Development of a Pipeline-Cleaning Robot for Heat-Exchanger Tubes
Abstract
:1. Introduction
- (1)
- The stability and adaptability of robot motion in confined pipelines are still limited, often resulting in slippage or jamming;
- (2)
- Due to variations in pipe diameter and spatial constraints, existing cleaning mechanisms often fail to reach and effectively clean the deep or branched regions of heat-exchanger tubes;
- (3)
- Many current systems lack real-time sensing and feedback control, making precise alignment and autonomous operation difficult to achieve.
2. Robot Structural Design
2.1. Mechanical Structure Design
2.2. Working Principle
3. Kinematic Analysis
- Force (): Newton (N).
- Mass (): kilogram (kg).
- Acceleration (): meters per second squared (m/s2).
- Velocity (): meters per second (m/s).
- Torque (): Newton meter (N·m).
- Radius/diameter (, ): meter (m).
- Pressure (): Pascal (Pa).
- Area (): square meter (m2).
- Angular velocity (): revolutions per minute (rpm), unless otherwise stated.
- Friction coefficient (), efficiency (), and safety factor (): dimensionless.
3.1. Drive-Mechanism Analysis
- is the friction coefficient between the wheel group and the inner wall of the pipeline (set as 0.35 in this study, based on typical engineering values for steel–rubber contact);
- is the total mass of the robot (approximately 25 kg, measured by weighing);
- is the gravitational acceleration (9.81 m/s2);
- is the inclination angle of the pipeline (default is 0°, but retained as a variable to account for extreme conditions);
- is the linear acceleration of the robot during startup or speed transitions (determined by actual control parameters).
3.2. Propulsion Mechanism Analysis
3.3. Alignment Mechanism Analysis
4. Control System Design
4.1. Overall Design of the Control System
- Modular control architecture with decoupled subsystems improves fault tolerance;
- Vision-based feedback dynamically corrects robot drift and localization errors inside the pipe;
- Independent and redundant circuit layouts for driving and control, including overload protection and physical limit switches;
- A state recognition and task-switching mechanism is embedded in the control logic to prevent malfunctions caused by abnormal data or environmental interference.
4.2. Hardware Design of the Control System
4.3. Software Design of the Control System
- (1)
- Image preprocessing: Grayscale conversion and bilateral filtering are applied to reduce noise while preserving edge features;
- (2)
- Feature extraction: Canny edge detection is performed, followed by morphological operations to enhance structural boundaries;
- (3)
- Geometric localization: Hough circle detection is employed to extract the centers of the brush head and the target sub-pipe for position recognition;
- (4)
- Deviation evaluation and control: The composite deviation is calculated from the center offset and compared with a threshold, . If , the system proceeds to the cleaning phase; otherwise, dual-channel PID controllers output horizontal and vertical correction commands iteratively.
Algorithm 1 Visual-Guided Alignment Algorithm with Closed-Loop Control |
Input: |
Initial pipeline image |
Alignment threshold |
Maximum iterations |
Output: |
Motor control sequence |
1: Initialize: |
2: while and do |
3: Step 1: Image Processing |
4: Detect pipe center |
5: Detect brush head center |
6: Calculate deviations: |
7: Compute total deviation: |
8: Step 2: Horizontal Alignment |
9: if then |
10: Horizontal control |
11: if then |
12: |
13: else |
14: |
15: end if |
16: end if |
17: Step 3: Vertical Alignment |
18: if then |
19: Horizontal control |
20: if then |
21: |
22: else |
23: |
24: end if |
25: end if |
26: Update image: |
27: |
28: end while |
29: if then |
30: |
31: else |
32: |
33: Error recovery starts |
34: Reset actuators to default state |
35: Log current position and trigger fallback protocol |
36: Notify operator or retry alignment in next cycle |
37: end if |
5. Experimental Results and Discussion
5.1. Simulated Mobility Experiment for the Primary Pipeline to Be Cleaned
5.2. Simulated Cleaning Experiment for the Secondary Pipeline
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
SoC | System on Chip |
UART | Universal Asynchronous Receiver/Transmitter |
GPIO | General-Purpose Input/Output |
EMAC | Ethernet Media Access Controller |
DSP | Digital Signal Processor |
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Symbol | Description | Mathematical Definition |
---|---|---|
Initial image | RGB image matrix | |
Alignment threshold | Position tolerance | |
Max iterations | Positive integer | |
Pipe center | Detected by Hough transform | |
Brush head center | Feature matching coordinates | |
Horizontal deviation | ||
Vertical deviation | ||
Total deviation | ||
Iteration counter | ||
Control commands | Set of motor commands | |
PID() | Control function |
Switching Case | Group 1 (s) | Group 2 (s) | Group 3 (s) | Mean (s) | Std Dev (s) |
---|---|---|---|---|---|
Tube 2 → 3 | 15 | 13 | 16 | 14.67 | 1.53 |
Tube 3 → 4 | 14 | 12 | 11 | 12.33 | 1.53 |
Tube 4 → 5 | 21 | 17 | 17 | 18.33 | 2.31 |
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Liu, Q.; Li, C.; Wang, G.; Li, L.; Wang, J.; Tan, J.; Wu, Y. Development of a Pipeline-Cleaning Robot for Heat-Exchanger Tubes. Electronics 2025, 14, 2321. https://doi.org/10.3390/electronics14122321
Liu Q, Li C, Wang G, Li L, Wang J, Tan J, Wu Y. Development of a Pipeline-Cleaning Robot for Heat-Exchanger Tubes. Electronics. 2025; 14(12):2321. https://doi.org/10.3390/electronics14122321
Chicago/Turabian StyleLiu, Qianwen, Canlin Li, Guangfei Wang, Lijuan Li, Jinrong Wang, Jianping Tan, and Yuxiang Wu. 2025. "Development of a Pipeline-Cleaning Robot for Heat-Exchanger Tubes" Electronics 14, no. 12: 2321. https://doi.org/10.3390/electronics14122321
APA StyleLiu, Q., Li, C., Wang, G., Li, L., Wang, J., Tan, J., & Wu, Y. (2025). Development of a Pipeline-Cleaning Robot for Heat-Exchanger Tubes. Electronics, 14(12), 2321. https://doi.org/10.3390/electronics14122321