Reciprocating Ship Spraying Robot System and Method for Metaverse Digital Twin

Abstract

Reciprocating ship spraying robot system and method for metaverse digital twin, which belong to the technical field of ship spraying. The system includes a reciprocating ship spraying AGV robot physical part, an entity mapping interaction layer, a simulation model architecture layer, a key data driving layer, and a reciprocating ship spraying AGV robot virtual twin part. Through the entity mapping interaction layer and the simulation model architecture layer, advanced control algorithms are integrated to realize real-time simulation and monitoring of the spraying process. The key data driving layer conducts parameter verification and optimization to ensure spraying quality. The virtual twin part simulates the spraying process and synchronizes parameters with the physical entity for easy monitoring and analysis. The present invention is mainly used for ship outer plate spraying, improving operation efficiency and coating quality while reducing labor costs and environmental pollution risks.

Description

Technical Field

[0001] The present invention relates to the technical fields of ship outer plate spraying and mechatronics, in particular to a reciprocating ship spraying robot system and method for metaverse digital twin. Background Art

[0002] Ships are in a high-temperature and high-salt environment for a long time, and the outer plates of ships are often corroded to varying degrees. In order to reduce the damage of corrosion to the outer plates of the ship, anti-rust paint needs to be sprayed on the outer plates of the ship. At present, the domestic ship outer plate painting operation has a high degree of manual participation, low spraying efficiency, high rework rate, poor safety in operation, and there is a risk of pollution from the sprayed paint mist. The overall spraying field shows a situation of being large but not strong, and the level of mechanization and intelligence needs to be improved.

[0003] In recent years, automated spraying AGV robots have gradually been applied to the shipbuilding field, but they have poor adaptability to complex ship surfaces and often it is difficult to achieve uniform spraying, resulting in inconsistent coating thickness. In addition, there is still room for improvement in the existing technology in terms of intelligence. Digital twin technology can accurately simulate and predict the behavior of real-world entities through virtual reflection of reality, helping to optimize monitoring. Metaverse technology combines virtual reality and augmented reality technologies, emphasizes virtual interaction, and can well simulate real situations. Although both technologies have shown great potential in many fields, their applications in the ship spraying field are still in their infancy. Summary of the Invention

[0004] In order to solve the above problems, promote the integration of digital twin technology, metaverse technology and the ship spraying industry, and promote the development of new quality productivity in the ship repair and construction field, the present invention provides a metaverse digital twin reciprocating ship spraying AGV robot system and its working method, which not only solves the problems of uneven painting during the current ship painting process, poor adaptability of ship surfaces, serious diffusion pollution of paint mist, and poor safety of manual operations, but also can dynamically display the real-time simulation and monitoring status, and optimize the actual spraying path and parameters according to the simulation results.

[0005] The technical solution of the present invention is: a reciprocating ship spraying AGV robot system empowered by metaverse digital twin, and the system architecture includes: a reciprocating ship spraying AGV robot entity part, an entity mapping interaction layer, a simulation model architecture layer, a key data driving layer, and a reciprocating ship spraying AGV robot virtual twin part.

[0006] The reciprocating ship spraying AGV robot entity part mainly includes: a spraying and recycling mechanism, a robot overhead AGV mechanism, and a spraying material traction mechanism.

[0007] The spraying and recycling mechanism mainly completes functions such as reciprocating spraying, paint mist recycling and treatment, and front-end distance detection and control. The spraying and recycling mechanism consists of an adaptive curved arm, an operation platform, an electric recycling rod, a recycling hood unit, and a binocular camera. The adaptive curved arm is connected to the end of the operation platform and is responsible for compensating for the areas that the robot's telescopic arm cannot reach. Two electric recycling rods are designed at the bottom of the operation platform to achieve fine adjustment of the spraying distance. A binocular camera is installed on the top of the operation platform for three-dimensional space distance detection of the robot. The recycling hood unit is connected to the two electric recycling rods and is used to perform spraying operations and recycle paint mist. The recycling hood unit includes: an upper slider mechanism, a lower slider mechanism, a first driving motor, a second driving motor, a recycling hood, a first infrared distance sensor, a second infrared distance sensor, a paint supply pipeline, and a recycling pipeline. The upper and lower slider mechanisms are installed inside the recycling hood and are driven by the first and second driving motors. The rotational motion of the two motors is converted into a linear motion mode through a crank-slider mechanism. The crankshaft is connected to the output shaft of the motor, and the slider moves along the guide rail. The first infrared distance sensor and the second infrared distance sensor are respectively installed at the left and right ends of the recycling hood for distance detection. The paint supply pipeline and the recycling pipeline are installed on the left side of the recycling hood and are used to supply paint and recycle the paint mist during the spraying operation respectively.

[0008] The robot overhead AGV mechanism includes a telescopic straight arm, an overhead turntable, and the main body part of the overhead AGV body. The telescopic straight arm can achieve lifting below 25m at most, allowing the robot to perform spraying operations within a large vertical range and covering different height parts of the ship. The overhead turntable is installed on the main body part of the robot overhead AGV and is used for the robot to rotate in angle. The main body part of the overhead AGV body includes four driving wheels, a chassis, and a body, which are used to support the ground movement of the robot and help achieve regional operation transfer.

[0009] The spraying material traction mechanism includes a front magnetic attraction traction rod, a rear magnetic attraction traction rod, and a material stacking vehicle. The front magnetic attraction traction rod is used to connect the material supply equipment and the main body part of the reciprocating ship spraying AGV robot and is connected to the rear part of the robot overhead mechanism. The rear magnetic attraction traction rod is used to connect the material stacking vehicle and adsorb to the front magnetic attraction traction rod. The material stacking vehicle is used to stack the feeding system and move together with the reciprocating ship spraying AGV robot.

[0010] The entity mapping interaction layer is used to convert the parameter information of the physical part of the reciprocating ship spraying AGV robot into digital signals for transmission mapping. The content mainly includes: twin parameters, physical dimensions, process status and other information. The twin parameters include motion control parameters such as the speed of the spraying AGV robot, information parameters such as the spraying flow rate of the spraying AGV robot, and adaptation parameters such as the working environment temperature of the robot; the physical dimensions include the overall length and width dimensions of the spraying AGV robot, the arm length of the telescopic arm, the load weight, the joint angle range, the nozzle diameter, the bottom dimensions and other information; the process status covers various status information of the reciprocating ship spraying AGV robot during the execution of the spraying task. These status information are for monitoring, optimization and fault diagnosis, including the working mode status of the spraying AGV robot, the spraying progress status of the robot, the energy consumption status and other information. The information data is collected using various sensors, including: laser ranging sensors for distance detection, angle sensors for angle detection, motion control sensors for speed detection, vision sensors for visual perception, flow sensors for flow detection, data storage devices for storing the original data collected from the sensors, CAN data buses for data transmission between the sensors and the control unit, etc.

[0011] The simulation model architecture layer, as the core part of the system architecture, is used to access and fuse various models and parameters, including: construction of the robot three-dimensional geometric model, import of the system control circuit, construction of the spraying simulation model, simulation of the motor control system, planning of the spraying path system, and import of the system optimization model.

[0012] The construction of the three-dimensional geometric model of the robot includes the following processes: completing the three-dimensional scanning and data acquisition of the overall shape of the ship painting AGV robot, integrating and calibrating the key data of the obtained ship painting AGV robot, converting the processed robot parameters into a triangular mesh model, importing it into SolidWorks, and further editing and processing the appearance color and details of the ship painting AGV robot to complete the construction of the three-dimensional model; the import of the system control circuit includes the following process: completing the design of the system control circuit through circuit design software and importing it into the system architecture; the construction of the spraying simulation model includes the following process: importing the three-dimensional geometric model of the ship painting AGV robot, collecting parameters such as flow rate and viscosity in the spraying flow field during the operation process of the spray gun, defining the boundary conditions of the spraying flow field and selecting the fluid model through ANSYS software to complete the finite element analysis of the spraying flow field of the AGV robot; the simulation of the motor control system includes the following process: establishing a vector control system model of the reciprocating ship painting AGV robot, applying control algorithms, and conducting system simulation experiments through MATLAB / Simulink, and importing the obtained data into the system; the planning of the spraying path system includes the following process: analyzing the obtained three-dimensional model and simulation model parameters, determining the specific spraying area according to the preset coating type, thickness, and uniformity parameters of the spraying, and generating the spraying path through the preset algorithm in the system; the construction of the system model includes the following process through the difference function represents the coupling relationship between the optimization of the overall ship spraying characteristics and the optimization of the spraying characteristics of the hull sectional area:

[0013] (1)

[0014] Among them, represents the optimization model of the spraying characteristics to be operated on the entire outer surface of the ship, represents the optimization model of the spraying characteristics of the local sectional area of the hull, represents the parameter set of the optimization model of the spraying characteristics of the hull sectional area, represents the relationship set of the optimization model of the spraying characteristics of the hull sectional area, represents the influence weight of the th feature in the optimization model of the spraying characteristics of the hull sectional area, represents the difference between the th feature in the optimization model of the spraying characteristics of the hull sectional area and its corresponding feature in the optimization model of the spraying characteristics to be operated on the entire outer surface of the ship, represents the influence weight of the th relationship in the optimization model of the spraying characteristics of the hull sectional area, represents the difference between the th relationship in the optimization model of the spraying characteristics of the hull sectional area and its corresponding relationship in the optimization model of the spraying characteristics to be operated on the entire outer surface of the ship.

[0015] The feature optimization model parameter set represents the preset spraying parameter set of the spraying AGV robot, including spraying thickness, flow rate, and the degree of concavity and convexity of the hull surface; the feature optimization model relationship set represents the spraying layer coverage rate and operation time efficiency of the hull area under different selected spraying paths. The consistency between the sectional area spraying operation and the overall spraying strategy of the reciprocating ship spraying AGV robot is determined through the system model, and performance optimization is completed according to the data analysis results, realizing the identification and correction of deviations in the spraying process to ensure the operation quality.

[0016] The key data-driven layer includes aspects such as parameter verification, data optimization, and performance prediction. The parameter verification is the process of ensuring the accuracy of the parameters used in the reciprocating ship spraying AGV robot system, which includes the verification of key parameters such as spraying speed, paint flow rate, and spraying pressure. By comparing with the data collected during the actual spraying process, it is ensured that the parameter settings can meet the expected spraying effect; the data optimization includes steps such as data cleaning, feature selection, and parameter adjustment of the spraying AGV robot, aiming to find the optimal combination of spraying parameters; the performance prediction includes statistical prediction of spraying thickness quality, problem fault points, maintenance requirements, etc.

[0017] The virtual twin part of the reciprocating ship spraying AGV robot is a virtual robot model integrated in the twin process, which can simulate the spraying process of the robot in a virtual environment and achieve parameter synchronization with the physical entity. As a mirror image of the physical entity of the spraying AGV robot, it can reflect the running state and spraying effect of the robot in real time, facilitating monitoring and analysis.

[0018] The present invention also provides a working process of a reciprocating ship spraying AGV robot empowered by the metaverse digital twin:

[0019] Step S1: The staff sets data such as the specific position parameters of the spraying operation and the required spraying thickness index at the robot control end, and determines the required number of spraying times, the relative distance between the spray gun and the hull surface, etc.

[0020] Step S2: The motor drives the main body of the robot overhead vehicle to a predetermined position to complete the robot positioning.

[0021] Step S3: According to the set operation height area index, the robot adjusts the arm length, and the telescopic straight arm is driven to the preset height.

[0022] Step S4: The binocular camera on the top of the operation platform detects whether the distance between the robot execution end and the hull is ≤ 3m. If the requirement is met, the infrared distance sensor further completes the distance detection of the left and right ends of the recovery cover; if the requirement is not met, the robot's adaptive curved arm performs distance readjustment, and after the process ends, the binocular camera distance detection is performed again.

[0023] Step S5: Determine the detection results of the two infrared ranging sensors. If the distance between the left end of the recovery hood and the hull is ≥ 300 mm, the first electric recovery rod receives an instruction to extend by a specified length until the preset distance requirement is met; if the distance between the left end of the recovery hood and the hull is ≤ 200 mm, the first electric recovery rod receives an instruction to contract by a specified length until the preset distance requirement is met; similarly, if the distance between the right end of the recovery hood and the hull is ≥ 300 mm, the second electric recovery rod receives an instruction to extend by a specified length until the preset distance requirement is met; if the distance between the right end of the recovery hood and the hull is ≤ 200 mm, the second electric recovery rod receives an instruction to contract by a specified length until the preset distance requirement is met;

[0024] Step S6: Open the ground master valve of the paint supply pipeline, and the paint supply pipeline starts to supply materials;

[0025] Step S7: The reciprocating spraying AGV robot starts small-area spraying. To reduce the mutual influence between the upper and lower slider mechanisms and their controllers, the spraying recovery mechanism needs to couple and control the two motors to drive the upper and lower slider mechanisms to reciprocate, and complete small-area spraying.

[0026] Further, the coupled drive control of the recovery mechanism includes the following steps:

[0027] S7.1 Complete the initialization settings for ship surface positioning, and set the initial position and motion parameters of the spraying slider, including motor speed and displacement;

[0028] S7.2 The first drive motor and the second drive motor of the spraying AGV robot respectively complete the control of the expected required speed in the spraying area through the first controller, the second controller, the first drive circuit, and the second drive circuit. The PID control algorithm is used, and the formula is:

[0029]

[0030] In the formula, u(t) represents the output signal of the drive motor controller, e(t) represents the difference between the target position and the actual detected position of the spraying slider, e( ) represents the control error at the historical moment when it is the difference between the target position and the actual detected position of the spraying slider, kp is the proportional constant, T I is the integral time constant, T D is the differential time constant, ξ(t) represents the predicted value of the time constant during the reciprocating operation of the spraying robot motor;

[0031] In S7.3, the built-in displacement detection sensor of the recovery hood unit detects the actual position and movement status of the slider. According to the slider displacement detection result, the control error is calculated through the PID controller, including setting the initial proportional gain of the spraying slider controller and adding integral and differential controls.

[0032] In S7.4, the PID controller outputs a control signal, and adjusts the motor speed through the drive circuit to achieve the positioning of the slider mechanism.

[0033] In S7.5, it is judged the influence of the wear or lubrication external condition disturbance changes between the upper slider mechanism, the lower slider mechanism and the track in the spraying recovery mechanism of the AGV robot on the spraying slider positioning, and adjusts in real time, increases or decreases the corresponding control signal, and adjusts the proportional gain for compensation control.

[0034] In S7.6, the control loops of the first drive motor and the second drive motor are coupled and driven coordinately to ensure the consistency and stability of the slider during the reciprocating spraying process.

[0035] In S7.7, the robot system forms a closed-loop feedback mechanism, monitors the slider position and feeds it back to the controller. The controller makes adaptive adjustments according to the data obtained by the displacement monitoring sensor and feeds back the data in real time.

[0036] In S7.8, when ending the spraying operation of the slider, the control system reduces the motor speed to zero.

[0037] Step S8: Start the paint mist and waste gas recovery pump, connect the recovery pipeline to the recovery hood, adsorb the paint mist particles, and complete the treatment of paint mist and waste gas during the operation process.

[0038] Step S9: After the small-area spraying is completed, the telescopic straight arm of the robot drives downward along the system preset path to reach the next spraying area, and repeats the above flow field until the preset spraying area is completed.

[0039] Step S10: The reciprocating spraying AGV robot judges whether the spraying is uniform by capturing the color distribution on the spraying surface, judges whether the robot lane change transition meets the requirements by the clarity of the spraying edge, and discriminates whether there are phenomena such as sagging and missing spraying through the gray values of different areas, and further determines whether the area of the preset spraying operation area meets the standard. If the gray threshold T true >T min then it meets the requirements, and the process ends; if the gray threshold T true ≤T min then it does not meet the requirements, then reset the target point, and the robot straight arm drives to the target position to re-perform the detection and spraying process until the preset spraying area is completed.

[0040] The beneficial effects of the present invention are as follows: Compared with the traditional manual spraying operation, it has the following advantages:

[0041] 1. A reciprocating ship spraying AGV robot is designed, adopting a reciprocating spraying method with two nozzles driven by double motors to ensure the consistency and uniformity of the spraying process; an adaptive control of the distance between the robot and the ship outer plate is realized by using high-precision sensors in cooperation with a telescopic device; a spraying recovery mechanism is designed, which can effectively collect and filter the waste gas and paint mist generated during the spraying process. This waste gas recovery system can reduce environmental pollution and lower the waste gas emission. At the same time, the robot can avoid the risk of workers contacting harmful chemicals and working at heights during the spraying operation. It can spray at high altitudes or in narrow spaces, reducing the probability of workplace accidents and improving work safety.

[0042] 2. A system architecture of a reciprocating ship spraying AGV robot empowered by the metaverse digital twin is designed. The modeling methods of the metaverse and digital twin are innovatively introduced into the reciprocating ship spraying AGV robot system, advanced control algorithms are integrated, and the real-time simulation and monitoring status of the robot are dynamically displayed. The actual spraying path and parameters are optimized according to the simulation results, thereby improving the operation and maintenance and operation efficiency of the robot and effectively reducing the input of operation and maintenance labor costs.

[0043] In summary, using a reciprocating ship spraying AGV robot empowered by the metaverse digital twin for ship spraying operations can improve operation efficiency, coating quality and safety, while reducing waste gas emissions and labor intensity. This advanced spraying AGV robot technology will bring more efficient, environmentally friendly and safe spraying solutions to the ship repair and construction industry and has broad application prospects. Brief Description of the Drawings

[0044] The present invention will be further described below in conjunction with the drawings and examples.

[0045] Figure 1 It is a system architecture diagram of a reciprocating ship spraying AGV robot empowered by the metaverse digital twin of the present invention.

[0046] Figure 2 It is an overall structure diagram of a reciprocating ship spraying AGV robot empowered by the metaverse digital twin of the present invention.

[0047] Figure 3 It is a spraying recovery mechanism diagram of a reciprocating ship spraying AGV robot empowered by the metaverse digital twin of the present invention.

[0048] Figure 4 It is an AGV mechanism diagram of a reciprocating ship spraying AGV robot empowered by the metaverse digital twin of the present invention.

[0049] Figure 5 It is a spraying material traction mechanism diagram of a reciprocating ship spraying AGV robot empowered by the metaverse digital twin of the present invention.

[0050] Figure 6 is the working flowchart of a reciprocating ship spraying AGV robot empowered by the digital twin of the metaverse in the present invention.

[0051] Figure 7 is the data processing flowchart of a reciprocating ship spraying AGV robot empowered by the digital twin of the metaverse in the present invention.

[0052] Figure 8 is the coupled drive control circuit diagram of the spraying and recovery mechanism of a reciprocating ship spraying AGV robot empowered by the digital twin of the metaverse in the present invention.

[0053] Figure 9 is the spraying trajectory diagram of a reciprocating ship spraying AGV robot empowered by the digital twin of the metaverse in the present invention.

[0054] Figure 10 is the schematic diagram of the telescopic rod state control of a reciprocating ship spraying AGV robot empowered by the digital twin of the metaverse in the present invention.

[0055] Figure 11 is the rotational speed simulation diagram of the motor drive control model of a reciprocating ship spraying AGV robot empowered by the digital twin of the metaverse in the present invention.

[0056] Figure 12 is the digital twin monitoring screen of the material consumption and motor operation of a reciprocating ship spraying AGV robot empowered by the digital twin of the metaverse in the present invention.

[0057] Figure 13 is the digital twin control screen of the dock operation state of a reciprocating ship spraying AGV robot empowered by the digital twin of the metaverse in the present invention.

[0058] In the figure: 1. Spraying and recovery mechanism, 2. Robot overhead AGV mechanism, 3. Spraying material traction mechanism, 1a. Paint supply pipeline, 1b. Recovery pipeline, 1c. Adaptive curved arm, 1d. Binocular camera, 1e. Operating platform, 1f. Second electric recovery rod, 1g. First electric recovery rod, 1h. Upper slider mechanism, 1i. First driving motor, 1j. Lower slider mechanism, 1k. Second driving motor, 1l. Recovery hood, 1m. First infrared ranging sensor, 1n. Second infrared ranging sensor, 2a. Telescopic straight arm, 2b. Overhead turntable, 2c. Overhead AGV body main body, 3a. Front magnetic attraction traction rod, 3b. End magnetic attraction traction rod, 3c. Material stacking vehicle. Detailed implementation manners

[0059] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0060] Figures 1 to 5 A reciprocating ship spraying AGV robot system for the metaverse digital twin is shown. The system architecture includes: a reciprocating ship spraying AGV robot entity part, an entity mapping interaction layer, a simulation model architecture layer, a key data driving layer, and a reciprocating ship spraying AGV robot virtual twin part;

[0061] The reciprocating ship spraying AGV robot entity part includes: a spraying and recycling mechanism 1, a robot overhead AGV mechanism 2, and a spraying material traction mechanism 3;

[0062] The spraying and recycling mechanism 1 completes reciprocating spraying, paint mist recovery processing, and front-end distance detection and control; the spraying and recycling mechanism 1 includes an adaptive curved arm 1c, an operation platform 1e, an electric recycling rod, a recycling hood unit, and a binocular camera 1d;

[0063] The adaptive curved arm 1c is connected to the end of the operation platform 1e to compensate for the area unreachable by the robot telescopic arm;

[0064] Two electric recycling rods are designed at the bottom of the operation platform 1e to realize the adjustment of the spraying distance; a binocular camera 1d is installed on the top of the operation platform 1e for three-dimensional space distance detection of the robot; the recycling hood unit is connected to the two electric recycling rods and is used to perform spraying operations and paint mist recovery; the upper slider mechanism 1h and the lower slider mechanism 1j in the recycling hood unit are respectively driven by a first driving motor 1i and a second driving motor 1k, and the slider mechanism moves along the guide rail; a first infrared ranging sensor 1m and a second infrared ranging sensor 1n are respectively installed at both ends of the recycling hood 1l for distance detection; a paint supply pipeline 1a and a recycling pipeline 1b are installed on the left side of the recycling hood, and the paint supply pipeline 1a is used to supply paint, and the recycling pipeline 1b recovers the paint mist during the spraying operation;

[0065] The robot overhead AGV mechanism 2 includes a telescopic straight arm 2a, an overhead turntable 2b, and an overhead AGV body main body 2c; the telescopic straight arm 2a realizes lifting below 25 m; the overhead turntable 2b is installed on the overhead AGV body main body 2c for the robot to rotate in angle; the overhead AGV body main body 2c is used to support the ground movement of the robot and realize regional operation transfer;

[0066] The spraying material traction mechanism 3 includes a front magnetic attraction traction rod 3a, a rear magnetic attraction traction rod 3b, and a material stacking vehicle 3c; the front magnetic attraction traction rod 3a is connected to the robot overhead AGV mechanism 2; the rear magnetic attraction traction rod 3b is used to connect the material stacking vehicle 3c and adsorbs to the front magnetic attraction traction rod 3a; the material stacking vehicle 3c is used to stack the feeding system and moves together with the robot overhead AGV mechanism 2;

[0067] The entity mapping interaction layer is used to convert the parameter information of the physical part of the reciprocating ship spraying AGV robot into digital signals for transmission mapping. The entity mapping interaction layer includes: twin parameters, physical dimensions, and process status; the twin parameters include the spraying AGV robot speed, the spraying flow rate of the spraying AGV robot, and the robot working environment temperature; the physical dimensions include the length and width dimensions, the bottom dimensions, the arm length of the telescopic arm, the load weight, the joint angle range, and the nozzle diameter of the spraying AGV robot; the process status includes the status information of the reciprocating ship spraying AGV robot during the spraying task execution, which is used for monitoring, optimization, and fault diagnosis. The status information includes the working mode status of the spraying AGV robot, the spraying progress status of the robot, and the energy consumption status; the information data is collected using various sensors, including: a laser ranging sensor for distance detection, an angle sensor for angle detection, a motion control sensor for speed detection, a vision sensor for visual perception, a flow sensor for flow rate detection, a data storage device for storing the original data collected from the sensors, a CAN data bus for data transmission between the sensors and the control unit, etc.

[0068] The simulation model architecture layer is used to access each model and parameter for fusion, including the construction of the robot three-dimensional geometric model, the import of the system control circuit, the construction of the spraying simulation model, the simulation of the motor control system, the planning of the spraying path system, and the construction of the system model;

[0069] The process of constructing the 3D geometric model of the robot is as follows: conduct 3D scanning and data acquisition of the overall shape of the ship painting AGV robot, integrate and calibrate the obtained data of the ship painting AGV robot, convert the processed robot parameters into a triangular mesh model, import it into SolidWorks, and edit and process the appearance color and details of the ship painting AGV robot to complete the construction of the 3D model; the process of importing the system control circuit is to complete the system control circuit design through circuit design software and import it into the system architecture; the process of constructing the spraying simulation model is as follows: import the 3D geometric model of the ship painting AGV robot, collect the flow rate and viscosity parameters in the spray gun spraying flow field during the operation process, define the boundary conditions of the spraying flow field and select the fluid model through ANSYS software to complete the finite element analysis of the spraying flow field of the AGV robot; the motor control system simulation process includes: establishing a vector control system model for the reciprocating ship painting AGV robot, applying control algorithms to conduct system simulation experiments through MATLAB / Simulink, and importing the obtained data into the system; the process of planning the spraying path system is as follows: analyze the parameters of the obtained 3D model and simulation model, determine the specific spraying area according to the preset coating type, thickness, and uniformity parameters of the spraying, and complete the generation of the spraying path through the preset algorithm in the system; the process of constructing the system model is as follows: through the difference function represents the coupling relationship between the optimization of the overall ship spraying characteristics and the optimization of the spraying characteristics of the hull sectional area:

[0070] (1)

[0071] Among them, represents the optimization model of the spraying characteristics to be operated on the entire outer surface of the ship, represents the optimization model of the spraying characteristics of the local sectional area of the hull, represents the parameter set of the optimization model of the spraying characteristics of the hull sectional area, represents the relationship set of the optimization model of the spraying characteristics of the hull sectional area, represents the influence weight of the th feature in the optimization model of the spraying characteristics of the hull sectional area, represents the difference between the th feature in the optimization model of the spraying characteristics of the hull sectional area and its corresponding feature in the optimization model of the spraying characteristics to be operated on the entire outer surface of the ship, represents the influence weight of the th relationship in the optimization model of the spraying characteristics of the hull sectional area, represents the difference between the th relationship in the optimization model of the spraying characteristics of the hull sectional area and its corresponding relationship in the optimization model of the spraying characteristics to be operated on the entire outer surface of the ship;

[0072] The feature optimization model parameter set represents the preset spraying parameter set of the spraying AGV robot, including spraying thickness, flow rate, and the degree of concavity and convexity of the hull surface; the feature optimization model relationship set represents the spraying layer coverage rate and operation time efficiency of the hull area under different spraying path selection conditions; the consistency between the sectional area spraying operation and the overall spraying strategy of the reciprocating ship spraying AGV robot is determined through the system model, and performance optimization is completed according to the data analysis results to identify and correct the deviations in the spraying process;

[0073] The key data-driven layer includes parameter verification, data optimization, and performance prediction; parameter verification is carried out by comparing with the data collected during the actual spraying process to verify the spraying speed, paint flow rate, and spraying pressure parameters; data optimization includes data cleaning, feature selection, and parameter adjustment of the spraying AGV robot, aiming to find the optimal combination of spraying parameters; performance prediction includes statistically predicting the spraying thickness quality, problem fault points, and maintenance requirements;

[0074] The virtual twin part of the reciprocating ship spraying AGV robot is a virtual robot model integrated in the twin process, which simulates the spraying process of the robot in the virtual environment and realizes parameter synchronization with the physical entity; as a mirror image of the physical entity of the spraying AGV robot, it reflects the running state and spraying effect of the robot in real time.

[0075] Refer to Figure 6 , a working method of a reciprocating ship spraying AGV robot empowered by the metaverse digital twin provided by the present invention includes but is not limited to the following steps:

[0076] Step S1: The staff sets data such as the specific position parameters of the spraying operation and the required spraying thickness index at the robot control end, and determines the required number of spraying times, the relative distance between the spray gun and the hull surface, etc.;

[0077] Step S2: The motor drives the robot's overhead AGV mechanism to the predetermined position to complete the robot positioning;

[0078] Step S3: According to the set operation height area index, the robot adjusts the arm length, and the telescopic straight arm 2a is driven to the preset height;

[0079] Step S4: The binocular camera 1d on the top of the operation platform 1e detects whether the distance between the robot execution end and the hull is ≤ 3m. If the requirement is met, the first infrared distance sensor 1m and the second infrared distance sensor 1n further complete the distance detection of the left and right ends of the recovery cover 1l; if the requirement is not met, the robot's adaptive curved arm 1c performs distance readjustment, and after the process ends, the binocular camera 1d distance detection is carried out again;

[0080] Step S5: according to the detection results of the first infrared ranging sensor 1m and the second infrared ranging sensor 1n, if the distance between the left end of the recovery cover 1l and the hull is ≥300mm, the first electric recovery rod 1g receives the instruction to extend the specified length until the preset distance requirement is met; if the distance between the left end of the recovery cover and the hull is ≤200mm, the first electric recovery rod 1g receives the instruction to shrink the specified length until the preset distance requirement is met; similarly, if the distance between the right end of the recovery cover and the hull is ≥300mm, the second electric recovery rod 1f receives the instruction to extend the specified length until the preset distance requirement is met; if the distance between the right end of the recovery cover and the hull is ≤200mm, the second electric recovery rod 1f receives the instruction to shrink the specified length until the preset distance requirement is met;

[0081] Step S6: the main control valve on the ground of the paint supply pipeline is opened, and the paint supply pipeline starts to supply material;

[0082] Step S7: The reciprocating spraying AGV robot starts spraying in a small area, and the spraying recovery mechanism couples and controls the two motors to drive the upper and lower slider mechanisms to reciprocate, completing the spraying in the small area;

[0083] Step S8: Start the paint mist and waste gas recovery pump, connect the recovery pipe 1b to the recovery cover 11, absorb the paint mist particles, and complete the paint mist and waste gas treatment during the operation;

[0084] Step S9: After the spraying of a small area is completed, the robot telescopic straight arm 2a drives downward according to the system preset path to reach the next spraying area, and repeats the above flow field until the preset spraying area is completed;

[0085] Step S10: The system detects whether the area of ​​the predetermined spraying operation area meets the requirements. If it does, the process ends; if it does not, the target point is reset, and the robot straight arm is driven to the target position to re-perform the detection and spraying process until the preset spraying area is completed.

[0086] Reference Figure 7 , the robot data processing flow, through the RS485 communication module to set the communication parameters between the motor equipment of the spraying AGV robot and the digital system, to perform logical sequence and condition judgment, to ensure the smooth progress of the spraying operation and the effective management of data, including but not limited to the following steps:

[0087] Step S1: The system obtains the start and end positions of the upper and lower slider mechanisms according to preset operation parameters, and determines the operation node positions of the spray recovery mechanism;

[0088] Step S2: The system determines the data sending situation of the operation node, checks whether the operation node data of the upper and lower slider spraying mechanisms has been sent. If the data has been sent, it determines the reception and storage of the data. If so, it completes the framing and sending of the write data frame and ends the operation. If not, it reads the framing and sending of the data frame and ends the operation. If the operation node data has not been sent, it determines whether the written operation node data is not empty.

[0089] Step S3: If the data is not empty, the system will receive and store the data and enter the data frame transmission. If the data is empty, it determines whether the time for data reception and storage has reached or exceeded 1 second. If it has exceeded, it determines that the slider mechanism state is abnormal and ends the operation. If it has not exceeded, it directly ends.

[0090] Step S4: Determine whether the data frame transmission is completed. If so, it reads the framing and parsing of the data frame, and based on the result of data processing, determines whether the current read operation node needs to point to the next node and ends the data processing. If not, it writes the framing and parsing of the data frame, determines whether the current write operation node needs to point to the next node, and ends the data processing.

[0091] Step S5: If all data processing is completed, or an abnormality is detected and needs to be stopped, the system will end the current data processing process.

[0092] Refer to Figure 8 , the coupling drive control loop of the robot spraying and recycling mechanism, the content includes but is not limited to the following steps:

[0093] First, complete the initialization settings for ship surface positioning, set the initial positions and motion parameters of the spraying sliders, including motor speed and displacement.

[0094] Furthermore, the first drive motor and the second drive motor of the spraying AGV robot respectively complete the control of the expected required speed in the spraying area through the first controller, the second controller, the first drive circuit, and the second drive circuit. The PID control algorithm is used, mainly for the change amount u(t) of the control quantity Δu(t) for operation, and the e(k) values at three moments are required. The formula is expressed as:

[0095]

[0096] In the formula, u(t) represents the output signal of the drive motor controller, e(t) represents the difference between the target position and the actual detected position of the spraying slider, e( ) represents the difference between the target position and the actual detected position of the spraying slider when the control error at the historical moment is , kp is the proportional constant.T I is the integral time constant, T D is the differential time constant, ξ(t) is expressed as the predicted value of the time constant during the reciprocating operation of the spraying robot motor;

[0097] Adopting this PID control algorithm can save the time for judgment, the error of misoperation generated by the system is small, the influence on the system is small, and it can realize the interference-free switching when two stepping motors work, etc.

[0098] Furthermore, the recovery hood system is internally equipped with a displacement detection sensor to detect the actual position and movement condition of the slider. According to the slider displacement detection result, the control error is calculated through the PID controller, and the control quantity is adjusted to reduce the error value;

[0099] Furthermore, the PID controller outputs a control signal, and the motor speed is adjusted through the drive circuit to realize the positioning of the slider mechanism;

[0100] Furthermore, judge the influence of external disturbance on the positioning of the spraying slider, and perform compensation control by real-time adjustment;

[0101] Furthermore, the two motor control loops are coupled and driven coordinately to ensure the consistency and stability of the slider during the reciprocating spraying process;

[0102] Furthermore, the robot system forms a closed-loop feedback mechanism to monitor the slider position and feed it back to the controller, and the controller makes adaptive adjustments according to the real-time feedback data;

[0103] Furthermore, when ending the spraying operation of the slider, the control system reduces the motor speed to zero.

[0104] Referring to Figure 9 , a spraying trajectory diagram of a reciprocating ship spraying AGV robot empowered by the digital twin of the metaverse provided by the present invention, wherein, the upper slider mechanism drives the first nozzle to move along the points α 1 、α 2 、α 3 、α 4 …… to perform a "zigzag" trajectory operation; the lower slider mechanism drives the second nozzle to move along the points Β 1 、Β 2 、Β 3 、 Β 4 …… to perform a "zigzag" trajectory operation. When the first nozzle is atα When the point starts to operate, the second nozzle also starts from the point Β to start its spraying operation. The two nozzles work together to ensure uniform coverage of the paint in the spraying area, reducing spraying omissions or overlaps. When encountering obstacles or irregular surfaces during spraying, the spraying AGV robot can intelligently adjust its trajectory to adapt to the actual situation.

[0105] Refer to Figure 10 , the schematic diagram of the state control of the robot telescopic rod, the content includes but is not limited to the following steps:

[0106] Figure 10 In (a), when the infrared ranging sensor detects that the distance between the nozzle and the hull exceeds 300 mm, the electric retractable rod extends by the corresponding length H 1 to ensure that the spraying film thickness meets 150 µm; Figure 10 In (b), when the infrared ranging sensor detects that the distance between the nozzle and the hull is less than 200 mm, the electric retractable rod shortens by the corresponding length H 2 to ensure that the film thickness meets the requirement of 150 µm; Figure 10 In (c), when the spraying area is a concave-convex curved surface, one electric retractable rod shortens by the corresponding distance H 3 ' and the other electric retractable rod extends by the corresponding distance H 3 '' to ensure that both ends are always parallel to the outer surface of the ship and the spraying thickness meets the requirement of 150 µm.

[0107] The speed simulation diagram of the robot motor drive control model is as Figure 11 shown. The vertical axis represents the running speed, and the horizontal axis represents the simulation time. The curve in the figure represents the change of the motor speed. At about 0.01 seconds of the simulation time, the motor starts to accelerate and always maintains a relatively high stable speed. This simulation shows that the speed of the motor drive control model meets the design requirements.

[0108] Refer to Figure 12 、 13 , the digital twin monitoring screen for material consumption and motor operation and the digital twin control screen for dock operation status provided by the present invention. This digital twin large screen is used to display the working status of the robot in real time and give an alarm when an abnormal situation occurs.

[0109] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0110] Finally, it should be pointed out that the above embodiments are only used to describe the technical solution of the present invention, rather than a limitation; although the present invention has been specifically described with reference to the above embodiments, those of ordinary skill in the art should understand that the present invention is not limited to the exact structures described above and shown in the drawings, and can be modified and changed in various ways without departing from its scope.

Claims

1. A reciprocating ship spraying AGV robot system based on Metaverse digital twin, characterized by: The system includes: a reciprocating ship painting AGV robot entity part, an entity mapping interaction layer, a simulation model architecture layer, a key data driving layer, and a reciprocating ship painting AGV robot virtual twin part; The physical part of the reciprocating ship spraying AGV robot comprises: a spraying recovery mechanism (1), a robot overhead AGV mechanism (2), and a spraying material traction mechanism (3); The entity mapping interaction layer is used to convert the parameter information of the entity part of the reciprocating ship spraying AGV robot into a digital signal for transmission mapping. The entity mapping interaction layer includes: twin parameters, physical dimensions, and process status; the twin parameters include the speed of the spraying AGV robot, the spraying flow rate of the spraying AGV robot, and the working environment temperature of the robot; the physical dimensions include the length and width of the spraying AGV robot, the bottom size, the arm length of the telescopic arm, the load weight, the joint angle range, and the nozzle diameter; the process status includes the state information of the reciprocating ship spraying AGV robot during the execution of the spraying task, which is used for monitoring, optimization and fault diagnosis. The state information includes the working mode state of the spraying AGV robot, the robot spraying progress state, and the energy consumption state; The simulation model architecture layer is used to access various models and parameters for fusion, including robot 3D geometric model construction, system control circuit introduction, spraying simulation model construction, motor control system simulation, spraying path system planning and system model construction; The process of constructing the robot's three-dimensional geometric model is as follows: perform three-dimensional scanning and data collection of the overall appearance of the ship spraying AGV robot, integrate and calibrate the acquired ship spraying AGV robot data, convert the processed robot parameters into a triangular mesh model, import it into SolidWorks, edit the appearance color and details of the ship spraying AGV robot, and complete the construction of the three-dimensional model; the process of importing the system control circuit is to complete the system control circuit design through the circuit design software and import it into the system architecture; the process of constructing the spraying simulation model is to import the three-dimensional geometric model of the ship spraying AGV machine, collect the flow rate and viscosity in the spray gun spraying flow field during the operation process, and then complete the construction of the three-dimensional model. Parameters, define the spraying flow field boundary conditions and select the fluid model through ANSYS software, and complete the finite element analysis of the AGV robot spraying flow field; the motor control system simulation process includes: establishing a vector control system model of a reciprocating ship spraying AGV robot, applying the control algorithm to perform system simulation experiments through MATLAB / Simulink, and importing the obtained data into the system; the spraying path system planning process is: analyzing the obtained three-dimensional model and simulation model parameters, determining the specific spraying area for the preset spraying coating type, thickness, and uniformity parameters, and generating the spraying path in the system through the preset algorithm; the system model construction process is: through the difference function It represents the coupling relationship between the optimization of the overall spraying characteristics of the ship and the optimization of the spraying characteristics of the hull section area: （1） in, Represents the optimization model of the spraying characteristics of all the outer surfaces of the ship to be operated, Represents the optimization model of spraying characteristics of local sections of the hull. represents the optimization model parameter set of the hull segment area spraying feature, Represents the relationship set of the optimization model of spraying characteristics in the hull segment area, The first The influence weight of each feature, The first The difference between the features and their corresponding features in the optimization model of the spraying features to be operated on the entire outer surface of the ship is The first The influence weight of a relationship, The first The difference between the relationship and its corresponding relationship in the optimization model of the spraying characteristics of the entire outer surface of the ship to be operated; The key data-driven layer includes parameter verification, data optimization, and performance prediction; parameter verification verifies the spraying speed, paint flow rate, and spraying pressure parameters by comparing with the data collected during the actual spraying process; data optimization includes data cleaning, feature selection, and parameter adjustment of the spraying AGV robot, with the aim of finding the optimal spraying parameter combination; performance prediction includes statistical prediction of spraying thickness quality, problem failure points, and maintenance requirements; The virtual twin part of the reciprocating ship spraying AGV robot is a virtual robot model integrating the twin process, which simulates the spraying process of the robot in a virtual environment and realizes parameter synchronization with the physical entity; as a mirror image of the physical entity of the spraying AGV robot, it reflects the operating status and spraying effect of the robot in real time.

2. According to claim 1, a reciprocating ship spraying AGV robot system based on a metaverse digital twin, characterized in that: The spray recovery mechanism (1) completes reciprocating spraying, paint mist recovery processing, and front-end distance detection control; the spray recovery mechanism (1) comprises an adaptive curved arm (1c), an operating platform (1e), an electric recovery rod, a recovery cover unit, and a binocular camera (1d); The adaptive curved arm (1c) is connected to the end of the working platform (1e) to compensate for the area that cannot be reached by the robot telescopic arm; The bottom of the working platform (1e) is designed with two electric recovery rods to adjust the spraying distance; the top of the working platform (1e) is equipped with a binocular camera (1d) for detecting the distance in three-dimensional space of the robot; the recovery cover unit is connected to the two electric recovery rods and is used to perform spraying operations and recover paint mist; the upper end slider mechanism (1h) and the lower end slider mechanism (1j) in the recovery cover unit are driven by a first drive motor (1i) and a second drive motor (1k) respectively, and the slider mechanism moves along the guide rail; the first infrared distance measuring sensor (1m) and the second infrared distance measuring sensor (1n) are respectively installed at both ends of the recovery cover (1l) for detecting the distance; the paint supply pipeline (1a) and the recovery pipeline (1b) are installed on the left side of the recovery cover (1l), the paint supply pipeline (1a) is used to supply paint, and the recovery pipeline (1b) recovers the paint mist during the spraying operation; The robot overhead AGV mechanism (2) comprises a telescopic straight arm (2a), an overhead turntable (2b), and an overhead AGV body (2c); the telescopic straight arm (2a) can achieve a lift of less than 25 m; the overhead turntable (2b) is installed on the overhead AGV body (2c) and is used for the robot to rotate its angle; the overhead AGV body (2c) is used to support the robot to move on the ground and achieve regional operation transfer; The spray material traction mechanism (3) comprises a front magnetic traction rod (3a), a terminal magnetic traction rod (3b) and a material stacking vehicle (3c); the front magnetic traction rod (3a) is connected to the robot overhead AGV mechanism (2); the terminal magnetic traction rod (3b) is used to connect the material stacking vehicle (3c) and the front magnetic traction rod (3a); the material stacking vehicle (3c) is used for stacking a material feeding system and moves together with the robot overhead AGV mechanism (2).

3. According to claim 2, a reciprocating ship spraying AGV robot system based on a metaverse digital twin is characterized in that: The parameter set of the hull segment area spraying feature optimization model represents a set of preset spraying parameters of the spraying AGV robot, including spraying thickness, flow rate, and hull surface unevenness; the relationship set of the hull segment area spraying feature optimization model represents the spray layer coverage and operation time efficiency of the hull area when different spraying paths are selected; the consistency between the segment area spraying operation of the reciprocating ship spraying AGV robot and the overall spraying strategy is determined through the system model, and performance optimization is completed according to the data analysis results to identify and correct deviations in the spraying process.

4. The working method of a metaverse digital twin reciprocating ship spraying AGV robot system as described in claim 3 is characterized in that: The following steps are involved: Step S1: The staff sets the specific position parameters of the spraying operation and the spraying thickness requirement index data on the robot control terminal, and determines the required number of spraying times and the relative distance between the spray gun and the hull surface; Step S2: The motor drives the robot to a predetermined position to complete the robot positioning; Step S3: According to the set working height area index, the robot adjusts the arm length and drives the telescopic straight arm (2a) to a preset height; Step S4: The binocular camera (1d) on the top of the working platform (1e) detects whether the distance between the robot execution end and the hull is ≤3m. If the requirement is met, the infrared distance sensor further completes the distance detection between the left and right ends of the recovery cover; if the requirement is not met, the robot's adaptive curved arm (1c) readjusts the distance, and the binocular camera (1d) is used again to detect the distance after the process is completed; Step S5: judging according to the detection results of the first infrared ranging sensor (1m) and the second infrared ranging sensor (1n), if the distance between the left end of the recovery cover and the hull is ≥300mm, the first electric recovery rod (1g) receives an instruction to extend a specified length until the preset distance requirement is met; if the distance between the left end of the recovery cover and the hull is ≤200mm, the first electric recovery rod (1g) receives an instruction to retract a specified length until the preset distance requirement is met; similarly, if the distance between the right end of the recovery cover and the hull is ≥300mm, the second electric recovery rod (1f) receives an instruction to extend a specified length until the preset distance requirement is met; if the distance between the right end of the recovery cover and the hull is ≤200mm, the second electric recovery rod (1f) receives an instruction to retract a specified length until the preset distance requirement is met; Step S6: the main control valve on the ground of the paint supply pipeline is opened, and the paint supply pipeline starts to supply material; Step S7: the reciprocating spraying AGV robot starts spraying in a small area, the spraying recovery mechanism is coupled to drive control, and the first drive motor (1i) and the second drive motor (1k) respectively drive the upper slider mechanism (1h) and the lower slider mechanism (1j) to reciprocate, thereby completing the spraying in the small area; Step S8: starting the paint mist and waste gas recovery pump, connecting the recovery pipeline (1b) to the recovery cover (1l), absorbing the paint mist particles, and completing the paint mist and waste gas treatment process; Step S9: After spraying of a small area is completed, the robot telescopic straight arm (2a) is driven downward according to a system preset path to reach the next spraying area, and the above flow field is repeated until the preset spraying area is completed; Step S10: Check whether the area of ​​the scheduled spraying operation area meets the requirements. If the requirements are met, the process ends; If it is not satisfied, the target point is reset, and the robot's straight arm is driven to the target position to re-perform the inspection and spraying process until the preset spraying area is completed.

5. The working method of a reciprocating ship spraying AGV robot system of a metaverse digital twin according to claim 4 is characterized in that: The recycling mechanism coupling drive control in step S7 includes the following steps: S7.1 completes the initialization setting of the ship surface positioning, sets the initial position and motion parameters of the spraying slider, including the motor speed and displacement; The first drive motor (1i) and the second drive motor (1k) of the S7.2 spraying AGV robot are controlled by the first controller, the second controller and the first drive circuit, and the second drive circuit respectively to complete the control of the expected speed required in the spraying area, using the PID control algorithm, and the formula is: ； In the formula, u(t) Represents the output signal of the drive motor controller, e(t) Indicates the difference between the target position of the spraying slider and the actual detection position. e( ) The historical moment is The control error is the difference between the target position of the spraying slider and the actual detection position. kp is the proportionality constant, T I is the integration time constant, T D is the differential time constant, ξ(t) It is expressed as the predicted value of the time constant in the reciprocating operation of the spray robot motor; The built-in displacement detection sensor of the S7.3 recovery cover unit detects the actual position and movement of the slider. According to the slider displacement detection result, the control error is calculated through the PID controller, including setting the initial proportional enhancement of the spray slider controller and adding integral and differential control; The S7.4PID controller outputs a control signal, which adjusts the motor speed through the drive circuit to achieve the positioning of the slider mechanism; S7.5 determines the influence of wear or lubrication external disturbance changes between the upper slider mechanism (1h) and the lower slider mechanism (1j) and the track in the AGV robot spray recovery mechanism on the positioning of the spray slider, and makes real-time adjustments to increase or decrease the corresponding control signal and adjust the proportional enhancement to perform compensation control; S7.6 The first drive motor (1i) and the second drive motor (1k) control circuits are coupled and driven to coordinate, ensuring the consistency and stability of the slider during the reciprocating spraying process; The S7.7 robot system forms a closed-loop feedback mechanism to monitor the slider position and feed it back to the controller, which makes adaptive adjustments based on the data obtained by the displacement monitoring sensor and the real-time feedback data; S7.8 ends the slider spraying operation, and the control system reduces the motor speed to zero.

6. The working method of a metaverse digital twin reciprocating ship spraying AGV robot system according to claim 5 is characterized in that: In step S10, it is detected whether the area of ​​the predetermined spraying operation area meets the standard: the reciprocating spraying AGV robot determines whether the spraying is uniform by capturing the color distribution of the spraying surface, and determines whether the robot lane change transition meets the requirements by the clarity of the spraying edge. If the grayscale value of different areas is used to judge, if the grayscale threshold T true >T min If the grayscale threshold T true ≤T min If it is not satisfied, the target point is reset, and the robot straight arm is driven to the target position to re-perform the inspection and spraying process until the preset spraying area is completed.

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