A method and device for quantifying the morphology deviation of a closed curve type defect

Abstract

The present application relates to the technical field of material microstructure characterization, and particularly relates to a method and device for quantifying the morphology deviation of closed curve type defects. The method comprises: performing curve extraction on a target image taken by a transmission electron microscope to obtain closed curve type defects and open curve type defects; for each closed curve type defect, determining a ring topology index of the closed curve type defect based on the open curve type defects and the remaining closed curve type defects; wherein the ring topology index is used to quantify the deviation degree of the actual morphology of the closed curve type defect from the ideal morphology predicted by the elasticity theory. Therefore, the above technical solution can effectively quantify the morphology deviation degree of the closed curve type defects.

Description

Technical Field

[0001] This invention relates to the field of material microstructure characterization technology, and in particular to a method and apparatus for quantifying the morphological deviation of closed curve-type defects. Background Technology

[0002] In irradiation experiments on nuclear materials (nuclear materials are a general term for materials used in the nuclear industry and nuclear science, mainly including nuclear fuel, reactor materials and related control and shielding materials, mainly referring to materials used in nuclear reactors), closed-curve defects (such as dislocation loops, pores, corrosion pits, bubbles, etc.) are usually found to form in the nuclear materials through microstructural characterization. The following uses dislocation loops as an example to explain closed-curve defects.

[0003] Under normal irradiation conditions, the actual morphology of dislocation loops formed in nuclear materials is usually quite close to the predicted morphology (or ideal morphology) calculated by elastic theory, specifically exhibiting smooth boundaries and an overall approximate predicted morphology. However, the inventors discovered during the research and development process that under special irradiation conditions (such as the introduction of hydrogen or high-dose irradiation) or when reactions, connections, and mergers occur between dislocation loops, the actual morphology may deviate significantly from the predicted morphology. That is, the actual morphology may exhibit irregular features such as polygonalization, enhanced boundary undulations, and spikes.

[0004] Most related technologies are limited to statistical characterization of the number, diameter, orientation, or type of dislocation loops (e.g., patents with publication numbers CN117116397A and CN115148384A), and no quantitative method for the morphological deviation of dislocation loops has been established. Therefore, there is an urgent need to provide a quantitative method and apparatus for morphological deviation of closed curve-type defects to solve the above-mentioned technical problems. Summary of the Invention

[0005] This invention provides a method and apparatus for quantifying the morphological deviation of closed curve defects, which can effectively quantify the morphological deviation of closed curve defects.

[0006] In a first aspect, embodiments of the present invention provide a method for quantifying the morphological deviation of closed curve-type defects, including:

[0007] Curve extraction is performed on the target image captured by transmission electron microscopy to obtain closed curve defects and open curve defects;

[0008] For each closed curve type defect, based on open curve type defects and other closed curve type defects, the loop topology index of the closed curve type defect is determined; wherein, the loop topology index is used to quantify the deviation between the actual shape of the closed curve type defect and the ideal shape predicted by elasticity theory.

[0009] The ring topology index includes nesting index, connectivity index, roughness index, and boundary undulation index. The nesting index is used to characterize the hierarchical nesting relationship between closed curve defects. The connectivity index is used to characterize the connection structure relationship within closed curve defects. The roughness index is used to characterize the boundary length variation of closed curve defects. The boundary undulation index is used to characterize the boundary curvature variation of closed curve defects.

[0010] Secondly, embodiments of the present invention also provide a metric device for measuring morphological deviation of closed curve-type defects, comprising:

[0011] The extraction module is used to extract curves from target images captured by a transmission electron microscope to obtain closed curve defects and open curve defects.

[0012] The determination module is used to determine the loop topology index of each closed curve defect based on open curve defects and other closed curve defects; wherein the loop topology index is used to quantify the deviation between the actual shape of the closed curve defect and the ideal shape predicted by elasticity theory.

[0013] The ring topology index includes nesting index, connectivity index, roughness index, and boundary undulation index. The nesting index is used to characterize the hierarchical nesting relationship between closed curve defects. The connectivity index is used to characterize the connection structure relationship within closed curve defects. The roughness index is used to characterize the boundary length variation of closed curve defects. The boundary undulation index is used to characterize the boundary curvature variation of closed curve defects.

[0014] Thirdly, embodiments of the present invention also provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the method of any embodiment of the present invention.

[0015] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the method of any embodiment of the present invention.

[0016] This invention provides a method, apparatus, electronic device, and storage medium for quantifying the morphological deviation of closed-curve defects. First, curves are extracted from the target image captured by a transmission electron microscope to obtain closed-curve and open-curve defects. This data serves as the basis for subsequent morphological deviation calculations. Specifically, for each closed-curve defect, the toroidal topology index is determined based on open-curve defects and other closed-curve defects. This method enables quantitative evaluation and standardized comparison of dislocation toroidal morphology under different materials and irradiation conditions, offering advantages such as strong comparability, high interpretability, and wide applicability. Therefore, the above technical solution can effectively quantify the morphological deviation of closed-curve defects. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the method for quantifying the morphological deviation of closed curve-type defects provided in this embodiment of the invention;

[0019] Figure 2 This is a hardware architecture diagram of the electronic device provided in an embodiment of the present invention;

[0020] Figure 3 This is a structural diagram of the morphological deviation quantification device for closed curve type defects provided in an embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram of the ring topology index provided in an embodiment of the present invention;

[0022] Figure 5 This is a schematic diagram of the analysis results of the morphological deviation of independent dislocation loops in an iron ion-irradiated pure iron sample provided in an embodiment of the present invention.

[0023] Figure 6 This is a schematic diagram of the transmission electron microscope image and its corresponding continuous curve extraction result provided in an embodiment of the present invention;

[0024] Figure 7 This is a schematic diagram illustrating the identification and topological feature extraction of the post-dislocation loop reaction structure provided in an embodiment of the present invention;

[0025] Figure 8 This is a visualization diagram of the calculation of roughness (T3) and boundary undulation (T4) of loop 6-7 provided in an embodiment of the present invention;

[0026] Figure 9 and Figure 10 These are all schematic diagrams illustrating the analysis results of the deviation of dislocation ring morphology after hydrogen irradiation provided in the embodiments of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0028] Please refer to Figure 1 This invention provides a method for quantifying the morphological deviation of closed curve-type defects, including:

[0029] Step 100: Extract curves from the target image captured by the transmission electron microscope to obtain closed curve defects and open curve defects;

[0030] Step 102: For each closed curve type defect, based on the open curve type defects and the remaining closed curve type defects, determine the loop topology index of the closed curve type defect; wherein, the loop topology index is used to quantify the deviation between the actual shape of the closed curve type defect and the ideal shape predicted by elasticity theory.

[0031] In this embodiment, curves are first extracted from the target image captured by a transmission electron microscope to obtain closed-curve defects and open-curve defects. This data serves as the basis for subsequent morphology deviation calculations. Specifically, for each closed-curve defect, the toroidal topology index is determined based on open-curve defects and other closed-curve defects. This method enables quantitative evaluation and standardized comparison of dislocation toroidal morphology under different materials and irradiation conditions, offering advantages such as strong comparability, high interpretability, and wide applicability. Therefore, the above technical solution can effectively quantify the morphology deviation of closed-curve defects.

[0032] In some implementations, the transmission electron microscope is typically TEM, but it may also include STEM, without specific limitations.

[0033] In some implementations, the target image can be saved in common image formats, including but not limited to TIFF, DM3, JPG, etc., without specific limitations.

[0034] In some implementations, curve extraction can be achieved using an image processing platform. The target image to be analyzed can be imported into the platform, and any continuous curve can be obtained from the target image through edge recognition or manual drawing. This continuous curve can be either a closed curve (i.e., a closed curve defect) or an open curve (i.e., an open curve defect). The image processing platform includes, but is not limited to, Adobe Illustrator, Photoshop, ImageJ, or other self-developed image recognition systems. Recognition methods include manual and automatic methods. Manual methods, for example, can use vector editing software (such as the pen tool or path tool in Adobe Illustrator) to draw continuous curves in the image. Automatic methods, for example, can automatically extract continuous curves from the image using edge recognition algorithms, such as the Canny operator, Sobel operator, morphological operations, or deep learning models (such as the U-Net network) for boundary extraction.

[0035] The extracted continuous curves can be exported to standardized data formats, including but not limited to: vector graphics files such as SVG (Scalable Vector Graphics) and AI (Adobe Illustrator) formats; coordinate data, such as the boundary point set {(x1,y1),(x2,y2),...}, stored in CSV, JSON, TXT, etc. In particular, if exporting using coordinate data, it is preferable to interpolate and smooth the boundaries before exporting to ensure curve continuity and shape accuracy. Thus, the continuous curve set {Γh} can be obtained.

[0036] The continuous curve candidate set {Γ} obtained after exporting the target image h Based on}, for each candidate curve Γ h Perform the following processes sequentially:

[0037] Record h The ordered sampling point sequence is

[0038] P1=(x1,y1),P2=(x2,y2),…,P n =(x n ,y n )

[0039] Calculate the Euclidean distance between the first and last points.

[0040] dist=∥P1-P n ∥

[0041] When dist < δ (closing threshold) and the curve has no obvious breaks (which can be determined by detecting the continuity of adjacent segments), Γ is considered to be true. h It is a closed curve; otherwise, it is an open curve.

[0042] In one embodiment of the present invention, closed curve defects include dislocation loops, holes, corrosion pits and bubbles, which are not specifically limited herein.

[0043] like Figure 4 As shown, in one embodiment of the present invention, the ring topology index includes a nesting index, a connectivity index, a roughness index, and a boundary undulation index. The nesting index is used to characterize the hierarchical nesting relationship between closed curve-type defects, the connectivity index is used to characterize the connection structure relationship within closed curve-type defects, the roughness index is used to characterize the boundary length variation of closed curve-type defects, and the boundary undulation index is used to characterize the boundary curvature variation of closed curve-type defects.

[0044] Understandably, the Loop Topology Index (LTI) is a single numerical index that can comprehensively reflect the overall topological deviation of closed-curve defects.

[0045] In one embodiment of the present invention, the nested index is determined in the following manner:

[0046] Select defect C, excluding the closed curve type. i The remaining closed curve type defect set {C j} j≠i As a set of candidate closed curve defects;

[0047] For each candidate closed curve type defect C j Calculate C i and C j The minimum Euclidean distance between them is dist(C) i C j );

[0048] If dist(C i C j If )≤δ1, and δ1 is the first preset value, then determine C. i and C j They are intersecting, but not considered as containing each other;

[0049] Otherwise, perform the following operation: From C j Several first sampling points are uniformly selected on the boundary; for each first sampling point, a direction is drawn towards C. i The center emits a first ray, and the correlation between this first ray and C is statistically analyzed. i The number of intersection points; if the number of intersection points is odd, then the first sampling point is determined to be in C. i If the number of intersection points is even within C, then the first sampling point is determined to be within C. i The outside; when all first sampling points are determined to be in C i When inside, record ;

[0050] Located at C i All C inside j The sum of the quantities is used as the nested index T1.

[0051] In one embodiment of the present invention, the connectivity index is determined as follows:

[0052] Remove open curve defects whose length is less than a preset length, and leave the set of open curve defects {L}. k} as a set of candidate open curve defects;

[0053] Denote the open curve class defect L for each candidate line. k The endpoint is A k and B k Calculate A k and B k to C respectively i The minimum Euclidean distance of the boundary, dist(A) k C i ) and dist(B k C i );

[0054] When dist(A) k C i )≤δ1 and dist(B k C i When )≤δ1, determine A k and B k Both are related to C i If the boundaries intersect, then L is determined to be an integer. k Not C i Internal connecting wires;

[0055] Regarding A k and B k Both are related to C i Each L intersecting the boundary k All of them perform the following operations: from L k Several second sampling points are uniformly selected on the boundary; for each second sampling point, a direction is drawn towards C. i The center emits a second ray, and the statistical analysis shows that this second ray is related to C. i The number of intersection points; if the number of intersection points is odd, then the second sampling point is determined to be in C. i If the number of intersection points is even within C, then the second sampling point is determined to be within C. i The outside; when all second sampling points are determined to be in C i When it is inside, and there is no other than A k and B k The second sampling point outside and C iThe boundaries intersect, denoted as L. k C i Internal connecting wires;

[0056] All C i The sum of the number of internal connecting lines is used as the connectivity index T2.

[0057] In one embodiment of the present invention, the roughness index is determined in the following manner:

[0058] Accumulate C sequentially according to the boundary point sequence. i The Euclidean distance between adjacent points is C. i The total perimeter P of the entire boundary loop ;

[0059] Calculate C using the shoelace rule i The area A of the entire boundary loop ;

[0060] Let A be the area of ​​the ideal closed-curve defect predicted by elasticity theory. loop And obtain the total perimeter P of the entire boundary of the ideal closed curve type defect. ideal ;

[0061] P loop and P ideal The quotient is used as the roughness index T3.

[0062] In one embodiment of the present invention, the boundary undulation index is determined as follows:

[0063] For C i Curvature calculations are performed on the sampling points of the entire boundary to obtain the curvature value κ[i] of the i-th sampling point on the boundary;

[0064] If a sampling point on the boundary satisfies the following condition, then the sampling point is determined to be a point where the curvature changes sign:

[0065] sign(κ[i])≠sign(κ[i+1]);

[0066] max(∣κ[i]∣,∣κ[i+1]∣)>δ2;

[0067] The curvature signs of the first five sampling points of the i-th sampling point are the same, and are consistent with the sign of κ[i].

[0068] The curvature signs of the five sampling points after the (i+1)th sampling point are the same and consistent with the sign of κ[i+1];

[0069] In the formula, sign(κ[i]) is the sign of curvature at the i-th sampling point, sign(κ[i+1]) is the sign of curvature at the (i+1)-th sampling point, max(∣κ[i]∣,∣κ[i+1]∣) is the maximum value of the absolute curvature values ​​of the i-th and (i+1)-th sampling points, δ2 is the second preset value, and the curvature sign is positive or negative;

[0070] Let N be the sum of the number of sampling points that simultaneously meet the above conditions. inflection Then C i The boundary undulation index T4 is determined by the following formula:

[0071]

[0072] The ring topology index LTI is determined by the following formula:

[0073] .

[0074] Understandably, the results of the Loop Topology Index (LTI) calculation can be automatically generated by a computer program and output in numerical or graphical form. Output methods include, but are not limited to: 1) tabular recording of each sub-index and the total LTI; 2) storing the results in a database for batch comparison and statistics; 3) generating visualizations, such as loop boundaries superimposed with ideal boundaries, curvature sign change points marked, nested relationship diagrams, etc.

[0075] Furthermore, the output results can be used for comparative analysis under different experimental or simulation conditions, including but not limited to different materials, temperatures, hydrogen concentrations, and irradiation doses. Through the above methods, this invention enables quantitative evaluation and standardized comparison of dislocation toroidal evolution, thereby providing support for statistical analysis, mechanistic explanation, and database construction of defect structures.

[0076] Therefore, it can be seen that the above four indicators (i.e., nesting indicator, connectivity indicator, roughness indicator, and boundary undulation indicator) are all dimensionless and independent indicators. Taking dislocation loops as closed curve defects for illustration, the embodiments of the present invention have the following significant advantages by constructing the above-mentioned loop topology indicators:

[0077] 1) Strong comparability: All defined indicators are dimensionless quantities with clear numerical ranges (i.e., typical values ​​are all in the range of 0 to 4, see examples below), which can be directly used for comparative analysis between different samples and different experimental conditions.

[0078] 2) Good additivity: The four indicators can be used individually or combined to form a total deviation indicator, which can adapt to the needs of different research and application scenarios;

[0079] 3) High interpretability: Each index corresponds to a specific physical meaning, and the results are intuitive, making them easy for researchers and engineers to understand and apply. For example, the physical meaning of the nested index is: the existence of nested structures indicates strong long-range stress field interactions and spatial constraints between dislocation loops, forming a multi-level defect structure; the physical meaning of the connectivity index is: the number of internal connecting lines characterizes the activity of dislocation loop reactions. A high connectivity index indicates frequent interactions between dislocation loops in the system, forming a deviated three-dimensional network, representing that the material is more likely to form stable dislocation entanglements under irradiation / stress, affecting strength and hardening; the physical meaning of the roughness index is: dislocation loops approaching the ideal dislocation loop shape indicate that the system's energy state is close to equilibrium, significantly deviating from the theoretical shape, indicating that dislocation loop growth is affected by stress disturbances, loop merging, or impurities, light elements such as hydrogen, and is in a non-uniform evolution state. The physical meaning of the boundary undulation index is as follows: a low boundary undulation index indicates that the growth rate of the dislocation loop is uniform, while a high boundary undulation index indicates that the boundary height of the loop is deviated and uneven, which may be directly related to the nucleation, uneven growth, or hydrogen regulation effect of the local steps of the dislocation loop.

[0080] 4) Wide range of applications: This method is not only applicable to dislocation loops, but also to the deviation analysis of other closed curve-shaped defects, such as holes, corrosion pits, bubbles, etc., and has good potential for expansion.

[0081] 5) Balanced magnitude distribution: The indicators are constructed to achieve a balanced distribution (typical values ​​are all in the 0-4 range), avoiding dominant bias and facilitating multi-factor sensitivity analysis and statistical interpretation;

[0082] 6) Balancing quantification and intuitiveness: This method can be used for rigorous numerical quantitative analysis as well as for generating graphical representations, meeting the needs of different users for intuitive explanations or engineering comparisons.

[0083] The following is combined Figures 5 to 9 The above technical solutions will be explained.

[0084] Benchmark Example 1: Morphological Deviation of an Ideal Dislocation Loop

[0085] In this invention, an ideal dislocation loop refers to the shape of a dislocation loop predicted by elasticity theory. An ideal dislocation loop is defined as having only one closed boundary, no nested loops (T1=0), no internal connecting structures (T2=0), a boundary shape consistent with the shape predicted by elasticity theory (T3=1), and no boundary undulation characteristics (T4=0). Therefore, the total morphological deviation index of this ideal dislocation loop is: LTI=1. This benchmark establishes a quantitative benchmark for evaluating morphological deviation, enabling subsequent embodiments to be compared under a unified standard. For any dislocation loop, the degree of deviation of the LTI value from the benchmark value of 1 directly reflects the magnitude of its morphological deviation.

[0086] Comparative Example 1: Case of slight deviation from ideal dislocation loop

[0087] like Figure 5 As shown, where: Figure 5 a is an image of a dislocation loop taken by transmission electron microscopy; Figure 5 b is a closed boundary curve obtained by manual drawing; Figure 5 c corresponds to the roughness ratio index T3 calculation result of three closed dislocation loops. The dashed line is the ideal dislocation loop boundary with equivalent area, and the solid line is the actual dislocation loop boundary. The image has been mirrored and rotated compared to the original image. Figure 5 The calculation result of the boundary undulation deviation index T4 corresponding to the three closed dislocation loops shows that there are no curvature sign change points at the boundaries of the three loops.

[0088] Irradiating body-centered cubic pure iron samples with iron ions without introducing a special atmosphere (such as hydrogen) or special irradiation conditions, such as... Figure 5 As shown in Figure a. The image is imported into an image processing platform, where a continuous curve is identified, and as shown in Figure a. Figure 5 As shown in b, it is exported as standardized vector data (such as SVG format).

[0089] Subsequently, it was determined that three closed dislocation loops existed in the obtained curves, denoted as loop1-3. These three dislocation loops have no nesting relationship or internal connection structure; therefore, for these three loops, T1=T2=0. The roughness index T3 and the boundary undulation index T4 were then calculated. After comparing with the perimeter of an ideal dislocation loop of equal area, the roughnesses of loop1–3 were 0.97, 0.95, and 0.97 respectively (e.g., ...). Figure 5 As shown in c), and there are no points where the curvature changes sign, therefore T4=0 ( Figure 5 (as shown in d).

[0090] Based on this, the LTI values ​​of the three rings were obtained as 0.97, 0.95, and 0.97, respectively, all close to the baseline LTI value of 1 for an ideal dislocation ring. This indicates that the dislocation ring morphology in this embodiment has extremely low deviation and is highly consistent with the projected shape of the ideal dislocation ring predicted by elasticity theory, with smooth boundaries and no obvious spikes or boundary undulations.

[0091] Comparative Example 2: Identification of Nested Rings and Calculation of Nested Indicators

[0092] like Figure 6 As shown, where: Figure 6 Image a is the original TEM image, showing a typical nested dislocation loop structure, characterized by the presence of a smaller loop inside a larger loop. Figure 6 b is from Figure 6 The continuous curve results identified and extracted in step a form two closed curves, corresponding to the external dislocation loop and the nested dislocation loop inside it, respectively. These can be used as input data for subsequent calculation of the nesting ratio index T1.

[0093] The dislocation loop images obtained under the experimental conditions of Kr ion irradiation of Mo-5Re are as follows: Figure 6 As shown in a. Export the image as vector data (such as SVG format). Figure 6 (b) A set of candidate continuous curves is obtained. The closure of the candidate curves is determined in turn. The results show that there are two closed curves in the image, denoted as loop4 and loop5. The Euclidean distance between the beginning and end of the two curves is less than the threshold δ, and the curves have no obvious breaks. Therefore, they are both determined to be closed dislocation loops.

[0094] Furthermore, nesting relationships were identified for the closed boundaries loop4 and loop5. The minimum Euclidean distance dist(loop4, loop5) between the boundaries of loop4 and loop5 was calculated. The result was greater than the set threshold δ, thus ruling out intersection relationships. Rays were emitted into the interior of loop4 using the ray casting method. The number of intersection points was always even, confirming that loop5 is completely located inside loop4 and has no contact with the outer boundary. Therefore, loop5 was determined to be a sub-loop of loop4.

[0095] Therefore, the nesting ratio index T1 of this image is calculated as follows:

[0096] T1 (loop4) = 1 (containing 1 sub-loop);

[0097] T1(loop5) = 0 (no child loop).

[0098] In summary, this embodiment demonstrates the automatic identification of nested dislocation loops and the calculation process of the T1 index. The hierarchical structure formed by the outer loop and the inner loop is a typical "nested" feature, and its nesting index can quantitatively characterize the number of sub-loops within the loop, providing a quantitative basis for deviation analysis.

[0099] Comparative Example 3: Calculation of Dislocation Loop Deviation with Internal Connectors

[0100] like Figure 7 As shown, where: Figure 7 a is the original dislocation loop image obtained by transmission electron microscopy; Figure 7 b represents the vectorized result of the continuous curve obtained through image processing and manual drawing; Figure 7 c is the closed dislocation loop 6 identified in the figure, whose outer boundary and internal connecting lines have been completely extracted; Figure 7 d represents the connectivity analysis result of loop 6. The figure shows the endpoint positions where the open line segment contacts the external boundary. Figure 7 e is the closed dislocation loop 7 identified in the figure, which contains an internal connecting line; Figure 7f represents the connectivity analysis result of loop 7, showing the endpoints formed by the intersection of the internal connecting lines and the boundary within the closed loop.

[0101] like Figure 8 As shown, where: Figure 8 a and Figure 8 b represents the boundary superposition comparison between the actual dislocation loop (solid line) and the ideal dislocation loop (dashed line); Figure 8 c and Figure 8 d represents the curvature sign change points of the actual dislocation loops (the hollow circles are the curvature sign change points that satisfy the criterion).

[0102] S1. First, obtain images of the dislocation loop reaction taken by transmission electron microscopy (e.g., ...). Figure 7 a). And on Figure 7 The curves in section a are manually traced. Specifically, Adobe Illustrator (AI) software is used to trace them and save them as SVG format (e.g., ...). Figure 7 b).

[0103] S2, Calculation Figure 7 The LTI of dislocation loops in b is specifically implemented through the following steps:

[0104] S21, to Figure 7 Closure identification was performed on the continuous curves in b, and the results showed that 2 closed boundaries and 5 open curves were identified. Therefore, there are two closed dislocation loops, loop 6 (e.g.). Figure 7 c) and loop 7 (e.g.) Figure 7 e).

[0105] S22. For loop6 and loop7, the same method as in Comparative Example 2 is used for calculation. Neither is completely surrounded by other loops, so T1=0.

[0106] S23. Based on the confirmed two closed boundaries (loop6 and loop7) and five open curves, further identify their internal connecting lines:

[0107] All four curves satisfy the condition that "both endpoints are in contact with the outer boundary of loop 6 and are located inside loop 6", such as Figure 7 As shown in d (the endpoints of the boundary contact are marked with a cross), it is therefore determined to be an internal connection line of loop 6.

[0108] A curve satisfies the condition that "both endpoints are in contact with the outer boundary of loop7 and are located inside loop7", such as... Figure 7 As shown in f, it is therefore determined to be an internal connection line of loop 7.

[0109] Therefore, we get T2 (loop6)=4 and T2 (loop7)=1.

[0110] S24. Construct an ideal dislocation loop. Based on the actual dislocation loop's Burgers vector (e.g., 1 / 2

[111] ), its crystal plane (e.g., (111)), and the observation axis under a transmission electron microscope (e.g., the

[001] axis), calculate the shape of the 1 / 2

[111] dislocation loop on the (111) crystal plane according to elasticity theory, and project it onto the

[001] observation axis as the ideal shape of the actual dislocation loop. Extract the closed boundary of the actual dislocation loop and calculate its perimeter P. loop With area A loop Generation and A loop Calculate the ideal perimeter P of an ideal dislocation loop with equal area. ideal Given T3=P loop / P ideal The results showed that Figure 8 In loop 6 of a, T3 = 1.38. Figure 8 In loop 7 of b, T3 = 1.02.

[0111] S25. Resample the boundary using uniform arc length, calculate the discrete curvature κ[i], and identify the curvature sign change point N. inflection .by A quantitative indicator of boundary variability. The results are as follows: Figure 8 As shown in c and 8d, T4 = 3.68 for loop 6 and T4 = 1.31 for loop 7.

[0112] S3. Add the four topological indices T1-T4 obtained from loop 6 and loop 7 in the previous step without weighting to obtain the total topological deviation index (i.e., the loop topological index). According to the formula:

[0113] For loop 6, given T1=0, T2=4, T3=1.38, T4=3.68, LTI=0+4+1.38+3.68=9.06. For loop 7, given T1=0, T2=1, T3=1.02, T4=1.31, LTI=0+1+1.02+1.31=3.33. In this embodiment, the morphological deviation of loop 6 is significantly higher than that of loop 7.

[0114] Comparative Example 4: Dislocation loops with high boundary roughness and significant undulation

[0115] like Figure 9 and Figure 10 As shown, where: Figure 9 Image a is a dislocation loop image taken with a transmission electron microscope; Figure 9 b is a continuous curve traced using image processing tools; Figure 9 c represents the boundary superposition comparison between the actual dislocation loop (i.e., the solid line) and the ideal dislocation loop (i.e., the dashed line); Figure 10The left column shows the extracted closed boundary, and the right column shows the curvature sign change point annotation diagram (the sign change point is represented by ×, and N is the number of sign change points), and gives the calculation result of the boundary undulation index T4.

[0116] against Figure 9 a- Figure 9 For the dislocation loop shown in b, the indices T1-T4 are calculated according to the steps described above. Since the detailed calculation method has been given in the previous embodiments, it will not be repeated here; only the results are given.

[0117] The results showed that ( Figure 9 c and Figure 10 Loop 8 is a non-nested loop and connection structure with T1=T2=0, roughness index T3=2.11, and boundary undulation index T4=3.17, therefore LTI=5.28. Similarly, loop 9 has T1=T2=0, T3=2.12, and T4=3.26, therefore LTI=5.38. Loop 10 has T1=T2=0, T3=2.02, and T4=3.58, therefore LTI=5.6. In this embodiment, all three dislocation loops exhibit obvious thorn-like and rough characteristics, thus resulting in high LTI, mainly reflected in T3 and T4, with similar values.

[0118] It is worth noting that the greater the deviation between the actual morphology of the dislocation loop and the ideal morphology, the worse the relevant performance of the nuclear material under the experimental conditions may be.

[0119] like Figure 2 , Figure 3 As shown, this embodiment of the invention provides a device for quantifying the morphological deviation of closed curve-type defects. The device embodiment can be implemented through software, hardware, or a combination of both. From a hardware perspective, as... Figure 2 The diagram shown is a hardware architecture diagram of an electronic device for measuring the morphological deviation of closed curve-type defects, provided in an embodiment of the present invention. (Except for...) Figure 2 In addition to the processor, memory, network interface, and non-volatile memory shown, the electronic device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing packets. Taking software implementation as an example, such as... Figure 3 As shown, a device in a logical sense is formed by the CPU of the electronic device in which it is located reading the corresponding computer program from the non-volatile memory into the memory for execution.

[0120] like Figure 3 As shown, the present invention provides a metric device for measuring morphological deviation of closed curve-type defects, comprising:

[0121] The extraction module 300 is used to extract curves from the target image captured by the transmission electron microscope to obtain closed curve defects and open curve defects.

[0122] The determination module 302 is used to determine the loop topology index of each closed curve type defect based on open curve type defects and other closed curve type defects; wherein the loop topology index is used to quantify the deviation between the actual shape of the closed curve type defect and the ideal shape predicted by elasticity theory.

[0123] In this embodiment of the invention, the extraction module 300 can be used to execute step 100 in the above method embodiment, and the determination module 302 can be used to execute step 102 in the above method embodiment.

[0124] In one embodiment of the present invention, closed curve defects include dislocation loops, holes, corrosion pits, and bubbles.

[0125] In one embodiment of the present invention, the ring topology index includes a nesting index, a connectivity index, a roughness index, and a boundary undulation index. The nesting index is used to characterize the hierarchical nesting relationship between closed curve-type defects, the connectivity index is used to characterize the connection structure relationship within closed curve-type defects, the roughness index is used to characterize the boundary length variation of closed curve-type defects, and the boundary undulation index is used to characterize the boundary curvature variation of closed curve-type defects.

[0126] In one embodiment of the present invention, the nested index is determined in the following manner:

[0127] Select defect C, excluding the closed curve type. i The remaining closed curve type defect set {C j} j≠i As a set of candidate closed curve defects;

[0128] For each candidate closed curve type defect C j Calculate C i and C j The minimum Euclidean distance between them is dist(C) i C j );

[0129] If dist(C i C j If )≤δ1, and δ1 is the first preset value, then determine C. i and C j They are intersecting, but not considered as containing each other;

[0130] Otherwise, perform the following operation: From C j Several first sampling points are uniformly selected on the boundary; for each first sampling point, a direction is drawn towards C.i The center emits a first ray, and the correlation between this first ray and C is statistically analyzed. i The number of intersection points; if the number of intersection points is odd, then the first sampling point is determined to be in C. i If the number of intersection points is even within C, then the first sampling point is determined to be within C. i The outside; when all first sampling points are determined to be in C i When inside, record ;

[0131] Located at C i All C inside j The sum of the quantities is used as the nested index T1.

[0132] In one embodiment of the present invention, the connectivity index is determined in the following manner:

[0133] Remove open curve defects whose length is less than a preset length, and leave the set of open curve defects {L}. k} as a set of candidate open curve defects;

[0134] Denote the open curve class defect L for each candidate line. k The endpoint is A k and B k Calculate A k and B k to C respectively i The minimum Euclidean distance of the boundary, dist(A) k C i ) and dist(B k C i );

[0135] When dist(A) k C i )≤δ1 and dist(B k C i When )≤δ1, determine A k and B k Both are related to C i If the boundaries intersect, then L is determined to be an integer. k Not C i Internal connecting wires;

[0136] Regarding A k and B k Both are related to C i Each L intersecting the boundary k All of them perform the following operations: from L k Several second sampling points are uniformly selected on the boundary; for each second sampling point, a direction is drawn towards C. i The center emits a second ray, and the statistical analysis shows that this second ray is related to C. iThe number of intersection points; if the number of intersection points is odd, then the second sampling point is determined to be in C. i If the number of intersection points is even within C, then the second sampling point is determined to be within C. i The outside; when all second sampling points are determined to be in C i When it is inside, and there is no other than A k and B k The second sampling point outside and C i The boundaries intersect, denoted as L. k C i Internal connecting wires;

[0137] All C i The sum of the number of internal connecting lines is used as the connectivity index T2.

[0138] In one embodiment of the present invention, the roughness index is determined in the following manner:

[0139] Accumulate C sequentially according to the boundary point sequence. i The Euclidean distance between adjacent points is C. i The total perimeter P of the entire boundary loop ;

[0140] Calculate C using the shoelace rule i The area A of the entire boundary loop ;

[0141] Let A be the area of ​​the ideal closed-curve defect predicted by elasticity theory. loop And obtain the total perimeter P of the entire boundary of the ideal closed curve type defect. ideal ;

[0142] P loop and P ideal The quotient is used as the roughness index T3.

[0143] In one embodiment of the present invention, the boundary undulation index is determined in the following manner:

[0144] For C i Curvature calculations are performed on the sampling points of the entire boundary to obtain the curvature value κ[i] of the i-th sampling point on the boundary;

[0145] If a sampling point on the boundary satisfies the following condition, then the sampling point is determined to be a point where the curvature changes sign:

[0146] sign(κ[i])≠sign(κ[i+1]);

[0147] max(∣κ[i]∣,∣κ[i+1]∣)>δ2;

[0148] The curvature signs of the first five sampling points of the i-th sampling point are the same, and are consistent with the sign of κ[i].

[0149] The curvature signs of the five sampling points after the (i+1)th sampling point are the same and consistent with the sign of κ[i+1];

[0150] In the formula, sign(κ[i]) is the sign of curvature at the i-th sampling point, sign(κ[i+1]) is the sign of curvature at the (i+1)-th sampling point, max(∣κ[i]∣,∣κ[i+1]∣) is the maximum value of the absolute curvature values ​​of the i-th and (i+1)-th sampling points, δ2 is the second preset value, and the curvature sign is positive or negative;

[0151] Let N be the sum of the number of sampling points that simultaneously meet the above conditions. inflection Then C i The boundary undulation index T4 is determined by the following formula:

[0152]

[0153] The ring topology index LTI is determined by the following formula:

[0154] .

[0155] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on a morphological deviation measurement device for closed curve type defects. In other embodiments of the present invention, a morphological deviation measurement device for closed curve type defects may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0156] The information interaction and execution process between the modules in the above-mentioned device are based on the same concept as the method embodiment of the present invention, and the specific details can be found in the description of the method embodiment of the present invention, and will not be repeated here.

[0157] This invention also provides an electronic device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements a method for quantifying the morphological deviation of closed curve-type defects according to any embodiment of this invention.

[0158] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform a morphological deviation quantification method for closed curve-type defects according to any embodiment of this invention.

[0159] Specifically, a system or apparatus equipped with a storage medium may be provided, on which software program code implementing the functions of any of the embodiments described above is stored, and the computer (or CPU or MPU) of the system or apparatus may read and execute the program code stored in the storage medium.

[0160] In this case, the program code read from the storage medium can itself implement the function of any of the above embodiments, and therefore the program code and the storage medium storing the program code constitute part of the present invention.

[0161] Storage media embodiments for providing program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, program code can be downloaded from a server computer via a communication network.

[0162] Furthermore, it should be clear that not only can the program code read by the computer be executed, but also the operating system or other components operating on the computer can be instructed based on the program code to perform some or all of the actual operations, thereby realizing the function of any of the embodiments described above.

[0163] Furthermore, it is understood that the program code read from the storage medium is written to the memory set in the expansion board inserted into the computer or to the memory set in the expansion module connected to the computer. Then, based on the instructions of the program code, the CPU or other components installed on the expansion board or expansion module execute some and all of the actual operations, thereby realizing the function of any of the above embodiments.

[0164] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0165] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as ROM, RAM, magnetic disk, or optical disk.

[0166] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention 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 of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for quantifying morphological deviation of closed curve-type defects, characterized in that, include: Curve extraction is performed on the target image captured by transmission electron microscopy to obtain closed curve defects and open curve defects; For each closed curve type defect, based on open curve type defects and other closed curve type defects, the loop topology index of the closed curve type defect is determined; wherein, the loop topology index is used to quantify the deviation between the actual shape of the closed curve type defect and the ideal shape predicted by elasticity theory. The ring topology index includes nesting index, connectivity index, roughness index and boundary undulation index. The nesting index is used to characterize the hierarchical nesting relationship between closed curve defects. The connectivity index is used to characterize the connection structure relationship within closed curve defects. The roughness index is used to characterize the boundary length variation of closed curve defects. The boundary undulation index is used to characterize the boundary curvature variation of closed curve defects. Closed-curve defects include dislocation loops, voids, corrosion pits, and bubbles; The nested metrics are determined in the following way: Select defect C, excluding the closed curve type. i The remaining closed curve type defect set {C j } j≠i As a set of candidate closed curve defects; For each candidate closed curve type defect C j Calculate C i and C j The minimum Euclidean distance between them is dist(C) i C j ); If dist(C i C j If )≤δ1, and δ1 is the first preset value, then determine C. i and C j They are intersecting, but not considered as containing each other; Otherwise, perform the following operation: From C j Several first sampling points are uniformly selected on the boundary; for each first sampling point, a direction is drawn towards C. i The center emits a first ray, and the correlation between this first ray and C is statistically analyzed. i The number of intersection points; If the number of intersection points is odd, then the first sampling point is determined to be in C. i If the number of intersection points is even within C, then the first sampling point is determined to be within C. i The outside; when all first sampling points are determined to be in C i When inside, record ; Located at C i All C inside j The sum of the quantities is used as the nested index T1.

2. The method according to claim 1, characterized in that, The connectivity index is determined in the following way: Remove open curve defects whose length is less than a preset length, and leave the set of open curve defects {L}. k } as a set of candidate open curve defects; Denote the open curve class defect L for each candidate line. k The endpoint is A k and B k Calculate A k and B k to C respectively i The minimum Euclidean distance of the boundary, dist(A) k C i ) and dist(B k C i ); When dist(A) k C i )≤δ1 and dist(B k C i When )≤δ1, determine A k and B k Both are related to C i The boundaries intersect; Otherwise, determine L k Not C i Internal connecting wires; Regarding A k and B k Both are related to C i Each L intersecting the boundary k All of them perform the following operations: from L k Several second sampling points are uniformly selected on the boundary; for each second sampling point, a direction is drawn towards C. i The center emits a second ray, and the statistical analysis shows that this second ray is related to C. i The number of intersection points; If the number of intersection points is odd, then the second sampling point is determined to be in C. i If the number of intersection points is even within C, then the second sampling point is determined to be within C. i The exterior; When all second sampling points are determined to be in C i When it is inside, and there is no other than A k and B k The second sampling point outside and C i The boundaries intersect, denoted as L. k C i Internal connecting wires; All C i The sum of the number of internal connecting lines is used as the connectivity index T2.

3. The method according to claim 2, characterized in that, The roughness index is determined in the following way: Accumulate C sequentially according to the boundary point sequence. i The Euclidean distance between adjacent points is C. i The total perimeter P of the entire boundary loop ; Calculate C using the shoelace rule i The area A of the entire boundary loop ; Let A be the area of ​​the ideal closed-curve defect predicted by elasticity theory. loop And obtain the total perimeter P of the entire boundary of the ideal closed curve type defect. ideal ; P loop and P ideal The quotient is used as the roughness index T3.

4. The method according to claim 3, characterized in that, The boundary undulation index is determined in the following manner: For C i Curvature calculations are performed on the sampling points of the entire boundary to obtain the curvature value κ[i] of the i-th sampling point on the boundary; If a sampling point on the boundary satisfies the following condition, then the sampling point is determined to be a point where the curvature changes sign: sign(κ[i])≠sign(κ[i+1]); max(∣κ[i]∣,∣κ[i+1]∣)>δ2; The curvature signs of the first five sampling points of the i-th sampling point are the same, and are consistent with the sign of κ[i]. The curvature signs of the five sampling points after the (i+1)th sampling point are the same and consistent with the sign of κ[i+1]; In the formula, sign(κ[i]) is the sign of curvature at the i-th sampling point, sign(κ[i+1]) is the sign of curvature at the (i+1)-th sampling point, max(∣κ[i]∣,∣κ[i+1]∣) is the maximum value of the absolute curvature values ​​of the i-th and (i+1)-th sampling points, δ2 is the second preset value, and the curvature sign is positive or negative; Let N be the sum of the number of sampling points that simultaneously meet the above conditions. inflection Then C i The boundary undulation index T4 is determined by the following formula: The ring topology index LTI is determined by the following formula: 。 5. A device for quantifying morphological deviation of closed-curve defects, characterized in that, The method applied to any one of claims 1-4 includes: The extraction module is used to extract curves from target images captured by a transmission electron microscope to obtain closed curve defects and open curve defects. The determination module is used to determine the loop topology index of each closed curve defect based on open curve defects and other closed curve defects; wherein the loop topology index is used to quantify the deviation between the actual shape of the closed curve defect and the ideal shape predicted by elasticity theory. The ring topology index includes nesting index, connectivity index, roughness index, and boundary undulation index. The nesting index is used to characterize the hierarchical nesting relationship between closed curve defects. The connectivity index is used to characterize the connection structure relationship within closed curve defects. The roughness index is used to characterize the boundary length variation of closed curve defects. The boundary undulation index is used to characterize the boundary curvature variation of closed curve defects.

6. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed in a computer, causes the computer to perform the method described in any one of claims 1-4.

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