System and method for automatically measuring pipe network parameters based on three-dimensional scanning of wellhead of inspection well

Abstract

The invention discloses a system and a method for automatically measuring pipe network parameters based on three-dimensional scanning of a wellhead of an inspection well, and belongs to the technical field of municipal engineering measurement. The system comprises a wellhead fixing assembly, a three-dimensional laser scanning assembly, a posture sensing assembly, a distance measuring assembly, a coordinate input assembly, a control processing assembly and a telescopic rod assembly. According to the method, through system deployment leveling, coordinate reference establishment, working condition judgment, point cloud acquisition, data processing and result output, automatic measurement of inspection well depth, pipe network pipe diameter, pipeline trend and pipe orifice center coordinates is realized. The system is fixed at a wellhead, does not need to descend, and adapts to scenes such as shallow wells / deep wells and good / weak signal areas; based on a high-density point cloud and an automatic algorithm, the measurement precision is high, the efficiency is improved, and output data can be directly used for pipe network modeling. The method solves the problems of low efficiency, strong manual dependence and poor safety of traditional measurement, and is suitable for parameter measurement of various inspection wells and pipe networks.

Description

Technical Field

[0001] This invention relates to the field of municipal engineering surveying technology, and in particular to an automatic measurement system and method for pipeline parameters based on three-dimensional scanning of manhole openings. Background Technology

[0002] In the field of municipal engineering, the measurement of parameters for manholes and pipe networks is a crucial foundation for pipe network maintenance, renovation, and new construction projects. The measured parameters mainly include manhole depth, pipe diameter, pipe direction, and pipe inlet center coordinates. Traditional manhole and pipe network parameter measurement primarily relies on equipment such as total stations and levels, employing a manual, point-by-point measurement method. Workers must first set up measuring prisms at the manhole opening or inside the manhole, then repeatedly aim the total station at the prisms to obtain discrete coordinates of the manhole opening, wall, bottom, and pipe inlet, before manually calculating parameters such as pipe diameter and depth.

[0003] This traditional measurement method has many drawbacks: First, it has extremely low measurement efficiency. Measuring a single manhole requires multiple manual aiming and prism adjustments, with each measurement typically taking 15 to 30 minutes, making it impossible to obtain complete data on the manhole and pipeline network in one go. Second, it is highly dependent on manual labor. In some scenarios, workers need to enter the manhole to set up the prism, where there may be risks such as toxic and harmful gases, oxygen deficiency, and water accumulation, seriously threatening the safety of workers. At the same time, manual parameter input and calculation are prone to introducing human error, and water mist and dust inside the manhole can interfere with the ranging accuracy. Third, it has poor data integrity. It can only output discrete coordinate points and cannot directly obtain parameters such as pipeline direction and continuous coordinates of pipe openings, requiring secondary calculations and derivations, which further increases the error. Fourth, it has limited measurement accuracy. Traditional equipment cannot fully scan deformed manhole walls, obstructed pipe openings, or bends, making it difficult to detect hidden defects, resulting in measurement data that cannot reflect the true state of the manhole and pipeline network. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an automatic measurement system and method for pipeline network parameters based on three-dimensional scanning of manhole openings. This system eliminates the need for personnel to enter the well or move equipment, and can acquire multiple key parameters of the manhole and connected pipeline network through a single scan, thereby automating and increasing the efficiency of the measurement process while improving measurement accuracy and operational safety.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: An automatic pipeline parameter measurement system based on 3D scanning of manhole openings includes a manhole fixing component, a 3D laser scanning component, an attitude sensing component, a distance measurement component, a coordinate input component, and a control processing component. The manhole fixing component secures the entire system to the manhole opening and is adaptable to manhole openings of different sizes. The 3D laser scanning component scans the interior of the manhole and the connected pipeline network to acquire 3D point cloud data. The attitude sensing component measures the system's own attitude information to assist in pipeline routing calculations. The distance measurement component obtains distance data from the manhole opening to the bottom of the manhole or the water surface. The system provides the initial depth measurement; the coordinate input component is used to establish the association between the measurement data and the geographic coordinate system; the control processing component is used to control the collaborative work of each component, process the three-dimensional point cloud data and attitude information, and automatically output the manhole depth, the diameter of the connected pipe network, the pipe direction, the center coordinates of each pipe opening in the manhole, and the three-dimensional model or point cloud inside the manhole; the system can switch between the working mode without telescopic rod and the working mode with telescopic rod according to the actual situation of the manhole and the pipe network, realize the adaptive measurement of pipeline parameters, calculate the hydraulic gradient by combining the water surface elevation data of multiple manholes, and then deduce the pipeline flow velocity and flow rate.

[0006] Furthermore, the coordinate input component integrates an RTKGNSS module, which can acquire geographic coordinates with centimeter-level accuracy in real time. The coordinate input component is also equipped with a wellhead automatic positioning target recognition sub-component, which includes pre-laid magnetic QR code targets. When the RTKGNSS module signal is weak, the coordinates are obtained by recognizing the magnetic QR code targets. Moreover, the control processing component can integrate the data from the RTKGNSS module and the wellhead automatic positioning target recognition sub-component through a data fusion algorithm.

[0007] Furthermore, it also includes a telescopic rod assembly, which is connected to the wellhead fixing assembly and is used to lower the three-dimensional laser scanning assembly in the telescopic rod working mode; the telescopic rod assembly is a multi-section electric telescopic structure that can realize length adjustment, and its end can be equipped with the three-dimensional laser scanning assembly and auxiliary attitude sensing sub-assemblies; the telescopic rod assembly is also equipped with anti-collision sub-assemblies and limiting sub-assemblies to avoid collision with the well wall.

[0008] Furthermore, the telescopic pole assembly is made of carbon fiber, with a length adjustment range of 0 to 10m and a diameter of less than 200mm; the telescopic pole assembly is driven by a servo motor with gear transmission, and the lowering speed is 0.5m / s; the telescopic pole assembly has an internal cavity for laying power lines and data lines.

[0009] Furthermore, the three-dimensional laser scanning component is a multi-beam lidar or a panoramic laser scanner, with the scanning direction facing downwards, capable of performing a 360° scan of the inside of the inspection well, and acquiring a three-dimensional point cloud data density greater than 10,000 points / second; the three-dimensional laser scanning component uses a 905nm near-infrared wavelength laser and has a power adjustment function; the attitude sensing component includes a high-precision IMU and an electronic compass, the high-precision IMU is used to measure the system's pitch angle, roll angle, and yaw angle, and the electronic compass is used to assist in measuring azimuth information.

[0010] Furthermore, the control processing component includes a high-performance embedded computer, and the processing algorithms running on the high-performance embedded computer include a point cloud preprocessing algorithm, a manhole structure identification and segmentation algorithm, a pipe opening identification and segmentation algorithm, a pipe parameter calculation algorithm, and a result fusion output algorithm. The point cloud preprocessing algorithm is used to perform noise reduction, filtering, registration, and coordinate system unification processing on the 3D point cloud data. The manhole structure identification and segmentation algorithm is used to identify the manhole wall and bottom and segment the corresponding point cloud regions. The pipe opening identification and segmentation algorithm is used to identify the pipe inlet and segment the point cloud regions of the pipe opening and connected pipes. The pipe parameter calculation algorithm is used to calculate the pipe diameter, the center coordinates of the pipe opening, and the pipe direction. The result fusion output algorithm is used to integrate all parameters and generate a structured data report.

[0011] Furthermore, in the pipeline parameter calculation algorithm, the pipe diameter is calculated by performing a circular fitting on the pipe inlet point cloud, using the RANSAC algorithm or the least squares method; the pipe inlet center coordinates are calculated by the pipe inlet point cloud or the fitted circle; the pipeline orientation includes azimuth and slope, the azimuth is calculated by the projection direction of the fitted pipeline central axis onto the horizontal plane, and the calculation formula is α=arctan(ΔY / ΔX), where ΔX and ΔY are the coordinate differences of two points on the pipeline central axis in the X-axis and Y-axis directions, respectively; the slope is calculated by the angle between the fitted pipeline central axis and the horizontal plane, and the calculation formula is θ=arccos(ΔZ / √(ΔX²+ΔY²+ΔZ²)), where ΔZ is the coordinate difference of two points on the pipeline central axis in the Z-axis direction.

[0012] Furthermore, the distance measurement component is a vertically downward laser rangefinder or ultrasonic sensor, which can acquire distance data from the wellhead to the bottom of the well or the water surface in real time and transmit the data to the control processing component to assist in calculating the depth of the inspection well; the wellhead fixing component is equipped with an electronic level and an automatic leveling mechanism, the automatic leveling mechanism is a three-point contact leveling base driven by a servo motor, which can realize the automatic centering of the system with a centering error of less than 0.5°; the contact surface of the wellhead fixing component has a corrugated structure, which has deformation compensation capability and can adapt to deformed inspection well rings.

[0013] Furthermore, it also includes a power supply component and a data interface component; the power supply component includes a built-in battery and an external power interface, which can provide power to various components of the system; the data interface component includes a WiFi module, a Bluetooth module, a 4G / 5G module and a USB interface, which are used to realize data transmission between the system and external devices, as well as the configuration of system parameters.

[0014] This invention also provides an automatic measurement method for pipeline network parameters based on three-dimensional scanning of the manhole head, using the automatic measurement system described above, including the following steps: Step 1: Fix the automatic pipeline parameter measurement system to the manhole opening using the manhole fixing component. After starting the system, the manhole fixing component will automatically center and level the system through the automatic leveling mechanism. Step 2: The coordinate input component obtains the position coordinates of the wellhead and establishes a measurement benchmark; the control processing component controls the three-dimensional laser scanning component to perform a preliminary scan, obtain preliminary three-dimensional point cloud data, and determines the working mode based on the integrity rate of the preliminary three-dimensional point cloud data. If the integrity rate of the preliminary three-dimensional point cloud data is greater than 80%, it switches to the working mode without telescopic rod; if the integrity rate of the preliminary three-dimensional point cloud data is less than 80%, it switches to the working mode with telescopic rod. Step 3: If it is the working mode without telescopic rod, the 3D laser scanning component directly scans the inside of the inspection well and the connected pipeline network from the wellhead to obtain complete 3D point cloud data; if it is the working mode with telescopic rod, the control processing component controls the telescopic rod component to lower the 3D laser scanning component to perform multiple scans at different depths of the inspection well to obtain multiple sets of 3D point cloud data, while the auxiliary attitude perception sub-component corrects the scanning attitude in real time. Step 4: The attitude perception component transmits the measured system attitude information to the control processing component, and the distance measurement component transmits the acquired depth data to the control processing component. Step 5: The control processing component performs noise reduction, filtering, registration, and coordinate system unification on the 3D point cloud data using a point cloud preprocessing algorithm; it identifies the well wall and bottom using a manhole structure recognition and segmentation algorithm, and calculates the manhole depth by combining the depth data from the distance measurement component. The manhole depth is the elevation difference between the wellhead reference surface and the bottom of the well. Step 6: The control processing component identifies the pipe inlet using a pipe inlet recognition and segmentation algorithm, segmenting the point cloud region of the pipe inlet and connected pipes; it performs circular fitting on the pipe inlet point cloud using a pipe parameter calculation algorithm to calculate the pipe diameter; it calculates the pipe inlet center coordinates from the pipe inlet point cloud or the fitted circle, and converts the pipe inlet center coordinates into coordinates in the geographic coordinate system by combining the geographic coordinate data from the coordinate input component; it fits the pipe point cloud to obtain the pipe central axis and calculates the azimuth and slope of the pipe direction. Step 7: The control processing component integrates the manhole depth, pipe diameter, pipe inlet center coordinates, pipeline direction and 3D point cloud data through the result fusion output algorithm, generates a structured data report, and transmits it to external devices through the data interface component. At the same time, it outputs the internal 3D model or point cloud of the manhole.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. Significantly improved measurement efficiency: All key parameters can be obtained in a single scan. The measurement time per well is reduced to less than 3 minutes in the no telescopic rod mode and less than 5 minutes in the telescopic rod mode. Compared with the traditional method (15-30 minutes / well), the efficiency is improved by more than 5 times.

[0016] 2. Significantly improved operational safety: The system is fixed at the wellhead, eliminating the need for personnel to go down into the well, thus avoiding safety risks such as toxic gases, oxygen deficiency, and falls inside the well, and is suitable for various complex well environments.

[0017] 3. Good data integrity and correlation: It can acquire continuous three-dimensional point cloud data of manholes and pipelines in one go, and directly output parameters such as manhole depth, pipe diameter, pipeline direction, and pipe outlet coordinates without secondary calculation. The data has strong correlation and can be directly used for GIS system input and pipeline modeling.

[0018] 4. Strong environmental adaptability: Through automatic judgment of working conditions and switching of working modes, it is suitable for various scenarios such as shallow wells / deep wells, straight pipes / bends, and unobstructed / obstructed conditions; IP67 protective shell and 905nm near-infrared laser ensure stable operation in humid and dusty well-side environments; the coordinate input scheme combining RTK and target solves the measurement problem in weak signal areas.

[0019] 5. Simple and standardized operation: The system can automatically level, automatically judge working conditions, and automatically calculate parameters without the need for professional surveyors; the output results are structured reports, and the measurement process and data format are standardized, which facilitates subsequent data management and comparative analysis. Detailed Implementation

[0020] The technical solutions of the present invention will be further described below with reference to the embodiments.

[0021] An automatic pipeline parameter measurement system based on three-dimensional scanning of manhole openings includes: Automatic measurement system for pipeline parameters The system includes a wellhead fixing component, a 3D laser scanning component, an attitude sensing component, a distance measurement component, a coordinate input component, a control processing component, a telescopic rod component, a power supply component, and a data interface component. These components work together to achieve automatic parameter measurement. Wellhead fixing assembly: Used to fix the entire system, suitable for inspection wellheads with diameters ranging from 600mm to 1200mm. It is equipped with an electronic level and a three-point contact leveling base driven by a servo motor, enabling automatic centering with a centering error of less than 0.5°; the contact surface adopts a corrugated structure, which has deformation compensation capability, can adapt to deformed well rings, and also serves as a fixing base for the telescopic rod assembly.

[0022] 3D laser scanning component: Employing a multi-beam lidar (such as Velodyne VLP-16) or panoramic laser scanner, with the scanning direction downwards, it can scan the interior of the inspection well 360°, acquiring 3D point cloud data with a density greater than 10,000 points / second. It uses a 905nm near-infrared wavelength laser with power adjustment to adapt to changes in humidity and light within the well, avoiding interference from water mist and dust. In telescopic mast operation mode, this component can be installed at the end of the telescopic mast assembly.

[0023] Attitude sensing components include a high-precision IMU (such as BMI088) and an electronic compass. The IMU measures the pitch, roll, and yaw angles of the system for point cloud attitude correction; the electronic compass assists in measuring azimuth information and assists in pipeline direction calculation; in the telescopic boom operation mode, an auxiliary IMU is installed at the end of the telescopic boom assembly to correct the scanning attitude in real time.

[0024] Distance measurement components: Using a vertically downward laser rangefinder (such as VL53L5CX) or ultrasonic sensor, it can quickly acquire depth data from the wellhead to the bottom of the well or the water surface, assisting in the calculation of the inspection well depth, with a measurement accuracy of ±2mm.

[0025] Coordinate input component: Integrates an RTKGNSS module (such as Trimble R10) to acquire geographic coordinates with centimeter-level accuracy in real time (based on the WGS84 coordinate system) and directly associates measurement parameters with the geographic coordinate system; Configures a magnetic QR code target recognition sub-component to acquire coordinates through pre-laid magnetic QR code targets in densely built-up areas, underground and other scenarios with weak RTK signals, as a backup for the RTK module. The control processing component fuses the two coordinate data through the Kalman filtering algorithm to ensure coordinate robustness.

[0026] Telescopic pole assembly: Used for depth scanning under complex working conditions, made of carbon fiber (lightweight and corrosion-resistant), with a length adjustment range of 0 to 10m and a diameter of less than 200mm. Driven by a servo motor and gear transmission, with a lowering speed of 0.5m / s. Equipped with ultrasonic anti-collision and limiting sub-assemblies to prevent collisions with the well wall; the internal cavity houses power and data lines, and the end can be fitted with a 3D laser scanning assembly and an auxiliary IMU.

[0027] Power supply components: Includes a 12V / 20Ah built-in lithium battery and a 220V external power interface. The built-in battery can support the system to work continuously for more than 4 hours, meeting the needs of outdoor mobile measurement.

[0028] Data interface components include a WiFi 6 module, a Bluetooth 5.0 module, a 4G / 5G full network compatible module, and a USB 3.0 interface, enabling data transmission with tablets, mobile phones, and cloud platforms, and supporting remote parameter configuration and data export.

[0029] In addition, the system is equipped with an IP67-rated protective shell, which is waterproof, dustproof, and shockproof, and can adapt to the harsh environment of damp and dusty wells.

[0030] The measurement method based on the above system includes the following steps: 1. System Deployment and Leveling: The system is fixed to the wellhead of the inspection well using the wellhead fixing components. After the system is started, the electronic level detects the system's level status, and the automatic leveling mechanism (three-point contact leveling base) drives the wellhead fixing components to adjust, so that the system can be automatically centered with a centering error of less than 0.5°, ensuring the stability of the scanning reference.

[0031] 2. Coordinate Baseline Establishment and Operating Condition Judgment: The coordinate input component is activated, and the RTKGNSS module receives satellite signals to obtain the geographic coordinates (X0, Y0, Z0) of the wellhead, establishing a measurement baseline. If the RTK signal is weak, the control processing component switches to the magnetic QR code target recognition sub-component to read the coordinates of the pre-laid target as the baseline. Simultaneously, the control processing component controls the 3D laser scanning component to perform a preliminary scan (scanning time approximately 10 seconds) to obtain preliminary 3D point cloud data and calculate the point cloud integrity rate (number of points at the pipe opening / expected number of points): if the integrity rate > 80%, it is determined to be a simple operating condition, and the system switches to the no-telescopic-rod operating mode; if the integrity rate < 80%, it is determined to be a complex operating condition, and the system switches to the telescopic-rod operating mode.

[0032] 3. 3D point cloud data acquisition: No telescopic rod working mode (suitable for shallow wells with depth <5m, unobstructed pipe openings, and straight pipes): The 3D laser scanning component performs a 360° complete scan of the inside of the inspection well and the connected pipe network directly from the wellhead (scanning time is about 2 minutes), acquiring complete 3D point cloud data with a point cloud density >10,000 points / second. The attitude perception component collects the system's attitude information (pitch angle, roll angle, yaw angle) in real time and transmits it to the control processing component. With telescopic boom working mode (suitable for deep wells with depth >5m, obstructed pipe openings, bends, or water accumulation inside): The control processing component controls the telescopic boom assembly to start, and the servo motor drives the telescopic boom to lower, lowering the 3D laser scanning component installed at the end to the middle of the inspection well (corresponding to the pipe opening position) and the bottom of the well (corresponding to the pipe axis position) to perform scanning (each scan takes about 1.5 minutes), acquiring 2-3 sets of 3D point cloud data; the auxiliary IMU corrects the scanning posture in real time to avoid point cloud offset caused by the swaying of the telescopic boom, and the scanning data is transmitted to the control processing component through the data cable inside the boom.

[0033] 4. Auxiliary data acquisition: The distance measurement component measures the depth data from the wellhead to the bottom of the well or the water surface in real time, once every 2 seconds, for a total of 5 times. The average value is taken as the preliminary depth data and transmitted to the control and processing component.

[0034] 5. Data processing and parameter calculation: Point cloud preprocessing: The control processing component runs a point cloud preprocessing algorithm to denoise (remove isolated noise points), filter (Gaussian filter to smooth point clouds), register (using ICP algorithm to fuse multi-depth point clouds in telescopic rod mode), and unify coordinate system (converting the scanning coordinate system to the equipment coordinate system with the wellhead center as the origin, and then combining it with the geographic coordinates of the coordinate input component to convert it to the geographic coordinate system). Inspection well depth calculation: The inspection well structure recognition and segmentation algorithm identifies the well wall (cylindrical or cubic structure) and the well bottom (planar structure) from the preprocessed point cloud. The minimum Z coordinate Z_min of the well bottom point cloud is extracted. The Z coordinate of the wellhead reference surface is Z0. The inspection well depth H = Z0 - Z_min is then corrected by combining the preliminary depth data of the distance measurement component to ensure that the depth error is <±3mm. Pipeline parameter calculation: The pipeline inlet identification and segmentation algorithm identifies pipeline inlets through edge detection (Canny algorithm) and a deep learning model (YOLOv8), segmenting the point cloud region of the pipeline inlet and connected pipelines. Pipe diameter calculation: The RANSAC algorithm is used to fit the point cloud of the pipe opening to obtain the radius r of the fitted circle. The pipe diameter D=2r and the fitting error is <±2mm. Pipe center coordinate calculation: Take the center coordinates (Xc, Yc, Zc) of the fitted circle (under the equipment coordinate system), and combine them with the geographic coordinates (X0, Y0, Z0) of the coordinate input component to convert them into coordinates (Xc+X0, Yc+Y0, Zc+Z0) under the geographic coordinate system. Pipeline routing calculation: The point cloud inside the pipeline is fitted with a cylinder using the least squares method to obtain the pipeline's central axis; the projection direction of the axis onto the horizontal plane is the azimuth angle α, calculated by the formula α=arctan(ΔY / ΔX) (ΔX and ΔY are the X and Y coordinate differences between two points on the axis), with an error of <±2°; the angle between the axis and the horizontal plane is the slope θ, calculated by the formula θ=arccos(ΔZ / √(ΔX²+ΔY²+ΔZ²)) (ΔZ is the Z coordinate difference between two points on the axis).

[0035] 6. Output Results: The algorithm integrates the results of the control processing component's operation, combining the manhole depth H, pipe diameter D, pipe inlet center coordinates (X,Y,Z), pipeline direction (α,θ), and the manhole's internal 3D point cloud data to generate a structured data report (supporting Excel and JSON formats). This report is then transmitted to a tablet or cloud platform via the data interface component. Simultaneously, a simplified 3D model of the manhole's interior (supporting STL and OBJ formats) is output for subsequent pipeline network modeling and analysis.

[0036] The solution will now be explained using simple operating conditions, complex operating conditions, and weak signal areas as examples.

[0037] Measurement under simple working conditions (without telescopic rod) Application scenario: A manhole on a municipal road, 4m deep, with a DN600 straight pipe, no water accumulation inside the manhole, no obstruction at the pipe opening, no tall buildings nearby, and good RTK signal.

[0038] System configuration: The 3D laser scanning component uses Velodyne VLP-16 multi-beam LiDAR, the attitude sensing component uses BMI088 high-precision IMU, the coordinate input component uses Trimble R10 RTK GNSS module, the distance measurement component uses VL53L5CX laser rangefinder, the control processing component uses NVIDIA Jetson AGX Orin embedded computer, and the power supply component is a 12V / 20Ah lithium battery.

[0039] Measurement process: (1) Fix the system to the wellhead of the inspection well through the wellhead fixing component. After the system is started, the electronic level instrument detects the horizontal status and the automatic leveling mechanism adjusts to achieve automatic centering (error 0.3°). (2) The RTKGNSS module receives satellite signals and obtains the wellhead geographic coordinates (X=116.3521°, Y=39.9152°, Z=45.20m); the three-dimensional laser scanning component performs a preliminary scan, and the point cloud integrity rate is calculated to be 92%, which is determined to be a simple working condition. The system is then switched to the no telescopic rod working mode. (3) The three-dimensional laser scanning component performs a 360° full scan from the wellhead, with a scanning time of 2 minutes, and acquires point cloud data (density 12,000 points / second); the attitude perception component collects pitch angle 0.2°, roll angle 0.1°, and yaw angle 358.5°, and transmits them to the control processing component; 4) The distance measurement component measured the depth from the wellhead to the bottom of the well. The five measurements were 3.998m, 4.001m, 3.999m, 4.000m, and 4.002m, with an average value of 4.000m. (5) Data processing by the control processing component: After point cloud preprocessing, noise points are removed, and the coordinate system is unified into the geographic coordinate system; the well wall and well bottom are identified, and the Z coordinate of the well bottom is calculated to be 41.20m, and the depth of the inspection well is H=45.20m-41.20m=4.000m (consistent with the distance measurement value); the point cloud of the pipe opening is segmented, and the RANSAC algorithm is used to fit a circle with a radius r=300.1mm and a pipe diameter D=600.2mm; the coordinates of the center of the pipe opening are calculated (X=116.3522°, Y=39.9153°, Z=42.70m); the central axis of the pipe is fitted, and the azimuth angle α=45.1° and the slope θ=3.0° are calculated; (6) Generate a structured report and output the manhole depth of 4.000m, pipe diameter of 600.2mm, pipe direction (45.1°, 3.0°), pipe port coordinates (116.3522°, 39.9153°, 42.70m) and three-dimensional point cloud data, and transmit them to a tablet computer via WiFi.

[0040] Measurement result verification: The well was remeasured using a traditional total station. The well depth was 4.002m, the pipe diameter was 600.3mm, the pipe azimuth angle was 45.0°, and the slope was 2.9°. The measurement results of this invention and the remeasurement results were within ±3mm and ±0.2°, respectively, which met the accuracy requirements.

[0041] Measurement under complex working conditions (with telescopic pole working mode) Application scenario: An underground inspection well in a residential community, 7.2m deep, with a DN800 bend in the pipe. There is a small amount of water in the well (0.5m deep), and the pipe opening is blocked by a ladder inside the well. The surrounding area is densely populated with tall buildings, and the RTK signal is weak (accuracy reduced to 1m level).

[0042] System configuration: The 3D laser scanning component uses a panoramic laser scanner (model FaroFocusS70), the attitude sensing component uses a BMI088 + electronic compass (model HMC5883L), the coordinate input component uses a Trimble R10RTKGNSS module + magnetic QR code target (custom pattern), the distance measurement component uses an ultrasonic sensor (model HC-SR04), the telescopic pole component is made of carbon fiber (length 0-10m), and the control processing component uses NVIDIA Jetson AGX Orin.

[0043] Measurement process: (1) Fix the system at the wellhead and adjust it with an automatic leveling mechanism to achieve a centering error of 0.4°; pre-lay two magnetic QR code targets around the wellhead and use the coordinate input component to read the target coordinates (X=116.3612°, Y=39.9205°, Z=43.80m) as the measurement reference. (2) The three-dimensional laser scanning component performs a preliminary scan. The point cloud integrity rate is calculated to be 68%, which is determined to be a complex working condition. Switch to the working mode with telescopic rod. (3) The control and processing component controls the telescopic pole assembly to start, the servo motor drives the telescopic pole to go down, and the panoramic laser scanner at the end is lowered to a depth of 4m (corresponding to the pipe opening position), scans for 1.5 minutes, and obtains the point cloud data of the pipe opening; it continues to go down to a depth of 6.7m (0.5m above the bottom of the well, avoiding water accumulation), scans for 1.5 minutes, and obtains the point cloud data of the pipe axis; the auxiliary IMU corrects the attitude, and the scan data is transmitted to the control and processing component through the data line inside the pole; (4) The ultrasonic sensor measured the depth from the wellhead to the water surface to be 6.7m. Combined with the water depth of 0.5m, the preliminary calculation of the bottom depth of the well is 7.2m. (5) Data processing: The ICP algorithm was used to fuse point cloud data at depths of 4m and 6.7m; the point cloud at the bottom of the well was identified, and the Z coordinate of the bottom of the well was calculated to be 36.60m, and the depth of the inspection well was H=43.80m-36.60m=7.20m; the point cloud at the pipe opening was segmented, and the RANSAC algorithm was used to fit a circle with a radius r=400.2mm and a pipe diameter D=800.4mm; the coordinates of the center of the pipe opening were calculated (X=116.3613°, Y=39.9206°, Z=39.80m); the central axis of the pipe was fitted, and the azimuth angle α=225.3° and the slope θ=2.1° were calculated; (6) Generate a structured report, outputting the manhole depth of 7.20m, pipe diameter of 800.4mm, pipe direction (225.3°, 2.1°), pipe port coordinates (116.3613°, Y=39.9206°, Z=39.80m) and a three-dimensional model, and transmit it to the cloud platform via a 4G module.

[0044] Measurement result verification: The measurement was re-measured by manually going down into the well (wearing protective equipment) and setting up a prism. The well depth was 7.21m, the pipe diameter was 800.3mm, the pipe azimuth angle was 225.2°, and the slope was 2.0°. The measurement results of this invention and the re-measurement results were within ±3mm and ±0.2°, respectively, which met the accuracy requirements.

[0045] Measurement in weak signal regions (RTK + target coordination) Application scenario: A manhole in an underground parking garage, 3.5m deep, with a DN500 straight pipe. There is no water accumulation in the manhole and the pipe opening is unobstructed. The RTK signal is completely blocked in the underground parking garage, making it impossible to receive satellite signals.

[0046] System configuration: The three-dimensional laser scanning component is Velodyne VLP-16, and the coordinate input component only uses the magnetic QR code target recognition sub-component (with 3 targets pre-laid). Other components are the same as in Example 1.

[0047] Measurement process: (1) The system is fixed at the wellhead. After automatic leveling, the coordinate input component reads the coordinates of the three targets and calculates the coordinates of the wellhead center (X=116.3456°, Y=39.9087°, Z=41.50m) through trigonometric calculation. (2) The initial scan point cloud integrity rate is 88%, which is determined to be a simple working condition and scanning mode without telescopic pole; (3) The subsequent data acquisition, processing and result output steps are the same as in Example 1. The final output is the manhole depth 3.50m, pipe diameter 500.1mm, pipe azimuth angle 135.2°, slope 1.8°, and pipe opening coordinates (116.3457°, Y=39.9088°, Z=38.00m).

[0048] Measurement result verification: The measurement was repeated using a total station with an indoor control network. The error between the measurement results and the output results of this invention was <±3mm, and the accuracy met the requirements.

[0049] As can be seen from the above embodiments, the automatic pipeline parameter measurement system and method of the present invention can be adapted to different scenarios, realize efficient, safe and high-precision parameter measurement, and meet the actual needs of manhole and pipeline measurement in municipal engineering.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An automatic measurement system for pipeline parameters based on three-dimensional scanning of manhole openings, characterized in that, The system comprises a wellhead fixing component, a 3D laser scanning component, an attitude sensing component, a distance measurement component, a coordinate input component, and a control processing component. The wellhead fixing component secures the entire system to the manhole opening and is adaptable to manholes of different sizes. The 3D laser scanning component scans the interior of the manhole and connected pipe networks to acquire 3D point cloud data. The attitude sensing component measures the system's own attitude information to assist in pipeline routing calculations. The distance measurement component obtains the preliminary depth from the manhole opening to the bottom of the manhole or the water surface. The coordinate input component establishes the association between the measurement data and the geographic coordinate system. The control processing component controls the collaborative work of each component, processes the 3D point cloud data and attitude information, and automatically outputs the manhole depth, the diameter of connected pipe networks, the pipeline routing, the center coordinates of each pipe opening within the manhole, and a 3D model or point cloud of the manhole's interior. The system can switch between a working mode without a telescopic rod and a working mode with a telescopic rod based on the actual conditions of the manhole and pipe network, enabling adaptive measurement of pipeline parameters. It can also calculate the hydraulic gradient by combining water surface elevation data from multiple manholes, thereby deducing the pipeline flow velocity and flow rate.

2. The automatic pipeline parameter measurement system based on three-dimensional scanning of the manhole head as described in claim 1, characterized in that, The coordinate input component integrates an RTKGNSS module, which can acquire geographic coordinates with centimeter-level accuracy in real time. The coordinate input component is also equipped with a wellhead automatic positioning target recognition sub-component, which includes pre-laid magnetic QR code targets. When the RTKGNSS module signal is weak, the coordinates are obtained by recognizing the magnetic QR code targets. The control processing component can integrate the data from the RTKGNSS module and the wellhead automatic positioning target recognition sub-component through a data fusion algorithm.

3. The automatic pipeline parameter measurement system based on three-dimensional scanning of the manhole head as described in claim 1, characterized in that, It also includes a telescopic rod assembly, which is connected to the wellhead fixing assembly and is used to lower the three-dimensional laser scanning assembly in the telescopic rod working mode; the telescopic rod assembly is a multi-section electric telescopic structure that can realize length adjustment, and its end can be equipped with the three-dimensional laser scanning assembly and auxiliary attitude sensing sub-assembly; the telescopic rod assembly is also equipped with anti-collision sub-assembly and limiting sub-assembly to avoid collision with the well wall.

4. The automatic pipeline parameter measurement system based on three-dimensional scanning of the manhole head as described in claim 1, characterized in that, The telescopic pole assembly is made of carbon fiber, with a length adjustment range of 0 to 10m and a diameter of less than 200mm. The telescopic pole assembly is driven by a servo motor with gear transmission, and the lowering speed is 0.5m / s. The telescopic pole assembly has an internal cavity for laying power and data lines.

5. The automatic pipeline parameter measurement system based on three-dimensional scanning of the manhole head as described in claim 1, characterized in that, The three-dimensional laser scanning component is a multi-beam lidar or panoramic laser scanner, with a downward scanning direction, capable of 360° scanning of the inside of the inspection well, and the density of the acquired three-dimensional point cloud data is greater than 10,000 points / second; the three-dimensional laser scanning component uses a 905nm near-infrared wavelength laser and has a power adjustment function; the attitude sensing component includes a high-precision IMU and an electronic compass, the high-precision IMU is used to measure the system's pitch angle, roll angle and yaw angle, and the electronic compass is used to assist in measuring azimuth information.

6. The automatic pipeline parameter measurement system based on three-dimensional scanning of the manhole head as described in claim 1, characterized in that, The control and processing component includes a high-performance embedded computer. The processing algorithms run by the high-performance embedded computer include a point cloud preprocessing algorithm, a manhole structure identification and segmentation algorithm, a pipe opening identification and segmentation algorithm, a pipe parameter calculation algorithm, and a result fusion and output algorithm. The point cloud preprocessing algorithm is used to perform noise reduction, filtering, registration, and coordinate system unification processing on the 3D point cloud data. The manhole structure identification and segmentation algorithm is used to identify the manhole wall and bottom and segment the corresponding point cloud regions. The pipe opening identification and segmentation algorithm is used to identify the pipe inlet and segment the point cloud regions of the pipe opening and connected pipes. The pipe parameter calculation algorithm is used to calculate the pipe diameter, pipe opening center coordinates, and pipe direction. The result fusion and output algorithm is used to integrate all parameters and generate a structured data report.

7. The automatic pipeline parameter measurement system based on three-dimensional scanning of the manhole head as described in claim 1, characterized in that, In the pipeline parameter calculation algorithm, the pipe diameter is calculated by performing a circular fitting on the pipe inlet point cloud, using the RANSAC algorithm or the least squares method; the pipe inlet center coordinates are calculated from the pipe inlet point cloud or the fitted circle; the pipeline orientation includes azimuth and slope, with the azimuth calculated by the projection direction of the fitted pipeline central axis onto the horizontal plane, using the formula α=arctan(ΔY / ΔX), where ΔX and ΔY are the coordinate differences between two points on the pipeline central axis in the X and Y axes, respectively; the slope is calculated by the angle between the fitted pipeline central axis and the horizontal plane, using the formula θ=arccos(ΔZ / √(ΔX²+ΔY²+ΔZ²)), where ΔZ is the coordinate difference between two points on the pipeline central axis in the Z axis direction.

8. The automatic pipeline parameter measurement system based on three-dimensional scanning of the manhole head as described in claim 1, characterized in that, The distance measurement component is a vertically downward laser rangefinder or ultrasonic sensor, which can acquire distance data from the wellhead to the bottom of the well or the water surface in real time and transmit the data to the control processing component to assist in calculating the depth of the inspection well; the wellhead fixing component is equipped with an electronic level and an automatic leveling mechanism. The automatic leveling mechanism is a three-point contact leveling base driven by a servo motor, which can realize the automatic centering of the system with a centering error of less than 0.5°; the contact surface of the wellhead fixing component has a corrugated structure, which has deformation compensation capability and can adapt to deformed inspection well rings.

9. The automatic pipeline parameter measurement system based on three-dimensional scanning of the manhole head as described in claim 1, characterized in that, It also includes a power supply component and a data interface component; the power supply component includes a built-in battery and an external power interface, which can provide power to various components of the system; the data interface component includes a WiFi module, a Bluetooth module, a 4G / 5G module and a USB interface, which are used to realize data transmission between the system and external devices, as well as the configuration of system parameters.

10. An automatic measurement method for pipeline parameters based on three-dimensional scanning of manhole openings, characterized in that, Using the automatic measurement system as described in any one of claims 1 to 9 includes the following steps: Step 1: Fix the automatic pipeline parameter measurement system to the manhole opening using the manhole fixing component. After starting the system, the manhole fixing component will automatically center and level the system through the automatic leveling mechanism. Step 2: The coordinate input component obtains the position coordinates of the wellhead and establishes a measurement benchmark; the control processing component controls the three-dimensional laser scanning component to perform a preliminary scan, obtain preliminary three-dimensional point cloud data, and determines the working mode based on the integrity rate of the preliminary three-dimensional point cloud data. If the integrity rate of the preliminary three-dimensional point cloud data is greater than 80%, it switches to the working mode without telescopic rod; if the integrity rate of the preliminary three-dimensional point cloud data is less than 80%, it switches to the working mode with telescopic rod. Step 3: If it is the working mode without telescopic rod, the 3D laser scanning component directly scans the inside of the inspection well and the connected pipeline network from the wellhead to obtain complete 3D point cloud data; if it is the working mode with telescopic rod, the control processing component controls the telescopic rod component to lower the 3D laser scanning component to perform multiple scans at different depths of the inspection well to obtain multiple sets of 3D point cloud data, while the auxiliary attitude perception sub-component corrects the scanning attitude in real time. Step 4: The attitude perception component transmits the measured system attitude information to the control processing component, and the distance measurement component transmits the acquired depth data to the control processing component. Step 5: The control processing component performs noise reduction, filtering, registration, and coordinate system unification on the 3D point cloud data using a point cloud preprocessing algorithm; it identifies the well wall and bottom using a manhole structure recognition and segmentation algorithm, and calculates the manhole depth by combining the depth data from the distance measurement component. The manhole depth is the elevation difference between the wellhead reference surface and the bottom of the well. Step 6: The control processing component identifies the pipe inlet using a pipe inlet recognition and segmentation algorithm, segmenting the point cloud region of the pipe inlet and connected pipes; it performs circular fitting on the pipe inlet point cloud using a pipe parameter calculation algorithm to calculate the pipe diameter; it calculates the pipe inlet center coordinates from the pipe inlet point cloud or the fitted circle, and converts the pipe inlet center coordinates into coordinates in the geographic coordinate system by combining the geographic coordinate data from the coordinate input component; it fits the pipe point cloud to obtain the pipe central axis and calculates the azimuth and slope of the pipe direction. Step 7: The control processing component integrates the manhole depth, pipe diameter, pipe inlet center coordinates, pipeline direction and 3D point cloud data through the result fusion output algorithm, generates a structured data report, and transmits it to external devices through the data interface component. At the same time, it outputs the internal 3D model or point cloud of the manhole.