Research progress on remotely operated vehicle technology for underwater inspection of large hydropower dams

XU Pengfei; CHEN Meiya; KAI Yan; WANG Zipeng; LI Xinyu; WAN Gang; WANG Yanjie

doi:10.16511/j.cnki.qhdxxb.2023.26.018

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Journal of Tsinghua University(Science and Technology) ›› 2023, Vol. 63 ›› Issue (7) : 1032-1040. DOI: 10.16511/j.cnki.qhdxxb.2023.26.018

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Research progress on remotely operated vehicle technology for underwater inspection of large hydropower dams

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Abstract

[Significance] China uses a large amount of hydropower, and the safety of hydropower dams is related to the safety of people's lives, properties, and the national economy. Therefore, regular inspection of dam defects in large hydropower plants is vital to ensure their safe operation. Most of the common dam defects, such as cracks and leakage, originate from the surface of the structure and can affect the service life of the dams. In recent years, remotely operated vehicles (ROVs) have been used for the underwater inspection of dam defects in hydropower plants, as they can mitigate many disadvantages associated with manual inspections while improving detection accuracy and efficiency. [Progress] Thus, we explore the environmental conditions of dams and the main content of dam defect inspection in hydropower plants and review the research on ROV application for underwater inspection in large hydropower dams. We find that different sensors can be combined with ROVs to inspect large hydropower dams underwater according to detection and operation needs. The method can achieve intelligent mobile inspection and remote control of dam operation safety, automatically identify dam defect characteristics, and store shore-station interactive information. At present, ROVs are less used for inspecting dam defects in large hydropower plants but are widely used in fields such as deep-sea exploration, undersea operations, and rescue assistance. The use of ROVs for crack and leakage inspection in hydropower plants has tremendous advantages. The research on using ROVs for the intelligent inspection of other structures has certain implications for developing ROVs for the intelligent underwater inspection of large hydropower dams. We analyze the progress of ROV technology in domestic and international research on hydropower engineering in terms of the overall technology, underwater absorber, power system, inspection technology, underwater positioning, and control system. Moreover, we explore the modular design and overall scale optimization of ROVs for underwater inspection in large hydropower dams, with the design objectives of lightweight, high stability, and high anti-current and anti-disturbance capability. Thrusters with high propulsion ratios have been developed to ensure high ROV power. Adsorbers have been added to the ROV systems to control the hovering of ROVs, which can also improve their underwater anti-disturbance ability to ensure stable detection and operation. Acoustic-optical inspection technology has been proposed to improve detection accuracy, and intelligent algorithms have been used for defect identification and image post-processing. Regarding underwater positioning and control systems, a complementary approach combining information from multiple sensors has been adopted, and the dam defect inspection is validated to improve the operational capability of the ROV movement and inspection. [Conclusions and Prospects] The use of ROVs for underwater inspection in large hydropower dams has major advantages in targeting cracks and other dam defects, and the research on the intelligent inspection of hydropower dams opens up a wide range of prospects.

Key words

remotely operated vehicle / hydropower dams / defect inspection / overall technology / underwater adsorber / acoustic-optical fusion inspection technology / power system / underwater positioning and control system

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XU Pengfei, CHEN Meiya, KAI Yan, WANG Zipeng, LI Xinyu, WAN Gang, WANG Yanjie. Research progress on remotely operated vehicle technology for underwater inspection of large hydropower dams[J]. Journal of Tsinghua University(Science and Technology). 2023, 63(7): 1032-1040 https://doi.org/10.16511/j.cnki.qhdxxb.2023.26.018

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