Machine Vision-Based Oil and Gas Pipeline Inspection Robot
DOI:
https://doi.org/10.62051/ijcsit.v8n1.13Keywords:
Petroleum and natural gas, Pipelines, Robots, Machine visionAbstract
Pipeline transportation is currently the main method for large-scale, long-distance transport of oil and natural gas. As the service life increases, the risk of pipeline leaks also gradually rises. Oil and gas pipeline inspection, as a key link in pipeline integrity, can provide a scientific basis for the prevention and maintenance of pipeline accidents. Pipeline robots play an important role in pipeline inspection, as they can enter complex pipeline environments to carry out tasks such as inspection, cleaning, and maintenance. At the same time, with the development of artificial intelligence, machine vision technology is widely applied in pipeline inspection. This paper provides a comprehensive review of pipeline inspection robots based on machine vision, including mechanical structures and visual inspection methods, and analyzes and compares their performance characteristics. It summarizes the factors limiting their development and proposes solutions, providing a reference for the further development of machine vision-based oil and gas pipeline inspection robots.
Downloads
References
[1] Li Qiuyang, Zhao Minghua, Zhang Bin, et al. Current Status and Development Trends of Global Oil and Gas Pipeline Construction in 2020 [J]. Oil & Gas Storage and Transportation, 2021, 40(12):1330-1337, 1348.
[2] Gao Zhenyu, Zhang Huiyu, Gao Peng. New Developments in China's Oil and Gas Pipeline Construction in 2022 [J]. International Petroleum Economics, 2023, 31(03):16-23.
[3] Pan J, Gao L. A novel method for defects marking and classifying in MFL inspection of pipeline [J]. International Journal of Pressure Vessels and Piping, 2023, 202: 104892.
[4] Yin F. Inspection robot for submarine pipeline based on machine vision [C]//Journal of Physics: Conference Series. IOP Publishing, 2021, 1952(2): 022034.
[5] Karthik C H, Sreedharan P. Design and Development of Pipe-inspection robot with vision 360°[C]//Journal of Physics: Conference Series. IOP Publishing, 2021, 2062(1): 012015.
[6] Lyu C, Zhang M, Li B, et al. High reliability pipeline leakage detection based onmachine vision in complex industrial environment [J]. IEEE Sensors Journal, 2022, 22(21): 20748-20760.
[7] Piciarelli C, Avola D, Pannone D, et al. A vision-based system for internal pipeline inspection [J]. IEEE Transactions on Industrial Informatics, 2018, 15(6): 3289-3299.
[8] Jiang Ye. Current Status and Prospects of Machine Vision Technology in Oilfield Applications [J]. Contemporary Petroleum & Petrochemicals, 2021, 29(01):44-48.
[9] Ren Tao. Research on Helical-Drive Pipeline Robots [D]. Southwest Petroleum University, 2020.
[10] Ab Rashid M Z, Yakub M F M, bin Shaikh Salim S A Z, et al. Modeling of the in-pipe inspection robot: A comprehensive review [J]. Ocean Engineering, 2020, 203: 107206.
[11] Song Z, Luo Y. Research Status and Development Trend of Oil and Gas PipelineRobot [J]. Academic Journal of Science and Technology, 2022, 3(3): 134-140.
[12] Liu Qingyou. Current Status and Development Trends of Oil and Gas Pipeline Robot Technology [J]. Journal of Xihua University (Natural Science Edition), 2016, 35(01): 1-6.
[13] Kahnamouei J T, Moallem M. A comprehensive review of in-pipe robots [J]. Ocean Engineering, 2023, 277: 114260.
[14] Jang H, Kim T Y, Lee Y C, et al. A review: technological trends and development direction of pipeline robot systems [J]. Journal of Intelligent & Robotic Systems, 2022, 105(3): 59.
[15] Hongwei Y, Yang W, Jianqiang M. Analysis of dynamic characteristics of wheeled pipe robot in bending [J]. Journal of Xi'an Jiaotong University, 2018, 52: 87-94.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 International Journal of Computer Science and Information Technology
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
