A three-dimensional scanning positioning and self-adaptive spraying control device for a tunnel shotcrete abutment vehicle and a control method thereof

Abstract

The present application relates to the technical field of tunnel shotcrete, and discloses a three-dimensional scanning positioning and self-adaptive shotcrete control device for a tunnel shotcrete abutment vehicle and a control method thereof. The device aims to solve the technical problems of low positioning accuracy, poor dust removal effect, path planning relying on manual operation, slow hydraulic control response, mismatched shotcrete parameters, serious rebound material waste, and high on-site debugging risk in the prior art. The device comprises a vehicle body positioning and sensing unit, a three-dimensional laser modeling unit, an electro-hydraulic servo control assembly, a follow-up dust removal unit, and a general control assembly. The device significantly improves the automation degree, operation accuracy and environmental protection level of tunnel shotcrete, and has outstanding substantial features and significant progress.

Description

Technical Field

[0001] This invention relates to the field of tunnel shotcrete technology, and in particular to a three-dimensional scanning positioning and adaptive shotcrete control device and its control method for a tunnel shotcrete bridge trolley. Background Technology

[0002] During tunnel excavation, full-face tunnel boring machines (TBMs) need to promptly apply shotcrete to the excavated tunnel walls to form an initial support structure, ensuring the stability of the surrounding rock and construction safety.

[0003] To address the shortcomings of existing tunnel shotcrete systems, such as high reliance on manual operation leading to unstable lining construction quality and efficiency, and low levels of intelligence, domestic and international experts and scholars have conducted some research. However, domestic intelligent shotcrete equipment exhibits poor performance, while imported equipment suffers from high costs and long production cycles. Therefore, research on intelligent shotcrete control technology can effectively promote the intelligentization process of domestic tunneling equipment and enhance the market competitiveness of domestically produced products. Through surveys, extensive research has been conducted on intelligentization, and some manufacturers have carried out industrial experiments, but the application results have been unsatisfactory. The main reason is the extremely harsh working environment. During long-term operation, the sprayed concrete covers the relevant sensors, and rebounding stones may damage these sensors, rendering the intelligent shotcrete control system unusable. Even if the sensors function normally, accidental concrete collapse cannot be effectively compensated for, resulting in poor shotcrete performance that fails to meet actual construction requirements. Shotcrete operations in TBM tunnels face two major technical challenges: shotcrete dust pollution and concrete rebound material waste.

[0004] On the one hand, shotcreting operations generate a large amount of cement dust and fine particulate matter. Due to the narrow and relatively enclosed space of the tunnel and limited ventilation, the dust is difficult to remove quickly, resulting in serious environmental pollution inside the tunnel. This not only affects the construction site's visibility and threatens the health of workers, but also accelerates the wear and tear of mechanical equipment. Studies have shown that the dust concentration generated during TBM excavation from rock breaking and shotcreting operations is high. Existing dry dust collection systems are limited by the space of the main unit, making it difficult to arrange dust collection ducts. If filtration is incomplete, dust will be re-dispersed into the tunnel with the exhaust air. Although wet dust collection can capture dust through water mist, traditional high-pressure spraying methods need to be operated during workers' rest periods to avoid wetting the work surface. Furthermore, the wet and slippery site after spraying affects the construction progress, indicating significant limitations in application.

[0005] On the other hand, shotcrete operations often result in a rebound rate of 20% to 30% due to factors such as the concrete not setting in time and the aggregate rebounding from the tunnel walls, leading to significant material waste. Current methods largely rely on manual cleaning, which is not only inefficient but also poses a safety hazard due to the continuous falling of uncured concrete. Some projects have attempted to install slag collection devices below the shotcrete equipment, but ordinary aggregate structures struggle to achieve timely transfer of rebound material, and the concrete easily solidifies on the slag collection plate, leading to cleaning difficulties and device failure.

[0006] Chinese patent document 202410098422.0 discloses a slag removal mechanism for an open-type TBM rockburst tunnel shotcrete bridge, applicable to the field of slag removal technology for open-type TBM shotcrete bridges. The mechanism includes a support frame connected to one end of a flap, and the other end of the flap is connected to a slag collection plate cylinder. A water flushing assembly is installed above the flap, and a vibrator is installed below the flap.

[0007] However, the above-mentioned solutions suffer from at least the following technical problems during implementation: low positioning accuracy, poor dust removal effect, reliance on manual path planning, slow hydraulic control response, mismatched shotcrete parameters, serious waste of rebound material, and high on-site debugging risks in TBM tunnel shotcrete operations. Therefore, there is an urgent need to propose a three-dimensional scanning positioning and adaptive shotcrete control device and its control method for tunnel shotcrete bridge trolleys. Summary of the Invention

[0008] In view of the above technical problems, this disclosure provides a three-dimensional scanning positioning and adaptive shotcreting control device and its control method for tunnel shotcreting bridge trolleys, which solves the technical problems existing in the prior art of TBM tunnel shotcreting operations, such as low positioning accuracy, poor dust removal effect, path planning relying on manual labor, slow hydraulic control response, mismatch of shotcreting parameters, serious waste of rebound material, and high risk of on-site debugging.

[0009] According to one aspect of this disclosure, a rapid dust removal and rebound material collection device for shotcrete in TBM tunnels is provided, including a shotcrete bridge trolley. The shotcrete bridge trolley is equipped with a circular slide rail for the mechanical arm to support the movement of the shotcrete mechanical arm, which is used to spray concrete onto the tunnel wall; the shotcrete mechanical arm is connected to a multi-axis spray gun to provide concrete slurry; The shotcrete bridge trolley is equipped with a dust removal component, which includes a water cyclone dust collector and a suction hood. The suction hood is located near the shotcrete robotic arm and moves with the shotcrete robotic arm to remove dust generated by shotcrete in real time. The shotcrete bridge trolley is equipped with a three-dimensional modeling component, which includes a two-dimensional laser scanner and a rotating mechanism. The rotating mechanism drives the two-dimensional laser scanner to rotate to obtain three-dimensional point cloud data of the tunnel inner wall.

[0010] In some embodiments of this disclosure, the dust removal assembly further includes a water cyclone fan, and the water cyclone dust collector is connected to the suction hood via a duct.

[0011] In some embodiments of this disclosure, the 3D modeling component further includes a pose calibration module among multiple scanners, used to unify the point cloud data acquired by the multiple 2D laser scanners into the same coordinate system.

[0012] In some embodiments of this disclosure, the 3D modeling component further includes a coordinate system transformation module for transforming the point cloud data in the local coordinate system of the 2D laser scanner to the global construction coordinate system.

[0013] In some embodiments of this disclosure, a tunnel model is also included for simulating a real tunnel environment for testing. The tunnel model includes a tunnel frame and a tunnel wall composed of detachable steel plates. The tunnel frame is an I-beam. The detachable steel plates are provided with multiple seepage holes. The tunnel model has a geological simulation structure that simulates fracture water and fault fracture zones.

[0014] In some embodiments of this disclosure, the tunnel model has a diameter of 6m and a longitudinal length of 5.4m (3 rings). The tunnel frame is made of 200mm*200mm I-beams. The tunnel wall model is made of 3mm thick detachable steel plates with a width of 1740mm and a length of 1790mm.

[0015] In some embodiments of this disclosure, the shotcrete bridge trolley is also equipped with a waste collection assembly, which includes a waste collection box and a scraper. The scraper can rotate 270 degrees around the shotcrete bridge trolley to scrape off the waste.

[0016] In some embodiments of this disclosure, the water cyclone dust collector has external dimensions of 2000*1480*2570mm, a processing air volume of 6200-6800 m³ / h, an air inlet size of φ400mm, and a water storage capacity of 1.2 m³.

[0017] In some embodiments of this disclosure, the movable range of the shotcrete robotic arm is 5120mm, and the length of the shotcrete bridge trolley is 7060mm and the height is 2867mm.

[0018] A three-dimensional scanning positioning and adaptive shotcreting control device for a tunnel shotcreting bridge trolley includes: a vehicle positioning and sensing unit, a three-dimensional laser modeling unit, an electro-hydraulic servo control component, a follow-up dust removal unit, and a main control component, all mounted on the shotcreting bridge trolley. The vehicle positioning unit is used to collect the vehicle's attitude and position data in real time. The three-dimensional laser modeling unit is used to scan the tunnel cross-section, construct a three-dimensional point cloud model of the tunnel, and generate a jetting path plan based on over-excavation and under-excavation analysis. The robotic arm execution unit includes a shotcrete robotic arm, an axial drive mechanism for driving the shotcrete robotic arm to move axially, a circumferential drive mechanism for driving the shotcrete robotic arm to move circumferentially, and position and speed sensors disposed on the axial drive mechanism and the circumferential drive mechanism. The electro-hydraulic servo control component is connected to the manipulator execution unit and is used to drive the axial drive mechanism and the circumferential drive mechanism to move according to the received control commands; The follow-up dust removal unit includes a water cyclone dust collector and an air intake located next to the nozzle of the shotcrete robotic arm. The air intake moves synchronously with the shotcrete robotic arm. The overall control component is communicatively connected to the vehicle positioning and sensing unit, the 3D laser modeling unit, the electro-hydraulic servo control component, and the follow-up dust removal unit. Based on the spray path planning generated by the 3D laser modeling unit and the attitude data fed back by the vehicle positioning and sensing unit, the overall control component controls the electro-hydraulic servo control component through a PID algorithm to form a closed-loop control of the robotic arm execution unit to adjust the spraying position.

[0019] In some embodiments of this disclosure, the vehicle positioning sensing unit includes: an inclination sensor for collecting tilt angle data of the vehicle body, a gyroscope for collecting angular velocity data of the vehicle body, and a speed encoder and a position sensor. The speed encoder and position sensor are disposed on the wheel of the trolley and are used to collect real-time position and speed data of the trolley.

[0020] In some embodiments of this disclosure, the three-dimensional laser modeling unit includes a lidar sensor integrated on the shotcrete bridge trolley, with a scanning range covering 270° of the tunnel cross section without blind spots; the overall control component is configured to: automatically stitch together multi-site cloud data, remove noisy point clouds, identify the topological features of the steel arch frame, calculate the zoned spraying volume based on the over- and under-excavation volume, and automatically generate the spraying path plan.

[0021] In some embodiments of this disclosure, both the axial drive mechanism and the circumferential drive mechanism include: a gear ring and rack assembly and a high-precision hydraulic motor, wherein the output end of the high-precision hydraulic motor is connected to a drive gear, and the drive gear meshes with the gear ring and rack assembly; the position and speed sensor is mounted on the drive gear.

[0022] In some embodiments of this disclosure, the electro-hydraulic servo control component includes: an electro-hydraulic servo hydraulic pump station and an electro-hydraulic proportional servo valve, wherein the electro-hydraulic proportional servo valve is connected between the high-precision hydraulic motor and the main control component; the main control component instructs the electro-hydraulic proportional servo valve to adjust the speed and position of the high-precision hydraulic motor through a PID program algorithm.

[0023] In some embodiments of this disclosure, the follow-up dust removal unit further includes: an air dust particle concentration detection sensor, used to detect the air pollution index in real time and feed it back to the main control component; the main control component automatically controls the start-up and shutdown of the water cyclone dust collector and the air volume adjustment according to the air pollution index.

[0024] In some embodiments of this disclosure, the air volume of the water cyclone dust collector is 6000-8000 cubic meters per hour, and the air inlet has a funnel-shaped structure.

[0025] In some embodiments of this disclosure, a quick-setting agent ratio control module and a shotcrete air volume and pressure control module are also included. The quick-setting agent ratio control module includes a sensor mounted on the quick-setting agent pump for real-time monitoring of the quick-setting agent ratio and feedback to the main control component. The shotcrete air volume and pressure control module is used to collect shotcrete air volume and pressure signals. The main control component is configured to perform closed-loop control using a PID algorithm based on the quick-setting agent ratio, air volume, and pressure signals, combined with the spray volume in the spray path planning.

[0026] In some embodiments of this disclosure, a leveling module disposed at the rear of the shotcrete robotic arm is also included, the leveling module including a scraper.

[0027] A method for three-dimensional scanning positioning and adaptive shotcreting control of a tunnel shotcreting bridge trolley includes the following steps: (1) Position and attitude control of shotcrete bridge trolley: The attitude and position data of the trolley are collected by the tilt sensor, gyroscope, speed encoder and position sensor installed on the shotcrete bridge trolley, and the data is transmitted to the PLC of the main control component. The axial and circumferential positions of the trolley and the attitude of the shotcrete robotic arm are adjusted in real time by the PID algorithm. (2) Dust control: A follow-up suction hood is installed next to the nozzle of the spraying robot arm. The suction hood is connected to the water cyclone dust collector. The dust concentration is detected in real time by the dust concentration sensor and the detection data is fed back to the main control component. The main control component controls the start and stop of the water cyclone dust collector and the air volume according to the dust concentration. (3) Three-dimensional laser modeling and path planning: Point cloud data of the inner wall of the tunnel is collected by the lidar sensor. After multi-sensor spatiotemporal synchronous calibration, automatic spatiotemporal stitching of multi-site point cloud, and noise point cloud removal, a three-dimensional point cloud model of the tunnel is constructed. The steel arch frame is identified and over-excavation and under-excavation analysis are performed to calculate the volume of spraying in each zone and automatically generate the spraying path. The lidar sensor adopts a two-dimensional laser scanner with a rotating mechanism to achieve three-dimensional scanning. The multi-sensor layout covers 270° of the tunnel cross section without blind spots. (4) Precision control of shotcrete robotic arm: An electro-hydraulic servo hydraulic closed-loop component is adopted. The motion signals are collected by the position and speed sensors installed on the axial and circumferential motion mechanism of the shotcrete bridge and the shotcrete robotic arm. The main control component controls the electro-hydraulic servo proportional valve according to the generated spray path through the PID algorithm to adjust the speed and position of each moving part and realize the precise movement of the shotcrete robotic arm. (5) Control of quick-setting agent ratio and shotcrete parameters: A sensor is installed on the quick-setting agent pump to monitor the quick-setting agent ratio in real time, and at the same time monitor the shotcrete air volume and pressure. The main control component adjusts the quick-setting agent ratio, air volume and pressure according to the spraying path and real-time feedback through PID algorithm to achieve closed-loop control; the adjustment of the shotcrete air volume and pressure is related to the spray volume of the point cloud model and the path planning to achieve adaptive control based on the spray volume. (6) Leveling: After the shotcrete is completed, the surface of the shotcrete is leveled by the scraper leveling component.

[0028] The beneficial effects of this invention are as follows: This invention achieves intelligent closed-loop control of the shotcrete process, significantly improving shotcrete accuracy and quality. It uses a vehicle positioning and sensing unit (tilt sensor, gyroscope, speed encoder) to collect real-time attitude and position data of the shotcrete bridge trolley. Combined with a tunnel point cloud model constructed by a 3D laser modeling unit, the overall control component uses a PID algorithm to precisely adjust the electro-hydraulic servo control component, forming a fully closed-loop control system of "perception-decision-execution-feedback". Position and speed sensors on the axial / circumferential motion mechanisms and the shotcrete robotic arm provide real-time feedback on the motion status, with a closed-loop response speed of less than 200 milliseconds. This ensures the shotcrete robotic arm strictly follows the preset path, effectively solving the technical problems of poor self-positioning accuracy and low motion path planning execution accuracy of existing shotcrete bridge trolleys, and significantly improving the consistency of shotcrete thickness and the accuracy of steel arch coverage.

[0029] The invention features a dynamic dust removal system linked to dust concentration feedback, significantly improving the working environment inside tunnels. The suction hood is positioned next to the nozzle of the shotcrete robotic arm and moves synchronously with it, achieving "source dust capture" before dust particles spread. The suction hood employs a trumpet-shaped structure, working in conjunction with a water-cyclone dust collector (handling an air volume of 6200-6800 m³ / h) to efficiently capture dust particles generated during shotcreting. Simultaneously, an airborne dust particle concentration sensor monitors the air pollution index inside the tunnel in real time and feeds it back to the central control unit. The central control unit automatically controls the start / stop and airflow adjustment of the dust removal fan based on the dust concentration, enabling on-demand operation of the dust removal system. This ensures a clean working environment while avoiding energy waste.

[0030] By combining 3D laser modeling with intelligent path planning, adaptive control of shotcrete volume is achieved. This invention uses a 2D laser scanner with a rotating mechanism to achieve 270° blind-spot-free 3D scanning of the tunnel cross-section. Through multi-sensor spatiotemporal synchronous calibration, automatic stitching of multi-site point clouds, and noise point cloud removal, a high-precision 3D point cloud model of the tunnel is constructed. Based on this, the system can automatically identify the topological characteristics of the steel arch frame, perform dynamic over-excavation and under-excavation analysis, calculate the shotcrete volume for each zone based on the over-excavation and under-excavation volumes, and automatically generate the optimal shotcrete path. This technology eliminates the reliance on manual experience in shotcrete operations, achieving precise matching between shotcrete volume and over-excavation / under-excavation conditions, and avoiding excessive consumption or insufficient shotcreting of concrete materials.

[0031] The electro-hydraulic servo closed-loop control, in conjunction with a high-precision mechanical structure, improves the motion accuracy and reliability of the manipulator. This invention incorporates position and speed sensors on the axial drive mechanism, circumferential drive mechanism, and the shotcrete manipulator arm of the shotcrete bridge. A closed-loop control system is constructed using an electro-hydraulic servo hydraulic pump station and an electro-hydraulic proportional servo valve. By installing a speed-displacement encoder on the drive gear, combined with a high-precision machined gear ring and rack assembly, gear backlash is effectively reduced, and gear meshing accuracy is improved. The central control component uses a PID algorithm to adjust the speed and position of the hydraulic motor in real time, achieving precise control of each degree of freedom of the shotcrete manipulator arm and overcoming the shortcomings of low control accuracy and slow response speed in existing hydraulic drive systems.

[0032] The adaptive adjustment of the accelerator ratio and shotcrete parameters ensures the stability of concrete shotcrete performance. This invention adds a sensor to the accelerator pump to monitor the accelerator ratio in real time and feed it back to the central control unit, while simultaneously collecting shotcrete airflow and pressure signals. Based on the shotcrete volume calculated using the point cloud model and path planning, the central control unit adjusts the accelerator ratio, airflow, and pressure in real time using a PID algorithm, achieving dynamic optimization of concrete shotcrete parameters. This technique ensures that the concrete slurry has suitable viscosity and fluidity under different working conditions, effectively improving the adhesion performance and rebound rate control of shotcrete.

[0033] By combining modular design with simulation testing, the risks and costs of on-site commissioning are reduced. This invention constructs a tunnel model with a diameter of 6m and a longitudinal length of 5.4m (3 rings). The tunnel walls are made of 3mm thick removable steel plates with seepage holes, which can simulate complex geological conditions such as fissure water and fault fracture zones. Indoor simulation tests are used to pre-commission and optimize the parameters of the shotcrete system, effectively reducing material consumption and safety risks in on-site testing, shortening the on-site commissioning cycle, and improving the system's reliability in actual engineering projects.

[0034] The waste collection and leveling device work together to achieve the recycling of rebound material and improve surface quality. This invention installs a waste collection component on the shotcrete bridge trolley. The waste collection box, combined with a 270° rotating scraper, effectively collects rebound material generated during shotcreting, reducing material waste and subsequent cleaning workload. Simultaneously, a leveling module (preferably a scraper-type leveling device) is installed at the rear of the shotcrete robotic arm to level the sprayed concrete surface, improving the surface smoothness of the tunnel lining and reducing subsequent manual finishing work.

[0035] In summary, this invention organically integrates technologies such as mechanical structure optimization, electro-hydraulic servo control, 3D laser modeling, intelligent path planning, and follow-up dust removal to construct a tunnel shotcrete operation system that integrates precise positioning, adaptive spraying, efficient dust removal, and waste recycling. This significantly improves the automation level, operational accuracy, and environmental protection level of tunnel shotcrete, and has outstanding substantive features and remarkable progress. Attached Figure Description

[0036] Figure 1 Schematic diagram of the development route for a rapid dust removal and rebound material collection device for shotcrete in TBM tunnels; Figure 2 This is a schematic diagram of the tunnel model structure; Figure 3 A schematic diagram of a rapid dust removal and rebound material collection device for TBM tunnel shotcrete. Figure 4 Schematic diagram of the installation structure of the rapid dust removal and rebound material collection device for TBM tunnel shotcrete; Figure 5 Structural block diagram of a 3D scanning positioning and adaptive shotcreting control device for a tunnel shotcreting bridge trolley; Figure 6 A schematic diagram of the installation structure for the robotic arm control module; The components in the diagram are as follows: 1. Shotcrete bridge trolley; 2. Robotic arm circular slide rail; 3. Shotcrete robotic arm; 4. Multi-axis spray gun; 5. Water vortex dust collector; 6. Suction hood; 7. 2D laser scanner; 8. Detachable steel plate; 9. Drainage hole; 10. Steel track; 11. Water vortex fan; 12. Track wheel; 13. Tilt sensor; 14. Speed ​​encoder; 15. Position sensor; 16. I-beam; 17. Waste collection box; 18. Scraper; 19. Leveling module; 20. Main control assembly; 21. Electro-hydraulic servo control assembly. Detailed Implementation

[0037] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention. Example 1

[0038] This example discloses a rapid dust removal and rebound material collection device for TBM tunnel shotcrete and its control method. (See also...) Figures 1 to 6 It includes a shotcrete bridge trolley 1; a robotic arm ring slide rail 2 is installed on the shotcrete bridge trolley 1 to support the movement of the shotcrete robotic arm 3 for spraying concrete onto the tunnel wall; the shotcrete robotic arm 3 is connected to a multi-axis spray gun 4 for providing concrete slurry. A dust removal component is installed on the shotcrete bridge trolley 1. The dust removal component includes a water cyclone dust collector 5 and a suction hood 6. The suction hood 6 is located near the shotcrete robotic arm 3 and moves with the shotcrete robotic arm 3 to remove dust generated by shotcrete in real time. A 3D modeling component is installed on the shotcrete bridge trolley 1. The 3D modeling component includes a 2D laser scanner 7 and a rotating mechanism. The rotating mechanism drives the 2D laser scanner to rotate to obtain 3D point cloud data of the tunnel inner wall.

[0039] The 3D modeling component also includes a pose calibration module for multiple scanners, which is used to unify the point cloud data acquired by multiple 2D laser scanners into the same coordinate system.

[0040] The 3D modeling component also includes a coordinate system transformation module, which is used to transform point cloud data in the local coordinate system of the 2D laser scanner to the global coordinate system of the construction.

[0041] It also includes a tunnel model for simulating real tunnel environments for testing. The tunnel model includes a steel track 10 set at the bottom of the tunnel, a tunnel frame and a tunnel wall composed of detachable steel plates 8. The tunnel frame is an I-beam 16, and multiple seepage holes 9 are set on the detachable steel plates 8. The tunnel model has a geological simulation structure that simulates fracture water and fault fracture zones.

[0042] It also includes a water-cyclone fan 11, which has track wheels 12 at its bottom and can move on steel rails 10. The water-cyclone fan 11 is installed on the section of the shotcrete bridge trolley that is close to the shotcrete robotic arm.

[0043] The tunnel model has a diameter of 6m and a longitudinal length of 5.4m (3 rings). The tunnel frame is made of 200mm*200mm I-beams. The tunnel wall model is made of 3mm thick detachable steel plates with a width of 1740mm and a length of 1790mm.

[0044] The shotcrete bridge trolley is also equipped with a waste collection component, which includes a waste collection box 17 and a scraper 18. The scraper 18 can rotate 270 degrees around the shotcrete bridge trolley to scrape off the waste.

[0045] The water cyclone dust collector has external dimensions of 2000*1480*2570mm, a processing air volume of 6200-6800 m³ / h, an air inlet size of φ400mm, and a water storage capacity of 1.2 m³.

[0046] The movable range of the shotcrete robotic arm is 5120mm, and the length of the shotcrete bridge trolley is 7060mm and the height is 2867mm.

[0047] A three-dimensional scanning positioning and adaptive shotcreting control device for a tunnel shotcreting bridge trolley includes: a vehicle positioning and sensing unit, a three-dimensional laser modeling unit, an electro-hydraulic servo control component, a follow-up dust removal unit, and a main control component 20, all mounted on the shotcreting bridge trolley. The vehicle positioning unit is used to collect the vehicle's attitude and position data in real time; The 3D laser modeling unit is used to scan the tunnel cross-section, construct a 3D point cloud model of the tunnel, and generate a jetting path plan based on over-excavation and under-excavation analysis. The robotic arm execution unit includes a shotcrete robotic arm, an axial drive mechanism for driving the shotcrete robotic arm to move axially, a circumferential drive mechanism for driving the shotcrete robotic arm to move circumferentially, and position and speed sensors mounted on the axial drive mechanism and the circumferential drive mechanism. The electro-hydraulic servo control component 21 is connected to the robot arm execution unit and is used to drive the axial drive mechanism and the circumferential drive mechanism to move according to the received control commands; The follow-up dust removal unit includes a water cyclone dust collector and an air inlet located next to the nozzle of the shotcrete robotic arm. The air inlet moves synchronously with the shotcrete robotic arm. The main control unit 20 is communicatively connected to the vehicle positioning and sensing unit, the 3D laser modeling unit, the electro-hydraulic servo control unit, and the follow-up dust removal unit. Based on the spray path planning generated by the 3D laser modeling unit and the attitude data fed back by the vehicle positioning and sensing unit, the main control unit controls the electro-hydraulic servo control unit 21 through a PID algorithm to form a closed-loop control of the manipulator execution unit to adjust the spraying position.

[0048] The vehicle positioning and sensing unit includes: an inclination sensor 13 for collecting tilt angle data of the vehicle body, a gyroscope for collecting angular velocity data of the vehicle body, a speed encoder 14 and a position sensor 15. The speed encoder 14 and the position sensor 15 are disposed on the wheel of the trolley and are used to collect the real-time position and speed data of the trolley.

[0049] The 3D laser modeling unit includes a lidar sensor integrated on the shotcrete bridge trolley, with a scanning range covering 270° of the tunnel cross section without blind spots; the overall control component is configured to automatically stitch together multi-site cloud data, remove noisy point clouds, identify the topological features of the steel arch frame, calculate the spraying volume of each zone based on the over- and under-excavation volume, and automatically generate a spraying path plan.

[0050] Both the axial drive mechanism and the circumferential drive mechanism include: a gear ring and rack assembly and a high-precision hydraulic motor. The output end of the high-precision hydraulic motor is connected to a drive gear, which meshes with the gear ring and rack assembly. A position and speed sensor is mounted on the drive gear.

[0051] The electro-hydraulic servo control component includes an electro-hydraulic servo hydraulic pump station and an electro-hydraulic proportional servo valve. The electro-hydraulic proportional servo valve is connected between the high-precision hydraulic motor and the main control component. The main control component uses a PID program algorithm to instruct the electro-hydraulic proportional servo valve to adjust the speed and position of the high-precision hydraulic motor.

[0052] The follow-up dust removal unit also includes: an air dust particle concentration detection sensor, which is used to detect the air pollution index in real time and feed it back to the main control component; the main control component automatically controls the start and stop of the water cyclone dust collector and adjusts the air volume according to the air pollution index.

[0053] The suction volume of the water cyclone dust collector is 6000-8000 cubic meters per hour, and the suction port has a funnel-shaped structure.

[0054] It also includes a quick-setting agent ratio control module and a shotcrete air volume and pressure control module. The quick-setting agent ratio control module includes a sensor installed on the quick-setting agent pump to monitor the quick-setting agent ratio in real time and feed it back to the main control component. The shotcrete air volume and pressure control module is used to collect shotcrete air volume and pressure signals. The main control component is configured to perform closed-loop control through a PID algorithm based on the quick-setting agent ratio, air volume and pressure signals, combined with the spray volume in the spray path planning.

[0055] It also includes a leveling module 19 located at the rear of the shotcrete robotic arm, the leveling module including a scraper.

[0056] A method for three-dimensional scanning positioning and adaptive shotcreting control of a tunnel shotcreting bridge trolley includes the following steps: (1) Position and attitude control of shotcrete bridge trolley: The attitude and position data of the trolley are collected by the tilt sensor, gyroscope, speed encoder and position sensor installed on the shotcrete bridge trolley, and the data is transmitted to the PLC of the main control component. The axial and circumferential positions of the trolley and the attitude of the shotcrete robotic arm are adjusted in real time by the PID algorithm. (2) Dust control: A follow-up suction hood is installed next to the nozzle of the spraying robot arm. The suction hood is connected to the water cyclone dust collector. The dust concentration is detected in real time by the dust concentration sensor and the detection data is fed back to the main control component. The main control component controls the start and stop of the water cyclone dust collector and the air volume according to the dust concentration. (3) Three-dimensional laser modeling and path planning: Point cloud data of the tunnel inner wall is collected by lidar sensor, and a three-dimensional point cloud model of the tunnel is constructed by multi-sensor spatiotemporal synchronous calibration, automatic splicing of multi-site point cloud, and noise point cloud removal; steel arch frame is identified and over-excavation and under-excavation analysis is performed, the volume of spraying in each zone is calculated, and the spraying path is automatically generated; the lidar sensor adopts a two-dimensional laser scanner with a rotating mechanism to realize three-dimensional scanning, and the multi-sensor layout covers 270° of the tunnel cross section without blind spots; (4) Precision control of shotcrete robotic arm: An electro-hydraulic servo hydraulic closed-loop component is adopted. The motion signals are collected by the position and speed sensors installed on the axial and circumferential motion mechanism of the shotcrete bridge and the shotcrete robotic arm. The main control component controls the electro-hydraulic servo proportional valve according to the generated spray path through the PID algorithm to adjust the speed and position of each moving part and realize the precise movement of the shotcrete robotic arm. (5) Control of quick-setting agent ratio and shotcrete parameters: A sensor is installed on the quick-setting agent pump to monitor the quick-setting agent ratio in real time, and at the same time monitor the shotcrete air volume and pressure. The main control component adjusts the quick-setting agent ratio, air volume and pressure according to the spraying path and real-time feedback through PID algorithm to achieve closed-loop control; the adjustment of shotcrete air volume and pressure is related to the spray volume of the point cloud model and path planning to achieve adaptive control based on the spray volume. (6) Leveling: After the shotcrete is completed, the surface of the shotcrete is leveled by the scraper leveling component.

[0057] Indoor testing is a crucial step in the successful development of an intelligent shotcrete system. By simulating the real environment of a tunnel, tests can highlight the challenges that need to be addressed in advance. Continuous improvement during the testing process provides experience and technical support for the system's field application. This test mainly includes the construction of a tunnel model, the composition of the shotcrete system, the selection and installation of dust removal components, the deployment of the 3D modeling system, and the overall control system assembly. This test is capable of simulating real-world shotcrete scenarios.

[0058] 1) Construction of the tunnel model Building a tunnel model requires balancing structural accuracy with detailed representation. To accurately simulate shotcrete effects while minimizing costs, this experiment set the tunnel diameter to 6m. This ensures sufficient space within the tunnel to accommodate the shotcrete trolley equipped with dust removal components and a shotcrete robotic arm, while maintaining a safe distance between the shotcrete nozzle and the tunnel wall. The tunnel's longitudinal length is 5.4m (3 rings). The tunnel frame uses 200mm x 200mm I-beams. The tunnel walls are simulated using 3mm thick, removable steel plates, 1740mm wide and 1790mm long. This tunnel is designed to simulate special geological features such as fissure water and fault fracture zones.

[0059] 2) Composition of the shotcrete system The shotcrete system mainly consists of a multi-axis spray gun, a shotcrete bridge trolley, a shotcrete robotic arm, a lidar, a water-swirling fan and dust removal system, and a waste collection system. The shotcrete bridge trolley is 7060mm long and 2867mm high, and the shotcrete robotic arm has a movable range of 5120mm. The parameters of the multi-axis spray gun are shown in the table below.

[0060] Parameter table of multi-axis spray gun

[0061] 3) Selection and installation of dust removal components Working Principle: The hydrocyclone dust collector is a highly efficient wet dust collection device. Its core working principle is based on the dual effects of centrifugal force and liquid film adsorption. Dust-laden gas enters the cylinder through a tangential inlet, forming a high-speed rotating airflow. This causes the dust particles to be thrown against the cylinder wall under centrifugal force. A pre-formed water film on the inner wall of the cylinder collides with the dust particles, capturing them and discharging them with the water flow. Simultaneously, fine dust particles condense with secondary water droplets generated under the impact of the airflow, achieving efficient separation. The purified gas is discharged through a dehydration device, ensuring the cleanliness of the outlet gas. This equipment has a simple structure, is easy to maintain, and is suitable for high-concentration dust treatment, especially for industrial dust removal needs in high-temperature and high-humidity environments.

[0062] Research indicates that current TBM shotcreting methods, whether manual or intelligent, suffer from poor dust control, leading to harsh working conditions and a high risk of pneumoconiosis in manual processes. Intelligent shotcreting faces the challenge of continuous operation due to the limitations of laser scanning, hindering continuous spraying. Therefore, this application selects a water-cyclone dust collector for real-time dust removal during the shotcreting process. The water-cyclone fan is installed on the shotcreting bridge trolley near the robotic arm, while the suction hood is installed near the robotic arm, moving with the spray head to remove dust generated during concrete spraying. The water-cyclone fan has dimensions of 2000*1480*2570mm and a processing air volume of 6200-6800m³. 3 / h, air inlet size φ400mm, water storage capacity 1.2m 3 .

[0063] 4) 3D modeling based on laser scanning Tunnel boring machines operate in a complex environment characterized by dust, vibration, and poor lighting. Hard rock tunnel boring machines (TBMs) are the world's most advanced ultra-large specialized equipment for tunnel boring, primarily used in railway, highway, and hydropower projects involving hard rock tunnels. The upcoming YX Hydropower Station, a major project in my country, will require TBMs for excavation of multiple tunnels. The automation and intelligentization of TBM's various functional modules are crucial for accelerating construction progress. Environmental perception is a prerequisite for intelligent automation; traditional vision methods are insufficient, hence the choice of laser scanning technology. Currently available high-precision 3D laser scanners, such as Faro, Riegl, and Leica, are expensive and difficult to operate continuously in harsh environments. Furthermore, their performance is excessive for applications where high precision is not required. To address these issues, numerous scholars both domestically and internationally have explored and developed low-cost 3D laser scanners applicable to relevant fields. The most common approach utilizes a 2D laser scanner combined with a rotating actuator (such as a turntable) to achieve 3D scanning; these scanners are known as DIY 3D laser scanners.

[0064] This project takes the development of an intelligent shotcrete system integrated into a TBM as an example to explore several key technologies involved in environmental perception using an engineering-grade laser sensor integrated with a three-dimensional laser system. These technologies include performance testing of the integrated system, pose calibration between multiple scanning sensing systems, and a scheme for converting the local scanning coordinate system to the global construction coordinate system, thus solving the problem of applying intelligent automation in complex environments.

[0065] To better address the current issues in intelligent tunnel shotcrete systems, market research and on-site visits revealed that the self-positioning accuracy and spraying motion path planning execution accuracy of the TBM intelligent shotcrete system's shotcrete bridge trolley are the primary technical challenges. This requires improving the manufacturing and control precision of the various mechanical components of the shotcrete bridge trolley. By enhancing the mechanical and electrical control precision of each actuator in the shotcrete path planning process, precise control of the spray gun position can be achieved. The main modules of the control system are: vehicle position, attitude, and speed control module; 3D laser modeling perception and path planning module; shotcrete robotic arm precision control module; accelerator ratio and shotcrete airflow and pressure control module; and dust removal module.

[0066] 1) Shotcrete bridge position, attitude, and speed control module The shotcrete bridge trolley's own position and attitude positioning system requires the installation of tilt sensors and gyroscopes on the vehicle body to collect the vehicle body attitude data and transmit the data to the main control system PLC. The PID program algorithm then adjusts the axial and circumferential directions of the shotcrete bridge and the position and attitude of the shotcrete robotic arm in real time.

[0067] The shotcrete bridge trolley has high requirements for the posture and self-positioning of the vehicle body during operation. The preliminary solution is to install speed encoders and position sensors on the wheels of the trolley. The algorithm monitors and provides feedback on the posture and position information of the trolley in real time, and transmits all the collected monitoring data to the intelligent shotcrete system control platform. Through high-performance PLC program algorithms, instructions are issued to various mechanisms on the shotcrete trolley that participate in the path planning of the shotcrete robotic arm.

[0068] 2) Dust removal system control module The dust removal system employs a water cyclone dust collector, initially designed with a suction capacity of 6000-8000 cubic meters. The water cyclone dust collector draws particulate pollutants into the treatment chamber, where they are purified by water flow, clean air is discharged, and dust particles settle. The suction inlet of the water cyclone dust collector is installed next to the nozzle of the shotcrete robotic arm. The dust collector automatically starts during shotcreting. The suction inlet is designed in a funnel shape and can move synchronously with the shotcrete nozzle, drawing dust particles into the treatment chamber before they diffuse. An air dust particle concentration sensor is installed to monitor the air pollution index in real time and feed this parameter back to the intelligent shotcrete system's central control platform. The central control platform determines when to activate the dust collector fan based on the on-site dust concentration.

[0069] 3) 3D laser modeling perception and path planning module The system comprehensively improves work efficiency and accuracy by completing the selection and integrated control of lidar sensors, optimizing the spatial layout of multiple sensors, and performing spatiotemporal synchronous calibration of multi-source sensors, achieving 270° blind-spot-free coverage of the tunnel cross-section and high-precision point cloud data acquisition; it also completes automatic stitching of multi-site point clouds, noise point cloud removal, and construction of a 3D point cloud model of the tunnel; it completes the identification of steel arch topology features and the research on dynamic over- and under-excavation intelligent analysis, achieving high-accuracy identification of steel arches and effective separation of the shotcrete surface and support structure point cloud based on over- and under-excavation analysis and adaptive control decision of shotcrete thickness; and it calculates the zoned shotcrete volume based on the over- and under-excavation volume and automatically generates the shotcrete path.

[0070] 4) Precision control module for shotcrete bridge and shotcrete robotic arm The axial and radial motion control of the shotcrete bridge is as follows: the existing shotcrete bridge consists of a gear ring beam and an axial rack slide rail. The shotcrete robotic arm carrier uses a trolley with gears meshing with the gear ring to achieve circumferential spraying. The motion posture of the shotcrete robotic arm is executed by a swing cylinder and a cycloidal hydraulic motor. All power sources are hydraulically driven.

[0071] The hydraulic system driving the shotcrete bridge in this project adopts an electro-hydraulic servo hydraulic closed-loop system. The mechanical mechanisms controlling the movement of the shotcrete robotic arm, including the circumferential motion gear carriage and the axial motion drive carriage, both utilize high-precision hydraulic motors and electro-hydraulic proportional servo valves. The overall shotcrete control system collects signals from position sensors installed on the axial / circumferential / shotcrete robotic arm components. Through the PID program algorithm of the overall control system, it instructs the electro-hydraulic servo proportional valves to adjust the speed and position of the gear carriage. The existing shotcrete robotic arm structure design has been optimized to improve the rigidity and manufacturing precision of the robotic arm itself. Position and speed sensors have been added to the rotating brushing parts, and a stroke closed-loop hydraulic servo system has been implemented to improve the motion accuracy and spray nozzle attitude control during the shotcrete process. The power system control is completed by the electro-hydraulic servo hydraulic system. The preliminary implementation plan involves improving the machining accuracy of the gear ring and rack gears, reducing gear backlash, and enhancing gear meshing accuracy. In the circumferential / axial motion control module, a speed-displacement encoder is installed on the axial / circumferential drive gear. After the main control system receives the shotcrete path planning signal, the high-performance motion controller (PLC) of the main control system collects speed signals, position signals, and shotcrete head position signals from the axial and circumferential motion of the shotcrete bridge and the motion execution system of the shotcrete robotic arm. Precise control is achieved through the PID program algorithm of the main control system.

[0072] The shotcrete main control system issues motion commands, and the electro-hydraulic servo hydraulic system can precisely control the axial and circumferential movement of the shotcrete bridge and the movement position of the spray gun head. Based on the path planning of the point cloud model given by the laser 3D model, the shotcrete operation is carried out. During the shotcrete operation, the system will continuously detect the motion accuracy signal of the shotcrete bridge and the positioning attitude signal of the shotcrete trolley. The system will then use the PID program algorithm of the main control system to adjust the position (response time <200 milliseconds) to achieve the shotcrete position requirements of the laser 3D model.

[0073] The above shotcrete system's mechanical actuators achieve closed-loop control, i.e., a fully closed-loop mode composed of electrical and hydraulic components. The hydraulic part is an electro-hydraulic servo hydraulic pump station. Position sensors are installed on the axial / radial movement parts of the shotcrete bridge and the movement parts of the spray gun frame. Through the PLC of the main control system and the algorithm of the PID program, precise control of the shotcrete actuators is achieved.

[0074] 5) Accelerator ratio and shotcrete air volume and pressure control module In intelligent shotcrete systems, the proportion of accelerators determines the effectiveness of automated shotcrete. The initial design involves adding sensors to existing accelerator pumps to monitor and provide feedback on the accelerator proportions in real time. The signals of shotcrete airflow and pressure are used in a closed-loop control system, integrating with the point cloud model and path planning to control the spray volume. The PID algorithm of the central control system adjusts the relationship between airflow, pressure, and flow rate in real time, further improving their accuracy to control the viscosity and fluidity of the concrete. The system calculates and provides appropriate slurry spraying parameters for the shotcrete operation.

[0075] 6) Leveling System Module The high-performance concrete spraying system developed by Xinjiang ABH Hydropower Bureau No. 3 includes a leveling device after concrete spraying. It features two leveling devices: a scraper and a spindle roller. However, field verification showed that the scraper performed better, while the spindle roller resulted in significant material adhesion. Therefore, this device was designed with a scraper as the leveling device.

[0076] Although some preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0077] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this application and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A three-dimensional scanning positioning and adaptive shotcreting control device for a tunnel shotcreting bridge trolley, characterized in that, include: The components installed on the shotcrete bridge trolley include a vehicle positioning and sensing unit, a 3D laser modeling unit, an electro-hydraulic servo control component, a follow-up dust removal unit, and a main control component. The vehicle positioning unit is used to collect the vehicle's attitude and position data in real time. The three-dimensional laser modeling unit is used to scan the tunnel cross-section, construct a three-dimensional point cloud model of the tunnel, and generate a jetting path plan based on over-excavation and under-excavation analysis. The robotic arm execution unit includes a shotcrete robotic arm, an axial drive mechanism for driving the shotcrete robotic arm to move axially, a circumferential drive mechanism for driving the shotcrete robotic arm to move circumferentially, and position and speed sensors disposed on the axial drive mechanism and the circumferential drive mechanism. The electro-hydraulic servo control component is connected to the manipulator execution unit and is used to drive the axial drive mechanism and the circumferential drive mechanism to move according to the received control commands; The follow-up dust removal unit includes a water cyclone dust collector and an air intake located next to the nozzle of the shotcrete robotic arm. The air intake moves synchronously with the shotcrete robotic arm. The overall control component is communicatively connected to the vehicle positioning and sensing unit, the 3D laser modeling unit, the electro-hydraulic servo control component, and the follow-up dust removal unit. Based on the spray path planning generated by the 3D laser modeling unit and the attitude data fed back by the vehicle positioning and sensing unit, the overall control component controls the electro-hydraulic servo control component through a PID algorithm to form a closed-loop control of the robotic arm execution unit to adjust the spraying position.

2. The three-dimensional scanning positioning and adaptive shotcreting control device for tunnel shotcreting bridge trolleys as described in claim 1, characterized in that: The vehicle positioning and sensing unit includes: an inclination sensor for collecting tilt angle data of the vehicle body, a gyroscope for collecting angular velocity data of the vehicle body, a speed encoder and a position sensor. The speed encoder and position sensor are installed on the wheels of the trolley and are used to collect real-time position and speed data of the trolley.

3. The three-dimensional scanning positioning and adaptive shotcreting control device for tunnel shotcreting bridge trolleys as described in claim 1, characterized in that: The three-dimensional laser modeling unit includes a lidar sensor integrated on the shotcrete bridge trolley, with a scanning range covering 270° of the tunnel cross section without blind spots; the overall control component is configured to automatically stitch together multi-site cloud data, remove noisy point clouds, identify the topological features of the steel arch frame, calculate the spraying volume of each zone based on the over- and under-excavation volume, and automatically generate the spraying path plan.

4. The three-dimensional scanning positioning and adaptive shotcreting control device for tunnel shotcreting bridge trolleys as described in claim 1, characterized in that: Both the axial drive mechanism and the circumferential drive mechanism include: a gear ring and rack assembly and a high-precision hydraulic motor. The output end of the high-precision hydraulic motor is connected to a drive gear, which meshes with the gear ring and rack assembly. The position and speed sensor is mounted on the drive gear. The electro-hydraulic servo control component includes: an electro-hydraulic servo hydraulic pump station and an electro-hydraulic proportional servo valve. The electro-hydraulic proportional servo valve is connected between the high-precision hydraulic motor and the main control component. The main control component uses a PID program algorithm to instruct the electro-hydraulic proportional servo valve to adjust the speed and position of the high-precision hydraulic motor.

5. The three-dimensional scanning positioning and adaptive shotcreting control device for tunnel shotcreting bridge trolleys as described in claim 1, characterized in that: The follow-up dust removal unit also includes: an air dust particle concentration detection sensor, used to detect the air pollution index in real time and feed it back to the main control component; the main control component automatically controls the start and stop of the water cyclone dust collector and the air volume adjustment according to the air pollution index; the air intake of the water cyclone dust collector is 6000-8000 cubic meters / hour, and the air intake is in the shape of a trumpet.

6. The three-dimensional scanning positioning and adaptive shotcreting control device for tunnel shotcreting bridge trolleys as described in claim 1, characterized in that: It also includes a quick-setting agent ratio control module and a shotcrete air volume and pressure control module. The quick-setting agent ratio control module includes a sensor installed on the quick-setting agent pump for real-time monitoring of the quick-setting agent ratio and feedback to the main control component. The shotcrete air volume and pressure control module is used to collect shotcrete air volume and pressure signals. The main control component is configured to perform closed-loop control using a PID algorithm based on the quick-setting agent ratio, air volume, and pressure signals, combined with the shotcrete volume in the shotcrete path planning.

7. The three-dimensional scanning positioning and adaptive shotcreting control device for tunnel shotcreting bridge trolleys as described in claim 1, characterized in that: It also includes a leveling module located at the rear of the shotcrete robotic arm, the leveling module including a scraper.

8. A three-dimensional scanning positioning and adaptive shotcreting control method for a tunnel shotcreting bridge trolley, applicable to the three-dimensional scanning positioning and adaptive shotcreting control device for a tunnel shotcreting bridge trolley as described in any one of claims 1 to 7, characterized in that, Includes the following steps: (1) Position and attitude control of shotcrete bridge trolley: The attitude and position data of the trolley are collected by the tilt sensor, gyroscope, speed encoder and position sensor installed on the shotcrete bridge trolley, and the data is transmitted to the PLC of the main control component. The axial and circumferential positions of the trolley and the attitude of the shotcrete robotic arm are adjusted in real time by the PID algorithm. (2) Dust control: A follow-up suction hood is installed next to the nozzle of the spraying robot arm. The suction hood is connected to the water cyclone dust collector. The dust concentration is detected in real time by the dust concentration sensor and the detection data is fed back to the main control component. The main control component controls the start and stop of the water cyclone dust collector and the air volume according to the dust concentration. (3) Three-dimensional laser modeling and path planning: Point cloud data of the inner wall of the tunnel is collected by the lidar sensor. After multi-sensor spatiotemporal synchronous calibration, automatic spatiotemporal stitching of multi-site point cloud, and noise point cloud removal, a three-dimensional point cloud model of the tunnel is constructed. The steel arch frame is identified and over-excavation and under-excavation analysis are performed to calculate the volume of spraying in each zone and automatically generate the spraying path. The lidar sensor adopts a two-dimensional laser scanner with a rotating mechanism to achieve three-dimensional scanning. The multi-sensor layout covers 270° of the tunnel cross section without blind spots. (4) Precision control of shotcrete robotic arm: An electro-hydraulic servo hydraulic closed-loop component is adopted. The motion signals are collected by the position and speed sensors installed on the axial and circumferential motion mechanism of the shotcrete bridge and the shotcrete robotic arm. The main control component controls the electro-hydraulic servo proportional valve according to the generated spray path through the PID algorithm to adjust the speed and position of each moving part and realize the precise movement of the shotcrete robotic arm. (5) Control of quick-setting agent ratio and shotcrete parameters: A sensor is installed on the quick-setting agent pump to monitor the quick-setting agent ratio in real time, and at the same time monitor the shotcrete air volume and pressure. The main control component adjusts the quick-setting agent ratio, air volume and pressure according to the spraying path and real-time feedback through PID algorithm to achieve closed-loop control; the adjustment of the shotcrete air volume and pressure is related to the spray volume of the point cloud model and the path planning to achieve adaptive control based on the spray volume. (6) Leveling: After the shotcrete is completed, the surface of the shotcrete is leveled by the scraper leveling component.

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