Abstract: Aiming at the numerous challenges the current underwater inspection work facing, such as the complexity and variability of the underwater environment, the inefficiency of the traditional inspection methods and the existence of safety hazards, an underwater inspection and detection platform for hydraulic structures is thoroughly studied. This platform consists of a hardware layer, a network layer, a data layer, a service layer and an application layer. Firstly, the hardware layer utilizes advanced underwater robots to collect critical data such as water quality information around the hydraulic structures, as well as underwater images or videos. Secondly, the network layer ensures real-time and stable data transmission, with the data being stored in the data layer. Thirdly, the service layer transmits the data to a software processing system and combines artificial intelligence technologies such as convolutional neural networks to achieve defect detection in hydraulic structures and route planning for underwater robots. Finally, the application layer provides interfaces for computer browsers and WeChat service accounts, allowing users to view the inspection and detection results visually. Experimental results show that the platform can accurately monitor water quality information around hydraulic structures, provide clear underwater images and video materials, and obtain high-precision defect detection results for hydraulic structures.

Key words: hydraulic structures, underwater inspection, detection operation platform, underwater robots, defect detection