Large pressure vessel automatic detection robot

Abstract

An automatic detection robot for a large pressure vessel relates to the technical field of posture adjustment of adsorption robots. In order to solve the technical defects of insufficient gravity center adjustment flexibility and single attitude adjustment means in the attitude adjustment technology of the existing wall-climbing robot in the prior art, the technical scheme provided by the invention is as follows: the wall-climbing robot attitude adjustment system comprises a driving system, comprising two driving wheels installed on the front-back central axis of the robot and two driven universal wheels installed at the front end and the rear end of the robot. The adsorption system comprises a permanent magnet which is modularly arranged, and the permanent magnet is mounted at the bottom of the robot; the nondestructive testing module comprises an eddy current probe sliding table; the camera swing arm module is arranged at the top of the robot, and a camera is installed at the tail end of a swing arm and used for monitoring the robot environment in real time and optimizing the gravity center through angle adjustment of the swing arm; and the inertial sensor module is used for monitoring attitude information of the robot on the wall surface in real time. The method is suitable for being applied to posture adjustment work of the wall-climbing robot.

Description

Technical Field

[0001] It relates to the technical field of adsorption robot attitude adjustment, specifically to the attitude adjustment of large pressure vessel automatic detection robots. Background Art

[0002] As a special robot that can adapt to complex wall environments, wall-climbing robots have a wide range of applications in industrial inspection, maintenance, and cleaning. Their ability to move on vertical metal walls or inclined surfaces makes them an ideal tool to replace manual operations. To achieve efficient and stable movement, wall-climbing robots need to have reliable adsorption capabilities, flexible movement methods, and precise attitude adjustment capabilities.

[0003] In terms of attitude adjustment, the existing technologies mainly focus on the following research directions:

[0004] 1. Application of inertial sensors

[0005] Wall-climbing robots are generally equipped with inertial sensors (such as accelerometers and gyroscopes) to obtain their acceleration and angular velocity data in real time. These sensors can monitor the tilt angle, center-of-gravity change, and motion state of the robot. By collecting sensor data, existing research attempts to use angle changes to judge abnormal robot postures and make adjustments. For example, some research has proposed a real-time tilt angle monitoring system based on inertial sensor data to issue an alarm when the robot's posture deviates. However, most existing methods only stay at the detection stage, and the adjustment measures after abnormal postures are relatively single.

[0006] 2. Center-of-gravity optimization methods

[0007] During wall movement, the position of the robot's center of gravity has a significant impact on the adsorption state. Existing technologies attempt to improve adsorption stability through fixed center-of-gravity design or structural optimization. For example, some robots use fixedly installed counterweights to keep the center of gravity close to the wall, but this method lacks flexibility and cannot cope with abnormal postures caused by real-time center-of-gravity shifts.

[0008] 3. Adjustment ability of the motion system

[0009] To solve the problem of abnormal postures, some technologies restore stability by adjusting the speed and direction of the robot's drive system. For example, differentially driven robots change the motion trajectory by adjusting the speed ratio of the driving wheels, thereby alleviating the impact of center-of-gravity shift. However, there is a lack of automated adjustment strategies for abnormal postures in existing technologies, and most rely on fixed programs or manual control, making it difficult to adapt to complex and dynamic wall environments.

[0010] 4. Research status of control algorithms

[0011] The control algorithm is the core for realizing attitude adjustment. Existing research mostly focuses on the proportional-integral-derivative (PID) control algorithm, which processes the data collected by sensors and adjusts the motion parameters of the driving motors. However, traditional PID control has the problem of response lag. Especially when the attitude changes drastically, it is difficult to achieve fast and precise adjustment. In addition, most existing control algorithms only adjust for a single variable and lack the multi-variable collaborative optimization of adsorption force, center of gravity, and drive system.

[0012] Although certain progress has been made in attitude adjustment technology, the following key problems still exist in practical applications:

[0013] 1. Insufficient real-time performance of attitude anomaly detection: Although existing methods can obtain attitude data through inertial sensors, the detection accuracy and real-time performance for abnormal states are limited. Especially in a complex wall environment, sensor noise and data delay can cause attitude anomalies to not be detected in time.

[0014] 2. Lack of flexibility in center of gravity adjustment: Traditional methods mostly rely on fixed center of gravity design and are difficult to cope with the problem of dynamic center of gravity offset, resulting in a decrease in adsorption force or even detachment of the robot during movement.

[0015] 3. Single means of attitude adjustment: Existing technologies mainly correct the attitude by adjusting the speed and direction of the drive system and lack multi-dimensional collaborative adjustment means (such as combining center of gravity optimization and adsorption force optimization).

[0016] 4. Response lag of the control algorithm: The response speed and sensitivity of traditional control algorithms in attitude adjustment are insufficient, making it difficult to achieve precise control in complex environments. Summary of the Invention

[0017] To solve the technical deficiencies of the existing attitude adjustment technology of wall-climbing robots, such as insufficient real-time performance of attitude anomaly detection, lack of flexibility in center of gravity adjustment, and single means of attitude adjustment, the technical solution provided by the present invention is as follows:

[0018] An automatic inspection robot for large pressure vessels, comprising:

[0019] A drive system, including two driving wheels installed on the front and rear central axes of the robot and two driven universal wheels installed at the front and rear ends of the robot;

[0020] An adsorption system, including modularly arranged permanent magnets, which are installed at the bottom of the robot;

[0021] A non-destructive testing module, including an eddy current probe slide;

[0022] A camera swing arm module, arranged at the top of the robot, with a camera installed at the end of the swing arm, for real-time monitoring of the robot environment and optimizing the center of gravity through the angle adjustment of the swing arm;

[0023] An inertial sensor module for real-time monitoring of the attitude information of the robot on the wall surface.

[0024] Furthermore, a preferred embodiment is provided, where the driving wheel is driven by an independent motor and adopts a differential driving mode, and the omnidirectional wheel has an elastic telescopic structure for auxiliary support and steering.

[0025] Furthermore, a preferred embodiment is provided, where the sliding table is a cross rail structure for covering the target detection area.

[0026] Furthermore, a preferred embodiment is provided, where the length and swing angle of the swing arm are adjustable.

[0027] Furthermore, a preferred embodiment includes two eddy current probe sliding tables.

[0028] Based on the same inventive concept, the present invention also provides a method for adjusting the attitude of a large pressure vessel automatic inspection robot, which is used to adjust the attitude of the robot and includes:

[0029] The step of collecting the attitude data of the robot on the wall surface;

[0030] The step of determining whether the inclination angle exceeds the safe range;

[0031] If the abnormal state condition is satisfied, trigger the gravity center optimization and attitude adjustment process:

[0032] The step of obtaining the adjustment angle of the swing arm of the camera according to the gravity center offset and the inclination state parameter;

[0033] The step of obtaining the adjustment parameter of the differential speed of the motor drive according to the real-time inclination angle and the gravity center offset after adjusting the swing arm angle of the camera.

[0034] Based on the same inventive concept, the present invention also provides a device for adjusting the attitude of a large pressure vessel automatic inspection robot, which is used to adjust the attitude of the robot and includes:

[0035] A module for collecting the attitude data of the robot on the wall surface;

[0036] A module for determining whether the inclination angle exceeds the safe range;

[0037] If the abnormal state condition is satisfied, trigger the gravity center optimization and attitude adjustment process:

[0038] A module for obtaining the adjustment angle of the swing arm of the camera according to the gravity center offset and the inclination state parameter;

[0039] A module for obtaining the adjustment parameter of the differential speed of the motor drive according to the real-time inclination angle and the gravity center offset after adjusting the swing arm angle of the camera.

[0040] Based on the same inventive concept, the present invention also provides a computer storage medium for storing a computing program, and when the computer program is read by a computer, the computer executes the method described above.

[0041] Based on the same inventive concept, the present invention also provides a computer, including a processor and a storage medium, and when the processor reads the computer program stored in the storage medium, the computer executes the method described above.

[0042] Based on the same inventive concept, the present invention also provides a computer program product, which is a computer program, and when the computer program is executed, the method described above is implemented.

[0043] Compared with the prior art, the beneficial effects of the technical solution provided by the present invention are as follows:

[0044] By using an inertial sensor to monitor the attitude change in real time, accurate detection of the abnormal attitude of the robot is achieved. Compared with the system in the existing research that only relies on the detection of basic angle changes, this method can quickly capture tilts and offsets in a complex wall environment, greatly improving the real-time performance and accuracy of detection.

[0045] The dynamic adjustment of the camera swing arm is used to optimize the center-of-gravity distribution of the robot. This method makes up for the deficiency of the fixed center-of-gravity design in the existing research, enabling the robot to adjust the center-of-gravity position in real time according to the attitude change, restoring stability in the case of a decrease in the adsorption force, and thus significantly improving the wall adaptation ability.

[0046] By adjusting the motor speed and direction through differential drive, rapid correction of the robot's attitude is effectively achieved. Compared with the traditional fixed-program control, this method combines sensor data and real-time feedback control, can respond more sensitively to abnormal attitudes, and reduces the risk of the robot detaching from the wall.

[0047] Based on a cooperative control algorithm, the linkage optimization of the motor drive and the swing-arm adjustment is realized. Compared with the single-variable control of the traditional PID algorithm, this method shows higher control sensitivity and response speed in multi-variable cooperative optimization, making the robot more flexible and stable in complex paths and dynamic environments.

[0048] Combining the permanent magnet adsorption technology and the center-of-gravity optimization enhances the reliability of the adsorption system. This method overcomes the problem of insufficient adsorption force of the existing electromagnetic adsorption system in the case of power failure, and further improves the safety of the adsorption state through dynamic center-of-gravity adjustment, making the robot more stable during long-term operation.

[0049] It is suitable for application in the attitude adjustment work of wall-climbing robots. Description of the Drawings

[0050] Figure 1 It is the front view of the automatic inspection robot for large pressure vessels;

[0051] Figure 2 It is a schematic diagram of the gear train configuration;

[0052] Figure 3 It is a schematic diagram of the cross slide;

[0053] Figure 4 It is a schematic diagram of the camera mounting; Specific implementation mode

[0054] To make the advantages and beneficial effects of the technical solution provided by the present invention more clearly reflected, the technical solution provided by the present invention will be further described in detail with reference to the accompanying drawings. Specifically:

[0055] Embodiment 1. This embodiment provides an automatic inspection robot for large pressure vessels, including:

[0056] A drive system, including two driving wheels installed on the front and rear central axes of the robot and two driven universal wheels installed at the front and rear ends of the robot;

[0057] An adsorption system, including modularly arranged permanent magnets, which are installed at the bottom of the robot;

[0058] A non-destructive testing module, including an eddy current probe slide;

[0059] A camera swing arm module, which is arranged on the top of the robot, and a camera is installed at the end of the swing arm, used for real-time monitoring of the robot environment and optimizing the center of gravity by adjusting the angle of the swing arm;

[0060] An inertial sensor module, used for real-time monitoring of the attitude information of the robot on the wall surface.

[0061] The driving wheels are driven by independent motors and adopt a differential driving mode. The universal wheels have an elastic telescopic structure, which is used for auxiliary support and steering.

[0062] The slide is a cross rail structure, which is used to cover the target detection area.

[0063] The length and swing angle of the swing arm are adjustable.

[0064] It includes two eddy current probe slides.

[0065] It also provides a method for adjusting the attitude of the automatic inspection robot for large pressure vessels, including:

[0066] The step of collecting the attitude data of the robot on the wall surface;

[0067] The step of judging whether the inclination angle exceeds the safety range;

[0068] If the abnormal state condition is met, trigger the center-of-gravity optimization and attitude adjustment process:

[0069] Steps to obtain the adjustment angle of the camera's swing arm based on the center-of-gravity offset and tilt state parameters;

[0070] Steps to obtain the adjustment parameters of the differential speed of the motor drive based on the real-time tilt angle and center-of-gravity offset after adjusting the angle of the camera's swing arm.

[0071] Embodiment 2. Combining Figures 1-4 To illustrate this embodiment, this embodiment is a further explanation of the technical solution provided in Embodiment 1. Specifically:

[0072] This embodiment provides a wall-climbing robot based on magnetic adsorption technology, which realizes the stable movement and attitude adjustment capabilities of the robot on the wall through the attitude monitoring of inertial sensors, the center-of-gravity adjustment of the camera swing arm, the differential control of the motor drive, and the cooperative control algorithm. The entire solution is implemented according to the following steps:

[0073] Step 1: Attitude data acquisition

[0074] The robot uses inertial sensors installed on the body to collect acceleration and angular velocity data in real time, and obtains the attitude information of the robot on the wall. These data include the current tilt angle, the degree of center-of-gravity offset, and the adsorption force state of the robot, providing basic information for subsequent adjustments. The inertial sensors include a three-axis accelerometer and a gyroscope, and their acquisition frequency should be higher than the response frequency of the robot's movement to ensure data real-time and accuracy. The collected data is preprocessed through built-in algorithms to filter out noise and calculate the attitude angle, and to judge whether the robot is tilted or in an abnormal state.

[0075] Step 2: Tilt state judgment and adsorption force detection

[0076] According to the attitude data collected in Step 1, analyze the angle between the robot and the wall surface through the attitude angle calculation formula, and estimate whether the current adsorption state is normal in combination with the adsorption force formula. Set an adsorption force threshold. When the adsorption force is less than this threshold and the tilt angle exceeds the safe range, the system judges that the robot is in an abnormal state and needs to enter the attitude adjustment stage. The output of this step is the current attitude state (normal or abnormal) of the robot and the center-of-gravity offset parameter.

[0077] Step 3: Dynamic adjustment of the camera swing arm

[0078] According to the tilt state and center-of-gravity offset parameters output in Step 2, the system controls the camera swing arm for dynamic adjustment to optimize the center-of-gravity distribution of the robot. The camera swing arm is driven by a motor, and the center-of-gravity position is adjusted by changing the swing-arm angle. The adjustment range of the swing-arm angle is determined by the design parameters and is usually set between 0° and 90°. During the adjustment process, the required change in the swing-arm angle is calculated through a formula, and the motor actuator precisely drives the swing arm to reach the target position. After the swing arm is adjusted, the center-of-gravity position is updated in real time, and the new center-of-gravity position is used as an input parameter for adsorption force optimization.

[0079] Step 4: Motor differential drive adjustment

[0080] While the camera swing arm is being adjusted, the system adjusts the motor drive through differential control. Based on the tilt state and the new center-of-gravity position parameters determined in Step 2, the target rotational speed for differential adjustment is calculated. If the robot needs to resume straight-line motion, the rotational speeds of the two driving wheels remain the same; if it needs to adjust the motion direction or rotate in place, the difference in the rotational speeds of the two driving wheels is calculated according to a formula. By adjusting the real-time rotational speed of the motor, the robot can quickly regain balance and enter a stable motion state.

[0081] Step 5: Cooperative control algorithm optimization

[0082] To ensure the coordination between Step 3 and Step 4, this embodiment introduces a cooperative control algorithm to comprehensively process the inertial sensor data, swing-arm adjustment parameters, and motor drive parameters. The cooperative control algorithm calculates the optimal swing-arm adjustment angle and motor differential rotational speed based on the attitude angle deviation and center-of-gravity offset, ensuring that the robot can quickly recover its attitude and achieve stable adsorption in a dynamic environment. The algorithm includes control gain parameters used to adjust the control sensitivity and response speed, ensuring that the swing-arm adjustment and motor drive are completed synchronously.

[0083] Step 6: Abnormal state monitoring and stop judgment

[0084] After implementing the above steps, the system monitors the robot's attitude and adsorption state in real time. If the tilt angle fails to return to the safe range or the adsorption force is still less than the set threshold, the system determines that the robot cannot maintain stability and stops all motor drives to prevent further tilting or detachment. After stopping, the system can try to restore the attitude again by adjusting the center-of-gravity position of the swing arm and optimizing the adsorption force.

[0085] The following details need to be noted during implementation:

[0086] Selection and installation of the inertial sensor: The inertial sensor should be selected as a high-precision model (such as with a resolution above 10 bits) to ensure accurate data. The sensor should be installed near the center of gravity of the robot to reduce errors caused by sensor offset.

[0087] Camera Swing Arm Design: The moment of inertia and length of the swing arm should be optimized according to the overall robot design to balance adjustment sensitivity and structural stability. The connection between the swing arm and the fuselage should use low-friction drive bearings to reduce the energy consumption of the control motor.

[0088] Motor Drive System: The differential drive motor must have the ability of rapid response, and its minimum rotational speed change range should be small enough to ensure the smoothness of the robot in the fine-tuning state.

[0089] Implementation of Cooperative Control Algorithm: The algorithm needs to combine the dynamic adjustment of attitude changes and center-of-gravity parameters, and optimize through loop feedback to ensure control accuracy. At the same time, introduce PID control as the basic algorithm module, and superimpose an adaptive gain adjustment strategy on it to improve the performance in complex scenarios.

[0090] Among them, the shape and structure of the robot

[0091] The wall-climbing robot is in the shape of a cuboid as a whole. It has a compact design and a smooth appearance, suitable for stable movement on vertical or inclined walls, and at the same time has good wind resistance and high reliability. The robot is mainly composed of the following components:

[0092] 1. Main Structure

[0093] The robot body is a frame structure, made of lightweight and high-strength materials (such as aluminum alloy or carbon fiber composite materials), ensuring that the robot reduces weight as much as possible while maintaining rigidity.

[0094] The lower part of the main body frame is the installation area for the drive system, the middle part is the installation area for the control system and detection equipment, and the upper part is the installation area for additional modules (such as camera swing arms and sensors).

[0095] 2. Drive System

[0096] The robot adopts a moving method with a four-wheel diamond distribution, in which two driving wheels and two universal wheels together form a diamond structure:

[0097] Two driving wheels: Installed on the front and rear central axes of the robot body, respectively driven by two independent motors, responsible for the main movement and attitude adjustment of the robot.

[0098] Two universal wheels: Installed at the front and rear ends of the robot body respectively, with elastic telescopic functions, used for support and auxiliary steering.

[0099] The outer surface of the driving wheels is coated with a high-friction material to enhance its grip on the wall.

[0100] 3. Adsorption System

[0101] The adsorption system is based on permanent magnet adsorption technology. Multiple high-strength permanent magnets are installed at the bottom of the robot to ensure the adsorption force of the robot on the metal wall surface.

[0102] The magnets are evenly distributed on the bottom frame through modular design, and there is a certain elastic adjustment device between the magnets and the bottom frame, which can adapt to the slight deformation or unevenness of different walls.

[0103] 4. Non-destructive testing module

[0104] Two eddy current probe slides are installed on both sides of the bottom frame of the robot. The slides are connected to the fuselage through guide rails and can perform precise displacement along the direction of the guide rails for non-destructive testing tasks.

[0105] The slide adopts a cross slide rail structure and can move left and right or be finely adjusted up and down to ensure that the detection probe can cover the target area.

[0106] 5. Camera swing arm module

[0107] A rotatable camera swing arm is installed on the top of the robot. The swing arm is driven by a motor and changes the center of gravity position of the robot by swinging to optimize the adsorption state.

[0108] The swing arm is made of lightweight and high-strength materials, and its length and swing angle are adjustable. The swing range is usually from 0° to 90°.

[0109] A high-definition camera is installed at the end of the swing arm for real-time monitoring of the environment around the robot to assist in detection tasks or positioning.

[0110] 6. Control and sensing module

[0111] An inertial sensor module is integrated inside the robot, including a three-axis accelerometer and a gyroscope, which is used to monitor the attitude information of the robot in real time, such as tilt angle and acceleration changes.

[0112] The control system is located in the middle of the robot and includes an embedded processor and a cooperative control algorithm module for comprehensively processing sensor data and executing attitude adjustment instructions.

[0113] The robot is also equipped with a communication module (such as Wi-Fi or 5G module) for data interaction with the remote operation terminal.

[0114] 7. Power supply system

[0115] The robot is built-in with a rechargeable battery module, which is installed at the bottom of the main frame to lower the center of gravity. The battery capacity is designed to support the robot to work for a long time, and it also has overload protection and low battery alarm functions.

[0116] 8. Shell and protection design

[0117] The robot housing adopts an integrated streamline design and its surface is covered with wear-resistant and anti-corrosive materials, enabling it to operate normally in harsh environments (such as high humidity or salt spray conditions).

[0118] The housing has good sealing performance, with an IP65 protection level, which can effectively prevent dust, rainwater or other impurities from entering the internal system.

[0119] Embodiment 3: In this embodiment, through specific examples, the above-provided technical solution will be further described in detail. Specifically:

[0120] 1. Algorithm design

[0121] 1.1 Attitude monitoring and anomaly detection algorithm

[0122] The inertial sensors installed on the robot can obtain the acceleration and angular velocity data of the robot on the wall surface. Based on these data, in this embodiment, the following formulas can be used to calculate the tilt angle (i.e., attitude) of the robot and judge the adsorption state.

[0123] Attitude angle calculation formula: Let the acceleration measured by the sensor be a x , a y , a z (acceleration components in three directions), in this embodiment, the attitude angle of the robot can be calculated by the following formula:

[0124]

[0125] Among them, θ represents the tilt angle of the robot. By continuously monitoring the angle change, in this embodiment, it can be judged whether the robot is in a tilted state.

[0126] Adsorption force judgment: According to the adsorption force F ads between the robot and the wall surface, in this embodiment, a threshold F ads，min is defined. If F ads < F ads，min , it is considered that the adsorption force is insufficient, which may cause detachment. The adsorption force F ads can be estimated by the following formula:

[0127] F ads = k·A·B·cos(θ)

[0128] Among them, k is the magnetic constant, A is the adsorption area, B is the magnetic field strength, and θ is the tilt angle of the robot.

[0129] 1.2 Center of gravity optimization and attitude adjustment algorithm

[0130] According to the sensor data, the system will calculate the current center of gravity G x , G y , Gz and determine whether it deviates from the normal area. If the center of gravity G of the robot deviates greatly, it is necessary to optimize the center of gravity position by adjusting the posture of the camera mount. Assuming the angle of the camera mount is φ, by adjusting the angle of the camera mount, the horizontal position of the robot's center of gravity can be changed, thereby affecting the adsorption state.

[0131] Center of gravity optimization formula:

[0132] G′ x = G x + Δx(φ)

[0133] G′ y = G y + Δy(φ)

[0134] Where, Δx(φ) and Δy(φ) represent the center of gravity offset that can be achieved by adjusting the camera mount angle φ.

[0135] 1.3 Motor drive and speed adjustment algorithm

[0136] When the posture is abnormal, the system changes the motion state of the robot by adjusting the motor speed v to avoid continuous tilting or loss of adsorption force. The adjustment of the motor speed can be achieved through the following formula:

[0137] Motor speed adjustment formula:

[0138]

[0139] Where, v 0 is the initial speed, Δθ is the deviation between the current posture and the standard posture, and θ max is the maximum allowable tilting angle.

[0140] Stop motion judgment: If it is detected that the robot posture is abnormal and adjusting the motor speed cannot restore stability, the system will choose to stop the robot motion. The judgment condition is:

[0141] Δθ > θ limit and F ads < F ads,min

[0142] If the above conditions are met, the system will immediately stop the motor drive and wait for the adsorption force to recover.

[0143] 2. Camera mount and arm design

[0144] In order to achieve the center of gravity optimization and posture adjustment of the robot, this embodiment needs to design reasonable physical parameters for the camera mount to ensure that it can be flexibly adjusted in a changing environment.

[0145] 2.1 Camera mount design parameters

[0146] The design of the camera ornament depends on the length L of its swing arm, the weight m of the ornament, and the connection points with other parts of the robot. To achieve the purpose of adjusting the center of gravity, the movement of the camera ornament should have sufficient flexibility and stability.

[0147] Swing arm length: Set the length of the swing arm of the camera ornament as L. This length determines the influence that the camera ornament can exert on the center of gravity of the robot. A longer swing arm can provide a larger space for adjusting the center of gravity.

[0148] Ornament weight: Set the mass m of the ornament. The relationship between mass and moment of inertia is:

[0149]

[0150] where I is the moment of inertia of the swing arm, which determines the power required for the swing arm to rotate and the response speed.

[0151] 2.2 Ornament angle adjustment mechanism

[0152] The adjustment of the camera ornament is driven by a motor, and the fine adjustment of the center of gravity position is achieved by changing the angle of the swing arm. Assume that the control angle range of the motor is φ min to φ max . The motor can control the rotation angle of the swing arm by adjusting the current.

[0153] Angle adjustment formula:

[0154] φ = φ 0 + Δφ

[0155] where φ 0 is the initial angle, and Δφ is the angle change obtained by controlling the motor adjustment.

[0156] 2.3 Cooperative control between the ornament and the drive system

[0157] To achieve the best adsorption state, cooperative control is required between the adjustment of the ornament and the motor drive system. According to the posture and center of gravity changes of the robot, the control signals of the motor and the ornament should change synchronously to achieve the optimal posture adjustment effect.

[0158] Cooperative control algorithm:

[0159]

[0160] where v is the motor speed, φ is the ornament angle, Δθ is the posture angle deviation, ΔG is the center of gravity offset, K 1 , K 2 , K 3 , K 4 are control gain coefficients, which determine the response sensitivity of the motor and ornament adjustments.

[0161] In this embodiment, by introducing the data and algorithms of inertial sensors, combining the attitude adjustment, center-of-gravity optimization of the camera mount, and dynamic control of motor drive, a comprehensive adsorption state stability control system is achieved. It can monitor the robot's attitude in real time, adjust the center of gravity, optimize the adsorption force, and optimize the robot's motion state through precise control algorithms.

[0162] Compared with the prior art, the innovation points of this embodiment are as follows:

[0163] Real-time detection of abnormal attitude: By combining inertial sensors and algorithms, the adsorption state of the robot is monitored and judged in real time.

[0164] Dynamic adjustment of the center of gravity: Through the attitude adjustment and center-of-gravity optimization of the camera mount, more efficient control of the adsorption state is achieved.

[0165] Cooperative work of motor drive and attitude control: By adjusting the motor speed and the angle of the camera mount, the best adsorption state is achieved to prevent the robot from falling off.

[0166] The combination of these technologies greatly improves the stability and flexibility of the robot in complex environments, effectively solving the deficiencies in the prior art.

[0167] In the specific implementation work:

[0168] In this embodiment, a wall-climbing robot based on magnetic adsorption technology is designed. When the robot adsorbs on the wall and starts to move, if it encounters an unstable working state, the robot needs to adjust its attitude, center of gravity, and driving mode in real time to avoid falling off. In this embodiment, the robot's attitude is monitored by an inertial sensor, the center of gravity is optimized by adjusting the angle of the camera swing arm, and the motion state is adjusted by motor control.

[0169] 1. Detection of abnormal states of the robot

[0170] In this embodiment, the robot is equipped with inertial sensors (such as a three-axis accelerometer and a gyroscope). These sensors obtain the robot's attitude data in real time, including acceleration and angular velocity.

[0171] Sensor data: The inclination angle θ of the robot: The measured acceleration a x , a y , a z Used to calculate the inclination angle θ:

[0172]

[0173] Adsorption force F ads : Estimate the adsorption force through acceleration and magnetic constant k:

[0174] F ads = k·A·B·cos(θ)

[0175] If F ads < F ads，min , the adsorption force of the robot is insufficient and it may fall off.

[0176] Assume that the robot detects θ = 15° at this time (the robot has a slight tilt) and the adsorption force F ads is less than the threshold F ads，min . The system determines it as an abnormal state and must be adjusted.

[0177] 2. Center of Gravity Optimization and Camera Swing Arm Adjustment

[0178] The robot system needs to optimize the center of gravity by adjusting the angle of the camera swing arm to ensure the recovery of the adsorption force and avoid tilting. Assume the design parameters of the camera swing arm are as follows:

[0179] The length of the swing arm L = 0.3m; the mass of the swing piece m = 0.2kg

[0180] The moment of inertia of the swing arm:

[0181] By adjusting the angle φ of the camera swing arm, the horizontal position of the robot's center of gravity can be changed, thereby affecting the adsorption state. Set the control angle range of the swing arm to φ min = -15° to φ max = 15°.

[0182] Assume that the current center of gravity G x and G y have a large offset and the center of gravity position needs to be optimized by adjusting the swing arm angle. The specific adjustment calculation is as follows:

[0183] Center of gravity optimization formula:

[0184] G′ x = G x + Δx(φ), G′ y = G y + Δy(φ)

[0185] Set the target center of gravity position adjustment amounts Δx(φ) = -0.05m and Δy(φ) = -0.03m. Then, optimize the center of gravity by adjusting the swing arm angle φ to keep the robot stable.

[0186] During this process, the robot adjusts the swing arm angle by controlling the motor current for real-time fine-tuning.

[0187] 3. Motor Drive and Speed Adjustment

[0188] By adjusting the swing arm angle in real time to optimize the center of gravity, the robot still needs to further adjust the motor speed vv to restore the stable state.

[0189] Motor speed adjustment formula:

[0190]

[0191] Assume the initial speed v 0 = 0.5 m / s, the current attitude deviation Δθ = 15° - 5° = 10°, the maximum tilt angle θ max = 15°, then the motor speed is adjusted to:

[0192]

[0193] By reducing the speed, the robot slows down its movement speed, thereby reducing the tilting speed and helping to restore the adsorption force.

[0194] If abnormal attitude is continuously detected and the recovery of the adsorption force is still not obvious, the system determines that the robot needs to stop moving to avoid further tilting.

[0195] Stop movement judgment: If the condition Δθ > 10°, F ads < F ads，min , the system immediately stops the motor drive and waits for the adsorption force to recover.

[0196] 4. Cooperative control and feedback

[0197] Through the cooperative control algorithm, the adjustment of the motor and the swing arm angle needs to change synchronously to ensure the best attitude adjustment effect.

[0198] Cooperative control algorithm:

[0199]

[0200] Assume the control gain coefficients are K 1 = 1.2, K 2 = 0.8, K 3 = 1.0, K 4 = 1.5, calculate the adjustment result, and through synchronous adjustment of the motor speed and the swing arm angle, ensure that the robot finally restores stability.

[0201] The above further describes the technical solutions provided by the present invention through several specific embodiments to highlight the advantages and beneficial effects of the technical solutions provided by the present invention. However, the above-mentioned several specific embodiments are not used as limitations to the present invention. Any reasonable modifications, improvements, combinations of embodiments, and equivalent replacements based on the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. Large pressure vessel automatic inspection robot, characterized by: include: The driving system includes two driving wheels installed on the front and rear center axes of the robot and two driven universal wheels installed on the front and rear ends of the robot; An adsorption system, comprising a modularly arranged permanent magnet, the permanent magnet being mounted on the bottom of the robot; Nondestructive testing module, including eddy current probe slide; The camera swing arm module is set on the top of the robot, and a camera is installed at the end of the swing arm to monitor the robot environment in real time and optimize the center of gravity by adjusting the angle of the swing arm; The inertial sensor module is used to monitor the robot's posture information on the wall in real time.

2. The large pressure vessel automatic inspection robot according to claim 1 is characterized in that: The driving wheel is driven by an independent motor in a differential driving mode, and the universal wheel has an elastic telescopic structure for auxiliary support and steering.

3. The large pressure vessel automatic inspection robot according to claim 1 is characterized in that: The slide table is a cross slide rail structure, which is used to cover the target detection area.

4. The large pressure vessel automatic inspection robot according to claim 1 is characterized in that: The length and swing angle of the swing arm are adjustable.

5. The large pressure vessel automatic inspection robot according to claim 1 is characterized in that: Includes two eddy current probe slides.

6. A method for adjusting the posture of a large pressure vessel automatic inspection robot, characterized in that: The method is used to adjust the posture of the robot according to claim 1, comprising: The step of collecting posture data of the robot on the wall; Steps for determining whether the tilt angle exceeds the safe range; If the abnormal state conditions are met, the center of gravity optimization and posture adjustment process is triggered: The step of obtaining the adjustment angle of the swing arm of the camera according to the center of gravity offset and the tilt state parameter; The step of obtaining the adjustment parameters of the differential speed driven by the motor according to the real-time tilt angle and the center of gravity offset after adjusting the swing arm angle of the camera.

7. Large pressure vessel automatic inspection robot posture adjustment device, characterized in that: The device is used to adjust the posture of the robot according to claim 1, comprising: A module for collecting the robot's posture data on the wall; A module that determines whether the tilt angle exceeds the safe range; If the abnormal state conditions are met, the center of gravity optimization and posture adjustment process is triggered: A module for obtaining the adjustment angle of the camera's swing arm according to the center of gravity offset and the tilt state parameters; A module for obtaining adjustment parameters of the differential speed of the motor drive according to the real-time tilt angle and the center of gravity offset after adjusting the swing arm angle of the camera.

8. A computer storage medium for storing a computing program, characterized in that: When the computer program is read by a computer, the computer executes the method according to claim 6.

9. A computer, comprising a processor and a storage medium, characterized in that: When the processor reads the computer program stored in the storage medium, the computer executes the method of claim 6 .

10. A computer program product, being a computer program, characterized in that When the computer program is executed, the method according to claim 6 is implemented.

Images