Modular pipeline detection robot suitable for pressurized water filling pipe network and detection control method

Abstract

This application belongs to the field of robotics technology, providing a modular pipeline inspection robot and its control method suitable for pressurized water-filled pipe networks. It includes a head-mounted vision acquisition mechanism, a magnetic flux leakage (MF) detection mechanism, and a propulsion mechanism. The head-mounted vision acquisition mechanism acquires images of the inner surface of the pipe and is rotatably and sealingly connected to the MF detection mechanism. The MF detection mechanism includes a folding mechanism and a MF detection sensor. The folding mechanism is configured to be driven to control the MF detection sensor to be in contact with or away from the inner surface of the pipe. The MF detection sensor is used to acquire pipeline defect data. The MF detection mechanism is rotatably and sealingly connected to the tail-mounted main propeller. The control motherboard adjusts the thrust of each vertical propeller in real time through closed-loop control, controlling the robot to travel along the centerline of the pipe. This robot has a compact structure, flexible movement, can adapt to water-filled and certain pressure environments, and integrates multiple detection methods, improving the reliability and applicability of pipeline inspection.

Description

Technical Field

[0001] This invention belongs to the field of robotics technology and relates to a pipeline robot, specifically a modular pipeline inspection robot and inspection control method suitable for pressurized water-filled pipe networks. Background Technology

[0002] In modern urban infrastructure and industrial systems, heating networks, water supply and drainage pipelines, and petrochemical pipelines constitute vital material transportation networks. These pipelines are typically characterized by deep burial, wide distribution, and complex operating environments, and often operate in a long-term closed state. Under the combined effects of high temperature, high pressure, water erosion, and media corrosion, the inner walls of these pipelines are prone to corrosion, scaling, cracks, and perforations. These defects are difficult to detect in a timely manner using external methods. Once a leak or rupture occurs, it not only wastes energy but may also lead to safety accidents and even environmental pollution. Therefore, there is an urgent need for a technology that can efficiently inspect the interior of pipelines without stopping operation.

[0003] Currently, various technical solutions exist for pipeline internal inspection. For example, while manual excavation is intuitive, it suffers from high costs, low efficiency, and significant damage. Fixed sensor monitoring systems can only achieve long-term monitoring of localized areas, making it difficult to cover long-distance pipelines. Pipeline inspection robots, due to their ability to enter pipelines and perform inspection tasks, are gradually becoming a research hotspot. However, existing pipeline inspection robots still have many shortcomings in practical applications:

[0004] First, their motion adaptability is poor. Most existing pipeline robots adopt wheeled, tracked, or wall-pressing structures, and their movement is highly dependent on the inner diameter and structure of the pipeline. When facing complex structures such as bends, reducing pipe diameters, valves, and T-shaped branches, they are prone to jamming, slipping, or being unable to pass, making it difficult to meet the inspection needs of complex pipeline network environments.

[0005] Secondly, they have high requirements for the working environment. Some inspection robots are only suitable for dry or semi-liquid environments. For heating pipes filled with water or under certain pressure, their sealing performance and pressure resistance are insufficient, making it difficult to achieve stable operation and limiting their application range.

[0006] Secondly, the detection methods are relatively limited. Existing equipment mostly uses a single detection method, such as relying solely on visual inspection or a single non-destructive testing method. Under complex working conditions, these methods are easily affected by factors such as lighting, water quality, and sediment, resulting in insufficient detection accuracy and reliability, and making it difficult to comprehensively identify internal defects in pipelines.

[0007] Furthermore, the control methods lack flexibility. Some robots rely on preset paths or simple control strategies, lacking the ability to actively adjust to multiple degrees of freedom. This makes it difficult to achieve posture adjustment and stable propulsion in complex spaces, affecting detection efficiency. Summary of the Invention

[0008] To overcome the shortcomings of existing technologies, this invention provides a modular pipeline inspection robot and inspection control method suitable for pressurized water-filled pipe networks. The robot has a compact structure, flexible movement, and can adapt to water-filled and certain pressure environments. It also integrates multiple inspection methods, thereby improving the reliability and applicability of pipeline inspection.

[0009] A modular pipeline inspection robot suitable for pressurized water-filled pipe networks includes:

[0010] The propulsion mechanism includes a vertical thruster that controls the robot to float horizontally in the water and a tail main thruster that provides navigation;

[0011] The head vision acquisition mechanism is used to acquire images of the inner surface of the pipe and is rotated and sealed to connect with the magnetic flux leakage detection mechanism to enable the robot to turn inside the pipe.

[0012] The magnetic flux leakage detection mechanism includes a folding mechanism and a magnetic flux leakage detection sensor. The folding mechanism is configured to be driven to control the magnetic flux leakage detection sensor to be in contact with or away from the inner surface of the pipe. The magnetic flux leakage detection sensor is used to collect pipe defect data. The magnetic flux leakage detection mechanism is rotatably and sealedly connected to the tail main thruster to enable the robot to turn inside the pipe.

[0013] IMU sensors are respectively arranged in the head vision acquisition mechanism, the magnetic flux leakage detection mechanism, and the propulsion mechanism to collect the robot's posture data in real time and feed the data back to the enclosed control motherboard. The control motherboard adjusts the thrust of each vertical thruster in real time through closed-loop control to control the robot to travel along the center line of the pipeline.

[0014] Furthermore, the folding mechanism is a scissor-type lifting mechanism, and the opening and closing motion is controlled by a linear motion mechanism to realize the radial linear movement of the magnetic flux leakage detection sensor.

[0015] Furthermore, the head vision acquisition mechanism is equipped with a vertical thruster, and the robot's tail is equipped with a vertical thruster. The robot's position can be controlled by controlling the vertical thruster and the tail main thruster.

[0016] Furthermore, the head vision acquisition mechanism is connected to the magnetic flux leakage detection mechanism through the steering mechanism, and the robot can smoothly navigate curves by controlling the steering mechanism.

[0017] Furthermore, the vertical thruster at the rear is connected to the magnetic flux leakage detection mechanism via a steering mechanism, and smooth cornering is achieved by controlling the steering mechanism.

[0018] Furthermore, the steering mechanism consists of two servo motors connected in series. By controlling the coordinated movement of the two servo motors, the robot's posture can be adjusted to adapt to the curvature of the pipe bend.

[0019] Furthermore, the linear motion mechanism is a motor-driven lead screw and nut pair mechanism. The motor is mounted on a fixed plate, and the lead screw is rotatably mounted on the movable plate of the folding mechanism. The rotation of the lead screw drives the movable plate to move linearly, thereby opening and closing the folding mechanism.

[0020] A pipeline inspection method, based on the modular pipeline inspection robot suitable for pressurized water-filled pipe networks, includes the following steps:

[0021] S1. System startup: The host computer connects to the sensor motherboard via optical fiber, initializes, and performs self-tests on each module.

[0022] S2, Attitude calibration: Vertical and horizontal thrusters are activated, IMU sensors provide attitude feedback, and the robot is adjusted to the centerline of the pipeline.

[0023] S3. Detection preparation: the leakage magnetic mechanism opens, and the sensor is pressed tightly against the inner wall of the pipe.

[0024] S4, linear propulsion, the main thruster runs at a constant speed, and the vertical thruster remains centered;

[0025] S5 features dual-mode detection: a camera and lighting lamp acquire images, while a magnetic flux leakage sensor acquires defect signals.

[0026] S6. Data feedback: The detection data and attitude data are transmitted back to the host computer via optical fiber. If the monitoring shows no bends, return to step S4.

[0027] S7. Curve detection: The host computer determines whether there is a curve ahead based on the collected images.

[0028] S8. Preparing for a curve: If a curve is detected, reduce the speed of the main thruster.

[0029] S9. Head turning: The first section of the turning mechanism moves, causing the head vision acquisition mechanism to deflect and align with the curve.

[0030] S10, rear-end coordinated steering, the second steering mechanism works together to adjust the rear attitude to adapt to the curve;

[0031] S11, Cornering thrust compensation, controls the vertical thruster to compensate for thrust and prevents it from sticking to the wall or getting stuck;

[0032] S12. Cornering recovery: Control the steering mechanism to the straight position, restore the straight detection mode, and return to step S4;

[0033] S13. Inspection complete. The robot exits the pipeline, completing the inspection.

[0034] Furthermore, the movements of the steering mechanism, vertical thruster, horizontal thruster, magnetic flux leakage sensor, and head vision acquisition mechanism are all controlled by commands issued by the Raspberry Pi 4B, ensuring coordinated and consistent movements of each mechanism. The IMU attitude sensor, magnetic flux leakage sensor, and camera collect data in real time and feed it back to the Raspberry Pi 4B. The Raspberry Pi 4B adjusts the mechanism's movements through algorithms, forming a closed-loop control of commands, actions, sensing, and corrections. The Raspberry Pi 4B communicates with the host computer via fiber optic cable to achieve remote control and monitoring.

[0035] The advantages of this application compared to the prior art are:

[0036] 1. The entire robot is completely sealed and has the pressure resistance to a depth of 10 meters underwater. It can adapt to working in pipelines with a certain pressure, avoiding losses such as work stoppages and production shutdowns caused by testing.

[0037] 2. Using at least two methods, such as visual inspection and magnetic flux leakage inspection, for pipeline inspection can identify the vast majority of pipeline damage problems.

[0038] 3. The robot configuration uses a steering mechanism as the active joint, enabling it to pass through narrow environments such as valves and T-shaped bends, and adapt to different pipe inner diameters and bend curvatures.

[0039] 4. By increasing the number of detection modules, the detection range can be expanded and the detection coverage improved; by adding a steering mechanism module, the robot's posture adjustment accuracy and motion flexibility in complex pipeline environments can be enhanced, thereby significantly improving its adaptability to bends, reducers, and branch pipes. This modular structural design improves the system's versatility and scalability. Attached Figure Description

[0040] Figure 1 This is a three-dimensional structural diagram of the pipeline inspection robot of this application;

[0041] Figure 2 This is a partial schematic diagram of the internal structure of the pipeline inspection robot of this application;

[0042] Figure 3 This is a top view of the pipeline inspection robot of this application;

[0043] Figure 4 For along Figure 3 Sectional view of line AA in the middle;

[0044] Figure 5 For along Figure 3 Sectional view of the middle BB line;

[0045] Figure 6 A schematic diagram of the unfolding mechanism;

[0046] Figure 7 This is an exploded view of the pipeline inspection robot of this application;

[0047] Figure 8 This is a timing flowchart for a robot inspecting a pipeline.

[0048] In the diagram: 1. Head vision acquisition mechanism; 11. Housing; 12. Camera; 13. Lighting lamp; 14. Waterproof sealing section;

[0049] 2. Magnetic leakage detection mechanism; 21. Folding mechanism; 22. Magnetic leakage detection sensor; 23. Linear motion mechanism; 24. Motor; 25. Cylindrical housing;

[0050] 3. First steering mechanism; 34. Servo motor; 35. Bellows;

[0051] 4. Second steering mechanism;

[0052] 5. Propulsion mechanism; 51. Vertical thruster; 52. Tail main thruster;

[0053] 6. Control motherboard. Detailed Implementation

[0054] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. Unless otherwise stated, the technical or scientific terms used in this application have the ordinary meaning as understood by those skilled in the art.

[0055] Example 1, Reference Figure 1 The pipeline inspection robot of this embodiment can perform internal inspections when the underground pipeline network is filled with water. It includes a head vision acquisition mechanism 1, a magnetic flux leakage detection mechanism 2, a first steering mechanism 3, a second steering mechanism 4, and a propulsion mechanism 5. The whole body is made of polyoxymethylene plastic, and the internal support material is 6061-T6. The propulsion mechanism 5 includes a vertical thruster 51 that controls the robot to float horizontally in the water and a tail main thruster 52 that provides navigation.

[0056] Two vertical thrusters 51 are located in the middle of the head vision acquisition mechanism. The two vertical thrusters 51 are arranged on the left and right sides of the head vision acquisition mechanism 1. The control line is connected to the rear section through the cabin screw. The tail main thruster 52 is located at the tail of the robot. For the tail of the robot, the two vertical thrusters 51 are symmetrically arranged on the left and right sides. The control motherboard 6 and the power supply that provides power to the entire robot are placed in the sealed cavity at the tail. The tail main thruster 52 provides thrust for the entire robot in the forward direction. It is connected to the host computer through the optical fiber of the cabin screw, and the detection results can be observed on the host computer in real time.

[0057] Two vertical thrusters 52 are positioned at the rear of the robot, and four vertical thrusters 51 ensure that the robot does not rub against the upper or lower walls of the pipe when moving forward in the water, maintaining the balance of the working center. The robot's position is controlled by horizontally arranging the vertical thrusters 51 and the main tail thruster 52. The first steering mechanism 3 and the second steering mechanism 4 form a biomimetic posture, ensuring that the robot as a whole can adapt to the curvature of the curve, enabling the robot to turn at the bends in the pipe.

[0058] For example, both the vertical thruster and the main thruster are propeller thrusters.

[0059] The head-mounted visual acquisition mechanism 1 is a permeable section, and all components are individually waterproofed. The control and power lines of the device are connected to the rear-end sealed waterproof section 14 through the sealed waterproof section 14. Exemplarily, the head-mounted visual acquisition mechanism 1 includes a housing 11, a camera 12, and lighting lamps 13. The camera 12 and the two lighting lamps 13 are housed in the housing 11, and each is individually waterproofed before being fixed to the housing 11. The robot is equipped with two lighting lamps and a forward-facing camera for visual navigation and detection. The camera 12 acquires images of the inner surface of the pipe.

[0060] The head vision acquisition mechanism 1 is rotatably and sealedly connected to the magnetic flux leakage detection mechanism 2 through the first steering mechanism 3. The first steering mechanism 3 enables the robot to turn smoothly in the pipeline without interrupting the detection.

[0061] The magnetic flux leakage detection mechanism 2 includes a folding mechanism 21 and a magnetic flux leakage detection sensor 22. The folding mechanism 21 is configured to be driven to control the magnetic flux leakage detection sensor 22 to be in contact with or away from the inner surface of the pipe. The magnetic flux leakage detection sensor 22 is used to collect pipe defect data. The magnetic flux leakage detection mechanism 2 is rotatably and sealedly connected to the tail main thruster 52 through the second steering mechanism 4. By controlling the second steering mechanism 4, the robot can turn smoothly in the pipe without interrupting the detection.

[0062] The first steering mechanism 3 and the second steering mechanism 4 have the same structure.

[0063] Taking the first steering mechanism 3 as an example: The steering mechanism consists of two servo motors 34 connected in series. By controlling the coordinated movement of the two servo motors 34, the robot's posture is adjusted to adapt to the curvature of the pipe bend. The output shafts of the two servo motors 34 are arranged orthogonally, and the output swing range of each servo motor is ±90°. The movement of one servo motor 34 causes the head vision acquisition mechanism 1 to deflect, and the movement of the other servo motor 34 causes the leakage magnetic field detection mechanism 2 to deflect. Taking the second steering mechanism 4 as an example: the movement of one servo motor 34 causes the leakage magnetic field detection mechanism 2 to deflect, and the movement of the other servo motor 34 causes the tail main thruster 52 to deflect, so that the front and rear ends of the robot form a serpentine bionic posture, ensuring that the robot as a whole can adapt to the curvature of the bend.

[0064] To ensure stable, reliable, and safe operation, the first steering mechanism 3 and the second steering mechanism 4 are externally encased in corrugated pipes 35 as waterproof shells. The corrugated pipes 35 are corrugated pipes with a certain pressure-bearing capacity. The external sealing connection between the steering mechanism and the head vision acquisition mechanism 1 involves the corrugated pipe 35 pressing against the edge of the sealed waterproof section 14, which has grooves and sealing rings. A clamp is used on the outer layer to fix the connection between the two parts and prevent them from falling off. O-rings and compression rings are used for sealing at both ends. This sealing method provides strong sealing performance and pressure resistance, enabling stable operation and avoiding losses such as downtime due to inspections, while also ensuring the robot's application range.

[0065] The bellows 35 is filled with hydraulic oil to prevent excessive deformation caused by pressure imbalance between the inside and outside. Similarly, the servo-related wiring harness is connected to the control mainboard 6 at the stern via hull bolts. During cornering, the bellows 43 outside the steering mechanism deforms synchronously with the servo's deflection. The control mainboard monitors the pressure data inside the pipe (indirectly through IMU attitude change feedback) to ensure the hydraulic oil pressure balance inside the bellows 35 and prevent seal failure.

[0066] In order to enable the camera 12 and the magnetic flux leakage detection sensor 22 to detect corrosion, cracks and other damage to the pipeline from different angles, the folding mechanism used in this embodiment is a scissor-type lifting mechanism, and the opening and closing movement is controlled by the linear motion mechanism 23 to realize the radial linear movement of the magnetic flux leakage detection sensor 22.

[0067] The two ends of the upper boom of the scissor lift mechanism are rotatably connected to the bottom surface of the magnetic bridge of the magnetic leakage detection sensor 22, and the two ends of the lower boom are rotatably connected to the chassis surface. The chassis is divided into a fixed plate and a movable plate. The magnetic bridge is lifted and lowered by unfolding and folding the cross-connected connecting rods, thereby enabling the guide wheel on the magnetic leakage detection sensor 22 to be in contact with or away from the inner surface of the pipe.

[0068] The unfolding and folding of the cross-connected links are driven by a linear motion mechanism 23 to adapt to different pipe inner diameters. For example, the linear motion mechanism 23 is a mechanism in which a motor 24 drives a lead screw and nut pair. The motor 24 is a waterproof motor and is installed on the fixed plate 26. The lead screw is rotatably set on the movable plate 27 of the scissor lift mechanism. The movable plate 27 is arranged inside the cylindrical housing 25. The rotation of the lead screw drives the movable plate 27 to move linearly, so that the scissor lift mechanism unfolds and folds.

[0069] To ensure that the cross-connected links can be unfolded and folded, a hollow cylindrical shell 25 is provided on the outside of the unfolding mechanism. The surface of the cylindrical shell 25 has a channel 251 that allows the cross-connected links to pass through. The two ends of the cylindrical shell 25 are sealed with O-rings and compression rings and connected to the bellows 35, so that the robot is fully sealed and has the ability to work in a certain pressure pipeline.

[0070] Optionally, the strong magnet on the magnetic bridge of the magnetic flux leakage detection sensor 22 can be removed, and the Hall element on the magnetic bridge can be replaced with an electromagnetic ultrasonic sensor to realize pipeline defect detection based on electromagnetic ultrasonic longitudinal guided waves. Multiple annular magnets arranged coaxially with the pipeline are set up to generate a radial static magnetic field on the pipeline surface. A solenoid coil is coaxially sleeved on both sides of each annular magnet array to generate circumferential eddy currents in the pipeline to be inspected. Under the combined action of the circumferential eddy currents and the radial static magnetic field, longitudinal modal guided waves are excited. When these waves encounter a defect, they are reflected, and the reflected echo causes a change in the induced voltage of the sensing coil, thereby determining whether a defect exists in the pipeline.

[0071] IMU sensors are deployed in the head vision acquisition mechanism, magnetic flux leakage detection mechanism, and propulsion mechanism to collect the robot's posture data in real time and feed the data back to the enclosed control motherboard. The control motherboard adjusts the thrust of each vertical thruster in real time through closed-loop control, controlling the robot to travel along the centerline of the pipeline. A Raspberry Pi 4B serves as the control motherboard in the sealed cavity at the robot's tail, and also carries an IMU to read posture and velocity data. An onboard optical transceiver converts fiber optic signals into electrical signals for reading control signals and transmitting sensor data.

[0072] Example 2: This example, based on the pipeline inspection robot of Example 1, provides a pipeline inspection method, which includes the following steps:

[0073] S1. System startup: The host computer connects to the control motherboard 6 via fiber optic cable, initializes, and performs self-tests on each module.

[0074] S2, Attitude calibration: The vertical thruster and tail main thruster are activated, the IMU sensor provides attitude feedback, and the robot is adjusted to the centerline of the pipeline.

[0075] S3. Inspection preparation: The unfolding mechanism opens, and the magnetic flux leakage detection sensor 22 is pressed tightly against the inner wall of the pipe.

[0076] S4, straight-line propulsion, the tail main thruster 51 runs at a constant speed, and the vertical thruster 51 remains centered;

[0077] S5, dual-mode detection: camera 12 and illumination lamp 13 acquire images, and magnetic flux leakage detection sensor 22 acquires defect signals;

[0078] S6. Data feedback: The detection data and attitude data are transmitted back to the host computer via optical fiber. If the monitoring shows no bends, return to step S4.

[0079] S7. Curve detection: The host computer determines whether there is a curve ahead based on the collected images.

[0080] S8. Preparing for a curve: If a curve is detected, reduce the speed of the main thruster.

[0081] S9. Head turning: The first section of the turning mechanism 3 moves, causing the head vision acquisition mechanism 1 to deflect and align with the curve.

[0082] S10, rear-end coordinated steering, the second steering mechanism 4 linkage, adjusts the rear attitude to adapt to the curve;

[0083] S11, Cornering thrust compensation, control the vertical thruster 51 to compensate for thrust and prevent sticking to the wall or getting stuck;

[0084] S12. Cornering recovery: Control the steering mechanism to the straight position, restore the straight detection mode, and return to step S4;

[0085] S13. Inspection complete. The robot exits the pipeline, completing the inspection.

[0086] The above testing process will be explained in detail below:

[0087] The robot's working process uses the Raspberry Pi 4B control motherboard in the sealed cavity at the tail as the control core, linking the head vision acquisition mechanism 1, the first steering mechanism 2, the second steering mechanism 3, the magnetic flux leakage detection mechanism 4, and the propulsion mechanism 5. Combined with the IMU attitude sensor and fiber optic communication, it completes the detection task in two main working conditions, realizing the coordinated linkage of mechanism movement and sensor control throughout the process.

[0088] I. Main Working Condition 1: Linear Detection Based on Uniform Velocity Detection + Attitude Stabilization + Dual-Sensor Acquisition

[0089] This working condition represents the robot's normal operating state. The core function is to precisely control the coordination of various mechanisms through the main control board to achieve comprehensive and stable detection of the pipe's inner wall. The complete process integrating mechanism movements and sensor control is as follows:

[0090] 1. Control motherboard initialization and mechanism preparation (control core startup)

[0091] After the control motherboard 6 (Raspberry Pi 4B) starts up, it first completes a self-test, establishes a communication connection with the host computer through optical fiber, and synchronously receives the host computer's start command. Then it sends initialization signals to each mechanism and collects initial attitude data through the IMU attitude sensor to determine whether the robot is in a horizontally centered state. If there is a deviation, it immediately sends a fine-tuning command to the vertical thruster 51 to complete the attitude calibration and prepare for testing.

[0092] 2. Motion and sensor control of the magnetic flux leakage detection mechanism

[0093] The control motherboard 6 sends an action command to the magnetic flux leakage detection mechanism 2, controlling the motor to run. The motor 24 drives the movable disc of the lead screw nut to move linearly, thereby driving the scissor lift mechanism to slowly open until the magnetic flux leakage detection sensor 22 is tightly attached to the inner wall of the pipe. The magnetic flux leakage detection sensor 22 collects the magnetic flux leakage signal of the inner wall of the pipe in real time and transmits the signal to the control motherboard 6. After the control motherboard 6 performs preliminary processing of the signal, it synchronously transmits it back to the host computer to realize real-time monitoring of defects such as corrosion and cracks.

[0094] 3. Closed-loop control of propulsion mechanism motion and attitude

[0095] The main control board 6 controls the tail main thruster 52 to start, outputting a constant thrust to drive the robot forward at a constant speed. At the same time, the two vertical thrusters 51 at the head and the two vertical thrusters 52 at the tail work together. The IMU attitude sensor collects the robot's position, speed, and attitude data (such as left and right offset and up and down tilt) in real time and feeds the data back to the main control board 6. The main control board 6 adjusts the thrust of each vertical thruster 51 in real time through a closed-loop control algorithm to ensure that the robot always travels along the center line of the pipe and avoids sticking to the wall or deviating.

[0096] 4. Visual sensing acquisition and synchronous data transmission

[0097] The control motherboard 6 controls the start of the head vision acquisition mechanism 1, turns on the underwater lighting 13, and the camera 12 acquires images of the inner wall of the pipe in real time. The visual data is transmitted to the control motherboard through the control line and integrated with the defect data acquired by the leakage magnetic field detection sensor 22 and the attitude data acquired by the IMU. The control motherboard 6 converts the integrated data into fiber optic signals through the optical transceiver and transmits them back to the host computer in real time via fiber optic cable. The host computer displays the detection images, defect signals and robot posture in a synchronized manner, realizing the visual monitoring of the detection process.

[0098] II. Main Operating Condition Two: Active Cornering Based on Dual Steering Assistance + Attitude Compensation + Sensor Closed-Loop

[0099] This working condition describes the robot's operation when encountering complex road sections such as curves, T-shaped pipes, and valves. The core is the precise control of the two-section steering mechanism by the mainboard 6, which works in conjunction with thruster compensation to achieve smooth cornering without interrupting detection. The complete process integrating mechanism motion and sensor control is as follows:

[0100] 1. Curve identification and cornering preparation

[0101] During straight-line detection, camera 12 captures real-time images of the pipeline ahead and transmits the visual data to the control motherboard 6. The control motherboard 6 uses image recognition algorithms to determine if there is a curve ahead. Simultaneously, the host computer can manually send curve commands via fiber optic cable to trigger the curve-taking mode. Upon receiving the curve signal, the control motherboard immediately sends a deceleration command to the rear main thruster 52 to reduce the robot's speed. At the same time, it increases the acquisition frequency of the IMU attitude sensor to capture real-time changes in the robot's attitude, providing data support for steering control.

[0102] 2. Coordinated operation of dual steering mechanisms

[0103] According to the preset steering algorithm, the control motherboard 6 sends a deflection command to the first steering mechanism 3, controlling the two servo motors 34 (rotation range ±90°) connected in series inside to work together, causing the head vision acquisition mechanism 1 to deflect and align with the curve. At the same time, the control motherboard 5 sends a linkage command to the second steering mechanism 4, controlling its servo motors to deflect synchronously, causing the vertical thruster 51 and the main thruster 52 at the tail to adjust their attitude, forming a serpentine bionic posture, ensuring that the robot as a whole can adapt to the curvature of the curve. During this process, the bellows outside the steering mechanism deforms synchronously with the deflection of the servo motors. The control motherboard 6 monitors the pressure data inside the pipe (indirectly through IMU attitude change feedback) to ensure the hydraulic oil pressure inside the bellows 35 is balanced, preventing seal failure.

[0104] 3. Thruster compensation and attitude stabilization control

[0105] During the turning process, the control motherboard 6 adjusts the thrust of each vertical thruster 51 in real time based on the attitude data collected by the IMU and the cornering angle: it outputs a smaller thrust to the vertical thruster 51 on the inside of the corner and a larger thrust to the vertical thruster 51 on the outside of the corner, forming a compensating torque to prevent the robot from sticking to the wall or getting stuck; at the same time, the tail main thruster 52 maintains a low and uniform speed to ensure that the robot passes through the corner smoothly and avoids loss of attitude control due to excessive speed.

[0106] 4. Post-corner recovery and inspection continuation

[0107] When the image captured by the camera shows that the robot has fully entered the straight section, or when the IMU attitude sensor reports that the robot's attitude has returned to horizontal, the control motherboard 6 sends a return-to-center command to the two-section steering mechanism, controls the servo motor to reset, and the steering mechanism returns to its initial state. At the same time, the control motherboard 6 adjusts the speed of the tail main thruster 52 to the normal detection speed, the vertical thruster 51 continues to maintain centering control, and the magnetic flux leakage detection sensor 22 and the camera 12 continue to collect detection data, achieving seamless continuation of the detection work after turning.

[0108] III. Common Control Logic for the Two Operating Conditions

[0109] 1. The mainboard controls the entire process: The actions of all mechanisms (steering, propulsion, detection, vision) are controlled by the Raspberry Pi 4B at the rear, achieving centralized control and ensuring that the actions of each mechanism are coordinated and consistent.

[0110] 2. Sensor feedback closed loop: The IMU attitude sensor, leakage magnetic field detection sensor 22, and camera 12 collect data in real time and feed it back to the control motherboard. The control motherboard adjusts the mechanism's actions through algorithms to form a closed loop control of "command-action-sensing-correction", which improves the stability and accuracy of detection.

[0111] 3. Synchronous data transmission: All mechanism action status and sensor data are transmitted back to the host computer in real time via optical fiber. The host computer can manually intervene in the mechanism action (such as emergency stop, adjustment of steering angle) to achieve remote control and monitoring.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions created by the present invention, and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions created by the present invention without departing from the essence and scope of the technical solutions created by the present invention.

Claims

1. A modular pipeline inspection robot suitable for pressurized water-filled pipe networks, characterized in that: Include: The propulsion mechanism includes a vertical thruster that controls the robot to float horizontally in the water and a tail main thruster that provides navigation; The head vision acquisition mechanism is used to acquire images of the inner surface of the pipe and is rotated and sealed to connect with the magnetic flux leakage detection mechanism to enable the robot to turn inside the pipe. The magnetic flux leakage detection mechanism includes a folding mechanism and a magnetic flux leakage detection sensor. The folding mechanism is configured to be driven to control the magnetic flux leakage detection sensor to be in contact with or away from the inner surface of the pipe. The magnetic flux leakage detection sensor is used to collect pipe defect data. The magnetic flux leakage detection mechanism is rotatably and sealedly connected to the tail main thruster to enable the robot to turn inside the pipe. IMU sensors are respectively arranged in the head vision acquisition mechanism, the magnetic flux leakage detection mechanism, and the propulsion mechanism to collect the robot's posture data in real time and feed the data back to the enclosed control motherboard. The control motherboard adjusts the thrust of each vertical thruster in real time through closed-loop control to control the robot to travel along the center line of the pipeline.

2. The modular pipeline inspection robot suitable for pressurized water-filled pipe networks according to claim 1, characterized in that: The folding mechanism is a scissor-type lifting mechanism, and the opening and closing motion is controlled by a linear motion mechanism to realize the radial linear movement of the magnetic flux leakage detection sensor.

3. The modular pipeline inspection robot suitable for pressurized water-filled pipe networks according to claim 1, characterized in that: The head vision acquisition mechanism is equipped with a vertical thruster, and the robot's tail is equipped with a vertical thruster. The robot's position is controlled by controlling the vertical thruster and the tail main thruster.

4. The modular pipeline inspection robot suitable for pressurized water-filled pipe networks according to claim 1, characterized in that: The head vision acquisition mechanism is connected to the magnetic flux leakage detection mechanism through the steering mechanism. By controlling the steering mechanism, the robot can smoothly navigate curves without interrupting the detection.

5. The modular pipeline inspection robot suitable for pressurized water-filled pipe networks according to claim 1, characterized in that: The vertical thruster at the rear is connected to the magnetic flux leakage detection mechanism via a steering mechanism. By controlling the steering mechanism, smooth cornering can be achieved without interrupting the detection.

6. A modular pipeline inspection robot suitable for pressurized water-filled pipe networks according to claim 4 or 5, characterized in that: The steering mechanism consists of two servo motors connected in series. By controlling the coordinated movement of the two servo motors, the robot's posture can be adjusted to adapt to the curvature of the pipe bend.

7. The modular pipeline inspection robot suitable for pressurized water-filled pipe networks according to claim 2, characterized in that: The linear motion mechanism is a motor-driven lead screw and nut pair mechanism. The motor is mounted on a fixed plate, and the lead screw is rotatably mounted on the movable plate of the folding mechanism. The rotation of the lead screw drives the movable plate to move linearly, thereby opening and closing the folding mechanism.

8. The modular pipeline inspection robot suitable for pressurized water-filled pipe networks according to claim 1, characterized in that: The head vision acquisition mechanism includes a housing, a camera, and a light source, with the camera and light source housed in the housing.

9. A pipeline inspection and control method, characterized in that: Based on the modular pipeline inspection robot applicable to pressurized water-filled pipe networks as described in any one of claims 1-8, the method comprises the following steps: S1. System startup: The host computer connects to the control motherboard via fiber optic cable, initializes, and performs self-tests on each module. S2, Attitude calibration: The vertical thruster and tail main thruster are activated, the IMU sensor provides attitude feedback, and the robot is adjusted to the centerline of the pipeline. S3. Inspection preparation: The folding mechanism opens, and the magnetic flux leakage detection sensor is attached to the inner wall of the pipe. S4, straight-line propulsion, with the tail main thruster running at a constant speed and the vertical thruster maintaining the center position; S5 features dual-mode detection: a camera and lighting lamp acquire images, while a magnetic flux leakage sensor acquires defect signals. S6. Data feedback: The detection data and attitude data are transmitted back to the host computer via optical fiber. If the monitoring shows no bends, return to step S4. S7. Curve detection: The host computer determines whether there is a curve ahead based on the collected images. S8. Preparing for a curve: If a curve is detected, reduce the speed of the main thruster. S9. Head turning: The first section of the turning mechanism moves, causing the head vision acquisition mechanism to deflect and align with the curve. S10, rear-end coordinated steering, the second steering mechanism works together to adjust the rear attitude to adapt to the curve; S11, Cornering thrust compensation, controls the vertical thrusters to compensate for thrust; S12. Cornering recovery: Control the steering mechanism to the straight position, restore the straight detection mode, and return to step S4; S13. Inspection complete. The robot exits the pipeline, completing the inspection.

10. The pipeline inspection and control method according to claim 9, characterized in that: The movements of the steering mechanism, vertical thruster, horizontal thruster, magnetic flux leakage sensor, and head vision acquisition mechanism are all controlled by commands issued by the Raspberry Pi 4B, ensuring coordinated and consistent movements of each mechanism. The IMU attitude sensor, magnetic flux leakage sensor, and camera collect data in real time and feed it back to the Raspberry Pi 4B. The Raspberry Pi 4B adjusts the mechanism's movements through algorithms, forming a closed-loop control of commands, actions, sensing, and corrections. The Raspberry Pi 4B communicates with the host computer via fiber optic cable to achieve remote control and monitoring.

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