Ship rust detection and adaptive rust removal wall-climbing robot system and its control method

Abstract

This invention discloses a ship corrosion detection and adaptive rust removal wall-climbing robot system and its control method. The mobile robot includes a permanent magnet adsorption active swing arm mechanism and a permanent magnet adsorption track walking mechanism to achieve stable movement on curved surfaces. A line laser profile sensor mounted on the nozzle bracket at the end of the four-degree-of-freedom robotic arm collects three-dimensional point cloud data and laser intensity maps of the ship surface, constructs a blind-spot-free map, and generates a full-coverage path. A high-pressure water jet nozzle array is installed at the end of the robotic arm, and a friction brush mechanism is installed at the bottom of the robot. In the pre-detection and path planning stages, the rust point cloud coverage, maximum pitting depth, and surface roughness are extracted simultaneously using the point cloud, and a full-ship path is generated based on the point cloud map. Based on this, the water jet pressure, moving speed, nozzle swing frequency, and brush rotation speed and downward pressure are adaptively planned. During rust removal, the laser intensity map of the line laser profile sensor is used to quantitatively calculate the rust area in real time. When the water jet pressure reaches the upper limit and the area reduction rate is lower than the threshold, it is determined to be stubborn rust, and the friction brush collaborative peeling is immediately initiated. After rust removal, the point cloud computing rust removal rate is collected again and the pitting depth is re-checked. If the standard is not met, rust removal is automatically performed again. The rust removal volume based on the point cloud computing before and after can be used as an additional evaluation index. This invention significantly improves the intelligence level of ship surface rust removal through closed-loop control of point cloud pre-detection, parameter adaptive planning, process verification, and stubborn rust compensation.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of robotics, three-dimensional vision perception and ship maintenance, and specifically relates to a ship rust detection and adaptive rust removal wall-climbing robot system and its control method. Background Technology

[0002] Ships operate in the marine environment for extended periods, and rust on the hull surface is a major factor affecting structural safety and service life. Without timely inspection and maintenance, it poses a serious threat to navigational safety. Traditional ship rust removal and inspection operations have long relied on manual visual inspection combined with handheld sandblasting or high-pressure water jet equipment. This approach is not only labor-intensive and inefficient, but also presents significant safety risks due to the high-altitude working environment. In recent years, wall-climbing robot technology has gradually developed, and some products already possess basic rust removal or inspection functions. However, the following key shortcomings still exist in existing technologies.

[0003] Regarding the structure of rust removal robots, CN118143865A discloses a rust removal actuator and an automatic rust removal robot, employing a multi-directionally rotating boom assembly in conjunction with a spray disc actuator and a wastewater recovery assembly to achieve rust removal operations in the dock area of ​​a ship's hull. However, the aforementioned inventions only focus on improvements to the mechanical structure and walking mechanism, lacking quantitative detection methods for the degree of rust on the curved surfaces of ships, and are unable to achieve autonomous planning and real-time adjustment of rust removal parameters. In terms of rust detection, CN117341853A discloses a motion-based online rust recognition method for rust removal robots used on ship hulls. This method combines machine vision technology with photosensitive elements, utilizing the difference in reflection phenomena after light shines on rusted and non-rusted areas of the steel plate to detect the rust removal effect in real time. However, this method only provides a qualitative judgment of the presence of rust, failing to output multi-dimensional quantitative parameters such as point cloud coverage, maximum pitting depth, and surface roughness for precise planning of rust removal parameters, and lacks closed-loop feedback between the detection results and the actuator.

[0004] In summary, existing ship wall-climbing rust removal and inspection technologies still have significant shortcomings in the following aspects: First, there is a lack of a quantitative planning method to directly map the quantitative detection results of rust on the curved surfaces of the ship into rust removal operation parameters, making it difficult to adaptively adjust key parameters such as rust removal pressure and moving speed according to the actual degree of rust. Second, the rust removal process lacks a rust area monitoring and adaptive compensation mechanism based on real-time feedback, making it impossible to identify and remove stubborn rust during the operation. Third, after rust removal, there is a lack of a closed-loop verification and evaluation mechanism based on the difference in detection data, making it difficult to achieve complete closed-loop quality control. Therefore, there is an urgent need for a ship rust detection and adaptive rust removal wall-climbing robot system and control method that integrates multi-dimensional quantitative rust detection, parameter adaptive planning, process verification compensation, and closed-loop re-inspection. Summary of the Invention

[0005] The first aspect of this invention provides a ship rust detection and adaptive rust removal wall-climbing robot system, comprising the following:

[0006] Mobile robot body, detection module, rust removal module, control and data processing module;

[0007] The mobile robot body includes a permanent magnet adsorption track walking mechanism and a permanent magnet adsorption active swing arm mechanism. The permanent magnet adsorption active swing arm mechanism is arranged on the left and right sides of the robot body, with two permanent magnet adsorption active swing arm mechanisms on each side, one in front and one in back. Each swing arm mechanism can independently and actively adjust the swing arm angle according to the wall curvature or adsorption force feedback, so that the permanent magnet adsorption auxiliary track on the swing arm maintains a constant adhesion force while working together to achieve the obstacle crossing function of crossing protruding obstacles, providing stable continuous movement conditions for the permanent magnet adsorption track walking mechanism on complex curved surfaces. The permanent magnet adsorption track walking mechanism is arranged on the left and right sides of the robot body.

[0008] The detection module includes a line laser profile sensor mounted on the nozzle bracket at the end of a four-degree-of-freedom robotic arm. The line laser profile sensor, based on the principle of laser triangulation, moves with the robotic arm and is used to collect three-dimensional point cloud data and laser intensity maps of the ship's surface to construct a blind-spot-free three-dimensional map and extract the point cloud coverage, maximum pitting depth, and surface roughness of the rusted area. The laser intensity map is used to quantitatively calculate the rate of change of rusted area.

[0009] The rust removal module includes a four-degree-of-freedom robotic arm, an array of ultra-high-pressure water jet nozzles mounted at the end of the robotic arm, and a friction brush mechanism mounted at the bottom of the robot. The robotic arm drives the nozzles to achieve multi-angle high-pressure water jet rust removal. The friction brush mechanism can press down on the wall surface and rotate at high speed when the stubborn rust determination condition is met, working in conjunction with the high-pressure water jet to peel off the rust layer. The stubborn rust determination condition is: the water jet pressure reaches a set maximum value, and the rust area reduction rate of two adjacent scans at the same position collected by the line laser profile sensor is lower than a set threshold.

[0010] The control and data processing module is used to perform motion control, path planning, point cloud data processing, rust parameter extraction, rust removal parameter adaptive planning, and to realize closed-loop control of pre-detection, rust removal and post-detection.

[0011] A second aspect of the present invention provides an integrated collaborative control method for ship rust detection and adaptive rust removal based on the above-mentioned wall-climbing robot system, comprising the following steps:

[0012] S1, Pre-detection and Path Planning Stage

[0013] Based on the continuous movement capability of the permanent magnet adsorption track walking mechanism and the collaborative obstacle-crossing capability of multiple permanent magnet adsorption active swing arm mechanisms, the robot uses a line laser contour sensor to collect three-dimensional point cloud data of the ship's surface. The collected point cloud data is filtered, segmented, and feature extracted to output the rust point cloud coverage, maximum pitting depth, and surface roughness. Based on the point cloud, a blind-spot-free three-dimensional map is constructed, and a fully covered path is generated. Then, the robot moves along the path, and each swing arm mechanism independently and dynamically adjusts the swing arm angle according to the curvature feedback so that the permanent magnet adsorption auxiliary track conforms to the curved surface and crosses obstacles.

[0014] S2, Adaptive Programming of Rust Removal Parameters

[0015] After the pre-inspection is completed, the robot sets the rust removal parameters according to the rust parameters output by S1. The specific rules are as follows: the maximum value of the water jet pressure is set according to the maximum pitting depth, and the greater the pitting depth, the higher the pressure limit; the robot's moving speed is set according to the coverage of the rust point cloud, and the greater the coverage, the slower the moving speed; the nozzle oscillation frequency and the friction brush rotation speed are set according to the surface roughness, and the higher the roughness, the higher the oscillation frequency and the higher the brush rotation speed; the downward pressure of the friction brush is set according to the maximum pitting depth, and the greater the depth, the lower the downward pressure.

[0016] S3, Rust Removal Stage

[0017] The robot moves along the path generated in S1 again, controlling the four-degree-of-freedom robotic arm to drive the nozzle to swing according to the parameters planned in S2 for high-pressure water jet rust removal. During this stage, the laser intensity map from the line laser profile sensor quantitatively calculates the rust area at the same location in real time, and calculates the rust area reduction rate between adjacent scans. If the reduction rate is not lower than the set threshold, the current rust removal parameters are maintained and no intervention is performed; otherwise, the control module first determines whether the current water jet pressure has reached the maximum value set in S2. If it has not yet reached it, the pressure is increased incrementally by a set step size (not exceeding the safety upper limit), and the rust area change is monitored again. If the pressure has increased to the maximum value but the area reduction rate is still continuously lower than the threshold, it is determined to be stubborn rust, indicating that the actual pitting depth in this area is greater than the pre-detection value. At this point, the control module automatically executes a coordinated action: the robot reduces its moving speed and moves back and forth to the stubborn rust area, controls the friction brush mechanism to press down on the wall and rotate at high speed, so that the water jet impact and mechanical rotation friction work together to peel off the stubborn rust layer; after the rust area reduction rate in this area reaches the set threshold, the control module raises the friction brush, and the robot resumes its original speed and continues to move forward.

[0018] S4, Post-detection stage

[0019] After rust removal is completed, the robot moves again along the path generated in S1, re-collects point cloud data, performs the same point cloud processing procedure as in S1, calculates the rust removal rate, and re-checks whether the maximum pitting depth has changed. Simultaneously, the rust removal volume is calculated based on the previous and subsequent point cloud data as an additional evaluation indicator. If the rust removal rate is lower than a set threshold or the pitting depth increases significantly, re-rust removal is automatically triggered, repeating S2 to S3; otherwise, an inspection report is generated and uploaded to the ground control station via wireless communication.

[0020] In one embodiment, the permanent magnet adsorption active swing arm mechanism includes a swing arm, a permanent magnet adsorption auxiliary track and its drive motor; the control module drives the swing arm in real time according to the feedback from the IMU or torque sensor, so that the permanent magnet adsorption auxiliary track actively conforms to the wall surface or is lifted over the protruding obstacle. When a certain swing arm performs a lifting action, the permanent magnet adsorption auxiliary track on that swing arm leaves the wall surface, and the air gap between it and the wall surface passively increases. The apparent adsorption force of the permanent magnet adsorption block naturally decreases as the air gap increases, thereby reducing the lifting resistance. At the same time, the permanent magnet adsorption auxiliary tracks of other non-lifted permanent magnet adsorption active swing arm mechanisms and the parts of the permanent magnet adsorption track walking mechanism that are still attached to the wall surface maintain their adsorption force unchanged, continuously providing basic adsorption force. When the robot walks normally, the total adsorption force has a preset safety redundancy. The obstacle-crossing lifting action only causes the local adsorption force to decrease, while the total effective adsorption force is always higher than the preset safety threshold, realizing the passive collaborative distribution of adsorption force among multiple adsorption units. The permanent magnet adsorption track walking mechanism is driven by a walking drive motor through drive gears and transmission gears to drive the walking track, and at the same time, it drives the permanent magnet adsorption auxiliary track to move synchronously through a coupling.

[0021] In one embodiment, the friction brush disc mechanism includes a swing motor, a rocker arm, an incomplete gear, a rack, a friction rotary motor, a preload spring, and a friction brush disc. When the stubborn corrosion judgment condition is met, the control module drives the swing motor, and through the meshing transmission of the incomplete gear and the rack, the friction brush disc is pressed downward against the wall surface. At the same time, the friction rotary motor is driven to make the friction brush disc rotate at high speed, forming stable mechanical friction.

[0022] In one implementation, the control and data processing module adopts an embedded platform and integrates a wireless communication module for real-time data transmission and remote control.

[0023] Compared with the prior art, the present invention has the following advantages:

[0024] (1) The present invention adopts a combination of permanent magnet adsorption track walking mechanism and permanent magnet adsorption active swing arm mechanism. Each swing arm can independently and actively adjust its angle to realize active adaptation and obstacle crossing function of complex curved surface. When crossing obstacles, the passive cooperative mechanism of increasing air gap to naturally attenuate adsorption force is used to reduce lifting resistance while ensuring adsorption stability.

[0025] (2) The present invention uses a line laser profile sensor to simultaneously acquire three-dimensional point cloud and laser intensity map. The point cloud is used to extract the rust point cloud coverage, maximum pitting depth and surface roughness, and the intensity map is used to quantitatively calculate the rust area change rate, realizing multi-dimensional quantitative detection of rust degree, and providing a complete input basis for adaptive planning of rust removal parameters.

[0026] (3) The present invention establishes a quantitative mapping rule between rust parameters and rust removal parameters. Based on the pitting depth, point cloud coverage, and surface roughness, the water jet pressure, moving speed, oscillation frequency, brush rotation speed and downward pressure are planned respectively, realizing the refined adaptive control of rust removal operation.

[0027] (4) During the rust removal process, the present invention monitors the rust area change in real time through the laser intensity map. When the change rate is normal, the original parameters are maintained. If the area reduction rate is continuously lower than the threshold, the control module adaptively increases the water jet pressure until the upper limit. If it is still ineffective, the friction brush and water jet are automatically triggered to peel off the stubborn rust layer in synergy. The reciprocating operation mode is adopted to enhance the rust removal effect, forming a multi-level closed-loop feedback mechanism of "effect monitoring - pressure adaptation - online compensation".

[0028] This invention achieves full-scale closed-loop verification of rust removal quality and automatic rust repair by collecting point cloud data again after rust removal, calculating rust removal rate and rust removal volume, and re-inspecting changes in pitting depth. This forms a complete intelligent maintenance process of "detection-planning-execution-verification-compensation". Attached Figure Description

[0029] Figure 1 This is a schematic front view of the overall structure of the wall-climbing robot according to an embodiment of the present invention.

[0030] Figure 2 This is a top-view cross-sectional view of the overall structure of the wall-climbing robot according to an embodiment of the present invention.

[0031] Figure 3 This is a schematic diagram of the permanent magnet adsorption type active swing arm mechanism according to an embodiment of the present invention.

[0032] Figure 4 This is a schematic diagram of the friction brush mechanism according to an embodiment of the present invention.

[0033] Figure 5 This is a schematic diagram of the four-degree-of-freedom robotic arm structure of a wall-climbing robot according to an embodiment of the present invention.

[0034] Figure 6 This is a flowchart of the overall closed-loop control method according to an embodiment of the present invention.

[0035] Figure 7 This is a flowchart of point cloud acquisition and data processing according to an embodiment of the present invention.

[0036] Figure 8 This is a logic diagram for the determination of stubborn rust and collaborative rust removal in an embodiment of the present invention.

[0037] The components include: 1. Robot body; 2. Control compartment; 3. Walking drive motor; 4. Walking track; 5. Walking drive gear; 6. First driven large gear; 7. Permanent magnet adsorption block; 8. Permanent magnet adsorption type active swing arm mechanism; 801. Swing arm pinion; 802. Swing arm; 803. Second driven large gear; 804. Coupling; 805. Permanent magnet adsorption type auxiliary track; 806. Swing arm drive motor; 807. Reducer; 808. Long flange; 809. Flange; 9. Friction brush mechanism; 901. Swing motor; 902. Rocker arm; 903. Friction rotary motor; 904. Incomplete gear; 905. Swing arm; 906. 907. Preloaded spring; 908. Protective shell; 10. Friction brush; 11. Ultra-high pressure water jet nozzle array; 12. Nozzle bracket; 13. Coupling water supply pipeline; 14. Four-degree-of-freedom robotic arm; 15. Swing arm motor; 16. Swing arm connecting plate; 17. Cover plate; 18. Bolt; 19. Optical axis; 10. Motor connecting plate; 10. Side plate; 11. Linear laser profile sensor. Detailed Implementation

[0038] This embodiment is implemented on an automated maintenance platform for the hull plating of large ships. It should be noted that the specific parameters described below are merely illustrative examples and can be adjusted according to the degree of corrosion and equipment capabilities in practical applications, and do not constitute a limitation on the scope of protection of this invention.

[0039] Robot system assembly

[0040] like Figure 1-5As shown, the mobile robot body 1 includes a permanent magnet adsorption type track walking mechanism and a permanent magnet adsorption type active swing arm mechanism 8. The permanent magnet adsorption type track walking mechanism has a walking track 4 installed on each of the left and right sides. The walking drive motor 3 drives the walking drive gear 5, which drives the first driven large gear 6 to rotate. The first driven large gear 6 drives the walking track 4 to move, realizing the movement of the robot on the wall. The permanent magnet adsorption type active swing arm mechanism 8 drives the swing arm 802 to swing around the hinge point through the speed adjustment of the swing arm drive motor 806 and the reducer 807, thereby changing the contact angle between the permanent magnet adsorption type auxiliary track 805 and the wall, so as to dynamically adapt to the hull surface with different curvatures. The first driven large gear 6 drives the second driven large gear 803 to rotate through the coupling 804, thereby driving the auxiliary track 805 and the swing arm pinion 801 to move. The front wheel bracket 802 provides support, the cover plate 14 and the side plate 18 provide protection, and the long flange 808, flange 809, bolt 15, optical shaft 16 and motor connecting plate 17 provide connection. The permanent magnet adsorption block 7 is embedded in the track walking mechanism and the swing arm mechanism. It uses high magnetic energy product neodymium iron boron magnets and is covered with a wear-resistant protective sleeve.

[0041] The detection module includes a line laser profile sensor 19 mounted on the nozzle bracket 11 at the end of the four-degree-of-freedom robotic arm 13. The line laser profile sensor is based on the principle of laser triangulation and moves with the robotic arm to collect three-dimensional point cloud data of the ship's surface. and laser intensity map .

[0042] The rust removal module includes the four-degree-of-freedom robotic arm 13, an ultra-high-pressure water jet nozzle array 10 mounted at the end of the robotic arm, and a friction brush disc mechanism 9 mounted on the bottom of the robot. The four-degree-of-freedom robotic arm 13 includes a swing arm motor 1301 and a swing arm connecting plate 1302, which can drive the nozzles to achieve multi-angle high-pressure water jet rust removal. A nozzle support 11 has multiple ultra-high-pressure water jet nozzle arrays 10 evenly arranged on it. The nozzles have a set diameter, rated pressure to meet rust removal requirements, and total flow rate matched with pressure. The coupling water is supplied by a branch of the coupling water supply pipeline 12. The friction brush disc mechanism 9 is mounted in the center of the robot's bottom for mechanical friction peeling of stubborn rust. The friction brush disc mechanism 9 includes: a swing motor 901, a rocker arm 902, a friction rotation motor 903, an incomplete gear 904, a swing arm 905, a preload spring 906, a protective shell 907, and a friction brush disc 908. The collaborative workflow is as follows: When the control system determines that mechanical friction needs to be initiated, the swing motor 901 drives the rocker arm 902 to swing, the rocker arm 902 drives the swing arm 905 to move, and the swing arm 905 further drives the incomplete gear 904 to rotate; the incomplete gear 904 meshes with the rack fixed to the top of the friction brush disk 908, and the friction brush disk 908 is pressed down or lifted up by the up and down movement of the rack; at the same time, the friction rotary motor 903 independently drives the friction brush disk 908 to rotate at high speed, so that under the constant pressure provided by the preload spring 906, the friction brush disk 908 forms a stable rotational friction contact with the wall surface. The protective shell 907 is used to encapsulate the internal transmission components to prevent the intrusion of high-pressure water jets and rust. This mechanism works in conjunction with the ultra-high pressure water jet nozzle array 10: the water jet first impacts and loosens the surface rust, and then the friction brush disk 908 rotates and rubs at a set speed and pressure to mechanically peel off the residual rust layer. The two work together to form a synergistic rust removal by water jets and mechanical friction.

[0043] The control and data processing module is built into the control compartment 2, including an embedded platform and a wireless communication module, and is used to perform motion control, point cloud processing, parameter planning and closed-loop control.

[0044] The overall control method of the present invention is as follows: Figure 6 As shown, it includes the following steps:

[0045] S1, Pre-detection and Path Planning Stage

[0046] After the robot starts, it first enters the pre-detection and path planning stage. The four-DOF robotic arm 13 unfolds, and the line laser contour sensor 19 moves with the robotic arm to collect three-dimensional point cloud data of the ship's surface at an actively adjusted scanning angle. The control module performs statistical filtering on the point cloud to remove outliers and uses a random sampling consensus algorithm to segment the plane reference, obtaining the reference plane equation. Then, the point cloud of rust pits is extracted by elevation threshold segmentation, assuming the deviation between the elevation of the measured point and the reference surface is . Then the rust pits are satisfied The set of points, where The depth threshold is set. Based on the above segmentation, the following corrosion parameters are calculated:

[0047] Rust point cloud coverage: ,in The number of point clouds representing rust pits. This represents the total number of point clouds in the detection area.

[0048] Maximum pitting depth: .

[0049] Surface roughness: using local elevation mean square error, within a sliding window. Internal computation The average value of the entire area is taken. At the same time, a blind-spot-free 3D map is constructed based on the point cloud, and a full-coverage path (such as a bow-shaped reciprocating path) with the spacing between adjacent rows smaller than the rust removal width is planned. Then the robot moves along the path, and each active swing arm mechanism independently and dynamically adjusts the swing arm angle based on the wall curvature feedback detected by the IMU, so that the permanent magnet adsorption auxiliary track can conform to the curved surface and cross obstacles.

[0050] S2, Adaptive Programming of Rust Removal Parameters

[0051] After the pre-detection is completed, the control module automatically sets the rust removal parameters based on the rust parameters output by S1. The process is as follows: Figure 7 As shown. Let the rust removal parameter vector be... , representing water jet pressure, robot movement speed, nozzle oscillation frequency, brush rotation speed, and brush downward pressure, respectively. The following empirical functions are used to implement the quantization mapping:

[0052]

[0053] in As the baseline parameter, The positive coefficients calibrated in the experiment. The maximum allowable pitting depth (usually a set percentage of the plate thickness). Based on the actual degree of rust, the control module automatically calculates and outputs the corresponding rust removal parameters.

[0054] S3, Rust Removal Stage

[0055] The robot moves along the path generated by S1 again, and the four-degree-of-freedom robotic arm drives the nozzle to oscillate according to the parameters planned in S2 to perform high-pressure water jet rust removal. At this stage, the laser intensity map from the line laser profile sensor... Real-time quantitative calculation of the corrosion area at the same location. In the intensity map, the corrosion area has low reflection intensity (small gray value), while the metal area has high reflection intensity (large gray value). The corrosion boundary can be extracted through adaptive threshold segmentation, and the corrosion area can be calculated. Define the rate of reduction in rusted area:

[0056]

[0057] The control module operates at fixed time intervals. (e.g., 1 second) Continuously monitor the rate of reduction in rusted area. .like This indicates that the rust removal effect is normal. The robot will continue to move forward while maintaining the current water jet pressure and speed. Otherwise, the control module will first determine the current water jet pressure. Has the maximum value set in step S2 been reached? ,like The pressure will then increase in preset increments (e.g., 100 bar increments each time), but not exceeding [a certain value]. And remonstrate with subsequent γ values; if the pressure has increased to If γ remains consistently below the threshold, it is considered stubborn corrosion, indicating that the actual pitting depth in the area is greater than the pre-detection value. At this point, the control module automatically executes a coordinated action: the robot reduces its speed and works back and forth in the area, while simultaneously driving the friction brush mechanism to press downwards against the wall and rotate at high speed, allowing the water jet impact and mechanical rotation friction to work together to peel away the stubborn rust layer. Once the rust area reduction rate in this area reaches a set threshold (e.g., 90%), the control module raises the friction brush, and the robot resumes its original speed and continues moving forward. The decision-making process is as follows: Figure 8 As shown.

[0058] S4, Post-detection stage

[0059] After rust removal is complete, the robot moves again along the path generated by S1, re-collects point cloud data, and performs the same point cloud processing procedure as S1. The rust removal rate is calculated.

[0060]

[0061] Simultaneously re-inspect the maximum pitting depth. To determine whether new damage has occurred to the base material, point cloud registration is used to calculate the rust removal volume. The pre-detection point cloud is assumed to be... The point cloud was detected later. After registering the two to a unified coordinate system, for each area within the corrosion region... Calculate elevation difference The volume removed is:

[0062]

[0063] This volume value can be used as an additional evaluation indicator for rust removal effectiveness. If the rust removal rate is higher than the set threshold (e.g., 95%) and the pitting depth does not increase significantly, the system determines it to be qualified and automatically generates a test report, including a rust distribution map, a rust removal parameter table, the rust removal rate of each area, the rust removal volume, and changes in pitting depth, which is then uploaded to the ground control station via wireless communication. If the rust removal rate is lower than the set threshold or the pitting depth increases abnormally, the rust removal repair mechanism is automatically triggered, repeating steps S2 to S3.

[0064] Obstacle crossing collaborative safety verification

[0065] When the robot traverses protruding obstacles such as weld seams and reinforcing ribs, the corresponding permanent magnet adsorption-type active swing arm mechanism needs to perform a lifting action. The permanent magnet adsorption-type auxiliary track on this swing arm leaves the wall surface, and the air gap between it and the wall surface... The value passively increases from a smaller value (e.g., 1-2 mm) under normal walking conditions to a larger value (up to 10 mm or more). According to the magnetic circuit model, the relationship between the adsorption force of the permanent magnet adsorption block and the air gap can be described by the following formula:

[0066]

[0067] in Residual magnetism, For the thickness of the magnet, This represents the effective adsorption area of ​​a single magnet. Let be the vacuum permeability. As can be seen from the above formula, the adsorption force varies with the air gap. The increase in torque significantly reduces the driving torque required to lift the swing arm, thus achieving passive drag reduction. Meanwhile, the remaining unlifted permanent magnet adsorption units (including permanent magnet blocks on the main track and auxiliary tracks on other swing arms still in contact with the wall) maintain normal air gaps, and their adsorption force remains at the design level. Let the sum of the robot's weight and load be... The total adsorption force provided by all permanent magnet units is The safe operating conditions are:

[0068]

[0069] In the formula A safety factor (typically 2-3) is used. During obstacle-crossing and lifting, although the local adsorption force decreases due to the increased air gap, the total adsorption force still satisfies the above inequality because there are sufficient other bonding units and the adsorption force remains unchanged. This ensures that the robot maintains stable adsorption and eliminates the risk of tipping over. This mechanism achieves a passive and coordinated distribution of adsorption force among different adsorption units without requiring additional control overhead.

[0070] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A ship rust detection and adaptive rust removal wall-climbing robot system, characterized in that: The system includes a mobile robot body, a detection module, a rust removal module, and a control and data processing module; The mobile robot body includes a permanent magnet adsorption track walking mechanism and a permanent magnet adsorption active swing arm mechanism. The permanent magnet adsorption active swing arm mechanism is arranged on the left and right sides of the robot body, with two permanent magnet adsorption active swing arm mechanisms on each side, one in front and one in back. Each swing arm mechanism can independently and actively adjust the swing arm angle according to the wall curvature or adsorption force feedback, so that the permanent magnet adsorption auxiliary track on the swing arm maintains a constant adhesion force while working together to achieve the obstacle crossing function of crossing protruding obstacles, providing stable continuous movement conditions for the permanent magnet adsorption track walking mechanism on complex curved surfaces. The permanent magnet adsorption track walking mechanism is arranged on the left and right sides of the robot body. The detection module includes a line laser profile sensor mounted on the nozzle bracket at the end of a four-degree-of-freedom robotic arm. The line laser profile sensor, based on the principle of laser triangulation, moves with the robotic arm and is used to collect three-dimensional point cloud data and laser intensity maps of the ship's surface to construct a blind-spot-free three-dimensional map and extract the point cloud coverage, maximum pitting depth, and surface roughness of the rusted area. The laser intensity map is used to quantitatively calculate the rate of change of rusted area. The rust removal module includes a four-degree-of-freedom robotic arm, an array of ultra-high-pressure water jet nozzles mounted at the end of the robotic arm, and a friction brush mechanism mounted at the bottom of the robot. The robotic arm drives the nozzles to achieve multi-angle high-pressure water jet rust removal. The friction brush mechanism can press down on the wall surface and rotate at high speed when the stubborn rust determination condition is met, working in conjunction with the high-pressure water jet to peel off the rust layer. The stubborn rust determination condition is: the water jet pressure reaches a set maximum value, and the rust area reduction rate of two adjacent scans at the same position collected by the line laser profile sensor is lower than a set threshold. The control and data processing module is used to perform motion control, path planning, point cloud data processing, rust parameter extraction, rust removal parameter adaptive planning, and to realize closed-loop control of pre-detection, rust removal and post-detection. The control method for a ship rust detection and adaptive rust removal wall-climbing robot system is characterized by the following steps: S1. Pre-detection and path planning stage: Relying on the continuous movement capability of the permanent magnet adsorption track walking mechanism and the cooperative obstacle-crossing capability of multiple permanent magnet adsorption active swing arm mechanisms, three-dimensional point cloud data of the ship surface is collected using a line laser contour sensor; the collected point cloud data is filtered, segmented and feature extracted, and the rust point cloud coverage, maximum pitting depth and surface roughness are output. Based on the point cloud, a blind-spot-free three-dimensional map is constructed, and a full-coverage path without omissions is generated accordingly; then the robot moves along the path, and each swing arm mechanism independently and dynamically adjusts the swing arm angle according to the curvature feedback so that the permanent magnet adsorption auxiliary track fits the curved surface and crosses obstacles. S2. Adaptive Planning of Rust Removal Parameters: After pre-inspection, the robot sets the rust removal parameters according to the rust parameters output by S1. The specific rules are as follows: the maximum value of the water jet pressure is set according to the maximum pitting depth. The greater the pitting depth, the higher the pressure limit. The robot's moving speed is set according to the coverage of the rust point cloud. The greater the coverage, the slower the moving speed. The nozzle oscillation frequency and friction brush rotation speed are set according to the surface roughness. The higher the roughness, the higher the oscillation frequency and brush rotation speed. The downward pressure of the friction brush is set according to the maximum pitting depth. The greater the depth, the lower the downward pressure. S3, Rust Removal Execution Phase: The robot moves along the path generated in S1 again, controlling the four-degree-of-freedom robotic arm to drive the nozzle to swing according to the parameters planned in S2 for high-pressure water jet rust removal. In this phase, the laser intensity map of the line laser profile sensor is used to quantitatively calculate the rust area at the same location in real time, and to calculate the rust area reduction rate between two adjacent scans. If the reduction rate is not lower than the set threshold, the current rust removal parameters are maintained and no intervention is performed. Otherwise, the control module first determines whether the current water jet pressure has reached the maximum value set in S2. If it has not yet reached the maximum value, the pressure is increased step by step according to the set step size. (Not exceeding the safety limit), and re-monitor the change in rust area; if the pressure has increased to the maximum value but the area reduction rate is still continuously lower than the threshold, it is judged as stubborn rust, indicating that the actual pitting depth in the area is greater than the pre-detection value; at this time, the control module automatically executes a coordinated action: the robot reduces its moving speed and moves back and forth in the stubborn rust area, controls the friction brush mechanism to press down on the wall and rotate at high speed, so that the water jet impact and mechanical rotation friction work together to peel off the stubborn rust layer; after the rust area reduction rate in the area reaches the set threshold, the control module raises the friction brush, and the robot resumes its original speed and continues to move forward; S4. Post-inspection stage: After rust removal is completed, the robot moves again along the path generated in S1, re-collects point cloud data, performs the same point cloud processing procedure as in S1, calculates the rust removal rate, and re-checks whether the maximum pitting depth has changed. At the same time, the rust removal volume is calculated based on the point cloud data before and after as an additional evaluation indicator. If the rust removal rate is lower than the set threshold or the pitting depth increases significantly, the robot will automatically trigger additional rust removal and repeat S2 to S3. Otherwise, an inspection report will be generated and uploaded to the ground control station via wireless communication.

2. The wall-climbing robot system and its control method according to claim 1, characterized in that, The permanent magnet adsorption type active swing arm mechanism includes a swing arm, a permanent magnet adsorption type auxiliary track and its drive motor; the control module drives the swing arm in real time according to the feedback of the IMU or torque sensor, so that the permanent magnet adsorption type auxiliary track actively conforms to the wall surface or is lifted over the protruding obstacle. When a certain swing arm performs a lifting action, the permanent magnet adsorption auxiliary track on that swing arm leaves the wall surface, passively increasing the air gap between it and the wall. The apparent adsorption force of the permanent magnet adsorption block naturally decreases as the air gap increases, thereby reducing the lifting resistance. At the same time, the permanent magnet adsorption auxiliary tracks of other non-lifted permanent magnet adsorption active swing arm mechanisms and the parts of the permanent magnet adsorption track walking mechanism that are still attached to the wall surface maintain their adsorption force unchanged, continuously providing basic adsorption force. When the robot walks normally, the total adsorption force has a preset safety redundancy. The obstacle-crossing lifting action only causes the local adsorption force to decrease, while the total effective adsorption force is always higher than the preset safety threshold, realizing the passive collaborative distribution of adsorption force among multiple adsorption units. The permanent magnet adsorption track walking mechanism is driven by a walking drive motor through drive gears and transmission gears to drive the walking track, and at the same time, it drives the permanent magnet adsorption auxiliary track to move synchronously through a coupling.

3. The wall-climbing robot system and its control method according to claim 1, characterized in that, The friction brush mechanism includes a swing motor, a rocker arm, an incomplete gear, a rack, a friction rotary motor, a preload spring, and a friction brush. When the stubborn corrosion judgment condition is met, the control module drives the swing motor, and through the meshing transmission of the incomplete gear and the rack, the friction brush presses the friction brush downward against the wall surface. At the same time, it drives the friction rotary motor to make the friction brush rotate at high speed, forming stable mechanical friction.

4. The wall-climbing robot system and its control method according to claim 1, characterized in that, The full-coverage path described in S1 uses the effective rust removal width of the nozzle as the grid unit to plan a reciprocating path with the spacing between adjacent rows being smaller than the rust removal width, and the path shape includes bow shape, square shape or spiral shape.

5. The wall-climbing robot system and its control method according to claim 1, characterized in that, The point cloud data processing described in S1 includes: performing statistical filtering on the original point cloud to remove outliers, using a random sampling consensus algorithm to segment the plane reference, extracting the rust pit point cloud through elevation threshold segmentation, and calculating the rust point cloud coverage, maximum pitting depth, and surface roughness.

6. The wall-climbing robot system and its control method according to claim 1, characterized in that, The threshold set in S3 is specifically as follows: the reduction rate of rust area calculated by the laser intensity map is lower than the set percentage, and the monitoring interval is the set value; when the friction brush is started after the stubborn rust is determined, the brush rotation speed is consistent with the rotation speed planned in S2, and the downward pressure is determined by the value set in S2 based on the maximum pitting depth.

7. The wall-climbing robot system and its control method according to claim 1, characterized in that, The method for calculating the rust removal volume is as follows: the point cloud data collected before and after rust removal are registered in a unified coordinate system, and the total volume of rust removal is calculated by point cloud difference and integration, which serves as an evaluation index for the rust removal effect.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method described in any one of claims 1 to 7.

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