A method and system for detecting inclusions in alloys

Abstract

This application provides a method and system for detecting inclusions in alloys, relating to the field of materials analysis. The method for detecting inclusions in alloys includes: selecting a scanning mode; determining a threshold for real-time scanning contrast of a scanning electron microscope within the maximum scanning contrast range based on the normal distribution curve of the matrix contrast median of the sample; adjusting the magnification and resolution according to a preset minimum inclusion size; performing a regional scan to obtain a backscattered electron image of the inclusions in the alloy; identifying and statistically analyzing the inclusions; and outputting the inclusion detection results. The normal distribution curve is: where is the median contrast of the matrix, and 'a' is the matrix material coefficient, ranging from 0.8 to 3.3. The method and system for detecting inclusions in alloys provided by this application improve the detection efficiency and accuracy of alloy inclusions, contributing to the optimization of steelmaking processes and the improvement of steel quality.

Description

Technical Field

[0001] This application relates to the field of materials analysis, and more particularly to a method and system for detecting inclusions in alloys. Background Technology

[0002] Inclusions in steel not only disrupt the continuity and density of the steel matrix but also significantly impact its mechanical and performance properties. They reduce the steel's strength, plasticity, toughness, fatigue resistance, and corrosion resistance, thus affecting its mechanical and processing properties. Furthermore, some non-metallic inclusions may be magnetic. By precisely controlling the size, quantity, morphology, composition, and distribution of these inclusions, steelmaking technology can be effectively improved, thereby enhancing the quality of the steel. Therefore, in the production process, to ensure the quality and performance of steel, it is essential to strictly control the content and type of inclusions in the steel.

[0003] An automated inclusion scanning and statistical system employing scanning electron microscopy / energy dispersive spectroscopy can efficiently and comprehensively capture various information about inclusions in steel, overcoming the problems of inefficiency, easy omissions, and limited detection range of traditional manual inspection. The principle of this automated statistical system is based on the molecular weight difference between the matrix and inclusions, which manifests as a contrast difference in backscattered electron images. By preset contrast thresholds between the matrix and a reference material, the system can accurately identify inclusions.

[0004] Traditional automatic inclusion scanning technology can only scan inclusions that appear black under an electron microscope, such as MnS and TiN. However, with the development of the steel industry, high-quality steel has emerged, and the elements added to steel are more complex. Therefore, traditional scanning technology cannot accurately identify these complex inclusions. Thus, how to accurately distinguish inclusions during statistical analysis has become a pressing problem to be solved.

[0005] Document CN202410875188.8 discloses an automatic grayscale adjustment method and device for inclusion statistics. After each acquisition of a field image, the field image is converted into grayscale information and filtered, and the average grayscale value of the substrate is taken. However, the program is too complicated and the detection needs to be filtered in real time.

[0006] Document CN202311096239.9 discloses a method and related equipment for inclusion analysis based on steel materials. This method requires determining the brightness of the matrix and the inclusions before detection, and then performing a proportional calculation based on the brightness relationship in the image and the standard brightness. However, the accuracy of this correspondence during the scanning process is still difficult to meet the actual needs of scientific research.

[0007] Document CN202111635455.7 discloses a characterization method and system for in-situ statistical distribution of inclusions in steel. This scheme can only identify inclusions that are darker than the matrix color and cannot detect composite inclusions, which has certain limitations.

[0008] Therefore, improving the efficiency and accuracy of inclusion detection in alloys is crucial for the development of materials testing. Summary of the Invention

[0009] The purpose of this application is to provide a method and system for detecting inclusions in alloys to solve the above-mentioned problems.

[0010] To achieve the above objectives, this application adopts the following technical solution:

[0011] A method for detecting inclusions in an alloy includes:

[0012] Based on the normal distribution curve of the matrix contrast median of the sample, the threshold of real-time scanning contrast of the scanning electron microscope is determined within the maximum scanning contrast range.

[0013] After correcting the threshold, select the scanning mode, adjust the magnification and resolution according to the preset target inclusion size, perform regional scanning on the sample to obtain backscattered electron images of inclusions in the alloy, identify and statistically analyze the inclusions, and output the inclusion detection results.

[0014] The normal distribution curve is:

[0015] ;

[0016] in, denoted as the median contrast value of the matrix, and α is the matrix material coefficient, which takes values ​​in the range of 0.8-3.3, where α is 2.37 for Fe-based, 3.23 for Ni-based, and 1.56 for Ti-based.

[0017] Preferably, after determining the threshold for the real-time scanning contrast, the method further includes:

[0018] Using aluminum foil as a reference, the selected substrate as the substrate, and the aforementioned threshold as the verification scanning contrast, the actual contrast value of the aluminum foil was determined. I Al ,when I Al If the verification formula is satisfied, the threshold is determined to be correctly selected; the verification formula is:

[0019] ;

[0020] in, I Al k is the actual contrast value of the aluminum foil.基 This is an indicator variable for the base type; it is 1 if the base type is compatible, and 0 if it is not. The matrix type coefficient is 1 for Fe-based, 0.8 for Ni-based, 1.15 for Ti-based, -0.05 for Ce, and -0.03 for La. This is the error term, with a maximum value of 200.

[0021] Preferably, the relationship between the size of the target inclusion and the magnification and resolution satisfies the following formula:

[0022] ;

[0023] in, A The size of the target inclusion is in μm; S This is the absolute value of the area of ​​the device's display area, dimensionless. P represents the single-sided dimension of a pixel in the scanned image, in μm; mag is the magnification factor; y is the pixel size.

[0024] Preferably, when the target inclusion size is 0.2-10µm, the magnification is 40-500 times and the resolution is 1-20 pixels; the scanned image size is 1024×1024, 2048×2048, 4096×4096 or 8192×8192 pixels, and the corresponding single-side size of the scanned image pixel is 1024, 2048, 4096 or 8192; the image acquisition time is 1-10µs and the energy spectrum acquisition time is 0.2-5s.

[0025] Preferably, the scanning mode includes a circular mode, a rectangular mode, or a trapezoidal mode.

[0026] Preferably, the region scanning further includes:

[0027] According to the scanning mode, points are selected within the set range for secondary focusing.

[0028] Preferably, the statistical analysis includes:

[0029] Based on the results of the area scan, data whose scan results consist entirely of the matrix, as well as data containing only C, O, and the matrix, are filtered out.

[0030] Statistics were compiled based on the size and type of inclusions.

[0031] Number density is calculated based on the scan results and the scanned area.

[0032] Preferably, the maximum scanning contrast range is 0-32767.

[0033] Preferably, during the area scanning process, the scanning electron microscope spot size is 500-550, the scanning current is 1.1-1.4nA, the scanning voltage is 15kV or 20kV, and the grating is 20μm or 30μm.

[0034] This application also provides a system for detecting inclusions in an alloy, for performing the method for detecting inclusions in an alloy;

[0035] The system includes:

[0036] Scanning electron microscope / energy dispersive spectroscopy is used to acquire backscattered electron images and composition of inclusions in alloys;

[0037] A contrast monitoring module is used to monitor changes in image contrast values ​​in real time.

[0038] The inclusion identification and statistical analysis module is used to identify and statistically analyze inclusions.

[0039] Compared with the prior art, the beneficial effects of this application include:

[0040] The method for detecting inclusions in alloys provided in this application first removes the contrast distribution range of the matrix within the maximum scanning contrast range based on the normal distribution curve of the matrix's median contrast value, thereby obtaining the threshold of real-time scanning contrast of the scanning electron microscope, thus reducing inclusion identification errors and improving the detection accuracy of inclusions in the alloy; furthermore, by selecting the scanning mode and adjusting the magnification and resolution according to the preset minimum inclusion size, the minimum detectable inclusion size is broken through, making the detection more accurate and efficient.

[0041] The system for detecting inclusions in alloys provided in this application enables real-time monitoring of image contrast values ​​during long-term testing, thereby improving the accuracy and efficiency of inclusion detection.

[0042] The method and system for detecting inclusions in alloys provided in this application help optimize smelting processes and improve alloy quality. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation on the scope of this application.

[0044] Figure 1 Schematic diagrams of different scanning modes;

[0045] Figure 2 The figure shows the analysis results obtained in Example 3;

[0046] Figure 3 This is a distribution map of inclusions differentiated by different colors obtained in Example 4;

[0047] Figure 4 This is a screenshot of the anomaly detection interface obtained from Comparative Example 1. Detailed Implementation

[0048] To better illustrate the technical solution provided in this application, the technical solution will be described in its entirety before the embodiments, as follows:

[0049] A method for detecting inclusions in an alloy includes:

[0050] Based on the normal distribution curve of the matrix contrast median of the sample, the threshold of real-time scanning contrast of the scanning electron microscope is determined within the maximum scanning contrast range.

[0051] After correcting the threshold, select the scanning mode, adjust the magnification and resolution according to the preset target inclusion size, perform regional scanning on the sample to obtain backscattered electron images of inclusions in the alloy, identify and statistically analyze the inclusions, and output the inclusion detection results.

[0052] The normal distribution curve is:

[0053] ;

[0054] in, denoted as the median contrast value of the matrix, and α is the matrix material coefficient, which takes values ​​in the range of 0.8-3.3, where α is 2.37 for Fe-based, 3.23 for Ni-based, and 1.56 for Ti-based.

[0055] It should be noted that the samples require pretreatment before testing, generally including cold mounting, hot mounting, and photocuring. The pretreated samples are then polished to remove any obvious scratches. Conductive adhesive is then applied to the sample surface to improve conductivity under an electron microscope. Aluminum foil is then adhered to the conductive adhesive to cover it and provide contrast with the substrate.

[0056] Cold setting: Select appropriate setting materials (such as epoxy resin or polyester resin) and a mold. Ensure the metal sample surface is clean, free of oil and oxides. Mix the resin and hardener in the specified ratio. Place the metal sample into the mold, ensuring the sample is positioned correctly. Slowly pour the mixed resin into the mold, covering the metal sample. Allow the resin to cure at room temperature; depending on the resin type, curing time may range from several hours to a day. Once the resin is fully cured, remove the set metal sample from the mold. Trim and polish the resin surface to make it smooth and flat.

[0057] Hot setting: Clean the metal sample, ensuring it is free of contaminants. Place the sample in the hot setting machine, and following the pre-set program, select the appropriate setting material (including conductive and non-conductive powders) to reach a specific temperature. After the program is complete, remove the sample and refine and polish it to ensure it is securely fixed and has a clean appearance.

[0058] After mounting, the sample can be scanned by region after setting the area on a plane. This efficiently solves the problem of having to reset the area after scanning a single sample. Since a group of samples are in the same detection environment, the error generated during the testing process is minimized.

[0059] Photocuring: Select a suitable resin and photoinitiator for photocuring. Ensure the metal sample surface is clean. Mix the resin and photoinitiator. Place the metal sample in a mold and pour in the mixed resin. Irradiate the mixture with a UV lamp to initiate resin curing. The resin cures rapidly under UV light. After curing, remove the inlaid metal sample from the mold and perform necessary trimming and polishing.

[0060] The alloy referred to in this application may be, for example, various types of steel, or other alloys that will produce inclusions during the smelting process.

[0061] It should be noted that the alloy refers not only to the final product of smelting, but also to the products of the smelting process.

[0062] In an optional implementation, after determining the threshold for real-time scan contrast, the method further includes:

[0063] Using aluminum foil as a reference, the selected substrate as the substrate, and the aforementioned threshold as the verification scanning contrast, the actual contrast value of the aluminum foil was determined. I Al ,when I Al If the verification formula is satisfied, the threshold is determined to be correctly selected; the verification formula is:

[0064] ;

[0065] in, I Al k is the actual contrast value of the aluminum foil. 基 This is an indicator variable for the base type; it is 1 if the base type is compatible, and 0 if it is not. The matrix type coefficient is 1 for Fe-based, 0.8 for Ni-based, 1.15 for Ti-based, -0.05 for Ce, and -0.03 for La. This is the error term, with a maximum value of 200.

[0066] The contrast threshold determined by the normal distribution formula may still not be accurate enough to determine the appropriate actual contrast threshold. Therefore, aluminum foil is used as a reference to verify the threshold. Typically, k... 基 Choosing option 1 means that the verification process initially assumes the substrate conforms. If the error between the actual detected contrast value and the calculated contrast value is controlled within 200, the determined contrast threshold can be considered appropriate. This verification process further ensures the accuracy of the determined threshold. If it does not conform, corrections are made by adjusting contrast, brightness, and filament position.

[0067] Ce and La elements are usually present as dopants, not in the pure matrix form. During verification, their relevant data are introduced to ensure the accuracy of the verification results.

[0068] In an optional implementation, the relationship between the size of the target inclusion and the magnification and resolution satisfies the following formula:

[0069] ;

[0070] in, A The size of the target inclusion is in μm; S This is the absolute value of the area of ​​the device's display area (this value is device-dependent) and is dimensionless. P represents the single-sided dimension of a pixel in the scanned image, in μm; mag is the magnification factor; y is the pixel size.

[0071] In one optional embodiment, when the inclusion size is 0.2-10µm, the magnification is 40-500 times and the resolution is 1-20 pixels; the scanned image size is 1024×1024, 2048×2048, 4096×4096 or 8192×8192 pixels, and the corresponding single-side size of the scanned image pixel is 1024, 2048, 4096 or 8192; the image acquisition time is 1-10µs and the energy spectrum acquisition time is 0.2-5s.

[0072] Preferably, when the target inclusion size is 0.2-10µm, the magnification is 100-300 times and the resolution is 3-15 pixels; the scanned image size is 1024×1024, 2048×2048, or 4096×4096 pixels, and the corresponding single-side size of the scanned image pixel is 1024, 2048, or 4096; the image acquisition time is 1-6µs, and the energy spectrum acquisition time is 0.2-3s.

[0073] In one optional implementation, the scanning mode includes a circular mode, a rectangular mode, or a trapezoidal mode.

[0074] Three scanning modes such as Figure 1As shown.

[0075] The preferred trapezoidal pattern has scanning areas of 3mm * 3mm, 5mm * 5mm, 7mm * 7mm, 10mm * 10mm, etc.

[0076] In an optional implementation, the region scan further includes:

[0077] According to the scanning mode, points are selected within the set range for secondary focusing.

[0078] In an optional implementation, the statistical analysis includes:

[0079] Based on the results of the area scan, data whose scan results consist entirely of the matrix, as well as data containing only C, O, and the matrix, are filtered out.

[0080] Statistics were compiled based on the size and type of inclusions.

[0081] Number density is calculated based on the scan results and the scanned area.

[0082] In one optional implementation, the maximum scan contrast range is 0-32767.

[0083] In one optional implementation, during the area scanning process, the scanning electron microscope spot size is 500-550, the scanning current is 1.1-1.4nA, the scanning voltage is 15kV or 20kV, and the grating is 20μm or 30μm.

[0084] This application also provides a system for detecting inclusions in an alloy, for performing the method for detecting inclusions in an alloy;

[0085] The system includes:

[0086] Scanning electron microscope / energy dispersive spectroscopy is used to acquire backscattered electron images and composition of inclusions in alloys;

[0087] A contrast monitoring module is used to monitor changes in image contrast values ​​in real time.

[0088] The inclusion identification and statistical analysis module is used to identify and statistically analyze inclusions.

[0089] The implementation schemes of this application will be described in detail below with reference to specific embodiments. However, those skilled in the art will understand that the following embodiments are only for illustrating this application and should not be regarded as limiting the scope of this application. Unless otherwise specified in the embodiments, conventional conditions or conditions recommended by the manufacturer shall apply. Reagents or instruments used without specified manufacturers are all conventional products that can be purchased commercially.

[0090] Example 1

[0091] This embodiment provides a system for detecting inclusions in alloys, including: a scanning electron microscope / energy dispersive spectroscopy instrument, a contrast monitoring module, and an inclusion identification and statistical analysis module;

[0092] Scanning electron microscope / energy dispersive spectroscopy is used to acquire backscattered electron images and composition of inclusions in alloys; contrast monitoring module is used to monitor changes in image contrast values ​​in real time; inclusion identification and statistical analysis module is used to identify and statistically analyze inclusions.

[0093] Example 2

[0094] This embodiment provides a method for detecting inclusions in an alloy. The sample is a high-temperature alloy smelted in a vacuum induction furnace, specifically grade GH4169. The system for detecting inclusions in alloys provided in Example 1 is used for detection, and the specific steps include:

[0095] (1) The sample is cold-mounted, and the prepared sample is polished to make its surface free of obvious scratches. Conductive adhesive is pasted on the sample surface to improve its conductivity under electron microscopy. Aluminum foil is pasted on the conductive adhesive to cover it and to compare the contrast with the substrate.

[0096] (2) Start the scanning electron microscope / energy dispersive spectrometer and name the storage path; set the scan according to the type of inclusion to obtain more accurate data on the chemical composition, size, morphology and coordinate position of the inclusion.

[0097] During the detection of inclusions, the electron microscope spot size was set to 500.

[0098] (3) Nickel metal was selected as the matrix, and the median value of the matrix contrast was chosen to satisfy the following normal distribution:

[0099] ,

[0100] Where a takes the value 3.23.

[0101] Within the maximum contrast range of 0-32767, based on the range corresponding to the removal of the intermediate matrix contrast value (μ±3σ, where μ is the x corresponding to the maximum value of the normal curve, σ=616.25a), the threshold values ​​for real-time scanning contrast of the scanning electron microscope are determined to be 0-12000 and 21984-32767.

[0102] Add a reference aluminum foil, and using the above threshold as the verification scan contrast, determine the actual contrast value of the aluminum foil. The following formulas can guarantee a relatively accurate range of inclusion contrast:

[0103] ,

[0104] Since the matrix of the test sample is Ni, its The value is 0.8, as measured in the experiment. The value is 2300, the difference is 100, which is less than 200. Based on this, the above threshold value is reasonable.

[0105] (4) Based on the target inclusion size required by the user (i.e. the minimum inclusion size set by the user), set the relationship between magnification and resolution to enable scanning of the minimum inclusion size required, and to scan, identify and count the inclusions. The sample scanning mode can be circular, rectangular, trapezoidal, etc.

[0106] The relationship between the size of the target inclusion and the magnification and resolution satisfies the following formula:

[0107] ;

[0108] The absolute value S of the display area in this device is 1.522, the minimum inclusion size detection is 0.38µm, the magnification is 219 times, the resolution is 3 pixels, the scanned image size is 2048×2048 pixels, the image acquisition time is 3µs, and the energy spectrum acquisition time is 0.3s.

[0109] The scanning mode is trapezoidal, and the scanning area is 5*5mm.

[0110] When the contrast value is detected to deviate from the preset value, the filament position is adjusted to bring the image contrast value back to the normal range; the scanning current is 1.3nA, the scanning voltage is 20kV, and the grating is 30µm.

[0111] (5) Take 4 points within the set area and perform secondary focusing to ensure the accuracy of scanning and output the inclusion detection results.

[0112] Inclusion analysis includes one or more of the following steps:

[0113] (1) Based on the scanning results, filter out data whose components are all matrix and data containing only C, O and matrix;

[0114] (2) Statistics can be compiled based on the size of the inclusions according to the scanning results;

[0115] (3) Based on the scanning results and the scanning area obtained from the test, further calculations such as number density are performed.

[0116] The final test results are shown in Table 1:

[0117] Table 1. Detection results of Example 2

[0118]

[0119] Example 3

[0120] Referring to the method provided in Example 2, steel samples were taken and tested throughout the entire smelting process. The system for detecting inclusions in alloys provided in Example 1 was used for detection, specifically including the following steps:

[0121] (1) The sample is cold-mounted, and the treated sample is polished to remove obvious scratches from its surface. Conductive adhesive is then applied to the sample surface to improve its conductivity under electron microscopy.

[0122] (2) Start the scanning electron microscope / energy dispersive spectrometer and name the storage path; set the scan according to the type of inclusion to obtain more accurate data on the chemical composition, size, morphology and coordinate position of the inclusion.

[0123] During the detection of inclusions, the electron microscope spot size was set to 530.

[0124] (3) With iron as the matrix, the median value of the matrix contrast makes it satisfy the following normal distribution:

[0125] ,

[0126] Where a takes the value 2.37.

[0127] Within the maximum contrast range of 0-32767, the range corresponding to the intermediate matrix contrast value (μ±3σ, where μ is the x corresponding to the maximum value of the normal curve, σ=616.25a) is removed, and the threshold values ​​of real-time scanning contrast for scanning electron microscopy are determined to be 0-12000 and 20384-32767.

[0128] Add a reference aluminum foil, and using the above threshold as the verification scan contrast, determine the actual contrast value of the aluminum foil. The following formulas can guarantee a relatively accurate range of inclusion contrast:

[0129] ,

[0130] Since the matrix of the test sample is Fe, its The value is 1, which is the result of the experimental detection. The value is 3000, the difference is 0, which is less than 200. Based on this, the above threshold value is reasonable.

[0131] (4) Based on the target inclusion size required by the user, set the relationship between magnification and resolution to enable scanning of the minimum required inclusion size, and to scan, identify and count the inclusions. The sample scanning mode can be circular, rectangular, trapezoidal, etc.

[0132] The relationship between the size of the target inclusion and the magnification and resolution satisfies the following formula:

[0133] ;

[0134] The absolute value S of the display area in this device is 1.522, the minimum inclusion size detection is 1µm, the magnification is 117 times, the resolution is 5 pixels, the scanned image size is 1024×1024 pixels, the image acquisition time is 2µs, and the energy spectrum acquisition time is 0.4s.

[0135] The scanning mode is rectangular, with a scanning area of ​​7*7mm. Three regions within a single plane are drawn simultaneously to minimize time consumption.

[0136] When the contrast value is detected to deviate from the preset value, the filament position is adjusted to bring the image contrast value back to the normal range; the scanning current is 1.2nA, the scanning voltage is 15kV, and the grating is 20µm.

[0137] (5) Take 4 points within the set area and perform secondary focusing to ensure the accuracy of scanning and output the inclusion detection results.

[0138] Inclusion analysis includes one or more of the following steps:

[0139] (1) Based on the scanning results, filter out data whose components are all matrix and data containing only C, O and matrix;

[0140] (2) Statistics can be compiled based on the size of the inclusions according to the scanning results;

[0141] (3) Based on the scanning results and the scanning area obtained from the test, further calculations such as number density are performed.

[0142] Analysis results as follows Figure 2 As shown.

[0143] Example 4

[0144] Referring to the method provided in Example 2, rare earth element Ce was added to ferritic stainless steel for laboratory smelting, and samples were sent for testing to ensure successful Ce incorporation. The system for detecting inclusions in the alloy provided in Example 1 was used for detection, specifically including the following steps:

[0145] (1) The sample to be tested is polished to remove obvious scratches and obtain a relatively flat test surface. Conductive adhesive is then applied to the sample surface to improve its conductivity under electron microscopy.

[0146] (2) Start the scanning electron microscope / energy dispersive spectrometer and name the storage path; set the scan according to the type of inclusion to obtain more accurate data on the chemical composition, size, morphology and coordinate position of the inclusion.

[0147] During the detection of inclusions, the electron microscope spot size was set to 550.

[0148] (3) With iron as the matrix, the median value of the matrix contrast makes it satisfy the following normal distribution:

[0149] ,

[0150] Where a takes the value 1.

[0151] Within the maximum contrast range of 0-32767, the range corresponding to the intermediate matrix contrast value (μ±3σ, where μ is the x corresponding to the maximum value of the normal curve, σ=616.25a) is removed, and the threshold values ​​of real-time scanning contrast for scanning electron microscopy are determined to be 0-12000 and 20384-32767.

[0152] Since the steel contains two relatively obvious types of inclusions, in order to make the contrast between black and white inclusions greater, the contrast value of the inclusions is in the range of 0-12000 and 20500-32767.

[0153] Add a reference aluminum foil, and using the above threshold as the verification scan contrast, determine the actual contrast value of the aluminum foil. The following formulas can guarantee a relatively accurate range of inclusion contrast:

[0154] ,

[0155] The matrix of the test sample is Fe, and its The value is 1. Since the rare earth content in steel is not negligible, the influence of rare earth on the matrix should also be considered, resulting in a value of -0.15. (This is from an experimental test.) The value is 2700, the difference Therefore, the values ​​of the above thresholds are reasonable.

[0156] (4) Based on the target inclusion size required by the user, set the relationship between magnification and resolution to enable scanning of the minimum required inclusion size, and to scan, identify and count the inclusions. The sample scanning mode can be circular, rectangular, trapezoidal, etc.

[0157] The relationship between the size of the target inclusion and the magnification and resolution satisfies the following formula:

[0158] ;

[0159] The absolute value S of the display area in this device is 1.522, the minimum inclusion size detection is 0.21µm, the magnification is 400 times, the resolution is 3 pixels, the scanned image size is 2048×2048 pixels, the image acquisition time is 2µs, and the energy spectrum acquisition time is 0.3s.

[0160] The scanning mode is trapezoidal, and the scanning area is 3*3mm. Three regions within a plane are drawn simultaneously to save time to the greatest extent possible.

[0161] When the contrast value is detected to deviate from the preset value, the filament position is adjusted to bring the image contrast value back to the normal range; the scanning current is 1.4nA, the scanning voltage is 20kV, and the grating is 30µm.

[0162] (5) Take 4 points within the set area and perform secondary focusing to ensure the accuracy of scanning and output the inclusion detection results.

[0163] Inclusion analysis includes one or more of the following steps:

[0164] (1) Based on the scanning results, filter out data whose components are all matrix and data containing only C, O and matrix;

[0165] (2) Statistics can be compiled based on the size of the inclusions according to the scanning results;

[0166] (3) Based on the scanning results and the scanning area obtained from the test, further calculations such as number density are performed.

[0167] The resulting inclusion distribution map, differentiated by different colors, is shown below. Figure 3 As shown.

[0168] Comparative Example 1

[0169] Unlike Example 3, a is selected as 2.9, and the contrast threshold is selected as 0-11022 and 21745-32767.

[0170] When using aluminum foil for verification, since the matrix of the test sample is Fe, its The value is 1, which is the result of the experimental detection. The value is 2700. Therefore, its value is unreasonable, further illustrating that the range of inclusion contrast is inaccurate.

[0171] The system for detecting inclusions in alloys provided in this application exhibits a detection anomaly when using the aforementioned contrast threshold. The system interface is as follows: Figure 4 As shown.

[0172] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for detecting inclusions in an alloy, characterized in that, include: Based on the normal distribution curve of the matrix contrast median of the sample, the threshold of real-time scanning contrast of the scanning electron microscope is determined within the maximum scanning contrast range. After correcting the threshold, select the scanning mode, adjust the magnification and resolution according to the preset target inclusion size, perform regional scanning on the sample to obtain backscattered electron images of inclusions in the alloy, identify and statistically analyze the inclusions, and output the inclusion detection results. The normal distribution curve is: ； in, denoted as the median contrast value of the matrix, and α is the matrix material coefficient, which takes values ​​in the range of 0.8-3.3, where α is 2.37 for Fe-based, 3.23 for Ni-based, and 1.56 for Ti-based.

2. The method for detecting inclusions in an alloy according to claim 1, characterized in that, After determining the threshold for the real-time scan contrast, the method further includes: Using aluminum foil as a reference, the selected substrate as the substrate, and the aforementioned threshold as the verification scanning contrast, the actual contrast value of the aluminum foil was determined. I Al ,when I Al If the verification formula is satisfied, the threshold is determined to be correctly selected; the verification formula is: ； in, I Al k is the actual contrast value of the aluminum foil. 基 This is an indicator variable for the base type; it is 1 if the base type is compatible, and 0 if it is not. The matrix type coefficient is 1 for Fe-based, 0.8 for Ni-based, 1.15 for Ti-based, -0.05 for Ce, and -0.03 for La. This is the error term, with a maximum value of 200.

3. The method for detecting inclusions in an alloy according to claim 1, characterized in that, The relationship between the size of the target inclusion and the magnification and resolution satisfies the following formula: ； in, A The size of the target inclusion is in μm; S This is the absolute value of the area of ​​the device's display area, dimensionless. P represents the single-sided dimension of a pixel in the scanned image, in μm; mag is the magnification factor; y is the pixel size.

4. The method for detecting inclusions in an alloy according to claim 3, characterized in that, When the target inclusion size is 0.2-10µm, the magnification is 40-500 times and the resolution is 1-20 pixels; the scanned image size is 1024×1024, 2048×2048, 4096×4096 or 8192×8192 pixels, and the corresponding single-side size of the scanned image pixel is 1024, 2048, 4096 or 8192; the image acquisition time is 1-10µs and the energy spectrum acquisition time is 0.2-5s.

5. The method for detecting inclusions in an alloy according to claim 1, characterized in that, The scanning modes include circular mode, rectangular mode, or trapezoidal mode.

6. The method for detecting inclusions in an alloy according to claim 5, characterized in that, The region scan also includes: According to the scanning mode, points are selected within the set range for secondary focusing.

7. The method for detecting inclusions in an alloy according to claim 1, characterized in that, The statistical analysis includes: Based on the results of the area scan, data whose scan results consist entirely of the matrix, as well as data containing only C, O, and the matrix, are filtered out. Statistics were compiled based on the size and type of inclusions. Number density is calculated based on the scan results and the scanned area.

8. The method for detecting inclusions in an alloy according to claim 1, characterized in that, The maximum scanning contrast range is 0-32767.

9. The method for detecting inclusions in an alloy according to claim 1, characterized in that, During the scanning of the area, the scanning electron microscope spot size is 500-550, the scanning current is 1.1-1.4nA, the scanning voltage is 15kV or 20kV, and the grating is 20μm or 30μm.

10. A system for detecting inclusions in an alloy, characterized in that, For performing the method for detecting inclusions in an alloy as described in any one of claims 1-9; The system includes: Scanning electron microscope / energy dispersive spectroscopy is used to acquire backscattered electron images and composition of inclusions in alloys; A contrast monitoring module is used to monitor changes in image contrast values ​​in real time. The inclusion identification and statistical analysis module is used to identify and statistically analyze inclusions.

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