Design of Control System for Underwater Inspection Robot in Hydropower Dam Structures

As critical infrastructure, hydropower dams require efficient and accurate detection of underwater structural surface defects to ensure their safety. This paper presents the design and implementation of a robotic control system specifically developed for underwater dam inspection in hydropower stations, aiming to enhance the robot’s operational capability under harsh hydraulic conditions. The study includes the hardware design of the control system and the development of a surface human–machine interface unit. At the software level, a modular architecture is adopted to ensure real-time performance and reliability. The solution employs a hierarchical architecture comprising hardware sensing, real-time interaction protocols, and an adaptive controller, and the integrated algorithm combining a fixed-time disturbance observer with adaptive super-twisting controller compensates for complex hydrodynamic forces. To validate the system’s effectiveness, field tests were conducted at the Baihetan Hydropower Station. Experimental results demonstrate that the proposed control system enables stable and precise dam inspection, with standard deviations of multi-degree-of-freedom automatic control below 0.5 and hovering control below 0.1. These findings confirm the system’s feasibility and superiority in performing high-precision, high-stability inspection tasks in complex underwater environments of real hydropower dams. The developed system provides reliable technical support for intelligent underwater dam inspection and holds significant practical value for improving the safety and maintenance of major hydraulic infrastructure.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-08-29
DOI
https://doi.org/10.3390/jmse13091656
Citations
1
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.82

Funders

Controls
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article

Design of Control System for Underwater Inspection Robot in Hydropower Dam Structures

Xin‐Yao Yu, Zhaoxu Meng, Shuo Li, Bing Zhao et al.
1 citations
Journal of Marine Science and Engineering
Water Quality Monitoring Technologies
0.82
article

Design of Control System for Underwater Inspection Robot in Hydropower Dam Structures

Xin‐Yao Yu, Zhaoxu Meng, Shuo Li, Bing Zhao, Xiangbin Wang, Mingyu Yang, Gang Wan
article en
1 citations

Abstract

As critical infrastructure, hydropower dams require efficient and accurate detection of underwater structural surface defects to ensure their safety. This paper presents the design and implementation of a robotic control system specifically developed for underwater dam inspection in hydropower stations, aiming to enhance the robot’s operational capability under harsh hydraulic conditions. The study includes the hardware design of the control system and the development of a surface human–machine interface unit. At the software level, a modular architecture is adopted to ensure real-time performance and reliability. The solution employs a hierarchical architecture comprising hardware sensing, real-time interaction protocols, and an adaptive controller, and the integrated algorithm combining a fixed-time disturbance observer with adaptive super-twisting controller compensates for complex hydrodynamic forces. To validate the system’s effectiveness, field tests were conducted at the Baihetan Hydropower Station. Experimental results demonstrate that the proposed control system enables stable and precise dam inspection, with standard deviations of multi-degree-of-freedom automatic control below 0.5 and hovering control below 0.1. These findings confirm the system’s feasibility and superiority in performing high-precision, high-stability inspection tasks in complex underwater environments of real hydropower dams. The developed system provides reliable technical support for intelligent underwater dam inspection and holds significant practical value for improving the safety and maintenance of major hydraulic infrastructure.

Journal of Marine Science and EngineeringVol. 13(9)
Shenyang Institute of Automation (CN), University of Chinese Academy of Sciences (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 23%
Water Quality Monitoring Technologies
0.82
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