Tunnel facility BIM modeling intelligent control method

Abstract

The invention belongs to the field of engineering data processing, and particularly relates to a tunnel facility BIM modeling intelligent control method, which comprises the steps of S1, tunnel data acquisition, including tunnel portal oblique photography acquisition, tunnel interior point cloud data acquisition and tunnel interior facility texture photo acquisition; s2, acquiring longitude, latitude and elevation data of the inclined model through oblique photography, converting the data into an OBJ format, and importing the data into three-dimensional modeling software to serve as coordinate information; processing the point cloud data and the texture photo to generate a tunnel model; and S3, docking the tunnel model with the inclination model, matching the coordinate information in the S2 with the image coordinates of the sky map, and uploading the coordinate information and the image coordinates to a GIS platform.

Description

Technical Field

[0001] The present invention belongs to the field of engineering data processing, and in particular relates to a tunnel facility BIM modeling intelligent control method. Background Art

[0002] With the acceleration of global urbanization and the continuous growth of traffic volume, higher requirements are placed on the transportation system. The modern transportation industry is undergoing a critical period of transformation from traditional models to intelligent, information-based and green ones. In this process, tunnels, as important transportation hubs, play an indispensable role in connecting different regions and improving transportation efficiency.

[0003] Among them, Building Information Modeling (BIM) as a digital tool, combined with emerging technologies such as drone technology, Internet of Things, big data analysis, artificial intelligence, cloud computing, AI recognition, etc., BIM can achieve holographic management and control of tunnel projects. The smart tunnel BIM modeling holographic intelligent control solution integrates various sensors, video surveillance equipment and other intelligent hardware to collect multi-source data such as tunnel internal environmental parameters and vehicle traffic conditions in real time, and provide support for decision-making through data analysis.

[0004] However, BIM applications are mainly concentrated at the micro level of a single building or project. When it comes to larger-scale urban planning, regional development, or collaborative work across multiple projects, it is necessary to introduce a geographic information system (GIS) to process and display large-scale spatial data. It can effectively integrate geographic spatial information from different sources and achieve resource management and decision support from a macro perspective. By loading and using the tunnel BIM model in a GIS environment, it can not only improve the decision-making efficiency of urban managers, but also provide the public with more intuitive and rich information services.

[0005] However, there are some challenges in this process: BIM models are usually built based on local coordinate systems, while GIS data relies on global or regional geographic coordinate systems, such as WGS84; during the modeling process, if there is a lack of clear reference objects, it will be difficult to accurately determine the specific location of the BIM model in the real world. Even if an approximate location can be estimated, significant positional deviations may occur. Summary of the invention

[0006] Based on the problems mentioned in the above background technology, the present invention provides a BIM modeling intelligent control method for tunnel facilities.

[0007] The technical solution adopted by the present invention is as follows: a BIM modeling intelligent control method for tunnel facilities, comprising the steps of: S1: tunnel data acquisition: including oblique photography acquisition at the tunnel entrance, point cloud data collection in the tunnel, and texture photo acquisition of facilities inside the tunnel; S2: oblique photography acquisition to obtain the longitude, latitude and elevation data of the oblique model, and convert the data into OBJ format and import it into the three-dimensional modeling software as coordinate information; generate a tunnel model after processing the point cloud data and texture photos; S3: docking the tunnel model with the oblique model, matching the coordinate information in S2 with the coordinates of the Tiandi Map image, and uploading it to the GIS platform.

[0008] Furthermore, after the point cloud data collected in S1 is preprocessed to generate data a and data b, data a and data b are processed with texture photos to generate a tunnel model.

[0009] Furthermore, the steps for generating data a are as follows: S11: importing point cloud data through LSV map new earth to determine and filter the data position; S12: importing the filtered point cloud data through AutoDesk Recap and cropping the imported file; S13: updating the origin processing of the cropped point cloud data: S14: saving the export to the Support folder of the rcp file and the contained rcs file, in which the optimized grid is set to be better than 5mm.

[0010] Furthermore, the processed point cloud data is put into CAD to determine the location of equipment and facilities in the tunnel.

[0011] Furthermore, the steps of generating data b are as follows: converting the las format point cloud file into a vpc format file, and opening the working view in Rhino to obtain the first model.

[0012] Furthermore, the following production steps exist in the RHino working view: S21: Produce the tunnel entrance; S22: Produce the tunnel shell: take the tunnel entrance as the reference plane and establish a tunnel surface sketch; S23: Repeat step S22; S24: Use the lofting function to make the first model.

[0013] Furthermore, the point cloud data and tilted model data of S1 were imported into the 3D modeling software. The first model was used as a reference and the CAD was used to determine the location of equipment and facilities in the tunnel. The internal components of the tunnel were produced by manual modeling based on the texture photos to obtain the tunnel model. The tunnel model was deconstructed to separate the tunnel top structure from the tunnel bottom structure. The tunnel bottom structure was integrated to form a unified base, and a composite model hierarchy was established, including the tilted model, base and tunnel top structure.

[0014] Furthermore, select all layers, in the Affect-Only-Axis mode, reset the coordinate axes of all selected objects to zero, export the corresponding files, and upload them to the GIS platform.

[0015] Beneficial effects of the present invention: The method of the present invention ensures that the size of a tunnel within five kilometers converted from a BIM model to a GIS platform does not exceed 10MB, thus realizing a lightweight model; the coordinate systems of the tunnel model and the tilt model are highly consistent with the Tiandi Map image; the accuracy of the model is significantly improved, without problems such as polygons, polygonal points, overlapping surfaces, black surfaces, and broken surfaces; the tunnel accuracy is improved, more in line with the actual size; and the overall quality and practicality of the model are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention can be further illustrated by the non-limiting examples given in the accompanying drawings; Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0017] like Figure 1 As shown, a BIM modeling intelligent control method for tunnel facilities includes the following steps: S1: tunnel data acquisition: including oblique photography acquisition of tunnel entrance, point cloud data collection in tunnel and texture photos of facilities inside tunnel; S2: obtaining the longitude, latitude and elevation data of the oblique model, and converting the data into OBJ format and importing it as coordinate information; generating a tunnel model after processing the point cloud data and texture photos; S3: docking the tunnel model with the oblique model, matching the coordinate information in S2 with the coordinates of the Tiandi Map image, and uploading them to the GIS platform.

[0018] The invention realizes a lightweight model in which the size of a tunnel within five kilometers is no more than 10MB after being converted into OSGB or 3DTiles; the coordinate systems of the tunnel model and the tilt model are highly consistent with the Tiandi Map image; the accuracy of the model is significantly improved, and there are no problems such as polygons, polygon points, overlapping surfaces, black surfaces, and broken surfaces; the tunnel accuracy is improved and more in line with the actual size; and the overall quality and practicality of the model are improved.

[0019] Tunnel data collection is an off-site process, using drones to perform oblique photography tasks to accurately collect structural images of the tunnel entrance and its surrounding mountains, ensuring that the final model constructed can accurately reflect the actual environmental conditions, and can be combined with manual modeling to make the tunnel location consistent with the Tiantu map image location; collect high-precision three-dimensional point cloud data inside the tunnel through on-board LiDAR equipment to determine the internal and external structures of the tunnel; combine manual photography of the internal facilities of the tunnel (including laser ranging) to ensure that details are recorded. The above operations ensure the accuracy and precision of the model, while also improving modeling efficiency, making geographic positioning more accurate, and facilitating subsequent integration and analysis.

[0020] After the collection is completed, since the collected point cloud data may be collected from several consecutive tunnels, there will be multiple consecutive tunnel point cloud data in one folder. Therefore, it is necessary to determine the location of the point cloud data to facilitate distinction into a single tunnel point cloud data folder.

[0021] S11: The name of the tunnel is first determined by the panoramic image data collected by the tunnel point cloud data. If there is no panoramic image, the point cloud position needs to be determined by the LSV map. The details are as follows: When searching for tunnel panoramic images in the image folder, a name sorting file should be used to facilitate sorting of the tunnel scanning sequence, so as to facilitate the subsequent sequential reasoning and classification of point cloud data; If there is no panoramic image, use the Point Cloud Master function in LSV Map New Earth to locate and process the .las format point cloud data in the folder: A. Point Cloud Master imports point cloud data in las format; B. After importing, the Extract Ground Points window pops up, click Cancel; C. After importing the point cloud, the original point cloud data set is processed by extracting the point cloud boundary to obtain the initial boundary geometry information, and then the extracted boundary line is optimized by the boundary line simplification algorithm, and the efficient representation of the boundary line is achieved by removing redundant vertices and simplifying curve segments; D. Import the extracted boundary lines into the map software, accurately identify the tunnel section according to the naming rules, and then copy the point cloud data of this section to the local computer hard disk for subsequent conversion and merging. Be careful not to miss this section of point cloud data; S12: Create a new project using AutoDesk Recap and import the filtered point cloud data through AutoDesk Recap: A. It is recommended to create a new project in the same directory as the point cloud data on the local computer to facilitate quick reading and later query. The project path cannot contain Chinese characters or special characters. B. Scan the file and select the default settings; C. When importing files, ensure that the scan and indexing are performed after the progress bar is read; Crop the imported point cloud: Use fence selection to clip the point cloud of the road outside the tunnel and the point cloud of trees on both sides, and use internal clipping or conditional deletion to clip the selected point cloud. When processing the tunnel entrance, apply conditional filtering to retain key facilities such as road signs and telephone boxes; S13: Update the origin of the cropped point cloud data: A. For the cropped point cloud data, the origin needs to be updated to facilitate display when the subsequent CAD drawing is imported; B. It is best to update the origin to the ground area of ​​the point cloud tunnel entrance to facilitate subsequent rotation in CAD; S14: Merge data conversion export: A. After saving the project, select "Export", export to rcp format, and export to the project folder.

[0022] B. When exporting settings, the "Optimize Grid" should be set to better than 5mm to reduce point cloud optimization and facilitate the display of more detailed parts in subsequent CAD drawing. After completing the settings, click "Act Now" to export.

[0023] C. After the export is completed, the exported file is a .rcp file and a Support folder containing the .rcs file.

[0024] The processed point cloud data is put into CAD to determine the location of equipment and facilities in the tunnel: First, determine the unit. In CAD, execute the UNITS command to adjust the unit settings, change the "unit for scaling inserted content" to "meters", and set the precision to "0.000", and select other default options; use the Insert and Attach commands to load the .rcp or .rcs format point cloud. After loading the point cloud, select the relative path type in the Attach Point Cloud window to load the server relative path point cloud data; use the UCS command to redefine the user coordinate system to accurately adjust the XY plane positioning of the point cloud data: find the vertical inflection point; when locating the XY coordinates, it is necessary to find the vertical angle area of ​​the tunnel that is vertically projected on the emergency lane or vertical escape passage of the tunnel wall for XYZ coordinate positioning; this is to facilitate the subsequent drawing of the vertical projection of the large-area straight tunnel area plan, which is convenient for subsequent loading into the model positioning facility projection position.

[0025] Then adjust to the bottom view, select the point cloud, pop up the point cloud management desktop, use polygon or rectangle cropping, crop half of the wall and the excess road outside the tunnel along the center line of the road, and set the point size to 1 to improve the point cloud display effect; the display mode uses the intensity display method, and adjusts the color mapping "maximum intensity" and "minimum intensity" to display intensity details, so as to display the point cloud details in the dark; adjust the azimuth viewing angle module in the upper right corner to adjust the point cloud mapping view direction of the remaining half of the wall, and the mapping view direction is from the inside of the tunnel to the wall. After locking this view as the top view, import the existing legend into the new drawing, copy the existing legend to the point cloud graphics project, and reset the point cloud graphics project layer to facilitate the subsequent drawing of the existing parts of the tunnel.

[0026] In a step parallel to the point cloud data preprocessing and CAD, the point cloud data collected in S1 is converted into a format and then opened in a working view in Rhino to obtain a first model.

[0027] Specifically: Since the point cloud data format is .las, it needs to be converted to .vpc format through a plug-in so that it can be loaded in the Rhino working view.

[0028] S21: Tunnel entrance production: When performing the view rotation operation, orient the current front view so that the tunnel entrance is accurately rotated to the left or right position. Draw an auxiliary line in the front view so that it coincides with the tunnel entrance. Use the slicing method to select two points for slicing. Click both ends of the auxiliary line to generate a working plane reference line. Use the curve command to draw the tunnel entrance.

[0029] S22: Tunnel shell production: In the top view, use a polyline to draw a vertical line perpendicular to the tunnel along the tunnel mural auxiliary line, select the vertical line by two-point slicing, and generate a vertical tunnel work reference plane. Click align to curve and then click the auxiliary line to ensure that the vertical tunnel work reference plane moves along the auxiliary line, so that it is always perpendicular to the tunnel moving work reference plane; S23: Move to the vicinity of the tunnel entrance, draw a curve to draw the tunnel and repeat the moving operation reference plane, and repeat the above steps. The smaller the moving interval, the more accurate the tunnel generated in the end.

[0030] S24: After all the tunnels are drawn, use the lofting function to make the first model: After clicking Lofting, click on the same side of the tunnel in turn to make the first model.

[0031] Taking the above first model as a reference and CAD as the location of internal facilities, manual modeling is performed to obtain the final tunnel model.

[0032] Import the point cloud data and oblique model (OBJ) data from S1 into 3d Max or other 3D software. Here, 3dMax is used as an example. The coordinates of the oblique model imported will match the actual coordinates of the Tiandi Map image. Therefore, after the import is completed, no movement operations can be performed on the oblique model.

[0033] Using the first model as a reference, CAD determines the location of equipment and facilities in the tunnel, and manually models the internal components of the tunnel based on texture photos to obtain a tunnel model. The tunnel top and tunnel bottom of the tunnel model are separated. If the tunnel contains an escape passage, after completing the in-and-out tunnel model, it is necessary to construct the escape passage based on the point cloud data and ensure that it is correctly connected to the tunnel model.

[0034] The internal components of the tunnel are placed in the order of large to small: large fixed facilities such as ventilation equipment, electrical boxes, etc. are placed first, and then small or mobile facilities such as monitoring, air detectors, signs, emergency lights, etc. are considered; such operations can effectively solve the challenges caused by scale differences between BIM and GIS during the modeling process, ensuring that the required information can be accurately and efficiently displayed at different scales.

[0035] After merging all the models at the bottom of the tunnel before exporting, group the tilted model, tunnel bottom and tunnel top, and unlock the normals to ensure that there will be no gaps at the connection after uploading to the GIS platform; select all layers (including models and groups), and then turn on the "Affect Axis Only" mode to reset the coordinate axes of all selected objects to zero to ensure that the model position can accurately match the Tiandi Map image after uploading to the GIS platform.

[0036] The model texture requires that, without affecting the image quality, the maps that do not need to be tiled must be merged into one map in Photoshop so that they can be used in the same material attribute ball to reduce the file size and achieve lightweight models; objects with the same map should ensure that only one material ball is used to avoid wasting resources and over-large model files due to repeated use of material balls, and achieve lightweight models.

[0037] Since there are problems such as data loss and reduced accuracy when switching between different sizes from micro to macro, through the above method, the tunnel within five kilometers of the present invention is converted into osgb or 3dtiles and does not exceed 10MB, thus realizing a lightweight model; the coordinate systems of the tunnel model and the tilt model are highly consistent with the Tiandi Map image; the accuracy of the model is significantly improved, and there are no problems such as polygons, polygon points, overlapping surfaces, black surfaces, and broken surfaces; the tunnel accuracy is improved, which is more in line with the actual size; and the overall quality and practicality of the model are improved.

[0038] The present invention has been described in detail above. The description of the specific embodiments is only used to help understand the method of the present invention and its core concept. It should be pointed out that for ordinary technicians in this technical field, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

Claims

1. A tunnel facility BIM modeling intelligent control method, characterized by: The following steps are involved: S1: Tunnel data collection: including tunnel entrance oblique photography collection, tunnel point cloud data collection and tunnel internal facility texture photo collection; S2: Oblique photography is used to acquire the longitude, latitude and elevation data of the inclined model, and the data is converted into OBJ format and imported into the 3D modeling software as coordinate information; the point cloud data and texture photos are processed to generate a tunnel model; S3: Connect the tunnel model with the tilt model, match the coordinate information in S2 with the coordinates of the Tiandi Map image, and upload them to the GIS platform.

2. A tunnel facility BIM modeling intelligent control method according to claim 1, characterized in that: After the point cloud data collected in S1 is preprocessed to generate data a and data b, data a and data b are processed with texture photos to generate a tunnel model.

3. A tunnel facility BIM modeling intelligent control method according to claim 2, characterized in that: The steps to generate data a are as follows: S11: Import point cloud data through LSV map New Earth to determine and filter data location; S12: import the filtered point cloud data through AutoDesk Recap, and crop the imported file; S13: updating the origin of the cropped point cloud data; S14: Save the exported rcp file and the included rcs file in the Support folder, where the optimized grid is set to better than 5mm.

4. A tunnel facility BIM modeling intelligent control method according to claim 3, characterized in that: The processed data a is put into CAD to determine the location of equipment and facilities in the tunnel.

5. A tunnel facility BIM modeling intelligent control method according to claim 2 or 4, characterized in that: The steps for generating data b are as follows: convert the las format point cloud file into a vpc format file, and open the working view in Rhino to obtain the first model.

6. A tunnel facility BIM modeling intelligent control method according to claim 5, characterized in that: The following production steps exist in the RHino work view: S21: making tunnel entrance; S22: Make tunnel shell: take the tunnel entrance as the reference plane and create the tunnel surface sketch; S23: repeat step S22; S24: The lofting function makes the first model.

7. A tunnel facility BIM modeling intelligent control method according to claim 6, characterized in that: The point cloud data and tilted model data of S1 were imported into the 3D modeling software. The first model was used as a reference and the CAD was used to determine the location of equipment and facilities in the tunnel. The internal components of the tunnel were produced based on the texture photos. The tunnel model was obtained by manual modeling. The tunnel model was deconstructed, the tunnel top structure and the tunnel bottom structure were separated, and the tunnel bottom structure was integrated to form a unified base. A composite model hierarchy was established, including the tilted model, base and tunnel top structure.

8. The tunnel facility BIM modeling intelligent control method according to claim 7 is characterized by: Select all layers, set the mode to affect axis only, reset the coordinate axes of all selected objects to zero, export the corresponding files, and upload them to the GIS platform.

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