Ebsd orientation bivector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-07-14
- Publication Date
- 2026-08-11
AI Technical Summary
该类表示方式虽然便于二维可视化，但单一单位方向向量仅包含两个独立自由度，只能确定一个方向，而无法确定围绕该方向的转动状态
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Figure CN122550832A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of material microstructure characterization and data-driven reconstruction technology, and in particular to an EBSD orientation-based bi-vector reversible periodic encoding method and system for three-dimensional reconstruction of polycrystalline materials. Background Technology
[0002] Backscattered electron diffraction (EBSD) technology has been widely used in the analysis of material microstructure and crystal orientation. EBSD data are typically characterized by Euler angles, inverse pole figure colors, pole figure projections, or orientation matrices to represent the local crystal orientation state of each pixel in a sample. For 3D generative learning and 3D orientation field reconstruction tasks, a key issue in related research is how to convert orientation information into a representation suitable for neural network learning while preserving the physical meaning of orientation.
[0003] In material sample characterization, the sample coordinate system typically consists of the rolling direction RD, the transverse direction TD, and the normal direction ND. RD, TD, and ND are pairwise orthogonal and form a right-handed coordinate system. Therefore, a complete crystal orientation can be considered as the directional relationship between the crystal coordinate system and this set of three-dimensional orthogonal directions in the sample coordinate system. In other words, a complete orientation is not uniquely characterized by a single direction, but is determined by multiple directions that satisfy orthogonal relationships.
[0004] In existing technologies, a single target direction is often used to characterize local orientation. For example, the inverse pole figure color corresponding to the normal direction ND or a single direction vector is used to describe the local crystal orientation of a sample. While this representation is convenient for two-dimensional visualization, a single unit direction vector only contains two independent degrees of freedom, which can only determine one direction and cannot determine the rotational state around that direction. Therefore, when only ND is known, there are still multiple possible orientations rotating around ND, which cannot be uniquely inversely mapped back to the complete orientation matrix. In other words, the traditional method of only looking at ND is inherently insufficient to support complete and reversible three-dimensional orientation reconstruction.
[0005] To address this technical problem, a bi-vector reversible periodic encoding method and system for EBSD orientation in three-dimensional reconstruction of polycrystalline materials is proposed. Summary of the Invention
[0006] To address the technical problems existing in the prior art, this invention provides an EBSD orientation bi-vector reversible periodic encoding method and system for three-dimensional reconstruction of polycrystalline materials. In the context of the sample coordinate system, two non-collinear direction vectors are used as the core representation of orientation, and the periodic attribute of the orientation angle is explicitly encoded as a continuous channel representation. Thus, while preserving the complete orientation recovery path, it provides an implementable representation basis for orientation field reconstruction in three-dimensional generative learning.
[0007] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions: In a first aspect, in one embodiment of the present invention, an EBSD orientation bivector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials is provided, the method comprising the following steps: Obtain the Euler angle parameters and their corresponding spatial coordinates for each pixel or voxel in the EBSD data; The Euler angle parameters are converted into an orientation matrix according to the crystallographic coordinate transformation relationship; The normal direction vector ND and rolling direction vector RD in the sample coordinate system are extracted from the orientation matrix to construct a two-vector orientation representation; The normal direction vector ND and the rolling direction vector RD are periodically encoded respectively to obtain a six-channel periodically encoded representation; Multi-directional slice training data is constructed based on the six-channel periodic encoding representation and used as the input representation of the three-dimensional generative learning model for model training and generation sampling to obtain the six-channel periodic encoding result; The six-channel periodic encoding results are periodically decoded to recover the normal direction vector ND and the rolling direction vector RD, and the three-dimensional orientation field is reconstructed based on the recovered two-vector orientation representation.
[0008] As a further aspect of the present invention, obtaining the Euler angle parameters and corresponding spatial coordinates of each pixel or voxel in the EBSD data includes: The sample is scanned to obtain the diffraction pattern signal of each pixel on the sample surface; The Euler angle parameters and their spatial coordinate information corresponding to each pixel are extracted through an automatic indexing process to form the original orientation dataset. When the input data consists of multiple consecutive two-dimensional slices, a three-dimensional spatial index is established based on the slice number; when the input data consists of three-dimensional volume data, the voxel coordinates are read directly.
[0009] As a further aspect of the present invention, the step of converting the Euler angle parameters into an orientation matrix according to crystallographic coordinate transformation includes: Construct the corresponding orientation matrix G based on the Euler angle parameters of each pixel or voxel; In the sample coordinate system, the first column vector of the orientation matrix is defined as the rolling direction vector RD, and the third column vector of the orientation matrix is defined as the normal direction vector ND. A right-handed orthogonal coordinate system is constructed using the rolling direction vector RD, the transverse direction vector TD, and the normal direction vector ND.
[0010] As a further aspect of the present invention, let the orientation matrix be:
[0011] Then, its first column vector is taken as the rolling direction vector RD:
[0012] Take its third column vector as the normal direction vector ND:
[0013] The lateral direction vector TD can be recovered from the cross product relation:
[0014] To obtain a complete right-handed orthogonal orientation base.
[0015] As a further aspect of the present invention, the normal direction vector ND and the rolling direction vector RD together constitute a two-vector original representation:
[0016] The bi-vector primitive representation is used to replace the single-direction representation in order to establish a reversible recovery path with complete orientation.
[0017] As a further aspect of the present invention, the step of periodically encoding the normal direction vector ND and the rolling direction vector RD respectively to obtain a six-channel periodically encoded representation includes: For any target direction vector Its azimuth is defined as And construct the corresponding three-channel periodic code.
[0018]
[0019] The normal direction vector ND is encoded as the first three channels, and the rolling direction vector RD is encoded as the last three channels, thus obtaining a six-channel periodic encoding representation.
[0020] As a further aspect of the present invention, the six-channel periodic encoding is represented as follows:
[0021] in, The azimuth angle is the normal direction vector ND. The azimuth angle is the rolling direction vector RD.
[0022] As a further aspect of the present invention, the six-channel periodic encoding represents a three-dimensional six-channel encoding body formed by arranging its corresponding spatial coordinates, wherein each voxel position in the three-dimensional six-channel encoding body corresponds to a set of six-channel periodic encoding vectors.
[0023] As a further aspect of the present invention, multi-directional slice training data is constructed based on the three-dimensional six-channel encoder. The multi-directional slice training data is obtained by sampling two-dimensional slices of the three-dimensional six-channel encoder along at least two of the three directions XY, XZ and YZ, and is used as the input representation of the three-dimensional generative learning model.
[0024] Secondly, in another embodiment provided by the present invention, an EBSD orientation bi-vector reversible periodic encoding system for three-dimensional reconstruction of polycrystalline materials is provided. This system includes: a data acquisition module, an orientation matrix construction module, a bi-vector extraction module, a periodic encoding module, a generation learning module, and a decoding reconstruction module, wherein: The data acquisition module is used to acquire the Euler angle parameters of each pixel or voxel in the EBSD data and their corresponding spatial coordinates. The orientation matrix construction module is used to convert the Euler angle parameters into an orientation matrix according to the crystallographic coordinate transformation relationship; The dual-vector extraction module is used to extract the normal direction vector ND and the rolling direction vector RD in the sample coordinate system from the orientation matrix to construct a dual-vector orientation representation. The periodic encoding module is used to periodically encode the normal direction vector ND and the rolling direction vector RD respectively to obtain a six-channel periodic encoding representation. The generative learning module is used to construct multi-directional slice training data based on the six-channel periodic encoding representation, and use it as the input representation of the three-dimensional generative learning model for model training and generation sampling to obtain the six-channel periodic encoding result; The decoding and reconstruction module is used to periodically decode the six-channel periodic encoding results, recover the normal direction vector ND and the rolling direction vector RD, and reconstruct the three-dimensional orientation field based on the recovered two-vector orientation representation.
[0025] The technical solution provided by this invention has the following beneficial effects: Firstly, within the sample coordinate system RD, TD, ND, a two-vector orientation representation is constructed using two non-collinear direction vectors, RD and ND. Compared to using only a single ND representation, this avoids the loss of degrees of freedom and provides a foundation for complete orientation recovery. Secondly, through... The third direction vector is recovered, thus reconstructing the complete right-handed orthogonal orientation basis under the condition of encoding only two direction vectors, reducing the redundancy caused by simultaneous encoding of three directions; third, by explicitly encoding the periodic attribute of the orientation angle as sine and cosine components, it is beneficial to reduce the influence of numerical breakage caused by periodic boundaries when directly using angle parameters, and it is suitable as an orientation input representation for three-dimensional generative learning; fourth, the constructed six-channel periodic encoding representation has a clear decoding path, which can be used to recover ND, RD and TD, and provide an implementable representation basis for the orientation field reconstruction of the generated results.
[0026] These or other aspects of the invention will become more apparent from the following description of embodiments. It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description
[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these drawings without creative effort.
[0028] Figure 1 This is a flowchart of an EBSD orientation bivector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials according to an embodiment of the present invention.
[0029] Figure 2 This is a right-handed diagram of the sample coordinate system RD, TD, ND in the EBSD orientation bi-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials according to an embodiment of the present invention.
[0030] Figure 3 This is a schematic diagram illustrating the extraction of RD and ND from Euler angles to the orientation matrix in the EBSD orientation bivector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials according to an embodiment of the present invention.
[0031] Figure 4 This is a three-channel periodic encoding diagram of a single direction vector in the EBSD orientation dual-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials according to an embodiment of the present invention.
[0032] Figure 5 This is a diagram illustrating the composition of a six-channel periodic encoding representation in an EBSD orientation-based bi-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials, according to an embodiment of the present invention.
[0033] Figure 6This is a multi-directional slice image in the 3D generation learning of the EBSD orientation bi-vector reversible periodic encoding method for 3D reconstruction of polycrystalline materials according to an embodiment of the present invention.
[0034] Figure 7 This is a decoding recovery and complete orientation reconstruction image in the EBSD orientation bivector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials according to an embodiment of the present invention.
[0035] Figure 8 This is a schematic diagram of the structure of the EBSD orientation bivector reversible periodic coding system for 3D reconstruction of polycrystalline materials.
[0036] In the diagram: Data acquisition module-100, orientation matrix construction module-200, dual vector extraction module-300, periodic encoding module-400, generative learning module-500, and decoding and reconstruction module-600. Detailed Implementation
[0037] 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 only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0038] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.
[0039] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.
[0040] Specifically, the embodiments of the present invention will be further described below with reference to the accompanying drawings.
[0041] Please see Figure 1 , Figure 1 This is a flowchart of an EBSD orientation bivector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials provided by an embodiment of the present invention, as shown below. Figure 1 As shown, the EBSD orientation bi-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials includes steps S10 to S60.
[0042] S10. Obtain the Euler angle parameters and their corresponding spatial coordinates for each pixel or voxel in the EBSD data.
[0043] In an embodiment of the present invention, step S10, obtaining the Euler angle parameters of each pixel or voxel in the EBSD data and their corresponding spatial coordinates, includes steps S101 to S103.
[0044] S101. Scan the sample to obtain the diffraction pattern signal of each pixel on the sample surface.
[0045] In an embodiment of the present invention, step S101, scanning the sample to obtain the diffraction pattern signal of each pixel on the sample surface, includes scanning the sample using backscattered electron diffraction.
[0046] S102. Extract the Euler angle parameters and spatial coordinate information corresponding to each pixel through an automatic indexing process to form the original orientation dataset.
[0047] In an embodiment of the present invention, step S102, extracting the Euler angle parameters and their spatial coordinate information corresponding to each pixel to form an original orientation dataset, includes: The Euler angle parameters and their spatial coordinates for each pixel are extracted through an automatic indexing process.
[0048] S103. When the input data consists of multiple consecutive two-dimensional slices, a three-dimensional spatial index is established based on the slice number; when the input data consists of three-dimensional volume data, the voxel coordinates are read directly.
[0049] Specifically, when the input data consists of multiple consecutive two-dimensional slices, a precise index is created for each slice in the three-dimensional coordinate system based on the number corresponding to each slice, thereby integrating the discrete two-dimensional image sequence into a three-dimensional data volume with spatial continuity. When the input data itself is already organized three-dimensional volume data, the three-dimensional coordinate value corresponding to each voxel (three-dimensional pixel) can be read directly without additional index construction steps.
[0050] like Figure 2 and Figure 3 As shown, in step S20, the Euler angle parameters are converted into an orientation matrix according to the crystallographic coordinate transformation relationship.
[0051] In an embodiment of the present invention, step S20, converting the Euler angle parameters into an orientation matrix according to the crystallographic coordinate transformation relationship, includes steps S201 to S203.
[0052] S201. Construct the corresponding orientation matrix G based on the Euler angle parameters of each pixel or voxel.
[0053] Let the orientation matrix be:
[0054] Then, its first column vector is taken as the rolling direction vector RD:
[0055] Take its third column vector as the normal direction vector ND:
[0056] The reason for choosing the rolling direction vector RD and the normal direction vector ND is that if only the normal direction vector ND is used, only the crystal orientation corresponding to the normal direction can be determined, but the rotation state around that direction cannot be determined, and therefore the complete orientation cannot be uniquely recovered. When the rolling direction vector RD is further introduced, the two non-collinear directions in the sample coordinate system are simultaneously determined, and the transverse direction vector TD can be recovered by the cross product relationship.
[0057] To obtain a complete right-handed orthogonal orientation base.
[0058] S202. In the sample coordinate system, the first column vector of the orientation matrix is defined as the rolling direction vector RD, and the third column vector of the orientation matrix is defined as the normal direction vector ND.
[0059] The normal direction vector ND and the rolling direction vector RD together constitute the original two-vector representation:
[0060] The bi-vector primitive representation is used to replace the single-direction representation in order to establish a reversible recovery path with complete orientation.
[0061] S203. A right-handed orthogonal coordinate system is constructed using the rolling direction vector RD, the transverse direction vector TD, and the normal direction vector ND.
[0062] In the embodiments of the present invention, the bi-vector orientation representation is more conducive to alleviating the problem of periodic discontinuity of orientation parameters than the direct use of Euler angle parameters, and is also conducive to reducing the redundant influence of symmetric equivalent orientations at the representation level, thereby improving its adaptability to 3D generative learning tasks.
[0063] S30. Extract the normal direction vector ND and rolling direction vector RD from the orientation matrix in the sample coordinate system to construct a two-vector orientation representation.
[0064] like Figure 4 and 5 As shown, in step S40, the normal direction vector ND and the rolling direction vector RD are periodically encoded to obtain a six-channel periodically encoded representation.
[0065] In specific implementation, the normal direction vector ND and the rolling direction vector RD are periodically encoded to obtain a six-channel periodic encoding representation, specifically as follows: In specific implementation, the unit direction representation of the normal direction vector ND and the rolling direction vector RD in the sample coordinate system is converted into a three-channel periodic encoding representation composed of the azimuth cosine component, the azimuth sine component, and the axial component. The normal direction vector ND corresponds to the first three channels, and the rolling direction vector RD corresponds to the last three channels, thus obtaining a six-channel periodic encoding result.
[0066] In an embodiment of the present invention, periodic decoding of the six-channel periodic encoding result specifically involves: performing inverse normalization on the six-channel periodic encoding result output by the generative learning model, and recovering the normal direction vector ND and the rolling direction vector RD based on the azimuth cosine component, azimuth sine component, and axial component, respectively; subsequently, performing normalization and orthogonalization on the recovered normal direction vector ND and rolling direction vector RD, and completing the third direction vector by using the lateral direction vector TD = ND × RD, thereby constructing a complete orientation matrix G = [RD, TD, ND] that satisfies the right-hand orthogonal relation. Under ideal encoding conditions, the six-channel periodic encoding representation has a clear decoding and recovery path; for the approximate encoding result output by the generative learning model, a geometrically consistent two-vector orientation representation can be obtained through normalization, orthogonalization, and projection correction, and further converted into Euler angle parameters or an equivalent three-dimensional orientation field representation.
[0067] In an embodiment of the present invention, S40, the normal direction vector ND and the rolling direction vector RD are periodically encoded respectively to obtain a six-channel periodically encoded representation, including: For any target direction vector Its azimuth is defined as And construct the corresponding three-channel periodic code.
[0068]
[0069] The normal direction vector ND is encoded as the first three channels, and the rolling direction vector RD is encoded as the last three channels, thus obtaining a six-channel periodic encoding representation.
[0070] In an embodiment of the present invention, the six-channel periodic encoding is represented as follows:
[0071] in, The azimuth angle is the normal direction vector ND. This represents the azimuth angle of the rolling direction vector RD. This representation explicitly expands the periodic property of the azimuth angle into a continuous channel, avoiding the numerical breakage problem caused by directly using angle parameters.
[0072] like Figure 6 As shown, in step S50, multi-directional slice training data is constructed based on the six-channel periodic encoding representation and used as the input representation of the three-dimensional generative learning model for model training and generation sampling to obtain the six-channel periodic encoding result.
[0073] The preferred 3D generative learning model is a 3D generative model based on 2D slice supervision, such as the SliceGAN model; in other embodiments, generative adversarial networks with 3D volume generation capabilities or other 3D generative learning models may also be used.
[0074] like Figure 7 As shown, S60 performs periodic decoding on the six-channel periodic encoding results to recover the normal direction vector ND and the rolling direction vector RD, and reconstructs the three-dimensional orientation field based on the recovered two-vector orientation representation.
[0075] In this embodiment of the invention, step S60, periodically decoding the six-channel periodic encoding result to recover the normal direction vector ND and the rolling direction vector RD, and reconstructing the three-dimensional orientation field based on the recovered dual-vector orientation representation, includes: For any three-channel code (a, b, c), the inverse normalization is first performed as follows:
[0076] Based on:
[0077] Recover the planar orientation information and construct a vector: , , Recover ND and RD separately. To ensure geometric consistency, normalization and orthogonalization processes can be performed on the recovered RD and ND. Then, through... Recover the third-direction vector TD, and by
[0078] Reconstruct the complete orientation matrix or its equivalent three-dimensional orientation field representation.
[0079] In this embodiment of the invention, the six-channel periodic encoding represents a three-dimensional six-channel encoding body formed by arranging its corresponding spatial coordinates, and each voxel position in the three-dimensional six-channel encoding body corresponds to a set of six-channel periodic encoding vectors.
[0080] In this embodiment of the invention, multi-directional slice training data is constructed based on the three-dimensional six-channel encoder. The multi-directional slice training data is obtained by sampling the three-dimensional six-channel encoder in two-dimensional slices along at least two of the three directions XY, XZ and YZ, and is used as the input representation of the three-dimensional generative learning model.
[0081] It should be understood that although the above description follows a certain order, these steps are not necessarily executed in that order. Unless otherwise expressly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, some steps in this embodiment may include multiple steps or multiple stages, which are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be performed alternately or in turn with other steps or at least a portion of the steps or stages of other steps.
[0082] In one embodiment, see Figure 8 As shown in the figure, this embodiment provides a structural block diagram of an EBSD orientation bi-vector reversible periodic coding system for three-dimensional reconstruction of polycrystalline materials. Figure 8 As shown, the system includes: a data acquisition module 100, an orientation matrix construction module 200, a bi-vector extraction module 300, a periodic encoding module 400, a generative learning module 500, and a decoding and reconstruction module 600, wherein: The data acquisition module 100 is used to acquire the Euler angle parameters of each pixel or voxel in the EBSD data and their corresponding spatial coordinates.
[0083] The orientation matrix construction module 200 is used to convert the Euler angle parameters into an orientation matrix according to the crystallographic coordinate transformation relationship.
[0084] The dual-vector extraction module 300 is used to extract the normal direction vector ND and the rolling direction vector RD in the sample coordinate system from the orientation matrix to construct a dual-vector orientation representation.
[0085] The periodic encoding module 400 is used to periodically encode the normal direction vector ND and the rolling direction vector RD respectively to obtain a six-channel periodic encoding representation.
[0086] The generative learning module 500 is used to construct multi-directional slice training data based on the six-channel periodic encoding representation, and use it as the input representation of the three-dimensional generative learning model for model training and generation sampling to obtain the six-channel periodic encoding result.
[0087] The decoding and reconstruction module 600 is used to periodically decode the six-channel periodic encoding results, recover the normal direction vector ND and the rolling direction vector RD, and reconstruct the three-dimensional orientation field based on the recovered two-vector orientation representation.
[0088] The above modules can be fully or partially integrated, or they can be separated independently. Those skilled in the art can adjust them according to actual needs. The specific functions of each module can be referred to the corresponding content in the above method embodiments, which will not be repeated here.
[0089] In one embodiment, the present invention also provides a computer device storing a computer program executable by a processor. When the program is executed, it implements the steps of the EBSD orientation bi-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials described in the above method embodiment. Those skilled in the art will understand that the computer device in this embodiment can be a desktop computer, laptop computer, server, mobile terminal, or other electronic device with computing capabilities. Its structure can refer to the conventional structure of such devices in the prior art, and is not limited here.
[0090] In one embodiment, the present invention also provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the program implements the steps of the EBSD orientation bi-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials as described in the above method embodiments. Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc., all of which are within the scope of protection of the present invention.
[0091] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.
[0092] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Furthermore, any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include at least one of non-volatile and volatile memory.
[0093] It should be understood that, as used herein, the singular form "a" is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, "and / or" refers to any and all possible combinations of one or more of the associatedly listed items. The embodiment numbers disclosed above are for descriptive purposes only and do not represent any superiority or inferiority of the embodiments.
[0094] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in detail for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.
Claims
1. An EBSD orientation bivector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials, characterized in that, The method includes: Obtain the Euler angle parameters and their corresponding spatial coordinates for each pixel or voxel in the EBSD data; The Euler angle parameters are converted into an orientation matrix according to the crystallographic coordinate transformation relationship; The normal direction vector ND and rolling direction vector RD in the sample coordinate system are extracted from the orientation matrix to construct a two-vector orientation representation; The normal direction vector ND and the rolling direction vector RD are periodically encoded respectively to obtain a six-channel periodically encoded representation; Multi-directional slice training data is constructed based on the six-channel periodic encoding representation and used as the input representation of the three-dimensional generative learning model for model training and generation sampling to obtain the six-channel periodic encoding result; The six-channel periodic encoding results are periodically decoded to recover the normal direction vector ND and the rolling direction vector RD, and the three-dimensional orientation field is reconstructed based on the recovered two-vector orientation representation.
2. The EBSD orientation bi-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials as described in claim 1, characterized in that, The process of obtaining the Euler angle parameters and corresponding spatial coordinates of each pixel or voxel in the EBSD data includes: The sample is scanned to obtain the diffraction pattern signal of each pixel on the sample surface; The Euler angle parameters and their spatial coordinate information corresponding to each pixel are extracted through an automatic indexing process to form the original orientation dataset. When the input data consists of multiple consecutive two-dimensional slices, a three-dimensional spatial index is established based on the slice number; when the input data consists of three-dimensional volume data, the voxel coordinates are read directly.
3. The EBSD orientation bi-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials as described in claim 1, characterized in that, The step of converting the Euler angle parameters into an orientation matrix according to crystallographic coordinate transformation includes: Construct the corresponding orientation matrix G based on the Euler angle parameters of each pixel or voxel; In the sample coordinate system, the first column vector of the orientation matrix is defined as the rolling direction vector RD, and the third column vector of the orientation matrix is defined as the normal direction vector ND. A right-handed orthogonal coordinate system is constructed using the rolling direction vector RD, the transverse direction vector TD, and the normal direction vector ND.
4. The EBSD orientation bi-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials as described in claim 3, characterized in that, Let the orientation matrix be: Then, its first column vector is taken as the rolling direction vector RD: Take its third column vector as the normal direction vector ND: The lateral direction vector TD can be recovered from the cross product relation: To obtain a complete right-handed orthogonal orientation base.
5. The EBSD orientation bi-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials as described in claim 4, characterized in that, The normal direction vector ND and the rolling direction vector RD together constitute the original two-vector representation: The bi-vector primitive representation is used to replace the single-direction representation in order to establish a reversible recovery path with complete orientation.
6. The EBSD orientation bi-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials as described in claim 5, characterized in that, The step of periodically encoding the normal direction vector ND and the rolling direction vector RD to obtain a six-channel periodically encoded representation includes: For any target direction vector Its azimuth is defined as And construct the corresponding three-channel periodic code: The normal direction vector ND is encoded as the first three channels, and the rolling direction vector RD is encoded as the last three channels, thus obtaining a six-channel periodic encoding representation.
7. The EBSD orientation bi-vector reversible periodic encoding method for three-dimensional reconstruction of polycrystalline materials as described in claim 6, characterized in that, The six-channel periodic encoding is represented as follows: in, The azimuth angle is the normal direction vector ND. The azimuth angle is the rolling direction vector RD.
8. The method according to any one of claims 1 to 7, characterized in that, The six-channel periodic encoding represents a three-dimensional six-channel encoding body formed by arranging its corresponding spatial coordinates. Each voxel position in the three-dimensional six-channel encoding body corresponds to a set of six-channel periodic encoding vectors.
9. The method according to claim 8, characterized in that, Multi-directional slice training data is constructed based on the three-dimensional six-channel encoder. The multi-directional slice training data is obtained by sampling two-dimensional slices of the three-dimensional six-channel encoder along at least two of the three directions XY, XZ and YZ, and is used as the input representation of the three-dimensional generative learning model.
10. An EBSD orientation-based bi-vector reversible periodic coding system for three-dimensional reconstruction of polycrystalline materials, characterized in that, include: The module comprises a data acquisition module, an orientation matrix construction module, a bi-vector extraction module, a periodic encoding module, a generative learning module, and a decoding and reconstruction module, among which: The data acquisition module is used to acquire the Euler angle parameters of each pixel or voxel in the EBSD data and their corresponding spatial coordinates. The orientation matrix construction module is used to convert the Euler angle parameters into an orientation matrix according to the crystallographic coordinate transformation relationship; The dual-vector extraction module is used to extract the normal direction vector ND and the rolling direction vector RD in the sample coordinate system from the orientation matrix to construct a dual-vector orientation representation. The periodic encoding module is used to periodically encode the normal direction vector ND and the rolling direction vector RD respectively to obtain a six-channel periodic encoding representation. The generative learning module is used to construct multi-directional slice training data based on the six-channel periodic encoding representation, and use it as the input representation of the three-dimensional generative learning model for model training and generation sampling to obtain the six-channel periodic encoding result; The decoding and reconstruction module is used to periodically decode the six-channel periodic encoding results, recover the normal direction vector ND and the rolling direction vector RD, and reconstruct the three-dimensional orientation field based on the recovered two-vector orientation representation.