Universe digital twinning reciprocating ship spraying robot system and method

Abstract

The invention discloses a universe digital twinning reciprocating ship spraying robot system and method, and belongs to the technical field of ship spraying. The system comprises 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. Through the entity mapping interaction layer and the simulation model architecture layer, an advanced control algorithm is integrated, and real-time simulation and monitoring of the spraying process are achieved. And the key data driving layer is subjected to parameter verification and optimization, so that the spraying quality is ensured. And the virtual twin body part simulates the spraying process and synchronizes parameters with the physical entity, so that monitoring and analysis are facilitated. The ship shell plate spraying device is mainly used for ship shell plate spraying, the working efficiency and the coating quality are improved, and meanwhile the labor cost and the environmental pollution risk are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of ship outer plate spraying and mechatronics, and in particular to a metaverse digital twin reciprocating ship spraying robot system and method. 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 hull, the outer plates of ships need to be sprayed with anti-rust paint. At present, the domestic outer plate painting operation of ships has a high degree of manual participation, low spraying efficiency, high rework rate, poor safety operation, and there is a risk of pollution from spraying paint mist. The overall spraying field is 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 used in the field of shipbuilding. However, they have poor adaptability to the complex curved surfaces of ships, and it is often difficult to achieve uniform spraying, resulting in inconsistent coating thickness. In addition, the existing technology still has room for improvement in terms of intelligence. Digital twin technology reflects reality through virtuality, can accurately simulate and predict the behavior of real-world entities, and help optimize monitoring. Metaverse technology combines virtual reality and augmented reality technologies, emphasizes virtual interaction, and can well simulate real situations. Although the two technologies have great potential in many fields, their application in the field of ship spraying is still in its 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 field of ship repair and construction, the present invention provides a metaverse digital twin reciprocating ship spraying AGV robot system and its working method, which not only solves the current problems of uneven painting in the ship painting process, poor adaptability to ship curved surfaces, serious paint mist diffusion pollution, and poor safety of manual operations, but also can dynamically display real-time simulation and monitoring conditions, 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 a metaverse digital twin, the system architecture including: 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 physical part of the reciprocating ship spraying AGV robot mainly includes: a spraying recovery mechanism, a robot overhead AGV mechanism, and a spraying material traction mechanism.

[0007] The spray recovery mechanism mainly completes functions such as reciprocating spraying, paint mist recovery processing, and front-end distance detection and control; the spray recovery mechanism consists of an adaptive curved arm, an operating platform, an electric recovery rod, a recovery cover unit, and a binocular camera; the adaptive curved arm is connected to the end of the operating platform and is responsible for compensating for the inaccessible area of ​​the robot's telescopic arm; two electric recovery rods are designed at the bottom of the operating platform to achieve fine-tuning of the spraying distance, and a binocular camera is installed on the top of the operating platform for three-dimensional spatial distance detection of the robot; the recovery cover unit is connected to the two electric recovery rods and is used to perform spraying operations and paint mist recovery. The recovery cover unit includes: an upper slider mechanism, a lower slider mechanism, a first drive motor, a second drive motor, a recovery cover, a first infrared ranging sensor, a second infrared ranging sensor, a paint supply pipeline and a recovery pipeline. The upper and lower slider mechanisms are installed inside the recovery cover and are driven by the first and second drive motors. The rotational motion of the two motors is converted into linear motion through a crank slider. The crankshaft is connected to the output shaft of the motor, and the slider moves along the guide rail; the first infrared ranging sensor and the second infrared ranging sensor are respectively installed at the left and right ends of the recovery cover for detecting the distance; the paint supply pipeline and the recovery pipeline are installed on the left side of the recovery cover, and are respectively used to supply paint and recover paint mist during the spraying operation.

[0008] The robot elevated AGV mechanism includes a telescopic straight arm, an elevated turntable, and an elevated AGV body body; the telescopic straight arm can achieve a maximum lifting height of less than 25m, allowing the robot to perform spraying operations within a larger vertical range and cover different height parts of the ship; the elevated turntable is installed on the robot elevated AGV body part and is used for robot angle rotation; the elevated AGV body body includes four driving wheels, a chassis and a body, which are used to support the robot's ground movement and help achieve regional operation transfer.

[0009] The spray material traction mechanism includes a front magnetic traction rod, a terminal magnetic traction rod and a material stacking vehicle. The front magnetic traction rod is used to connect the material supply equipment with the main body of the reciprocating ship spraying AGV robot, and is connected to the rear of the robot's elevated mechanism; the terminal magnetic traction rod is used to connect the material stacking vehicle, and is mutually adsorbed with the front magnetic 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 entity part of the reciprocating ship spraying AGV robot into a digital signal for transmission mapping, and 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 adaptability parameters such as the robot's working environment temperature; the physical dimensions include the overall length and width of the spraying AGV robot, the arm length of the telescopic arm, the load weight, the joint angle range, the nozzle diameter, the bottom size and other information; the process state covers the various state information of the reciprocating ship spraying AGV robot in the process of performing the spraying task. These state information are for monitoring, optimization and fault diagnosis, including the spraying AGV robot working mode status, robot spraying progress status, energy consumption status and other information. The information data collection uses various types of sensors, including: laser ranging sensors for distance detection, angle sensors for angle detection, motion control sensors for speed detection, visual sensors for visual perception, flow sensors for flow detection, data storage devices for storing raw data collected from sensors, CAN data buses for data transmission between sensors and control units, etc.

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

[0012] The process of constructing the three-dimensional geometric model of the robot includes: completing the three-dimensional scanning and data collection of the overall appearance of the ship spraying AGV robot, integrating and calibrating the key data of the ship spraying AGV robot, converting the processed robot parameters into a triangular mesh model, importing it into SolidWorks, further editing and processing the appearance color and details of the ship spraying AGV robot, and completing the construction of the three-dimensional model; the process of importing the system control circuit includes: completing the system control circuit design through the circuit design software and importing it into the system architecture; the process of constructing the spraying simulation model includes: importing the three-dimensional geometric model of the ship spraying AGV machine, collecting the flow rate, The parameters such as viscosity are defined by ANSYS software, the boundary conditions of the spraying flow field are defined, the fluid model is selected, and the finite element analysis of the spraying flow field of the AGV robot is completed; the simulation of the motor control system includes: establishing a vector control system model of a reciprocating ship spraying AGV robot, applying a control algorithm, and performing a system simulation experiment through MATLAB / Simulink, and the obtained data is imported into the system; the spraying path system planning includes: analyzing the obtained three-dimensional model and simulation model parameters, determining the specific spraying area according to the preset spraying coating type, thickness, and uniformity parameters, and generating the spraying path in the system through a preset algorithm; the system model construction process includes using a 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.

[0013] The characteristic optimization model parameter set represents the preset spraying parameter set of the spraying AGV robot, including spraying thickness, flow rate, and hull surface concave-convex degree; the characteristic optimization model relationship set represents the spray coating coverage rate and operation time efficiency of the hull area when different spraying paths are selected. The consistency between the segmented 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 deviations in the spraying process to ensure the quality of the operation.

[0014] The key data driving layer includes: parameter verification, data optimization, performance prediction and other aspects. The parameter verification is the process of ensuring that the parameters used in the reciprocating ship spraying AGV robot system are accurate, which includes the verification of key parameters such as spraying speed, paint flow, spraying pressure, etc., and 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 spraying AGV robot data cleaning, feature selection, parameter adjustment, etc., in order to find the optimal spraying parameter combination; the performance prediction includes statistical prediction of spraying thickness quality, problem failure points, maintenance requirements and other contents.

[0015] The virtual twin of the reciprocating ship spraying AGV robot is a virtual robot model integrated with the twin process, which can simulate the robot's spraying process 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 robot's operating status and spraying effect in real time, which is convenient for monitoring and analysis.

[0016] The present invention also provides a reciprocating ship spraying AGV robot workflow enabled by the Metaverse digital twin: Step S1: The staff sets the specific position parameters of the spraying operation, the spraying thickness requirement index and other data on the robot control terminal, and determines the required number of spraying times, the relative distance between the spray gun and the hull surface and other contents; Step S2: The motor drives the robot elevated vehicle body 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 to a preset height; Step S4: The binocular camera on the top of the work platform detects whether the distance between the robot execution end and the hull is ≤3m. If the requirement is met, the infrared ranging sensor further completes the distance detection of the left and right ends of the recovery cover; if the requirement is not met, the robot adaptively adjusts the distance by the arm, and the binocular camera distance detection is performed again after the process is completed; Step S5: the detection results of the two infrared ranging sensors are judged. If the distance between the left end of the recovery cover and the hull is ≥300mm, the first electric recovery rod 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 receives the instruction to retract 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 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 receives the instruction to retract the 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. In order to reduce the mutual influence between the upper and lower slider mechanisms and their controllers, the spray recovery mechanism needs to couple and control the two motors to drive the upper and lower slider mechanisms to reciprocate to complete the small area spraying.

[0017] Further, the recycling mechanism is coupled to the driving control, comprising 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; S7.2 The first drive motor and the second drive motor of the spraying AGV robot respectively control the expected speed required in the spraying area through the first controller, the second controller and the first drive circuit, and the second drive circuit, using the PID control algorithm, and the formula is:

[0018] 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 condition disturbance changes between the upper slider mechanism, the lower slider mechanism 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 and the second drive motor control circuit are coupled and driven to coordinate to ensure 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.

[0019] Step S8: starting the paint mist and waste gas recovery pump, connecting the recovery pipeline to the recovery cover, absorbing the paint mist particles, and completing the paint mist and waste gas treatment during the operation; Step S9: After spraying of a small area is completed, the robot telescopic straight arm 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; Step S10: The reciprocating spraying AGV robot determines whether the spraying is uniform by capturing the color distribution of the spraying surface, determines whether the robot's lane change transition meets the requirements by the clarity of the spraying edge, and determines whether there is sagging, spray leakage, etc. by the grayscale values ​​of different areas, and then determines whether the area of ​​the predetermined spraying operation area meets the standard. 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.

[0020] The beneficial effects of the present invention are as follows: compared with the traditional manual spraying operation, it has the following advantages: 1. A reciprocating ship spraying AGV robot was designed, which adopts a two-nozzle reciprocating spraying method driven by dual motors to ensure the consistency and uniformity of the spraying process; a high-precision sensor combined with a telescopic device was used to achieve adaptive control of the distance between the robot and the ship's outer plate; a spray recovery mechanism was designed to effectively collect and filter the exhaust gas and paint mist generated during the spraying process. This exhaust gas recovery system can reduce pollution to the environment and reduce exhaust gas emissions. At the same time, the robot can avoid workers from exposure to harmful chemicals and the risk of working at heights during spraying operations. It can spray at high altitudes or in confined spaces, reducing the probability of workplace accidents and improving work safety.

[0021] 2. A reciprocating ship spraying AGV robot system architecture empowered by Metaverse Digital Twin was designed. The modeling methods of Metaverse and Digital Twin were innovatively introduced into the reciprocating ship spraying AGV robot system, and advanced control algorithms were integrated to dynamically display the robot's real-time simulation and monitoring status. The actual spraying path and parameters were optimized according to the simulation results, thereby improving the robot's operation and maintenance and operating efficiency, which can effectively reduce the operation and maintenance labor cost investment.

[0022] In summary, the use of a reciprocating ship spraying AGV robot enabled by the Metaverse digital twin for ship spraying operations can improve operating efficiency, coating quality and safety, while reducing exhaust emissions and labor intensity. This advanced spraying AGV robot technology will bring more efficient, environmentally friendly and safe spraying solutions to the shipbuilding industry, and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention will be further described below in conjunction with the accompanying drawings and examples.

[0024] Figure 1 This is an architecture diagram of a reciprocating ship spraying AGV robot system enabled by a metaverse digital twin of the present invention.

[0025] Figure 2 This is the overall structure diagram of a reciprocating ship spraying AGV robot enabled by the Metaverse digital twin of the present invention.

[0026] Figure 3 This is a diagram of the spray recovery mechanism of a reciprocating ship spraying AGV robot enabled by the metaverse digital twin of the present invention.

[0027] Figure 4 This is a diagram of the AGV mechanism of a reciprocating ship spraying AGV robot enabled by the Metaverse digital twin of the present invention.

[0028] Figure 5 This is a diagram of the material traction mechanism of a reciprocating ship spraying AGV robot enabled by the Metaverse digital twin of the present invention.

[0029] Figure 6 This is a workflow diagram of a reciprocating ship spraying AGV robot enabled by the metaverse digital twin of the present invention.

[0030] Figure 7 This is a data processing flow chart of a reciprocating ship spraying AGV robot enabled by a metaverse digital twin of the present invention.

[0031] Figure 8 This is a coupling drive control loop diagram of a reciprocating ship spraying AGV robot spraying recovery mechanism enabled by a metaverse digital twin of the present invention.

[0032] Fig. 9 It is a spraying trajectory diagram of a reciprocating ship spraying AGV robot enabled by the metaverse digital twin of the present invention.

[0033] Fig.10 This is a schematic diagram of the telescopic rod state control of a reciprocating ship spraying AGV robot enabled by the metaverse digital twin of the present invention.

[0034] Fig.11 This is a speed simulation diagram of a motor drive control model of a reciprocating ship spraying AGV robot enabled by the Metaverse digital twin of the present invention.

[0035] Fig.12 It is a digital twin monitoring screen for material consumption and motor operation of a reciprocating ship spraying AGV robot enabled by a metaverse digital twin of the present invention.

[0036] Fig.13 It is a digital twin control screen of the dock operation status of a reciprocating ship spraying AGV robot enabled by a metaverse digital twin of the present invention.

[0037] In the figure: 1. Spray recovery mechanism, 2. Robot elevated AGV mechanism, 3. Spray material traction mechanism, 1a. Paint supply pipeline, 1b. Recovery pipeline, 1c. Adaptive curved arm, 1d. Binocular camera, 1e. Working platform, 1f. Second electric recovery rod, 1g. First electric recovery rod, 1h. Upper end slider mechanism, 1i. First drive motor, 1j. Lower end slider mechanism, 1k. Second drive motor, 1l. Recovery cover, 1m. First infrared ranging sensor, 1n. Second infrared ranging sensor, 2a. Telescopic straight arm, 2b. Elevated turntable, 2c. Elevated AGV body, 3a. Front end magnetic traction rod, 3b. End magnetic traction rod, 3c. Material stacking vehicle. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with 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.

[0039] Figures 1 to 5 A reciprocating ship painting AGV robot system of a metaverse digital twin is shown, and the system architecture 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 includes: a spraying recovery mechanism 1, a robot overhead AGV mechanism 2, and a spraying material traction mechanism 3; The spray recovery mechanism 1 completes reciprocating spraying, paint mist recovery processing, and front end distance detection control; the spray recovery mechanism 1 includes an adaptive crank arm 1c, a work 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 inaccessible area of ​​the robot telescopic arm; Two electric recovery rods are designed at the bottom of the working platform 1e to adjust the spraying distance; a binocular camera 1d is installed on the top of the working platform 1e for the robot to detect the three-dimensional space distance; the recovery cover unit is connected to the two electric recovery rods for performing spraying operations and paint mist recovery; the upper slider mechanism 1h and the lower slider mechanism 1j in the recovery cover unit are driven by the first drive motor 1i and the second drive motor 1k respectively, and the slider mechanism moves along the guide rail; the first infrared ranging sensor 1m and the second infrared ranging 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, 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 includes 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 25m; 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's ground movement to achieve regional operation transfer; The spray material traction mechanism 3 includes 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 is mutually adsorbed with the front magnetic traction rod 3a; the material stacking vehicle 3c is used for stacking the feeding system and moves together with the robot overhead AGV mechanism 2; The entity mapping interaction layer is used to convert the parameter information of the entity 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 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 information data collection uses various sensors, including: laser ranging sensors for distance detection, angle sensors for angle detection, motion control sensors for speed detection, visual sensors for visual perception, flow sensors for flow detection, data storage devices for storing raw data collected from sensors, and CAN data buses for data transmission between sensors and control units.

[0040] The simulation model architecture layer is used to connect various models and parameters for integration, including the construction of robot 3D geometric model, system control circuit import, spraying simulation model construction, motor control system simulation, spraying path system planning and system model construction; The process of building the robot's three-dimensional geometric model is as follows: perform three-dimensional scanning and data collection on the overall shape 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 building 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 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 according to 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 feature optimization model parameter set represents the preset spraying parameter set of the spraying AGV robot, including spraying thickness, flow rate, and hull surface concave-convex degree; the feature optimization model relationship set represents the spray coating coverage rate and operation time efficiency of the hull area when different spraying paths are selected; the consistency between the segmented area spraying operation and the overall spraying strategy of the reciprocating ship spraying AGV robot is determined through the system model, and the performance optimization is completed according to the data analysis results to identify and correct the deviation in the spraying process; 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 goal 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 that integrates the twin process. It simulates the robot's spraying process 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 robot's operating status and spraying effect in real time.

[0041] Reference Figure 6 The present invention provides a working method of a reciprocating ship spraying AGV robot enabled by a metaverse digital twin, including but not limited to the following steps: Step S1: The staff sets the specific position parameters of the spraying operation, the spraying thickness requirement index and other data on the robot control terminal, and determines the required number of spraying times, the relative distance between the spray gun and the hull surface and other contents; Step S2: The motor drives the robot overhead AGV mechanism 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 first infrared ranging sensor 1m and the second infrared ranging 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 adaptive curved arm 1c readjusts the distance, and the binocular camera 1d distance detection is performed again after the process is completed; 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; 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, 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; 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; 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; 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.

[0042] 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: 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; Step S2: The system determines the sending status of the operation node data, checks whether the operation node data of the upper and lower slider spraying mechanism has been sent, and if the data has been sent, determines the reception and storage of the data, and if so, completes the writing of the data frame framing and sends it to end the operation, and if not, reads the data frame framing and sends it to end the operation; if the operation node data has not been sent, determines whether the writing of the operation node data is not empty; 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 is determined whether the data receiving and storing time reaches or exceeds 1 second. If it exceeds, it is determined that the slider mechanism state is abnormal and the operation is terminated. If it does not exceed, it is terminated directly; Step S4: Determine whether the data frame transmission is completed. If so, read the data frame framing and parse it. According to the result of data processing, determine whether the current read operation node needs to point to the next node, and end the data processing. If not, write the data frame framing and parse it, determine whether the current write operation node needs to point to the next node, and end the data processing. 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 flow.

[0043] Reference Figure 8 , the robot spray recovery mechanism is coupled to the drive control loop, including but not limited to the following steps: First, complete the initialization setting of the ship surface positioning and set the initial position and motion parameters of the spraying slider, including motor speed and displacement; Furthermore, the first drive motor and the second drive motor of the spraying AGV robot respectively control the speed required for the expected spraying area through the first controller, the second controller and the first drive circuit, and the second drive circuit, and adopts the PID control algorithm, which is mainly to control the control quantity u(t) The amount of change Δu(t) To operate, three moments are required e(k) Value, the formula is:

[0044] 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 use of this PID control algorithm can save judgment time, the error of malfunction generated by the system is small, the impact on the system is small, and it can achieve interference-free switching when two stepper motors are working.

[0045] Furthermore, the recovery cover system has a built-in displacement detection sensor to detect the actual position and movement of the slider. According to the slider displacement detection result, the control error is calculated through the PID controller, and the control amount is adjusted to reduce the error value; Furthermore, the PID controller outputs a control signal to adjust the motor speed through the drive circuit to achieve the positioning of the slider mechanism; Furthermore, the influence of external disturbance on the positioning of the spraying slide is judged, and compensation control is performed through real-time adjustment; Furthermore, the two motor control loops are coupled and driven to coordinate, ensuring the consistency and stability of the slider during the reciprocating spraying process; Furthermore, the robot system forms a closed-loop feedback mechanism to monitor the slider position and provide feedback to the controller, which makes adaptive adjustments based on the real-time feedback data; Further, the spraying operation of the slider is ended and the control system reduces the motor speed to zero.

[0046] Reference Fig. 9 The present invention provides a reciprocating ship spraying AGV robot spraying trajectory diagram enabled by the Metaverse digital twin, in which the upper end slider mechanism drives the first nozzle to move along the point position during the spraying process. α 1 、α 2 、α 3 、α 4 ...runs in a zigzag trajectory; the slider mechanism at the lower end drives the second nozzle to move along the point position during the spraying process. Β 1 , Β 2 , Β 3 、 Β 4... to run in a zigzag trajectory. α When the point position starts to run, the second nozzle also starts from the point position Β When the spraying operation begins, the two nozzles work together to ensure uniform coating coverage in the spraying area and reduce spraying omissions or overlaps. When encountering obstacles or irregular surfaces during the spraying process, the spraying AGV robot can intelligently adjust its trajectory to adapt to the actual situation.

[0047] Reference Fig.10 , the robot telescopic rod state control diagram, including but not limited to the following steps: Fig.10 (a) When the infrared distance sensor detects that the distance between the nozzle and the hull exceeds 300mm, the electric recovery rod extends the corresponding length H 1 , ensure that the spraying film thickness meets 150µm; Fig.10 (b) When the infrared distance sensor detects that the distance between the nozzle and the hull is less than 200mm, the electric recovery rod is shortened by a corresponding length. H 2 , to ensure that the film thickness meets the 150µm requirement; Fig.10 (c) When the spraying area is a concave or convex surface, an electric recovery rod shortens the corresponding distance H 3 ' , the other electric recovery rod extends the corresponding distance H 3 '' , ensuring that both ends are always parallel to the outer surface of the ship, and the spraying thickness meets the requirement of 150µm.

[0048] The robot motor drive control model speed simulation diagram is as follows Fig.11 As shown in the figure, the vertical axis represents the running speed, the horizontal axis represents the simulation time, and the curve in the figure represents the change of motor speed. The simulation time is about 0.01 seconds, the motor starts to accelerate, and always maintains a high and stable speed. The simulation shows that the speed of the motor drive control model meets the design requirements.

[0049] Reference Fig.12 , 13 The present invention provides a digital twin monitoring screen for material consumption and motor operation, and a digital twin control screen for dock operation status. The digital twin large screen is used to display the working status of the robot in real time and to issue an alarm when an abnormal situation occurs.

[0050] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, i.e., may be located in one place, or may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0051] Finally, it should be pointed out that the above embodiments are only used to describe the technical solutions of the present invention, and are not restrictive. Although the present invention has been specifically described with reference to the above embodiments, a person skilled in the art should understand that the present invention is not limited to the exact structures described above and shown in the accompanying drawings, and can be subjected to various modifications and changes without departing from the scope thereof.

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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