In this paper, the blade solidity of the tidal current turbine was investigated. Based on the blade element momentum theory, different design flow velocities were selected to design two blade types with different solidities. The geometric parameters of the blade were calculated using MATLAB programming, and the performance of two blades was compared in terms of the start-up flow rate, power generation and thrust by test experiment, which showed that the blade with higher solidity has better start-up performance and higher energy capture efficiency at low flow rates. The performance is better than that of the blade with low solidity, but due to the high solidity, the thrust is also high, which should be taken into account when installing the turbine.

Aiming at the performance evaluation problem of tidal energy turbines in the application of periodic time-varying flow velocity, with the goal of maximizing the efficiency of energy harvesting in practical applications, an evaluation system combining the characteristics of flow velocity changes in practical applications is proposed. After long-term monitoring of tidal current flow velocity in the applied sea area, the actual measured tidal current periodic flow velocity is divided into several flow velocity segments by using statistical segmentation, and the evaluation flow velocity of each flow velocity segment and its time proportion in the tidal current cycle are obtained. A test device with constant torque regulation is built, and capture power tests of different torque loads are carried out under each evaluation flow rate. After comparison, the maximum captured power at each evaluation flow rate is determined. We calculate the weight based on the time proportion of each evaluation flow velocity and obtain the turbine average power of the tidal cycle, thereby evaluating the overall energy capture performance of the turbine under the periodic time-varying flow velocity. Finally, the application test of the turbine in the actual sea area shows that the thin-walled airfoil turbine is more suitable for the sea area, which is the same as the pool evaluation result. The result shows that the evaluation system is reliable and effective and has significance for guiding practical engineering.

Net-cage aquaculture faces challenges from biofouling, which reduces water exchange and threatens structural integrity. Automated cleaning robots provide an alternative to human divers but require effective, low-cost localization. Conventional acoustic–inertial systems are expensive and complex, while vision-only or IMU-based methods suffer from drift in turbid, low-texture waters. This paper presents a lightweight Visual–Inertial–Depth (VID) fusion framework for underwater net-cage cleaning robots. Built on the VINS-Fusion system the method estimates scene scale using optical flow and stereo matching, and incorporates IMU pre-integration for high-frequency motion prediction. A pressure-based depth factor constrains Z-axis drift, and reflective-anchor initialization ensures global alignment. The system runs in real time on a Jetson Orin NX with ROS. Experiments in air, tank, pool, and ocean settings demonstrate its robustness. In controlled environments, the mean anchor coordinate error (ACE) was 0.05–0.16 m, and loop-closure drift (LCD) was ≤0.5 m per 5 m. In ocean trials, turbulence and biofouling led to drift (LCD 1.32 m over 16.05 m, 8.3%), but IMU and depth cues helped maintain vertical stability. The system delivers real-time, cost-effective localization in structured underwater cages and offers insights for improvements in dynamic marine conditions.