Intelligent wet spraying machine and spraying control method

Abstract

The invention belongs to the technical field of wet spraying machines, and discloses an intelligent wet spraying machine and a spraying control method, and the method comprises the steps: obtaining the actual contour point cloud of a working face through a three-dimensional scanning device; comparing the data with a design model to generate deviation data; based on the deviation data, the motion path of the mechanical arm is planned, and the injection flow of the concrete pump and the motion speed of the mechanical arm are cooperatively controlled so as to accurately match the target injection thickness required by each area; and in the spraying process, the sprayed forming thickness is monitored in real time through an after-spraying detection device arranged at the tail end of the mechanical arm, follow-up spraying parameters are dynamically adjusted according to the feedback thickness deviation, and closed-loop control over the spraying quality is formed. The intelligent wet spraying machine disclosed by the invention integrates a posture sensing module, an environment sensing module, an after-spraying detection device and a control module. According to the invention, the spraying error can be controlled within a relatively low range, the material waste is reduced, unmanned operation is realized, and the construction quality, efficiency and safety are improved.

Description

Technical Field

[0001] This invention belongs to the field of wet spraying machine technology, specifically relating to an intelligent wet spraying machine and a spraying control method. Background Technology

[0002] In infrastructure projects such as tunnels and slope engineering, wet shotcrete machines are core equipment for concrete spraying, and their performance directly determines project quality and construction efficiency. Traditional wet shotcrete machines suffer from the following key problems:

[0003] 1. High reliance on manual labor: Operators need to visually observe the tunnel outline and manually adjust the joint angles and spraying parameters of the robotic arm. Subjective judgment errors can easily lead to uneven concrete spraying thickness (often with an error of ±50mm or more), affecting the structural strength and waterproofing performance of the project.

[0004] 2. Lack of working condition perception: There are no real-time angle monitoring devices for the various moving joints of the robotic arm (such as the upper arm-lower arm connection joint, the pitch joint of the spray arm, etc.), which cannot accurately reflect the joint posture and are prone to deviation of the spray trajectory due to joint displacement deviation.

[0005] 3. Poor tunnel profile adaptation: The lack of digital perception of the actual shape of the tunnel means that when there is over-excavation, under-excavation, or irregular cross-section, the spraying path cannot be dynamically adjusted, resulting in material waste (waste rate of about 15%-20%) and construction rework.

[0006] Currently, the infrastructure industry is continuously upgrading its demands for construction precision (requiring a spraying error of ≤10mm), efficiency (requiring a 30% increase in daily output per machine), and safety. The technical shortcomings of traditional wet spraying machines have become a key bottleneck restricting the improvement of project quality, and it is urgent to achieve a performance breakthrough through intelligent transformation. Summary of the Invention

[0007] The present invention aims to at least partially solve the aforementioned technical problems. Therefore, the objective of the present invention is to provide an intelligent wet spraying machine and a spraying control method.

[0008] To achieve the above objectives, the present invention provides a spray control method for an intelligent wet spraying machine, comprising the following steps:

[0009] Environmental perception step: Use a 3D scanning device to scan the working surface to be sprayed to obtain the original point cloud data of the actual contour;

[0010] Model comparison steps: After processing the raw point cloud data, compare it with the preset design model to generate deviation data that characterizes the over-excavation or under-excavation state of the working face;

[0011] Path planning steps: Based on deviation data, automatically plan the spray path, including the motion trajectory of the robotic arm end effector and the target spray thickness;

[0012] Collaborative control steps: Based on the spraying path, the spraying flow rate of the concrete pump and the movement speed of the robotic arm are collaboratively controlled to ensure that the actual spraying thickness approximates the target spraying thickness. This step achieves precise control of the spraying quantity by establishing a dynamic model of spraying thickness, flow rate, and arm speed.

[0013] Real-time feedback process: During the spraying process, the post-spray detection device set at the end of the robotic arm monitors the forming thickness of the sprayed area in real time, and dynamically adjusts the subsequent spraying parameters based on the difference between the monitoring results and the target spraying thickness, forming a closed-loop control of spraying quality.

[0014] Furthermore, before executing the injection path, the method of the present invention also includes a robotic arm posture calculation step: by collecting raw data from various sensors installed on each joint of the robotic arm, a multi-sensor data fusion algorithm (such as the Kalman filter algorithm) is used to calculate the high-precision real-time pose of the robotic arm end, providing a basis for accurate path execution.

[0015] The present invention also provides an intelligent wet spraying machine, including a wet spraying machine body, a multi-axis robotic arm, and a spraying system, and further includes:

[0016] Attitude sensing module: Installed at each moving joint of the multi-axis robotic arm, used to monitor the real-time motion status of each joint. Specifically, it may include a rotary encoder installed at the rotary joint, a tilt sensor installed at the pitch joint, and a cable sensor installed at the telescopic arm.

[0017] Environmental perception module: includes at least one 3D scanning device installed on the wet spraying machine for scanning the contour of the working surface to be sprayed.

[0018] Post-spray inspection device: preferably a line laser profile scanner, installed at the end of a multi-axis robotic arm (such as behind the nozzle), for real-time monitoring of the forming thickness of the sprayed area.

[0019] Control module: Electrically connected to the above modules and the injection system.

[0020] The control module is configured to execute the methods described in this invention, namely: acquiring and processing sensor data; planning a path based on deviation data; coordinating the control of spray flow and arm speed; and dynamically adjusting based on real-time feedback from the post-spray detection device. Furthermore, the control module incorporates a multi-sensor data fusion algorithm for accurately calculating the robotic arm's posture. Each sensor can communicate with the control module at high speed via a CAN bus, ensuring real-time data transmission.

[0021] The beneficial effects of this invention are as follows:

[0022] This invention achieves a complete closed loop of scanning, planning, collaborative control, and real-time feedback. In particular, it introduces real-time monitoring of post-spray thickness and flow-arm speed collaborative control, reducing the spray thickness error from more than ±50mm to within ±10mm.

[0023] This invention's automated path planning and precise material control significantly reduce material waste caused by overspraying (estimated to be reduced by 15%-20%), while avoiding rework and increasing the daily output of a single machine.

[0024] This invention employs multi-sensor data fusion technology, which effectively overcomes the errors and drift problems of single sensors, making the positioning and attitude control of the robotic arm more stable and reliable. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the structure of the intelligent wet spraying machine modification in an embodiment of the present invention.

[0026] Figure 2 This is a flowchart illustrating the injection control method in an embodiment of the present invention. Detailed Implementation

[0027] The technical solutions of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0028] It should be understood that, and also noted, in the embodiments, the functions / actions may appear in a different order than those shown in the figures. For example, depending on the functions / actions involved, they may actually be performed substantially concurrently, or sometimes the two figures shown consecutively may be performed in reverse order.

[0029] like Figure 1 As shown, this embodiment discloses an intelligent wet spraying machine based on the modification of a traditional six-axis wet spraying machine. The wet spraying machine includes a main body 1, a rotary boom 3, a pitch boom 4, a pitch arm 5, a telescopic arm 6, an end effector rotary arm 7, and a swing arm 8. The rotary boom 3, pitch boom 4, pitch arm 5, telescopic arm 6, end effector rotary arm 7, and swing arm 8 together constitute a multi-axis robotic arm.

[0030] The intelligent wet spraying machine of the present invention also includes a spraying system, an attitude sensing module, an environmental sensing module, a post-spraying detection device, and a control module.

[0031] The attitude perception module is designed to accurately acquire the robot arm's own attitude. High-precision sensors are installed on each key moving joint: a rotary encoder is installed on the drive shaft of the rotary arm 3 to detect its rotation angle relative to the vehicle body. Static tilt sensors are installed on the pitch arm 4 and pitch forearm 5 to detect their respective angles relative to the horizontal plane. A wire sensor is installed between the telescopic arm 6 and pitch forearm 5 to detect the extension length of the telescopic arm 6. Rotary encoders are installed on the output shafts of the end effector rotary arm 7 and swing arm 8 to detect their rotation angles.

[0032] All acquired sensor data is transmitted to the control module via the CAN bus at a frequency of no less than 100Hz. The control module runs an Extended Kalman Filter (EKF) algorithm to fuse multi-source heterogeneous data from the encoder, tilt sensor, and drawwire sensor. This algorithm uses the robotic arm's kinematic model as a prediction model and the measurements from each sensor as observations for state updates. This approach effectively filters out noise from individual sensors, compensates for dynamic errors in the tilt sensor, and corrects for cumulative encoder errors, ultimately outputting a highly accurate and robust set of Cartesian space coordinates (X, Y, Z) and attitude angles (Roll, Pitch, Yaw) for the robotic arm's end effector.

[0033] The environmental perception module is a three-dimensional scanning device 2 installed at the front of the wet spraying machine body 1. As the core of the environmental perception module, the three-dimensional scanning device 2 can quickly perform a 360° scan of the tunnel cross section ahead.

[0034] The post-spraying inspection device is a line laser profile scanner (not shown in the figure, but structurally attached to the end of the swing arm 8) installed at the end of the swing arm 8, immediately behind the nozzle. The scanner's scanning line is perpendicular to the spraying direction and is used to measure the surface profile of the wet concrete film immediately after spraying in real time, thereby obtaining real-time spray layer thickness data.

[0035] The workflow of the control module is as follows: Figure 2 As shown, the specific steps are as follows:

[0036] Step S1: Scan the working environment. After the equipment enters the designated construction area, the operator starts the scanning program. The 3D scanning device 2 at the front of the vehicle performs a comprehensive scan of the tunnel face and surrounding area to obtain the original 3D point cloud data.

[0037] Step S2: Point Cloud Processing and Model Comparison. The control module processes the original point cloud, including: a) Denoising: filtering out noise points caused by dust, water mist, etc. in the air; b) Registration: aligning the point cloud data with the vehicle coordinate system; c) Comparison: spatially aligning and comparing the processed actual contour point cloud with the pre-imported tunnel design model (such as CAD drawings), calculating the deviation of each point in the normal direction, and generating a visualized "over-excavation / under-excavation" cloud map. The map clearly uses different colors to represent areas requiring additional spraying (over-excavation) and areas requiring thin spraying or no spraying (under-excavation).

[0038] Step S3: Multidimensional path planning.

[0039] Based on the deviation cloud map generated in the previous step, the control module automatically plans the injection path. This planning is not just about generating a spatial trajectory, but a multi-dimensional task sequence:

[0040] Trajectory planning: Generate a series of dense target points (X,Y,Z) at the end of the robotic arm and corresponding nozzle orientations (A,B,C) to ensure that the nozzle is always approximately perpendicular to the sprayed surface and the distance is kept within the optimal range (e.g., 1-1.5 meters).

[0041] Speed ​​and flow rate coordinated planning: The control module has a built-in empirical or calibrated model H≈k*Q / V, where H is the target thickness, Q is the concrete pump flow rate, V is the boom speed, and k is the process coefficient. For over-excavated areas (larger target thickness H), the system plans a lower boom speed V or a higher flow rate Q; for under-excavated areas (smaller target thickness H), it plans a higher boom speed V or a lower flow rate Q. Finally, it generates timing commands for speed V(t) and flow rate Q(t) corresponding one-to-one with the spatial trajectory points.

[0042] Step S4: Control the operation of the wet spraying machine and adjust it in real time.

[0043] The control module decomposes the planned multi-dimensional instructions into target angles and angular velocities for each joint, and sends them to the servo drivers of each joint via the CAN bus, driving the robotic arm to start automatic spraying operations.

[0044] During the spraying process, a line laser profile scanner located behind the nozzle continuously scans the surface of the newly formed wet spray layer and transmits real-time thickness data H. real (t) Feedback is sent to the control module.

[0045] The control module will H real (t) and the target thickness H at the current location target The difference ΔH(t) is generated by comparing (t) with the difference ΔH(t).

[0046] Instantaneous fine-tuning: If ΔH(t) is within a small acceptable threshold, the system can fine-tune the flow rate Q or velocity V at the next injection point (e.g., 0.1 seconds later) for compensation.

[0047] Next correction: If ΔH(t) is large, or if it cannot be adjusted in real time due to material properties, the system will record this deviation area. When planning the next coverage path, the spray volume will be automatically increased or decreased in this area to achieve interlayer correction.

[0048] Through the complete closed-loop process of pre-scanning planning, multi-variable collaborative control, and real-time post-spray feedback correction described above, this invention achieves unprecedented spraying accuracy and quality. The entire process is automated, requiring only monitoring and necessary emergency stop intervention from the operator's cab, significantly improving construction safety, efficiency, and economic benefits.

[0049] This invention is not limited to the above-described optional embodiments. Anyone can derive other various forms of products under the guidance of this invention. However, regardless of any changes made in their shape or structure, any technical solution that falls within the scope of the claims of this invention shall be protected by this invention.

Claims

1. A spray control method for an intelligent wet spraying machine, characterized in that, The method comprises the following steps: An environment sensing step: using a three-dimensional scanning device to scan the working surface to be sprayed to obtain original point cloud data of the actual profile; A model comparison step: comparing the original point cloud data after processing with a preset design model to generate deviation data representing overbreak or underbreak of the working surface; A path planning step: planning a spraying path including an end-of-arm trajectory of the mechanical arm and a target spraying thickness based on the deviation data; A collaborative control step: collaboratively controlling a spraying flow of the concrete pump and a movement speed of the mechanical arm according to the spraying path to make the actual spraying thickness approximate to the target spraying thickness; A real-time feedback step: during the spraying process, a post-spraying detection device arranged at the end of the mechanical arm is used to monitor the formed thickness of the sprayed area in real time, and the spraying parameters are dynamically adjusted according to the difference between the monitoring result and the target spraying thickness.

2. The method of claim 1, wherein, The collaborative control step specifically comprises: establishing a function model between the spraying thickness and the spraying flow and the movement speed of the mechanical arm, and calculating and outputting the matching spraying flow instruction and the movement speed instruction of the mechanical arm in real time according to the target spraying thickness at different positions.

3. The method of claim 1, wherein, The post-spraying detection device is a line laser profile scanner which is installed behind the spraying nozzle and moves synchronously with the nozzle.

4. The method of claim 1, wherein, Before executing the spraying path, a mechanical arm posture solving step is further included: original data of various sensors arranged on each joint of the mechanical arm are collected, and a high-precision real-time posture of the end of the mechanical arm is calculated by using a multi-sensor data fusion algorithm.

5. The method of claim 4, wherein, The multi-sensor data fusion algorithm is a Kalman filtering algorithm.

6. An intelligent wet sprayer comprising a wet sprayer body, a multi-axis robotic arm, and a spray system, wherein, Further included are: A posture sensing module arranged at each movable joint of the multi-axis mechanical arm for monitoring the real-time movement state of each joint; An environment sensing module including at least one three-dimensional scanning device arranged on the wet spraying machine for scanning the profile of the working surface to be sprayed; A post-spraying detection device arranged at the end of the multi-axis mechanical arm for monitoring the formed thickness of the sprayed area in real time; A control module electrically connected to the posture sensing module, the environment sensing module, the post-spraying detection device and the spraying system; The control module is configured to: collect and process the data collected by the environment sensing module and the posture sensing module; plan the spraying path based on the processed data, and collaboratively control the spraying flow of the spraying system and the movement speed of the mechanical arm; dynamically adjust the spraying parameters according to the real-time feedback of the post-spraying detection device.

7. The intelligent wet sprayer of claim 6, wherein, The posture sensing module includes a rotary encoder arranged at a rotary joint, an inclination sensor arranged at a tilting joint and a wire tension sensor arranged at a telescopic arm.

8. The intelligent wet probe of claim 7, wherein, The control module is further configured to: adopt a multi-sensor data fusion algorithm to fuse the data from the rotary encoder, the inclination sensor and the wire tension sensor to accurately solve the real-time posture of the mechanical arm.

9. The intelligent wet sprayer of claim 6, wherein, The post-spraying detection device is a line laser profile scanner which is installed close to the nozzle of the spraying system.

10. The intelligent wet sprayer of claim 6, wherein, The control module communicates with the posture sensing module through a CAN bus, and the data update frequency is not less than 100 Hz.

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