A method and system for generating a pipe network map with assistance

Abstract

The application provides a kind of pipe network map auxiliary generation method and system, it is related to pipe network information management technical field, the method comprises: obtaining the unique ID number, central coordinate and attitude angle of pipe fitting electronic identification;Attribute characteristics are obtained by analyzing ID number;Match three-dimensional legend and obtain three-dimensional pipe fitting model with port coordinate by spatial transformation;The comprehensive matching confidence between ports is calculated and topological connection is carried out, and the pipe network topology is obtained;With ID number as index, the whole life cycle information is associated, and the pipe network map with semantic information is generated.The application realizes the automatic construction of pipe network map, improves the efficiency and accuracy of mapping, and provides visual information support for the operation and maintenance of pipe network.

Description

Technical Field

[0001] This invention relates to the field of pipeline network information management technology, and in particular to a pipeline network map-assisted generation method and system. Background Technology

[0002] Plastic pipe fittings (such as straight fittings, elbows, and tees) are essential components for pipe connections and are widely used in water supply, gas, and drainage networks. Traditionally, pipe fittings were used only as connection joints and did not possess detectability or identification functions. With the development of Internet of Things (IoT) technology, passive wireless RFID tags have been attempted for use in pipelines, but they typically only store a small amount of static information (such as burial depth and coordinates), and are mostly attached to the outer wall of the pipe, making them easily damaged and with limited reading distance.

[0003] While existing technologies integrate electronic tags with non-metallic pipes, they remain at a rudimentary level, using tags as information storage carriers and failing to fully leverage the topological value of pipe fittings as key nodes in the pipeline network. In terms of generating pipeline network GIS maps, current methods primarily rely on manual measurement and drawing, which is inefficient, error-prone, and unable to automatically construct a complete pipeline network topology from discrete pipe fitting coordinates. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method and system for auxiliary generation of pipeline network maps.

[0005] The first aspect of the present invention provides a pipeline network map-assisted generation method, comprising: obtaining the unique ID number of an electronic identifier on a pipe fitting, the center coordinates of the pipe fitting, and the attitude angle of the pipe fitting; The unique ID number is split and parsed to obtain the attribute characteristics of the pipe fitting, which include at least the pipe network type and the pipe fitting type; The corresponding 3D legend is matched according to the attribute features, and the 3D legend is spatially transformed according to the center coordinates and the attitude angle to obtain a 3D pipe model with port coordinates; Using the port coordinates of the three-dimensional pipe fitting model as nodes, the comprehensive matching confidence between different ports is calculated, and the topology connection processing of multiple three-dimensional pipe fitting models is performed according to the comprehensive matching confidence and connection rules to obtain the pipe network topology. Using the unique ID number as an index, the pipeline network topology is associated with the full lifecycle information in the database to generate a pipeline network map with semantic information.

[0006] Furthermore, before parsing the unique ID number, the process also includes: The unique ID number is verified using a CRC check algorithm. If the verification fails, the fitting is marked as abnormal data and excluded from subsequent processing.

[0007] Furthermore, matching the corresponding 3D legend based on the attribute features specifically includes: Based on the network type and fitting type in the attribute features, match the corresponding 3D legend and color style from the preset 3D legend library; If a match fails, a generic 3D legend will be automatically generated, and the attribute feature will be stored in the legend library update queue.

[0008] Furthermore, based on the center coordinates and the attitude angle, the three-dimensional legend is subjected to spatial transformation processing to obtain a three-dimensional pipe fitting model with port coordinates, specifically including: Obtain the local port coordinates corresponding to the pipe fitting type; Construct a spatial rotation matrix based on the attitude angle; The port's local coordinates are transformed using the spatial rotation matrix and superimposed with the center coordinates to obtain the port's world coordinates; The 3D illustration is translated to the center coordinates and rotated to the attitude angle to obtain a 3D pipe fitting model with port world coordinates.

[0009] Furthermore, the overall matching confidence between different ports is calculated, specifically including: Calculate the overall matching confidence between different ports based on at least one of the following factors: port distance, port direction collinearity, and port elevation difference. Port pairs with a comprehensive matching confidence score greater than a preset threshold are selected as candidate connections; A global optimization matching algorithm is used to allocate the candidate connections, so that each port is allocated at most one connection; Based on the allocation results, connecting pipe segments are generated to obtain the pipeline network topology.

[0010] Furthermore, after generating the pipeline network map with semantic information, a correction step is also included: Obtain the coordinates of the construction drawing nodes, and calculate the deviation between the coordinates of the pipe fitting nodes in the pipeline network map and the coordinates of the construction drawing nodes. When the deviation exceeds a preset threshold, the corresponding node is marked as a node with abnormal position, and a correction interface is provided. In response to the correction command, the node coordinates of the pipe fitting are updated, and the connection lines of adjacent pipe segments are regenerated based on the updated node coordinates. For pipe sections with natural bends, a curve fitting algorithm is used to generate a bend centerline to replace the original straight pipe section and update the pipe network map.

[0011] A second aspect of the present invention provides a pipeline network map-assisted generation system, comprising: The data acquisition module is used to acquire the unique ID number of the electronic identification on the pipe fitting, the center coordinates of the pipe fitting, and the attitude angle of the pipe fitting; The ID parsing module is used to split and parse the unique ID number to obtain the attribute characteristics of the pipe fitting. The attribute characteristics include at least the pipe network type and the pipe fitting type. The model generation module is used to match the corresponding 3D legend according to the attribute features, and to perform spatial transformation processing on the 3D legend according to the center coordinates and the attitude angle to obtain a 3D pipe model with port coordinates. The topology connectivity module is used to calculate the comprehensive matching confidence between different ports using the port coordinates of the three-dimensional pipe fitting model as nodes, and to perform topology connectivity processing on multiple three-dimensional pipe fitting models according to the comprehensive matching confidence and connectivity rules to obtain the pipe network topology structure. The map generation module is used to associate the pipeline network topology with the full life cycle information in the database using the unique ID number as an index, and generate a pipeline network map with semantic information.

[0012] A third aspect of the present invention provides an electronic device including a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps in the pipeline map-assisted generation method as described in the first aspect of the present invention.

[0013] A fourth aspect of the present invention provides a computer-readable storage medium having a program stored thereon that, when executed by a processor, implements the steps of the pipeline map-assisted generation method as described in the first aspect of the present invention.

[0014] A fifth aspect of the present invention provides a computer program product comprising software code, wherein the program in the software code performs the steps of the pipeline map-assisted generation method as described in the first aspect of the present invention.

[0015] Compared with existing technologies, the present invention provides a pipeline network map auxiliary generation method and system, which realizes the automated construction of pipeline network maps carrying business data from discrete pipe fitting data. It no longer relies on manual drawing, but instead utilizes the irreplaceable nature of the pipe fittings as key nodes of the pipeline network, integrating geometric information, spatial orientation and engineering management data, which significantly improves the generation efficiency and location accuracy of pipeline network maps, and provides visualized information support for the operation and maintenance of pipeline networks. Attached Figure Description

[0016] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0017] Figure 1 This is a flowchart of the pipeline map auxiliary generation method provided in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the structure of the tube with electronic identification provided in Embodiment 1 of the present invention; Figure 3 This is a top view of a cap with an electronically marked tube provided in Embodiment 1 of the present invention; Figure 4 This is an architecture diagram of the pipeline map auxiliary generation system provided in Embodiment 2 of the present invention. Detailed Implementation

[0018] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form as well. Furthermore, it should be understood that the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0020] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0021] All data acquisition in this embodiment is carried out in accordance with laws and regulations and with user consent, and the data is used legally.

[0022] Example 1 like Figure 1 This embodiment provides a method for auxiliary generation of pipeline network maps, including: S1. Obtain the unique ID number of the electronic identification on the pipe fitting, the center coordinates of the pipe fitting, and the attitude angle of the pipe fitting.

[0023] like Figure 2 and Figure 3As shown, the pipe fittings involved in this step include: the main pipe fitting 1, made of any one of PE, PVC, PP, PA, PVDF, or POK, and of any one of the following types: straight, sleeve, tee, multi-way, elbow, or reducer. An electronic tag 3 is installed inside the pipe fitting. This electronic tag uses passive radio frequency identification (RFID) reading, has a unique ID number, and can store a small amount of information (such as burial depth, coordinates, diameter, laying date, construction unit, etc.). The electronic tag 3 is placed at installation point 2, which is made of the same material as the pipe fitting and protrudes from the pressure-bearing main body of the pipe fitting. The electronic tag 3 is placed inside the cavity of installation point 2. Antifreeze 5 can be added to the cavity according to the leveling requirements of the electronic tag or the customer's precision requirements to achieve a self-leveling effect; antifreeze can also be omitted depending on actual needs. A sealing groove is provided above installation point 2 for placing a matching rubber ring 4, and it has external threads for connecting with the cap 6. After the cap 6 is tightened, it compresses the rubber ring 4 to form a sealing structure. The cap 6 is made of the same material as the pipe fitting and has an internal thread that connects to the external thread of the installation point 2. The cap 6 is equipped with a level 7, which can be used to correct and adjust the horizontality of the pipe fitting installation.

[0024] Specifically, in this step, the unique ID number of the electronic tag inside the pipe fitting is obtained through an RFID reader / writer; the center coordinates of the pipe fitting are collected through an RTK device. Read the attitude angles, including the horizontal tilt angle, from the level on the pipe fitting cap. and azimuth .

[0025] The unique ID number is constructed according to a predefined encoding rule, and its format is: ID=C1C2C3C4C5C6+T1T2+M1M2+D1D2D3D4+K1K2+S1S2S3S4S5S6S7S8.

[0026] Wherein: C1-C6 are city codes, T1-T2 are pipeline type codes (01 water supply, 02 gas, 03 drainage, 04 heating), M1-M2 are pipe material codes, D1-D4 are nominal diameter codes, K1-K2 are pipe fitting type codes (tees, crosses, straights, elbows, reducers, plugs, flanges, and inlet fittings, etc.), and S1-S8 are production serial numbers.

[0027] S2. The unique ID number is split and parsed to obtain the attribute characteristics of the pipe fitting. The attribute characteristics include at least the pipe network type and the pipe fitting type.

[0028] According to the predefined encoding rules described in S1, the ID string is split to obtain the structured attribute feature set Attr = {city code, pipeline type T, pipe material, nominal diameter, fitting type K, production serial number}.

[0029] Before parsing the unique ID number, a verification step is included: the ID number is verified for integrity using the CRC-16 check algorithm, and the verification formula is: ; in, The generator polynomial is based on the first 24 bits of the basic encoding. If the calculated check value does not match the last two digits of the ID, the fitting is marked as abnormal data and excluded from subsequent processing.

[0030] S3. Match the corresponding 3D legend according to the attribute features, and perform spatial transformation processing on the 3D legend according to the center coordinates and the attitude angle to obtain a 3D pipe model with port coordinates.

[0031] S3.1 Matching the corresponding 3D legend based on the attribute features, specifically including: Based on the network type T and fitting type K in the attribute characteristics, match the corresponding 3D legend and color style from the preset 3D legend library. Establish a 3D legend library index table, using a hash mapping method to store the correspondence between attributes and legends: ; in, Provide corresponding 3D model illustrations. Simultaneously, establish a color style mapping table to assign different visualization colors based on the pipeline network type: ; If there is no corresponding legend in the legend library If so, a general 3D legend will be automatically generated, and the attribute combination will be marked as an item to be supplemented and stored in the legend library update queue.

[0032] S3.2. Perform spatial transformation processing on the three-dimensional legend based on the center coordinates and the attitude angle to obtain a three-dimensional pipe fitting model with port coordinates, specifically including: Based on the pipe fitting type K, obtain the number N of ports for that type of pipe fitting and the local coordinates of each port relative to the center of the pipe fitting from the predefined parameter library. .

[0033] According to attitude angle Construct the spatial rotation matrix R: ; Calculate the world coordinates of each port: ; Translate the 3D legend to the center coordinates. And rotate to attitude angle A 3D pipe fitting model with port world coordinates is obtained. Thus, a three-dimensional pipe fitting model with port coordinates is obtained.

[0034] S4. Using the port coordinates of the three-dimensional pipe fitting model as nodes, calculate the comprehensive matching confidence between different ports, and perform topological connection processing on multiple three-dimensional pipe fitting models according to the comprehensive matching confidence and connection rules to obtain the pipe network topology.

[0035] S4.1. Establish the port distance matrix and port vector field. Define the spatial state of the pipe fitting: including not only the center coordinates. It also includes a set of port vectors determined according to the fitting type. , where the port vector represents the direction of the port.

[0036] S4.2 Calculate the overall matching confidence between different ports. In one implementation, the following evaluation function is used, comprehensively considering three constraints: distance, pipe diameter, and pipe network type: ; in: , , These are the weighting coefficients; Let be the port distance matrix, where, For the first The first pipe fitting The port and the first The first pipe fitting Euclidean distance between ports: ; The maximum allowable connection distance is preset (default value is 1.5 times the nominal diameter); The function is the Kronecker function, which takes the value 1 when a=b and 0 otherwise. For the nominal diameter of the two ports, This is a network type with two ports.

[0037] when When it is determined that two ports can be connected, a pipe segment is generated to connect the two ports; at the same time, the connection rule verification is performed: blocking pipe fittings are only allowed to be connected to 1 port; inlet pipe fittings are the termination node of the pipeline network and are not allowed to extend backward; each port is only allowed to be connected once.

[0038] In another implementation, a comprehensive matching confidence calculation formula based on port vector field similarity is used: ; in, The Euclidean distance between the centers of the two ports. The first term is the distance attenuation coefficient; the second term is the port vector collinearity constraint, which calculates the absolute value of the cosine of the angle between the direction vectors of the two ports. Theoretically, the direction vectors connecting the ports should be collinear in opposite directions (the dot product should be close to -1). This constraint can effectively eliminate incorrect connections with mismatched directions; the third term is the elevation continuity constraint. The difference in elevation between the two ports. Elevation attenuation coefficient; It is a weighting factor, and satisfies .

[0039] S4.3. Port pairs with a comprehensive matching confidence score greater than a preset threshold are selected as candidate connections. A global optimization matching algorithm (such as the Hungarian algorithm) is used to allocate the candidate connections, ensuring that each port is assigned at most one connection, thus avoiding "one-to-many" topology conflicts.

[0040] S4.4 Generate connecting pipe segments based on the allocation results. For rigid pipes, generate straight connecting pipe segments; for flexible pipes, when the port distance is greater than the rigid connection threshold, use a cubic Bézier curve interpolation algorithm to automatically generate smooth arc-shaped pipe segments.

[0041] Based on the above rules, the pipeline topology containing pipe fitting nodes and pipe segments is obtained.

[0042] S5. Using the unique ID number as an index, associate the pipeline network topology with the full lifecycle information in the database to generate a pipeline network map with semantic information.

[0043] Specifically, using the unique ID number of the electronic identification of the pipe fitting as an index, a mapping between the 3D model and an external database is established. The external database stores full lifecycle information, which includes: Construction management information: connection type, welding process, welding parameters, construction node pictures, supervision unit, construction unit, general contractor, design unit, connector type, embedment depth, construction date, acceptance records, etc. Product traceability information: pipe model, pipe material, technical requirements, connector material, product batch, manufacturer, product testing report, product acceptance report, production date, test witness report, etc.; Operation and maintenance management information: repair records, replacement records, inspection records, incident reports, etc.

[0044] Using the electronic identifier (ID) as the unique primary key, establish a mapping between the 3D model and the database: ; in, It includes the aforementioned full lifecycle data. In the GIS map interactive interface, mouse hover and click event responses are implemented: when the mouse hovers over a pipe fitting or pipe segment, the basic attributes of the associated ID are automatically parsed, and a pop-up window displays information such as pipe network type, diameter, pipe material, and installation date; when the mouse clicks on a pipe fitting, it jumps to the details page corresponding to that ID, displaying complete full lifecycle data.

[0045] At this point, a 3D GIS map of the pipeline network with full lifecycle semantic information is generated.

[0046] Preferably, after generating the pipeline network map with semantic information, the following correction steps may be included to further improve map accuracy: S6.1 For each straight pipe segment, extract the port coordinates of the fittings at both ends. and Generate the initial straight centerline If the length of the pipe section exceeds a preset threshold... (Default value is 20m), then select at equal intervals along the centerline. sampling points Calculate the distance from each sampling point to the initial line. vertical distance Standard deviation of statistical distance : ; in, This is the average distance. When ( When the pipe diameter is (not specified), the pipe section is determined to have a natural bend and marked as a bend section to be corrected.

[0047] S6.2 Obtain the coordinates of the construction drawing nodes, convert the coordinates of the pipe fitting nodes in the construction drawing to the same coordinate system as the GIS map, and generate a construction drawing node set. Calculate the coordinates of the generated pipe fitting nodes. Coordinates of corresponding construction drawing nodes Deviation: ; when When this happens, the node is marked as an abnormal node, a correction prompt box pops up, and the node position can be manually adjusted by dragging and dropping; after adjustment, the centerline of the adjacent pipe section is automatically recalculated.

[0048] S6.3 For marked curved sections, manual import of the coordinates of the curved points measured on-site is supported, and the curved centerline is generated by fitting a cubic B-spline curve: ; in, For three spline basis functions These are the coordinates of the measured bending control points.

[0049] S6.4 Update the pipeline map with the corrected data.

[0050] Example 2 like Figure 4 As shown, this embodiment provides a pipeline network map-assisted generation system, including: The data acquisition module is used to acquire the unique ID number of the electronic identification on the pipe fitting, the center coordinates of the pipe fitting, and the attitude angle of the pipe fitting; The ID parsing module is used to split and parse the unique ID number to obtain the attribute characteristics of the pipe fitting. The attribute characteristics include at least the pipe network type and the pipe fitting type. The model generation module is used to match the corresponding 3D legend according to the attribute features, and to perform spatial transformation processing on the 3D legend according to the center coordinates and the attitude angle to obtain a 3D pipe model with port coordinates. The topology connectivity module is used to calculate the comprehensive matching confidence between different ports using the port coordinates of the three-dimensional pipe fitting model as nodes, and to perform topology connectivity processing on multiple three-dimensional pipe fitting models according to the comprehensive matching confidence and connectivity rules to obtain the pipe network topology structure. The map generation module is used to associate the pipeline network topology with the full life cycle information in the database using the unique ID number as an index, and generate a pipeline network map with semantic information.

[0051] Example 3 Embodiment 3 of the present invention provides an electronic device.

[0052] An electronic device includes a memory, a processor, and a program stored in the memory and running on the processor. The processor includes, but is not limited to, at least one of a central processing unit (CPU), a graphics processing unit (GPU), a neural network processor (NPU), a tensor processor (TPU), or an artificial intelligence acceleration chip. The program is used to implement the steps in the pipeline map-assisted generation method as described in Embodiment 1 of the present invention when executing the program.

[0053] The detailed steps are the same as those of the pipeline map generation method provided in Example 1, and will not be repeated here.

[0054] Example 4 Embodiment 4 of the present invention provides a computer-readable storage medium.

[0055] A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the pipeline map-assisted generation method as described in Embodiment 1 of the present invention.

[0056] The detailed steps are the same as those of the pipeline map generation method provided in Example 1, and will not be repeated here.

[0057] Example 5 Embodiment 5 of the present invention provides a computer program product.

[0058] A computer program product includes software code, wherein the program in the software code performs the steps of the pipeline map-assisted generation method as described in Embodiment 1 of the present invention.

[0059] The detailed steps are the same as those of the pipeline map generation method provided in Example 1, and will not be repeated here.

[0060] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages. For example, in one implementation, the methods and systems can be developed based on deep learning frameworks (such as TensorFlow, PyTorch, etc.) and using the Python language. Those skilled in the art will understand that other suitable programming languages ​​or tools can also be used for implementation without departing from the core ideas of the present invention.

[0061] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0062] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0063] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0064] The above description is merely a preferred embodiment of this practice and is not intended to limit the scope of this practice. Various modifications and variations can be made to this practice by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this practice should be included within the protection scope of this practice.

Claims

1. A method for generating pipeline network maps, characterized in that, include: Obtain the unique ID number of the electronic identification on the pipe fitting, the center coordinates of the pipe fitting, and the attitude angle of the pipe fitting; The unique ID number is split and parsed to obtain the attribute characteristics of the pipe fitting, which include at least the pipe network type and the pipe fitting type; The corresponding 3D legend is matched according to the attribute features, and the 3D legend is spatially transformed according to the center coordinates and the attitude angle to obtain a 3D pipe model with port coordinates; Using the port coordinates of the three-dimensional pipe fitting model as nodes, the comprehensive matching confidence between different ports is calculated, and the topology connection processing of multiple three-dimensional pipe fitting models is performed according to the comprehensive matching confidence and connection rules to obtain the pipe network topology. Using the unique ID number as an index, the pipeline network topology is associated with the full lifecycle information in the database to generate a pipeline network map with semantic information.

2. The method according to claim 1, characterized in that, Before parsing the unique ID number, the process also includes: The unique ID number is verified using a CRC check algorithm. If the verification fails, the fitting is marked as abnormal data and excluded from subsequent processing.

3. The method according to claim 1, characterized in that, Matching the corresponding 3D legend based on the attribute features specifically includes: Based on the network type and fitting type in the attribute features, match the corresponding 3D legend and color style from the preset 3D legend library; If a match fails, a generic 3D legend will be automatically generated, and the attribute feature will be stored in the legend library update queue.

4. The method according to claim 1, characterized in that, Based on the center coordinates and the attitude angle, the 3D legend is spatially transformed to obtain a 3D pipe fitting model with port coordinates, specifically including: Obtain the local port coordinates corresponding to the pipe fitting type; Construct a spatial rotation matrix based on the attitude angle; The port's local coordinates are transformed using the spatial rotation matrix and superimposed with the center coordinates to obtain the port's world coordinates; The 3D illustration is translated to the center coordinates and rotated to the attitude angle to obtain a 3D pipe fitting model with port world coordinates.

5. The method according to claim 1, characterized in that, Calculating the overall matching confidence between different ports specifically includes: Calculate the overall matching confidence between different ports based on at least one of the following factors: port distance, port direction collinearity, and port elevation difference. Port pairs with a comprehensive matching confidence score greater than a preset threshold are selected as candidate connections; A global optimization matching algorithm is used to allocate the candidate connections, so that each port is allocated at most one connection; Based on the allocation results, connecting pipe segments are generated to obtain the pipeline network topology.

6. The method according to claim 1, characterized in that, After generating the pipeline network map with semantic information, a correction step is also included: Obtain the coordinates of the construction drawing nodes, and calculate the deviation between the coordinates of the pipe fitting nodes in the pipeline network map and the coordinates of the construction drawing nodes. When the deviation exceeds a preset threshold, the corresponding node is marked as a node with abnormal position, and a correction interface is provided. In response to the correction command, the node coordinates of the pipe fitting are updated, and the connection lines of adjacent pipe segments are regenerated based on the updated node coordinates. For pipe sections with natural bends, a curve fitting algorithm is used to generate a bend centerline to replace the original straight pipe section and update the pipe network map.

7. A pipeline network map-aided generation system, characterized in that, include: The data acquisition module is used to acquire the unique ID number of the electronic identification on the pipe fitting, the center coordinates of the pipe fitting, and the attitude angle of the pipe fitting; The ID parsing module is used to split and parse the unique ID number to obtain the attribute characteristics of the pipe fitting. The attribute characteristics include at least the pipe network type and the pipe fitting type. The model generation module is used to match the corresponding 3D legend according to the attribute features, and to perform spatial transformation processing on the 3D legend according to the center coordinates and the attitude angle to obtain a 3D pipe model with port coordinates. The topology connectivity module is used to calculate the comprehensive matching confidence between different ports using the port coordinates of the three-dimensional pipe fitting model as nodes, and to perform topology connectivity processing on multiple three-dimensional pipe fitting models according to the comprehensive matching confidence and connectivity rules to obtain the pipe network topology structure. The map generation module is used to associate the pipeline network topology with the full life cycle information in the database using the unique ID number as an index, and generate a pipeline network map with semantic information.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements the steps of the pipeline map-assisted generation method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the pipeline map-assisted generation method according to any one of claims 1 to 6.

10. A computer program product, comprising software code, characterized in that, The program in the software code executes the steps of the pipeline map-assisted generation method according to any one of claims 1 to 6.

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