A portable pipeline outer wall cleaning mechanism suitable for different pipe diameters

Abstract

This invention discloses an adaptive portable pipe external wall cleaning mechanism and control method suitable for different pipe diameters, belonging to the technical field of pipe maintenance equipment. The mechanism includes a grinding mechanism, a cylinder, a scanning device, and a clamping and moving mechanism. This invention employs a centralized-distributed intelligent control system and method, where the centralized unit uses a nonlinear model predictive control algorithm based on Koopman operator theory to dynamically map the system nonlinearly to a high-dimensional linear space for rolling optimization; the distributed unit is responsible for the real-time control of each actuator. This system updates model parameters through an online adaptive mechanism, significantly improving control accuracy and robustness in complex nonlinear and time-varying operating environments. This invention solves the problems of poor adaptability, low efficiency, and insufficient intelligence in traditional pipe external wall cleaning methods, achieving efficient, high-quality, and fully automated pipe external wall cleaning operations.

Description

Technical Field

[0001] This invention belongs to the field of automated equipment technology, and specifically discloses a portable pipe external wall cleaning mechanism suitable for different pipe diameters. Background Technology

[0002] As a core component of modern production and infrastructure, the cleanliness of industrial piping systems directly impacts equipment lifespan, production safety, and the quality of the working environment. During operation, various contaminants accumulate on the outer walls of pipelines, including industrial dust, chemical residues, oil stains, rust, and environmental deposits. These contaminants not only affect the aesthetics of the pipelines but can also trigger a series of serious problems: First, corrosive substances accelerate the thinning of the pipeline walls, leading to a decrease in structural strength; second, dirt cover can conceal surface defects such as cracks and corrosion spots, making it difficult to detect potential safety hazards during routine inspections; finally, in certain precision industrial environments (such as food and pharmaceutical, and electronics and semiconductor industries), the cleanliness of the pipeline's outer walls even directly affects product quality and the cleanliness level of the production environment.

[0003] Traditional pipe cleaning methods rely heavily on manual labor, requiring maintenance personnel to wipe the pipe surface with hand cloths, steel brushes, or simple tools, resulting in low levels of automation. While simple and easy to implement, this method has significant limitations: First, it is inefficient, especially for large-scale pipeline systems, where manual cleaning consumes considerable time and manpower. Second, the cleaning quality is inconsistent, greatly affected by the skill level and working conditions of the personnel, making it difficult to guarantee consistent cleanliness. Third, most cleaning equipment is designed for specific pipe diameters or routes, and its effectiveness drops significantly when encountering pipes of different diameters, curvatures, or levels of contamination.

[0004] Meanwhile, innovation in mechanical structure alone is insufficient to fully address the extreme complexity of pipeline cleaning operations. The working environment on the outer wall of a pipeline is highly unstructured, and the cleaning mechanism faces multiple dynamic challenges during its crawling on curved surfaces: on the one hand, the coefficient of friction on the pipeline surface fluctuates dramatically depending on the degree of corrosion, wetness / dryness, and type of contaminants, exhibiting significant nonlinear time-varying characteristics; on the other hand, the robot needs to simultaneously coordinate the travel speed of the drive motor, the attitude adjustment of the steering mechanism, and the contact pressure between the grinding head and the pipe wall, resulting in strong coupling between these subsystems. Traditional PID control or simple open-loop logic struggles to maintain constant grinding force and precise motion trajectory while ensuring operational efficiency, easily leading to uneven grinding or mechanism jamming.

[0005] Based on the above problems, there is a need to develop a portable pipe external wall cleaning mechanism suitable for different pipe diameters to overcome the above technical problems. Summary of the Invention

[0006] The present invention addresses many pain points of traditional cleaning methods, such as poor adaptability, insufficient portability, and limited cleaning effect, through closed-loop control of intelligent sensing, dynamic decision-making, and precise execution. It has broad application prospects and significant technical and economic benefits.

[0007] The technical solution adopted in this invention is as follows: In a first aspect, the present invention provides an adaptive portable pipe wall cleaning mechanism suitable for different pipe diameters, including a grinding mechanism 1, a cylinder 2, a scanning device 3, a clamping and moving mechanism 4, and a centralized-distributed control system; The clamping and moving mechanism 4 constitutes the main frame and walking platform of the mechanism; the grinding mechanism 1 is fixedly connected to the clamping and moving mechanism 4 via a fixed shaft 15; the cylinder body end of the cylinder 2 is connected to the clamping and moving mechanism 4, and its push rod end is hinged to the pressing shaft 11 of the grinding mechanism 1, used to drive the grinding mechanism 1 to press against or away from the outer wall of the pipe; the scanning device 3 is set outside the clamping and moving mechanism 4 and connected to the centralized-distributed control system carried by the clamping and moving mechanism 4, used to scan the cleanliness of the outer wall of the pipe; the centralized-distributed control system is communicatively connected to the sensors and actuators of the grinding mechanism 1 and the clamping and moving mechanism 4, respectively, configured to receive instructions from the centralized unit, and be responsible for real-time distributed control of the grinding drive and tension control of the grinding mechanism 1, the clamping force and multi-degree-of-freedom movement of the clamping and moving mechanism 4, while handling local disturbances and performing critical state estimation; The grinding mechanism 1 includes a clamping shaft 11, a centrally located electric drive wheel 12, a main housing 13, a rearly located electric drive wheel 14, a fixed shaft 15, a grinding belt 19, and a grinding belt tensioning structure 16. The grinding belt 19 is wrapped around the centrally located electric drive wheel 12, the rearly located electric drive wheel 14, and the frontly located electric drive wheel 18. The grinding belt tensioning structure 16 is connected to the frontly located electric drive wheel 18 and is used to drive the frontly located electric drive wheel 18 to move so that the grinding belt 19 remains taut. The clamping and moving mechanism 4 includes a clamping wall 41 for clamping the pipe, a clamping push cylinder 44 for driving the clamping wall 41, and at least one power unit. The clamping wall 41 is hinged to the main frame 46 of the clamping and moving mechanism 4. The cylinder end of the clamping push cylinder 44 is hinged to the main frame 46, and its push rod end is connected to the clamping wall 41, forming a lever-type clamping drive structure. The power unit includes a power unit frame 421, a drive wheel 426, a travel motor 424, and a steering motor 425. The power unit frame 421 is fixed to the main frame 46. The drive wheel 426 is mounted on a cross roller 422 with an external gear. The steering motor 425 meshes with the external gear of the cross roller 422 through a drive gear 423 to drive the drive wheel 426 to change direction. The travel motor 424 is connected to the drive wheel 426 to drive the drive wheel 426 to rotate around its own axis.

[0008] Preferably, the grinding belt tensioning structure 16 includes a push cylinder 161, a guide post 162, an adapter block 163, a base 164, and a connector 165; The base 164 is connected to the main housing 13, and the connector 165 is connected to a motor fixing housing 17 that accommodates the front motor drive wheel 18. The output end of the push cylinder 161 is connected to the connector 165 through the adapter block 163, and is used to drive the motor fixing housing 17 and the front motor drive wheel 18 to move, so as to achieve tensioning of the grinding belt 19. Guide posts 162 are provided on the sides of the push cylinder 161 and the adapter block 163.

[0009] Preferably, the polishing belt 19 has a plurality of detachable friction blocks 191 distributed on it, and the friction blocks 191 are connected to the polishing belt 193 by quick-connect buckles 192.

[0010] Preferably, the main frame 46 of the clamping moving mechanism 4 is provided with a rotating disk device 464, and the clamping wall 41 is hinged to the rotating disk device 464. The cylinder body of the push cylinder 44 is hinged to the main frame 46 via cylinder lug 463.

[0011] Preferably, the power unit is a front power unit 42 and a rear power unit 43.

[0012] Preferably, the centralized-distributed control system includes a centralized unit and multiple distributed units; The centralized unit is configured to dynamically map the nonlinear system of the cleaning mechanism to a high-dimensional linear space using the Koopman operator theory, and run the nonlinear model predictive control (MPC) algorithm to generate global optimization control commands. The distributed unit, connected to the sensors of the grinding mechanism 1, cylinder 2, and clamping moving mechanism 4, is configured to receive instructions from the centralized unit and is responsible for real-time control of the local actuator, critical state estimation, and local disturbance handling.

[0013] In a second aspect, the present invention provides a control method for the pipe outer wall cleaning mechanism described in the first aspect, comprising the following steps: S1: The centralized-distributed control system establishes a parameterized nonlinear dynamic model of the pipeline outer wall cleaning mechanism; S2: Construct a state boosting and linear predictor. The original state vector x of the system is mapped to a high-dimensional linear space using a nonlinear boosting function ψ(x), resulting in the boosted state vector z=ψ(x). A linear Koopman prediction model is then learned using the Extended Dynamic Mode Decomposition (EDMD) method. Constructing a linear prediction model ; in ; u To control the input vector, A and B are Koopman operator matrices; The original state vector x includes the velocity v and steering angle θ from the power unit of the clamping moving mechanism (4), the angular velocity ω of the grinding head from the drive motor of the grinding mechanism (1), and the tension T from the grinding belt tensioning structure (16); System original state vector ; The control input vector u includes the driving force command F output to the travel motor (424) in the power unit of the clamping moving mechanism (4). drive The steering torque command τ is output to its steering motor (425). steer and the tool torque command τ output to the drive motor of the grinding mechanism (1) tool ; Control input ; S3: Within each control cycle, based on the linear Koopman prediction model, solve the rolling optimization problem under preset constraints, and output the optimal control command u( for the current control cycle). k To the implementing agency; The control unit of the centralized-distributed control system is composed of a programmable logic controller (PLC). The PLC acts as the master station and exchanges data and issues commands in real time with each slave station (including drivers and sensor interface modules) through a fieldbus network based on the MODBUS protocol, forming a low-level field control network to realize the synchronous control and data acquisition of the grinding mechanism and the clamping moving mechanism.

[0014] S4: Calculate the model-based prediction output C z ( k ) and actual sensor measurement output y ( k Prediction error between ) e (k)=y( k )- C z (k); if the prediction error e ( k If the norm of a given matrix exceeds a set threshold, the Koopman operator matrices A and B are updated online.

[0015] The calculation of the prediction error e(k), the threshold judgment, and the update logic of matrices A and B can be completed on the host computer. The updated matrix parameters are sent to the PLC control unit in real time through the industrial Ethernet communication, thereby updating the linear Koopman prediction model online and realizing adaptive control.

[0016] The solution to the rolling optimization problem, the online update of the Koopman operator matrix (step S4), and the historical and real-time state data x(k) and control commands u(k) required for prediction error calculation are all efficiently transmitted bidirectionally between the PLC control unit and the host computer via industrial Ethernet. The host computer is responsible for running advanced control algorithms, data storage, model updates, and the visual monitoring interface, while the PLC is responsible for real-time logic control, field device driving, and safety interlocks.

[0017] Preferably, the nonlinear dynamic model established in step S1 includes: Dynamic model of the drive mechanism: Steering mechanism dynamics model: Dynamic model of grinding mechanism speed control: And the dynamic model of the tensioning system: ; in, m For quality, v For speed, F drive As the driving force, F friction For friction, F torsion For torsional force, F process For operational resistance; J i For rotational inertia, f iFor steering angle, t isteer For steering torque, t ifriction For frictional torque, t interaction For interactive torque; I tool To measure the rotational inertia of the grinding head, oh Angular velocity, t tool For tool torque, t load For load torque; T For tension, k This is the stiffness coefficient. c Δ is the damping coefficient. x For displacement, Δ For speed.

[0018] Preferably, the preset constraints in step S3 include: Actuator limiting constraints: ; Controlling smoothness constraints: ; Tension safety constraints: ; in, i To predict the number of steps in the time domain.

[0019] Preferably, in step S4, a forgetting factor is applied. Least Squares (RLS) method for updating the matrix A and B .

[0020] The beneficial effects achieved by this invention are as follows: 1. High adaptability and versatility: Through the lever-type clamping mechanism consisting of a rotatable clamping wall and a push cylinder, as well as the power unit that can rotate as a whole, this device can reliably clamp and adhere to the outer wall of pipes of different diameters, and realize multi-degree-of-freedom movement along the axial direction (linear travel) and circumferential direction (rotational cleaning) of the pipe, thereby adapting to the outer wall cleaning needs of complex pipeline systems.

[0021] 2. Stable and efficient cleaning quality: The automatically tensioned grinding belt mechanism ensures that the grinding belt maintains appropriate tension under different working conditions. Combined with quickly replaceable modular friction blocks, the optimal grinding tool can be selected for different contaminants. The centralized-distributed control system ensures uniform cleaning intensity and complete coverage by adjusting grinding pressure, travel speed, and steering angle in real time, significantly improving the consistency of cleaning efficiency and quality.

[0022] 3. High Intelligence and Robustness: The innovative centralized-distributed control architecture combines high-level global optimization decision-making with low-level rapid distributed execution, resulting in a swift response. In particular, the nonlinear model predictive control (MPC) method based on the Koopman operator maps complex nonlinear system dynamics into a linear model for optimal control, solving the control challenges of strong nonlinearity and strong coupling in pipeline cleaning. The online adaptive update mechanism (RLS) can correct model errors in real time, making the system highly robust to time-varying disturbances such as changes in pipeline surface friction coefficient and load fluctuations. Attached Figure Description

[0023] Figure 1 This is an overall structural diagram of the adaptive portable pipe wall cleaning mechanism applicable to different pipe diameters of the present invention.

[0024] Figure 2 This is a partially enlarged structural schematic diagram of the grinding mechanism of the present invention.

[0025] Figure 3 This is a partially enlarged structural schematic diagram of the grinding belt of the present invention.

[0026] Figure 4 This is a partially enlarged schematic diagram of the tensioning structure of the grinding belt of the present invention.

[0027] Figure 5 This is a partially enlarged structural schematic diagram of the scanning device of the present invention.

[0028] Figure 6 This is a schematic diagram of the clamping and moving mechanism of the present invention.

[0029] Figure 7 This is a schematic diagram of the internal structure of the power unit of the present invention.

[0030] Figure 8 This is a schematic diagram of the main framework of the present invention.

[0031] Figure 9 This is a block diagram illustrating the principle of the centralized-distributed control system architecture of the present invention.

[0032] Figure 10 This is a flowchart of the control method of the present invention. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the following embodiments.

[0034] Unless otherwise defined, the technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0035] Example 1 An adaptive portable pipe wall cleaning mechanism suitable for different pipe diameters includes a grinding mechanism 1, a cylinder 2, a scanning device 3, a clamping and moving mechanism 4, and a centralized-distributed control system. The clamping and moving mechanism 4 constitutes the main frame and walking platform of the mechanism; the grinding mechanism 1 is fixedly connected to the clamping and moving mechanism 4 via a fixed shaft 15; the cylinder body end of the cylinder 2 is connected to the clamping and moving mechanism 4, and its push rod end is hinged to the pressing shaft 11 of the grinding mechanism 1, used to drive the grinding mechanism 1 to press against or away from the outer wall of the pipe; the scanning device 3 is set outside the clamping and moving mechanism 4 and connected to the centralized-distributed control system carried by the clamping and moving mechanism 4, used to scan the cleanliness of the outer wall of the pipe; the centralized-distributed control system is communicatively connected to the sensors and actuators of the grinding mechanism 1 and the clamping and moving mechanism 4, respectively, configured to receive instructions from the centralized unit, and be responsible for real-time distributed control of the grinding drive and tension control of the grinding mechanism 1, the clamping force and multi-degree-of-freedom movement of the clamping and moving mechanism 4, while handling local disturbances and performing critical state estimation; The grinding mechanism 1 includes a clamping shaft 11, a centrally located electric drive wheel 12, a main housing 13, a rearly located electric drive wheel 14, a fixed shaft 15, a grinding belt 19, and a grinding belt tensioning structure 16. The grinding belt 19 is wrapped around the centrally located electric drive wheel 12, the rearly located electric drive wheel 14, and the frontly located electric drive wheel 18. The grinding belt tensioning structure 16 is connected to the frontly located electric drive wheel 18 and is used to drive the frontly located electric drive wheel 18 to move so that the grinding belt 19 remains taut. The clamping and moving mechanism 4 includes a clamping wall 41 for clamping the pipe, a clamping push cylinder 44 for driving the clamping wall 41, and at least one power unit. The clamping wall 41 is hinged to the main frame 46 of the clamping and moving mechanism 4. The cylinder end of the clamping push cylinder 44 is hinged to the main frame 46, and its push rod end is connected to the clamping wall 41, forming a lever-type clamping drive structure. The power unit includes a power unit frame 421, a drive wheel 426, a travel motor 424, and a steering motor 425. The power unit frame 421 is fixed to the main frame 46. The drive wheel 426 is mounted on a cross roller 422 with an external gear. The steering motor 425 meshes with the external gear of the cross roller 422 through a drive gear 423 to drive the drive wheel 426 to change direction. The travel motor 424 is connected to the drive wheel 426 to drive the drive wheel 426 to rotate around its own axis.

[0036] The grinding belt tensioning structure 16 includes a push cylinder 161, a guide post 162, an adapter block 163, a base 164, and a connector 165; The base 164 is connected to the main housing 13, and the connector 165 is connected to a motor fixing housing 17 that accommodates the front motor drive wheel 18. The output end of the push cylinder 161 is connected to the connector 165 through the adapter block 163, and is used to drive the motor fixing housing 17 and the front motor drive wheel 18 to move, so as to achieve tensioning of the grinding belt 19. Guide posts 162 are provided on the sides of the push cylinder 161 and the adapter block 163.

[0037] The polishing belt 19 has several detachable friction blocks 191 distributed on it, and the friction blocks 191 are connected to the polishing belt 193 by quick-connect buckles 192.

[0038] The main frame 46 of the clamping moving mechanism 4 is provided with a rotating disk device 464, and the clamping wall 41 is hinged to the rotating disk device 464. The cylinder body of the push cylinder 44 is hinged to the main frame 46 via cylinder lug 463.

[0039] The power units are a front power unit 42 and a rear power unit 43.

[0040] The centralized-distributed control system includes a centralized unit and multiple distributed units; The centralized unit is configured to dynamically map the nonlinear system of the cleaning mechanism to a high-dimensional linear space using the Koopman operator theory, and run the nonlinear model predictive control (MPC) algorithm to generate global optimization control commands. The distributed unit, connected to the sensors of the grinding mechanism 1 and the clamping moving mechanism 4, is configured to receive instructions from the centralized unit and is responsible for the real-time control of the local actuator, critical state estimation, and local disturbance processing.

[0041] Example 2 A control method for the pipe outer wall cleaning mechanism described in Embodiment 1 includes the following steps: S1: The centralized-distributed control system establishes a parameterized nonlinear dynamic model of the pipeline outer wall cleaning mechanism; S2: Construct a state boosting and linear predictor. The original state vector x of the system is mapped to a high-dimensional linear space using a nonlinear boosting function ψ(x), resulting in the boosted state vector z=ψ(x). A linear Koopman prediction model is then learned using the Extended Dynamic Mode Decomposition (EDMD) method. Constructing a linear prediction model ; in ; u is the control input vector, and A and B are Koopman operator matrices; The original state vector x includes the velocity v and steering angle θ from the power unit of the clamping moving mechanism (4), the angular velocity ω of the grinding head from the drive motor of the grinding mechanism (1), and the tension T from the grinding belt tensioning structure (16); System original state vector ; The control input vector u includes the driving force command F output to the travel motor (424) in the power unit of the clamping moving mechanism (4). drive The steering torque command τ is output to its steering motor (425). steer and the tool torque command τ output to the drive motor of the grinding mechanism (1) tool ; Control input ; S3: In each control cycle, based on the linear Koopman prediction model, solve the rolling optimization problem under the condition of satisfying the preset constraints, and output the optimal control command u(k) of the current control cycle to the actuator. The control unit of the centralized-distributed control system is composed of a programmable logic controller (PLC). The PLC acts as the master station and exchanges data and issues commands to each slave station in real time through a fieldbus network based on the MODBUS protocol, forming a low-level field control network to realize the synchronous control and data acquisition of the grinding mechanism and the clamping moving mechanism.

[0042] S4: Calculate the prediction error e(k) = y(k) - Cz(k) between the model-based predicted output Cz(k) and the actual sensor measurement output y(k); if the norm of the prediction error e(k) exceeds the set threshold, then update the Koopman operator matrices A and B online.

[0043] The calculation of the prediction error e(k), the threshold judgment, and the update logic of matrices A and B can be completed on the host computer. The updated matrix parameters are sent to the PLC control unit in real time through the industrial Ethernet communication, thereby updating the linear Koopman prediction model online and realizing adaptive control.

[0044] The solution to the rolling optimization problem, the online update of the Koopman operator matrix (step S4), and the historical and real-time state data x(k) and control commands u(k) required for prediction error calculation are all efficiently transmitted bidirectionally between the PLC control unit and the host computer via industrial Ethernet. The host computer is responsible for running advanced control algorithms, data storage, model updates, and the visual monitoring interface, while the PLC is responsible for real-time logic control, field device driving, and safety interlocks.

[0045] The nonlinear dynamic model established in step S1 includes: Dynamic model of the drive mechanism: Steering mechanism dynamics model: Dynamic model of grinding mechanism speed control: And the dynamic model of the tensioning system: ; in, m For quality, v For speed, F drive As the driving force, F friction For friction, F torsion For torsional force, F process For operational resistance; J i For rotational inertia, f i For steering angle, t isteer For steering torque, t ifriction For frictional torque, t interaction For interactive torque; I tool To measure the rotational inertia of the grinding head, oh Angular velocity, t tool For tool torque, t load For load torque; T For tension, k This is the stiffness coefficient. c Δ is the damping coefficient. x For displacement, Δ For speed.

[0046] The preset constraints mentioned in step S3 include: Actuator limiting constraints: ; Controlling smoothness constraints: ; Tension safety constraints: ; in, i To predict the number of steps in the time domain.

[0047] In step S4, the forgetting factor is applied. Least Squares (RLS) method for updating the matrix A and B .

[0048] It is understood that those skilled in the art can make equivalent substitutions or modifications to the technical solution and inventive concept of the present invention, and all such substitutions or modifications should fall within the protection scope of the appended claims.

Claims

1. A self-adapting portable pipe external wall cleaning mechanism suitable for different pipe diameters, characterized in that, It includes a grinding mechanism (1), a cylinder (2), a scanning device (3), a clamping and moving mechanism (4), and a centralized-distributed control system; The clamping and moving mechanism (4) constitutes the main frame and walking platform of the mechanism; the grinding mechanism (1) is fixedly connected to the clamping and moving mechanism (4) through the fixed shaft (15); the cylinder body end of the cylinder (2) is connected to the clamping and moving mechanism (4), and its push rod end is hinged to the pressing shaft (11) of the grinding mechanism (1), which is used to drive the grinding mechanism (1) to press against or away from the outer wall of the pipe; the scanning device (3) is set outside the clamping and moving mechanism (4) and connected to the centralized-distributed control system carried by the clamping and moving mechanism (4), which is used to scan the cleanliness of the outer wall of the pipe; the centralized-distributed control system is respectively connected to the sensors and actuators of the grinding mechanism (1) and the clamping and moving mechanism (4); The grinding mechanism (1) includes a clamping shaft (11), a central electric drive wheel (12), a main housing (13), a rear electric drive wheel (14), a fixed shaft (15), a grinding belt (19), and a grinding belt tensioning structure (16); the grinding belt (19) is wrapped around the central electric drive wheel (12), the rear electric drive wheel (14), and the front motor drive wheel (18); the grinding belt tensioning structure (16) is connected to the front motor drive wheel (18); The clamping and moving mechanism (4) includes a clamping wall (41) for clamping the pipe, a clamping push cylinder (44) for driving the clamping wall (41) to move, and at least one power unit; the clamping wall (41) is hinged to the main frame (46) of the clamping and moving mechanism (4), the cylinder end of the clamping push cylinder (44) is hinged to the main frame (46), and its push rod end is connected to the clamping wall (41), forming a lever-type clamping drive structure; the power unit includes a power unit frame (421). The unit includes a drive wheel (426), a walking motor (424), and a steering motor (425). The power unit frame (421) is fixed on the main frame (46). The drive wheel (426) is mounted on a cross roller (422) with an external gear. The steering motor (425) meshes with the external gear of the cross roller (422) through a drive gear (423) to drive the drive wheel (426) to change direction as a whole. The walking motor (424) is connected to the drive wheel (426) in a transmission connection.

2. The self-adapting portable pipe external wall cleaning mechanism suitable for different pipe diameters according to claim 1, characterized in that, The grinding belt tensioning structure (16) includes a push cylinder (161), a guide column (162), an adapter block (163), a base (164), and a connector (165). The base (164) is connected to the main housing (13), and the connector (165) is connected to a motor mounting housing (17) that accommodates the front motor drive wheel (18). The output end of the push cylinder (161) is connected to the connector (165) through the adapter block (163) to drive the motor fixing housing (17) and the front motor drive wheel (18) to move, so as to achieve tensioning of the grinding belt (19); The push cylinder (161) and the adapter block (163) are provided with guide posts (162) on their sides.

3. The self adaptive portable pipe external wall cleaning mechanism suitable for different pipe diameters as claimed in claim 1 wherein, The grinding belt (19) has several detachable friction blocks (191) distributed on it, and the friction blocks (191) are connected to the grinding belt (193) by quick-connect buckles (192).

4. The adaptive portable pipe wall cleaning mechanism suitable for different pipe diameters according to claim 1, characterized in that, The main frame (46) of the clamping moving mechanism (4) is provided with a rotating disk device (464), and the clamping wall (41) is hinged to the rotating disk device (464). The cylinder body of the push cylinder (44) is hinged to the main frame (46) via cylinder lugs (463).

5. The adaptive portable pipe wall cleaning mechanism suitable for different pipe diameters according to claim 1, characterized in that, The power unit consists of a front power unit (42) and a rear power unit (43).

6. The adaptive portable pipe wall cleaning mechanism suitable for different pipe diameters according to claim 1, characterized in that, The centralized-distributed control system includes a centralized unit and multiple distributed units; The centralized unit is configured to dynamically map the nonlinear system of the cleaning mechanism to a high-dimensional linear space using the Koopman operator theory, and run a nonlinear model predictive control algorithm to generate global optimization control commands. The dynamic model includes a drive mechanism dynamic model, a steering mechanism dynamic model, a grinding mechanism speed control dynamic model, and a tensioning system dynamic model. The distributed unit is connected to the sensors of the grinding mechanism (1), cylinder (2), and clamping moving mechanism (4), and is configured to receive instructions from the centralized unit and be responsible for the real-time control of the local actuator, critical state estimation and local disturbance processing.

7. A control method for a pipe outer wall cleaning mechanism according to any one of claims 1 to 6, characterized in that, Includes the following steps: S1: The centralized-distributed control system establishes a parameterized nonlinear dynamic model of the pipeline outer wall cleaning mechanism; S2: Construct a state lifting and linear predictor, utilizing a nonlinear lifting function. ψ ( x The original state vector x of the system is mapped to a high-dimensional linear space to obtain the boosted state vector. z = ψ ( x And learn a linear Koopman prediction model by using the Extended Dynamic Mode Decomposition (EDMD) method: Constructing a linear prediction model ; in ; u is the control input vector, and A and B are Koopman operator matrices; The original state vector x includes the velocity v and steering angle θ from the power unit of the clamping moving mechanism (4), the angular velocity ω of the grinding head from the drive motor of the grinding mechanism (1), and the tension T from the grinding belt tensioning structure (16); System original state vector ; The control input vector u includes a drive force command F output to a walking motor (424) in a power unit of the clamping moving mechanism (4) drive , a steering torque command τ output to a steering motor (425) thereof steer , and a tool torque command τ output to a driving motor of the polishing mechanism (1) tool ; Control input ; S3: In each control cycle, based on the linear Koopman prediction model, solve the rolling optimization problem under the condition of satisfying the preset constraints, and output the optimal control command u(k) of the current control cycle to the actuator. S4: Calculate the prediction error e(k) = y(k) - Cz(k) between the model-based predicted output Cz(k) and the actual sensor measurement output y(k); if the norm of the prediction error e(k) exceeds the set threshold, then update the Koopman operator matrices A and B online.

8. The control method for the pipe outer wall cleaning mechanism according to claim 7, characterized in that, The nonlinear dynamic model established in step S1 includes: Dynamic model of the drive mechanism: Steering mechanism dynamics model: Dynamic model of grinding mechanism speed control: And the dynamic model of the tensioning system: ; in, m For quality, v For speed, F drive As the driving force, F friction For friction, F torsion For torsional force, F process For operational resistance; J i For rotational inertia, φ i For steering angle, τ isteer For steering torque, τ ifriction For frictional torque, τ interaction For interactive torque; I tool To measure the rotational inertia of the grinding head, ω Angular velocity, τ tool For tool torque, τ load For load torque; T For tension, k This is the stiffness coefficient. c Δ is the damping coefficient. x For displacement, Δ For speed.

9. The control method for the pipe outer wall cleaning mechanism according to claim 7, characterized in that, The preset constraints mentioned in step S3 include: Actuator limiting constraints: ; Controlling smoothness constraints: ; Tension safety constraints: ; in, i To predict the number of steps in the time domain.

10. The control method for the pipe outer wall cleaning mechanism according to claim 7, characterized in that, In step S4, the forgetting factor is applied. Least squares update matrix A and B .

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