Method for representing relationship between material defect and performance and metal additive manufacturing method

Abstract

The invention discloses a method for representing the relationship between material defects and performance and a metal additive manufacturing method. The method comprises the following steps that S1, a cavity size model is set; s2, arranging the cavities of each size in a test block in a preset array mode, and melting and forming a sample through selective laser; s3, separating the metallographic sample, and carrying out metallographic sample preparation; s4, preparing a prefabricated defect sample according to the selected project; s5, testing the performance of the sample according to the standard, enabling the test result to correspond to the defect size, the porosity and the metallograph of the test result, and counting all data to form a defect proportion and performance corresponding map of the material; and S6, performing performance prediction and qualification judgment by using the atlas. According to the method, defects are prefabricated in the samples, and the material performance can be further predicted through the defects by testing the performance of the samples with different defect sizes.

Description

Technical Field

[0001] This invention relates to the field of additive manufacturing technology, and in particular, to a method for characterizing the relationship between material defects and properties. Furthermore, this invention also relates to a metal additive manufacturing method including the aforementioned method for characterizing the relationship between material defects and properties. Background Technology

[0002] Defects in materials and components can significantly impact their performance and lifespan. With the emergence of new processes and methods, testing material performance using traditional defect and performance characterization techniques suffers from long testing cycles and costly practices.

[0003] Additive manufacturing is a high-performance metal forming technology used to manufacture precision and complex structures. It has broad application prospects in high-precision fields such as aerospace. However, defects in the manufactured materials can significantly affect the mechanical properties of the parts, further impacting their service life. With the continuous emergence of new processes and methods, predicting material life using traditional defect characterization and material property characterization methods suffers from long testing cycles and cost waste. Therefore, finding a method to predict the relationship between material defects and mechanical properties is crucial.

[0004] In the prior art, such as the technical solutions with publication numbers CN111203539A, CN111203537A, CN111203536A, CN117900507A, and CN114839010A, a method for defect prefabrication is disclosed. In the technical solutions with publication numbers CN118275539A and CN119804514A, standard samples are provided for non-destructive testing of additively manufactured parts. In the prior art, such as publication number CN1148... The technical solution 39010A addresses porosity and incomplete fusion defects in additive manufacturing. It provides drawings of mechanical property test bars and defect manufacturing methods, focusing only on static tensile and fatigue properties. Furthermore, the porosity defect prefabrication method has significant problems: the spherical cavity cannot produce porosity defects with smooth inner walls, and can only produce localized incomplete fusion defects. Porosity defects require high energy input to generate. Although this technical solution evaluates the impact of defects on performance, it is difficult to guide the judgment of part qualification in practical applications, resulting in low efficiency and high testing costs. Summary of the Invention

[0005] This invention provides a method for characterizing the relationship between material defects and performance, as well as a metal additive manufacturing method, to solve the technical problems of long test cycles and cost waste in predicting the life of materials using traditional defect characterization and material performance characterization methods.

[0006] According to one aspect of the present invention, a method for characterizing the relationship between material defects and properties is provided, comprising the following: S1. Set the cavity size model; S2. Arrange cavities of each size in a preset array in the test block, and form the test specimen by selective laser melting; S3. After separating the metallographic sample, perform metallographic sample preparation; S4. Prepare pre-made defect samples according to the selected project; S5. Perform performance tests on the specimens according to the standard, and correlate the test results with the defect size, porosity and metallographic photographs of the specimens. After statistical analysis of all data, based on the metallographic photographs of defects generated by various cavity cross-sectional shapes and sizes, systematically summarize the relationship between defects and performance, and obtain a spectrum of the relationship between defects and performance of the specimen material to define the allowable range of defects in the parts. S6. Use graphs for performance prediction and qualification determination. Make a preliminary judgment on room temperature tensile properties by comparing the metallographic images in the furnace with those in the graphs. Make a comprehensive judgment on whether the parts are qualified based on the preliminary judgment of room temperature tensile properties and the index requirements. When the results of the metallographic test in the furnace contradict the results of the performance test of the furnace test sample, use the comparison relationship as a reference for judgment.

[0007] As a further improvement to the above technical solution, step S1 includes: S11. Match and set the size of the cavity cross section according to the experimental requirements. By adjusting the size parameters of the built-in cavity, samples with different defect ratios of incomplete fusion defects and linear defects can be obtained in the sample preparation step. S12. Establish a test list and perform cavity modeling.

[0008] As a further improvement to the above technical solution, step S2 includes: S21. Determine whether the cavity array arrangement direction is horizontal or vertical based on the observation direction of the cavity cross section. The top surface of the horizontal metallographic sample is a polished surface, and the side surface of the vertical metallographic sample is a polished surface. S22. Adjust the distance difference between each row or column and the polished surface, taking into account observation efficiency and observation effect; S23. Selective laser melting to form a specimen.

[0009] As a further improvement to the above technical solution, step S2 includes: The raw materials for selective laser melting forming are aluminum or aluminum alloy powder, titanium or titanium alloy powder, copper or copper alloy powder, nickel or nickel alloy powder, or iron or iron alloy powder, and the particle size of the raw materials is 5μm to 180μm.

[0010] As a further improvement to the above technical solution, step S2 includes: The selective laser melting forming is performed under the protection of argon or nitrogen atmosphere or in a vacuum.

[0011] As a further improvement to the above technical solution, step S3 includes: After separating the metallographic sample, metallographic sample preparation was performed, and optical microscopy was used to take photos. The defect size corresponding to each cavity in the photo was analyzed, and the sample with the largest defect size in each row was selected as the porosity analysis object. Its porosity and size were correlated with the cavity size placed in the corresponding row. The defect size was classified, the porosity was recorded, and a statistical table of defect and porosity data of the material was obtained.

[0012] As a further improvement to the above technical solution, step S4 includes: Pre-fabricate defects throughout the blank, or pre-fabricate defects in the working section of the specimen.

[0013] As a further improvement to the above technical solution, in step S5, the performance test includes density, metallography, tensile strength, fatigue, fracture toughness, crack propagation, thermal conductivity, electrical conductivity, and specific heat capacity.

[0014] According to another aspect of the present invention, a metal additive manufacturing method is also provided, which includes the above-described method for characterizing the relationship between material defects and properties.

[0015] The present invention has the following beneficial effects: This method, using a built-in cavity method, produces defects with strong consistency in size and good reproducibility. Based on prior performance testing of samples with different defect proportions, material properties can be quickly inferred from metallographic results. Furthermore, the metallographic index requirements can be derived by combining this comparison with performance requirements, eliminating the need for frequent testing of furnace-fired samples, thus saving costs. In actual production, when furnace-fired metallographic test results contradict furnace-fired performance test results, the above comparison can be used as a reference for judgment, reducing repeated tests. Moreover, after performance testing, the test results are correlated with their defect size, porosity, and metallographic photographs. After statistical analysis of all data, a defect proportion and performance correlation chart for the material is generated, allowing for a more precise definition of the allowable defect range for parts and improving the efficiency of inspection and testing procedures. This method improves efficiency and reduces the cost of mass-produced parts inspection. The modeling used is reusable, and the cavity size can be adjusted arbitrarily. It can be applied to different materials to obtain the relationship between defects and performance, making it widely applicable. This method goes beyond simply pre-creating defects in samples; further, performance testing of samples with different defect sizes allows for the prediction of material properties through defects. Furthermore, the performance testing in this method allows for the free selection and adjustment of testing items according to actual needs, making costs flexible and controllable. It allows for testing of a specific performance and obtaining the corresponding defect-performance relationship. Based on this method, when determining the qualification of parts in actual production, the method can detect permissible defects and classify defect levels, allowing some minor defects to pass acceptance requirements, increasing the part qualification rate and reducing production costs.

[0016] In addition to the objectives, features, and advantages described above, the present invention has other objectives, features, and advantages. The invention will now be described in further detail with reference to the figures. Attached Figure Description

[0017] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a schematic diagram of the defect array and polished surface in a transverse metallographic sample according to a preferred embodiment of the present invention, wherein... Figure 1 (a) is a schematic diagram of the defect array in a transverse metallographic sample according to a preferred embodiment of the present invention. Figure 1 (b) Schematic diagram of the polished surface of the transverse metallographic specimen according to a preferred embodiment of the present invention. Figure 1 , Figure 1 (c) is a top view of the defect array in a transverse metallographic specimen according to a preferred embodiment of the present invention. Figure 1 (d) is a schematic diagram of the polished surface of the transverse metallographic sample according to a preferred embodiment of the present invention. Figure 2 ; Figure 2 This is a schematic diagram of the defect array and polished surface in a vertical metallographic sample according to a preferred embodiment of the present invention, wherein... Figure 2 (a) is a schematic diagram of the defect array in a vertical metallographic specimen according to a preferred embodiment of the present invention. Figure 2 (b) Schematic diagram of the polished surface of a vertical metallographic specimen according to a preferred embodiment of the present invention. Figure 1 , Figure 2 (c) is a top view of the defect array in a vertical metallographic specimen according to a preferred embodiment of the present invention. Figure 2 (d) is a schematic diagram of the polished surface of a vertical metallographic specimen according to a preferred embodiment of the present invention. Figure 2 ; Figure 3 This is a statistical table of defect size and porosity according to a preferred embodiment of the present invention, wherein, Figure 3 (a) is a metallographic photograph of a preferred embodiment of the present invention. Figure 3 (b) is a second metallographic photograph of a preferred embodiment of the present invention. Figure 3 (c) is a schematic diagram of defect size and porosity statistics in a preferred embodiment of the present invention; Figure 4 The drawings for machining room temperature tensile test specimens used in the preferred embodiment of the present invention are shown. Figure 5 This is a schematic diagram of a defective blank sample according to a preferred embodiment of the present invention; Figure 6 For different porosities in a specific embodiment of the present invention Comparison of properties between hollow and dense specimens; Figure 7 For different porosities in a specific embodiment of the present invention Comparison of properties between hollow and dense specimens; Figure 8 For different porosities in a specific embodiment of the present invention Comparison of metallographic images of hollow and dense structures, among which... Figure 8 (a) is a specific embodiment of the present invention Schematic diagram of the dense control sample with a porosity of 0.01%. Figure 8 (b) is a specific embodiment of the present invention. Schematic diagram of a defective sample with a porosity of 0.06%. Figure 8 (c) is a specific embodiment of the present invention. Schematic diagram of a defective sample with a porosity of 0.12%. Figure 8 (d) is a specific embodiment of the present invention. Schematic diagram of a defective sample with a porosity of 0.18%; Figure 9 For different porosities in a specific embodiment Comparison of metallographic images of hollow and dense structures, among which... Figure 9 (a) is a specific embodiment Schematic diagram of the dense control sample with a porosity of 0.01%. Figure 9 (b) is a specific embodiment Schematic diagram of a defective sample with a porosity of 0.3%. Figure 9 (c) is a specific embodiment Schematic diagram of a defective sample with a porosity of 0.6%. Figure 9 (d) is a specific embodiment Schematic diagram of a defective sample with a porosity of 0.9%; Figure 10 This is a flowchart of a preferred embodiment of the present invention. Detailed Implementation

[0018] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, the present invention can be implemented in many different ways as defined and covered below.

[0019] Figure 1 This is a schematic diagram of the defect array and polished surface in a transverse metallographic sample according to a preferred embodiment of the present invention, wherein... Figure 1 (a) is a schematic diagram of the defect array in a transverse metallographic sample according to a preferred embodiment of the present invention. Figure 1 (b) Schematic diagram of the polished surface of the transverse metallographic specimen according to a preferred embodiment of the present invention. Figure 1 , Figure 1 (c) is a top view of the defect array in a transverse metallographic specimen according to a preferred embodiment of the present invention. Figure 1 (d) is a schematic diagram of the polished surface of the transverse metallographic sample according to a preferred embodiment of the present invention. Figure 2 ; Figure 2 This is a schematic diagram of the defect array and polished surface in a vertical metallographic sample according to a preferred embodiment of the present invention, wherein... Figure 2 (a) is a schematic diagram of the defect array in a vertical metallographic specimen according to a preferred embodiment of the present invention. Figure 2 (b) Schematic diagram of the polished surface of a vertical metallographic specimen according to a preferred embodiment of the present invention. Figure 1 , Figure 2 (c) is a top view of the defect array in a vertical metallographic specimen according to a preferred embodiment of the present invention. Figure 2 (d) is a schematic diagram of the polished surface of a vertical metallographic specimen according to a preferred embodiment of the present invention. Figure 2 ; Figure 3 This is a statistical table of defect size and porosity according to a preferred embodiment of the present invention, wherein, Figure 3 (a) is a metallographic photograph of a preferred embodiment of the present invention. Figure 3 (b) is a second metallographic photograph of a preferred embodiment of the present invention. Figure 3 (c) is a schematic diagram of defect size and porosity statistics in a preferred embodiment of the present invention; Figure 4 The drawings for machining room temperature tensile test specimens used in the preferred embodiment of the present invention are shown. Figure 5This is a schematic diagram of a defective blank sample according to a preferred embodiment of the present invention; Figure 6 For different porosities in a specific embodiment of the present invention Comparison of properties between hollow and dense specimens; Figure 7 For different porosities in a specific embodiment of the present invention Comparison of properties between hollow and dense specimens; Figure 8 For different porosities in a specific embodiment of the present invention Comparison of metallographic images of hollow and dense structures, among which... Figure 8 (a) is a specific embodiment of the present invention Schematic diagram of the dense control sample with a porosity of 0.01%. Figure 8 (b) is a specific embodiment of the present invention. Schematic diagram of a defective sample with a porosity of 0.06%. Figure 8 (c) is a specific embodiment of the present invention. Schematic diagram of a defective sample with a porosity of 0.12%. Figure 8 (d) is a specific embodiment of the present invention. Schematic diagram of a defective sample with a porosity of 0.18%; Figure 9 For different porosities in a specific embodiment Comparison of metallographic images of hollow and dense structures, among which... Figure 9 (a) is a specific embodiment Schematic diagram of the dense control sample with a porosity of 0.01%. Figure 9 (b) is a specific embodiment Schematic diagram of a defective sample with a porosity of 0.3%. Figure 9 (c) is a specific embodiment Schematic diagram of a defective sample with a porosity of 0.6%. Figure 9 (d) is a specific embodiment Schematic diagram of a defective sample with a porosity of 0.9%; Figure 10 A flowchart of a preferred embodiment of the present invention; like Figures 1 to 10 As shown, the method for characterizing the relationship between material defects and properties in this embodiment includes the following: S1. Set the cavity size model; S2. Arrange cavities of each size in a preset array in the test block, and form the test specimen by selective laser melting; S3. After separating the metallographic sample, perform metallographic sample preparation; S4. Prepare pre-made defect samples according to the selected project; S5. Perform performance tests on the samples according to the standard and correlate the test results with the defect size, porosity and metallographic photographs. After statistical analysis of all data, form a defect ratio and performance correspondence chart for the material. S6. Use graphs for performance prediction and qualification determination.

[0020] Understandably, this method, using the built-in cavity method, produces defects with strong consistency in size and good reproducibility. Based on the prior performance testing of samples with different defect proportions, material properties can be quickly inferred from metallographic results. Furthermore, the metallographic index requirements can be derived by combining this comparison with performance requirements, eliminating the need for frequent testing of furnace-fed samples, thus saving costs. In actual production, when furnace-fed metallographic test results contradict furnace-fed performance test results, the above comparison can be used as a reference for judgment, reducing repeated tests. Moreover, after performance testing, the test results are correlated with their defect sizes, porosity, and metallographic photographs. After statistical analysis of all data, a defect proportion and performance correlation chart for the material is generated, allowing for a more precise definition of the allowable defect range for parts and improving inspection and testing capabilities. This method improves process efficiency and reduces the cost of mass-produced parts inspection. The modeling used is reusable, and the cavity size can be adjusted arbitrarily. It can be applied to different materials to obtain the relationship between defects and performance, making it widely applicable. This method goes beyond simply pre-creating defects in samples; further, performance testing of samples with different defect sizes allows for the prediction of material properties through defects. Furthermore, the performance testing in this method allows for the free selection and adjustment of testing items according to actual needs, making costs flexible and controllable. It allows for testing of specific performance characteristics and obtaining the corresponding defect-performance relationship. Based on this method, when determining the qualification of parts in actual production, the method can detect permissible defects and classify defect levels, allowing some minor defects to pass acceptance requirements, increasing the part qualification rate and reducing production costs.

[0021] In some preferred embodiments, step S1 includes: S11. Match and set the size of the cavity cross section according to the experimental requirements. By adjusting the size parameters of the built-in cavity, samples with different defect ratios of incomplete fusion defects and linear defects can be obtained in the sample preparation step. It is understandable that the cavity cross-section can be circular, quadrilateral, or other shapes, and the size of the cavity cross-section and the cavity length are set according to the experimental requirements; S12. Establish a test list and perform cavity modeling; By adjusting the parameters of the built-in cavity, samples with different defect ratios of unfused defects and linear defects can be obtained, a test list can be established, and cavity modeling can be performed. The cavity shape can be adjusted at will, and by controlling the aspect ratio of the cavity, samples with different defect ratios and sizes of unfused defects and linear defects can be obtained. In a specific embodiment, taking the prefabrication of linear defects as an example, the cavity cross-section is rectangular, and the dimensions are shown in Table 1. The selected forming layer thickness is 30 μm, and metallographic sample modeling can be performed according to Table 1. Table 1. Dimensions of the planned linear cavity in the preliminary experiments.

[0022] In some preferred embodiments, step S2 includes: S21. Determine whether the cavity array arrangement direction is horizontal or vertical based on the observation direction of the cavity cross section. The top surface of the horizontal metallographic sample is a polished surface, and the side surface of the vertical metallographic sample is a polished surface. Specifically, the Z-axis height of the cavity should be a multiple of the layer thickness. The array has two orientations: a horizontal orientation for later metallographic sample preparation to observe the cavity cross-section in the XY plane, and a vertical orientation for later metallographic sample preparation to observe the cavity cross-section in the XZ plane. To reduce sampling costs, the metallographic blocks are designed to be flat for rapid separation, improving experimental efficiency. (Reference) Figure 1 and Figure 2 The top surface of the horizontal metallographic sample is polished, and the side surface of the vertical metallographic sample is polished. It should be noted that the placement direction of the cavity does not change with the horizontal or vertical sample, only the array method is changed. S22. Adjust the distance difference between each row or column and the polished surface, taking into account observation efficiency and observation effect; Understandably, in order to observe more defect cross-sections caused by linear cavities, the distance difference between each row / column and the polished surface is adjusted appropriately during arraying. If the distance difference is too large, more defect cross-sections cannot be observed, and if the distance difference is too small, a larger metallographic sample is required, thus reducing efficiency. S23. Selective laser melting forming; its heat source is a laser beam or an electron beam; In some preferred embodiments, step S23 includes: The raw materials for selective laser melting forming are aluminum or aluminum alloy powder, titanium or titanium alloy powder, copper or copper alloy powder, nickel or nickel alloy powder, or iron or iron alloy powder, with a particle size of 5μm to 180μm.

[0023] In some preferred embodiments, step S23 includes: Selective laser melting forming is performed under argon or nitrogen atmosphere protection or in a vacuum.

[0024] In some preferred embodiments, step S3 includes: After separating the metallographic samples, metallographic sample preparation was performed, and optical microscopy was used to take photographs. The defect size corresponding to each cavity in the photographs was analyzed, and the sample with the largest defect size in each row was selected as the porosity analysis object. Its porosity and size were correlated with the cavity size placed in the corresponding row. The defect sizes were classified, and the porosity was recorded to obtain a statistical table of defect and porosity data for the material. The defect size and porosity analysis methods included metallographic sample preparation and CT. It is understandable that a single test is not limited to one cavity size; multiple sizes of linear cavities can be tested as needed, or multiple cavities of different sizes can be tested simultaneously in a single metallographic study. In a specific embodiment, after obtaining the statistical table of defects and porosity data for the material, refer to... Figure 3 This is an example of the smallest unit in the table, containing metallographic images, dimensions, and porosity. Based on this, select the cavity size table for the performance to be tested, and confirm the required testing items, such as density, metallography, tensile strength, fatigue, fracture toughness, crack propagation, thermal conductivity, electrical conductivity, specific heat capacity, etc. Select according to actual needs to ensure cost control.

[0025] In some preferred embodiments, step S4 includes: Defects can be pre-formed throughout the blank or in the working section of the specimen; specifically, the blank can be machined into a standard specimen for testing. Specific machining drawings can be found in the standards for each test. In one specific embodiment, taking room temperature tensile testing as an example, the machining drawing is as follows: Figure 4 As shown, based on the sample size required for this test, a corresponding defect placement method was designed, and the following results were obtained: Figure 5 The model diagram shown; Step S5 includes: performing performance tests on the sample according to the standard and corresponding the test results with its defect size, porosity and metallographic photographs, and statistically analyzing all the data to form a defect ratio and performance correspondence spectrum for the material; In one specific embodiment, the data results are shown in Table 2, for reference. Figure 6 For different porosities Comparison chart of performance between hollow and dense specimens (see reference) Figure 7 For different porosities A comparison chart of the performance of hollow and dense specimens, based on... Figure 6 It can be observed that when the width of the linear defect is approximately 20-50 μm, there is no significant effect on the tensile and yield strengths, while the elongation decreases from 6.5% to approximately 5.5%. This indicates that when the porosity is controlled below 0.18%, smaller linear defects have little impact on the static mechanical tensile properties of the material. According to... Figure 7It can be observed that when the width of linear defects is approximately 80-120 μm, a 0.3% increase in porosity leads to a decrease in tensile strength of about 15 MPa, but the yield strength is not significantly affected. Elongation is significantly affected; linear defects with 0.3% porosity can reduce elongation from 6.5% to about 4%. Thereafter, for every 0.3% increase in porosity, elongation continues to decrease by about 0.5%. The above tests were performed on linear cavities of various sizes and numbers, ultimately yielding a graph comparing the proportion of linear defects with room-temperature tensile properties in additively manufactured AlSi7Mg materials. Table 2 Comparison of Defect Quantity, Porosity, and Room Temperature Tensile Properties of Samples in One Example

[0026] In some preferred embodiments, step S6 includes: S61. Preliminary assessment of room temperature tensile properties was made by comparing the metallographic images taken during the furnace with those in the spectral catalog. S62. Based on the preliminary assessment of room temperature tensile properties and index requirements, comprehensively determine whether the parts are qualified; In one specific embodiment, reference is made to Figure 8 and Figure 9 Metallographic images with different porosities are provided. When compiling the atlas, representative metallographic images and porosities can be included. In actual production, the approximate room temperature tensile properties can be determined by comparing the metallographic images in the furnace with those in the atlas. For example, if 6-8 linear defects with a width of less than 50 μm are found in the metallographic image and the overall porosity is less than 0.18%, and if the only requirements for room temperature tensile properties are tensile strength ≥320 MPa, yield strength ≥240 MPa, and elongation ≥4.0%, then the room temperature tensile properties can be estimated based on the metallographic results. If the metallographic image meets the above requirements, the furnace part is qualified. However, if linear defects with a width of more than 80 μm are found and the porosity is greater than 0.3%, then the elongation is likely to be less than 4.0% based on the above relationship atlas, and the furnace part is unqualified. This method can greatly simplify the inspection process of mass-produced parts, and can also provide strong data support for non-mass-produced parts of the same material. For example, when forming an AlSi7Mg part, furnace tensile and metallographic samples were printed at the same time. The test showed that the tensile properties met the requirements, but five linear defects with a size of less than 40μm were found in the metallography. However, the specifications require that there should be no lack of fusion and linear defects in the metallography. At this time, the part can only be judged as unqualified and scrapped. However, based on the spectrum data, it can be considered that the defects of this level will not affect the room temperature tensile properties. Moreover, the furnace tensile data is consistent with the spectrum. After consultation, it can be considered that the part meets the usage requirements, reducing the economic losses caused by scrapping the part.

[0027] In summary, this method can rapidly obtain metallographic images of defects caused by various cavity cross-sectional shapes and sizes, greatly reducing the cost of defect control. By systematically summarizing the relationship between defects and performance, a defect-performance relationship map is obtained, and based on this, two methods are proposed to reduce costs for actual production testing. This method not only produces defects with strong dimensional consistency and good reproducibility through the built-in cavity method, but also allows for rapid inference of material properties from metallographic results by conducting performance tests on samples with different defect proportions in the early stage. Furthermore, the metallographic index requirements can be derived by combining this comparison relationship with performance requirements, eliminating the need for frequent testing of furnace-fed sample performance and saving costs. When furnace-fed metallographic test results contradict furnace-fed performance sample test results, the above comparison relationship can be used as a reference for judgment, reducing repeated tests. This method goes beyond simply pre-introducing defects in samples. It further predicts material properties through performance testing of samples with different defect sizes. By using a defect-performance correlation graph, it more precisely defines the allowable range of part defects, improves the efficiency of inspection and testing processes, and reduces the inspection cost of batch-produced parts. In actual production, it can test the allowable standards for part defects, classify defect levels, and enable some minor defects to pass acceptance requirements, thereby increasing the part pass rate and reducing production costs.

[0028] On the other hand, a preferred embodiment of the present invention also provides a metal additive manufacturing method, which applies the above-mentioned method for characterizing the relationship between material defects and performance.

[0029] In the description of this invention, it should be noted that the terms "upper", "lower", "front", "rear", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention.

[0030] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0031] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for characterizing the relationship between material defects and performance, characterized in that, The method comprises the following steps: S1. Perform cavity size model setting; S2. Arrange cavities of each size in a preset array manner in a test block, and form a sample by selective laser melting; S3. Separate the metallographic sample and perform metallographic sample preparation; S4. Prepare a pre-prepared defect sample according to the selected item; S5. Perform performance testing on the sample according to the standard, and correspond the test results with the defect size, porosity and metallographic photo of the sample, after statistical analysis of all data, based on the obtained metallographic photos of defects generated by various cavity cross-sectional shapes and sizes, systematically summarize the relationship between defects and performance, and obtain a defect and performance relationship corresponding atlas of the sample material to determine the allowable range of part defects; S6. Use the atlas to perform performance prediction and qualification, preliminarily judge the room temperature tensile performance by comparing the in-furnace metallographic photo with the metallographic photo in the atlas; comprehensively judge whether the part is qualified according to the preliminary judgment of the room temperature tensile performance and the index requirement; when the in-furnace metallographic detection result and the in-furnace performance sample test result are contradictory, use the contrast relationship as a reference for judgment.

2. The method for characterizing material defect-performance relationships of claim 1, wherein, Step S1 comprises: S11. According to the experimental requirements, match and set the size of the cavity cross section, and by adjusting the size parameters of the built-in cavity, obtain the unmelted defect and linear defect sample with different defect proportions in the sample preparation step; S12. Prepare a test list and build a cavity model.

3. The method for characterizing material defect-performance relationships of claim 1, wherein, Step S2 comprises: S21. According to the observation direction of the cavity cross section, determine the cavity array arrangement direction as horizontal or vertical, the top surface of the horizontal metallographic sample is the polishing surface, and the side surface of the vertical metallographic sample is the polishing surface; S22. Adjust the distance difference between each row or each column and the polishing surface considering the observation efficiency and observation effect; S23. Form a sample by selective laser melting.

4. The method for characterizing material defect-performance relationships of claim 1, wherein, Step S2 comprises: The raw material for selective laser melting is aluminum or aluminum alloy powder, titanium or titanium alloy powder, copper or copper alloy powder, nickel or nickel alloy powder, iron or iron alloy powder, and the particle size of the raw material is 5-180 μm.

5. The method for characterizing material defect-performance relationships of claim 1, wherein, Step S2 comprises: The selective laser melting is performed under the protection of argon or nitrogen atmosphere or in vacuum.

6. The method for characterizing material defect-performance relationships of claim 1, wherein, Step S3 comprises: After separating the metallographic sample, perform metallographic sample preparation, and use an optical microscope to take a light microscope photo, analyze the defect size corresponding to each cavity in the photo, and select the sample with the largest defect size in each row as the object for porosity analysis, and correspond the porosity, size and cavity size of the corresponding row; classify the defect size, record the porosity, and obtain a defect and porosity data statistical table of the material.

7. The method for characterizing material defect-performance relationships of claim 1, wherein, Step S4 comprises: Pre-prepare defects in the entire blank or pre-prepare defects in the working section of the sample.

8. The method for characterizing material defect-performance relationships of claim 1, wherein, In step S5, the performance test includes density, metallography, tensile, fatigue, fracture toughness, crack propagation, thermal conductivity, electrical conductivity and specific heat capacity.

9. A method of metal additive manufacturing, characterized by, The application has the right to use the method for characterizing the relationship between material defects and performance according to any one of claims 1-8.

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