A sewer three-dimensional laser scanning detection method

Abstract

The application belongs to the technical field of urban drainage pipe and channel detection, and discloses a three-dimensional laser scanning detection method for drainage pipes and channels. The method comprises eight steps of establishing a preliminary pipe and channel three-dimensional design model, mastering the internal condition of the drainage pipe and channel, classifying the drainage pipes according to the internal condition of the drainage pipe and channel according to the complexity of the pipe and channel, selecting a corresponding three-dimensional laser scanning operation mode according to the classification, laying a positioning target, obtaining the three-dimensional coordinates of the positioning target, implementing three-dimensional laser scanning detection, processing detection data, and extracting and identifying detection result information. The method gives corresponding operation modes under different working conditions, can realize the acquisition of three-dimensional information of the pipe and channel space, realizes the double improvement of detection efficiency and result quality through model lightweight transformation, can effectively detect the changes of complex large-diameter drainage pipes and channels, and the detection result can be used as a basis for the treatment design of the drainage pipe and channel, which has important significance for ensuring the safe operation of urban drainage.

Description

Technical Field

[0001] This invention belongs to the field of urban drainage pipe and channel inspection technology, specifically relating to a three-dimensional laser scanning inspection method for drainage pipes and channels. Background Technology

[0002] Drainage pipes are a crucial part of urban infrastructure, and their structural stability and functional integrity are essential for ensuring urban drainage safety. Scientific testing is a powerful means of verifying this assurance. Drainage pipes are enclosed, limited spaces, and commonly used testing methods such as pipe periscopes (QV) and closed-circuit television (CCTV) are employed to capture two-dimensional images, aiding in understanding the internal conditions of the pipes, such as misconnections, outlet depth, and defects. However, two-dimensional images can only detect planar information and suffer from drawbacks such as missing depth information and inaccurate judgments. This is especially true for complex pipe structures and large diameter pipes, where internal structural obstructions and image divergence make it difficult to obtain clear outlines and extract effective information. Furthermore, achieving measurement and positioning within drainage pipes with complex environments such as poor ventilation, complex gas composition, siltation, and narrow inlets and outlets is even more challenging, failing to meet the final testing requirements for complex structures and large-diameter drainage pipes.

[0003] This leads to the introduction of non-contact 3D laser scanning technology, which simultaneously acquires high-density 3D point clouds, 2D images, reflection intensity, and other information within drainage pipes and channels. The large amount of information collected is undoubtedly very beneficial for information extraction and recognition, but the massive amount of data also reduces the efficiency of processing the detection results. Summary of the Invention

[0004] The purpose of this invention is to provide a three-dimensional laser scanning detection method for drainage pipes and channels, providing a reliable method for three-dimensional detection of complex large-diameter drainage pipes and channels, and overcoming the shortcomings of two-dimensional image detection, which is difficult to detect due to internal structure occlusion and image divergence.

[0005] The technical solution adopted in this invention is a three-dimensional laser scanning detection method for drainage pipes and channels, which includes the following steps:

[0006] Step 1: Establish a preliminary three-dimensional design model for the pipeline;

[0007] Step 2: Assess the internal condition of the drainage pipes and channels;

[0008] Step 3: Classify the drainage pipes according to their complexity based on the internal condition of the drainage pipes and channels described in Step 2.

[0009] Step 4: Select the appropriate 3D laser scanning operation method based on the classification in Step 3;

[0010] Step 5: Deploy the positioning target and obtain its three-dimensional coordinates;

[0011] Step 6: Perform 3D laser scanning inspection;

[0012] Step 7, Data Processing;

[0013] Step 8: Extraction and recognition of detection result information.

[0014] Further, step 1 specifically includes the following steps: collecting the original design drawings and as-built drawings of the pipeline to be inspected; establishing a preliminary three-dimensional design model of the pipeline based on the dimensions of the original design drawings and the as-built drawings; and further determining the center line of the bottom plane of the pipeline and the central axis of the pipeline space from the three-dimensional design model.

[0015] Furthermore, the classification results of step 3 are as follows:

[0016] Category I of pipeline complexity: Clear height not less than 1.3m, clear width not less than 1.0m, flow velocity not greater than 0.5m / s, water depth not greater than 0.5m, and all requirements for columns or obstacles are met;

[0017] Category II complexity of pipelines and channels: Clear height not less than 1.0m, clear width not less than 1.0m, water depth not greater than 0.1m, and no columns or obstacles are all met;

[0018] Class III complexity of pipework: Clear height not less than 1.0m, clear width not less than 1.0m, water depth 0.1m to 0.5m, and no columns or obstacles are all met;

[0019] Category IV of the complexity of pipelines and channels: Clear height not less than 2.0m, clear width not less than 2.0m, fullness not greater than 20% of the cross-section, and no columns or obstacles are required.

[0020] Furthermore, the three-dimensional laser scanning operation methods in step 4 include: fixed three-dimensional laser scanning, handheld SLAM three-dimensional laser scanning, tracked SLAM three-dimensional laser scanning, wheeled SLAM three-dimensional laser scanning, ship-mounted SLAM three-dimensional laser scanning, amphibious SLAM three-dimensional laser scanning, and UAV SLAM three-dimensional laser scanning.

[0021] Furthermore, the Class I complex pipelines employ one or a combination of fixed 3D laser scanning and handheld SLAM 3D laser scanning methods.

[0022] The Class II complexity pipelines shall employ one or a combination of several of the following operational methods: tracked SLAM 3D laser scanning, wheeled SLAM 3D laser scanning, and amphibious SLAM 3D laser scanning.

[0023] For Class III complexity pipelines, one or a combination of ship-based SLAM 3D laser scanning and amphibious SLAM 3D laser scanning methods shall be selected;

[0024] For Class IV complex pipelines, UAV SLAM three-dimensional laser scanning was selected.

[0025] Furthermore, step 6, which involves implementing three-dimensional laser scanning detection, specifically includes the following steps: importing path trajectory data into the controller, setting scanning detection parameters and remote connection control, and starting the scanning to acquire spatial information data through remote control.

[0026] Furthermore, the path trajectory data includes the preliminary three-dimensional design model, the center line of the pipeline bottom plane, and the center line of the pipeline bottom plane.

[0027] Furthermore, the spatial information data includes three-dimensional point clouds, two-dimensional images, and laser reflection intensity.

[0028] Further, step 7 specifically includes the following steps: generating a three-dimensional point cloud of the culvert wall based on the scanning detection data, generating a reflection intensity image based on the three-dimensional point cloud, establishing a mapping fusion between the reflection intensity image and the two-dimensional image through geometric relationships, performing coordinate transformation on the data of the three-dimensional point cloud, the reflection intensity image, and the two-dimensional image by locating the three-dimensional coordinates of the target, and establishing a three-dimensional real-scene model of the culvert based on the coordinate transformed data.

[0029] Further, step 8 specifically includes the following steps: flattening the three-dimensional real-scene model of the pipeline in a counterclockwise direction from the left side of the water flow direction according to the actual shape to form a pipeline flattening diagram; then combining the three-dimensional point cloud, the three-dimensional real-scene model of the pipeline, and the pipeline flattening diagram with the three-dimensional design model of the pipeline to obtain a change cloud map; finally, assessing the defect type and level and extracting the location coordinates.

[0030] The beneficial effects of this invention are as follows:

[0031] This invention has the advantage of being able to effectively detect defects in complex, large-diameter drainage pipes, overcoming the shortcomings of two-dimensional image detection, which is difficult to perform due to internal structural obstruction and image divergence. By providing corresponding operating methods under different working conditions, it is possible to acquire three-dimensional information of the pipe space, process the data to generate visualized two-dimensional and three-dimensional product results, thereby achieving more efficient pipe defect detection.

[0032] This invention achieves lightweight processing by transforming massive point cloud data into models, not only overcoming the drawbacks of large computational demands when large amounts of point cloud data are involved in the detection process, but also improving the efficiency and quality of 3D laser point cloud detection. Using this invention, changes in complex, large-diameter drainage pipes can be effectively detected, and the detection results can serve as a basis for drainage pipe management design, which is of great significance for ensuring the safe operation of urban drainage. Attached Figure Description

[0033] Figure 1 This is a flowchart illustrating the method of the present invention. Detailed Implementation

[0034] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0035] See Figure 1 The method of the present invention specifically includes the following steps:

[0036] Step 1: Establish a preliminary three-dimensional design model for the pipeline;

[0037] Step 2: Assess the internal condition of the drainage pipes and channels;

[0038] Step 3: Classify the drainage pipes according to their complexity based on the internal condition of the drainage pipes and channels described in Step 2.

[0039] Step 4: Select the appropriate 3D laser scanning operation method based on the classification in Step 3;

[0040] Step 5: Deploy the positioning target and obtain its three-dimensional coordinates;

[0041] Step 6: Perform 3D laser scanning inspection;

[0042] Step 7, Data Processing;

[0043] Step 8: Extraction and recognition of detection result information.

[0044] Specifically, step 1 includes the following steps: collecting the original design drawings and as-built drawings of the pipeline to be inspected; establishing a preliminary three-dimensional design model of the pipeline based on the dimensions of the original design drawings and the as-built drawings; and further determining the center line of the bottom plane of the pipeline and the central axis of the pipeline space from the three-dimensional design model.

[0045] Specifically, step 2 includes the following steps: conducting on-site inspections of the surrounding environment, traffic, pipeline direction, distribution and number of inspection wells, and opening the inspection wells to use a low-light camera system in conjunction with a mud probe or depth sounding rod to understand the siltation, water depth, flow velocity, internal structure and environmental conditions related to personnel entry within the culvert.

[0046] Specifically, step 3 includes the following steps: Based on the analysis of the internal characteristics of the drainage pipes and channels in step 2, such as net height, net width, flow velocity, water depth, and fullness, the pipes and channels are classified into four categories according to their complexity:

[0047] The Class I complexity of the pipeline is defined as follows: net height not less than 1.3m, net width not less than 1.0m, flow velocity not greater than 0.5m / s, water depth not greater than 0.5m, and the presence of columns or obstacles.

[0048] Category II of the complexity of the pipeline is defined as follows: the net height is not less than 1.0m, the net width is not less than 1.0m, the water depth is not greater than 0.1m, and there are no columns or obstacles.

[0049] Class III for the complexity of pipe channels is defined as follows: net height not less than 1.0m, net width not less than 1.0m, water depth 0.1m to 0.5m, and no columns or obstacles.

[0050] Class IV of the complexity of pipelines and channels is defined as follows: net height not less than 2.0m, net width not less than 2.0m, fullness not greater than 20% of the cross-section, and no columns or obstacles.

[0051] Specifically, step 4 includes the following steps: Based on the classification results of the complexity of the pipeline in step 3, select the appropriate three-dimensional laser scanning operation method. This can be a fixed-station three-dimensional laser scanner operated by personnel entering the culvert, a handheld SLAM three-dimensional laser scanner, or an externally remotely controlled SLAM three-dimensional laser scanner carried by a self-driving tracked, wheeled, ship-type, amphibious, or drone-type vehicle.

[0052] The aforementioned three-dimensional laser scanning methods include fixed three-dimensional laser scanning, handheld SLAM three-dimensional laser scanning, tracked SLAM three-dimensional laser scanning, wheeled SLAM three-dimensional laser scanning, ship-mounted SLAM three-dimensional laser scanning, amphibious SLAM three-dimensional laser scanning, and UAV SLAM three-dimensional laser scanning.

[0053] The aforementioned SLAM 3D laser scanner is a 3D laser scanner that uses SLAM technology; SLAM stands for Simultaneous Localization and Mapping.

[0054] The aforementioned 3D laser scanner is a small, lightweight, portable or easy-to-install scanning device with a vertical field of view greater than 300°, and is equipped with an illumination system.

[0055] For Class I complex pipes and channels, one or a combination of fixed 3D laser scanning and handheld SLAM 3D laser scanning methods are suitable; when there are obvious distinguishing features inside the culvert, handheld SLAM 3D laser scanning method is preferred.

[0056] For Class II complexity pipe channels, one or more of the following methods are suitable: tracked SLAM 3D laser scanning, wheeled SLAM 3D laser scanning, and amphibious SLAM 3D laser scanning. When there is a large area of ​​silt deposit in the culvert, tracked SLAM 3D laser scanning is preferred. When there is no silt deposit in the culvert, wheeled SLAM 3D laser scanning is preferred.

[0057] For Class III complexity pipe channels, one or a combination of ship-based SLAM 3D laser scanning and amphibious SLAM 3D laser scanning methods are suitable; when the water depth inside the culvert is between 0.3m and 0.5m, ship-based SLAM 3D laser scanning method is preferred.

[0058] For Class IV complex pipelines, the SLAM three-dimensional laser scanning method using unmanned aerial vehicles (UAVs) is suitable; the UAVs must have anti-collision capabilities.

[0059] Specifically, step 5 includes the following steps: setting up a positioning target, extending the plumb bob of the positioning target into the culvert through the inspection well, establishing a connection with the ground marker, so as to facilitate the determination of the three-dimensional coordinates of the positioning target using GNSS or a total station;

[0060] Specifically, step 6 includes the following steps: Implementing three-dimensional laser scanning detection: Importing the design path trajectory data into the controller, setting the scanning detection parameters and remote connection control, and starting the scanning to obtain spatial information data through remote control.

[0061] The determination of path trajectory data is divided into the following two types:

[0062] For SLAM 3D laser scanning of tracked, wheeled, ship-type, and amphibious vehicles, the process includes the preliminary 3D design model of the pipeline and the centerline of the pipeline bottom plane; the vehicle travels along the predetermined centerline of the pipeline bottom plane.

[0063] For UAV SLAM 3D laser scanning, it includes the preliminary 3D design model of the pipeline and the central axis of the pipeline space; the UAV flies along the predetermined central axis of the pipeline space.

[0064] The scanning and detection parameters in step 6 include parameters such as scanning distance, resolution, and dot spacing density.

[0065] The spatial information data in step 6 includes three-dimensional point clouds, two-dimensional images, laser reflection intensity, etc. Furthermore, the point clouds and images should be acquired simultaneously.

[0066] Specifically, step 7 includes the following steps: generating a three-dimensional point cloud of the culvert wall based on the scan detection data, generating a reflection intensity image based on the three-dimensional point cloud, establishing a mapping and fusion between the reflection intensity image and the two-dimensional image through geometric correspondence, performing coordinate transformation on the data of the three-dimensional point cloud, reflection intensity image, and two-dimensional image by locating the three-dimensional coordinates of the target, and establishing a three-dimensional real-scene model of the culvert based on the coordinate transformed data.

[0067] Specifically, step 8 includes the following steps: The 3D real-world model obtained in step 7 is flattened counter-clockwise from the left side of the water flow direction according to its actual shape, forming a pipe and channel flattening diagram. For example, a rectangular pipe and channel is flattened as the left wall - top wall - right wall - culvert bottom, and a circular pipe and channel is flattened as the plane of the left side line - top axis line - right side line. Further, the 3D point cloud, the 3D real-world model of the pipe and channel, and the pipe and channel flattening diagram are combined with the 3D design model of the pipe and channel to obtain a change cloud map. Finally, it is determined whether there are any defects. If defects are found, the defect type and level are further evaluated, and the location coordinates are extracted.

Claims

1. A sewer channel three-dimensional laser scanning detection method, characterized in that, The method comprises the following steps: Step 1, establishing a preliminary pipe channel three-dimensional design model; Step 2, mastering the internal situation of the drainage pipe channel; Step 3, classifying the drainage pipe according to the internal situation of the drainage pipe channel in step 2 according to the complexity of the pipe channel; the classification at least includes: Class I of pipe channel complexity: net height not less than 1.3m, net width not less than 1.0m, flow velocity not greater than 0.5m / s, water depth not greater than 0.5m, all columns or obstacles meet; Class II of pipe channel complexity: net height not less than 1.0m, net width not less than 1.0m, water depth not greater than 0.1m, no column or obstacle meets; Class III of pipe channel complexity: net height not less than 1.0m, net width not less than 1.0m, water depth 0.1m-0.5m, no column or obstacle meets; Class IV of pipe channel complexity: net height not less than 2.0m, net width not less than 2.0m, fullness not greater than 20% of the cross section, no column or obstacle meets; Step 4, selecting the corresponding three-dimensional laser scanning operation mode according to the classification of step 3, wherein: the Class I pipe channel of complexity selects one or a combination of the two of the fixed three-dimensional laser scanning, handheld SLAM three-dimensional laser scanning operation mode; The Class II pipe channel of complexity selects one or a combination of several of the tracked SLAM three-dimensional laser scanning, wheeled SLAM three-dimensional laser scanning, amphibious SLAM three-dimensional laser scanning operation mode; The Class III pipe channel of complexity selects one or a combination of the two of the ship SLAM three-dimensional laser scanning, amphibious SLAM three-dimensional laser scanning operation mode; The Class IV pipe channel of complexity selects the unmanned aerial vehicle SLAM three-dimensional laser scanning operation mode; Step 5, laying out positioning targets and obtaining three-dimensional coordinates of the positioning targets; Step 6, implementing three-dimensional laser scanning detection; Step 7, detection data processing; Specifically comprising the following steps: generating a pipe channel wall surface three-dimensional point cloud according to the scanning detection data, generating a reflection intensity image based on the three-dimensional point cloud, establishing a mapping fusion of the reflection intensity image and the two-dimensional image through geometric relationship correspondence, and performing coordinate conversion of the data of the three-dimensional point cloud, the reflection intensity image and the two-dimensional image through the three-dimensional coordinates of the positioning targets, and establishing a pipe channel three-dimensional real scene model of the coordinate-converted data; Step 8, detection result information extraction and identification Specifically comprising the following steps: the pipe channel three-dimensional real scene model is flattened in the actual shape counterclockwise from the left of the water flow direction to form a pipe channel flattened graph, then the three-dimensional point cloud, the pipe channel three-dimensional real scene model and the pipe channel flattened graph are combined and compared with the pipe channel three-dimensional design model to obtain a change cloud graph, and finally the defect type and grade are evaluated and the position coordinates are extracted.

2. The sewer three-dimensional laser scanning detection method according to claim 1, wherein, The step 1 specifically comprises the following steps: collecting original design drawings and as-built drawing technical data of the pipe channel to be detected, establishing a preliminary pipe channel three-dimensional design model according to the original design drawing size and the as-built drawing, and further determining the pipe channel bottom plane center line and the pipe channel space center axis from the three-dimensional design model.

3. The sewer pipe three-dimensional laser scanning detection method according to claim 2, characterized in that, The step 6 of implementing the three-dimensional laser scanning detection specifically comprises the following steps: importing path trajectory data in the controller, setting scanning detection parameters and remote connection control, and starting scanning to obtain spatial information data through remote control.

4. The sewer pipe three-dimensional laser scanning detection method according to claim 3, characterized in that, The path trajectory data comprises the preliminary pipe trench three-dimensional design model, the pipe trench bottom plane center line and the pipe trench space center axis.

5. The sewer pipe three-dimensional laser scanning detection method according to claim 3, wherein, The spatial information data comprises three-dimensional point cloud, two-dimensional image and laser reflection intensity.

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