A municipal pipeline-oriented BIM model efficient construction method and system

Abstract

The application belongs to the field of three-dimensional applications, and particularly relates to a municipal pipeline-oriented BIM model efficient construction method and system, comprising: S1. adaptive analysis and standardized reconstruction of multi-source pipeline data; S2. pipeline turning point interpolation correction and smooth fitting based on a space vector rule; S3. adaptive matching mechanism of a complex elbow family based on multi-dimensional quadrant mapping; S4. reverse deduction and reconstruction of pipeline network auxiliary facilities under multiple spatial topological constraints, and the advantage lies in that a standardized multi-source data base is constructed through three-dimensional affine transformation and feature vector reorganization, thereby laying a solid data interface foundation for seamless access of a BIM model to a city digital twin base.

Description

Technical Field

[0001] This application belongs to the field of 3D applications, specifically involving a method and system for efficient BIM model construction for municipal pipelines. Background Technology

[0002] With the development of smart city and digital twin technologies, the high-precision construction of 3D BIM (Building Information Modeling) for municipal pipeline networks, as the underground "lifeline" of cities, has become particularly important. Currently, BIM modeling of municipal pipeline networks typically relies heavily on 2D GIS discrete data generated by geophysical exploration or surveying, such as pipe point, pipeline, and attribute table data stored in MDB format. However, existing technologies still face significant technical bottlenecks in the engineering practice of converting these massive amounts of 2D discrete graphic data into high-fidelity 3D BIM models.

[0003] Existing technologies have significant shortcomings in handling the three-dimensional spatial continuity of pipeline junctions. Current automated modeling tools generally employ a rigid generation logic based on direct end-to-end connections when dealing with topological inflection points at pipeline junctions. This approach inevitably leads to physical interpenetration between the pipeline end and the inside of the elbow after inserting a solid elbow fitting at the pipeline junction, or leaves noticeable geometric gaps between their flange faces. This rigid splicing cannot eliminate spatial geometric interference, making it difficult to achieve a smooth physical transition and seamless fit between pipelines and fittings in three-dimensional space.

[0004] Faced with complex pipeline systems exhibiting highly random spatial orientations, existing dynamic matching mechanisms for elbow components are extremely inefficient. The spatial deflection angles of municipal pipelines in underground spaces are intricately varied. Traditional modeling methods typically require manually creating large and cumbersome angle lookup tables beforehand, and then using the program to call different elbow family libraries by looking up each table or writing lengthy and inefficient conditional statements. This matching logic, based on manual prediction and hard coding, not only consumes significant computational resources but is also prone to matching errors when dealing with cross-quadrant or large deflection angle conditions, making it difficult to meet the automated, second-level assembly requirements of large-scale pipeline networks. Summary of the Invention

[0005] To address the aforementioned issues, this application provides a method and system for efficient BIM model construction for municipal pipelines, the technical solution of which is as follows:

[0006] An efficient method for constructing BIM models for municipal pipelines includes the following steps: S1. Adaptive parsing and standardized reconstruction of multi-source pipeline data; S2. Pipeline inflection point interpolation correction and smooth fitting based on spatial vector rules; S3. Adaptive matching mechanism for complex elbow families based on multi-dimensional quadrant mapping; S4. Reverse deduction and reconstruction of pipeline ancillary facilities under multiple spatial topological constraints.

[0007] Preferably, step S1 involves adaptive parsing and standardized reconstruction of multi-source pipeline data: S11. Obtain the discrete point and line data and tables of the original municipal pipelines from multiple sources and heterogeneous structures. Introduce a three-dimensional affine transformation matrix to map the discrete spatial point system with coordinate deviations to a unified absolute engineering coordinate system to achieve spatial benchmark unification. Then, iterate through and extract the original pipeline attribute tables to construct multi-dimensional parameter attribute feature vectors for each standard pipe segment. Define the original input multi-source pipeline point set as... The line set is ;

[0008] S12. Introduced the three-dimensional affine transformation matrix M trans All original discrete points Forced mapping to a unified BIM absolute engineering coordinate system to obtain standardized coordinate points. ( , , Its spatial analytic transformation process satisfies the equation: ; - Together, they constitute the elements of the third-order rotation submatrix, used to adjust and align the spatial orientation, orientation, and scale of the original pipeline data with the target BIM environment; , and These constitute the three independent components of the translation vector, representing the linear physical distance that the data needs to be translated in the X, Y, and Z axis directions, respectively. S13. After completing the spatial reference unification, further traverse the MDB attribute table for each standard pipe segment. Constructing multidimensional attribute feature vectors ,in For pipe diameter, Material coefficient, For connection method, For pipeline types, the dimensionality reduction and recombination of this feature vector achieves deep binding between geometric spatial information and non-geometric engineering attributes, completing the standardized reconstruction of the underlying data structure.

[0009] Preferably, in step S2 of the BIM modeling paradigm, the elbow fitting connecting two non-collinear pipelines is usually anchored as a topological inflection point, and an adaptive inflection point tangent interpolation correction algorithm is used to achieve a smooth three-dimensional transition between the pipeline and the elbow assembly. S21. Suppose there are two adjacent pipe segments in space. , Converging at topological inflection points Extract the absolute planar coordinates of the initial turning point and the spatial vectors of the two pipelines' orientations. and And calculate the actual angle between the two pipelines in three-dimensional space. : ; S22. The standard diameter D of the pipeline, the theoretical bending radius R of the elbow component at the node, and to ensure that the pipeline end face and the elbow flange face are absolutely tangent in three-dimensional space, a geometric tangent equation is constructed in the neighborhood of the turning point, and the required back displacement of the pipeline along the original direction vector is dynamically calculated, i.e., the tangent length. : ; Using the derived backward displacement, the original topological intersection point is... By performing bidirectional interpolation calculations, the coordinates of two corrected tangency points where the two extended pipelines are physically tangent to the outer edge of the elbow are derived, as follows: ; ; After obtaining the above tangent coordinates, the endpoints of the original connecting pipeline segment are adjusted for displacement, updated and anchored to the two geometric tangent points.

[0010] Preferably, step S3 establishes an adaptive matching mechanism for complex elbow families based on multi-dimensional quadrant mapping: Define the azimuth angles of the two connected pipelines entering the junction on the two-dimensional horizontal projection plane as follows: and Calculated using the built-in quadrant function Calculate the spatial projection quadrant values ​​of the two pipelines mentioned above. and ; Calculate the azimuth angle of the angle bisector formed by the direction vectors of the two pipelines. Similarly, the spatial projection quadrant value of the angle bisector can be obtained. ; Let the actual plane angle between the two pipelines be... A pre-established collection of three-dimensional elbow family models covering various spatial deflection patterns was created. ; Calling the multi-condition branch mapping operator Using quadrant values ​​and included angle parameters as joint input variables, the system automatically outputs matching elbow component numbers. : ; For other spatial deflection forms, the mapping operator follows the same dimensionality reduction logic and applies the corresponding rules for extended mapping.

[0011] Preferably, step S4 involves reverse engineering and reconstructing of pipeline ancillary facilities under multiple spatial topology constraints: Regarding the alignment of the foundation orientation of ground-level ancillary facilities, let the tangent direction vector of the adjacent road centerline be . The foundation orientation vector of the ancillary facilities is And introduce relative relation operators The yaw angle required for the appendage to rotate about the vertical Z-axis is determined based on spatial geometric constraints. : when When orthogonal constraints are present, the algorithm forces the solution of constraint equations based on dot products: ; when When there are parallel constraints, the algorithm forces the solution of constraint equations based on the cross product: ; The yaw angle obtained through the solution This enables spatial alignment and correction of the BIM model's posture.

[0012] Preferably, to address the deficiency of missing well bottom elevation in the original exploration data, the regional pipeline network topology is abstracted into an undirected connected graph. The node set V contains inspection wells, and the edge set E contains pipe segments; 3D coordinates of a target inspection well node with missing depth attribute , To determine the absolute surface elevation of the inspection well location, extract the set of all pipe segment edges directly topologically connected to it from the connected graph. ; Let the absolute elevation of the bottom of each connected pipe segment at the junction be... And set a bottoming margin constant that conforms to hydraulic specifications. The effective bottom elevation of the target inspection well is calculated. This allows us to determine the overall depth of the three-dimensional well. Ultimately, the automated reconstruction of the high-precision BIM model of all elements of the municipal pipeline network was completed.

[0013] A high-efficiency BIM model construction system for municipal pipelines includes an adaptive analysis and standardized reconstruction module, a pipeline turning point interpolation correction and smooth fitting module, a complex elbow family adaptive matching mechanism module, and a pipeline ancillary facilities reverse deduction and reconstruction module. Adaptive parsing and standardized reconstruction module: acquires discrete point and line data and table data of original municipal pipelines from multiple sources and heterogeneous sources, introduces a three-dimensional affine transformation matrix to map the discrete spatial point system with coordinate deviation to a unified absolute engineering coordinate system to complete the unification of spatial reference, and traverses and extracts the original attribute table of pipelines to construct attribute feature vectors of multi-dimensional parameters for each standard pipe section, thereby realizing the deep binding of geometric spatial information and non-geometric engineering attributes and the structural reconstruction of the underlying data. Pipeline bend point interpolation correction and smooth fitting module: Adopts an adaptive bend point tangent interpolation correction algorithm to solve the physical intersection and geometric gap defects caused by direct pipeline connection, and realize the three-dimensional smooth transition between pipeline and elbow assembly. Adaptive matching mechanism module for complex elbow families: Establishes an adaptive matching mechanism for complex elbow families based on multi-dimensional quadrant mapping to solve the problem of adaptively calling the corresponding type of elbow under different spatial deflection angles; Pipeline ancillary facilities reverse deduction and reconstruction module: The introduced multi-topology constraint reverse deduction technology explores the topological relationships of existing pipeline data, completes the absolute spatial orientation and underground depth parameters of ancillary facilities, so that the final model fully matches the real physical engineering environment in terms of spatial attitude and hydraulic elevation logic.

[0014] Preferably, a standardized multi-source data base is constructed through three-dimensional affine transformation and feature vector recombination, providing a data interface foundation for the later integration of the BIM model into the urban digital twin base.

[0015] Compared with the prior art, the beneficial effects of this application are as follows: (1) This invention completely eliminates the defects of solid mold penetration and flange surface gap caused by traditional direct connection of endpoints from the underlying geometric algorithm through the tangent interpolation correction mechanism, which greatly improves the appearance quality and geometric accuracy of the pipeline intersection node model.

[0016] (2) This invention abandons the computationally intensive manual table lookup logic and constructs a pure mathematical multidimensional quadrant mapping operator that can instantly transform the complex pipeline deflection shape into a definite component index, realizing automatic assembly of irregular pipe fittings in seconds with zero error rate, which greatly improves the overall modeling efficiency.

[0017] (3) The multi-topology constraint inverse deduction technology introduced in this invention can fully explore the topological relationships of existing pipeline data, accurately complete the absolute spatial orientation and underground depth parameters of ancillary facilities, and make the final model completely fit the real physical engineering environment in terms of spatial attitude and hydraulic elevation logic. A standardized multi-source data base is constructed through three-dimensional affine transformation and feature vector recombination, which lays a solid data interface foundation for the seamless integration of the BIM model into the urban digital twin base in the later stage. Attached Figure Description

[0018] Figure 1 For flowcharts; Figure 2 Diagram of interpolation correction geometry for inflection points; Figure 3 A logic diagram for multidimensional octet mapping of elbow space; Figure 4 This is a schematic diagram illustrating the reverse calculation of the depth of the inspection well. Detailed Implementation

[0019] 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 drawings can be obtained based on these drawings without creative effort.

[0020] An efficient method for constructing BIM models for municipal pipelines includes:

[0021] (1) Adaptive parsing and standardized reconstruction of multi-source pipeline data: First, the discrete point and line data and table data of the original municipal pipelines from multiple heterogeneous sources are obtained. A three-dimensional affine transformation matrix is ​​introduced to map the discrete spatial point system with coordinate deviations to a unified absolute engineering coordinate system to achieve spatial benchmark unification. Then, the original attribute table of the pipeline is extracted and attribute feature vectors containing multi-dimensional parameters such as pipe diameter, material coefficient and connection method are constructed for each standard pipe section. This achieves deep binding of geometric spatial information and non-geometric engineering attributes and structural reconstruction of the underlying data.

[0022] Define the multi-source pipeline point set of the original input as The line set is To address potential coordinate system biases during heterogeneous data acquisition, the system's underlying layer introduces a three-dimensional affine transformation matrix M. trans All original discrete points Forced mapping to a unified BIM absolute engineering coordinate system to obtain standardized coordinate points. Its spatial analytic transformation process satisfies the equation: ; to Together, these elements constitute the third-order rotation submatrix, used to adjust and align the spatial orientation, orientation, and scale of the original pipeline data with the target BIM environment. , and These constitute the three independent components of the translation vector, representing the linear physical distance that the data needs to be translated along the X, Y, and Z axes, respectively.

[0023] After unifying the spatial reference, the MDB attribute table is further traversed for each standard pipe segment. Constructing multidimensional attribute feature vectors ,in For pipe diameter, Material coefficient, For connection method, This refers to the pipeline type. Through dimensionality reduction and recombination of this feature vector, the system achieves deep binding between geometric spatial information and non-geometric engineering attributes, completing the standardized reconstruction of the underlying data structure. This provides high-precision, attribute-complete underlying data support for subsequent pipeline entity generation and pipeline network topology deduction.

[0024] (2) Pipeline inflection point interpolation correction and smooth fitting based on spatial vector rules: After obtaining the high-precision standardized pipeline data output in step (1), the main framework of the pipeline is constructed. In the BIM modeling paradigm, the elbow fitting connecting two non-collinear pipelines is usually anchored as a topological turning point. To address the spatial continuity problem at pipeline intersections, that is, to solve the physical interpenetration and geometric gap defects caused by direct pipeline connection and to achieve a smooth three-dimensional transition between pipelines and elbow components, this invention proposes and applies an adaptive turning point tangent interpolation correction algorithm.

[0025] Suppose that two adjacent pipe segments are extracted in step (1) in the space. , Converging at topological inflection points The system first extracts the absolute planar coordinates of the initial turning point and the spatial vectors of the two pipelines' directions. and And calculate the actual angle between the two pipelines in three-dimensional space: .

[0026] Subsequently, the algorithm couples the standard diameter attribute D of the pipeline with the corresponding elbow manufacturing standard specifications to determine the theoretical bending radius R of the elbow component at that node. To ensure that the pipeline end face and the elbow flange face are absolutely tangent in three-dimensional space, the system constructs a geometric tangent equation in the neighborhood of the turning point and dynamically calculates the required back displacement (i.e., tangent length) of the pipeline along its original direction vector. .

[0027] Using the derived backward displacement, the system re-intersections the original topology. By performing bidirectional interpolation calculations, the coordinates of the two corrected tangency points where the two extended pipelines are physically tangent to the outer edge of the elbow are accurately calculated. and .

[0028] After obtaining the aforementioned tangent coordinates, the system immediately corrects the displacement of the endpoints of the original connecting pipeline segment, accurately updating and anchoring them to the two geometric tangent points. This interpolation correction mechanism reserves accurate geometric space for subsequent elbow insertion, effectively ensuring that the pipeline and elbow can achieve seamless and natural physical connection fitting under the parametric model under different pipe diameters and deflection angles.

[0029] (3) Adaptive matching mechanism for complex elbow families based on multi-dimensional quadrant mapping: After completing the space reservation and endpoint correction at the pipeline junction in step (2), it is necessary to further precisely assemble the actual elbow entity into the reserved space. In order to address the pain point of low generation efficiency of irregular pipeline junction nodes, that is, to solve the problem of adaptively calling the corresponding type of elbow model under different spatial deflection angles, this invention establishes an adaptive matching mechanism for complex elbow families based on multi-dimensional quadrant mapping.

[0030] Define the azimuth angles of the two connected pipelines entering the junction on the two-dimensional horizontal projection plane as follows: and (The value range is from 0° to 360°), the system first uses the built-in quadrant calculation function. Quickly calculate the spatial projection quadrant values ​​of the two pipelines mentioned above. and Simultaneously, the algorithm calculates the azimuth angle of the angle bisector formed by the direction vectors of the two pipelines. Similarly, the spatial projection quadrant value of the angle bisector can be obtained. Let the actual plane angle between the two pipelines be... The system pre-establishes a collection of three-dimensional elbow family models covering various spatial deflection patterns. .

[0031] To replace the tedious manual table lookup logic, the modeling engine calls the system's built-in multi-condition branch mapping operator. Using quadrant values ​​and included angle parameters as joint input variables, the system automatically outputs matching elbow component numbers. .

[0032] ; For other spatial deflection patterns, the mapping operator follows the same dimensionality reduction logic and extends the mapping using the corresponding rules. This purely mathematical mapping mechanism completely avoids the tedious process of manual judgment and trial and error in traditional BIM modeling, achieving algorithm-level, second-level adaptive assembly of components.

[0033] (4) Reverse deduction and reconstruction of pipeline ancillary facilities under multiple spatial topological constraints: After completing the precise splicing of the main pipelines and elbow components in steps (1) to (3) above, in order to form a complete and engineering-compliant full-element BIM model of the municipal pipeline network, it is also necessary to perform spatial constraint alignment and missing data extrapolation on the surrounding ancillary facilities. Regarding the alignment of the foundation orientation of ground ancillary facilities such as streetlights and storm drains, let the tangent direction vector of the adjacent road centerline be... The foundation orientation vector of the ancillary facilities is It also introduces relative relation operators that reflect the actual engineering layout specifications. .

[0034] The system calculates the yaw angle required for the appendage to rotate about the vertical Z-axis based on spatial geometric constraints. : when When orthogonal constraints are present, the algorithm forces the solution of constraint equations based on dot products: ; when When there are parallel constraints, the algorithm forces the solution of constraint equations based on the cross product: ; The yaw angle obtained through the solution The system automatically drives the BIM model to complete spatial correction and alignment.

[0035] In addition, to address the common deficiency of missing well bottom elevation in raw exploration data, the system abstracts the regional pipeline network topology into an undirected connected graph. The node set V contains inspection wells, and the edge set E contains pipe segments. For a target inspection well node with a missing depth attribute... , To determine the absolute surface elevation of the inspection well location, the algorithm extracts the set of all pipe segment edges directly topologically connected to it in the connected graph. .

[0036] Let the absolute elevation of the bottom of each connected pipe segment at the junction be... And set a bottoming margin constant that conforms to hydraulic specifications. The effective bottom elevation of the target inspection well is calculated. This allows us to determine the overall depth of the three-dimensional well. Through the alignment of ancillary facilities and the deduction of missing elevations, the automated reconstruction of a high-precision BIM model of all elements of the municipal pipeline network was finally completed.

[0037] A high-efficiency BIM model construction system for municipal pipelines includes an adaptive analysis and standardized reconstruction module, a pipeline turning point interpolation correction and smooth fitting module, a complex elbow family adaptive matching mechanism module, and a pipeline ancillary facilities reverse deduction and reconstruction module. Adaptive parsing and standardized reconstruction module: acquires discrete point and line data and table data of original municipal pipelines from multiple sources and heterogeneous sources, introduces a three-dimensional affine transformation matrix to map the discrete spatial point system with coordinate deviation to a unified absolute engineering coordinate system to complete the unification of spatial reference, and traverses and extracts the original attribute table of pipelines to construct attribute feature vectors of multi-dimensional parameters for each standard pipe section, thereby realizing the deep binding of geometric spatial information and non-geometric engineering attributes and the structural reconstruction of the underlying data. Pipeline bend point interpolation correction and smooth fitting module: Adopts an adaptive bend point tangent interpolation correction algorithm to solve the physical intersection and geometric gap defects caused by direct pipeline connection, and realize the three-dimensional smooth transition between pipeline and elbow assembly. Adaptive matching mechanism module for complex elbow families: Establishes an adaptive matching mechanism for complex elbow families based on multi-dimensional quadrant mapping to solve the problem of adaptively calling the corresponding type of elbow under different spatial deflection angles; Pipeline ancillary facilities reverse engineering and reconstruction module: Introduces multi-dimensional topology constraint reverse engineering technology to mine the topological relationships of existing pipeline data, complete the absolute spatial orientation and underground depth parameters of ancillary facilities, so that the final model fully matches the real physical engineering environment in terms of spatial attitude and hydraulic elevation logic. The present invention also discloses an electronic device, comprising: at least one processor, at least one memory, a communication interface, and a bus; wherein the processor, memory, and communication interface communicate with each other through the bus; the memory stores program instructions executable by the processor, and the processor calls the program instructions to implement the aforementioned method of the present invention.

[0038] The present invention also discloses a computer-readable storage medium that stores computer instructions, which cause the computer to implement all or part of the steps of the method described in the embodiments of the present invention. The storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0039] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, meaning they can be distributed across multiple network units. Those skilled in the art can select some or all of the modules to achieve the purpose of this embodiment without any inventive effort, based on actual needs.

[0040] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for efficiently constructing BIM models for municipal pipelines, characterized in that, Includes the following steps: S1. Adaptive parsing and standardized reconstruction of multi-source pipeline data; S2. Pipeline inflection point interpolation correction and smooth fitting based on spatial vector rules; S3. Adaptive matching mechanism for complex elbow families based on multi-dimensional quadrant mapping; S4. Reverse deduction and reconstruction of pipeline ancillary facilities under multiple spatial topological constraints.

2. The efficient BIM model construction method for municipal pipelines according to claim 1, characterized in that, Step S1: Adaptive parsing and standardized reconstruction of multi-source pipeline data: S11. Obtain the discrete point and line data and tables of the original municipal pipelines from multiple sources and heterogeneous structures. Introduce a three-dimensional affine transformation matrix to map the discrete spatial point system with coordinate deviations to a unified absolute engineering coordinate system to achieve spatial benchmark unification. Then, iterate through and extract the original pipeline attribute tables to construct multi-dimensional parameter attribute feature vectors for each standard pipe segment. Define the original input multi-source pipeline point set as... The line set is ; S12. Introduced the three-dimensional affine transformation matrix M trans All original discrete points Forced mapping to a unified BIM absolute engineering coordinate system to obtain standardized coordinate points. ( , , Its spatial analytic transformation process satisfies the equation: ； - Together, they constitute the elements of the third-order rotation submatrix, used to adjust and align the spatial orientation, orientation, and scale of the original pipeline data with the target BIM environment; , and These constitute the three independent components of the translation vector, representing the linear physical distance that the data needs to be translated in the X, Y, and Z axis directions, respectively. S13. After completing the spatial reference unification, traverse the MDB attribute table for each standard pipe segment. Constructing multidimensional attribute feature vectors ,in For pipe diameter, Material coefficient, For connection method, For pipeline types, the dimensionality reduction and recombination of this feature vector achieves deep binding between geometric spatial information and non-geometric engineering attributes, completing the standardized reconstruction of the underlying data structure.

3. The efficient BIM model construction method for municipal pipelines according to claim 1, characterized in that, In step S2 of the BIM modeling paradigm, elbow fittings connecting two non-collinear pipelines are typically anchored as topological inflection points. An adaptive inflection point tangent interpolation correction algorithm is used to achieve a smooth 3D transition between the pipeline and the elbow assembly. S21. Suppose there are two adjacent pipe segments in space. , Converging at topological inflection points Extract the absolute planar coordinates of the initial turning point and the spatial vectors of the two pipelines' directions. and And calculate the actual angle between the two pipelines in three-dimensional space. : ； S22. The standard diameter D of the pipeline, the theoretical bending radius R of the elbow component at the node, and to ensure that the pipeline end face and the elbow flange face are absolutely tangent in three-dimensional space, a geometric tangent equation is constructed in the neighborhood of the turning point, and the required back displacement of the pipeline along the original direction vector is dynamically calculated, i.e., the tangent length. : ； Using the derived backward displacement, the original topological intersection point is... By performing bidirectional interpolation calculations, the coordinates of two corrected tangency points where the two extended pipelines are physically tangent to the outer edge of the elbow are derived, as follows: ； ； After obtaining the tangent coordinates, the endpoints of the original connecting pipeline segment are corrected for displacement, updated, and anchored to the two geometric tangent points.

4. The efficient BIM model construction method for municipal pipelines according to claim 1, characterized in that, Step S3: Establish an adaptive matching mechanism for complex elbow families based on multi-dimensional quadrant mapping. Define the azimuth angles of the two connected pipelines entering the junction on the two-dimensional horizontal projection plane as follows: and Calculated using the built-in quadrant function Calculate the spatial projection quadrant values ​​of the two pipelines mentioned above. and ; Calculate the azimuth angle of the angle bisector formed by the direction vectors of the two pipelines. Similarly, the spatial projection quadrant value of the angle bisector can be obtained. ; Let the actual plane angle between the two pipelines be... A pre-established collection of three-dimensional elbow family models covering various spatial deflection patterns was created. ; Calling the multi-condition branch mapping operator Using quadrant values ​​and included angle parameters as joint input variables, the system automatically outputs matching elbow component numbers. : ； For other spatial deflection forms, the mapping operator follows the same dimensionality reduction logic and applies the corresponding rules for extended mapping.

5. The efficient BIM model construction method for municipal pipelines according to claim 1, characterized in that, Step S4: Reverse deduction and reconstruction of pipeline ancillary facilities under multiple spatial topology constraints: Regarding the alignment of the foundation orientation of ground-level ancillary facilities, let the tangent direction vector of the adjacent road centerline be . The foundation orientation vector of the ancillary facilities is And introduce relative relation operators The yaw angle required for the appendage to rotate about the vertical Z-axis is determined based on spatial geometric constraints. : when When orthogonal constraints are present, the algorithm forces the solution of constraint equations based on dot products: ； when When there are parallel constraints, the algorithm forces the solution of constraint equations based on the cross product: ； The yaw angle obtained through the solution This enables spatial alignment and correction of the BIM model's posture.

6. The efficient BIM model construction method for municipal pipelines according to claim 5, characterized in that, To address the deficiency of missing well bottom elevation in the original exploration data, the regional pipeline network topology is abstracted as an undirected connected graph. The node set V contains inspection wells, and the edge set E contains pipe segments; 3D coordinates of a target inspection well node with missing depth attribute , To determine the absolute surface elevation of the inspection well location, extract the set of all pipe segment edges directly topologically connected to it from the connected graph. ; Let the absolute elevation of the bottom of each connected pipe segment at the junction be... And set a bottoming margin constant that conforms to hydraulic specifications. The effective bottom elevation of the target inspection well is calculated. This allows us to determine the overall depth of the three-dimensional well. Ultimately, the automated reconstruction of the high-precision BIM model of all elements of the municipal pipeline network was completed.

7. A high-efficiency BIM model construction system for municipal pipelines, adapted to the method described in any one of claims 1-6, characterized in that, It includes an adaptive analysis and standardized reconstruction module, a pipeline inflection point interpolation correction and smooth fitting module, a complex elbow family adaptive matching mechanism module, and a pipeline ancillary facilities reverse deduction and reconstruction module; Adaptive parsing and standardized reconstruction module: acquires discrete point and line data and table data of original municipal pipelines from multiple sources and heterogeneous sources, introduces a three-dimensional affine transformation matrix to map the discrete spatial point system with coordinate deviation to a unified absolute engineering coordinate system to complete the unification of spatial reference, and traverses and extracts the original attribute table of pipelines to construct attribute feature vectors of multi-dimensional parameters for each standard pipe section, thereby realizing the deep binding of geometric spatial information and non-geometric engineering attributes and the structural reconstruction of the underlying data. Pipeline bend point interpolation correction and smooth fitting module: Adopts an adaptive bend point tangent interpolation correction algorithm to solve the physical intersection and geometric gap defects caused by direct pipeline connection, and realize the three-dimensional smooth transition between pipeline and elbow assembly. Adaptive matching mechanism module for complex elbow families: Establishes an adaptive matching mechanism for complex elbow families based on multi-dimensional quadrant mapping to solve the problem of adaptively calling the corresponding type of elbow under different spatial deflection angles; Pipeline ancillary facilities reverse deduction and reconstruction module: The introduced multi-topology constraint reverse deduction technology explores the topological relationships of existing pipeline data, completes the absolute spatial orientation and underground depth parameters of ancillary facilities, so that the final model fully matches the real physical engineering environment in terms of spatial attitude and hydraulic elevation logic.

8. The efficient BIM model construction system for municipal pipelines according to claim 7, characterized in that, A standardized multi-source data foundation was constructed through three-dimensional affine transformation and eigenvector recombination, providing a data interface basis for the later integration of BIM models into the city's digital twin foundation.

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