Development of A Novel Subsea Pipeline Inspection System ‎Using Autonomous Underwater Vehicles

  • Authors

    • Krishna Chittipedhi Department of Nautical Science, AMET University, Kanathur, Tamil Nadu, India
    • Gopal Srinivas Department of Nautical Science, AMET University, Kanathur, Tamil Nadu, India
    https://doi.org/10.14419/wfa00h97

    Received date: May 10, 2025

    Accepted date: May 29, 2025

    Published date: July 8, 2025

  • Subsea; Pipeline Inspection; Autonomous Underwater Vehicles.

  • Abstract

    In inspection, the AUV travels the programmed pipeline path autonomously, capturing water column imagery with MBES, and monitors ‎gas-filled bubbles to evaluate leak hazards. If detected, it surfaces to transmit a satellite alarm to the control center. The AUV is equipped ‎with a variable buoyancy system (VBS) to navigate efficiently and uses online collision avoidance because of the complicated operating ‎environment. Nevertheless, the traditional image segmentation method is inappropriate owing to high noise and bottom reverberation in the ‎operating environment, thus the necessity for alternative methods. An enhanced Otsu algorithm is suggested to increase the denoise effect ‎and operation speed based on the conventional technique. Consequently, an enhanced Otsu method is suggested to precisely detect ‎impediments. To estimate dynamic obstacles, Kalman filtering is also introduced. Pipelines carrying natural gas underground are essential ‎pieces of infrastructure for the delivery of energy. In addition to immediately endangering the ecosystems of lakes and coastal areas, any ‎damage or leak in these pipelines could result in operational problems and financial losses for the energy supply chain. Due to their heavy ‎reliance on divers, which is expensive and ineffective, existing techniques for identifying deterioration and conducting routine inspections of ‎these submerged pipes are still limited. Because of these challenges, unmanned underwater vehicles (UUVs), which provide a more reliable ‎and effective option for pipeline monitoring and repair, are becoming more and more significant in this industry.

  • References

    1. Calvo, O., Sousa, A., Bibiloni, J., Curti, H., Acosta, G., & Rozenfeld, A. (2009). Low-cost autonomous underwater vehicle for underwater acoustic inspections. Journal of Maritime Research, 6(2), 37–52.
    2. Zhang, L., Fernandez, M., & Gupta, P. (2025). Acoustic imaging techniques for underwater infrastructure monitoring: A review. Ocean Engineering, 255, 111726. https://doi.org/10.1016/j.oceaneng.2025.111726
    3. Jacobi, M., & Karimanzira, D. (2013). Underwater pipeline and cable inspection using autonomous underwater vehicles. In 2013 MTS/IEEE OCEANS-Bergen (pp. 1–6). IEEE. https://doi.org/10.1109/OCEANS-Bergen.2013.6608089.
    4. Tarrillo, S. J. S., Rosas, R. G. N., Vásquez, E. J. F., Reyes, E. M. A., Canales, H. B. G., Medina, A. O. B., Luna, R. D. O., & Bulnes, J. L. L. (2024). The impact of internet security awareness among undergraduates in learning management system. Journal of Internet Services and Information Secu-rity, 14(3), 256–264. https://doi.org/10.58346/JISIS.2024.I3.015.
    5. Kartal, S. K., & Cantekin, R. F. (2024). Autonomous underwater pipe damage detection positioning and pipeline tracking experiment with unmanned underwater vehicle. Journal of Marine Science and Engineering, 12(11), 2002. https://doi.org/10.3390/jmse12112002.
    6. Dhayanidhi, G., & Brindha Devi, E. (2024). An examination of consumer knowledge and satisfaction with private sector bank’s e-banking services in Chennai. Indian Journal of Information Sources and Services, 14(3), 226–231. https://doi.org/10.51983/ijiss-2024.14.3.29.
    7. Tang, U., Krezger, H., & LonnerbyRakob. (2024). Design and validation of 6G antenna for mobile communication. National Journal of Antennas and Propagation, 6(1), 6–12. https://doi.org/10.31838/NJAP/06.01.02.
    8. Usikalu, M. R., Alabi, D., & Ezeh, G. N. (2025). Exploring emerging memory technologies in modern electronics. Progress in Electronics and Com-munication Engineering, 2(2), 31–40.
    9. Rumson, A. G. (2021). The application of fully unmanned robotic systems for inspection of subsea pipelines. Ocean Engineering, 235, 109214. https://doi.org/10.1016/j.oceaneng.2021.109214.
    10. Nazari, M., & Attaran Fariman, G. (2022). Unialgal culture of Pseudonitzschia (Bacillariophyceae) species a domoic acid (AD) toxin producer, local of Oman Sea. International Journal of Aquatic Research and Environmental Studies, 2(1), 1–8. https://doi.org/10.70102/IJARES/V2I1/1.
    11. Foresti, G. L. (2001). Visual inspection of sea bottom structures by an autonomous underwater vehicle. IEEE Transactions on Systems, Man, and Cy-bernetics, Part B (Cybernetics), 31(5), 691–705. https://doi.org/10.1109/3477.956031.
    12. Kabirian, M., Sardari, D., & Babapour, F. (2014). Determination of proper neutron beam energy spectrum for penetration depth in liver BNCT. Inter-national Academic Journal of Science and Engineering, 1(2), 17–25.
    13. Ho, M., El-Borgi, S., Patil, D., & Song, G. (2020). Inspection and monitoring systems subsea pipelines: A review paper. Structural Health Monitor-ing, 19(2), 606–645. https://doi.org/10.1177/1475921719837718.
    14. Andy, G. S., Lardeux, M., Gilmour, B., & Ling, D. (2022). Subsea robotics–AUV pipeline inspection development project. In Offshore Technology Conference (p. D021S024R001). OTC. https://doi.org/10.4043/31733-MS.
    15. Zhang, H., Zhang, S., Wang, Y., Liu, Y., Yang, Y., Zhou, T., & Bian, H. (2021). Subsea pipeline leak inspection by autonomous underwater vehicle. Applied Ocean Research, 107, 102321. https://doi.org/10.1016/j.apor.2020.102321.
    16. Hu, S., Feng, R., Wang, Z., Zhu, C., Wang, Z., Chen, Y., & Huang, H. (2022). Control system of the autonomous underwater helicopter for pipeline inspection. Ocean Engineering, 266, 113190. https://doi.org/10.1016/j.oceaneng.2022.113190.
    17. Lucena, K., Luedeke, H. J., & Wirth, T. (2025). The evolution of embedded systems in smart wearable devices: Design and implementation. SCCTS Journal of Embedded Systems Design and Applications, 2(1), 23–35.
    18. Velliangiri, A. (2024). Security challenges and solutions in IoT-based wireless sensor networks. Journal of Wireless Sensor Networks and IoT, 1(1), 8-14. https://doi.org/10.31838/WSNIOT/01.01.02.
    19. Abdullah, D. (2025). Comparative Analysis of SIC and GAN-Based Power Converters in Renewable Energy Systems. National Journal of Electrical Machines & Power Conversion, 11-20.
    20. Smith, J., Wang, H., & Patel, R. (2024). Deep-sea pipeline inspection using hybrid AUV platforms: Challenges and advancements. Journal of Marine Robotics, 58(2), 112-129. https://doi.org/10.1016/j.jmarrob.2024.01.007
    21. Kim, D., & Singh, S. (2025). Energy-efficient navigation strategies for AUVs in pipeline inspection tasks. IEEE Journal of Oceanic Engineering, 50(1), 45-59. https://doi.org/10.1109/JOE.2025.3148790

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  • How to Cite

    Chittipedhi, K. ., & Srinivas, G. . (2025). Development of A Novel Subsea Pipeline Inspection System ‎Using Autonomous Underwater Vehicles. International Journal of Basic and Applied Sciences, 14(SI-1), 185-190. https://doi.org/10.14419/wfa00h97