A power grid equipment three-dimensional twin model slice simplification method based on visual relationship

Abstract

The application provides a kind of power grid equipment three-dimensional twin model slice simplification method based on visual relationship, belong to power grid three-dimensional visualization technical field, the method steps: the data format of power grid equipment three-dimensional model is unified and is parsed;Construct power grid equipment three-dimensional model object instantiation information;From model data, texture is compressed;Using octree structure is handled to model data slice and vertex optimization and monomer;According to octree structure, the model slice data after processing is merged, generates each level LOD;In three-dimensional network application end, according to the format requirement, the device and component instantiation of multiplexing are instantiated, load power grid equipment three-dimensional model in current window current level LOD data rendering.The application is compressed model vertex and texture data, multiplexing device and component instantiation, and load the LOD of current window, realizes the efficient transmission, loading and rendering effect of power grid equipment three-dimensional model data in the application without plug-in.

Description

Technical Field

[0001] This invention belongs to the field of power grid 3D visualization technology, specifically relating to a method for slicing and simplifying 3D twin models of power grid equipment based on visual relationships. Background Technology

[0002] LOD stands for Level of Detail, which means using different levels of detail to represent the same object in rendering. LOD technology refers to determining the allocation of rendering resources based on the position and importance of the object model's nodes in the display environment, reducing the face count and detail of less important objects, thereby achieving high-efficiency rendering computation.

[0003] With the development of digital twin technology, 3D twin models have been applied to power grid equipment to simulate its operation, diagnose operational status, predict equipment faults, and achieve operational analysis and safety control. Due to the large number of power grid devices, the corresponding 3D twin models have extremely high data density. These dense and complex models place high demands on computer storage capacity and processing speed, becoming a bottleneck for real-time rendering and network transmission. Therefore, it is necessary to simplify the 3D twin models of power grid equipment.

[0004] In the application of 3D twin models of power grid equipment, two common simplification methods are used: one is to simply slice the 3D twin model and construct a Level of Detail (LOD); the other is to use professional graphics workstations to significantly improve computer hardware configuration and enhance rendering and application efficiency. However, these two simplification methods still result in slow loading, low transmission and rendering efficiency of the 3D twin model of power grid equipment, failing to meet the application requirements of digital twin scenarios for power grid equipment.

[0005] This is a shortcoming of the existing technology. Therefore, it is necessary to provide a method for slicing and simplifying the three-dimensional twin model of power grid equipment based on visual relationships, in order to address the above-mentioned defects in the existing technology. Summary of the Invention

[0006] To address the shortcomings of existing simplification methods for 3D twin models of power grid equipment, which suffer from slow model loading, low transmission and rendering efficiency and cannot meet the application requirements of digital twin scenarios for power grid equipment, this invention provides a slicing simplification method for 3D twin models of power grid equipment based on visual relationships to solve the above-mentioned technical problems.

[0007] This invention provides a method for slicing 3D twin models of power grid equipment based on visual relationships, comprising the following steps:

[0008] S 1. Convert the format of the 3D model of the power grid equipment into a pre-defined standard format, and parse the 3D model of the power grid equipment in the standard format to obtain model data;

[0009] S2. Automatically construct image object instantiation information of the same model of equipment and components for the 3D model of power grid equipment based on model data;

[0010] S3. Read texture data from the model data and compress the size and number of texture images in the texture data using a texture merging algorithm;

[0011] S4. Use an octree structure to slice the model data, and then perform vertex optimization and slice individualization on the sliced ​​model data;

[0012] S 5. Based on the preset LOD simplification parameters, merge the processed model slice data according to the octree structure, reconstruct the vertices and perform individual identification to generate LOD at each level, and output the LOD data of the three-dimensional model of the power grid equipment;

[0013] S6. In the 3D network application, instantiate the reused equipment and components according to the format requirements, load the 3D model of the power grid equipment, and render the current level LOD data in the current view window.

[0014] Furthermore, the specific steps of step S1 are as follows:

[0015] S 11. Select one of the 3D model formats used as the standard format in advance;

[0016] S 12. Determine whether the data format of the 3D model of the power grid equipment is a standard format;

[0017] If so, proceed to step S14;

[0018] If not, proceed to step S13;

[0019] S 13 converts the data format of the three-dimensional model of the power grid equipment into a standard format;

[0020] S 14. Parse the standard format 3D model of power grid equipment to obtain model data. Convert commonly used 3D model formats to a unified standard format for subsequent processing; for example, commonly used formats are OBJ and FBX.

[0021] Furthermore, the specific steps of step S2 are as follows:

[0022] S21. Obtain model data for the three-dimensional model of power grid equipment;

[0023] S22. Read the first device object of the model data, and use the first device object as the positioning device object;

[0024] S23. Read each sub-object of the positioning device object sequentially;

[0025] S24. Compare and calculate whether the number of outer boxes and polygons of each sub-object are completely equal;

[0026] If so, proceed to step S25;

[0027] If not, locate the next device object and return to step S23;

[0028] S25. Record the location device object as a reused object for each sub-object in the instantiation relationship table to obtain the instantiation relationship of each sub-object of the location device;

[0029] S26. Output the instantiation relationships of all sub-objects of each device and component in the power grid equipment model. For a large number of devices and components of the same model in the power grid equipment, it automatically constructs instantiation information, realizing the instantiation of graphical objects at the component level, equipment level, and combined equipment level, solving the problems of repeated object references and repeated loading during rendering, and optimizing the amount of rendering data to the greatest extent.

[0030] Furthermore, the specific steps of step S3 are as follows:

[0031] S31. Obtain texture data from the 3D model of the power grid equipment;

[0032] S32. Locate a texture data;

[0033] S33. Determine if there are zero values ​​in the location texture data;

[0034] If so, proceed to step S34;

[0035] If not, proceed to step S35;

[0036] S34. Crop and locate all zero-value regions in the texture image corresponding to the texture data;

[0037] S35. Determine whether the texture data has been located;

[0038] If so, proceed to step S36;

[0039] If not, locate the next texture data and return to step S33;

[0040] S36. Stitch together all the texture images corresponding to the cropped texture data into texture data within a preset pixel threshold;

[0041] S 37. Recalculate the texture data coordinates, perform texture compression, and output the latest texture data for the 3D model of the power grid equipment. The 3D model of the operating power grid equipment contains a large number of texture photos. Using the intelligent texture merging algorithm in this step, texture images are merged without losing image clarity, reducing blank pixels and maximizing the compression of texture image size and quantity.

[0042] Furthermore, the specific steps of step S4 are as follows:

[0043] S41. Based on the octree structure, the spatial region objects of the three-dimensional model of power grid equipment are segmented to realize model data slicing;

[0044] S42. Merge duplicate vertices in the model slice data and recalculate the normals for the merged vertices;

[0045] S43. Assign identifiers to vertices in the model data to achieve entity slicing and individualization of equipment or components. An octree structure is used to segment spatial regions, automatically employing different slicing strategies based on the complexity of the entity. Typically, buildings and large entities use larger span slices, while equipment entities use smaller span slices. During modeling, there are many duplicate vertices; this step merges these duplicates, reducing unnecessary vertices without losing model accuracy, and recalculating normals for merged vertices. Vertex identifiers are used to individualize equipment and components, achieving slicing and individualization. After slicing each equipment or component entity, the slice vertices record the equipment or component entity identifier, enabling professional applications such as selection, visibility, and analysis of equipment or component entities.

[0046] Furthermore, the specific steps of step S41 are as follows:

[0047] SS 1. Obtain model data for the 3D model of power grid equipment;

[0048] SS 2. Read the outer box information of the 3D model and calculate the smallest cube of the outer box, which is counted as a zero-order cube;

[0049] SS 3. Using the zero-level cube as the zero-level node, divide the zero-level cube into eight quadrants, and label the eight quadrants as slice spaces in sequence;

[0050] SS4. Read the device objects from the model data and obtain the sub-objects of each device object;

[0051] SS 5. Locate a slice space, locate a device object, and locate a child object from the located device object;

[0052] SS6. Calculate the intersection relationship between the positioning sub-object and the positioning slice space, and determine whether the positioning sub-object contains the positioning slice space or intersects with the positioning slice space;

[0053] If so, proceed to step SS7;

[0054] If not, locate the next slice space and return to step SS6;

[0055] SS 7. Using the positioning slice space as the secondary space node, divide the cube corresponding to the secondary space node into eight quadrants, and mark the eight quadrants in sequence as the current level slice space;

[0056] SS8. Determine if the side length of the cube corresponding to the current slice space is less than the set length unit;

[0057] If so, proceed to step SS9;

[0058] If not, use the current level slice space as the positioning slice space and return to step SS7;

[0059] SS9. Determine if the positioned child object intersects with the current level slice space;

[0060] If so, proceed to step SS 10;

[0061] If not, proceed to step SS 11;

[0062] SS 10. Calculate the intersection edges between the current level slice space and the located sub-objects, and reconstruct new polygon data using the intersection edges and the polygons of the located sub-objects inside the current level slice space as the slice data of the current level slice space, then proceed to step SS 12;

[0063] SS 11. Use the positioned child object as the slice data for the current level slice space;

[0064] SS 12. Outputs slice data of the octree structure of the power grid equipment model.

[0065] Furthermore, the specific steps of step S42 are as follows:

[0066] SA 1. Locate a device object and locate a child object from the located device object;

[0067] SA2. Retrieves the cube in the current level slice space corresponding to the positioned sub-object;

[0068] SA3. Obtain one of the six faces of the cube in the current level slice space, overlay it with the positioned sub-object to find the intersection, and determine whether there is an intersection;

[0069] If so, proceed to step SA5;

[0070] If not, return to step SA4;

[0071] SA4. Determine whether all six faces have been compared.

[0072] If so, proceed to step SA6;

[0073] If not, locate the next face and return to step SA3;

[0074] SA5. Combine the intersecting new edges with the vertex data of the sub-objects inside the cube in the current level slice space to form a new object, thus merging the vertices;

[0075] SA6. Recalculate the normals for the merged vertices.

[0076] Furthermore, the specific steps of step S43 are as follows:

[0077] SC 1. Locate a device object;

[0078] SC2. Locate a sub-object within the location device object;

[0079] SC3. Assign singleton identifiers to the vertices of the locating sub-objects and recalculate the vertex indices;

[0080] SC4. Determine whether the sub-objects in the positioning device object have been positioned.

[0081] If so, proceed to step S5;

[0082] If not, locate the next child object and return to step SC3;

[0083] SC5. Determine if all equipment objects have been positioned.

[0084] If not, locate the next device object and return to step SC2;

[0085] If so, proceed to step SC6;

[0086] SC6. Outputs slice data of the octree structure of the entire power grid equipment model.

[0087] Furthermore, the specific steps of step S5 are as follows:

[0088] S51. Pre-set LOD simplification parameters for each level;

[0089] S52. Organize the slice data of the power grid equipment model in an octree manner, starting from the slice data of the child object corresponding to the lowest level child node, and merge the three-dimensional model data of every eight child nodes into a three-dimensional model block;

[0090] S53. Reconstruct the vertices and individual identifiers for each 3D model block to obtain slices at the corresponding LOD level;

[0091] S54. Output the LOD slicing results at each level according to the preset format. Based on the set LOD simplification parameters for each level, organize the model slices in an octree manner, starting from the smallest child node. Every 8 child nodes of 3D model data are merged into a whole 3D model block. At the same time, vertices are reconstructed and individual identifiers are created. The LOD slicing results can be output in glTF format and other common formats.

[0092] Furthermore, the specific steps of step S6 are as follows:

[0093] S61. Obtain the 3D model and instantiation relationship table of power grid equipment from the 3D network application terminal;

[0094] S62. Load device object reuse, load instantiation information for the devices and components that need to be loaded;

[0095] S63. Obtain the LOD level data of the current level within the current viewport and render it.

[0096] The beneficial effects of this invention are as follows:

[0097] The present invention provides a simplified method for slicing 3D twin models of power grid equipment based on visual relationships. This method fully optimizes and compresses the amount of vertex and texture data in the model, greatly reducing network data transmission and hardware resource consumption. Simultaneously, the instantiation of reusable equipment and components effectively reduces rendering batches in 3D network applications, improving rendering efficiency. Combined with the generation of multi-level LODs, only the current level data within the current viewport needs to be loaded during rendering, enabling smooth application of the 3D model of power grid equipment. The adoption of a device and component individualization strategy ensures the professional application of individualized slice data.

[0098] This invention enables efficient transmission, loading, and rendering of 3D model data of power grid equipment in plug-in-free applications; it preserves the hierarchical structure, geometric position information, and material texture information of the original equipment model, and has good data scheduling efficiency.

[0099] This invention provides users with a superior interactive experience, meeting their needs in power grid digital twin application scenarios. It improves upon the traditional octree construction algorithm, significantly enhancing rendering performance.

[0100] This invention outperforms traditional mature 3D slicing technology in terms of rendering efficiency and effect, data structure inheritance, and resource utilization. It has good applicability to mainstream 3D platforms and is more suitable for processing refined models of power grid equipment.

[0101] Furthermore, the design principle of this invention is reliable, the structure is simple, and it has a very wide range of application prospects.

[0102] Therefore, it is evident that the present invention has outstanding substantive features and significant progress compared with the prior art, and the beneficial effects of its implementation are also obvious. Attached Figure Description

[0103] 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, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0104] Figure 1 This is a schematic flowchart of Embodiment 1 of the present invention, which is a simplified method for slicing three-dimensional twin models of power grid equipment based on visual relationships.

[0105] Figure 2 This is a schematic diagram of the second embodiment of the present invention, which is a simplified method for slicing three-dimensional twin models of power grid equipment based on visual relationships.

[0106] Figure 3 This is a schematic diagram of the second embodiment of the present invention, which is a simplified method for slicing three-dimensional twin models of power grid equipment based on visual relationships.

[0107] Figure 4 This is a schematic diagram of the process of data slicing of a three-dimensional model of power grid equipment based on an octree structure according to the present invention. Detailed Implementation

[0108] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0109] Example 1:

[0110] like Figure 1 As shown, this invention provides a method for slicing 3D twin models of power grid equipment based on visual relationships, comprising the following steps:

[0111] S 1. Convert the format of the 3D model of the power grid equipment into a pre-defined standard format, and parse the 3D model of the power grid equipment in the standard format to obtain model data;

[0112] S2. Automatically construct image object instantiation information of the same model of equipment and components for the 3D model of power grid equipment based on model data;

[0113] S3. Read texture data from the model data and compress the size and number of texture images in the texture data using a texture merging algorithm;

[0114] S4. Use an octree structure to slice the model data, and then perform vertex optimization and slice individualization on the sliced ​​model data;

[0115] S 5. Based on the preset LOD simplification parameters, merge the processed model slice data according to the octree structure, reconstruct the vertices and perform individual identification to generate LOD at each level, and output the LOD data of the three-dimensional model of the power grid equipment;

[0116] S6. In the 3D network application, instantiate the reused equipment and components according to the format requirements, load the 3D model of the power grid equipment, and render the current level LOD data in the current view window.

[0117] Example 2:

[0118] like Figure 2 and Figure 3 As shown, this invention provides a method for slicing 3D twin models of power grid equipment based on visual relationships, comprising the following steps:

[0119] S1. Convert the format of the 3D model of the power grid equipment into a pre-defined standard format, and parse the standard format 3D model of the power grid equipment to obtain model data; the specific steps of step S1 are as follows:

[0120] S 11. Select one of the 3D model formats used as the standard format in advance;

[0121] S 12. Determine whether the data format of the 3D model of the power grid equipment is a standard format;

[0122] If so, proceed to step S14;

[0123] If not, proceed to step S13;

[0124] S 13 converts the data format of the three-dimensional model of the power grid equipment into a standard format;

[0125] S 14. Analyze the standard format 3D model of power grid equipment to obtain model data;

[0126] S2. Automatically construct image object instantiation information for the same type of equipment and components based on the model data for the 3D model of the power grid equipment; the specific steps of step S2 are as follows:

[0127] S21. Obtain model data for the three-dimensional model of power grid equipment;

[0128] S22. Read the first device object of the model data, and use the first device object as the positioning device object;

[0129] S23. Read each sub-object of the positioning device object sequentially;

[0130] S24. Compare and calculate whether the number of outer boxes and polygons of each sub-object are completely equal;

[0131] If so, proceed to step S25;

[0132] If not, locate the next device object and return to step S23;

[0133] S25. Record the location device object as a reused object for each sub-object in the instantiation relationship table to obtain the instantiation relationship of each sub-object of the location device;

[0134] S26. Output the instantiation relationships of all sub-objects of each device and component in the power grid equipment model;

[0135] S3. Read texture data from the model data, and compress the size and number of texture images in the texture data using a texture merging algorithm; the specific steps of step S3 are as follows:

[0136] S31. Obtain texture data from the 3D model of the power grid equipment;

[0137] S32. Locate a texture data;

[0138] S33. Determine if there are zero values ​​in the location texture data;

[0139] If so, proceed to step S34;

[0140] If not, proceed to step S35;

[0141] S34. Crop and locate all zero-value regions in the texture image corresponding to the texture data;

[0142] S35. Determine whether the texture data has been located;

[0143] If so, proceed to step S36;

[0144] If not, locate the next texture data and return to step S33;

[0145] S36. Stitch together all the texture images corresponding to the cropped texture data into texture data within a preset pixel threshold;

[0146] S37. Recalculate the texture data coordinates, perform texture compression, and output the latest texture data of the 3D model of the power grid equipment;

[0147] S4. Slice the model data using an octree structure, and then perform vertex optimization and slice individualization on the sliced ​​data; the specific steps of step S4 are as follows:

[0148] S41. Based on the octree structure, the spatial region objects of the three-dimensional model of power grid equipment are segmented to realize model data slicing;

[0149] like Figure 4 As shown, the specific steps of step S41 are as follows:

[0150] SS 1. Obtain model data for the 3D model of power grid equipment;

[0151] SS 2. Read the outer box information of the 3D model and calculate the smallest cube of the outer box, which is counted as a zero-order cube;

[0152] SS 3. Using the zero-level cube as the zero-level node, divide the zero-level cube into eight quadrants, and label the eight quadrants as slice spaces in sequence;

[0153] SS4. Read the device objects from the model data and obtain the sub-objects of each device object;

[0154] SS 5. Locate a slice space, locate a device object, and locate a child object from the located device object;

[0155] SS6. Calculate the intersection relationship between the positioning sub-object and the positioning slice space, and determine whether the positioning sub-object contains the positioning slice space or intersects with the positioning slice space;

[0156] If so, proceed to step SS7;

[0157] If not, locate the next slice space and return to step SS6;

[0158] SS 7. Using the positioning slice space as the secondary space node, divide the cube corresponding to the secondary space node into eight quadrants, and mark the eight quadrants in sequence as the current level slice space;

[0159] SS8. Determine if the side length of the cube corresponding to the current slice space is less than the set length unit;

[0160] If so, proceed to step SS9;

[0161] If not, use the current level slice space as the positioning slice space and return to step SS7;

[0162] SS9. Determine if the positioned child object intersects with the current level slice space;

[0163] If so, proceed to step SS 10;

[0164] If not, proceed to step SS 11;

[0165] SS 10. Calculate the intersection edges between the current level slice space and the located sub-objects, and reconstruct new polygon data using the intersection edges and the polygons of the located sub-objects inside the current level slice space as the slice data of the current level slice space, then proceed to step SS 12;

[0166] SS 11. Use the positioned child object as the slice data for the current level slice space;

[0167] SS 12. Outputs octree-structured slice data of the power grid equipment model;

[0168] S42. Merge duplicate vertices in the model slice data and recalculate the normals for the merged vertices; the specific steps of step S42 are as follows:

[0169] SA 1. Locate a device object and locate a child object from the located device object;

[0170] SA2. Retrieves the cube in the current level slice space corresponding to the positioned sub-object;

[0171] SA3. Obtain one of the six faces of the cube in the current level slice space, overlay it with the positioned sub-object to find the intersection, and determine whether there is an intersection;

[0172] If so, proceed to step SA5;

[0173] If not, return to step SA4;

[0174] SA4. Determine whether all six faces have been compared.

[0175] If so, proceed to step SA6;

[0176] If not, locate the next face and return to step SA3;

[0177] SA5. Combine the intersecting new edges with the vertex data of the sub-objects inside the cube in the current level slice space to form a new object, thus merging the vertices;

[0178] SA6. Recalculate the normals for merged vertices;

[0179] S43. Assign identifiers to vertices in the model data to achieve solid slicing and individualization of devices or components; the specific steps of step S43 are as follows:

[0180] SC 1. Locate a device object;

[0181] SC2. Locate a sub-object within the location device object;

[0182] SC3. Assign singleton identifiers to the vertices of the locating sub-objects and recalculate the vertex indices;

[0183] SC4. Determine whether the sub-objects in the positioning device object have been positioned.

[0184] If so, proceed to step S5;

[0185] If not, locate the next child object and return to step SC3;

[0186] SC5. Determine if all equipment objects have been positioned.

[0187] If not, locate the next device object and return to step SC2;

[0188] If so, proceed to step SC6;

[0189] SC6. Outputs slice data of the entire power grid equipment model in an octree structure;

[0190] S5. Based on the preset LOD simplification parameters, merge the processed model slice data according to the octree structure, then reconstruct the vertices and perform individual labeling to generate LODs at each level, and output the LOD data of the 3D model of the power grid equipment; the specific steps of step S5 are as follows:

[0191] S51. Pre-set LOD simplification parameters for each level;

[0192] S52. Organize the slice data of the power grid equipment model in an octree manner, starting from the slice data of the child object corresponding to the lowest level child node, and merge the three-dimensional model data of every eight child nodes into a three-dimensional model block;

[0193] S53. Reconstruct the vertices and individual identifiers for each 3D model block to obtain slices at the corresponding LOD level;

[0194] S54. Output the LOD slicing results at each level according to the preset format;

[0195] S6. Instantiate the reused equipment and components in the 3D network application according to the format requirements, and load the 3D model of the power grid equipment into the current viewport and render the current level LOD data; the specific steps of step S6 are as follows:

[0196] S61. Obtain the 3D model and instantiation relationship table of power grid equipment from the 3D network application terminal;

[0197] S62. Load device object reuse, load instantiation information for the devices and components that need to be loaded;

[0198] S63. Obtain the LOD level data of the current level within the current viewport and render it.

[0199] Through experimental comparison, the simplification method for slicing 3D twin models of power grid equipment based on visual relationships in this invention is superior to traditional mature 3D slicing techniques in terms of rendering efficiency and effect, data structure inheritance, and resource utilization. It has good applicability to mainstream 3D platforms and is more suitable for processing refined models of power grid equipment.

[0200] Although the present invention has been described in detail with reference to the accompanying drawings and preferred embodiments, the invention is not limited thereto. Various equivalent modifications or substitutions can be made to the embodiments of the invention by those skilled in the art without departing from the spirit and essence of the invention, and such modifications or substitutions should all be within the scope of the invention. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the invention should also be covered within the protection scope of the invention. Therefore, the protection scope of the invention should be determined by the scope of the claims.

Claims

1. A method for simplifying the 3D twin model of power grid equipment based on visual relationships, characterized in that, Includes the following steps: S1. Convert the format of the 3D model of the power grid equipment into a pre-defined standard format, and parse the 3D model of the power grid equipment in the standard format to obtain model data; S2. Automatically construct image object instantiation information of the same model of equipment and components for the 3D model of power grid equipment based on model data; S3. Read texture data from the model data and compress the size and number of texture images in the texture data using a texture merging algorithm; The specific steps of step S3 are as follows: S31. Obtain texture data from the 3D model of the power grid equipment; S32. Locate a texture data; S33. Determine if there are zero values ​​in the location texture data; If so, proceed to step S34; If not, proceed to step S35; S34. Crop and locate all zero-value regions in the texture image corresponding to the texture data; S35. Determine whether the texture data has been located; If so, proceed to step S36; If not, locate the next texture data and return to step S33; S36. Stitch together all the texture images corresponding to the cropped texture data into texture data within a preset pixel threshold; S37. Recalculate the texture data coordinates, perform texture compression, and output the latest texture data of the 3D model of the power grid equipment; S4. Use an octree structure to slice the model data, and then perform vertex optimization and slice individualization on the sliced ​​model data; The specific steps of step S4 are as follows: S41. Based on the octree structure, the spatial region objects of the three-dimensional model of power grid equipment are segmented to realize model data slicing; S42. Merge duplicate vertices in the model slice data and recalculate the normals for the merged vertices; S43. Assign identifiers to vertices in the model data to achieve solid slicing and individualization of devices or components; S5. Based on the preset LOD simplification parameters, merge the processed model slice data according to the octree structure, reconstruct the vertices and perform individual identification to generate LOD at each level, and output the LOD data of the three-dimensional model of the power grid equipment; S6. In the 3D network application, instantiate the reused equipment and components according to the format requirements, load the 3D model of the power grid equipment, and render the current level LOD data in the current view window.

2. The method for slicing and simplifying 3D twin models of power grid equipment based on visual relationships as described in claim 1, characterized in that, The specific steps of step S1 are as follows: S11. Pre-select one of the 3D model formats used as the standard format; S12. Determine whether the data format of the 3D model of the power grid equipment is a standard format; If so, proceed to step S14; If not, proceed to step S13; S13 converts the data format of the 3D model of power grid equipment into a standard format; S14. Analyze the standard format 3D model of power grid equipment to obtain model data.

3. The method for slicing and simplifying 3D twin models of power grid equipment based on visual relationships as described in claim 2, characterized in that, The specific steps of step S2 are as follows: S21. Obtain model data for the three-dimensional model of power grid equipment; S22. Read the first device object of the model data, and use the first device object as the positioning device object; S23. Read each sub-object of the positioning device object sequentially; S24. Compare and calculate whether the number of outer boxes and polygons of each sub-object are completely equal; If so, proceed to step S25; If not, locate the next device object and return to step S23; S25. Record the location device object as a reused object for each sub-object in the instantiation relationship table to obtain the instantiation relationship of each sub-object of the location device; S26. Output the instantiation relationships of all sub-objects of each device and component in the power grid equipment model.

4. The method for slicing and simplifying 3D twin models of power grid equipment based on visual relationships as described in claim 3, characterized in that, The specific steps of step S41 are as follows: SS1. Obtain model data for the 3D model of power grid equipment; SS2. Read the bounding box information of the 3D model and calculate the smallest cube within the bounding box, classifying it as a zero-order cube; SS3. Using the zero-level cube as the zero-level node, divide the zero-level cube into eight quadrants, and label the eight quadrants as slice spaces in sequence; SS4. Read the device objects from the model data and obtain the sub-objects of each device object; SS5. Locate a slice space, locate a device object, and locate a child object from the located device object; SS6. Calculate the intersection relationship between the positioning sub-object and the positioning slice space, and determine whether the positioning sub-object contains the positioning slice space or intersects with the positioning slice space; If so, proceed to step SS7; If not, locate the next slice space and return to step SS6; SS7. Using the positioning slice space as the secondary space node, divide the cube corresponding to the secondary space node into eight quadrants, and mark the eight quadrants in sequence as the current level slice space; SS8. Determine if the side length of the cube corresponding to the current slice space is less than the set length unit; If so, proceed to step SS9; If not, use the current level slice space as the positioning slice space and return to step SS7; SS9. Determine if the positioned child object intersects with the current level slice space; If so, proceed to step SS10; If not, proceed to step SS11; SS10. Calculate the intersection edges between the current level slice space and the located sub-objects, and reconstruct new polygon data using the intersection edges and the polygons of the located sub-objects inside the current level slice space as the slice data of the current level slice space, then proceed to step SS12; SS11. Use the positioned child object as the slice data for the current level slice space; SS12. Outputs slice data of the octree structure of the power grid equipment model.

5. The method for slicing and simplifying 3D twin models of power grid equipment based on visual relationships as described in claim 4, characterized in that, The specific steps of step S42 are as follows: SA1. Locate a device object and then locate a child object from the located device object; SA2. Retrieves the cube in the current level slice space corresponding to the positioned sub-object; SA3. Obtain one of the six faces of the cube in the current level slice space, overlay it with the positioned sub-object to find the intersection, and determine whether there is an intersection; If so, proceed to step SA5; If not, return to step SA4; SA4. Determine whether all six faces have been compared. If so, proceed to step SA6; If not, locate the next face and return to step SA3; SA5. Combine the intersecting new edges with the vertex data of the sub-objects inside the cube in the current level slice space to form a new object, thus merging the vertices; SA6. Recalculate the normals for merged vertices.

6. The method for slicing and simplifying 3D twin models of power grid equipment based on visual relationships as described in claim 5, characterized in that, The specific steps of step S43 are as follows: SC1. Locate a device object; SC2. Locate a sub-object within the location device object; SC3. Assign singleton identifiers to the vertices of the locating sub-objects and recalculate the vertex indices; SC4. Determine whether the sub-objects in the positioning device object have been positioned. If so, proceed to step S5; If not, locate the next child object and return to step SC3; SC5. Determine if all equipment objects have been positioned. If not, locate the next device object and return to step SC2; If so, proceed to step SC6; SC6. Outputs slice data of the octree structure of the entire power grid equipment model.

7. The method for slicing and simplifying 3D twin models of power grid equipment based on visual relationships as described in claim 1, characterized in that, The specific steps of step S5 are as follows: S51. Pre-set LOD simplification parameters for each level; S52. Organize the slice data of the power grid equipment model in an octree manner, starting from the slice data of the child object corresponding to the lowest level child node, and merge the three-dimensional model data of every eight child nodes into a three-dimensional model block; S53. Reconstruct the vertices and individual identifiers for each 3D model block to obtain slices at the corresponding LOD level; S54. Output the LOD slice results at each level according to the preset format.

8. The method for slicing and simplifying 3D twin models of power grid equipment based on visual relationships as described in claim 1, characterized in that, The specific steps of step S6 are as follows: S61. Obtain the 3D model and instantiation relationship table of power grid equipment from the 3D network application terminal; S62. Load device object reuse, load instantiation information for the devices and components that need to be loaded; S63. Obtain the LOD level data of the current level within the current viewport and render it.

Images