Method for constructing powder defect distribution curve for probabilistic damage tolerance evaluation

Abstract

The invention relates to a method for constructing a powder defect distribution curve for probabilistic damage tolerance evaluation. The method comprises the following steps: carrying out a fatigue test on a test bar with an examination section; performing fracture analysis on the fractured examination section to at least obtain the defect size, the defect type and the defect number of all defects; fitting the obtained defect size according to extreme value distribution to form a defect size distribution curve; calculating a defect occurrence rate according to the number of defects and the volume of the examination section; and combining the defect size distribution curve and the defect occurrence rate to obtain the powder defect distribution curve.

Description

Technical Field

[0001] This disclosure relates to the field of aero-engines, and in particular to the risk assessment of powder defect damage tolerance in life-limiting components of aero-engine rotors. Background Technology

[0002] Airworthiness regulations FAR33.70 / CCAR33.70 / CS-E 515, specifically the engine life-limited parts clause, stipulate that appropriate damage tolerance assessments must be performed to determine potential failures due to defects in materials, manufacturing, and use within the approved lifespan of the part. Powder metallurgy superalloys possess excellent high-temperature mechanical properties and avoid problems such as segregation that occur during the casting / forging process of traditional superalloys, thus making them a preferred material for turbine disks. However, the manufacturing process of powder metallurgy superalloys inevitably introduces defects such as non-metallic inclusions and porosity. These defects are prone to becoming fatigue crack initiation points under cyclic loading, causing the actual fatigue life of the part to be lower than the life calculation results under the defect-free assumption, thereby significantly increasing the risk of accidental turbine disk fracture.

[0003] Therefore, Advisory Circular AC33.70-4 requires consideration of the potential failure of powder metallurgy superalloy rotating parts due to material defects. When determining the life of a powder disk, both conventional low-cycle fatigue life calculation and probabilistic damage tolerance assessment must be performed simultaneously, and the lower result should be taken as the allowable life. When assessing the probabilistic damage tolerance of a powder disk, the powder defect distribution curve, which represents the defect size distribution and defect incidence rate, is an essential input. However, currently, no reference defect distribution curves exist.

[0004] This disclosure addresses, but is not limited to, the many factors mentioned above. Summary of the Invention

[0005] To this end, this disclosure provides a method for constructing powder defect distribution curves for probabilistic damage tolerance assessment of aero-engines. The method of this disclosure designs a large test bar fatigue test, and obtains comprehensive defect data such as the true size, type, shape, inclusion composition, and distance of the defect from the surface by measuring the defects at the fatigue fracture surface. A defect distribution curve is then established to fill the gaps in key input items for probabilistic damage tolerance, supporting engine airworthiness certification.

[0006] This disclosed method breaks through the traditional approach to obtaining defect data, proposing a novel method based on fatigue test fracture surface analysis to acquire defect data. The test section designed in this method has a sufficiently large volume to reduce the influence of surface processing on fatigue crack initiation, maximizing stress concentration at the largest defect, with the fracture section of the specimen passing through this defect. The fracture surface analysis of this disclosed method can obtain the true size of the largest defect within the measured volume, and can also distinguish information such as defect type, defect shape, inclusion composition, defect distance from the surface, and defect occurrence rate. This disclosed method samples from the disc forging state, eliminating subsequent preparation processes that could alter the defect size. This disclosed method can establish the powder defect distribution curve without first determining the ultrasonic testing POD curve. Furthermore, in this disclosed technical solution, sample preparation is relatively easy, and the testing environment has very low safety risks.

[0007] According to a first aspect of this disclosure, a method is provided for constructing a powder defect distribution curve for probabilistic damage tolerance assessment, the method comprising: performing a fatigue test on a test bar having a test section; performing fracture surface analysis on the test section where fracture has occurred to obtain at least the defect size, defect type, and defect number of all defects; fitting the obtained defect sizes to an extreme value distribution to form a defect size distribution curve; calculating a defect incidence rate based on the defect number and the volume of the test section; and combining the defect size distribution curve and the defect incidence rate to obtain the powder defect distribution curve.

[0008] According to one embodiment, the test section of the test bar is made of the same powder high-temperature alloy as the actual part, and the volume of the test section is designed to be sufficient to ignore the influence of the test bar surface processing on fatigue crack initiation.

[0009] According to another embodiment, the fatigue test is conducted under different combinations of stress and temperature.

[0010] According to yet another embodiment, the extreme value distribution is a Gumbel distribution or a Weibull distribution.

[0011] According to yet another embodiment, the defect incidence rate α is calculated using the following formula:

[0012]

[0013] Where α represents the defect incidence rate per million kilograms, N represents the number of defects, ρ×V represents the total mass of the test segment in kilograms, and where ρ represents the density of the test segment and V represents the volume of the test segment.

[0014] According to yet another embodiment, the number of defects is the number of defects whose size exceeds the minimum defect size.

[0015] According to yet another embodiment, the minimum defect size depends on the type of defect.

[0016] According to another embodiment, the method further includes excluding a predetermined number or predetermined proportion of defects from all the defects obtained, wherein the largest size of the excluded defects is smaller than the smallest size of the remaining unexcluded defects, whereby the largest size of the excluded defects is the smallest defect size, and the number of remaining unexcluded defects is the number of defects.

[0017] According to another embodiment, the defect size distribution curve is in a coordinate system in which the horizontal axis represents the defect size and the vertical axis represents the cumulative probability of defect occurrence.

[0018] According to another embodiment, combining the defect size distribution curve and the defect occurrence rate to obtain the powder defect distribution curve includes: translating the defect size distribution curve so that the intersection of the defect size distribution curve and the vertical axis of the coordinate system is at point (0,1); and multiplying the translated defect size distribution curve by the defect occurrence rate to obtain the powder defect distribution curve.

[0019] According to yet another embodiment, the method further includes using the powder defect distribution curve to perform probabilistic damage tolerance assessment.

[0020] According to yet another embodiment, the probabilistic damage tolerance assessment also uses stress distribution, material data, POD curves, and inspection intervals.

[0021] According to another embodiment, the method further includes constructing powder defect distribution curves for defects belonging to the same defect type and constructing powder defect distribution curves for defects of all defect types, wherein the defect types include at least pores and non-metallic inclusions.

[0022] The aspects generally include, as substantially as described herein with reference to the accompanying drawings and as explained by the drawings, methods, apparatus, systems, computer program products, and processing systems.

[0023] The foregoing has broadly outlined the features and technical advantages of the examples according to this disclosure so that the following detailed description may be better understood. Additional features and advantages will be described thereafter. The disclosed concepts and specific examples can be readily used as the basis for modifying or designing other structures for implementing the same purposes as this disclosure. Such equivalent constructions do not depart from the scope of the appended claims. The characteristics of the concepts disclosed herein, in both their organization and manner of operation, and their associated advantages, will be better understood by considering the following description in conjunction with the accompanying drawings. Each drawing is provided for illustrative and descriptive purposes and does not define any limitation on the claims. Attached Figure Description

[0024] To gain a more detailed understanding of the features described above in this disclosure, reference can be made to various aspects of the above-briefly summarized content, some of which are illustrated in the accompanying drawings. However, it should be noted that the drawings illustrate only certain typical aspects of this disclosure and should not be considered as limiting its scope, as other equivalent aspects are permissible in this description. Identical reference numerals in different drawings may identify the same or similar elements.

[0025] Figure 1 A flowchart is shown of a method for constructing a powder defect distribution curve for probabilistic damage tolerance assessment according to an example embodiment of the present disclosure;

[0026] Figure 2 A schematic diagram of a test bar according to an example embodiment of the present disclosure is shown;

[0027] Figure 3 A schematic diagram illustrating the measurement of defect size according to an example embodiment of the present disclosure is shown;

[0028] Figure 4 A schematic diagram is shown of a defect size distribution curve obtained by fitting a Weibull distribution according to an example embodiment of the present disclosure;

[0029] Figure 5 A schematic diagram of a powder defect distribution curve according to an example embodiment of the present disclosure is shown;

[0030] Figure 6 A schematic diagram of the defect distribution of a test specimen according to an example embodiment of the present disclosure is shown; and

[0031] Figure 7 Example defect data obtained by fracture analysis according to an exemplary embodiment of the present disclosure is shown. Detailed Implementation

[0032] Terminology Explanation:

[0033] Rotor life-limiting components: Rotor parts whose primary failure may lead to jeopardy of engine life;

[0034] Probabilistic damage tolerance: An element in the life management process used to identify potential defects caused by materials, processing, or use, and to assess the potential for such defects to reduce the structural integrity of parts through fracture mechanics, process control, and non-destructive testing, as a complement to existing safe life methods.

[0035] Powder defects: Defects in powder alloys, such as inclusions and porosity, caused by manufacturing processes.

[0036] Defect distribution curve: The statistical defect information is expressed as the defect size distribution and defect occurrence frequency. The defect distribution curve is a key input for probabilistic damage tolerance assessment.

[0037] The inventors recognized that powder defect distribution curves, which represent defect size distribution and defect incidence, are essential inputs for probabilistic damage tolerance assessment of powder discs. However, currently, no reference defect distribution curves exist. For example, Advisory Circular AC33.70-4 does not provide any reference defect distribution curves. Furthermore, there is currently no defect database for qualified disc forgings, nor are there any powder defect distribution curves representative of qualified parts, severely hindering the airworthiness certification of aero engines.

[0038] The inventors also recognized that existing methods for establishing defect distribution curves, including heavy liquid separation, cross-sectional methods, and ultrasonic testing, are used to accumulate defect data. Heavy liquid separation uses a liquid with a density less than the matrix metal powder but greater than the inclusions to separate the inclusions from the metal powder. While this method can obtain a large amount of data and the size and shape of defects are easy to measure, the size of pores generated during forging cannot be detected, and inclusion defects may change in size due to crushing. Furthermore, the liquid used for heavy liquid separation is highly toxic, making this method difficult to apply. The cross-sectional method involves cutting cross-sections from different locations on the forging to prepare metallographic test samples, using an optical microscope to observe and measure the defect size on the cross-section. However, because the defect incidence rate of qualified disc forgings is low, obtaining sufficient defect data requires an extremely large number of cross-sectional tests. The preparation process for cross-sectional metallographic samples is difficult and cumbersome, and it is difficult to guarantee that the test cross-section passes through the maximum size of the defect, potentially resulting in an underestimation of the defect size. Ultrasonic testing can statistically analyze the non-destructive testing (NDT) defect dimensions in the initial ingot and combine this with the NDT detection probability to obtain a defect distribution curve. Then, by simulating the processing from the ingot to the billet, the defect dimensions in the billet are obtained, and the defect distribution curve is corrected using the NDT detection probability. However, the echo signal recorded by ultrasonic testing, when converted into equivalent defect size, may deviate from the actual defect size due to factors such as defect shape and detection direction. Furthermore, it cannot distinguish between defect types (inclusions / porosity), failing to meet the requirement of separately assessing the probabilistic damage tolerance of inclusion defects and porosity defects in the powder disk.

[0039] To this end, this disclosure proposes a method for constructing powder defect distribution curves for probabilistic damage tolerance assessment of aero-engines. The method of this disclosure designs a large test bar fatigue test, and obtains comprehensive defect data such as the true size, type, shape, inclusion composition, and distance of the defect from the surface by measuring the defects on the fatigue fracture surface. A defect distribution curve is then established to fill the gaps in key input items for probabilistic damage tolerance, supporting engine airworthiness certification.

[0040] This disclosed method breaks through the traditional approach to obtaining defect data, proposing a novel method based on fatigue test fracture surface analysis to acquire defect data. The test section designed in this method has a sufficiently large volume to reduce the influence of surface processing on fatigue crack initiation, maximizing stress concentration at the largest defect, with the fracture section of the specimen passing through this defect. The fracture surface analysis of this disclosed method can obtain the true size of the largest defect within the measured volume, and can also distinguish information such as defect type, defect shape, inclusion composition, defect distance from the surface, and defect occurrence rate. This disclosed method samples from the disc forging state, eliminating subsequent preparation processes that could alter the defect size. This disclosed method can establish the powder defect distribution curve without first determining the ultrasonic testing POD curve. Furthermore, in this disclosed technical solution, sample preparation is relatively easy, and the testing environment has very low safety risks.

[0041] The detailed description that follows, taken in conjunction with the accompanying drawings, is intended as a description of various configurations and is not intended to represent the only configurations in which the concepts described herein can be practiced. This detailed description includes specific details to provide a thorough understanding of the various concepts. However, it will be apparent to those skilled in the art that these concepts can be practiced without these specific details.

[0042] The following is for reference. Figure 1 The document illustrates a flowchart of a method 100 for constructing a powder defect distribution curve for probabilistic damage tolerance assessment according to an exemplary embodiment of the present disclosure. Method 100 departs from traditional methods of accumulating defect data by designing large test specimens for fatigue testing, analyzing measured defect data from the fracture surface, and constructing a powder defect distribution curve based on this analysis.

[0043] As shown in the figure, method 100 may include box 110, which performs fatigue tests on a test bar with a test section.

[0044] In one embodiment of this disclosure, the test section of the test bar is made of the same powder metallurgy superalloy as the actual part, and the volume of the test section is designed to be sufficient to negate the influence of the test bar's surface finish on fatigue crack initiation, so that the test section fails (e.g., fractures) at internal defects (e.g., non-metallic inclusions, porosity, etc.) during fatigue testing. Therefore, the volume of the test section is designed to be large enough to negate the influence of the test bar's surface finish on fatigue crack initiation, resulting in maximum stress concentration at the largest defect. Of course, the size of the test section is also limited by the clamping and loading capacity of the fatigue testing machine. (Reference) Figure 2The diagram illustrates a test bar according to an exemplary embodiment of the present disclosure. Those skilled in the art will understand that the central cylinder is the aforementioned test section. It will be understood that, within the constraints of the clamping and loading capacity of the fatigue testing machine, making the test section as large as possible will, under a given defect density, make it easier for the test bar to fail from internal defects, thereby increasing the probability of accumulating defect data, i.e., making it more likely to obtain defect data from fatigue testing.

[0045] In another embodiment of this disclosure, the fatigue test is conducted under different combinations of stress and temperature. Of course, the fatigue test may also include any other suitable constraints, which will not be elaborated upon here.

[0046] Next, in block 120, method 100 may include fracture surface analysis of the fractured test segment to obtain at least the defect size, defect type, and number of all defects. In one embodiment of this disclosure, the defect type may include at least porosity and non-metallic inclusions. It will be understood that multiple test bars may be prepared and fatigue tests performed in this disclosure to obtain sufficient data. Figure 3 As shown, it illustrates a schematic diagram of defect size measurement. Figure 3 As shown, the exemplary defect is depicted as generally elliptical, and the defect size can be measured by measuring its minor axis and major axis (i.e., Figure 3 This is accomplished by drawing two perpendicular straight line segments at the defect location. In one embodiment of this disclosure, the defect size is represented by the area of ​​the defect. Therefore, in Figure 3 In the example shown, after measuring the minor and major axes, the defect size of the elliptical defect can be obtained using the ellipse area formula. It will be understood that any suitable method can be used to measure the defect size, such as the mesh-filling method for measuring area (i.e., covering the defect with a mesh of appropriate size and estimating the defect area by the number of meshes intersecting with the defect), etc., which will not be elaborated upon here.

[0047] Continue to refer to Figure 1 In box 130, method 100 may include fitting the acquired defect size to an extreme value distribution to form a defect size distribution curve. In one embodiment of this disclosure, the extreme value distribution may be a Gumbel distribution or a Weibull distribution.

[0048] refer to Figure 4 This illustrates a schematic diagram of a defect size distribution curve obtained by fitting a Weibull distribution according to an example embodiment of the present disclosure. Figure 4 In the example curves shown, the horizontal axis of the coordinate system represents the defect size, and the vertical axis represents the cumulative probability of defect occurrence. It will become clear that... Figure 4 The curves shown only represent the defect size distribution and do not consider the defect incidence rate. Although Figure 4 The defect dimensions are in square millimeters, but any other suitable unit may be used, which will not be elaborated here.

[0049] Refer back Figure 1 In box 140, method 100 may include calculating the defect rate based on the number of defects and the volume of the test segment.

[0050] In one embodiment of this disclosure, the defect incidence rate α is calculated using the following formula:

[0051]

[0052] Where α represents the defect incidence rate per million kilograms, N represents the number of defects, ρ×V represents the total mass of the test segment in kilograms, and where ρ represents the density of the test segment and V represents the volume of the test segment.

[0053] In a preferred embodiment of this disclosure, the number of defects is the number of defects whose size exceeds the minimum defect size. In this embodiment, the minimum defect size depends on the type of defect. For example, for porosity defects, the minimum defect size may be a first value; for non-metallic inclusion defects, the minimum defect size may be a second value different from the first value. Alternatively, the minimum defect size may be any suitable fixed value applicable to all defect types.

[0054] In another embodiment of this disclosure, the minimum defect size may be the defect size of the defect in a predetermined order of size among all defects. Thus, method 100 may include excluding a predetermined number or percentage of defects from all acquired defects, wherein the largest size among the excluded defects is smaller than the smallest size among the remaining unexcluded defects, whereby the largest size among the excluded defects is the minimum defect size, and the number of remaining unexcluded defects is the number of defects. For example, if in block 120, method 100 acquires 10,000 defects, and the predetermined number is set to 100, then the size of the 101st defect among these 10,000 defects sorted by size from smallest to largest can be used as the minimum defect size; or, a predetermined percentage of defects may be excluded, for example, the predetermined percentage may be set to 5%, then the 500 smallest defects may be excluded from the acquired 10,000 defects, and the size of the 501st defect can be used as the minimum defect size.

[0055] In a preferred embodiment of this disclosure, the minimum defect size can be determined by fracture surface analysis. In this embodiment, firstly, fracture surface analysis identifies first sizes of defects corresponding to the source regions of crack initiation in the fracture surface, and second sizes of defects not associated with the source regions of crack initiation in the fracture surface. Subsequently, the minimum defect size can be set to any suitable value between the smallest of the first sizes and the largest of the second sizes.

[0056] It will be understood that although method 100 describes that the operation of box 140 is completed after the operation of box 130, the operations of boxes 130 and 140 can be performed in reverse order or simultaneously, as long as they are performed after the defect size and number of defects are acquired in box 120.

[0057] Finally, in box 150, method 100 may include combining a defect size distribution curve and a defect occurrence rate to obtain a powder defect distribution curve.

[0058] In one embodiment of this disclosure, combined with Figure 4 Combining the defect size distribution curve and the defect occurrence rate to obtain the powder defect distribution curve may include: translating the defect size distribution curve so that the intersection of the defect size distribution curve and the vertical axis of the coordinate system is at point (0,1); and multiplying the translated defect size distribution curve by the defect occurrence rate to obtain the hole surface defect distribution curve. For example... Figure 4 As shown, the horizontal axis of the coordinate system represents the defect size, and the vertical axis represents the cumulative probability of defect occurrence. The curve translation described above is equivalent to a normalization operation, which can then be combined with the defect occurrence rate to obtain the desired powder defect distribution curve.

[0059] refer to Figure 5 This illustrates a schematic diagram of a powder defect distribution curve according to an example embodiment of the present disclosure. As can be seen, Figure 5 The vertical axis of the example curve shown represents the number of defects per million kilograms, and the horizontal axis represents the defect size (in this example, in square millimeters). It will be understood that the units for area and length can be any suitable units, which will not be elaborated upon here.

[0060] In yet another embodiment of this disclosure, method 100 may optionally include using a powder defect distribution curve to perform a probabilistic damage tolerance assessment. It will be understood that the probabilistic damage tolerance assessment also utilizes the stress distribution of the part, material data, POD curves, inspection intervals, etc., which will not be elaborated upon here.

[0061] In yet another embodiment of this disclosure, as a supplement, method 100 may also measure defect shape, inclusion composition, and distance of defect from surface, etc., at block 120.

[0062] In a preferred embodiment of this disclosure, when field service data becomes available in the future, method 100 may update the obtained powder defect distribution curve. For example, method 100 may include obtaining actual defect data (such as defect size, defect type, defect number, etc.) from the field service data when it is available. Thus, method 100 may obtain an updated powder defect distribution curve based on the field service data.

[0063] In another embodiment of this disclosure, method 100 may further include constructing powder defect distribution curves for defects belonging to the same defect type and constructing powder defect distribution curves for defects of all defect types, wherein the defect types include at least pores and non-metallic inclusions.

[0064] The following specific example further illustrates the method of this disclosure, and the constructed powder defect distribution curve is applied to a certain type of powder turbine disk to assess the probabilistic failure risk:

[0065] 1) Design and conduct fatigue tests on a large test bar with a parallel section length and diameter much larger than that of a standard round bar. A schematic diagram of the test bar can be shown below. Figure 3 As shown.

[0066] 2) Fracture surface analysis was performed on the fatigue fracture test specimens to obtain defect distribution maps and related defect information, as shown in the diagrams. Figure 6 and Figure 7 To facilitate observation, defects in the defect distribution diagram are magnified to a certain extent. Figure 6 A schematic diagram of the defect distribution of the test piece is shown, in which the dots in the diagram are schematic representations of the defects, and the size of the dots correspondingly represents the size of the defects. Figure 7 Example defect data obtained through fracture analysis is shown, including, for example, distance from the surface, area (i.e. defect size), defect type, defect composition, defect shape, location, etc.

[0067] 3) Fit the defect size to a Weibull distribution to form a defect size distribution curve, for example... Figure 5 As shown.

[0068] 4) Calculate the defect incidence rate based on the measured number of defects and the volume being assessed. Then, combine this with the defect size distribution curve from step 3) to obtain the powder defect distribution curve, for example, as shown in Figure 1. Figure 4 As shown.

[0069] 5) After obtaining the defect distribution curve, a probabilistic damage tolerance assessment of the powder turbine disk can be performed. Taking a certain type of powder turbine disk as an example, the defect distribution curve, stress distribution, material data, POD curve, and inspection interval are input into the probabilistic damage tolerance risk assessment system, and the component life is determined based on the specified failure risk. For example, the powder defect distribution curve may include a distribution curve for porosity defects and a distribution curve for non-metallic inclusion defects. Therefore, the probabilistic damage tolerance assessment of the powder turbine disk can evaluate the component life based on these two distribution curves separately. In this example, the smaller of the two evaluated lifespans is selected as the component life.

[0070] This invention proposes a large-scale fatigue test to obtain comprehensive defect data, including defect size, type, shape, inclusion composition, and distance from the surface, by measuring the defects through fatigue fracture surfaces. This data is used to establish a defect distribution curve, fill the gap in the critical input of powder disk probabilistic damage tolerance, and support the airworthiness certification of aero-engines.

[0071] It will be understood that the methods disclosed herein can be applied to fields other than aero-engines for evaluating the lifespan of powder metallurgy superalloy parts.

[0072] In this disclosure, the terms "engine" and "aircraft engine" are used interchangeably.

[0073] The above detailed description includes references to the accompanying drawings, which form part of the detailed description. The drawings illustrate specific embodiments that can be practiced by way of illustration. These embodiments are also referred to herein as “examples.” Such examples may include elements other than those shown or described. However, examples including the shown or described elements are also contemplated. Furthermore, examples of any combination or arrangement of those elements shown or described are contemplated, or with reference to specific examples (or one or more aspects thereof) shown or described herein, or with reference to other examples (or one or more aspects thereof) shown or described herein.

[0074] In the appended claims, the terms “comprising” and “including” are open-ended, meaning that a system, apparatus, article of manufacture, or process containing elements other than those listed after such terms in a claim is still considered to fall within the scope of that claim. Furthermore, in the appended claims, the terms “first,” “second,” and “third,” etc., are used merely as designations and are not intended to indicate a numerical order of their contents.

[0075] Furthermore, the order of operations described in this specification is exemplary. In alternative embodiments, the operations may be performed in a different order than that shown in the accompanying drawings, and the operations may be combined into a single operation or broken down into more operations.

[0076] The above description is intended to be illustrative and not restrictive. For example, the examples described above (or one or more aspects thereof) may be used in conjunction with other embodiments. Other embodiments may be used by those skilled in the art after reviewing the above description. The abstract allows the reader to quickly determine the nature of this technical disclosure. This abstract is submitted and it is understood that it is not intended to interpret or limit the scope or meaning of the claims. Furthermore, in the above detailed description, various features may be grouped together to make this disclosure flow smoothly. However, the claims may not state every feature disclosed herein, as embodiments may characterize a subset of said features. Furthermore, embodiments may include fewer features than those disclosed in a particular example. Therefore, the appended claims are thus incorporated into the detailed description, with each claim existing independently as a separate embodiment. The scope of the embodiments disclosed herein should be determined by reference to the full scope of the appended claims and equivalents of such claims.

Claims

1. A method for constructing a powder defect distribution curve for probabilistic damage tolerance assessment, the method comprising: Fatigue tests were conducted on test bars with test sections. Perform fracture analysis on the test section where fracture occurred to obtain at least the defect size, defect type, and number of all defects. The obtained defect sizes are fitted according to the extreme value distribution to form a defect size distribution curve; The defect incidence rate is calculated based on the number of defects and the volume of the test section; and The powder defect distribution curve is obtained by combining the defect size distribution curve and the defect occurrence rate.

2. The method according to claim 1, characterized in that, The test section of the test bar is made of the same powder high-temperature alloy as the actual part, and the volume of the test section is designed to be sufficient to ignore the influence of the test bar surface processing on the initiation of fatigue cracks.

3. The method according to claim 1, characterized in that, The fatigue tests were conducted under different combinations of stress and temperature.

4. The method according to claim 1, characterized in that, The extreme value distribution is either a Gumbel distribution or a Weibull distribution.

5. The method according to claim 1, characterized in that, The defect incidence rate α is calculated using the following formula: Where α represents the defect incidence rate per million kilograms, N represents the number of defects, ρ×V represents the total mass of the test segment in kilograms, and where ρ represents the density of the test segment and V represents the volume of the test segment.

6. The method according to claim 5, characterized in that, The number of defects is the number of defects whose size exceeds the minimum defect size.

7. The method according to claim 6, characterized in that, The minimum defect size depends on the type of defect.

8. The method according to claim 6, characterized in that, It also includes excluding a predetermined number or proportion of defects from all the defects obtained, wherein the largest size of the excluded defects is smaller than the smallest size of the remaining unexcluded defects, whereby the largest size of the excluded defects is the smallest defect size, and the number of remaining unexcluded defects is the number of defects.

9. The method according to claim 1, characterized in that, The defect size distribution curve is in the following coordinate system: the horizontal axis of the coordinate system represents the defect size, and the vertical axis of the coordinate system represents the cumulative probability of defect occurrence.

10. The method according to claim 9, characterized in that, The powder defect distribution curve is obtained by combining the defect size distribution curve and the defect occurrence rate. Translate the defect size distribution curve so that the intersection of the defect size distribution curve and the vertical axis of the coordinate system is at point (0,1); and The powder defect distribution curve is obtained by multiplying the translated defect size distribution curve by the defect occurrence rate.

11. The method according to claim 1, characterized in that, It also includes using the powder defect distribution curve to perform probabilistic damage tolerance assessment.

12. The method according to claim 11, characterized in that, The probabilistic damage tolerance assessment also uses stress distribution, material data, POD curves, and inspection intervals.

13. The method according to claim 1, characterized in that, It also includes constructing powder defect distribution curves for defects belonging to the same defect type and constructing powder defect distribution curves for defects of all defect types, wherein the defect types include at least porosity and non-metallic inclusions.

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