Deep-sea mining, as a critical direction for the future development of mineral resources, places significant importance on the mechanical characteristics of its transportation pipelines for the safety and efficiency of the entire mining system. This paper establishes a simulation model of the deep-sea mining system based on oceanic environmental loads and the mechanical theory of deep-sea mining transportation pipelines. Through a static analysis, the effective tension along the pipeline length, the maximum values of bending moment, and the minimum values of bending radius are determined as critical points for the dynamic analysis of pipeline mechanical characteristic monitoring. A dynamic simulation analysis of the pipeline’s mechanical characteristics was conducted, and simulation sensor data were obtained as inputs for the prediction model construction. A prediction model of pipeline mechanical characteristics based on the BP neural network was constructed, with the model’s prediction correlation coefficients all exceeding 0.95, enabling an accurate prediction of pipeline state parameters.

Magnetically coupled resonant wireless power transfer (MCR-WPT) technology offers longer effective transmission distances and higher efficiency compared to traditional charging methods, making it better suited to the prolonged and efficient operation of autonomous underwater vehicles. This paper first establishes a traditional mathematical model and then refines it while analyzing the variations in the self-inductance and mutual inductance of underwater coils. To further enhance the system’s performance, a multi-objective optimization of the coupling mechanism is conducted. An orthogonal experiment is employed to determine the effects of various influencing factors on the coils’ self-inductance and mutual inductance. Subsequently, an RBF neural network is used to create a regression prediction model based on the results of the orthogonal experiment. The NSGA-II algorithm is then applied for the multi-objective optimization of the coupling mechanism, resulting in a Pareto front solution set. The optimized efficiency is 93.35%, representing an approximately 6% improvement over the original system, with the power density increasing from ${1.267\times 10}^6 \mathrm{W}/{\mathrm{m}}^3$ before optimization to ${4.782\times 10}^6 \mathrm{W}/{\mathrm{m}}^3$ after optimization. Significant enhancement in system performance is achieved.

Compared to the traditional wet-mate underwater power supply method, Magnetic Coupling Resonant Wireless Power Transfer (MCR-WPT) technology boasts advantages such as excellent insulation, high safety, and convenient operation, showing promising application prospects in the field of power supply for underwater vehicles and other mobile underwater devices. In order to explore the transmission characteristics of this technology underwater, this article first establishes a traditional mathematical model, and then modifies the underwater model through analysis of changes in coil self-inductance and mutual inductance, as well as the impact of eddy current losses. Using the modified mathematical model of the underwater MCR-WPT system, the transmission characteristics are analyzed, and simulations and experimental validations are performed using MATLAB R2022a software. In the study of frequency characteristics, it is found that the system operates optimally when both ends of the circuit work at the resonant state; that is, when f_input = f_resonance = 100 kHz, the output performance is at its best, and the optimal resonant frequency significantly improves power and transmission efficiency. When the input frequency is less than 87.3 kHz or greater than 122.9 kHz, the output power decreases to less than half of the maximum power. In the investigation of load effects, the optimal load for maximizing system output power was identified, but the load that maximizes transmission efficiency is different from this optimal load. This study provides strong theoretical support and guidance for improving the performance of underwater wireless power transmission systems.