High slope backfill construction method under karst landform based on laser scanning technology

Abstract

The invention relates to the technical field of three-dimensional models, in particular to a laser scanning technology-based high slope backfill construction method under karst landform. Comprising the following steps that S1, construction site data are determined, and the construction data comprise a project range, a digging and filling boundary, a digging area, a filling area and a site level elevation; s2, performing three-dimensional scanning in the construction site, and establishing a three-dimensional point cloud model of the construction site; s3, the construction site is calculated according to the three-dimensional point cloud model, and the excavation amount and the filling amount are obtained; s4, slope stability evaluation is conducted on the high slope of the construction site, and high slope construction design is conducted; s5, in the construction process, three-dimensional point cloud data and material information of materials of the material storage yard are collected, and a material database is established for storage; and S6, collecting equipment is designed on the transport vehicle, the loading capacity and the material type are collected in the loading process, and a transport strategy is generated according to the material type.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional models, and particularly relates to a method for backfilling and constructing high slopes under karst landforms based on laser scanning technology. Background Art

[0002] The karst landform in Guizhou is a unique geological landscape, which includes multiple characteristics: 1. Diverse surface forms: including various forms such as stone forests, peak clusters, solution hills, funnels, and sinkholes, with large topographic undulations. 2. Complex underground development: There are a large number of underground rivers, karst caves, and subterranean river systems, forming a complex groundwater network. 3. Intense karstification: Due to the extensive distribution of limestone, the dissolution of water on rocks is very significant, resulting in continuous changes in surface and underground topography. 4. Barren land: Due to rock dissolution, the soil layer is often thin and rich in calcium carbonate, leading to poor soil fertility. 5. Uneven distribution of water resources: Surface water is prone to leakage, forming a special hydrological phenomenon of "drought on the ground and flood underground". These characteristics pose many challenges in engineering construction in Guizhou's karst landform, and factors such as geological conditions, hydrological characteristics, and ecological protection need to be particularly considered.

[0003] Currently, the main technologies for the method of backfilling and constructing high slopes under karst landforms are: foundation treatment technology, slope reinforcement technology, and monitoring systems. Due to the complexity of the karst landform, existing technologies require the use of advanced technologies, which inevitably increases the project cost. The complex geological conditions may affect the stability and accuracy of monitoring equipment. The non-uniformity of the karst landform may lead to unexpected situations during the construction process, affecting the construction quality. Therefore, there are problems such as a significant increase in project cost due to technical complexity, uncertainty in long-term stability prediction, possible insufficiency in environmental impact assessment, especially the long-term impact on the local ecosystem, insufficient reliability of the monitoring system, possible data interruption or false alarms, and great construction difficulty and challenges in quality control. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for backfilling and constructing high slopes under karst landforms based on laser scanning technology, which can improve the accuracy of backfilling high slopes under karst landforms.

[0005] The basic solution provided by the present invention: A method for backfilling and constructing high slopes under karst landforms based on laser scanning technology includes the following steps:

[0006] S1. Determine the construction site data, and the construction data includes the project scope, excavation and filling demarcation line, excavation area, filling area, and site leveling elevation;

[0007] S2. Conduct three-dimensional scanning of the construction site to establish a three-dimensional point cloud model of the construction site;

[0008] S3. Calculate the excavation volume and filling volume for the construction site based on the three-dimensional point cloud model;

[0009] S4. Evaluate the slope stability of the high slope of the construction site and conduct the design of the high slope construction;

[0010] S5. During the construction process, collect the three-dimensional point cloud data and material information of the materials in the material yard, and establish a material database for storage;

[0011] S6. Design a collection device on the transport vehicle to collect the loading volume and material type during the loading process, and generate a transportation strategy according to the material type.

[0012] Furthermore, the S3 includes the following steps:

[0013] S31. Reconstruct the mesh of the point cloud model of the construction site through modeling software, convert the point cloud model into a triangular network model, and perform surface conversion to obtain a high-precision terrain model;

[0014] S32. Obtain the design elevation data and reconstruct the design site triangular network;

[0015] S33. Extract the single grid vertices from the design site triangular network and project them into the high-precision terrain model grid to calculate the elevation difference;

[0016] S34. Subdivide the rectangle according to the building area to obtain multiple site space bounding boxes;

[0017] S35. In each site space bounding box, establish a one-to-one correspondence between the site triangular network, the design site triangular network, and the high-precision terrain grid;

[0018] S36. According to the design site triangular network, the high-precision three-dimensional terrain grid, and the elevation difference of each site space bounding box, perform the calculation of the three-section volume, calculate the earthwork volume of a single grid respectively, and obtain the total excavation and filling volume.

[0019] Furthermore, the S4 includes the following steps:

[0020] S41. Identify the discontinuity surfaces in the rock mass through the point cloud segmentation algorithm, obtain the reflection intensity information, and conduct a preliminary classification of the lithology in combination with the reflection intensity information;

[0021] S42. Convert the point cloud data into a finite element model;

[0022] S43. Conduct a numerical analysis of the slope stability.

[0023] Furthermore, the S4 also includes the following steps:

[0024] S44. Determine the backfill site of the slope according to the project scope and slope stability value;

[0025] S45. Generate a backfill plan according to the slope analysis results, and the backfill plan includes the backfill height, slope, and layer thickness;

[0026] S46. Judge the stability of the slope after backfill through data simulation analysis.

[0027] The above S5 includes the following steps:

[0028] S51. Set up a laser scanner in the material yard, and obtain the three-dimensional point cloud data of the filling materials through the laser scanner;

[0029] S52. Analyze the particle size distribution of the materials by using an image processing algorithm for life and death, and classify the filling materials;

[0030] S53. Establish a material database to store the information of different classified filling materials.

[0031] Furthermore, the above S5 includes the following steps:

[0032] S51. Set up a laser scanner in the material yard, and obtain the three-dimensional point cloud data of the filling materials through the laser scanner;

[0033] S52. Analyze the particle size distribution of the materials by using an image processing algorithm for life and death, and classify the filling materials;

[0034] S53. Establish a material database to store the information of different classified filling materials.

[0035] Furthermore, the above S6 includes the following steps:

[0036] S61. Install a high-precision lidar scanner, an on-vehicle computing unit, and a high-precision GPS on each transport vehicle;

[0037] S62. During the loading process, continuously scan the inside of the cargo box through the lidar, the on-vehicle computing unit receives the radar data, calculates the loading capacity of the transport vehicle and analyzes the material type according to the radar data, and determines the position of the transport vehicle through the high-precision GPS;

[0038] S63. Generate the optimal unloading point according to the current loading capacity, position of each vehicle and the material conditions required for each layer of the high slope.

[0039] Furthermore, it also includes the following steps:

[0040] S71. Install a lidar monitoring unit on the slope, conduct quarterly terrain scans, and generate a high-precision digital terrain model;

[0041] S72. A slope stability prediction model based on machine learning, which combines multi-source monitoring data, sets multi-level early warning thresholds, is linked with the emergency response system, and uses a cloud computing platform for big data analysis to identify long-term deformation trends.

[0042] The principle and effect of the present invention are as follows:

[0043] 1. Compared with the prior art, this solution can accurately calculate the excavation and filling volume. By reconstructing the grid, the calculation progress is improved, the site space is subdivided, and the three-section volume value is calculated to achieve a more accurate earthwork volume estimation. The three-dimensional point cloud data of the construction site is obtained through a laser scanner, a high-precision terrain model (triangular grid model) is constructed, and combined with the design elevation data, the excavation and filling volume is accurately calculated. Solve the measurement problems caused by the large terrain undulation and complex underground structure in karst landforms.

[0044] 2. Comprehensive high-slope assessment: Use the point cloud segmentation algorithm to realize the rock mass discontinuity surface, improve the accuracy of slope stability analysis, and conduct a preliminary lithology analysis in combination with the reflection intensity information to provide rich basic data for subsequent analysis. By converting the point cloud data into a finite element model, the numerical analysis method is used to evaluate the slope stability, and combined with the lithology classification (identifying the discontinuity surface through the reflection intensity information), an adapted backfill plan (including the layer thickness, slope, etc.) is generated to ensure the long-term safety of the slope after backfilling.

[0045] 3. Dynamic management of materials and transportation: The particle size distribution information of the filling materials is collected in real time through laser scanning and classified and stored. Combined with vehicle-mounted sensors (lidar, GPS), the loading volume, position, and material type of the transportation vehicles are dynamically monitored, and the optimal transportation route and unloading point are intelligently generated to achieve the precision and efficiency of material allocation. Brief Description of the Drawings

[0046] Figure 1 It is a schematic flow chart of an embodiment of the high-slope backfill construction method under karst landforms based on laser scanning technology of the present invention. Detailed Description of the Invention

[0047] The following is a further detailed description through specific embodiments:

[0048] The embodiment is basically as shown in the attached Figure 1 figure:

[0049] A high-slope backfill construction method under karst landforms based on laser scanning technology includes the following steps:

[0050] S1. Determine the construction site data, where the construction data includes the project scope, the cut-fill demarcation line, the cut area, the fill area, and the site leveling elevation. Specifically, determine the project scope, the cut-fill demarcation line, the cut area, the fill area, and the site leveling elevation, and reasonably divide the grid blocks according to the site leveling elevation, the construction plan, and the actual terrain, etc.

[0051] S2. Conduct a three-dimensional scan of the construction site to establish a three-dimensional point cloud model of the construction site. Specifically, use a ground three-dimensional laser scanner to conduct an initial scan of the project scope, and establish a point cloud model after preprocessing (denoising, filtering, etc.) the point cloud model.

[0052] S3. Calculate the construction site based on the three-dimensional point cloud model to obtain the cut volume and the fill volume;

[0053] S4. Evaluate the slope stability of the high slope of the construction site and conduct the design of the high slope construction;

[0054] S5. During the construction process, collect the three-dimensional point cloud data and material information of the materials in the material yard, and establish a material database for storage;

[0055] S6. Design a collection device on the transport vehicle to collect the loading volume and the material type during the loading process, and generate a transportation strategy according to the material type.

[0056] The said S3 includes the following steps:

[0057] S31. Through the modeling software, specifically through Rhino software in this embodiment, conduct grid reconstruction on the point cloud model of the construction site, convert the point cloud model into a triangular network model, and conduct surface conversion through NURBS to obtain a high-precision terrain model;

[0058] S32. Obtain the design elevation data and reconstruct the design site triangular network;

[0059] S33. Extract the single grid vertices from the design site triangular network and project them into the grid of the high-precision terrain model to calculate the elevation difference;

[0060] S34. Subdivide the rectangle according to the building area to obtain multiple site space bounding boxes;

[0061] S35. In each site space bounding box, establish a one-to-one correspondence between the site triangular network, the design site triangular network, and the high-precision terrain grid;

[0062] S36. According to the design site triangular network, the high-precision three-dimensional terrain grid, and the elevation difference in each site space bounding box, conduct three-section volume calculation, calculate the earthwork volume of a single grid respectively, and obtain the total cut and fill volumes.

[0063] The said S4 includes the following steps:

[0064] S41. Identify the discontinuity surfaces in the rock mass through a point cloud segmentation algorithm, obtain the reflection intensity information, and conduct a preliminary lithology classification in combination with the reflection intensity information;

[0065] S42. Convert the point cloud data into a finite element model;

[0066] S43. Conduct a numerical analysis of the slope stability.

[0067] The said S4 further includes the following steps:

[0068] S44. Determine the slope backfill site selection according to the project scope and the numerical value of the slope stability;

[0069] S45. Generate a backfill plan according to the slope analysis results, and the backfill plan includes the backfill height, slope, and layered thickness;

[0070] S46. Judge the stability of the slope after backfill through data simulation analysis.

[0071] The said S5 includes the following steps:

[0072] S51. Set up a laser scanner in the material yard, and obtain the three-dimensional point cloud data of the filling materials through the laser scanner;

[0073] S52. Analyze the particle size distribution of the materials by using an image processing algorithm for life and death, and classify the filling materials;

[0074] S53. Establish a material database to store the information of different classified filling materials.

[0075] The said S5 includes the following steps:

[0076] S51. Set up a laser scanner in the material yard, and obtain the three-dimensional point cloud data of the filling materials through the laser scanner;

[0077] S52. Analyze the particle size distribution of the materials by using an image processing algorithm for life and death, and classify the filling materials;

[0078] S53. Establish a material database to store the information of different classified filling materials.

[0079] The said S6 includes the following steps:

[0080] S61. Install a high-precision lidar scanner, an on-vehicle computing unit, and a high-precision GPS on each transport vehicle;

[0081] S62. During the loading process, continuously scan the interior of the cargo box through a lidar. The on-vehicle computing unit receives the radar data, calculates the loading capacity of the transport vehicle based on the radar data, analyzes the material type, and determines the position of the transport vehicle through high-precision GPS.

[0082] S63. Generate the optimal unloading point according to the current loading capacity, position of each vehicle, and the material conditions required for each layer of the high slope construction.

[0083] It also includes the following steps:

[0084] S71. Install a lidar monitoring unit on the slope to conduct quarterly terrain scans and generate a high-precision digital terrain model.

[0085] S72. Based on the slope stability prediction model of machine learning, combined with multi-source monitoring data, set multi-level warning thresholds, link with the emergency response system, and use the cloud computing platform for big data analysis to identify the long-term deformation trend.

[0086] The principle and effect of the present invention are as follows:

[0087] 1. Compared with the prior art, this solution can accurately calculate the excavation and filling volume. By reconstructing the grid, it improves the calculation progress, subdivides the site space, calculates the three-section volume values, and realizes more accurate earthwork volume estimation. Obtain the three-dimensional point cloud data of the construction site through a laser scanner, construct a high-precision terrain model (triangular grid model), and combine with the design elevation data to accurately calculate the excavation and filling volume. Solve the measurement problems caused by the large terrain undulation and complex underground structure in karst landforms.

[0088] 2. Comprehensive high slope assessment: Use the point cloud segmentation algorithm to realize the rock mass discontinuity surface, improve the accuracy of slope stability analysis, and conduct a preliminary lithology analysis by combining the reflection intensity information to provide rich basic data for subsequent analysis. Convert the point cloud data into a finite element model, use numerical analysis methods to evaluate the slope stability, and combine with lithology classification (identify the discontinuity surface through the reflection intensity information) to generate a suitable backfill plan (including layer thickness, slope, etc.) to ensure the long-term safety of the slope after backfilling.

[0089] 3. Dynamic management of materials and transportation: Real-time collect the particle size distribution information of the filling materials through laser scanning and classify and store them. Combine on-vehicle sensors (lidar, GPS) to dynamically monitor the loading capacity, position, and material type of transport vehicles, and intelligently generate the optimal transportation route and unloading point to achieve the precision and efficiency of material allocation.

[0090] The above are only embodiments of the present invention. Specific structures and common knowledge such as characteristics well known in the art are not described in detail herein. Those of ordinary skill in the art know all the common general technical knowledge in the technical field to which the invention pertains before the filing date or the priority date, can learn about all the prior arts in this field, and have the ability to apply conventional experimental means before this date. Those of ordinary skill in the art can, under the inspiration given in this application, perfect and implement this solution in combination with their own abilities. Some typical well-known structures or well-known methods should not become obstacles for those of ordinary skill in the art to implement this application. It should be noted that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can still be made, and these should also be regarded as the protection scope of the present invention, and these will not affect the implementation effect of the present invention and the practicality of the patent. The protection scope claimed in this application shall be subject to the content of its claims, and the specific implementation manners and the like recorded in the specification can be used to interpret the content of the claims.

Claims

1. A method for backfilling high slopes in karst landforms based on laser scanning technology, characterized in that: The following steps are involved: S1. Determine the construction site data, which includes the project scope, cut-fill boundary, cut area, fill area and site elevation; S2. Perform a three-dimensional scan on the construction site to establish a three-dimensional point cloud model of the construction site; S3. Calculate the construction site according to the three-dimensional point cloud model to obtain the excavation volume and the filling volume; S4. Evaluate the slope stability of the high slope at the construction site and design the high slope structure; S5. During the construction process, collect the 3D point cloud data and material information of the materials in the material yard, and establish a material database for storage; S6. Design collection equipment on the transport vehicle to collect the load volume and material type during the loading process, and generate a transportation strategy based on the material type.

2. The method for backfilling high slopes in karst landforms based on laser scanning technology according to claim 1 is characterized in that: The S3 comprises the following steps: S31, reconstructing the grid of the point cloud model of the construction site through modeling software, converting the point cloud model into a triangulated network model, and performing surface conversion to obtain a high-precision terrain model; S32, obtaining design elevation data and reconstructing the design site triangulation network; S33, extracting a single mesh vertex from the design site triangulation network and projecting it into the high-precision terrain model grid to calculate the elevation difference; S34, subdividing the rectangle according to the building area to obtain multiple site space bounding boxes; S35. In each site space bounding box, a site triangulation network, a design site triangulation network, and a high-precision terrain grid are established and corresponded one to one; S36. Perform three-segment volume calculations based on the design site triangulation, high-precision three-dimensional terrain grid and elevation difference of each site space bounding box, calculate the earthwork volume of a single grid respectively, and obtain the total excavation and filling volume.

3. The method for backfilling and constructing high slopes in karst landforms based on laser scanning technology according to claim 2 is characterized in that: The S4 comprises the following steps: S41, identifying discontinuities in the rock mass through a point cloud segmentation algorithm, obtaining reflection intensity information, and performing preliminary lithology classification based on the reflection intensity information; S42, converting the point cloud data into a finite element model; S43. Perform numerical analysis on slope stability.

4. The method for backfilling and constructing high slopes in karst landforms based on laser scanning technology according to claim 3 is characterized in that: The S4 further comprises the following steps: S44. Determine the location of slope backfill based on the project scope and slope stability value; S45, generating a backfilling scheme according to the slope analysis result, wherein the backfilling scheme includes backfilling height, slope and layer thickness; S46. Determine the stability of the slope after backfilling through data simulation analysis.

5. The method for backfilling and constructing high slopes in karst landforms based on laser scanning technology according to claim 4 is characterized in that: The S5 comprises the following steps: S51, setting up a laser scanner at the material yard, and obtaining three-dimensional point cloud data of the filling material through the laser scanner; S52, using image processing algorithms to analyze material particle size distribution and classify filling materials; S53. Establish a material database to store filling material information of different categories.

6. The method for backfilling and constructing high slopes in karst landforms based on laser scanning technology according to claim 5 is characterized in that: The S6 comprises the following steps: S61. Install high-precision lidar scanners, on-board computing units, and high-precision GPS on each transport vehicle; S62. During the loading process, the interior of the cargo box is continuously scanned by a laser radar, and the on-board computing unit receives radar data, calculates the loading volume of the transport vehicle and analyzes the material type based on the radar data, and determines the location of the transport vehicle through a high-precision GPS; S63, generating an optimal unloading point according to the current load and position of each vehicle and the conditions of each layer of materials required for high slope construction.

7. The method for backfilling and constructing high slopes in karst landforms based on laser scanning technology according to claim 1 further comprises the following steps: S71. Install a laser radar monitoring unit on the slope to conduct quarterly terrain scanning and generate a high-precision digital terrain model; S72. A slope stability prediction model based on machine learning is developed, combining multi-source monitoring data, setting multi-level warning thresholds, linking with the emergency response system, and using the cloud computing platform for big data analysis to identify long-term deformation trends.

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