Bridge and tunnel engineering three-dimensional model automatic modeling method and system

Abstract

The invention discloses a bridge and tunnel engineering three-dimensional model automatic modeling method and system, and relates to bridge modeling. The method comprises the steps that component data are divided into point component data and linear component data according to component types; respectively establishing a parameterized template database of the point component and a parameterized template database of the linear component; analyzing the route design file to extract route line metadata; calculating coordinate conversion parameters between the source coordinate system and the target coordinate system; according to stake number parameter data input by a user, extracting coordinate data of a target stake position point and an adjacent point from the route line metadata; generating a local coordinate system transformation matrix containing position data and attitude data through vector calculation according to the coordinate data of the target pile position point and the adjacent points; acquiring a corresponding local coordinate system transformation matrix or route line metadata according to the instantiated control parameters; according to the template data and the local coordinate system transformation matrix or the route line metadata, modeling parameters of component instances are generated in batches through matrix matching calculation; the conversion efficiency is improved.

Description

An automated modeling method and system for three-dimensional models of bridge and tunnel engineering Technical Field

[0001] This application relates to the field of bridge modeling, and more specifically, to an automated modeling method and system for three-dimensional models of bridge and tunnel engineering. Background Technology

[0002] Currently, the most commonly used method for creating linear engineering models is the skeleton + template method. This method uses the route as the skeleton, and the route is created based on design file data (such as data exported from software like EICAD and Weidi) using the line element method. The standard parametric models of each individual component serve as templates, and the model is created by placing the corresponding templates on the skeleton. Its modeling process is similar to building with blocks.

[0003] However, the existing skeleton + template method has the following technical drawbacks:

[0004] First, there is a lack of an automatic conversion mechanism from route parameters to 3D models. While the skeleton + template method outlines the overall framework for model creation, in practice, the placement, positioning, and orientation adjustment of component templates on the skeleton primarily rely on manual operation. Users need to manually select locations on the route and manually adjust the rotation and tilt angles of components to adapt to the route's curves, slopes, and other geometric features.

[0005] Second, there is a lack of batch parametric modeling capabilities. Linear engineering projects are characterized by a large number of components and their repetitive arrangement along the route. For example, bridge piers are placed every 30 meters, streetlights are placed every 50 meters, and guardrails are continuously installed along the entire route. Existing methods require manually placing component templates one by one or using simple copy and paste operations, and cannot automatically generate component instances in batches based on route parameters (such as start and end station numbers and pile spacing).

[0006] Third, there is a lack of an automatic model update mechanism after route changes. During the design phase, the route plan may be dynamically adjusted and optimized according to the actual situation. Changes in the upstream skeleton (i.e., the route) will cause changes in the position and orientation of all downstream components attached to the skeleton. In existing methods, after the route is adjusted, the old component models must be deleted, and the new models must be manually placed and adjusted. Each modification requires a large amount of repetitive modeling work.

[0007] Fourth, the coordinate systems of route data exported by different design software are not consistent. Different route design software (such as Civil 3D, OpenRoads, and Latitude) use different coordinate systems, including independent coordinate systems, construction coordinate systems, geodetic coordinate systems, etc., and the azimuth references may also be inconsistent.

[0008] In summary, while existing skeleton + template modeling methods provide a basic modeling framework, they have significant shortcomings in key technical aspects such as automatic conversion of route parameters to 3D models, batch parametric modeling, automatic model updating after route changes, and data integration of different coordinate systems. These shortcomings make it difficult to meet the actual needs of efficient, accurate, and flexible modeling for large-scale linear engineering projects. Summary of the Invention

[0009] To address the lack of an effective conversion mechanism between route design data (one-dimensional linear parameters) and three-dimensional component models (spatial coordinates and orientation) in existing technologies, this application provides an automated modeling method and system for three-dimensional models of bridge and tunnel engineering. This method utilizes a global coordinate transformation matrix M and a local coordinate system transformation matrix... The dual homogeneous coordinate transformation enables the automatic conversion from route station parameters to three-dimensional component models.

[0010] One aspect of this application provides an automated modeling method for three-dimensional models of bridge and tunnel engineering, comprising: S1, dividing component data into point component data and linear component data according to component type; establishing parameterized template databases for point components and linear components respectively, wherein the template databases store geometric parameter data, constraint relationship data, and pose control data; S2, parsing route design files to extract route metadata; calculating coordinate transformation parameters between the source coordinate system and the target coordinate system, wherein the coordinate transformation parameters include azimuth difference and translation vector; constructing a coordinate transformation matrix containing rotation and translation transformations based on the coordinate transformation parameters; and transforming the extracted route metadata from the source coordinate system to the target coordinate system using the coordinate transformation matrix. S3. Establish a global mapping relationship from the source coordinate system to the target coordinate system; S4. Based on the station number parameter data input by the user, extract the coordinate data of the target station point and adjacent points from the route metadata transformed in step S2; Based on the coordinate data of the target station point and adjacent points, generate a local coordinate system transformation matrix containing position data and attitude data through vector calculation; S5. Extract the corresponding template data from the template database according to the component type, and obtain the instantiation control parameters input by the user; Obtain the corresponding local coordinate system transformation matrix or route metadata based on the instantiation control parameters; Based on the template data, and the local coordinate system transformation matrix or route metadata, generate the modeling parameters of the component instances in batches through matrix matching calculation.

[0011] The template database for the point component dataset contains pose control parameter data based on a single positioning point; the template database for the linear component dataset contains cross-sectional control parameter data based on path sweep; and the route metadata includes the three-dimensional coordinate data of the route control points.

[0012] Point-type components typically have a relatively concentrated geometric shape, and their modeling datum is a clearly defined positioning point (usually the center point or bottom center point of the component). When arranging them on the route, it is only necessary to determine the station number of this positioning point on the route, and the component can automatically determine its spatial position and orientation based on the route's geometric characteristics (tangent direction, slope, superelevation, etc.) of that point.

[0013] Linear components typically extend continuously along the route direction. Their modeling is based on a sweep algorithm, which sweeps the cross-sectional profile along the route path to generate a 3D solid. The geometry of the component is controlled by two parts of data: path data (extracted from route metadata) and cross-sectional data (extracted from a template database). The cross-section automatically adapts to the geometric changes of the route during the sweep process.

[0014] The source coordinate system is the coordinate system used by the original route metadata in the route design file. It is usually the default coordinate system of the route design software or the coordinate system specified during the design phase.

[0015] The target coordinate system is the coordinate system used for creating and displaying 3D models in modeling software or BIM platforms, serving as a unified reference benchmark for the final spatial position and orientation of all component instances.

[0016] Location data describes the numerical data of the position of a component or its positioning point in three-dimensional space, usually expressed in three-dimensional coordinates (x, y, z).

[0017] Attitude data describes the orientation and tilt of a component in three-dimensional space. It is usually expressed in the form of rotation matrices, Euler angles or quaternions.

[0018] Instantiate control parameters: The user-input control component instance generates a set of parameter data with attributes such as range, quantity, position, and size.

[0019] Furthermore, the instantiated control parameters include: station number, quantity, pile spacing, or pile start and end positions.

[0020] Furthermore, point components include: bridge piers, streetlights, signs, sensors, and expansion joints; linear components include: bridge superstructure, roadbed and pavement, tunnel body, and guardrails.

[0021] Furthermore, a coordinate transformation matrix is ​​constructed based on the translation vector, including determining the azimuth angle of the source coordinate system. This represents the clockwise angle between the X-axis of the source coordinate system and the north direction of the absolute coordinate system; it determines the azimuth angle of the target coordinate system. This represents the clockwise angle between the X-axis of the target coordinate system and the north direction of the absolute coordinate system; a reference point is selected in the source coordinate system. Obtain the coordinates of the reference point in the source coordinate system. and the corresponding coordinates in the target coordinate system According to azimuth and azimuth reference Calculate the azimuth difference. According to coordinates and Calculate the translation vector; based on the azimuth difference value Construct a rotation matrix around the Z-axis Construct the translation transformation matrix T based on the translation vector; construct the rotation matrix... Using the translation matrix T, construct the coordinate transformation matrix M. Wherein, , and Represents the coordinate components in the source coordinate system. , and Represents the coordinate components in the target coordinate system.

[0022] Specifically, in highway route design, regardless of the coordinate system used, the vertical reference (gravity direction) is unified; the only difference between different coordinate systems lies in the azimuth reference in the horizontal plane (e.g., true north, grid north, magnetic north, etc.). The azimuth difference is calculated, and a rotation matrix around the Z-axis is constructed to accurately achieve orientation correction in the horizontal plane, ensuring that the converted route data maintains the correct planar orientation.

[0023] Furthermore, in highway route design, horizontal orientation (azimuth) and spatial location (coordinates) are relatively independent parameters. Azimuth difference The translation vector T reflects the directional difference between coordinate systems, while the translation vector T reflects the positional difference between coordinate systems. Separating these two processes makes the physical meaning of coordinate transformation clearer.

[0024] Furthermore, a local coordinate system transformation matrix containing position and attitude data is generated, including: calculating the route tangent vector from the target pile point to adjacent points, normalizing the route tangent vector to obtain the X-axis unit vector, which represents the attitude control data of the component along the route's forward direction; and obtaining the Y-axis and Z-axis unit vectors respectively through vector cross product operation based on the X-axis unit vector and a preset vertical reference vector, where the Y-axis unit vector represents the attitude control data of the component perpendicular to the route tangent direction, and the Z-axis unit vector represents the vertical attitude control data of the component.

[0025] Based on the unit vectors of the X-axis, Y-axis, and Z-axis, and the position coordinates of the target pile location, construct a 4x3 local coordinate system transformation matrix: ;in, These are the components of the unit vector along the X-axis. The components of the unit vector along the Y-axis. The components of the unit vector along the Z-axis. This refers to the location coordinates of the target pile location.

[0026] In particular, highway routes are continuously changing spatial curves, with the direction constantly changing in horizontal curves and the slope constantly changing in vertical curves. The tangent vector, calculated through the coordinate difference between adjacent stake points, accurately reflects the instantaneous direction of the route at that point, incorporating comprehensive information on both the horizontal azimuth and the longitudinal slope. This is more accurate than using only the route azimuth (which only reflects the horizontal direction and ignores the longitudinal slope).

[0027] Furthermore, on straight sections, the direction of the line connecting adjacent pile points remains unchanged; on curved sections (such as a circular curve with a radius R = 300m), the direction of the line connecting adjacent pile points gradually changes, reflecting the curve's turning angle. Using the X-axis unit vector, the longitudinal direction of structural members (such as the longitudinal direction of piers and the extension direction of guardrails) automatically aligns with the tangent direction of the route, eliminating the need for manual calculation of the rotation angle at each location. This automatic adaptation works for both large-radius curves (where the turning angle changes slowly) and small-radius curves (where the turning angle changes drastically).

[0028] Furthermore, the modeling parameters for batch generation of component instances include: for point components, based on the user-inputted station number, quantity, and pile spacing, batch generation of spatial position and orientation data of point component instances at each target pile point; for linear components, based on the user-inputted starting station number, ending station number, oblique angle, and cross-sectional parameters, batch generation of three-dimensional geometric data of linear component instances.

[0029] Furthermore, the system generates spatial position and orientation data of point component instances at each target pile location in batches, including: calculating the pile number sequence for each target pile location based on the user-input pile number, quantity, and pile spacing; and obtaining the corresponding local coordinate system transformation matrix for each pile number in the pile number sequence. Extract template data for point-based components from the template database. The template data contains a set of vertex coordinates of the components in the local coordinate system. Convert the vertex coordinates to homogeneous coordinates and apply the local coordinate system transformation matrix. Expanded into a homogeneous transformation matrix; through Calculate the coordinates of each vertex in the target coordinate system, where M is the coordinate transformation matrix. Let be the homogeneous coordinates of the vertex. The transformed homogeneous coordinates are represented by i, which represents the index of each station number; j represents the index of each vertex in the set of point-type component vertices; h represents the coordinates in homogeneous coordinate form; and global represents the global coordinate system. Three-dimensional coordinates are extracted from the homogeneous coordinate results of each vertex to form the component instance geometric data for the corresponding station point. Based on the component instance geometric data, the spatial position and attitude parameters of the component at the corresponding station point are determined. The above steps are repeated for all stations in the station number sequence to generate the spatial position and attitude data of each point-type component in batches.

[0030] Furthermore, the batch generation of 3D geometric data for linear component instances includes: generating a sampling station sequence along the route based on the user-inputted starting station, ending station, and station spacing; for each station in the sampling station sequence, extracting the corresponding route center point coordinates and tangent vector from the transformed route metadata; extracting the cross-sectional contour data of the linear component from the template database based on the user-inputted cross-sectional parameters; the cross-sectional contour data being a set of two-dimensional coordinate points of the cross-section on the local coordinate system plane; for each sampling position in the sampling station sequence, obtaining the corresponding local coordinate system transformation matrix based on the route center point and tangent vector; expanding the local coordinate system transformation matrix into a homogeneous transformation matrix; expanding the two-dimensional coordinates of the cross-sectional contour data into three-dimensional homogeneous coordinates, where the coordinate components along the route direction are zero; and through... Calculate the coordinates of the cross-sectional contour points at each sampling location in the target coordinate system. These are the homogeneous coordinates of the points on the cross-sectional profile. where k represents the homogeneous coordinates of the transformed cross-sectional contour points; k represents the index of each contour point in the set of cross-sectional contour points; the cross-sectional contour point sets at adjacent sampling positions are connected by a triangular mesh algorithm to generate a swept surface; the above sweep calculation is repeated along the sampling station sequence to generate three-dimensional geometric data of linear component instances along the entire route in batches.

[0031] The triangular mesh connection algorithm refers to a computational method that organizes discrete spatial point sets into a mesh surface composed of triangular patches through topological connection rules. In this application, it specifically refers to generating triangular patches from the cross-sectional profile point sets at two adjacent sampling positions according to specific connection rules, thereby constructing the three-dimensional geometric surface of a linear component.

[0032] Sweep surfaces are a surface modeling method in Computer-Aided Geometric Design (CAGD). It refers to moving a two-dimensional cross-sectional profile (called a generator or profile) along a three-dimensional spatial path (called a guide or path), while adjusting the position and orientation of the cross-section according to the local geometric features of the path (tangent direction, curvature, etc.), and forming a three-dimensional surface by the envelope of the cross-section at each position.

[0033] In particular, highway design exists in three different parameter spaces:

[0034] Design parameter space: a one-dimensional linear parameter system with station number, offset, and elevation difference as parameters (e.g., at K5+235, the bridge pier is arranged 3m to the left of the centerline and at an elevation of +0.5m).

[0035] Route coordinate space: The source coordinate system of the route design software (which may be an independent coordinate system, a construction coordinate system, etc.);

[0036] BIM coordinate space: The target coordinate system (engineering coordinate system or geodetic coordinate system) of the BIM platform.

[0037] In traditional methods, the conversion from design parameter space to BIM coordinate space requires two manual translations: from design parameters to human understanding, to manual selection of points on the route, to manual adjustment of the coordinate system, and finally to placement in the BIM coordinate system. This process is complex and prone to errors.

[0038] This application first uses a first-level mapping, namely, from the design parameter space to the route coordinate space, to map the design parameters (station number, offset, elevation difference) into the position and attitude in the route coordinate space. Specifically, it automatically constructs the center point coordinates (position mapping) and tangent vector (attitude mapping) corresponding to the station number by extracting them from the route metadata. The matrix enables automatic conversion from abstract parameters such as "station number K5+235" to three-dimensional coordinates (x, y, z) and attitude matrix R, accurately transforming the designer's design intent (expressed in station numbers) into geometric data (expressed in coordinates and attitude).

[0039] Next, through a second layer of mapping, the route coordinate space is transformed into the BIM coordinate space. This is achieved by using the azimuth difference Δα (to handle differences in directional references) and the translation vector T (to handle differences in origin position), establishing a global mapping relationship from the source coordinate system to the target coordinate system. This transforms the data in the route coordinate space to the BIM coordinate space, realizing cross-coordinate system data integration. This allows route data from different design software (Civil3D, OpenRoads, Latitude & Longitude, etc., each using different coordinate systems) to be seamlessly integrated into a unified BIM platform.

[0040] Finally, through matrix multiplication, the fixed template data is combined with the dynamic adaptation matrix to generate component instances that adapt to the local geometry of the route in batches: for point components, each station corresponds to one... Matrix, same template Through different The transformation generates component instances with different postures; specifically, it generates n pile points based on the start and end pile numbers and spacing, with each pile number corresponding to one. Establish a station number and attitude mapping table, calculate n component instances in parallel, and generate n component models at once.

[0041] For linear components, each sampling position corresponds to one Matrix, same cross-sectional profile Through continuous The sequence transformation generates a swept surface along the route. Specifically, m sampling points are generated based on the start and end station numbers and sampling interval. Cross-sectional data at m locations are calculated through batch transformation of the interface contour. These data are then connected in batches using triangular meshes to generate m-1 swept surface segments.

[0042] Furthermore, the batch generation of modeling parameters for component instances also includes: establishing an association index relationship between component instance data and route metadata; when the route metadata changes, identifying the changed component instance data through the association index relationship; and executing steps S2 to S4 for the changed component instance data to achieve parameterized updates of the spatial position and attitude data of the component instances.

[0043] Another aspect of this application provides an automated modeling system for three-dimensional models of bridge and tunnel engineering, comprising: a template database module for storing parametric template data of point components and linear components; a route data parsing module for parsing route design files and extracting route metadata; a coordinate transformation calculation module for calculating coordinate transformation parameters between the source coordinate system and the target coordinate system, the coordinate transformation parameters including azimuth difference and translation vector; constructing a coordinate transformation matrix M containing rotation and translation transformations based on the coordinate transformation parameters; transforming the extracted route metadata from the source coordinate system to the target coordinate system through the coordinate transformation matrix M to establish a global mapping relationship between the source coordinate system and the target coordinate system; and a local coordinate system generation module for extracting the coordinate data of the target pile point and adjacent points from the transformed route metadata based on the station number parameter data input by the user; and generating a local coordinate system transformation matrix containing position data and attitude data through vector calculation based on the coordinate data of the target pile point and adjacent points. The parametric modeling engine extracts corresponding template data from the template database module based on the component type and obtains the instantiation control parameters input by the user; it obtains the corresponding local coordinate system transformation matrix or route metadata based on the instantiation control parameters; based on the template data and the local coordinate system transformation matrix or route metadata, it generates modeling parameters for component instances in batches through matrix matching calculations; the parametric update module establishes an association index relationship between component instance data and route metadata; when the route metadata changes, it identifies the affected component instance data through the association index relationship; and it performs incremental parametric updates on the affected component instance data.

[0044] Compared to existing technologies, the advantages of this application are:

[0045] For point-type components (such as bridge piers and streetlights), this application automatically generates a station number sequence based on the station number range and station spacing. The system batch extracts the route center coordinates and tangent vectors of each station point, and automatically constructs a local coordinate system transformation matrix containing the route's geometric features through vector cross product operations. Then, combined with the global coordinate transformation matrix M and component template data The system generates all component instances in batches through a dual homogeneous coordinate transformation. For linear components (such as guardrails and bridge superstructures), it automatically generates continuous sampling sequences based on the start and end station numbers, extracts the cross-sectional profile control data of each sampling position, and generates 3D geometric data in batches using a sweep algorithm. Throughout the process, the components can automatically adapt to complex geometric features of the route, such as horizontal curves, vertical curves, and superelevations, without requiring manual calculation of any coordinate or angle parameters. This achieves semantic conversion between route design data and 3D component models.

[0046] When the route design changes, the system accurately identifies the affected component instances through associated indexes and performs incremental local recalculation based on the change type: if only the global coordinate system changes, the local coordinate system transformation matrix is ​​maintained. and template data If the route remains unchanged, only the global coordinate transformation matrix M is recalculated; if the local alignment is adjusted, only the route data for the affected stake points is re-extracted and the corresponding coordinates are recalculated. Matrix, M and The template data remains unchanged; if the component type is modified, only the template data is updated. M and It remains unchanged. It improves the responsiveness of design iterations. Attached Figure Description

[0047] Figure 1 is an exemplary flowchart of an automated modeling method for three-dimensional models of bridge and tunnel engineering according to this application;

[0048] Figure 2 is a schematic diagram of the point and linear components of this application;

[0049] Figure 3 is a schematic diagram of coordinate transformation in this application;

[0050] Figure 4 is a partial coordinate diagram of this application;

[0051] Figure 5 is a logic view of the point component processing in this application;

[0052] Figure 6 is a logic view of the linear component processing in this application;

[0053] Figure 7 is a schematic diagram of the construction and instantiation process of this application. Detailed Implementation

[0054] The present application will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0055] Example 1

[0056] As shown in Figure 1, component data is divided into point component data and linear component data according to component type. Parametric template databases are established for point components and linear components respectively. These template databases store geometric parameter data, constraint relationship data, and pose control data. Route design files are parsed to extract route metadata. Coordinate transformation parameters between the source and target coordinate systems are calculated, including azimuth difference and translation vectors. A coordinate transformation matrix containing rotation and translation transformations is constructed based on these parameters. The extracted route metadata is transformed from the source to the target coordinate system using the coordinate transformation matrix to establish a global mapping relationship between the source and target coordinate systems. Based on the user-input station number parameters, the target station location and phase are extracted from the transformed route metadata. The system generates local coordinate system transformation matrices containing position and attitude data based on the coordinate data of the target pile point and its adjacent points through vector calculation. It also extracts corresponding template data from the template database according to the component type and obtains the instantiated control parameters input by the user. Based on the instantiated control parameters, it obtains the corresponding local coordinate system transformation matrix or route metadata. Finally, based on the template data and the local coordinate system transformation matrix or route metadata, it generates modeling parameters for component instances in batches through matrix matching calculation. Specifically, the template database for point-based component datasets contains pose control parameter data based on a single positioning point; the template database for linear component datasets contains cross-sectional control parameter data based on path sweep; and the route metadata includes the three-dimensional coordinate data of the route control points.

[0057] Specifically, in S1, the development of the toolset first divides the templates according to the characteristics of the components, mainly by distinguishing between point-based and linear types, as shown in Figures 2 and 3.

[0058] The most obvious characteristic of point-based components is their coordinate system. A component is positioned and placed according to this coordinate system. Placing the component's own coordinate system alongside the coordinate system of the road framework completes the placement. The most important control factor is the positioning axis system, which includes placement point information and the component's pose information (rotation angle, orientation, and normal). Common point-based components in highway engineering include bridge piers, signs, various sensors, guardrails, and streetlights.

[0059] The most obvious characteristic of linearity is its linear elements. Components are laid out along the direction of the route. Linear components follow the route's direction, their width limited by left and right spatial boundaries or given numerical values, and their length constrained by both the starting and ending points on the route. The oblique angle with the route can be limited by calculating the angle between the route's normal plane and its own plane at the same point. In highway engineering, common linear components include various beams in bridge superstructures, roadbeds and pavements, and tunnels.

[0060] S2 identifies the route design file format type (such as industry-specific formats like XML, JSON, CSV, DAT, HJD, etc.); extracts route metadata, including horizontal alignment metadata, longitudinal profile data, and cross-section data; among which, horizontal alignment metadata includes starting station number, starting coordinates (x, y), azimuth angle, length, etc.; longitudinal profile data includes station number, ground elevation, design elevation, longitudinal slope value, etc.; cross-section data includes parameters such as roadbed width, slope ratio, and cross slope.

[0061] Determine the azimuth of the source coordinate system , representing the clockwise angle between the X-axis of the source coordinate system and the north direction of the absolute coordinate system;

[0062] Determine the orientation reference of the target coordinate system ;

[0063] Select a reference point in the source coordinate system Obtain the coordinates of the reference point in the source coordinate system. and the corresponding coordinates in the target coordinate system ;

[0064] Calculate the azimuth difference: ;

[0065] Calculate the translation vector ,in: ; ; ;

[0066] Based on the azimuth difference value Construct a rotation matrix around the Z-axis :

[0067] ;

[0068] Based on the translation vector t, construct the translation transformation matrix T: ;

[0069] Calculate the homogeneous coordinate transformation matrix M using matrix multiplication: ;

[0070] For any point in the source coordinate system Construct its homogeneous coordinate vector ;

[0071] Through matrix operations Obtain the homogeneous coordinates of the point in the target coordinate system;

[0072] S3, based on the station number parameter data input by the user, extract the coordinate data of the target station point and adjacent points from the route metadata converted in step S2;

[0073] Calculate the tangent vector data of the route from the target pile point to adjacent points: ;in, Indicates adjacent points Three-dimensional coordinate components in the target coordinate system; Indicates the target pile location Three-dimensional coordinate components in the target coordinate system;

[0074] Calculate the vector magnitude data: ;

[0075] Normalization yields the X-axis unit vector data: ;in, This represents the magnitude of the vector.

[0076] The X-axis unit vector data represents the attitude control data of the component along the path of travel;

[0077] Define vertical reference vector data: , serving as the reference data in the vertical direction;

[0078] Calculate the Y-axis unit vector data using the cross product operation: The Y-axis vector data is perpendicular to the tangent direction of the route and represents the lateral attitude control data of the component.

[0079] The Z-axis unit vector data is calculated using the cross product operation: V = W × U. The Z-axis vector data is perpendicular to both the X-axis and Y-axis, forming a right-handed coordinate system.

[0080] The three-axis vector data are ensured to be orthogonal to each other through two cross product operations, forming an orthonormal basis;

[0081] Based on the unit vectors of the X-axis, Y-axis, and Z-axis, and the position coordinates of the target pile location, construct a 4x3 local coordinate system transformation matrix: ;in, These are the components of the unit vector along the X-axis. The components of the unit vector along the Y-axis. The components of the unit vector along the Z-axis. The location coordinates of the target pile point are shown in Figure 4; the local coordinate system transformation matrix (relative coordinate system) is shown in Figure 4.

[0082] S4. Extract the corresponding template data from the template database according to the component type, and obtain the instantiation control parameters input by the user; obtain the corresponding local coordinate system transformation matrix or route metadata according to the instantiation control parameters;

[0083] For point-type components, as shown in Figure 5:

[0084] S4.1 Generation of modeling parameters for point components:

[0085] Based on the station number, quantity, and spacing of the stations entered by the user, calculate the station number sequence for each target station location;

[0086] For each station in the station number sequence, obtain the corresponding local coordinate system transformation matrix from step S3. ;

[0087] Extract template geometric data of point-like components from the template database. The template geometric data contains the set of vertex coordinates of the components in the local coordinate system. , where each vertex ;

[0088] Convert the vertex coordinates of the template geometry data to homogeneous coordinate form. ;

[0089] By supplementing the local coordinate system transformation matrix The fourth row [0, 0, 0, 1] expands it into a 4×4 homogeneous transformation matrix;

[0090] Calculate the coordinates of each vertex in the target coordinate system using homogeneous coordinate transformation matrix operations: Where M is the coordinate transformation matrix constructed in step S2, This is the expanded homogeneous transformation matrix;

[0091] From the homogeneous coordinates of the transformation result Extracting 3D coordinates Generate spatial position and attitude data of point component instances at each target pile location in batches;

[0092] For linear components, as shown in Figure 6:

[0093] Based on the starting station number entered by the user Termination chainage and pile spacing Generate a sampling station sequence along the route. ,in, ;

[0094] For each station in the sampling station sequence Extract the corresponding route center point coordinates and tangent vectors from the route metadata transformed in step S2;

[0095] Based on the cross-sectional parameters input by the user, extract the cross-sectional profile data of linear members from the template database. The cross-sectional profile data is a set of two-dimensional coordinate points of the cross-section on the local coordinate system YZ plane;

[0096] For each sampling location in the sampling station sequence, a local coordinate system transformation matrix is ​​constructed based on the route center point and the tangent vector. And by adding the fourth row [0, 0, 0, 1], it is expanded into a 4×4 homogeneous transformation matrix;

[0097] Extend the two-dimensional coordinates of the cross-sectional profile data to three-dimensional homogeneous coordinates. ,in, and The coordinates of the cross-sectional profile points on the local coordinate system YZ plane;

[0098] The coordinates of the cross-sectional contour points in the target coordinate system are calculated using homogeneous coordinate transformation matrix operations. , where M is the coordinate transformation matrix constructed in step S2;

[0099] The cross-sectional contour point sets at adjacent sampling positions i and i+1 are used to generate a swept surface through a triangular mesh connection algorithm. The triangular mesh connection algorithm includes: for two adjacent points on the cross section and Construct quadrilateral patches at two adjacent sampling locations, with the four vertices of the quadrilateral being... Then, the quadrilateral facet is further subdivided into two triangular facets;

[0100] Repeat the sweep calculation process described above to generate a batch of three-dimensional geometric data for linear component instances along the entire route.

[0101] The modeling parameters for batch generation of component instances also include:

[0102] Skeleton Change Detection: Monitors modification timestamp data or version identifier data of route design documents; when changes to the line data of the route skeleton are detected, the scope of impact data of the change is parsed to determine the affected station interval data. ;

[0103] Cascading update triggering mechanism:

[0104] Based on the scope of impact data from the changes, the following data processing flow will be automatically triggered:

[0105] First-level update: Re-execute step S2 to calculate the updated coordinate transformation matrix data. ;

[0106] Second-level update: For the affected station range For all pile locations within the local coordinate system, repeat step S3 to batch calculate the updated local coordinate system dataset. ;

[0107] Level 3 update: Search the related database to find all component instance data within the affected area based on the location criteria;

[0108] Level 4 Update: For each retrieved component instance data: read its associated stationing data or stationing range data; extract the corresponding new coordinate system data from the updated local coordinate system dataset; re-execute the matrix matching calculation in step S4 to generate updated position data and attitude data; if it is a linear component, re-execute the sweep path data calculation and sweep operation.

[0109] The updated geometric data, position data, and attitude data are synchronized to the 3D model database; the refresh function of the modeling software is called through the model interface to realize the automatic redrawing of component instances; update log data is recorded, including metadata such as update time, scope of impact, and number of instances;

[0110] Example 2

[0111] The Chongqi Bridge is located on the G40 Shanghai-Shaanxi Expressway. The main bridge is 944m long and uses a 102+4×185+102m continuous steel beam bridge, currently the largest span of its kind in China. The approach bridges are 3.6km long, using 50m (external) and 30m prestressed uniform cross-section continuous box girders. As a continuous steel box girder structure, the main bridge has complex components, and the final model needs to be used in the maintenance phase. This requires not only high accuracy of the model but also numerous additional sensor models.

[0112] The framework is selected from the horizontal center line, spatial center line, and edge line of the bridge. The template of the standard section of the steel box girder is retrieved, the framework elements are replaced, and the components are instantiated. The construction parameters are modified by design condition constraints to meet the design requirements. Subsequently, the components are manually copied, and the above process is repeated to meet the model requirements of the next stage.

[0113] The above process requires a significant amount of time to continuously operate the software. Furthermore, because components are interconnected by parameters, updates or modifications to upstream components affect their associated components. Modifying any individual component essentially requires a global update, demanding even more time. The rapidly developed modeling tool, however, operates on a holistic basis, saving considerable time on manual modifications. By inputting information such as the template's location, the number of copies required, the parameter values ​​to be modified, and the placement location, it instantiates all components at once. Compared to manual copying and modification, efficiency is improved by at least 50%.

[0114] To meet the needs of rapid modeling, 54 templates were first created in three main categories—superstructure, substructure, and ancillary structures—based on point-based and linear models, as detailed in Table 1. Templates with the same name include models of different subcategories; for example, the steel box girder diaphragm includes different types of diaphragms, such as central diaphragms, end diaphragms, support diaphragms, vertical stiffeners, and horizontal stiffeners. Reference elements refer to the names of the skeletons on which the template depends; these skeletons need to be replaced during instantiation. Input factors refer to the conditions input by the user to meet the requirements of model construction. Using the rapidly developed modeling tool and parametric templates, the entire Chongqi Bridge model was created, including the main bridge model, approach bridge models, and ancillary facility models. The final model is shown in Figure 7.

[0115] Table 1 Component Instantiation Process

[0116]

[0117] The foregoing illustrative description of the present application and its embodiments is not restrictive and can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application. The accompanying drawings are only one embodiment of the present application, and the actual structure is not limited thereto. Therefore, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the present application, such designs should fall within the scope of protection of this application. Furthermore, the word "comprising" does not exclude other elements or steps, and the word "a" preceding an element does not exclude the inclusion of "a plurality" of that element. Terms such as "first," "second," etc., are used to indicate names and do not indicate any specific order.

Claims

1. An automated modeling method for three-dimensional models of bridge and tunnel engineering, characterized in that, include: S1, based on component type, divide component data into point component data and linear component data; Establish parameterized template databases for point-based components and linear components respectively. The template databases store geometric parameter data, constraint relationship data, and pose control data; S2, parse the route design file to extract route metadata; Calculate the coordinate transformation parameters between the source coordinate system and the target coordinate system. The coordinate transformation parameters include the azimuth difference and translation vector. Construct a coordinate transformation matrix containing rotation and translation transformations based on the coordinate transformation parameters. Transform the extracted route metadata from the source coordinate system to the target coordinate system using the coordinate transformation matrix to establish a global mapping relationship between the source and target coordinate systems. S3, Based on the station number parameter data input by the user, extract the coordinate data of the target station point and adjacent points from the route metadata transformed in step S2. Based on the coordinate data of the target pile point and adjacent points, a local coordinate system transformation matrix containing position and attitude data is generated through vector calculation; S4, according to the component type, the corresponding template data is extracted from the template database, and the instantiated control parameters input by the user are obtained; based on the instantiated control parameters, the corresponding local coordinate system transformation matrix or route metadata is obtained; Based on template data and local coordinate system transformation matrices or route metadata, modeling parameters for component instances are generated in batches through matrix matching calculations. Among them, the template database of the point component dataset contains pose control parameter data based on a single positioning point; the template database of the linear component dataset contains cross-sectional control parameter data based on path sweep. The route metadata includes the three-dimensional coordinate data of the route control points.

2. The automated modeling method for three-dimensional models of bridge and tunnel engineering according to claim 1, characterized in that: Instantiated control parameters include: station number, quantity, pile spacing, or pile start and end positions.

3. The automated modeling method for three-dimensional models of bridge and tunnel engineering according to claim 2, characterized in that: Point-based components include: bridge piers, streetlights, signs, sensors, and expansion joints; linear components include: bridge superstructure, roadbed and pavement, tunnel body, and guardrails.

4. The automated modeling method for three-dimensional models of bridge and tunnel engineering according to claim 3, characterized in that: Constructing a coordinate transformation matrix based on the translation vector includes: determining the azimuth of the source coordinate system. This represents the clockwise angle between the X-axis of the source coordinate system and the north direction of the absolute coordinate system; it determines the azimuth angle of the target coordinate system. This represents the clockwise angle between the X-axis of the target coordinate system and the north direction of the absolute coordinate system; a reference point is selected in the source coordinate system. Obtain the coordinates of the reference point in the source coordinate system. and the corresponding coordinates in the target coordinate system According to azimuth and azimuth reference Calculate the azimuth difference. According to coordinates and Calculate the translation vector; based on the azimuth difference value Construct a rotation matrix around the Z-axis Construct the translation transformation matrix T based on the translation vector; construct the rotation matrix... Using the translation transformation matrix T, construct the coordinate transformation matrix M.

5. The automated modeling method for three-dimensional models of bridge and tunnel engineering according to claim 3, characterized in that: Generating a local coordinate system transformation matrix containing position and attitude data includes: calculating the route tangent vector from the target pile point to adjacent points; normalizing the route tangent vector to obtain an X-axis unit vector, which represents the attitude control data of the component along the route's forward direction; obtaining the Y-axis and Z-axis unit vectors respectively through vector cross product operation based on the X-axis unit vector and a preset vertical reference vector, where the Y-axis unit vector represents the attitude control data of the component perpendicular to the route tangent direction; and the Z-axis unit vector represents the vertical attitude control data of the component; and constructing a 4x3 local coordinate system transformation matrix based on the X-axis unit vector, Y-axis unit vector, Z-axis unit vector, and the position coordinate data of the target pile point. ;in, These are the components of the unit vector along the X-axis. The components of the unit vector along the Y-axis. The components of the unit vector along the Z-axis. This refers to the location coordinates of the target pile location.

6. The automated modeling method for three-dimensional models of bridge and tunnel engineering according to claim 4, characterized in that: Modeling parameters for batch generation of component instances include: for point components, generating spatial position and orientation data of point component instances at each target pile point based on the user-inputted station number, quantity, and pile spacing; for linear components, generating three-dimensional geometric data of linear component instances based on the user-inputted starting station number, ending station number, oblique angle, and cross-sectional parameters.

7. The automated modeling method for three-dimensional models of bridge and tunnel engineering according to claim 6, characterized in that: The system generates spatial position and orientation data of point component instances at each target pile location in batches. This includes: calculating the pile number sequence for each target pile location based on the user-input pile number, quantity, and pile spacing; and obtaining the corresponding local coordinate system transformation matrix for each pile number in the pile number sequence. Extract template data for point-based components from the template database. The template data contains a set of vertex coordinates of the components in the local coordinate system. Convert the vertex coordinates to homogeneous coordinates and apply the local coordinate system transformation matrix. Expanded into a homogeneous transformation matrix; through Calculate the coordinates of each vertex in the target coordinate system, where M is the coordinate transformation matrix. Let be the homogeneous coordinates of the vertex. The homogeneous coordinates are transformed; three-dimensional coordinates are extracted from the homogeneous coordinates of each vertex to form the component instance geometric data of the corresponding pile point; based on the component instance geometric data, the spatial position and attitude parameters of the component at the corresponding pile point are determined; the above steps are repeated for all piles in the pile number sequence to generate the spatial position and attitude data of each point component in batches.

8. The automated modeling method for three-dimensional models of bridge and tunnel engineering according to claim 7, characterized in that: The process of batch generating 3D geometric data for linear component instances includes: generating a sampling station sequence along the route based on the user-input start station, end station, and station spacing; for each station in the sampling station sequence, extracting the corresponding route center point coordinates and tangent vector from the transformed route metadata; extracting the cross-sectional contour data of the linear component from the template database based on the user-input cross-sectional parameters; the cross-sectional contour data being a set of two-dimensional coordinate points of the cross-section on the local coordinate system plane; for each sampling position in the sampling station sequence, obtaining the corresponding local coordinate system transformation matrix based on the route center point and tangent vector; expanding the local coordinate system transformation matrix into a homogeneous transformation matrix; and expanding the two-dimensional coordinates of the cross-sectional contour data into three-dimensional homogeneous coordinates, where the coordinate components along the route direction are zero. Calculate the coordinates of the cross-sectional contour points at each sampling location in the target coordinate system. These are the homogeneous coordinates of the points on the cross-sectional profile. The homogeneous coordinates of the transformed cross-sectional profile points are used; the cross-sectional profile point sets at adjacent sampling positions are connected by a triangular mesh algorithm to generate a swept surface; the above sweep calculation is repeated along the sampling station sequence to generate three-dimensional geometric data of linear component instances along the entire route in batches.

9. The automated modeling method for three-dimensional models of bridge and tunnel engineering according to claim 7 or 8, characterized in that: The batch generation of modeling parameters for component instances also includes: establishing an association index relationship between component instance data and route metadata; when the route metadata changes, identifying the changed component instance data through the association index relationship; and executing steps S2 to S4 for the changed component instance data to achieve parameterized updates of the spatial position and attitude data of the component instances.

10. An automated modeling system for three-dimensional models of bridge and tunnel engineering, used to execute the method described in any one of claims 1 to 9, characterized in that, include: The template database module stores parametric template data for point-like and linear components; The route data parsing module parses the route design file and extracts route metadata. The coordinate transformation calculation module calculates the coordinate transformation parameters between the source coordinate system and the target coordinate system. The coordinate transformation parameters include the azimuth difference and the translation vector. Based on the coordinate transformation parameters, a coordinate transformation matrix M containing rotation and translation transformations is constructed. The extracted route metadata is transformed from the source coordinate system to the target coordinate system using the coordinate transformation matrix M to establish a global mapping relationship between the source and target coordinate systems. The local coordinate system generation module extracts the coordinate data of the target station point and adjacent points from the transformed route metadata based on the station number parameter data input by the user. Based on the coordinate data of the target pile location and adjacent points, a local coordinate system transformation matrix containing position and attitude data is generated through vector calculation. The parametric modeling engine extracts the corresponding template data from the template database module according to the component type and obtains the instantiation control parameters input by the user; it then obtains the corresponding local coordinate system transformation matrix or route metadata based on the instantiation control parameters. Based on the template data, as well as the local coordinate system transformation matrix or route metadata, the modeling parameters of component instances are generated in batches through matrix matching calculation. The parameterized update module establishes an association index relationship between component instance data and route metadata; When route metadata changes, the affected component instance data is identified through the associated index relationship; incremental parameterized updates are performed on the affected component instance data.

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