Key technology and practice of intelligent underwater inspection in multiple scenarios of hydropower station
QI Ningchun1, NIE Qiang1, LAI Jitao1, CHEN Yongcan2, LI Yonglong3
1. Yalong River Hydropower Development Co., Ltd., Chengdu 610051, China; 2. State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China; 3. Sichuan Energy Internet Research Institute, Tsinghua University, Chengdu 610213, China
Abstract：[Objective]Underwater building safety inspection is a vital tool for ensuring reservoir dam operation safety of hydropower stations. Due to the high expense of traditional drainage inspections and the high safety risk of divers performing underwater inspections for areas that cannot be drained, underwater detection technology provides a new solution to underwater building safety inspection. [Methods] Using the Yalong River basin step operation hydropower stations as a typical scenario, the target water environment and structural boundary conditions were analyzed; combined with open water underwater inspection experience and technical differences, underwater robot inspection equipment and essential technology systems under various scenarios of hydropower stations were constructed. Through robot system integration and testing, a small-sized, powerful, multi-sensor fusion cable remote control submersible was developed for tunnel-like structures with lengthy cavern lines. A high-strength, zero buoyancy photoelectric composite umbilical cable with a small diameter was designed, and remote power supply and fiber optic real-time communication were carried out through high-frequency medium voltage transmission technology. The real-time monitoring system for underwater robot movement based on the virtual exercise platform was built, and the robot was directed to return autonomously by an adaptive control algorithm in the case of communication and power supply failure. The combined inertial navigation-based positioning technology was investigated, and the position information, such as structural seams and feature markings detected by sonar and camera, was used to calibrate the inertial guidance positioning information. A high-frequency three-dimensional real-time sonar system with 360° mobility, continuous scanning, and real-time generation of a three-dimensional point cloud model was jointly developed, which improved precise positioning capability and detection efficiency for large cross-sections and long-distance closed structures. The research offers a defect identification technology based on dynamic feature distillation to intelligently identify the inspection images and uses the joint analysis method of inspection information and a 3D digital model to conduct intelligent spatiotemporal correlation analysis of defect information. Intelligent unmanned vessel systems and RTK-GNSS combined positioning technology are introduced for underwater inspection in semi-open waters in high mountain canyon areas. A joint inspection scheme of multibeam sonar and underwater robots is proposed to make full use of the advantages of fast and high-density scanning of multibeam sonar and fine inspection of robots to improve inspection efficiency. [Results] The robot system successfully passed through the access channel with only 2.1 m in diameter, the diversion tunnel with 12.0 m in diameter and 2.30 km in length, and the pressure pipeline with a 250.0 m vertical drop in the practice of normalized underwater inspection of multi-water scenes at Yalong River Basin Hydropower Station. The flaw detection accuracy reached the millimeter level, the plane positioning precision reached 10 cm, and the axial positioning accuracy was better than 1‰ of the traveled distance. The intelligent recognition rate of common defects in concrete structures, such as broken or exposed bars and cracks, reached 96.5%. The intelligent unmanned vessel successfully inspected various types of semi-open waters, such as tailwater channels of hydropower stations with a flow speed of 2 m/s and turbulent flows, obtaining three-dimensional topographic maps of underwater environments and identifying the distribution characteristics of underwater defects with a horizontal positioning accuracy better than ±8 mm+1 ppm and a vertical orientation better than ±15 mm+1 ppm. [Conclusions] The underwater intelligent inspection system features a high degree of innovation and integration, a large number of practical cases, safe and reliable inspection, and accurate and intuitive results. The system has effectively guided the safe operation and maintenance of underwater structures at the Yalong River Basin Hydropower Station and significantly reduced the cost of traditional inspection, which has important significance for industry promotion.
祁宁春, 聂强, 来记桃, 陈永灿, 李永龙. 水电站多元场景水下智能巡检关键技术与实践[J]. 清华大学学报（自然科学版）, 2023, 63(7): 1124-1134.
QI Ningchun, NIE Qiang, LAI Jitao, CHEN Yongcan, LI Yonglong. Key technology and practice of intelligent underwater inspection in multiple scenarios of hydropower station. Journal of Tsinghua University(Science and Technology), 2023, 63(7): 1124-1134.
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2023, Vol. 63 
