An underground pipe network modeling method and system based on feature position calibration

Abstract

The present invention provides an underground pipe network modeling method and system based on feature position calibration, including steps of three-dimensional pipe network modeling, constructing a pipe network basic model according to a pipe network plane design drawing; flight path planning step, planning a UAV flight path according to feature position points; detection data acquisition step, acquiring a scene image and pipe network data; pipe point data analysis step, obtaining the actual coordinates of feature position points according to the scene image, analyzing the road surface adjustment data at the reference objects around the pipe points, and analyzing the pipe network data at the pipe points through an anomaly detection strategy to obtain the pipe point status; pipe network model update step, respectively updating the feature position points and the buried depths of each pipe point in the pipe network basic model with the actual coordinates and the road surface adjustment data, and updating the status of each pipe point in the pipe network basic model according to the pipe point status to obtain an accurate pipe network model; the advantages of the present invention are to improve the accuracy and practicability of the three-dimensional model of the underground pipe network and realize the real-time update of the pipe network status.

Description

Technical Field

[0001] The present invention relates to the technical field of underground pipe network modeling, and more specifically, to an underground pipe network modeling method and system based on feature position calibration. Background Art

[0002] In the process of urban construction and development, the municipal underground pipe network, as the "lifeline" of the city, undertakes important functions such as water supply, drainage, gas, electricity, and communication. Its safe and stable operation is crucial for the normal operation of the city. However, there are many problems in traditional municipal underground pipe network management. On the one hand, the existing underground pipe network data are mostly stored in the form of two-dimensional drawings and text records, with scattered and unintuitive information, making it difficult to comprehensively and accurately display the spatial position, orientation, connection relationship of the pipe network, and its interaction with the surrounding environment.

[0003] With the continuous expansion of the city scale and the increasing complexity of the underground pipe network system, the traditional two-dimensional management method is inefficient in tasks such as pipe network planning and design, daily maintenance, fault detection and repair. For example, during pipe network planning and design, it is difficult for designers to effectively analyze and optimize the spatial conflicts between different types of pipe networks based on two-dimensional data; during daily maintenance, it is difficult for inspection personnel to quickly locate potential problem points of the pipe network; during fault detection and repair, maintenance personnel need to spend a lot of time and effort sorting out pipe network information, resulting in an extended fault handling time.

[0004] With the rapid development of computer technology, surveying and mapping technology, and geographic information system (GIS) technology, three-dimensional modeling technology has been increasingly widely used in the municipal field. Three-dimensional modeling technology can integrate various information of the underground pipe network, construct an intuitive and realistic three-dimensional model, and realize the visual management of the underground pipe network. Through the three-dimensional model, managers can observe the distribution of the pipe network from different angles and levels, quickly obtain detailed information of the pipe network, and provide strong support for tasks such as municipal engineering construction, pipe network planning and design, daily maintenance, and fault handling. However, the current three-dimensional modeling is only directly based on the data size on the original plane drawing for modeling, and the actual scene is prone to change, resulting in the constructed model being difficult to accurately and intuitively match the actual scene, and unable to provide accurate pipe network layout information for inspection personnel and subsequent municipal planning. Summary of the Invention

[0005] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide an underground pipe network modeling method and system based on feature position calibration.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] An underground pipe network modeling method based on feature position calibration, comprising:

[0008] Steps for three-dimensional modeling of pipe networks: retrieve the scene model in the record, and construct a basic pipe network model in the scene model according to the pipe network plane design drawing;

[0009] Steps for flight path planning: select characteristic position points in the pipe network plane design drawing, and plan the UAV flight path according to the characteristic position points;

[0010] Steps for detecting data collection: obtain the scene images and pipe network data collected by the equipment carried on the UAV;

[0011] Steps for pipe point data analysis: obtain the actual coordinates of the characteristic position points according to the scene images, select pipe detection points between two adjacent characteristic position points in the scene images as pipe points, select the reference objects around the pipe points in the scene images to analyze the road surface adjustment data, and analyze the pipe network data at the pipe points through an anomaly detection strategy to obtain the pipe point status, where the pipe point status includes the normal state of the pipeline, the deformed state of the pipeline, and the settlement state of the pipeline;

[0012] Steps for updating the pipe network model: update the coordinates of the characteristic position points in the basic pipe network model with the actual coordinates, update the burial depth of each pipe point in the basic pipe network model with the road surface adjustment data, and update the status of each pipe point in the basic pipe network model according to the pipe point status and the pipe network data at the pipe point to obtain an accurate pipe network model.

[0013] Further, the pipe point data analysis step includes a road surface analysis strategy, and the road surface analysis strategy includes a reference object analysis sub-step and a road surface analysis sub-step.

[0014] In the reference object analysis sub-step, measure the actual exposed height value of the reference object according to the scene image, compare the actual exposed height value with the recorded exposed height value of the reference object in the scene model, and if the two do not match, perform the road surface analysis sub-step;

[0015] In the road surface analysis sub-step, retrieve the construction record at the reference object in the municipal system. If the retrieval is successful, analyze whether the road surface construction data is consistent with the exposed change amount of the reference object. If they are consistent, use the road surface construction data as the road surface adjustment data for updating the burial depth of the pipe point. Otherwise, combine the exposed change amount of the reference object with the road surface construction data to analyze whether the changed area covers the pipe point. If so, use the calculated change amount of the pipe point as the road surface adjustment data for updating the burial depth of the pipe point.

[0016] Further, the road surface analysis sub-step includes a pipe point coverage analysis sub-strategy. According to the scene image, the slope change of the reference object is analyzed. Based on the exposed change amount of the reference object and the slope change of the reference object, the radius of the reference object change area is calculated. Then, the straight-line distance between the reference object and the pipe point is calculated and compared with the radius of the reference object change area. If the radius of the reference object change area is greater than the straight-line distance, the change amount at the pipe point within the reference object change area is calculated.

[0017] Further, the pipe network data is a detection map, which includes the actual buried depth of the pipeline, the pipeline contour points, and the stress and strain. The anomaly detection strategy includes a pipeline anomaly judgment sub-step and a pipeline state calculation sub-step.

[0018] In the pipeline anomaly judgment sub-step, it is determined whether the theoretical buried depth of the pipeline in the pipe network basic model under the modification of the road surface adjustment data is consistent with the actual buried depth of the pipeline. If they are consistent, the normal state of the pipeline is output; otherwise, the pipeline state calculation step is performed.

[0019] In the pipeline state calculation sub-step, the pipeline centerline offset and the ellipticity are calculated respectively according to the actual pre-buried depth of the pipeline and the pipeline contour points. Then, the pipeline deformation rate is calculated through the pipeline deformation formula using the pipeline centerline offset, ellipticity, stress and strain, and the pipe wall thickness. The pipeline deformation rate is compared with a preset deformation threshold, and the pipeline state is output according to the comparison result.

[0020] Further, the pipeline deformation calculation formula is configured as:

[0021] ,

[0022] ,

[0023] Among them, is the pipeline centerline offset, is the surface ellipticity of the pipeline, is the stress and strain of the pipeline, is the pipe wall thickness, is the pipeline deformation rate, are the first constant, the second constant, the third constant, the fourth constant, and the fifth constant respectively, is the deformation threshold.

[0024] Further, the pipe point data analysis step includes a pipe point selection strategy. The pipe point selection strategy includes that when there are marked points such as pipeline intersection points and pipeline alignment points between two adjacent characteristic position points, the marked points and the pipeline detection points evenly selected between the two adjacent characteristic position points are jointly used as pipe points.

[0025] Further, for the step of updating the pipe network model, where the actual coordinates are longitude and latitude coordinates, the actual relative position is judged according to the longitude and latitude coordinates of two adjacent characteristic position points, and the theoretical relative position of the same two characteristic position points in the basic pipe network model is updated through the actual relative position.

[0026] Further, for the step of updating the pipe network model, when the deviation of the theoretical relative position of every two adjacent characteristic position points is the same, the coordinate deviation value of any one characteristic position point is calculated, and each characteristic position point in the basic pipe network model is translated based on the coordinate deviation value.

[0027] Further, for the step of updating the pipe network model, when the theoretical relative positions of some of the characteristic position points deviate, these characteristic position points are delimited as a local offset area. Taking the boundary points of the local offset area as control points, the displacement of the control points is adjusted according to the coordinate deviation value, and the grids within the area are deformed in the basic pipe network model through a grid deformation algorithm.

[0028] An underground pipe network modeling system based on characteristic position calibration includes:

[0029] A pipe network three-dimensional construction module, which retrieves the scene model in the record and constructs a basic pipe network model in the scene model according to the pipe network plane design drawing;

[0030] A flight path planning module, which selects characteristic position points in the pipe network plane design drawing and plans the flight path of the unmanned aerial vehicle according to the characteristic position points;

[0031] A detection data acquisition module, which acquires the scene images and pipe network data collected by the equipment carried on the unmanned aerial vehicle;

[0032] A pipe point data analysis module, which obtains the actual coordinates of the characteristic position points according to the scene images, selects pipe detection points as pipe points between two adjacent characteristic position points in the scene images, selects the reference objects around the pipe points in the scene images to analyze the road surface adjustment data, and analyzes the pipe network data at the pipe points through an anomaly detection strategy to obtain the pipe point state, where the pipe point state includes the normal state of the pipeline, the deformed state of the pipeline, and the settlement state of the pipeline;

[0033] A pipe network model update module, which updates the coordinates of the characteristic position points with the actual coordinates in the basic pipe network model, updates the burial depth of each pipe point in the basic pipe network model with the road surface adjustment data, and updates the states of each pipe point in the basic pipe network model according to the pipe point state and the pipe network data at the pipe point to obtain an accurate pipe network model.

[0034] Advantages of the present invention: Through steps such as three-dimensional basic modeling of the pipe network, flight path planning of the unmanned aerial vehicle, detection data collection, pipe point data analysis, and pipe network model update, the unmanned aerial vehicle is used to collect actual scene data, combined with feature position calibration and anomaly detection strategies, realizing the accurate construction and real-time update of the three-dimensional pipe network model, solving the problem that traditional modeling methods are difficult to accurately reflect the changes in the actual scene, improving the accuracy and practicality of the three-dimensional model of the underground pipe network, and realizing the real-time update of the pipe network status and the intelligent identification of abnormal situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is the overall flowchart in the present invention;

[0036] Figure 2 is the flowchart of road surface adjustment and reference object coverage area analysis in the present invention;

[0037] Figure 3 is the pipe network model diagram in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] The present invention will be further described in detail below with reference to the drawings and embodiments. The same reference numerals are used for the same components. It should be noted that the terms "front", "rear", "left", "right", "up" and "down" used in the following description refer to the directions in the drawings, and the terms "bottom surface" and "top surface", "inner" and "outer" refer to the directions towards or away from the geometric center of a specific component respectively.

[0039] The current three-dimensional modeling is only directly based on the data dimensions on the original plane drawings for modeling. However, the actual scene is prone to changes, resulting in the constructed model being difficult to accurately and intuitively match the actual scene, and unable to provide accurate pipe network layout information for inspection personnel and subsequent municipal planning. Therefore, the present invention designs this underground pipe network modeling method based on feature position calibration, as Figure 1-2 shown, including:

[0040] Steps for 3D modeling of pipe networks. First, from the existing record database, according to specific retrieval conditions, accurately retrieve the scene model corresponding to the current pipe network design area. This scene model is obtained and stored through previous geographical information collection, satellite remote sensing image processing, or other professional surveying and mapping means. It contains basic geographical information such as the terrain and landform, building distribution, and road orientation of the area. Based on the successfully retrieved scene model, gradually construct the pipe network basic model according to the pipe network plane design drawing. The pipe network plane design drawing details the information such as the orientation, pipe diameter size, node position, and connection relationship between different pipes of various pipe networks (such as water supply pipe network, drainage pipe network, gas pipe network, etc.). According to these design information, in the geographical space of the scene model, using professional 3D modeling software, by defining the spatial position, geometric shape, and topological relationship of each pipe network, transform the 2D plane design drawing into a 3D pipe network basic model.

[0041] As the basic data model for the entire pipe network detection and update process, the pipe network basic model provides accurate spatial position references and geometric shape information for subsequent steps such as flight path planning, data collection, and model update. It ensures that subsequent work can be closely carried out around the actual design situation of the pipe network, guaranteeing the accuracy and coherence of the entire detection process.

[0042] Steps for flight path planning. On the pipe network plane design drawing, carefully identify and select representative feature position points. These feature position points usually include the starting point, ending point, turning point, pipe diameter change point, node, and connection points with other important facilities (such as pump stations, valve wells, etc.) of the pipe network. Based on the selected feature position points, use existing path planning algorithms and UAV flight control software to plan a reasonable UAV flight path.

[0043] By planning the UAV flight path based on feature position points, it can ensure that the UAV accurately covers all key positions and areas in the pipe network during flight. This enables the data collected subsequently to comprehensively reflect the key information of the pipe network, avoiding data collection blind spots or missing important feature points.

[0044] In the detection data collection step, when the UAV flies according to the pre-planned flight path, various professional equipment carried by the UAV start working. Among them, the optical camera or other imaging equipment is responsible for collecting scene images around the pipeline network. These images record the actual situation of the environment in which the pipeline network is located, including the ground topography, building conditions, surrounding vegetation coverage and other information, providing an intuitive visual basis for the subsequent analysis of the relationship between the pipeline network and the surrounding environment and the actual location of the pipe points. At the same time, the carried pipeline detection equipment (such as underground pipeline detectors, lidar, etc.) collects data on the pipeline network itself. The pipeline network data is a detection map, which includes key parameter information such as the actual buried depth of the pipeline, pipeline contour points, and stress and strain.

[0045] The pipe point data analysis step is to obtain the actual coordinates of the feature position points based on the scene image. In the scene image, according to the distance between two adjacent feature position points and the direction of the pipeline, several pipeline detection points are evenly selected as pipe points according to certain rules. Then, in the scene image, objects with obvious characteristics and relatively stable (such as street light poles, fire hydrants, etc.) around the pipe points are carefully selected as reference objects. By analyzing the relationship between these reference objects and the position changes of the pipe points in the image, combined with topographic data and historical image data, it is determined whether the road surface at the location of the pipe point has been adjusted (such as construction changes, settlement, uplift, etc.), and the corresponding road surface adjustment data, such as road surface settlement, uplift height, etc., are calculated. The pipeline network data at the pipe point is analyzed through anomaly detection strategy to obtain the pipe point status, which includes the normal state of the pipeline, the deformation state of the pipeline, and the settlement state of the pipeline.

[0046] By accurately obtaining the actual coordinates of characteristic location points and analyzing the status of pipe points, the actual location of each pipe point in the pipeline network can be precisely determined in geographic space, and its operating status can be accurately assessed. Combined with road surface adjustment data and pipeline network data, it can be determined whether problems such as pipeline settlement or deformation may occur, thereby further updating the pipeline network model to provide an accurate pipeline network model.

[0047] Steps for updating the pipe network model: Update the coordinates of the feature position points of the actual coordinates in the basic pipe network model, and update the buried depth of each pipe point in the basic pipe network model with the road surface adjustment data. If the road surface around a certain pipe point has settled, according to the magnitude of the settlement, correspondingly reduce the buried depth value of this pipe point in the pipe network model; conversely, if the road surface bulges, increase the buried depth value of the pipe point. Update the status of each pipe point in the basic pipe network model according to the pipe point status and the pipe network data of this pipe point to obtain the accurate pipe network model. For the pipe points in the normal state of the pipeline, keep the corresponding attribute parameters in the model unchanged; for the pipe points in the deformed state of the pipeline, adjust its relevant geometric parameters such as pipe diameter in the model to visually display the deformation of the pipeline; for the pipe points in the settlement state of the pipeline, in addition to updating the buried depth, corresponding marks or color distinctions can also be added in the model (such as Figure 3 as shown), so as to clearly identify the pipe points in different states in the model, and finally obtain an accurate pipe network model that can accurately reflect the actual state of the pipe network.

[0048] By comprehensively updating the coordinates, buried depth, and status of the basic pipe network model, the obtained accurate pipe network model can highly accurately reflect the true state of the pipe network in the actual geographical environment. Whether it is the spatial position of the pipe network, the buried depth of the pipe points, or the operating status of the pipe points, they are all closely in line with the actual situation. As time goes by, the state of the pipe network will constantly change. By continuously updating the pipe network model, the state change situation of the pipe network at different times can be recorded, the aging trend and fault development law of the pipe network can be analyzed, which helps to formulate reasonable pipe network maintenance and update plans and optimize the operation of the pipe network.

[0049] As Figure 2 shown, the pipe point data analysis steps include a road surface analysis strategy, and the road surface analysis strategy includes a reference object analysis sub-step and a road surface analysis sub-step.

[0050] Reference object analysis sub-step: In the obtained scene image, select obvious and relatively stable objects around the pipe point, such as street lamp poles, fire hydrants, etc. as reference objects. Using professional image measurement technology, through the known image ratio relationship and relevant measurement algorithms, accurately measure the actual exposed height value of the reference object. At the same time, retrieve the recorded exposed height value corresponding to this reference object from the pre-constructed scene model, and compare the actually measured height value with the recorded value in the scene model. If the two values are the same, it means that the road surface around the reference object may not have changed significantly during this time period; if the two do not match, it means that there may be changes such as settlement and bulge on the road surface, and further road surface analysis sub-step is required;

[0051] Pavement analysis sub-step. When it is determined that further analysis of the pavement condition is required, interact with the municipal system database to retrieve the construction records of the location where the reference object is located. The municipal system database stores detailed information on various construction activities in the city, including construction time, location, construction content, etc. If the construction records are successfully retrieved, then analyze the relationship between the pavement construction data and the exposed change amount of the reference object. The pavement construction data may include information such as construction type (e.g., road renovation, underground facility laying, etc.), construction depth, construction scope, etc. Calculate the difference between the actually measured exposed height value and the value recorded in the scene model as the exposed change amount of the reference object. If the impact of the construction reflected in the pavement construction data on the pavement height is consistent with the exposed change amount of the reference object, for example, the construction record shows that a certain depth of pavement backfill has been carried out and the exposed height of the reference object has exactly decreased by the corresponding value, then it can be relatively certain that the pavement change is caused by this construction. At this time, the pavement construction data is used as the pavement adjustment data for updating the buried depth of the pipe point. On the contrary, if the two are inconsistent, it indicates the possibility of underground settlement or uplift, and it is necessary to further analyze whether the change area covers the pipe point. Combine the exposed change amount of the reference object with the pavement construction data, and use spatial analysis methods to determine the approximate range of the pavement change and judge whether this range covers the pipe points of concern. If the change area covers the pipe points, it is necessary to calculate the change amount of the pipe points under this change situation as the pavement adjustment data for updating the buried depth of the pipe points.

[0052] The pavement analysis strategy can avoid the limitations of making judgments based only on single data or simple comparison, comprehensively consider the actually measured data, scene model records, and municipal construction information, greatly improve the accuracy of pavement change judgment, and update the buried depth of the pipe points through the pavement adjustment data obtained based on scientific analysis, which can more accurately simulate the actual state of the pipe network underground and provide reliable basic data for the maintenance, repair, and planning of new projects of the pipe network.

[0053] As Figure 2 shown, the pavement analysis sub-step includes a pipe point coverage analysis sub-strategy. Analyze the change slope of the reference object according to the scene image (measure the vertical height difference and horizontal distance between different positions at the bottom of the reference object and the surrounding ground feature points, and use mathematical methods such as trigonometric functions to calculate the slope value of this area). Based on the obtained exposed change amount of the reference object (i.e., the difference between the actually measured exposed height value and the value recorded in the scene model) and the calculated change slope of the reference object, use relevant mathematical models to calculate the radius of the change area of the reference object, then calculate the straight-line distance between the reference object and the pipe point, and compare it with the radius of the change area of the reference object. If the radius of the change area of the reference object is greater than the straight-line distance, calculate the change amount at the pipe point within the change area of the reference object; assume that the projected distance between the pipe point and the reference object in the horizontal direction is , according to the change slope The exposed change amount of the reference object , which can be calculated by the formula to calculate the change amount at the pipe point .

[0054] By analyzing the change slope of the reference object, calculating the radius of the reference object's change area, and comparing it with the straight-line distance between the reference object and the pipe point, the influence range of road surface changes on the pipe point can be accurately defined. This method is based on scientific measurement and calculation, is more accurate and reliable. In a complex urban pipe network environment, there may be differences in road surface changes in different areas. Through this precise analysis method, it can be clearly determined whether each pipe point is affected by road surface changes, providing accurate basic data for subsequent pipe point status analysis and model update, which is crucial for updating the buried depth of pipe points in the pipe network model, ensuring that the model can truly reflect the actual state of the pipe network underground. Accurate pipe point change amount data helps pipe network managers more accurately evaluate the operation status of the pipe network.

[0055] The anomaly detection strategy includes a pipeline anomaly judgment sub-step and a pipeline status calculation sub-step.

[0056] The pipeline anomaly judgment sub-step determines whether the theoretical buried depth of the pipeline in the pipe network basic model under the modification of the road surface adjustment data is consistent with the actual buried depth of the pipeline (the theoretical pre-buried depth of the pipeline is the design depth in the pipe network basic model plus the road surface adjustment data). If they are consistent, the normal state of the pipeline is output; otherwise, the pipeline status calculation step is carried out.

[0057] The pipeline status calculation sub-step calculates the pipeline centerline offset and ellipticity respectively according to the actual pre-buried depth of the pipeline and the pipeline contour points. Among them, the pipeline centerline offset is obtained by comparing the actual centerline position of the pipeline (fitted according to the contour points) with the centerline position in the original design or normal state, and using methods such as coordinate calculation to obtain the offset distance value. The ellipticity is determined according to the distribution of the pipeline contour points, and the degree of deviation of the pipeline cross-sectional shape from a circle is determined through specific mathematical algorithms (such as calculating the ratio of the long axis to the short axis, etc.). Then, the pipeline centerline offset, ellipticity, stress and strain, and wall thickness are calculated through the pipeline deformation formula to obtain the pipeline deformation rate. The pipeline deformation rate is compared with the preset deformation threshold, and the pipeline status is output according to the comparison result. In the actual operation of the pipe network, the pipeline may be affected by various factors such as ground settlement, uneven soil pressure, and internal fluid pressure changes. Through this multi-parameter comprehensive calculation method, the anomaly degree of the pipeline can be more accurately evaluated, which plays a true and accurate role in the display of the pipe network three-dimensional model.

[0058] The pipeline deformation calculation formula is configured as:

[0059] ,

[0060] ,

[0061] wherein, is the offset of the pipeline center line, which measures whether the pipeline deviates from its original position, is the ovality of the pipeline surface, is the stress and strain of the pipeline, is the pipeline wall thickness, is the deformation rate of the pipeline, are the first constant, the second constant, the third constant, the fourth constant, and the fifth constant respectively, which are used to adjust the weights and ratios of each item in the deformation rate calculation, The deformation threshold.

[0062] The pipe point data analysis step includes a pipe point selection strategy. When it is found during the investigation that there are marker points such as pipe intersections and pipe alignment points between two adjacent characteristic position points, these marker points will be included in the selection range of pipe points due to their special significance in the pipe network system. A pipe intersection is the position where different pipes intersect. The connection, sealing, and mutual influence between pipes here are relatively complex, and it is a key part for monitoring the operation status of the pipe network; the pipe alignment point is related to the accuracy and continuity of pipe laying, and is used to judge the rationality of the overall layout of the pipe network and whether the pipes are displaced. In addition to including these marker points, a certain number of pipe detection points also need to be selected between two adjacent characteristic position points according to the principle of uniform distribution, so as to comprehensively cover the key parts and provide reasonable multi-point data for subsequent pipe updates.

[0063] In the pipe point data analysis step, the actual coordinates are longitude and latitude coordinates. The longitude and latitude coordinate information of the characteristic points is obtained by using the high-precision navigation satellite system receiver carried by the UAV. At the same time, combined with the inertial measurement unit data on the UAV, attitude compensation and dynamic correction are performed on the obtained longitude and latitude coordinates to improve the accuracy of the coordinates. The actual relative position is judged according to the longitude and latitude coordinates of two adjacent characteristic position points, and the theoretical relative position of the same two characteristic position points in the pipe network basic model is updated through the actual relative position. There are two situations that need to be updated separately. One is the overall offset, and it can be updated by the way of overall translation. The other is the partial deviation, and it can be updated by the way of local offset.

[0064] Specifically, the way of overall offset is as follows: in the pipe network model update step, when the theoretical relative position deviation of each two adjacent characteristic position points is the same, calculate the coordinate deviation value of any one characteristic position point, and translate each characteristic position point in the pipe network basic model based on the coordinate deviation value.

[0065] Specifically, the method of local offset is as follows: in the step of updating the pipe network model, when there are theoretical relative position deviations of some of the feature position points, these feature position points are delimited as a local offset area. Taking the boundary points of the local offset area as control points, the displacement of the control points is adjusted according to the coordinate deviation value, and the grids within the area are deformed through a grid deformation algorithm in the basic pipe network model.

[0066] The above are only the preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the idea of the present invention belong to the protection scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. An underground pipeline network modeling method based on feature position calibration, characterized in that: Including: Steps for three-dimensional modeling of the pipe network, retrieving the scene model in the record, and constructing a basic pipe network model in the scene model according to the pipe network plane design drawing; Steps for flight path planning, selecting characteristic position points in the pipe network plane design drawing, and planning the UAV flight path according to the characteristic position points; Steps for detecting data acquisition, obtaining the scene images and pipe network data collected by the equipment carried on the UAV; Steps for analyzing pipe point data, obtaining the actual coordinates of the characteristic position points according to the scene images, selecting pipe detection points between two adjacent characteristic position points in the scene images as pipe points, selecting the reference objects around the pipe points in the scene images to analyze the road surface adjustment data, and analyzing the pipe network data at the pipe points through an anomaly detection strategy to obtain the pipe point state, where the pipe point state includes the normal state of the pipeline, the deformed state of the pipeline, and the settlement state of the pipeline; Steps for updating the pipe network model, updating the coordinates of the characteristic position points in the basic pipe network model with the actual coordinates, updating the buried depth of each pipe point in the basic pipe network model with the road surface adjustment data, and updating the state of each pipe point in the basic pipe network model according to the pipe point state and the pipe network data at the pipe point to obtain an accurate pipe network model; The pipe network data is a detection map, which includes the actual buried depth of the pipeline, the pipeline contour points, and the stress and strain, and the anomaly detection strategy includes a pipeline anomaly judgment sub-step and a pipeline state calculation sub-step. The pipeline anomaly judgment sub-step, judging whether the theoretical buried depth of the pipeline in the basic pipe network model under the modification of the road surface adjustment data is consistent with the actual buried depth of the pipeline. If they are consistent, the normal state of the pipeline is output. Otherwise, the pipeline state calculation step is performed; The pipeline state calculation sub-step, calculating the pipeline center line offset and ellipticity according to the actual pre-buried depth and pipeline contour points of the pipeline respectively, and then calculating the pipeline deformation rate through the pipeline deformation formula with the pipeline center line offset, ellipticity, stress and strain, and pipe wall thickness, comparing the pipeline deformation rate with a preset deformation threshold, and outputting the pipeline state according to the comparison result; The pipeline deformation calculation formula is configured as: ， ， Among them, is the offset of the pipeline center line, is the ovality of the pipeline surface, is the stress and strain of the pipeline, is the pipeline wall thickness, is the deformation rate of the pipeline, are the first constant, the second constant, the third constant, the fourth constant, and the fifth constant respectively, is the deformation threshold.

2. The underground pipe network modeling method based on feature position calibration according to claim 1, wherein: The steps for analyzing pipe point data include a road surface analysis strategy, and the road surface analysis strategy includes a reference object analysis sub-step and a road surface analysis sub-step. The reference object analysis sub-step, measuring the actual exposed height value of the reference object according to the scene image, comparing the actual exposed height value with the recorded exposed height value of the reference object in the scene model. If they do not match, the road surface analysis sub-step is performed; The road surface analysis sub-step, retrieving the construction record at the reference object in the municipal system. If the retrieval is successful, analyzing whether the road surface construction data is consistent with the exposed change amount of the reference object. If they are consistent, the road surface construction data is used as the road surface adjustment data for updating the buried depth of the pipe point. Otherwise, analyzing whether the change area covers the pipe point by combining the exposed change amount of the reference object and the road surface construction data. If so, the calculated change amount of the pipe point is used as the road surface adjustment data for updating the buried depth of the pipe point.

3. The method for modeling an underground pipe network based on feature position calibration according to claim 2, characterized in that: The pavement analysis sub-step includes a pipe point coverage analysis sub-strategy. According to the scene image, the slope change of the reference object is analyzed. Based on the exposed change amount of the reference object and the slope change of the reference object, the radius of the reference object change area is calculated. Then, the straight-line distance between the reference object and the pipe point is calculated and compared with the radius of the reference object change area. If the radius of the reference object change area is greater than the straight-line distance, the change amount at the pipe point within the reference object change area is calculated.

4. The underground pipe network modeling method based on feature position calibration according to claim 1, characterized in that: The pipe point data analysis step includes a pipe point selection strategy. The pipe point selection strategy includes that when there are marked points such as pipe intersections and pipe alignment points between two adjacent characteristic position points, the marked points and the pipe detection points evenly selected between the two adjacent characteristic position points are jointly used as pipe points.

5. The underground pipe network modeling method based on feature position calibration according to claim 4, wherein: The pipe network model update step. The actual coordinates are longitude and latitude coordinates. According to the longitude and latitude coordinates of two adjacent characteristic position points, the actual relative position is judged, and the theoretical relative position of the same two characteristic position points in the pipe network basic model is updated through the actual relative position.

6. The underground pipe network modeling method based on feature position calibration according to claim 5, characterized in that: In the pipe network model update step, when the theoretical relative position deviation of every two adjacent characteristic position points is the same, the coordinate deviation value of any one characteristic position point is calculated, and each characteristic position point in the pipe network basic model is translated based on the coordinate deviation value.

7. The method for modeling an underground pipe network based on feature position calibration according to claim 6, wherein: In the pipe network model update step, when the theoretical relative position of some of the characteristic position points deviates, these characteristic position points are designated as a local offset area. Taking the boundary points of the local offset area as control points, the displacement of the control points is adjusted according to the coordinate deviation value, and the grid within the area is deformed in the pipe network basic model through the grid deformation algorithm.

8. An underground pipe network modeling system based on feature position calibration, characterized in that: including A pipe network three-dimensional construction module, which retrieves the scene model in the record and constructs a pipe network basic model according to the pipe network plane design drawing in the scene model; A flight path planning module, which selects characteristic position points in the pipe network plane design drawing and plans the flight path of the unmanned aerial vehicle according to the characteristic position points; A detection data acquisition module, which acquires the scene image and pipe network data collected by the equipment carried on the unmanned aerial vehicle; A pipe point data analysis module, which obtains the actual coordinates of the characteristic position points according to the scene image, selects the pipe detection points between two adjacent characteristic position points in the scene image as pipe points, selects the reference objects around the pipe points in the scene image to analyze the pavement adjustment data, and analyzes the pipe network data at the pipe points through an anomaly detection strategy to obtain the pipe point state. The pipe point state includes the normal state of the pipeline, the deformation state of the pipeline, and the settlement state of the pipeline; A pipe network model update module, which updates the coordinates of the characteristic position points with the actual coordinates in the pipe network basic model, updates the buried depth of each pipe point in the pipe network basic model with the pavement adjustment data, and updates the state of each pipe point in the pipe network basic model according to the pipe point state and the pipe network data of the pipe point to obtain an accurate pipe network model; The pipe network data is a detection map, which includes the actual buried depth of the pipeline, the pipeline contour points, and the stress and strain. The anomaly detection strategy includes a pipeline anomaly judgment sub-step and a pipeline state calculation sub-step. The abnormal pipeline judgment sub-step determines whether the theoretical buried depth of the pipeline in the pipe network basic model under the modification of the road surface adjustment data is consistent with the actual buried depth of the pipeline. If they are consistent, the normal state of the pipeline is output; otherwise, the pipeline state calculation step is performed; The pipeline state calculation sub-step calculates the pipeline center line offset and ellipticity respectively according to the actual pre-buried depth of the pipeline and the pipeline profile points, and then calculates the pipeline deformation rate through the pipeline deformation formula with the pipeline center line offset, ellipticity, stress-strain and pipe wall thickness. The pipeline deformation rate is compared with the preset deformation threshold, and the pipeline state is output according to the comparison result; The pipeline deformation calculation formula is configured as: ， ， Among them, is the offset of the pipeline center line, is the ovality of the pipeline surface, is the stress and strain of the pipeline, is the pipeline wall thickness, is the deformation rate of the pipeline, are the first constant, the second constant, the third constant, the fourth constant and the fifth constant respectively, is the deformation threshold.

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