of the metal sample; μ a,l Indicates the X-ray mass attenuation coefficient of the main elements in the liquid phase; μ a,s Indicates the X-ray mass attenuation coefficient of the main elements in the solid phase; μ b,l Indicates the X-ray mass attenuation coefficient of the solute element in the liquid phase; μ b,s represents the X-ray mass attenuation coefficient of the solute element in the solid phase; w0 represents the solute concentration in the reference frame; w b,l represents the mass fraction of the solute element in the liquid phase; w b,s Represents the solid phase mass fraction of the solute element. After obtaining the solid phase thickness corresponding to all pixels in the solid phase mixing area, the server can construct a three-dimensional structural diagram of the microstructure based on the above solid phase thickness to represent the three-dimensional microstructure. Figure 9 , is a schematic diagram of a three-dimensional microstructure provided by an embodiment of the present application, such as Figure 9 As shown, the solid phase thickness of the microstructure at different locations is different.

[0119] In one embodiment, see Figure 10, is a schematic diagram of a process for calculating the solid fraction and specific surface area provided in one embodiment of the present application, such as Figure 10 As shown, the method may include the following steps 341-342.

[0120] Step 341: Determine the solid phase fraction in the mushy region and the height of the mushy region in the metal sample based on the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image, the thickness of the metal sample, and the width of the mushy region in the metal sample.

[0121] The width of the mushy area can be considered as the width of the metal sample.

[0122] The server can calculate the solid fraction and the height of the mushy area using the following formula (6):

[0123]

[0124] Where fs represents the solid fraction; δ s (i, j) represents the solid phase thickness corresponding to the pixel at coordinate (i, j) in the image; δ represents the thickness of the metal sample; w represents the width of the mushy region; and h represents the height of the mushy region, where the solid phase fraction exceeds a preset value. The preset value can be an empirical value, such as 0.03.

[0125] Step 342: Determine the specific surface area of ​​the solidified structure based on the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image and the width and height of the mushy region in the metal sample.

[0126] After obtaining the height of the mushy area, the specific surface area of ​​the solidified structure in the mushy area can be calculated.

[0127] In one embodiment, see Figure 11 , is a schematic diagram of a flow chart for calculating specific surface area provided in an embodiment of the present application, such as Figure 8 As shown, the method may include the following steps 342A-342D.

[0128] Step 342A: Calculate the solid phase volume of the solidified structure based on the solid phase thickness corresponding to each pixel in the solid-liquid mixed region of the microstructure image and the width and height of the mushy region in the metal sample.

[0129] The server can calculate the solid phase volume using the following formula (7):

[0130]

[0131] Where V represents the solid phase volume; w represents the width of the mushy area; h represents the height of the mushy area; δ s(i, j) represents the solid phase thickness corresponding to the pixel at coordinate (i, j) in the image.

[0132] Step 342B: Determine the gradients of the solid phase thickness in the vertical and horizontal directions according to the solid phase thickness corresponding to each pixel in the solid-liquid mixed region of the microstructure image.

[0133] For any two adjacent pixels in the rows and columns of the solid-liquid mixed area, the server can calculate the difference in solid thickness to obtain the gradient corresponding to each pixel in the horizontal direction of the image. The gradient corresponding to each pixel in the vertical direction

[0134] Step 342C: Determine the surface area of ​​the solidified tissue based on the vertical and horizontal gradients.

[0135] The server can calculate the surface area of ​​the solidified tissue using the following formula (8):

[0136]

[0137] Where S represents the surface area; w represents the width of the mushy area; h represents the height of the mushy area; Represents the horizontal gradient of the pixel at coordinate (i, j); Represents the gradient of the pixel at coordinate (i, j) in the vertical direction.

[0138] Step 342D: Calculate the specific surface area based on the solid phase volume and surface area of ​​the solidified structure.

[0139] The server can calculate the specific surface area using the following formula (9):

[0140]

[0141] Among them, S v represents the specific surface area; S represents the surface area of ​​the solidified structure; V represents the volume of the solidified structure.

[0142] Figure 12 This is a device for measuring the permeability of a metal solidification process according to an embodiment of the present invention. Figure 12 As shown, the device may include:

[0143] An acquisition module 1210 is configured to acquire a microstructure image of a metal sample during solidification and a binary image corresponding to the microstructure image; wherein the binary image is an image segmentation result of a solid-liquid mixed region and a pure liquid region in the microstructure image;

[0144] A first calculation module 1220 is configured to determine a pure liquid phase image of the microscopic tissue image based on the pure liquid phase region indicated by the binary image;

[0145] A second calculation module 1230 is configured to determine the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image based on the pure liquid phase image, a preset reference frame, and the property parameters of the metal sample;

[0146] A third calculation module 1240 is configured to determine the solid phase fraction and specific surface area of ​​the solidified tissue in the microscopic tissue image based on the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microscopic tissue image and the attribute parameter;

[0147] The fourth calculation module 1250 is configured to calculate the permeability of the solidified structure based on the solid fraction and the specific surface area.

[0148] The implementation process of the functions and effects of each module in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method for measuring the permeability of the metal solidification process, and will not be repeated here.

[0149] In several embodiments provided in this application, the disclosed devices and methods may also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of the devices, methods, and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a portion of code, and the module, program segment, or a portion of code contains one or more executable instructions for implementing the specified logical functions. In some alternative implementations, the functions marked in the boxes may also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes may actually be executed substantially in parallel, or they may sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, may be implemented using a dedicated hardware-based system that performs the specified functions or actions, or may be implemented using a combination of dedicated hardware and computer instructions.

[0150] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0151] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

Claims

1. A method for measuring the permeability of a metal solidification process, characterized in that: include: Acquire a microstructure image of the metal sample during solidification and a binary image corresponding to the microstructure image; wherein the binary image is an image segmentation result of a solid-liquid phase mixed region and a pure liquid phase region in the microstructure image; determining a pure liquid phase image of the microstructure image according to the pure liquid phase region indicated by the binary image; Determining the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image based on the pure liquid phase image, a preset reference frame, and the property parameters of the metal sample; determining a solid phase fraction and a specific surface area of ​​the solidified structure in the microstructure image according to the solid phase thickness corresponding to each pixel in the solid-liquid phase mixing region in the microstructure image and the attribute parameter; The permeability of the solidified structure is calculated based on the solid phase fraction and the specific surface area.

2. The method according to claim 1, characterized in that The step of obtaining a microstructure image of a metal sample during solidification and a binary image corresponding to the microstructure image includes: Obtain X-ray imaging images of the solidification process of metal samples; performing image enhancement processing on the X-ray imaging image to obtain the microscopic tissue image; Perform image segmentation on the microscopic tissue image to obtain the binary image.

3. The method according to claim 1, characterized in that Determining the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image based on the pure liquid phase image, a preset reference frame, and the property parameters of the metal sample includes: determining a liquid phase solute concentration distribution map corresponding to the microscopic tissue image based on the pure liquid phase image, the reference frame, and the attribute parameters; The solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image is determined based on the reference frame, the liquid phase solute concentration distribution map and the property parameter.

4. The method according to claim 3, characterized in that The attribute parameters include the thickness of the metal sample, the density of the main elements and solute elements in the metal sample, and the X-ray mass attenuation coefficients of the main elements and solute elements in the metal sample; The determining of the liquid phase solute concentration distribution map corresponding to the microscopic tissue image based on the pure liquid phase image, the reference frame, and the attribute parameters includes: Calculating the concentration corresponding to each pixel in the pure liquid phase image based on the pixel average value of the reference frame, the concentration of the solute element corresponding to the reference frame, the attribute parameters including the thickness of the metal sample, the density of the main element and the solute element in the metal sample, the X-ray mass attenuation coefficient of the main element and the solute element in the metal sample, and the pixel value of each pixel in the pure liquid phase image to obtain a solute concentration distribution map corresponding to the pure liquid phase image; The solute concentration distribution map corresponding to the pure liquid phase image is interpolated to obtain the liquid phase solute concentration distribution map corresponding to the microstructure image.

5. The method according to claim 3, characterized in that The property parameters include the thickness of the metal sample, and the X-ray mass attenuation coefficients of the main elements and solute elements in the metal sample; The determining, based on the reference frame, the liquid solute concentration distribution map, and the attribute parameter, of the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image comprises: For each pixel in the microstructure image, determining the liquid phase mass fraction of the solute element according to the liquid phase solute concentration distribution map; For each pixel in the solid-liquid mixed area in the microstructure image, the solid phase thickness of the solute element corresponding to the pixel is calculated based on the pixel average value of the reference frame, the solid phase mass branch and liquid phase mass fraction corresponding to the pixel, and the X-ray mass attenuation coefficient of the main element and solute element in the metal sample.

6. The method according to claim 1, wherein The property parameters include the thickness of the metal sample and the width of the mushy area in the metal sample; Determining the solid phase fraction and specific surface area of ​​the solidified structure in the microstructure image according to the solid phase thickness corresponding to each pixel in the solid-liquid phase mixing region in the microstructure image and the attribute parameter includes: Determining the solid phase fraction in the mushy region and the height of the mushy region in the metal sample based on the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image, the thickness of the metal sample, and the width of the mushy region in the metal sample; The specific surface area of ​​the solidified structure is determined according to the solid phase thickness corresponding to each pixel of the solid-liquid phase mixed area in the microstructure image and the width and height of the mushy area in the metal sample.

7. The method according to claim 6, characterized in that Determining the specific surface area of ​​the solidified structure according to the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image and the width and height of the mushy region in the metal sample includes: Calculating the solid phase volume of the solidified structure according to the solid phase thickness corresponding to each pixel of the solid-liquid phase mixed area in the microstructure image and the width and height of the mushy area in the metal sample; determining the gradients of the solid phase thickness in the vertical and horizontal directions according to the solid phase thickness corresponding to each pixel in the solid-liquid phase mixing area in the microstructure image; determining the surface area of ​​the solidified tissue based on the gradients in the vertical direction and the horizontal direction; The specific surface area is calculated based on the solid phase volume and surface area of ​​the solidified structure.

8. A device for measuring the permeability of a metal solidification process, characterized in that: include: An acquisition module, configured to acquire a microstructure image of a metal sample during solidification and a binary image corresponding to the microstructure image; wherein the binary image is an image segmentation result of a solid-liquid mixed region and a pure liquid region in the microstructure image; a first calculation module, configured to determine a pure liquid phase image of the microstructure image according to the pure liquid phase region indicated by the binary image; a second calculation module, configured to determine the solid phase thickness corresponding to each pixel in the solid-liquid mixed region in the microstructure image based on the pure liquid phase image, a preset reference frame, and the property parameters of the metal sample; a third calculation module, configured to determine the solid phase fraction and specific surface area of ​​the solidified tissue in the microscopic tissue image based on the solid phase thickness corresponding to each pixel in the solid-liquid phase mixing region in the microscopic tissue image and the attribute parameter; A fourth calculation module is configured to calculate the permeability of the solidified structure based on the solid phase fraction and the specific surface area.

9. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to execute the method for determining the permeability of a metal solidification process according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and the computer program can be executed by a processor to complete the method for measuring the permeability of a metal solidification process according to any one of claims 1 to 7.

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