Modeling method and system for non-closed main beam

Abstract

The invention discloses a modeling method and system for a non-closed main beam, and the method comprises the steps: laying a target on the cross section of the end part of the non-closed main beam as a shared control point, solving a coordinate transformation matrix according to the coordinates of the shared control point, and transforming the point clouds of the inner and outer contours of the main beam under different coordinate systems into the same coordinate system, thereby achieving the modeling of the non-closed main beam. Accurate splicing of point clouds of the inner contour and the outer contour of the main beam is achieved, and finally a main beam point cloud model is converted into a 3D real model. According to the method, a series of problems of obtaining the point cloud data of the inner and outer contours of the non-closed main beam in construction, splicing the point cloud data of the inner and outer contours, finally constructing a main beam 3D real model consistent with a construction site and the like are effectively solved, the target of establishing the non-closed main beam from the three-dimensional laser point cloud model to the 3D real model is achieved, and the process is simple in principle and easy to implement. And the practicability is high.

Description

Technical Field

[0001] The present invention belongs to the technical field of bridge model construction, and relates to a modeling method and system for non-closed main girders. Background Art

[0002] The 3D modeling of bridge components plays a crucial role in bridge construction and maintenance. An accurate 3D model not only helps improve the accuracy of bridge construction, ensuring the controllability and efficiency of the construction process, but also provides reliable data support for the long-term maintenance of the bridge. However, existing 3D models of bridge components are usually modeled based on design documents, and these models may not accurately reflect the actual state of the components, especially affected by factors such as construction deviations, material aging, and damage, resulting in a large difference between the model and the actual situation. Therefore, how to construct a more accurate 3D real model of bridge components has become a problem to be solved in the field of bridge engineering.

[0003] In recent years, as an advanced measurement tool, laser scanning technology has gradually become a research hotspot in the 3D real modeling of bridges. Laser scanning can accurately obtain the geometric shape and surface features of bridge components, providing a reliable data basis for constructing a real three-dimensional model. For solid bridge components, significant progress has been made in the modeling method based on laser scanning, and the three-dimensional shape of the components can be reconstructed relatively accurately. However, the modeling of bridge hollow components remains a technical problem. Due to the complex and closed internal cross-section structure of hollow components, laser scanning technology often faces great challenges when dealing with such components. This also leads to most existing research focusing on the modeling of solid bridge components, and there are relatively few modeling methods for the 3D real model of hollow components, which need to be further explored and developed to meet the needs of bridge full-life cycle management. Summary of the Invention

[0004] The purpose of the present invention is to solve the problem that there are relatively few modeling methods for the 3D real model of hollow components in the prior art, which cannot adapt to the characteristics of the complex and closed internal cross-section structure of hollow components and cannot accurately construct the three-dimensional shape of the components, and to provide a modeling method and system for non-closed main girders.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A modeling method for non-closed main girders includes the following steps:

[0007] Obtain the position information of shared control points at the end cross-section of the non-closed bridge main girder;

[0008] Collect the inner contour point cloud data of the non-closed main girder. Based on the inner contour point cloud data and the position information of the shared control points, obtain the relative coordinates between the inner contour point cloud data and the control points, and generate an inner contour point cloud model;

[0009] Collect the outer contour point cloud data of the non-closed main girder. Based on the outer contour point cloud data and the position information of the shared control points, obtain the relative coordinates between the outer contour point cloud data and the control points, and generate an outer contour point cloud model;

[0010] Convert and splice the inner contour point cloud model and the outer contour point cloud model in the same coordinate system to obtain a spliced non-closed main girder point cloud model, and construct a 3D real model of the non-closed main girder based on the spliced non-closed main girder point cloud model.

[0011] A further improvement of the present invention lies in:

[0012] When arranging the shared control points at the end section of the non-closed main girder, it includes: arranging at least three target balls at the corner points of the internal cavity of the end section of the box girder.

[0013] The collection of the inner contour point cloud data of the non-closed main girder includes:

[0014] Arrange several feature points in the inner cavity of the non-closed main girder;

[0015] Scan the inner cavity of the non-closed main girder, several feature points and control points to obtain the original inner contour point cloud data;

[0016] Calibrate the original inner contour point cloud data according to the coordinates of several feature points to obtain the outer contour point cloud model.

[0017] Calibrate the original inner contour point cloud data through the SLAM model.

[0018] The collection of the outer contour point cloud data of the non-closed main girder includes:

[0019] Scan the outer contour of the box girder and the shared control points by using an unmanned aerial vehicle (UAV)-mounted laser scanner to obtain the outer contour point cloud data of the box girder

[0020] Convert the inner contour point cloud model and the outer contour point cloud model in the same coordinate system by using the Bursa seven-parameter method.

[0021] The construction of the 3D real model of the non-closed main girder based on the spliced non-closed main girder point cloud model includes:

[0022] Import the spliced non-closed main girder point cloud model into the CloudCompare model, calculate the normal vectors of the inner and outer contour point clouds of the box girder, generate the inner and outer contour surfaces of the box girder based on the calculation results, and construct a 3D real model of the non-closed main girder based on the generated inner and outer contour surfaces of the box girder.

[0023] A modeling system for a non-closed main girder, comprising:

[0024] A shared control point acquisition module for acquiring the position information of the shared control points at the end section of the main girder of a non-closed bridge;

[0025] An inner contour generation module for collecting the inner contour point cloud data of the non-closed main girder, obtaining the relative coordinates between the inner contour point cloud data and the control points based on the inner contour point cloud data and the position information of the shared control points, and generating an inner contour point cloud model;

[0026] An outer contour generation module for collecting the outer contour point cloud data of the non-closed main girder, obtaining the relative coordinates between the outer contour point cloud data and the control points based on the outer contour point cloud data and the position information of the shared control points, and generating an outer contour point cloud model;

[0027] A model construction module for converting and splicing the inner contour point cloud model and the outer contour point cloud model in the same coordinate system to obtain a spliced non-closed main girder point cloud model, and constructing a 3D real model of the non-closed main girder based on the spliced non-closed main girder point cloud model.

[0028] A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of any method of the present invention are implemented.

[0029] A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the steps of any method of the present invention are implemented.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The present invention discloses a modeling method for an open main girder. By arranging targets at the end sections of the open main girder as shared control points, according to the coordinates of the shared control points, the coordinate transformation matrix is solved, and the point clouds of the inner and outer contours of the main girder in different coordinate systems are transformed into the same coordinate system to achieve precise splicing of the point clouds of the inner and outer contours of the main girder. Finally, the point cloud model of the main girder is transformed into a 3D real model. This method effectively solves a series of problems in construction, such as obtaining the point cloud data of the inner and outer contours of the open main girder, splicing the point clouds of the inner and outer contours, and finally constructing a 3D real model of the main girder consistent with the construction site, achieving the goal of establishing a 3D real model of the open main girder from a three-dimensional laser point cloud model. Moreover, the principle of this process is simple and it has high practicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other relevant drawings can also be obtained based on these drawings.

[0033] Figure 1 It is a schematic flow chart of the method of the present invention;

[0034] Figure 2 It is a layout position diagram of the targets at the end section of the main girder of the present invention;

[0035] Figure 3 It is a top view of the layout diagram of the characteristic points on the bottom surface of the inner cavity of the main girder of the present invention;

[0036] Figure 4 It is a system framework diagram of the SLAM technology of the present invention;

[0037] Figure 5 It is a flight path diagram of the drone-mounted laser scanner of the present invention;

[0038] Figure 6 It is a schematic flow chart of solving the coordinate transformation matrix of the present invention;

[0039] Figure 7 It is a schematic flow chart of the coordinate transformation process of the present invention;

[0040] Figure 8 It is a point cloud model diagram after the splicing of the point clouds of the inner and outer contours of the open main girder of the present invention is completed. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. Components of the embodiments of the present invention generally described and illustrated in the accompanying drawings herein may be arranged and designed in a variety of different configurations.

[0042] Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0043] It should be noted that like reference numerals and letters denote like items in the following drawings. Therefore, once an item is defined in one drawing, it does not require further definition and explanation in subsequent drawings.

[0044] In the description of the embodiments of the present invention, it should be noted that if terms such as "upper", "lower", "horizontal", "inner", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the inventive product is usually placed during use, it is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation of the present invention. In addition, terms such as "first", "second", etc. are only used for descriptive distinction and cannot be construed as indicating or implying relative importance.

[0045] In addition, if the term "horizontal" appears, it does not mean that the component is required to be absolutely horizontal, but it can be slightly inclined. For example, "horizontal" only means that its direction is more horizontal relative to "vertical", and does not mean that the structure must be completely horizontal, but it can be slightly inclined.

[0046] In the description of the embodiments of the present invention, it should also be noted that unless otherwise clearly specified and limited, if terms such as "set", "installed", "connected", "connected" are understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0047] The following further describes the present invention in detail with reference to the accompanying drawings:

[0048] SeeFigures 1 to 8 , this embodiment discloses a modeling method for an open main girder. First, target points are reasonably arranged at the end section of the open main girder as shared control points; a handheld laser scanner combined with SLAM technology is used to obtain the point cloud data of the inner contour of the main girder; an unmanned aerial vehicle (UAV)-mounted laser scanner is used to obtain the point cloud data of the outer contour of the main girder; according to the coordinates of the shared control points, the Bursa seven-parameter coordinate transformation matrix is solved to transform the point clouds of the inner and outer contours of the main girder in different coordinate systems to the same coordinate system to achieve precise stitching of the point clouds of the inner and outer contours of the main girder; finally, the point clouds of the inner and outer contours of the main girder are triangulated by combining the triangulation network method to generate a 3D real model of the open main girder.

[0049] Specifically, it includes the following steps:

[0050] Step 1: Conduct on-site investigation and reasonably arrange shared control points at the end section of the open main girder.

[0051] Specifically, at least three target points are reasonably arranged at the end section of the open main girder as shared control points. In this embodiment, three target balls can be arranged at the corner points of the inner cavity of the end section of the box girder, as Figure 2 shown, so that all three target balls can be scanned when scanning the inner and outer contours of the box girder to serve as shared control points for stitching the point clouds of the inner and outer contours of the open box girder.

[0052] Step 2: Use a handheld laser scanner (the laser scanner is equipped with a positioning system 1) to obtain the point cloud data of the inner contour of the open main girder and the relative coordinates of the control points, and combine the laser SLAM technology to perform calibration processing on the point cloud data of the inner contour to generate an inner contour point cloud model.

[0053] Specifically, in this embodiment, parameters such as the path and density of the feature point arrangement are reasonably selected, and feature points are arranged in the inner cavity of the open box girder, as Figure 3 shown. Use a handheld laser scanner to obtain the point cloud data of the inner contour, feature points, and shared control points of the open box girder, and combine the laser SLAM technology to register the point cloud of the inner contour based on the coordinates of the feature points to generate an inner contour point cloud model of the open box girder. The schematic diagram of the scanning instrument is as Figure 5 shown.

[0054] The SLAM system framework is generally divided into five parts: sensor data acquisition and processing, front-end odometer, back-end optimization, loop detection, and map construction, as Figure 4 shown. The specific processing process includes:

[0055] First, the laser radar scanner collects the point cloud of the inner contour of the main girder and the feature points;

[0056] The scanned data is handed over to the front - end odometer for processing and analysis to extract feature - point information. According to the feature - point coordinates, the inner - contour point cloud of the main girder is registered, and the pose transformation between adjacent lidar data frames is quickly estimated. At this time, the calculated pose contains cumulative errors and is not accurate enough;

[0057] The back - end optimization is responsible for global trajectory optimization to obtain an accurate pose and construct a globally consistent map.

[0058] During this process, loop detection is always being executed. It is used to identify the passed - by scenes, achieve a closed - loop, and eliminate cumulative errors.

[0059] Step 3: Use an unmanned - aerial - vehicle (UAV) - mounted laser scanner (with a built - in positioning system 2) to obtain the outer - contour point cloud data of the non - enclosed main girder and the relative coordinates of the control points, and generate an outer - contour point - cloud model.

[0060] Specifically, in this embodiment, the UAV flight path is reasonably planned, such as Figure 5 shown, use the UAV - mounted laser scanner to scan the outer contour of the box girder and the shared control points, obtain the outer - contour point cloud data of the box girder, and generate an outer - contour point - cloud model of the box girder.

[0061] Step 4: Based on the different relative coordinates of the shared control points in the two positioning systems, use the Bursa seven - parameter method to determine the coordinate transformation matrix between the two positioning systems.

[0062] Specifically, in this embodiment, with the relative coordinates of the shared control points in the two positioning systems as known data, solve the seven unknown parameters of the Bursa seven - parameter model to determine the coordinate transformation matrix between the two positioning systems. Among them, the coordinate system of the UAV system is used as the target coordinate system, and the coordinate system of the hand - held laser scanner is used as the source coordinate system.

[0063] Bursa seven - parameter model: [P']=(1 + s)·[R]·[P]+[T]+[ΔP i .

[0064] Where [P'] and [P] are the measured three - dimensional coordinates of the shared control points in the target coordinate system and the source coordinate system respectively; s is the scale factor, indicating the scale difference between the two coordinate systems; [R] is the rotation matrix, describing the rotation relationship between the two coordinate systems, represented by the rotation parameters R X , R Y , R Z ; [T] is the translation vector, describing the translation relationship between the two coordinate systems, represented by the translation parameters T X , T Y , T Z ; [ΔP i is the error vector caused by the instrument measurement error.

[0065] (1) Matrix form of the Bursa seven-parameter model:

[0066]

[0067] (2) Solving the seven unknown parameters:

[0068] The measured coordinates of the shared control points in the source coordinate system and the target coordinate system (the original data of the inner and outer contours measured by two laser instruments) are respectively: (X i , Y i , Z i ), (X' i , Y' i , Z' i ), i = 1, 2, …, n, n ≥ 3.

[0069] Through the transformation matrix, the three-dimensional coordinates of the control points in the target coordinate system can be calculated from the measured source coordinates, which are called the transformed coordinates of the control points. In an ideal situation, the transformed coordinates of the control points calculated by the transformation matrix should be exactly the same as their measured coordinates in the target coordinate system, that is, [ΔP i is 0. However, in practice, due to instrument measurement errors, there are often deviations between the transformed coordinates of the control points and their measured coordinates in the target coordinate system, that is, [ΔP i is not 0.

[0070] To calculate the most accurate coordinate transformation matrix and improve the coordinate transformation accuracy, it is necessary to minimize the deviation between the transformed coordinates and the measured coordinates of the control points in the target coordinate system. Therefore, an error model is constructed, and the deviation between the measured coordinates and the transformed coordinates of the control points in the target coordinate system can be represented by the following error vector [ΔP i :

[0071]

[0072] Using the least squares method to fit the seven unknown parameters to make [ΔP i tend to be the smallest, a matrix equation is constructed:

[0073] [A]·[X] = [L]

[0074] where [A] is a 3n×7 coefficient matrix (n is the number of shared control points), represented by the coordinates of the known points; [X] is the column vector of the seven unknown parameters (s, R X , R Y , R Z , T X , T Y , T Z ); [L] is a 3n×1 measured coordinate vector of the control points in the target coordinate system (n is the number of shared control points).

[0075] Solved:

[0076] [X]=([A] T [A]) -1 [A] T ·[L]

[0077] The schematic diagram of the coordinate transformation matrix solution process is as follows Figure 6 shown.

[0078] Step 5: According to the coordinate conversion matrix between the above two positioning systems, the point cloud of the inner and outer contours of the main beam is converted to the same coordinate system to complete the splicing of the point cloud of the inner and outer contours of the main beam.

[0079] Specifically, in this embodiment, according to the Bursa seven-parameter coordinate transformation matrix solved in step 4, the original coordinates of the inner contour point cloud of the box girder (in the coordinate system of the handheld laser scanner) are brought into the coordinate transformation matrix as the source coordinates to solve its coordinates in the target coordinate system (in the coordinate system of the drone). At this time, the inner and outer contour point clouds of the box girder are both in the coordinate system of the drone, which can realize the accurate splicing of the inner and outer contour point cloud data of the box girder, such as Figure 7 and Figure 8 shown.

[0080] Step 6: Use the Poisson surface reconstruction method to generate the surface of the point cloud model of the inner and outer contours of the main beam, and construct a 3D real model of the non-closed main beam.

[0081] Specifically, in this embodiment, the box girder point cloud model after the inner and outer contour point clouds are spliced ​​is imported into the CloudCompare software, the normal vectors of the inner and outer contour point clouds of the box girder are first calculated, and then the inner and outer contour surfaces of the box girder are generated through Poisson surface reconstruction to construct a 3D real model of the non-closed box girder.

[0082] Due to the complexity of the internal cross-section of bridge components and the defects of laser scanning technology, the existing 3D real modeling methods of bridge components based on laser scanning technology are mostly centered on solid component modeling, while there are fewer 3D real modeling methods for hollow components. The present invention arranges targets as shared control points in the end cross-section of a non-closed main beam, solves the coordinate conversion matrix according to the coordinates of the shared control points, and converts the inner and outer contour point clouds of the main beam in different coordinate systems to the same coordinate system, so as to achieve accurate splicing of the inner and outer contour point clouds of the main beam, and finally converts the main beam point cloud model into a 3D real model. This method effectively solves a series of problems in the construction of a non-closed main beam, such as obtaining the inner and outer contour point cloud data, splicing the inner and outer contour point clouds, and finally constructing a 3D real model of the main beam consistent with the construction site, and achieves the goal of establishing a non-closed main beam from a three-dimensional laser point cloud model to a 3D real model. The process is simple in principle and has high practicality.

[0083] This embodiment also discloses a modeling system for an open main girder, including:

[0084] A shared control point acquisition module, configured to acquire the position information of the shared control points at the end section of the open bridge main girder;

[0085] An inner contour generation module, configured to collect the inner contour point cloud data of the open main girder, obtain the relative coordinates between the inner contour point cloud data and the control points based on the inner contour point cloud data and the position information of the shared control points, and generate an inner contour point cloud model;

[0086] An outer contour generation module, configured to collect the outer contour point cloud data of the open main girder, obtain the relative coordinates between the outer contour point cloud data and the control points based on the outer contour point cloud data and the position information of the shared control points, and generate an outer contour point cloud model;

[0087] A model construction module, configured to convert and splice the inner contour point cloud model and the outer contour point cloud model in the same coordinate system to obtain a spliced open main girder point cloud model, and construct a 3D real model of the open main girder based on the spliced open main girder point cloud model.

[0088] Schematic diagram of a terminal device provided by an embodiment of the present invention. The terminal device of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor executes the computer program, the functions of each module / unit in the above-mentioned device embodiments are implemented.

[0089] The computer program can be divided into one or more modules / units, and the one or more modules / units are stored in the memory and executed by the processor to complete the present invention.

[0090] The terminal device may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor and a memory.

[0091] The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0092] The memory can be used to store the computer program and / or module. By running or executing the computer program and / or module stored in the memory, and by invoking the data stored in the memory, the processor realizes various functions of the terminal device.

[0093] If the modules / units integrated in the terminal device are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above-described embodiment methods of the present invention, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-described various method embodiments can be realized. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0094] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A modeling method for a non-enclosed main beam, characterized in that: The following steps are involved: Obtain the position information of the shared control points at the end section of the main beam of a non-enclosed bridge; Collect the inner contour point cloud data of the non-enclosed main beam, obtain the relative coordinates between the inner contour point cloud data and the control points based on the inner contour point cloud data and the position information of the shared control points, and generate the inner contour point cloud model; Collect the outer contour point cloud data of the non-enclosed main beam, obtain the relative coordinates between the outer contour point cloud data and the control points based on the outer contour point cloud data and the position information of the shared control points, and generate an outer contour point cloud model; The inner contour point cloud model and the outer contour point cloud model are transformed and spliced ​​in the same coordinate system to obtain a spliced ​​non-closed main beam point cloud model, and a non-closed main beam 3D real model is constructed based on the spliced ​​non-closed main beam point cloud model.

2. A modeling method for a non-enclosed main beam according to claim 1, characterized in that: The method of arranging the shared control points at the end section of the non-enclosed main beam includes: arranging at least three target balls at the corner points of the inner cavity of the end section of the box beam.

3. A modeling method for a non-enclosed main beam according to claim 1, characterized in that: The collecting of inner contour point cloud data of the non-enclosed main beam comprises: Arrange several characteristic points in the inner cavity of the non-enclosed main beam; Scan the inner cavity of the non-enclosed main beam with several characteristic points and control points to obtain the original inner contour point cloud data; According to the coordinates of several feature points, the original inner contour point cloud data is calibrated to obtain the outer contour point cloud model.

4. A modeling method for a non-enclosed main beam according to claim 3, characterized in that: The original inner contour point cloud data is calibrated through the SLAM model.

5. The modeling method for a non-enclosed main beam according to claim 1, characterized in that: The collecting of the outer contour point cloud data of the non-enclosed main beam comprises: The outer contour point cloud data of the box girder is obtained by scanning the outer contour of the box girder and shared control points using a drone-mounted laser scanner.

6. A modeling method for a non-enclosed main beam according to claim 1, characterized in that: The inner contour point cloud model and the outer contour point cloud model are transformed in the same coordinate system by using the Bursa seven-parameter method.

7. A modeling method for a non-enclosed main beam according to claim 1, characterized in that: The method of constructing a 3D real model of a non-closed main beam based on the spliced ​​non-closed main beam point cloud model includes: Import the spliced ​​non-closed main beam point cloud model into the CloudCompare model, calculate the point cloud normal vectors of the inner and outer contours of the box beam, generate the inner and outer contour surfaces of the box beam based on the calculation results, and construct a 3D real model of the non-closed main beam based on the generated inner and outer contour surfaces of the box beam.

8. A modeling system for a non-enclosed main beam, characterized in that: include: A shared control point acquisition module is used to obtain the position information of the shared control points at the end section of the main beam of the non-enclosed bridge; An inner contour generation module is used to collect the inner contour point cloud data of the non-enclosed main beam, obtain the relative coordinates between the inner contour point cloud data and the control points based on the inner contour point cloud data and the position information of the shared control points, and generate an inner contour point cloud model; The outer contour generation module is used to collect the outer contour point cloud data of the non-enclosed main beam, obtain the relative coordinates between the outer contour point cloud data and the control points based on the outer contour point cloud data and the position information of the shared control points, and generate the outer contour point cloud model; The model building module is used to transform and splice the inner contour point cloud model and the outer contour point cloud model in the same coordinate system to obtain a spliced ​​non-closed main beam point cloud model, and to build a non-closed main beam 3D real model based on the spliced ​​non-closed main beam point cloud model.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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