A communication pipeline laying system for underground smart pipe gallery

Abstract

The present invention discloses a communication pipeline laying system for an underground smart pipeline gallery, and relates to the technical field of underground smart pipeline gallery construction, including collecting point cloud data and underground environmental parameters through laser radar and sensors, and performing synchronous processing; fusing the synchronously processed point cloud data and underground environmental parameters to construct a three-dimensional geographic information model; using artificial intelligence to analyze and plan the three-dimensional geographic model, and optimize the laying path to obtain the optimal laying path; according to the optimal laying path, using automated construction equipment to perform automated pipeline laying; the present invention uses artificial intelligence to analyze and plan the three-dimensional geographic model, and optimizes the laying path to obtain the optimal laying path, thereby effectively avoiding risk areas under complex geological conditions, reducing construction costs, and improving the reliability of communication pipeline laying path planning.

Description

Technical Field

[0001] The present invention relates to the technical field of underground smart pipe gallery construction, and in particular to a communication pipeline laying system for an underground smart pipe gallery. Background Art

[0002] In recent years, with the acceleration of urbanization, urban infrastructure construction has put forward higher requirements for the development and utilization of underground space. Underground comprehensive pipeline corridors, as an infrastructure for intensive and systematic management of urban underground pipelines, can effectively solve the safety hazards and maintenance difficulties caused by the scattered laying of traditional underground pipelines, and have gradually become an important part of smart city construction.

[0003] Traditional communication pipeline laying technology mainly relies on manual surveying, mechanical excavation and pipeline docking. In recent years, with the gradual development of geographic information technology, lidar technology and automated construction equipment, some pipeline laying methods combined with intelligent systems have gradually emerged, but their application still has many limitations. However, the results of path planning in existing technologies are often not targeted and cannot be dynamically adjusted according to complex geological conditions, resulting in frequent problems such as detours and obstacle handling during construction, further reducing construction efficiency and the reliability of pipeline laying. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a communication pipeline laying system for an underground smart pipeline corridor to solve the reliability problem of communication pipeline laying path planning.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] The present invention provides a communication pipeline laying system for an underground smart pipeline gallery, which comprises:

[0008] Data acquisition module, used to collect point cloud data and underground environmental parameters through lidar and sensors;

[0009] The 3D model building module is used to integrate the synchronously processed point cloud data and underground environmental parameters to build a 3D geographic information model;

[0010] The path planning module is used to analyze and plan the three-dimensional geographic model using artificial intelligence, and optimize the paving path to obtain the optimal paving path;

[0011] The automatic laying module is used to perform automatic pipeline laying according to the optimal laying path using automated construction equipment.

[0012] As a preferred solution of the communication pipeline laying system of the underground smart pipe gallery of the present invention, wherein: the point cloud data and underground environmental parameters are collected by laser radar and sensors and synchronously processed, the specific steps are as follows:

[0013] Preset the flight route of the drone based on the planning scope of the underground smart pipeline corridor and the terrain of the location;

[0014] The laser radar is mounted on the drone, and the multi-beam laser radar is used to vertically project the laser beam and receive the reflected signal to generate point cloud data;

[0015] By installing IoT sensors in the planning area of ​​underground smart pipe corridors, underground environmental parameters can be collected simultaneously with the laser radar on drones;

[0016] Integrate the point cloud data and underground environmental parameters collected by LiDAR and IoT sensors into multi-dimensional geographic parameters, and transmit them to the data processing center for synchronous processing via wireless transmission protocols;

[0017] Convert multidimensional geographic parameters into the same geographic coordinate system;

[0018] The Kalman filter algorithm is used to clean the multidimensional geographic parameters and remove outliers.

[0019] As a preferred solution of the communication pipeline laying system of the underground smart pipe gallery of the present invention, the specific steps of integrating the synchronously processed point cloud data and underground environmental parameters are as follows:

[0020] Use the point cloud data collected by LiDAR as the basis of three-dimensional space;

[0021] Through coordinates, each underground environmental parameter collected by the IoT sensor is mapped to three-dimensional space;

[0022] By adding multiple attribute fields to each 3D point based on the point cloud data, underground environmental parameters are attached to the point cloud data with the same coordinates;

[0023] The Kriging interpolation method is used to estimate underground environmental parameters and fill in the gaps in uncovered areas.

[0024] As a preferred solution of the communication pipeline laying system of the underground smart pipe gallery of the present invention, the specific steps of constructing the three-dimensional geographic information model are as follows:

[0025] The local point cloud data fragments of different scanning areas generated by the LiDAR are seamlessly spliced ​​together through a splicing algorithm to generate a three-dimensional model;

[0026] The three-dimensional model is modeled layer by layer through the layer-by-layer construction method;

[0027] Using triangulated meshing algorithm, a three-dimensional surface model is constructed for the surface layer based on the point cloud data of LiDAR;

[0028] Based on multi-dimensional geographic information, locate the location and direction of underground pipelines, as well as the location and shape of building foundations, and use parametric modeling methods to construct a three-dimensional underground structure model;

[0029] Based on the point cloud data of the mapped geographic environment parameters, a continuous three-dimensional geological layer model is generated using the isosurface interpolation method;

[0030] Integrate the 3D surface model, 3D underground structure model and 3D geological layer model into a 3D geographic information model;

[0031] GIS software is used to render three-dimensional geographic information, and different categories of objects in the three-dimensional geographic information are displayed with different colors and transparencies.

[0032] As a preferred solution of the communication pipeline laying system of the underground smart pipe gallery of the present invention, wherein: the three-dimensional geographic model is analyzed and planned by artificial intelligence, and the laying path is optimized to obtain the optimal laying path. The specific steps are as follows:

[0033] The three-dimensional geographic information model is spatially divided into regular equilateral three-dimensional grid units;

[0034] Extract soil density, groundwater level, terrain slope and obstacle area from 3D grid cells and quantify them;

[0035] The cost function is used to quantitatively evaluate the paving path, and the paving cost function is defined for the three-dimensional grid unit;

[0036] Determine the excavation cross-sectional dimensions and depth of the laying path based on the cross-sectional dimensions and burial depth of the communication pipeline;

[0037] Using Dijkstra algorithm, the paving path is planned to obtain a preliminary paving path;

[0038] The preliminary paving path is optimized using the Bezier curve smoothing algorithm;

[0039] The feasibility of the optimized paving path is verified to obtain the optimal paving path.

[0040] As a preferred solution of the communication pipeline laying system of the underground smart pipe gallery of the present invention, wherein: the Dijkstra algorithm is used to plan the laying path to obtain a preliminary laying path, and the specific steps are as follows:

[0041] According to the planning requirements of the underground smart pipe gallery, determine the starting point and end point of the laying path of the communication pipeline;

[0042] Assign an initial cost value to each three-dimensional grid cell;

[0043] Create a priority queue to store the three-dimensional grid cells with calculated costs and sort them according to the cost value;

[0044] The path cost plus the 3D grid cell cost value is the total cost of passing through the 3D grid cell;

[0045] Using Dijkstra algorithm, the total cost from the starting point of the paved path to each adjacent three-dimensional grid unit is calculated along the end point direction;

[0046] If the total cost of a 3D grid cell to reach an adjacent 3D grid cell is lower than the previously recorded cost, the cost of the adjacent 3D grid cell is updated, and the adjacent 3D grid cell with the lower total cost is added to the priority queue;

[0047] Select the three-dimensional grid cell with the smallest cost in the priority queue as the next three-dimensional grid cell to be processed until the end of the paving path;

[0048] The coordinates of all the three-dimensional grid cells passed through are recorded in sequence to generate a continuous path and obtain a preliminary paving path.

[0049] As a preferred solution of the communication pipeline laying system of the underground smart pipe gallery of the present invention, wherein: the preliminary laying path is optimized by using the Bezier curve smoothing algorithm, and the specific steps are as follows:

[0050] According to the display of the preliminary paving path in the three-dimensional geographic information model, the turning points in the preliminary paving path are used as the control points of the Bezier curve;

[0051] The preliminary paving path is divided into segments, and a quadratic Bezier curve is generated for each segment. By adjusting the positions of the control points of the Bezier curve, unnecessary turning points in the preliminary paving path are eliminated while the overall direction remains unchanged, and each quadratic Bezier curve is smoothed;

[0052] Connect each Bezier curve to obtain the optimized paving path.

[0053] As a preferred solution of the communication pipeline laying system of the underground smart pipe gallery of the present invention, wherein: the feasibility of the optimized laying path is verified to obtain the optimal laying path, and the specific steps are as follows:

[0054] Measure the soil density and groundwater level in the area where the optimized paving path passes;

[0055] Set the soil density threshold according to the foundation bearing capacity requirements of the communication pipeline;

[0056] When the soil density in the area through which the optimized communication path passes is lower than the soil density threshold, measures are taken to make adjustments;

[0057] According to the measurement results of the groundwater level, the height difference between the groundwater level and the top of the communication pipeline is compared, and the groundwater level threshold is set based on the size of the communication pipeline;

[0058] When the height difference between the groundwater level and the top of the communication pipeline in the area where the optimized communication path passes is less than the groundwater level threshold, measures are taken to make adjustments;

[0059] Display the optimized laying path in the 3D geographic information model, calculate the distance between underground pipelines, building foundations and the optimized laying path, and compare it with the safety distance. If the distance is less than the safety distance, make adjustments;

[0060] After feasibility verification, the optimal paving path is obtained.

[0061] As a preferred solution of the communication pipeline laying system of the underground smart pipe gallery of the present invention, wherein: the automated pipeline laying is performed according to the optimal laying path using automated construction equipment, and the specific steps are as follows:

[0062] Automatically excavate trenches for communication pipelines according to the optimal laying path using an automated hydraulic excavator equipped with LiDAR and inertial navigation;

[0063] The six-axis robot arm with integrated hydraulic clamping device at the end grabs the communication pipe and lays it in the trench;

[0064] For metal communication pipes, each section of metal communication pipes is welded by flanges, and for plastic communication pipes, each section of plastic communication pipes is connected by hot melting;

[0065] For areas where external protection of communication pipelines is required, the outer sheath of the communication pipelines shall be constructed;

[0066] After paving is completed, the trench is backfilled to restore the original topography.

[0067] As a preferred solution of the communication pipeline laying system of the underground smart pipe gallery of the present invention, wherein: trench excavation and pipeline laying are performed by automated equipment, and the specific steps are as follows:

[0068] Import the optimal paving path data into the control center of the automated hydraulic excavator and synchronize it with the coordinate system of the optimal communication path;

[0069] Calibrate the lidar and inertial navigation of the automated hydraulic excavator, synchronize with the control center, and generate excavation trajectories;

[0070] The automated hydraulic excavator sets the slope coefficient according to the excavation trajectory, excavation section size, depth of the optimal paving path and the surrounding environment and construction requirements;

[0071] The industrial camera on the six-axis robot arm can identify the position and posture of the pipeline, and automatically adjust the position and gripping angle of the six-axis robot arm based on the recognition results;

[0072] According to the three-dimensional coordinates of the optimal laying path, the six-axis robotic arm grabs the communication pipe and places it in the trench.

[0073] The beneficial effects of the present invention are as follows: through high-precision laser radar and Internet of Things sensors, multi-dimensional geographic parameters are synchronously collected and integrated to generate a comprehensive and accurate three-dimensional geographic information model, providing a scientific basis for path planning; artificial intelligence technology is used to comprehensively analyze geological characteristics, construction costs and other factors to generate the optimal laying path, effectively avoiding risk areas under complex geological conditions and reducing construction costs; automated construction equipment is linked to the optimal path to achieve full-process automation from trench excavation to pipeline laying and backfilling, significantly improving construction accuracy and efficiency while reducing errors caused by manual intervention; the overall design of the system improves the intelligence level and reliability of communication pipeline laying, which not only improves construction efficiency and pipeline stability, but also realizes construction visualization and convenience of later maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0075] Figure 1 This is a schematic diagram of the communication pipeline laying system of the underground smart pipeline corridor in Example 1.

[0076] Figure 2 This is a module diagram of the communication pipeline laying system of the underground smart pipeline corridor in Example 1. DETAILED DESCRIPTION

[0077] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0078] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0079] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0080] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, and which provides a communication pipeline laying system for an underground smart pipe gallery, comprising the following steps:

[0081] The data acquisition module is used to collect point cloud data and underground environmental parameters through lidar and sensors for synchronous processing.

[0082] According to the planning scope of the underground smart utility corridor and the terrain of the location, the flight route of the drone is preset to achieve full coverage of the planning scope of the underground smart utility corridor. The flight altitude should be controlled between 50 meters and 100 meters to ensure the high accuracy of the scanning data while avoiding excessive impact on the capture of data details;

[0083] The laser radar is mounted on the drone. Through the multi-beam laser radar, the laser beam is projected vertically and the reflected signal is received to generate point cloud data, accurately depicting the terrain contour, geological layer structure, underground pipelines and building foundations. In order to ensure the accuracy of the data, the scanning resolution of the laser radar should be set to 0.1 meters, and the scanning frequency should be controlled at about 500,000 points per second.

[0084] By installing IoT sensors in the planning area of ​​the underground smart pipeline corridor, the underground environmental parameters, such as soil density, groundwater level and soil moisture, are collected simultaneously with the laser radar on the drone.

[0085] Integrate the point cloud data and underground environmental parameters collected by LiDAR and IoT sensors into multi-dimensional geographic parameters, and transmit them to the data processing center for synchronous processing via wireless transmission protocols;

[0086] Convert multidimensional geographic parameters to the same geographic coordinate system WGS84;

[0087] The Kalman filter algorithm is used to clean the multidimensional geographic parameters and remove outliers.

[0088] The 3D model building module is used to fuse the synchronously processed point cloud data and underground environmental parameters to build a 3D geographic information model.

[0089] Point cloud data is a set of discrete points in three-dimensional space, each point has a specific three-dimensional coordinate, and the point cloud data collected by the lidar is used as the basis of three-dimensional space;

[0090] Through coordinates, each underground environmental parameter collected by the IoT sensor is mapped to three-dimensional space;

[0091] By adding multiple attribute fields to each 3D point based on the point cloud data, underground environmental parameters are attached to the point cloud data with the same coordinates;

[0092] Specifically, the sensor collects soil density data at a certain location, and the location also has a corresponding terrain point in the point cloud data generated by the lidar. The soil density value of the location is assigned to the corresponding point in the point cloud data to form a three-dimensional space point with physical properties (such as density, humidity, etc.);

[0093] Since geological sensors are sparsely distributed, many spatial points will be missing these physical environment data when directly mapped to point cloud data;

[0094] The Kriging interpolation method is used to estimate underground environmental parameters and fill in the gaps in uncovered areas;

[0095] Specifically, known IoT sensor data points are selected, and the spatial change trend of underground environmental parameters in the area covered by the known IoT sensor data points is calculated according to the Kriging difference method. The underground environmental parameters of the surrounding non-covered areas are deduced, and point cloud data of the corresponding spatial positions are assigned to fill the uncovered areas and generate continuous underground environmental parameters.

[0096] The local point cloud data fragments of different scanning areas generated by the LiDAR are seamlessly spliced ​​together through a splicing algorithm to generate a three-dimensional model;

[0097] Specifically, based on the point cloud data aligned in space, for two sets of point cloud data fragments A and B, starting from each point in A, by calculating the Euclidean distance, find the nearest neighbor point in B, and use the ICP algorithm to calculate the rotation matrix and translation vector from A to B, so as to minimize the error in the overlapping area of ​​the two sets of point cloud data fragments;

[0098] The three-dimensional model is modeled layer by layer through the layer-by-layer construction method;

[0099] Using triangulated meshing algorithms (such as Delaunay triangulation) and based on the point cloud data of LiDAR, a three-dimensional surface model is constructed for the surface layer to generate elevation changes on the surface and accurately reflect the slope, undulations and building boundaries of the surface;

[0100] Delaunay triangulation can ensure that the shape of the triangular mesh is close to equilateral, avoid overly thin and long triangles, and improve the accuracy and stability of the model;

[0101] Based on multi-dimensional geographic information, use spatial segmentation algorithms (such as region growing method or DBSCAN algorithm) to extract pipeline point cloud data from the overall point cloud data, locate the position and direction of underground pipelines, as well as the position and shape of building foundations, and use parametric modeling methods (such as least squares method) to extract the diameter, center point, direction vector of pipelines and the shape, depth and distribution of building foundations, fit the extracted point cloud data, model underground pipelines and building foundations as regular geometric bodies, and construct a three-dimensional underground structure model;

[0102] Based on the point cloud data of the mapped geographic environment parameters, a continuous three-dimensional geological layer model is generated using the isosurface interpolation method;

[0103] Specifically, the continuous geological characteristic field is decomposed into multiple surfaces reflecting specific geological features through isosurface extraction technology, and isovalue intervals are divided according to geological characteristics (such as soil density and groundwater level range);

[0104] Use the isosurface tracing algorithm to slice the geological feature field, extract points that meet specific isovalue conditions in each slice, connect and smooth the extracted isovalue lines, and generate a complete three-dimensional isosurface;

[0105] The three-dimensional isosurfaces are grouped according to the numerical range of geological properties (such as soil density or groundwater level), and each group of isosurfaces represents a geological layer;

[0106] Determine that the upper boundary of each geological layer is the minimum isosurface of the previous layer, and the lower boundary is the maximum isosurface of the previous layer;

[0107] Through Delaunay triangulation, each 3D isosurface is discretized into a triangular mesh, and the corresponding points and triangles between two adjacent 3D isosurfaces are obtained;

[0108] Connect the triangles of adjacent three-dimensional isosurfaces according to corresponding points to generate quadrilateral or triangular prism units, construct closed surfaces, generate closed three-dimensional surfaces, perform volume meshing on the closed surfaces, and obtain a three-dimensional geological layer model;

[0109] Using Blender software, the 3D surface model, 3D underground structure model and 3D geological layer model are integrated into a 3D geographic information model;

[0110] GIS software is used to render three-dimensional geographic information, and different categories of objects in the three-dimensional geographic information are displayed with different colors and transparencies. For example, gray represents buildings and brown represents foundations.

[0111] The path planning module is used to use artificial intelligence to analyze and plan the three-dimensional geographic model and optimize the paving path to obtain the optimal paving path.

[0112] The three-dimensional geographic information model is spatially divided into regular equilateral three-dimensional grid units, each of which contains position coordinates, geological information and geometric information;

[0113] Specifically, the location coordinates represent the specific location in three-dimensional space, the geological information includes physical parameters such as soil density, groundwater level, and soil moisture, and the geometric information includes geometric features such as terrain slope, existing pipelines, and building foundations;

[0114] Extract soil density, groundwater level, terrain slope and obstacle area from 3D grid cells and quantify them;

[0115] The cost function is used to quantitatively evaluate the paving path. The paving cost function is defined for the three-dimensional grid unit. The expression is as follows:

[0116] ;

[0117] , , , ;

[0118] in, is the three-dimensional grid unit cost, is the soil density cost, is the groundwater level cost, is the terrain slope cost, Obstacle area cost, when there is no obstacle in the 3D grid cell, , when there are obstacles in the three-dimensional grid cells, , is the soil density, is the depth of groundwater level relative to the ground surface, is the terrain slope;

[0119] Determine the excavation cross-sectional dimensions and depth of the laying path based on the cross-sectional dimensions and burial depth of the communication pipeline;

[0120] According to the planning requirements of the underground smart pipe gallery, determine the starting point and end point of the laying path of the communication pipeline;

[0121] Assign an initial cost value to each 3D grid cell, with the starting cost being 0 and the remaining uncalculated 3D grid cells being infinite;

[0122] Create a priority queue to store the three-dimensional grid cells with calculated costs and sort them according to the cost value;

[0123] The path cost for directly adjacent 3D grid cells is 1, and the path cost for diagonally adjacent cells is , to reflect the increase in spatial distance, the path cost plus the three-dimensional grid unit cost value is the total cost of passing through the three-dimensional grid unit;

[0124] Using Dijkstra algorithm, the total cost from the starting point of the paved path to each adjacent three-dimensional grid unit is calculated along the end point direction;

[0125] If the total cost of a 3D grid cell to reach an adjacent 3D grid cell is lower than the previously recorded cost, the cost of the adjacent 3D grid cell is updated, and the adjacent 3D grid cell with the lower total cost is added to the priority queue;

[0126] Select the three-dimensional grid cell with the smallest cost in the priority queue as the next three-dimensional grid cell to be processed until the end of the paving path;

[0127] The coordinates of all the three-dimensional grid cells passed through are recorded in sequence to generate a continuous path and obtain a preliminary paving path;

[0128] The preliminary laying path is optimized through the Bezier curve smoothing algorithm to generate smoother curves, reduce unnecessary sharp turns, ensure the smoothness and stability of pipeline laying, and make the path more suitable for actual construction;

[0129] According to the display of the preliminary paving path in the three-dimensional geographic information model, the turning points in the preliminary paving path are used as the control points of the Bezier curve;

[0130] Divide the preliminary paving path into segments, and generate a quadratic Bezier curve for each segment. The expression is as follows:

[0131] ;

[0132] in, is the quadratic Bezier curve equation, represents the interpolation of the curve between the control points, , , They are the control points on the quadratic Bezier curve respectively;

[0133] By adjusting the positions of the control points of the Bezier curve, the unnecessary turning points in the preliminary paving path are eliminated while the overall direction remains unchanged, and each segment of the quadratic Bezier curve is smoothed;

[0134] Specifically, unnecessary turning points refer to points where the local direction of the path changes suddenly, including "sawtooth" turning points caused by rasterization, subtle directional swing turning points, such as frequent left and right swings in a straight line area, forming a small "wave" shape, local sharp turns, such as sudden 90-degree or even larger turns in certain areas, and overly complex paths when bypassing obstacles, such as multiple turns in the path near obstacles.

[0135] Connect each Bezier curve to obtain the optimized paving path;

[0136] The soil density and groundwater level of the area where the optimized paving path passes are measured by using the knife-ring method and the arrangement of monitoring wells.

[0137] According to the requirements of the communication pipeline on the foundation bearing capacity, the soil density threshold is set as ;

[0138] When the soil density in the area through which the optimized communication path passes is lower than the soil density threshold, measures are taken to make adjustments;

[0139] Specifically, bypassing the area where the soil density is below the soil density threshold, and improving the foundation bearing capacity in the area where the soil density is below the soil density threshold by means of compaction, replacement filling and grouting reinforcement;

[0140] According to the measurement results of the groundwater level, the height difference between the groundwater level and the top of the communication pipeline is compared. Based on the size of the communication pipeline, the groundwater level threshold is set to 1m, which is expressed as the height difference between the groundwater level and the top of the communication pipeline;

[0141] When the height difference between the groundwater level and the top of the communication pipeline in the area where the optimized communication path passes is less than the groundwater level threshold, measures are taken to make adjustments;

[0142] By adjusting the route, avoid areas with high groundwater levels. When it is impossible to avoid them, set up drainage ditches and precipitation wells in high-water areas to lower the groundwater level. Use anti-corrosion materials as a protective layer for communication pipelines to prevent water from corroding the communication pipelines.

[0143] Display the optimized laying path in the 3D geographic information model, calculate the distance between underground pipelines, building foundations and the optimized laying path, and compare it with the safety distance. If the distance is less than the safety distance, make adjustments;

[0144] Specifically, it is stipulated that the horizontal safety distance between the communication pipeline and the power pipeline shall not be less than 0.5m, the vertical safety distance shall not be less than 0.3m, the safety distance from the gas pipeline shall not be less than 1m, the vertical safety distance shall not be less than 0.5m, and the safety distance from the water supply and drainage pipeline shall not be less than 0.5m. When the distance between the optimized laying path and other underground pipelines does not meet the safety distance, the laying path needs to be adjusted to increase the distance from other underground pipelines;

[0145] The distance between the communication pipeline and the building foundation should be no less than 1m. When it is necessary to pass near the building foundation, anti-extrusion protection measures should be taken. When the communication pipeline passes under transportation facilities such as roads and railways, the vertical distance between the top of the pipeline and the bottom of the roadbed should be no less than 1m. When laying under transportation facilities, casing protection should be used, and the casing length should cover the full width of the transportation facilities;

[0146] After feasibility verification, the optimal paving path is obtained.

[0147] The automatic laying module is used to perform automatic pipeline laying according to the optimal laying path using automated construction equipment.

[0148] The optimal paving path data is imported into the control center of the automated hydraulic excavator through the USB data interface and synchronized with the coordinate system of the optimal communication path;

[0149] Calibrate the LiDAR and inertial navigation of the automated hydraulic excavator using the calibration software that comes with the LiDAR and inertial navigation system, and synchronize with the control center of the automated hydraulic excavator.

[0150] The automated hydraulic excavator control center analyzes the optimal laying path data and generates the excavation trajectory;

[0151] The automated hydraulic excavator sets the slope coefficient according to the excavation trajectory, excavation section size, depth and surrounding environment and construction requirements of the optimal paving path to ensure the stability of the trench;

[0152] The bucket of the automated hydraulic excavator adjusts its position point by point according to the excavation trajectory. Combined with the ground height detected by the laser radar, the bucket's excavation depth and angle are dynamically controlled. The servo motor achieves smooth movement to ensure that the trench edge is neat and avoid over-excavation and under-excavation.

[0153] During the excavation process, the automated hydraulic excavator's laser radar scans the trench area in real time. When obstacles (such as large rocks, underground pipelines, etc.) and areas that require foundation bearing capacity reinforcement are detected, it automatically pauses and prompts the operator to intervene manually.

[0154] The excavated earth and stone are directly piled on both sides of the trench for backfilling;

[0155] The industrial camera on the six-axis robot captures images of the pipe material, and uses image processing software (such as OpenCV) to identify the position and posture of the pipe. Based on the recognition results, the six-axis robot automatically adjusts the position and gripping angle of the six-axis robot.

[0156] According to the three-dimensional coordinates of the optimal laying path, the six-axis robotic arm grabs the communication pipe and places it in the trench;

[0157] For metal communication pipes, each section of metal communication pipes is welded by flanges, and for plastic communication pipes, each section of plastic communication pipes is connected by hot melting;

[0158] For areas where external anti-corrosion protection of communication pipelines is required, the construction of external anti-corrosion layer for communication pipelines shall be carried out;

[0159] After paving is completed, the earth and stone piled on both sides of the trench will be used to backfill the trench and restore the vegetation and facilities on the original ground.

[0160] In summary, the present invention achieves synchronous collection and fusion of multi-dimensional geographic parameters through: LiDAR and IoT sensors, generates a comprehensive and accurate three-dimensional geographic information model, provides a scientific basis for path planning, uses artificial intelligence technology to comprehensively analyze geological characteristics, construction costs and other factors, generates the optimal laying path, effectively avoids risk areas under complex geological conditions, reduces construction costs, and links automated construction equipment with the optimal path to achieve full-process automation from trench excavation to pipeline laying and backfilling, significantly improves construction accuracy and efficiency, and reduces errors caused by manual intervention. The overall design of the system improves the intelligence level and reliability of communication pipeline laying, which not only improves construction efficiency and pipeline stability, but also realizes construction visualization and convenience of later maintenance.

[0161] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A communication pipeline laying system for an underground smart pipe gallery, characterized in that: include, Data acquisition module, used to collect point cloud data and underground environmental parameters through lidar and sensors, and perform synchronous processing; The 3D model building module is used to integrate the synchronously processed point cloud data and underground environmental parameters to build a 3D geographic information model; The path planning module is used to analyze and plan the three-dimensional geographic model using artificial intelligence, and optimize the paving path to obtain the optimal paving path; Automatic laying module, used to carry out automatic pipeline laying according to the optimal laying path using automated construction equipment; The point cloud data and underground environment parameters are collected by laser radar and sensors and processed synchronously. The specific steps are as follows: Preset the flight route of the drone based on the planning scope of the underground smart pipeline corridor and the terrain of the location; The laser radar is mounted on the drone, and the multi-beam laser radar is used to vertically project the laser beam and receive the reflected signal to generate point cloud data; By installing IoT sensors in the planning area of ​​underground smart pipe corridors, underground environmental parameters can be collected simultaneously with the laser radar on drones; Integrate the point cloud data and underground environmental parameters collected by LiDAR and IoT sensors into multi-dimensional geographic parameters, and transmit them to the data processing center for synchronous processing via wireless transmission protocols; Convert multidimensional geographic parameters into the same geographic coordinate system; Use Kalman filter algorithm to clean multi-dimensional geographic parameters and remove outliers; The specific steps of fusing the synchronously processed point cloud data and underground environmental parameters are as follows: Use the point cloud data collected by LiDAR as the basis of three-dimensional space; Through coordinates, each underground environmental parameter collected by the IoT sensor is mapped to three-dimensional space; By adding multiple attribute fields to each 3D point based on the point cloud data, underground environmental parameters are attached to the point cloud data with the same coordinates; The Kriging interpolation method is used to estimate underground environmental parameters and fill in the gaps in uncovered areas.

2. The communication pipeline laying system of the underground smart pipe gallery according to claim 1, characterized in that: The specific steps of constructing the three-dimensional geographic information model are as follows: The local point cloud data fragments of different scanning areas generated by the lidar are seamlessly spliced ​​through the splicing algorithm to generate a three-dimensional model; The three-dimensional model is modeled layer by layer through the layer-by-layer construction method; Using triangulated meshing algorithm, a three-dimensional surface model is constructed based on the point cloud data of LiDAR. Based on multi-dimensional geographic information, locate the location and direction of underground pipelines, as well as the location and shape of building foundations, and use parametric modeling methods to construct a three-dimensional underground structure model; Based on the point cloud data of the mapped geographic environment parameters, a continuous three-dimensional geological layer model is generated using the isosurface interpolation method; Integrate the 3D surface model, 3D underground structure model and 3D geological layer model into a 3D geographic information model; GIS software is used to render three-dimensional geographic information, and different categories of objects in the three-dimensional geographic information are displayed with different colors and transparencies.

3. The communication pipeline laying system of the underground smart pipe gallery according to claim 2, characterized in that: The specific steps of using artificial intelligence to analyze and plan the three-dimensional geographic model and optimize the paving path to obtain the optimal paving path are as follows: The three-dimensional geographic information model is spatially divided into regular equilateral three-dimensional grid units; Extract soil density, groundwater level, terrain slope and obstacle area from 3D grid cells and quantify them; The cost function is used to quantitatively evaluate the paving path, and the paving cost function is defined for the three-dimensional grid unit; Determine the excavation cross-sectional dimensions and depth of the laying path based on the cross-sectional dimensions and burial depth of the communication pipeline; Using Dijkstra algorithm, the paving path is planned to obtain a preliminary paving path; The preliminary paving path is optimized using the Bezier curve smoothing algorithm; The feasibility of the optimized paving path is verified to obtain the optimal paving path.

4. The communication pipeline laying system of the underground smart pipe gallery according to claim 3, characterized in that: The Dijkstra algorithm is used to plan the paving path to obtain a preliminary paving path. The specific steps are as follows: According to the planning requirements of the underground smart pipe gallery, determine the starting point and end point of the laying path of the communication pipeline; Assign an initial cost value to each three-dimensional grid cell; Create a priority queue to store the three-dimensional grid cells with calculated costs and sort them according to the cost value; The path cost plus the 3D grid cell cost value is the total cost of passing through the 3D grid cell; Using Dijkstra algorithm, the total cost from the starting point of the paved path to each adjacent three-dimensional grid unit is calculated along the direction of the end point; If the total cost of a 3D grid cell to reach an adjacent 3D grid cell is lower than the previously recorded cost, the cost of the adjacent 3D grid cell is updated, and the adjacent 3D grid cell with the lower total cost is added to the priority queue; Select the three-dimensional grid cell with the smallest cost in the priority queue as the next three-dimensional grid cell to be processed until the end of the paving path; The coordinates of all the three-dimensional grid cells passed through are recorded in sequence to generate a continuous path and obtain a preliminary paving path.

5. The communication pipeline laying system of the underground smart pipe gallery according to claim 4, characterized in that: The Bezier curve smoothing algorithm is used to optimize the preliminary paving path. The specific steps are as follows: According to the display of the preliminary paving path in the three-dimensional geographic information model, the turning points in the preliminary paving path are used as the control points of the Bezier curve; The preliminary paving path is divided into segments, and a quadratic Bezier curve is generated for each segment. By adjusting the positions of the control points of the Bezier curve, unnecessary turning points in the preliminary paving path are eliminated while the overall direction remains unchanged, and each quadratic Bezier curve is smoothed; Connect each Bezier curve to obtain the optimized paving path.

6. The communication pipeline laying system of the underground smart pipe gallery according to claim 5, characterized in that: The feasibility of the optimized paving path is verified to obtain the optimal paving path. The specific steps are as follows: Measure the soil density and groundwater level in the area where the optimized paving path passes; Set the soil density threshold according to the foundation bearing capacity requirements of the communication pipeline; When the soil density in the area passed by the optimized paving path is lower than the soil density threshold, measures are taken to make adjustments; According to the measurement results of the groundwater level, the height difference between the groundwater level and the top of the communication pipeline is compared, and the groundwater level threshold is set based on the size of the communication pipeline; When the height difference between the groundwater level and the top of the communication pipeline in the area where the optimized laying path passes is less than the groundwater level threshold, measures are taken to make adjustments; Display the optimized laying path in the 3D geographic information model, calculate the distance between underground pipelines, building foundations and the optimized laying path, and compare it with the safety distance. If the distance is less than the safety distance, make adjustments; After feasibility verification, the optimal paving path is obtained.

7. The communication pipeline laying system of the underground smart pipe gallery according to claim 6, characterized in that: The specific steps of performing automated pipeline laying using automated construction equipment according to the optimal laying path are as follows: Automatically excavate trenches for communication pipelines according to the optimal laying path using an automated hydraulic excavator equipped with LiDAR and inertial navigation; The six-axis robot arm with integrated hydraulic clamping device at the end grabs the communication pipe and lays it in the trench; For metal communication pipes, each section of metal communication pipes is welded by flanges; for plastic communication pipes, each section of plastic communication pipes is connected by hot melting; For areas where external protection of communication pipelines is required, the outer sheath of the communication pipelines shall be constructed; After paving is completed, the trench is backfilled to restore the original topography.

8. The communication pipeline laying system of the underground smart pipe gallery according to claim 7, characterized in that: The trench excavation and pipeline laying are carried out by automated equipment. The specific steps are as follows: Import the optimal paving path data into the control center of the automated hydraulic excavator and synchronize it with the coordinate system of the optimal communication path; Calibrate the lidar and inertial navigation of the automated hydraulic excavator, synchronize with the control center, and generate excavation trajectories; The automated hydraulic excavator sets the slope coefficient according to the excavation trajectory, excavation section size, depth of the optimal paving path and the surrounding environment and construction requirements; The industrial camera on the six-axis robot arm can identify the position and posture of the pipeline, and automatically adjust the position and gripping angle of the six-axis robot arm based on the recognition results; According to the three-dimensional coordinates of the optimal laying path, the six-axis robotic arm grabs the communication pipe and places it in the trench.

Images