In order to improve the power quality of ships under complex working conditions, an energy management strategy based on wavelet decomposition is proposed for fuel cell ships with a hybrid energy storage system (HESS) consisting of a battery and supercapacitor.

First, wavelet decomposition and fuzzy logic control are used to distribute the load power of the ship and optimize the charging and discharging process of the battery. Next, grey wolf optimizer （GWO） is used to optimize the parameters of the HESS and ensure that the energy management strategy matches the equipment parameters. Finally, the ship power system model is built using the Matlab/Simulink platform, and the simulation experiment is verified.

The simulation results show that the proposed energy management strategy can effectively suppress the output power fluctuation of the fuel cell and realize rational power distribution among devices, reducing the optimized bus voltage fluctuation by 23.19%.

This study can provide useful references for the optimization design of the power quality of ships.

In order to solve the problems of the traditional interactive ship engine room simulation system such as its single simulation form and poor immersivity and realism, a new immersive interactive ship engine room simulation system is designed and implemented, divided into the hardware-in-the-loop （HIL）simulation system and 3D virtual reality (VR) system.

Real-time simulation technology is adopted to realize the real-time connection between the VR system and HIL simulation system through a high-speed network. At the same time, an immersive stereo projection system and multi-station VR system are combined and integrated with the data.

This design realizes the real-time interaction and cooperative operation of the whole system, and the real-time synchronization of the system state between the HIL and VR systems. The internal synchronization characteristics of the VR system are given, and the real-time synchronization of 3D images is realized. Meanwhile, a collaborative interactive operation function of the multi-station VR system is added.

The new immersive interactive ship engine room simulation system proposed herein has guiding significance for ship operation and maintenance management and personnel operation training.

Artificial intelligent technologies have become an important approach to improving the safety of shipping and reducing the operating costs of shipping companies. In order to further improve the level of ship intelligence and break down the data barriers between different shipping companies, an efficient privacy-preserving federated learning method (EPFL) is proposed in this paper.

Federated learning is adopted to organize multiple ship participants to collaboratively train a global fault diagnosis model, and cryptography technologies are used to protect their local data information. Considering Internet of Ships (IoS) scenarios, this paper introduces sparsification technology to compress the model parameters uploaded by shipping participants and reduce their number.

Theoretical analysis and the experimental results show that the proposed EPFL method can effectively reduce the resource consumption of cryptographic computation and data communication while protecting the local data information of ship participants.

The proposed EPFL method can provide references for the establishment of intelligent ship systems.

The class imbalance problems which are prevalent in the condition monitoring data of marine diesel engines significantly deteriorate the performance of data-driven models for the automatic and accurate identification of the health condition of engines. In this paper, a graph convolutional network (GCN) model based on probability similarity between samples is proposed to solve the classification problem of unbalanced datasets.

First, the Kullback-Leibler divergence is introduced to calculate the probability similarity between samples and mine the nonlinear relationship, and a probability topological graph is constructed to represent the similarity of samples. Graph learning is then introduced to learn and extract the correlations between adjacent samples in addition to their own features, providing more information for the imbalanced classification task. After multi-layer graph learning, the higher-level features of each node are extracted.

The two cases of the simulation model and bench test clearly show that the proposed method efficiently extracts more information based on aggregating neighboring samples'features, and improves the classification accuracy under imbalanced datasets.

The precision and recall rate of the proposed GCN model are higher than those of other state-of-the-art algorithms, giving it certain practical application value.

There are multiple operation conditions for ships navigation in inland river waterway, such as sailing downstream, upstream as well as in rapid stream, but the traditional ship-engine-propeller matching method can only ensure that the inland ships meet the design requirements when they travels upstream. Under downstream conditions, the ship propulsion's efficiency and energy utilization rate of main engine are both low, resulting in high fuel consumption and less cost-effectivness. To this end, the optimal design of ship-engine-propeller matching for the inland ships under multiple conditions is carried out.

First, the parameters of an inland ship's propulsion system under various conditions are designed, and the results are compared to ascertain the influence of each design parameter on the overall propulsion system. Then, the design process of the propulsion system is analyzed, and a mathematical model is established with navigation cost and propulsion system efficiency as the objective functions, and the design parameters of the propeller, main engine power and ship speeds (upstream & downstream) as variables. Finally, the main engine power and design parameters of propulsion system are determined balancing both economy and efficiency using the NSGA-II algorithm.

The design parameters obtained using this method are easily adapted to the traffic environment of inland ships, making them more economical.

The results of this study can not only provide design tools for the selection of ship propulsion systems, but also provide a theoretical basis for its practical application.