Multi-pipe-diameter self-adaptive multi-working-condition heat supply pipeline inspection robot control method and system and related devices

Abstract

The invention provides a multi-pipe-diameter self-adaptive multi-working-condition heat supply pipeline inspection robot control method and system and a related device, and the method comprises the following steps: 1, obtaining the operation data of an inspection robot, the operation data comprises the distance between the inner wall of the to-be-detected pipeline and a crawler belt in the self-adaptive crawler belt moving chassis assembly, the contact pressure of a bottom supporting wheel in the self-adaptive crawler belt moving chassis assembly, the expansion amount of a transverse expansion assembly in the self-adaptive crawler belt moving chassis assembly and the working condition of the to-be-detected pipeline; step 2, generating a pipe diameter self-adaptive control instruction for controlling the self-adaptive crawler mobile chassis assembly to perform pipe diameter adaptation based on the acquired operation data; 3, after the self-adaptive crawler belt moving chassis assembly is matched, a moving posture control instruction of the inspection robot is generated; and step 4, finishing the inspection of the to-be-detected pipeline based on the generated moving posture control instruction of the inspection robot. According to the invention, efficient, accurate and safe cooperative control of each execution assembly of the robot is realized.

Description

Technical Field

[0001] This invention belongs to the field of control technology for heating pipeline inspection robots, specifically relating to a control method, system and related devices for a multi-diameter adaptive multi-working-condition heating pipeline inspection robot. Background Technology

[0002] Urban heating pipeline inspection robots are core equipment for ensuring the safe operation of the pipeline network, but the rationality of their control methods directly affects inspection efficiency and reliability. Existing inspection robot control methods have the following technical shortcomings: 1. Low efficiency of pipe diameter adaptive control: The pipe diameter is mostly identified by a single sensor, resulting in large data errors. Furthermore, the telescopic mechanism and the support mechanism are adjusted independently, lacking coordination logic. This leads to long adaptation time and poor fit in the variable diameter pipe, making it easy for slippage or pipe scratches to occur. 2. Insufficient coordination in task execution: The control timing of the gimbal, robotic arm, and end effector is chaotic, there is a lack of linkage algorithms, the detection area is not fully covered, the end effector replacement requires manual intervention, the switching time is >30 seconds, and the task efficiency is low; 3. Poor accuracy of movement attitude control: The wheel set adjustment parameters are fixed and are not dynamically adjusted for working conditions such as welds and protrusions. The shock absorption control relies solely on hardware buffering, and the vibration amplitude of the machine body is greater than 2mm, resulting in distorted detection data. The path correction relies on a single navigation system, with a deviation of greater than 20mm, making it easy to deviate from the inspection route. 4. Inadequate safety protection and control: The early warning mechanism only targets single faults, and the emergency response process is generalized and not adapted to specific scenarios such as pipeline flammable gas leaks and mechanical jamming; the power protection logic is simple, resulting in a high risk of battery overcharging and over-discharging, and an equipment failure rate >15%. 5. Unsmooth switching between dual modes: When switching between automatic and manual modes, sudden changes in attitude and work interruptions are likely to occur. The communication link has no redundancy design, and data is easily lost after the interruption, affecting the continuity of inspection.

[0003] To address the aforementioned issues, there is an urgent need to develop a control method that features rapid adaptation to all pipe diameters, collaborative operation of multiple structures, high-precision attitude control, and highly reliable safety protection, in order to meet the inspection needs of urban heating pipe networks under complex operating conditions. Summary of the Invention

[0004] The purpose of this invention is to provide a control method, system, and related device for a multi-diameter adaptive multi-condition heating pipeline inspection robot. This invention solves the technical problems in existing heating pipeline inspection robot control methods, such as lagging pipe diameter adaptive response, poor work execution coordination, low movement posture control accuracy, insufficient safety protection reliability, and unsmooth dual-mode switching. It achieves rapid and accurate adaptation to all pipe diameters, efficient collaborative operation of multiple components, stable movement under complex working conditions, safe and controllable process throughout, and seamless switching between dual modes.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, the present invention provides a control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot, based on a multi-diameter adaptive multi-condition heating pipeline inspection robot, the inspection robot comprising an adaptive tracked mobile chassis assembly, a body assembly, a modular operation execution assembly, a multimodal perception integrated assembly, and a control and communication integrated assembly; the adaptive tracked mobile chassis assembly is fixedly connected to the body assembly; the modular operation execution assembly is mounted on the top of the body assembly; The modular operation execution component is used to perform specific inspection operations; The multimodal sensing integration component is used to achieve data acquisition; The control and communication integration component is used to control the execution of inspection operations based on the collected data; The control method includes the following steps: Step 1: Obtain the operation data of the inspection robot. The operation data includes the distance between the inner wall of the pipe to be tested and the track in the adaptive tracked mobile chassis assembly, the contact pressure of the bottom support wheel in the adaptive tracked mobile chassis assembly, the extension and retraction of the lateral extension component in the adaptive tracked mobile chassis assembly, and the working condition of the pipe to be tested. Step 2: Generate pipe diameter adaptive control commands based on the acquired operating data to control the adaptive tracked mobile chassis assembly for pipe diameter adaptation. Step 3: After the adaptive tracked mobile chassis component is adapted, generate the mobile posture control command for the inspection robot. Step 4: Complete the inspection of the pipeline under test based on the generated movement posture control commands of the inspection robot.

[0006] Preferably, the pipe diameter adaptive control command for controlling the adaptive tracked mobile chassis assembly to adapt the pipe diameter is generated based on the acquired operating data. The specific method is as follows: The diameter of the pipe to be tested is calculated based on the acquired operational data; Based on the obtained pipe diameter value and the operating data, an adaptive pipe diameter control command is generated.

[0007] Preferably, the generated movement posture control commands for the inspection robot include: Action commands for the track and adjusting wheel assembly in the adaptive tracked mobile chassis assembly; Track speed adjustment command in the track and adjuster wheel assembly; Commands regarding the support strength of the wheel assembly and track tension in the track and adjusting wheel assembly; In addition, path correction calibration instructions for track and adjustment wheel assemblies.

[0008] Preferably, the adaptive tracked mobile chassis structure includes a lateral telescopic assembly, a track and adjusting wheel assembly, and a bottom vertical support wheel assembly, wherein: There are two lateral telescopic components, which are respectively arranged on both sides of the fuselage structure; each lateral telescopic component is connected to a track and adjusting wheel assembly at its end. The bottom vertical support wheel assembly is located at the bottom of the machine body to provide vertical support and adapt to unevenness of the inner wall of the pipe.

[0009] Preferably, the track and adjusting wheel assembly includes a track frame, a drive wheel, a driven track roller, a support wheel, and a track body, wherein: The track frame is hinged to the end of the lateral telescopic mechanism; the drive wheel, driven track roller and support wheel are mounted on the track frame; the track body is wrapped around the drive wheel, driven track roller and support wheel.

[0010] Preferably, the bottom vertical support wheel assembly includes two independent adjustable support modules symmetrically distributed front and rear, the two adjustable support modules are symmetrically arranged at the bottom of the fuselage, and the two adjustable support modules are arranged along the axial direction of the fuselage.

[0011] Secondly, the present invention provides a multi-diameter adaptive multi-condition heating pipeline inspection robot control system, comprising: The data acquisition unit is used to acquire the operating data of the inspection robot. The operating data includes the distance between the inner wall of the pipe under test and the track in the adaptive tracked mobile chassis assembly, the contact pressure of the bottom support wheel in the adaptive tracked mobile chassis assembly, the extension and retraction of the lateral extension component in the adaptive tracked mobile chassis assembly, and the operating condition of the pipe under test. An adaptive control command generation unit is used to generate pipe diameter adaptive control commands for the adaptive tracked mobile chassis assembly to adapt the pipe diameter based on the acquired operating data. The movement posture command generation unit is used to generate movement posture control commands for the inspection robot after the adaptive tracked mobile chassis components are adapted. The inspection control unit is used to complete the inspection of the pipeline under test based on the generated movement posture control commands of the inspection robot.

[0012] Thirdly, the present invention provides an electronic device including a processor and a memory, wherein the memory stores computer instructions, and when the computer instructions are executed by the processor, the electronic device performs the method described thereon.

[0013] Fourthly, the present invention provides a computer program product, the computer program product including computer-executable instructions, which, when executed, implement the method described.

[0014] Fifthly, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the method described herein.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention provides a control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot. By constructing a hierarchical collaborative control architecture of "main control layer - drive layer - execution layer," and based on multi-source data fusion and intelligent decision-making algorithms, it achieves efficient, accurate, and safe collaborative control of the robot's various execution components. Specifically, based on collected operational data, a weighted fusion algorithm is used to calculate the pipe diameter in real time. Combined with the linkage closed-loop adjustment of lateral extension and bottom support, an adaptive control command is generated for the adaptive tracked mobile chassis component to adapt to the pipe diameter. This fundamentally solves the problems of slow adaptation, poor fit, and easy slippage caused by single sensor errors and independent adjustments in traditional methods.

[0016] Furthermore, based on the motion commands of the track and adjusting wheel assembly in the adaptive tracked mobile chassis assembly, the wheel speed adjustment commands of the track in the track and adjusting wheel assembly, the support force and track tension commands of the wheel group in the track and adjusting wheel assembly, and the path correction and calibration commands of the track and adjusting wheel assembly, the robot's movement attitude control performance on the inner wall of complex pipes is greatly optimized. By independently adjusting the ±30° pitch of the driving wheel, driven wheel and support wheel through independent servo motors, and combined with PID speed synchronous control, dynamic vibration reduction compensation based on vibration sensors, and multi-source fusion positioning and QR code periodic calibration, high-stability movement in straight pipes, curved pipes and uneven pipes with obstacles ≤50mm is achieved. The body vibration amplitude is controlled within ±0.5mm, and the trajectory tracking deviation does not exceed ±10mm, ensuring the accuracy of detection data and the reliability of inspection paths. Detailed Implementation

[0017] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0018] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0019] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0020] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0021] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0022] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0023] Example 1 This embodiment provides a control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot. The robot comprises an adaptive tracked chassis assembly, a body assembly, a modular operation execution assembly, a multimodal perception integration assembly, and a control and communication integration assembly. The adaptive tracked chassis assembly is fixedly connected to the body assembly. The modular operation execution assembly is mounted on top of the body assembly. The modular operation execution component is used to perform specific inspection operations; The multimodal sensing integration component is used to achieve data acquisition; The control and communication integration component is used to control the execution of inspection operations based on the collected data.

[0024] In this embodiment, the adaptive tracked mobile chassis structure includes a lateral telescopic assembly, a track and adjusting wheel assembly, and a bottom vertical support wheel assembly, wherein: There are two lateral telescopic components, which are respectively arranged on both sides of the fuselage structure; each lateral telescopic component is connected to a track and adjusting wheel assembly at its end. The bottom vertical support wheel assembly is located at the bottom of the machine body to provide vertical support and adapt to unevenness of the inner wall of the pipe.

[0025] In this embodiment, the lateral telescopic assembly includes a telescopic base, an electric push rod, a guide rail, a two-stage telescopic arm, and a displacement sensor assembly structure, wherein: The telescopic base is fixed to the side wall of the machine body. An electric push rod is installed on the telescopic base. The electric push rod drives and connects to two-stage telescopic arms. A guide rail is installed on the telescopic base. The two-stage telescopic arms are slidably installed on the guide rail. The ends of the two-stage telescopic arms are connected to a track and an adjusting wheel assembly.

[0026] The displacement sensor assembly structure is installed at the end of the two-stage telescopic arm to assemble a pressure sensor that detects the contact pressure between the track and adjusting wheel system and the inner wall of the pipeline in real time.

[0027] In this embodiment, the track and adjusting wheel assembly includes a track frame, a drive wheel, a driven track roller, a support wheel, and a track body, wherein: The track frame is hinged to the end of the lateral telescopic mechanism; the drive wheel, driven track roller and support wheel are mounted on the track frame; the track body is wrapped around the drive wheel, driven track roller and support wheel.

[0028] The active drive wheel, driven support wheel, and support wheel are all equipped with independent micro servo drive structures, which can achieve ±30° independent pitch adjustment.

[0029] It also includes an automatic tension adjustment mechanism installed on the track frame, which is driven and connected to the driven track roller.

[0030] In this embodiment, the bottom vertical support wheel assembly includes two independent adjustable support modules symmetrically distributed front and rear. The two adjustable support modules are symmetrically arranged at the bottom of the fuselage and are arranged along the axial direction of the fuselage.

[0031] The control method adopts a hierarchical control process of "main control layer - driver layer - execution layer", based on the collaborative processing of STM32H743 MCU and FPGA, to complete pipe diameter adaptive control, job execution collaborative control, movement posture control and safety protection control, specifically including the following steps: S1: After the robot starts, the control and communication integration component initializes each component, the multimodal perception integration component collects the initial environmental data of the pipeline, and the FPGA preprocesses the data and transmits it to the MCU; S2: The MCU performs pipe diameter adaptive control, identifies the pipe diameter through multi-source data fusion, and drives the adaptive tracked mobile chassis component to complete the adaptation and adjustment. S3: After the adaptation is completed, the MCU switches to mobile posture control, drives the track wheel group in the adaptive track mobile chassis assembly to move in coordination and dynamically compensate for vibration, ensuring that the robot moves along the preset path; S4: During the movement, the MCU performs collaborative control of job execution and schedules modular job execution components to complete defect detection and emergency operations; S5: The entire process involves monitoring equipment status and environmental parameters through safety protection and control, triggering multi-level early warnings and emergency responses; S6: Supports dual-mode switching between "automatic inspection and manual remote control" to ensure operational continuity and flexibility.

[0032] Example 2 Based on Example 1, this example provides a multi-diameter adaptive multi-condition heating pipeline inspection robot control method. In S2, the pipe diameter adaptive control specifically includes: S21: Multi-source data acquisition: LiDAR acquires distance data from the inner wall of the pipe, pressure sensor of the bottom support wheel acquires contact pressure data, displacement sensor of the lateral telescopic arm acquires telescopic data, acquisition frequency ≥10Hz; S22: Data fusion and recognition: The FPGA filters and reduces noise in the collected data, and the MCU calls the DN300-DN1200 pipe diameter database to calculate the pipe diameter value through a weighted fusion algorithm. The recognition error is ≤±5mm. S23: Coordinated Adaptive Adjustment: The MCU generates a linkage command for lateral extension and vertical support. The lateral extension component performs 0-500mm extension and contraction according to "rapid coarse adjustment (speed 50mm / s) + precise fine adjustment (accuracy ±0.1mm)", with a response time ≤0.8s. The bottom vertical support wheel assembly adjusts the lifting amount from 0-100mm through pressure closed-loop control to maintain a support pressure of 50-80N, ensuring that the track fits the inner wall of the pipe ≥95%.

[0033] Example 3 Based on Example 1, this example provides a control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot. In S3, the movement posture control specifically includes: S31: Wheelset Coordinated Adjustment: The MCU drives the independent servo motors of the active drive wheel, driven track roller, and support wheel according to the pipeline conditions (straight pipe section / obstacle) to achieve ±30° pitch adjustment; for obstacles with a height of ≤50mm, it generates a "lift track - cross obstacle - reset support" action sequence; S32: Speed ​​synchronization control: The PID algorithm is used to adjust the speed of the track wheels on both sides, with a synchronization error of ≤±2%, to prevent the robot from deviating from its side. S33: Dynamic vibration compensation: Vibration sensors collect chassis vibration data, MCU calculates the compensation amount, and dynamically adjusts the wheel support force and track tension to control the vibration amplitude of the machine body within ±0.5mm. S34: Path correction calibration: The trajectory is calculated by integrating inertial navigation and odometer data, and the positioning is calibrated every 50 meters by using QR code markers on the inner wall of the pipeline. The trajectory deviation is ≤ ±10mm.

[0034] Example 4 Based on Example 1, this example provides a control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot. In S4, the collaborative control of the operation execution specifically includes: S41: Gimbal-robotic arm linkage: Based on positioning data and defect location, the MCU calculates the gimbal rotation angle and robotic arm motion parameters. The servo motor closed-loop control achieves positioning within the maximum extension length of 800mm with an error of ≤±2mm. When the joint torque is ≥15N·m, it triggers emergency braking and retracts 50mm. S42: End effector quick change: The sensor monitors the "magnetic suction + snap-on" status, and the MCU sends a switching command according to the operation requirements to complete high-definition perception, multi-dimensional detection, and emergency operation unit replacement. The response time is ≤10s, and automatic calibration is performed after replacement. S43: Multi-dimensional inspection scheduling: The inspection units are scheduled in the order of "visual pre-inspection → ultrasonic flaw detection → infrared thermometry → gas detection". The FPGA caches the data and the MCU performs correlation analysis to generate a comprehensive defect evaluation result.

[0035] Example 5 Based on Example 1, this example provides a control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot. In S5, the safety protection control specifically includes: S51: Multi-level early warning monitoring: Real-time collection of temperature, combustible gas concentration, and equipment status data, triggering "Level 1 alert - Level 2 derating - Level 3 shutdown" early warning; S52: Specialized emergency response: When combustible gas exceeds the standard, cut off unnecessary power and plan the shortest return path; when the robotic arm collides or gets stuck, perform reverse unlocking, and if it fails, alarm and wait for intervention; when communication is interrupted, start 128GB SSD local storage, and automatically upload data after recovery; S53: Power safety protection: Monitors the voltage, current and temperature of the lithium battery pack, and automatically cuts off the output in case of overcharging, over-discharging, overcurrent or short circuit; triggers power-off protection and power-on calibration when hot-swapped.

[0036] Example 6 Based on Example 1, this example provides a control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot. In S6, the dual-mode switching specifically includes: S61: Automatic Inspection Mode: The MCU automatically completes pipe diameter identification, path planning, and defect detection according to preset paths and parameters, and supports breakpoint continuation inspection; S62: Manual remote control mode: Receives commands from PC / mobile terminal via 5G / WiFi, executes them according to the priority of "emergency stop > motion control > operation control", and the command response delay is ≤100ms; S63: Disturbance-free switching: Maintain robot posture stability and operation continuity during switching, with a switching time ≤0.5s.

[0037] Example 7 Based on Example 1, this example provides a control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot. The control method further includes self-diagnosis and adaptive optimization steps. S71: Self-diagnosis: Checks the status of sensors, actuators, and communication modules every 30 minutes, generates a health report, and has a fault diagnosis accuracy rate of ≥98%. S72: Adaptive optimization: Based on operating condition data, control parameters are dynamically adjusted through machine learning to improve operating condition adaptability.

[0038] Example 8 Based on Example 1, this example provides a control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot. In the control method, the communication processing adopts "fiber optic + 5G / WiFi" dual-mode redundancy: fiber optic communication is given priority inside the pipeline, and 5G / WiFi is automatically switched at the outlet; when communication is interrupted, the backup link is switched within 1 second to ensure continuous control.

[0039] Example 9 This embodiment provides a multi-diameter adaptive multi-condition heating pipeline inspection robot control system, including: The data acquisition unit is used to acquire the operating data of the inspection robot. The operating data includes the distance between the inner wall of the pipe under test and the track in the adaptive tracked mobile chassis assembly, the contact pressure of the bottom support wheel in the adaptive tracked mobile chassis assembly, the extension and retraction of the lateral extension component in the adaptive tracked mobile chassis assembly, and the operating condition of the pipe under test. An adaptive control command generation unit is used to generate pipe diameter adaptive control commands for the adaptive tracked mobile chassis assembly to adapt the pipe diameter based on the acquired operating data. The movement posture command generation unit is used to generate movement posture control commands for the inspection robot after the adaptive tracked mobile chassis components are adapted. The inspection control unit is used to complete the inspection of the pipeline under test based on the generated movement posture control commands of the inspection robot.

[0040] Example 10 This embodiment also provides a computing device. The computing device includes a bus, a processor, a memory, and a communication interface. The processor, memory, and communication interface communicate with each other via the bus. The computing device can be a server or a terminal device. It should be understood that this application does not limit the number of processors and memory in the computing device.

[0041] A bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, a bus can include a path for transmitting information between various components of a computing device (e.g., memory, processor, communication interfaces).

[0042] The processor may include any one or more of the following: central processing unit (CPU), graphics processing unit (GPU), tensor processing unit (TPU), application specific integrated circuit (ASIC), field-programmable gate array (FPGA), microprocessor (MP), or digital signal processor (DSP).

[0043] Memory can include volatile memory, such as random access memory (RAM). Processors can also include non-volatile memory. volatile memory, such as read-only memory (ROM). ROM (memory only), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0044] The memory stores executable program code, which the processor executes to implement the functions of the aforementioned units, thereby achieving, for example, the method described in Embodiment 1. That is, the memory may store instructions for the methods and functions relating to the computing device in any of the above embodiments.

[0045] The communication interface uses transceiver modules such as, but not limited to, network interface cards and transceivers to enable communication between computing devices and other devices or communication networks.

[0046] Example 11 This embodiment also provides a computer-readable storage medium storing computer instructions that, when executed by a processor, cause the processor to perform the methods and functions of the computing device involved in any of the above embodiments.

[0047] Generally, the various embodiments of this disclosure can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects can be implemented in hardware, while others can be implemented in firmware or software, which can be executed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of this disclosure are shown and described as block diagrams, flowcharts, or represented using some other illustration, it should be understood that the blocks, apparatuses, systems, techniques, or methods described herein can be implemented as, as non-limiting examples, in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0048] Example 12 This embodiment provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, which execute in a device on a target real or virtual processor to perform the processes / methods described above. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of program modules can be combined or divided among program modules as needed. The machine-executable instructions for the program modules can execute within a local or distributed device. In a distributed device, the program modules can reside in both local and remote storage media.

[0049] Computer program code used to implement the methods of this disclosure may be written in one or more programming languages. This computer program code may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus, such that when executed by the computer or other programmable data processing apparatus, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be performed. The program code may be executed entirely on a computer, partially on a computer, as a stand-alone software package, partially on a computer and partially on a remote computer, or entirely on a remote computer or server.

[0050] In the context of this disclosure, computer program code or related data may be carried on any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, and so on. Examples of signals may include electrical, optical, radio, sound, or other forms of propagation signals, such as carrier waves, infrared signals, etc.

[0051] Computer-readable media can be any tangible medium that contains or stores programs for or relating to an instruction execution system, apparatus, or device, or a data storage device such as a data center containing one or more available media. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. More detailed examples of computer-readable storage media include electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0052] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot, characterized in that, Based on a multi-diameter adaptive multi-condition heating pipeline inspection robot, the inspection robot includes an adaptive tracked mobile chassis assembly, a body assembly, a modular operation execution assembly, a multimodal perception integrated assembly, and a control and communication integrated assembly; the adaptive tracked mobile chassis assembly is fixedly connected to the body assembly; the modular operation execution assembly is mounted on the top of the body assembly; The modular operation execution component is used to perform specific inspection operations; The multimodal sensing integration component is used to achieve data acquisition; The control and communication integration component is used to control the execution of inspection operations based on the collected data; The control method includes the following steps: Step 1: Obtain the operation data of the inspection robot. The operation data includes the distance between the inner wall of the pipe to be tested and the track in the adaptive tracked mobile chassis assembly, the contact pressure of the bottom support wheel in the adaptive tracked mobile chassis assembly, the extension and retraction of the lateral extension component in the adaptive tracked mobile chassis assembly, and the working condition of the pipe to be tested. Step 2: Generate pipe diameter adaptive control commands based on the acquired operating data to control the adaptive tracked mobile chassis assembly for pipe diameter adaptation. Step 3: After the adaptive tracked mobile chassis component is adapted, generate the mobile posture control command for the inspection robot. Step 4: Complete the inspection of the pipeline under test based on the generated movement posture control commands of the inspection robot.

2. The control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot according to claim 1, characterized in that, Based on the acquired operational data, pipe diameter adaptive control commands are generated to control the adaptive tracked mobile chassis component for pipe diameter adaptation. The specific method is as follows: The diameter of the pipe to be tested is calculated based on the acquired operational data; Based on the obtained pipe diameter value and the operating data, an adaptive pipe diameter control command is generated.

3. The control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot according to claim 1, characterized in that, The generated movement posture control commands for the inspection robot include: Action commands for the track and adjusting wheel assembly in the adaptive tracked mobile chassis assembly; Track speed adjustment command in the track and adjuster wheel assembly; Commands regarding the support strength of the wheel assembly and track tension in the track and adjusting wheel assembly; In addition, path correction calibration instructions for track and adjustment wheel assemblies.

4. The control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot according to claim 1, characterized in that, The adaptive tracked mobile chassis structure includes a lateral telescopic assembly, a track and adjusting wheel assembly, and a bottom vertical support wheel assembly, wherein: There are two lateral telescopic components, which are respectively arranged on both sides of the fuselage structure; each lateral telescopic component is connected to a track and adjusting wheel assembly at its end. The bottom vertical support wheel assembly is located at the bottom of the machine body to provide vertical support and adapt to unevenness of the inner wall of the pipe.

5. The control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot according to claim 1, characterized in that, The track and adjusting wheel assembly includes a track frame, a drive wheel, a driven track roller, a support wheel, and the track body, wherein: The track frame is hinged to the end of the lateral telescopic mechanism; the drive wheel, driven track roller and support wheel are mounted on the track frame; the track body is wrapped around the drive wheel, driven track roller and support wheel.

6. The control method for a multi-diameter adaptive multi-condition heating pipeline inspection robot according to claim 1, characterized in that, The bottom vertical support wheel assembly includes two independent adjustable support modules symmetrically distributed front and rear. The two adjustable support modules are symmetrically arranged at the bottom of the fuselage and are arranged along the axial direction of the fuselage.

7. A multi-diameter adaptive multi-condition heating pipeline inspection robot control system, characterized in that, include: The data acquisition unit is used to acquire the operating data of the inspection robot. The operating data includes the distance between the inner wall of the pipe under test and the track in the adaptive tracked mobile chassis assembly, the contact pressure of the bottom support wheel in the adaptive tracked mobile chassis assembly, the extension and retraction of the lateral extension component in the adaptive tracked mobile chassis assembly, and the operating condition of the pipe under test. An adaptive control command generation unit is used to generate pipe diameter adaptive control commands for the adaptive tracked mobile chassis assembly to adapt the pipe diameter based on the acquired operating data. The movement posture command generation unit is used to generate movement posture control commands for the inspection robot after the adaptive tracked mobile chassis components are adapted. The inspection control unit is used to complete the inspection of the pipeline under test based on the generated movement posture control commands of the inspection robot.

8. An electronic device, characterized in that, It includes a processor and a memory, the memory storing computer instructions that, when executed by the processor, cause the electronic device to perform the method of any one of claims 1 to 6.

9. A computer program product, characterized in that, The computer program product includes computer-executable instructions that, when executed, implement the method of any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when executed by a processor, implement the method of any one of claims 1 to 6.