This letter proposes a rotation-free wireless power transfer (WPT) system based on a new coil structure to achieve stable output power and efficiency against rotational misalignments for charging autonomous underwater vehicles. The new coil structure has two decoupled receivers composed of two reversely wound receiver coils and the magnetic flux directions of the two receivers are perpendicular to each other, guaranteeing a relatively constant total mutual inductance and a decoupled characteristic under rotational misalignments. The proposed coil structure is verified via finite element analysis based on ANSYS Maxwell. A rotation-free LCC-LCC compensated WPT prototype is built and the experimental results verify the theoretical analysis and simulations. The system can deliver 664 W with a dc-dc efficiency of 92.26% under the best case and 485 W with a 92.10% dc-dc efficiency under the worst case.

As marine observation technology develops rapidly, underwater optical image object detection is beginning to occupy an important role in many tasks, such as naval coastal defense tasks, aquaculture, etc. However, in the complex marine environment, the images captured by an optical imaging system are usually severely degraded. Therefore, how to detect objects accurately and quickly under such conditions is a critical problem that needs to be solved. In this manuscript, a novel framework for underwater object detection based on a hybrid transformer network is proposed. First, a lightweight hybrid transformer-based network is presented that can extract global contextual information. Second, a fine-grained feature pyramid network is used to overcome the issues of feeble signal disappearance. Third, the test-time-augmentation method is applied for inference without introducing additional parameters. Extensive experiments have shown that the approach we have proposed is able to detect feeble and small objects in an efficient and effective way. Furthermore, our model significantly outperforms the latest advanced detectors with respect to both the number of parameters and the mAP by a considerable margin. Specifically, our detector outperforms the baseline model by 6.3 points, and the model parameters are reduced by 28.5 M.

Under the inspiration of polar coordinates, a novel parametric modeling and optimization method for Savonius wind turbines was proposed to obtain the highest power output, in which a quadratic polynomial curve was bent to describe a blade. Only two design parameters are needed for the shape-complicated blade. Therefore, this novel method reduces sampling scale. A series of transient simulations was run to get the optimal performance coefficient (power coefficient C p) for different modified turbines based on computational fluid dynamics (CFD) method. Then, a global response surface model and a more precise local response surface model were created according to Kriging Method. These models defined the relationship between optimization objective Cp and design parameters. Particle swarm optimization (PSO) algorithm was applied to find the optimal design based on these response surface models. Finally, the optimal Savonius blade shaped like a “hook” was obtained. Cm (torque coefficient), Cp and flow structure were compared for the optimal design and the classical design. The results demonstrate that the optimal Savonius turbine has excellent comprehensive performance. The power coefficient Cp is significantly increased from 0.247 to 0.262 (6% higher). The weight of the optimal blade is reduced by 17.9%.

Savonius wind turbine is a common vertical axis wind turbine which simply comprises two or three arc-type blades and can generate power under poor wind conditions. With the aim of increasing the turbine’s power efficiency, the effect of the blade arc angle on the performance of a typical two-bladed Savonius wind turbine is investigated with a transient computational fluid dynamics method. Simulations were based on the Reynolds Averaged Navier–Stokes equations, and the renormalization group $k-\epsilon$ turbulent model was utilized. The numerical method was validated with existing experimental data. The results indicate that the turbine with a blade arc angle of $160\circ$ generates the maximum power coefficient, 0.2836, which is 8.37% higher than that from a conventional Savonius turbine.