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Marine Current Turbines (MCTs) play a critical role in converting the kinetic energy of water into electricity. However, due to the influence of marine organisms, marine current equipment often experiences imbalance faults. Additionally, affected by the underwater environment, the fault characteristics are submerged in disturbances such as waves and turbulence. Against the background of the above problems, this article proposes a fault detection strategy based on a Generalized Likelihood Ratio Test (GLRT) detector. Firstly, a simulation model of the MCT system is established to obtain prior knowledge. Then, combining the Matrix Pencil Method (MPM) for calculating instantaneous frequency, imbalance fault metrics are selected based on the proposed GLRT detector. At the end, the marine current turbine experimental platform is established, which can simulate imbalanced faults and environmental disturbances, helping to verify the effectiveness of the proposed strategy. The experimental results indicate that the proposed strategy can detect imbalanced faults in complex underwater environments. Imbalance faults are the main manifestation of blade attachments. Thus, it is very meaningful to accomplish fault detection in order to maintain the working order of the MCT system. [ABSTRACT FROM AUTHOR]

In order to guide and optimize structural design, this paper proposes a numerical simulation method for quickly predicting the mechanical test performance of marine electronic cabinets. According to the structural mechanics test standard of marine electronic equipment, the mechanical test simulation analysis of a type of marine electronic cabinet is carried out. Firstly, the finite element model of the electronic cabinet is established by ANSYS. Secondly, based on finite numerical solution method, the modal frequency, sine sweep vibration response, bumping response and shock response of the cabinet were obtained. Finally, according to the calculation results, the strength of the cabinet is checked, and the mechanical reliability of the cabinet is analyzed. The results show that the stresses near the right angles at the top and bottom, side boss and the right angles at the back are relatively high, but they are all lower than the maximum allowable stress of the cabinet, and the cabinet can work reliably under various test conditions. The modeling and analysis method presented in this paper can provide a good reference for the mechanical analysis of similar electronic equipment. [ABSTRACT FROM AUTHOR]

In this study, a comprehensive digital twin monitoring system for ship equipment was designed and implemented, including the system architecture, key technologies, and applications. Through data-driven models and operational monitoring system analysis, our PSO-SVM-based time series prediction method demonstrated excellent predictive capabilities for catamaran equipment, achieving efficient fault warnings using a threshold method. The digital twin model and virtual scenarios constructed here provide a visualisation and simulation platform for equipment status monitoring, enhanced fault diagnosis and support for maintenance decisions. The system integrates real-time monitoring, fault warning, and data analysis, and testing results show good stability and accuracy. In addition, the system optimises the user experience through multi-round feedback testing, and ensures data security and privacy protection through multi-layer encryption, identity verification, and role-based access control. A case study indicates that the proposed system effectively monitors equipment status and provides fault warnings, and has broad application prospects and practical value. Future work will focus on optimising the functionality and improving the applicability and security of the system. [ABSTRACT FROM AUTHOR]

This study investigated the dry sliding wear behavior of Cor-Ten steel, a material commonly used in harsh environments such as ports, sea bridges, and drilling rigs. Understanding how Cor-Ten steel performs in abrasive conditions is crucial for predicting potential wear issues. To assess its wear performance, tests were conducted using three types of abrasive balls: AISI-52100 steel, WC-Co, and Alumina. The wear tests involved a reciprocating ball-on-disc device at loads of 3, 7, and 10 N and sliding speeds of 0.4 mm/s and 0.8 mm/s. Results showed that the largest wear volumes occurred with the Alumina ball, while the AISI 52100 steel ball, despite its lower hardness, produced higher wear volumes than the WC-Co ball. Additionally, increased sliding speed led to higher wear volumes across all tests. SEM images revealed distinct wear tracks on both surfaces. These results provide valuable insights into the wear mechanisms of Cor-Ten steel, which can aid in optimizing material selection and maintenance strategies in marine construction.

ABSTRACT To evaluate the global seawater corrosivity and ensure the service safety of marine equipment, the methods of seawater corrosivity classification, which contained the standard metal corrosion rates method and the environmental factors evaluation method, are proposed and then applied to the seawater corrosivity classification in typical China seas. By comparing the results from both methods, the feasibility of the environmental factors evaluation method based on the grey relational model is verified. Furthermore, with the collection and processing of typical seawater factors data of global ocean, the corrosivity of global seawater is classified into six grades with the corrosion test data of carbon steel as baseline, and its distribution in different months is visualized by means of ArcGIS technology. The results show that the sea areas with high corrosivity are mainly located at equatorial and tropical sea areas, and for carbon steel, seawater temperature was the main influence on seawater corrosivity. [ABSTRACT FROM AUTHOR]

The paper presents a novel approach of cooperative multiagent reinforcement learning (CMARL) combined with A* search to address ship multicabin equipment layout considering pipe route, aiming to minimize pipe cost while considering practical requirements. The formulation is established through equipment simplification and grid marking, and A* search is utilized to value the pipe route. By designing equipment states, the equipment layout in each cabin is solved using a CMARL approach that involves three actions. Subsequently, comparative experiments were conducted on an engine room case by CMARL against genetic algorithm and single multiagent reinforcement learning methods under the condition of coupling with A* search. The parameter values for these methods were sampled using Latin Hypercube. The findings demonstrate that CMARL has superior combination properties. [ABSTRACT FROM AUTHOR]

Exploring on reliability modeling and analysis on a marine equipment in a dynamic environment is a meaningful and challenging issue, because the system commonly carries out the task at sea away from land and suffers a distinct influence of environment. Thus, a reliability model of a multi‐state repairable system operating in dynamic environment is developed by introducing the background of the marine power system in this paper. The novelty of the research lies in the modeling and computing methods are relatively innovative by employing the aggregated stochastic processes, Hadamard production and matrix‐analytic method. First, the working modes of the marine power system under several different kinds of conditions are introduced. Then, the evolution of both the system states and environment are described as discrete‐time Markov chains with multiple and different transition probability matrices. The failure probability and repair probability of components are also distinct in different environments. Furthermore, some performance indexes, especially the index relevant to the environment, are derived, respectively. Finally, the conclusion is obtained by a numerical example of the marine power system, which also illustrates the validity and applicability of the proposed model. [ABSTRACT FROM AUTHOR]

Detecting anomalies in engine and machinery data during ship operations is crucial for maintaining the safety and efficiency of the vessel. We conducted experiments using device data from the maritime industry, consisting of time series records from IoT (Internet of Things) datasets such as cylinder and exhaust gas temperatures, coolant temperatures, and cylinder pressures collected from various sensors on the ship's equipment. We propose data enrichment and validation techniques by generating synthetic outliers through data degradation and data augmentation with a Transformer backbone, utilizing the maritime operational data. We extract a portion of the input data and replace it with synthetic outliers. The created anomaly data are then used to train the model via a self-supervised learning approach. Synthetic outliers are generated using methods such as the arithmetic mean, geometric mean, median, local scale, global scale, and magnitude warping. With our methodology, we achieved a 17.23% improvement in F1 performance compared to existing state-of-the-art methods across five publicly available datasets and actual maritime operational data collected from the industry. [ABSTRACT FROM AUTHOR]

The impact of the Fourth Industrial Revolution has brought significant attention to Condition-based maintenance (CBM) for autonomous ships. This study aims to apply CBM to the fuel supply pump of a ship. Five major failures were identified through reliability analysis, and structural analysis was conducted to investigate the mechanisms by which one failure induces another, leading to the identification of three compound failure scenarios. Data were collected on a test bed under normal conditions, five single failure conditions, and three compound failure conditions. The acceleration data from the experiments were transformed into 2D arrays corresponding to a single pump rotation, and a method was proposed to compensate for the errors accumulated during the repeated array generation. The data were vectorized using a simplified CNN structure and applied to six multi-label learning methods, which were compared to identify the optimal approach. Among the six methods, the Label Powerset (LP) was found to be the most effective. Multi-label learning captures correlations between labels, similar to the failure-inducing mechanisms learned from structural analysis. [ABSTRACT FROM AUTHOR]

The task of automatically and intelligently diagnosing faults in marine equipment is of great significance due to the numerous duties that shipboard professionals must handle. Incorporating automated and intelligent systems on ships allows for more efficient equipment monitoring and better decision-making. This approach has attracted considerable interest in both academia and industry because of its potential for economic savings and improved safety. Several fault diagnosis methods are documented in the literature, often involving mathematical and control theory models. However, due to the inherent complexity of some processes, not all characteristics are precisely known, making mathematical modeling highly challenging. As a result, fault diagnosis often depends on data or heuristic information. Fuzzy logic theory is particularly well suited for processing this type of information. Therefore, this paper employs fuzzy models to diagnose faults in a marine pneumatic servo-actuated valve. The fuzzy models used in fault diagnosis are obtained from the data. These fuzzy models are identified for the normal operation of the marine pneumatic servo-actuated valve, and for each fault, predicting the system's outputs from the inputs and outputs of the process. The proposed fault diagnosis framework analyzes the discrepancy signals between the outputs of the fuzzy models and the actual process outputs. These discrepancies, known as residuals, help in detecting and isolating equipment faults. The fault isolation process uses an intelligent decision-making approach to determine the specific fault in the system. This method is applied to diagnose abrupt faults in a marine pneumatic servo-actuated valve. The approach presented was used to detect and diagnose three very important faults in the operation of a marine pneumatic servo-actuated valve. The three faults were correctly detected and isolated, and no errors were detected in this detection and isolation process. [ABSTRACT FROM AUTHOR]

Friction in marine engineering machinery produces abrasive particles containing valuable information. By employing oil detection technology, we can analyze these particles to monitor and diagnose mechanical system faults. This paper introduces an inductive oil detection sensor and wireless signal transmission circuit. The sensor utilizes two opposing solenoid coils of the same specifications, with the detection coil connected to a chip capacitor to form an LC resonant unit. The designed wireless transmission circuit wirelessly transmits a sensing signal from a detection coil to a receiving coil to detect metal particles in oil. This paper deduces the sensor's inductance principle and simulates the magnetic field distribution using finite element simulation software. Through experiments, the optimal excitation frequency, coil spacing, and oil sample flow path location were determined. The sensor successfully detected 55 μm iron particles and 138 μm copper particles in a 1 mm microfluidic channel. With its simple structure, distinct signal characteristics, and high sensitivity, the sensor is suitable for detecting metal abrasive particles in hydraulic oil, providing a new approach for wireless transmission in oil detection sensors. [ABSTRACT FROM AUTHOR]

Due to the inherent unpredictability of marine trial conditions, safety issues in the launching and recovery process are commonplace. For these issues, digital twin (DT) maintenance offers a novel idea. In this paper, a blended-wing-body underwater glider skeleton is selected as a research object. And a simple demo is created to investigate the major technologies that may be involved in DT maintenance. According to this specimen, the necessary development environments are developed to obtain physical information and produce a DT model in cyberspace respectively. An attitude sensor is used as the physical data collector, while real-time structural field prediction and virtual reality visualisation are employed. By using the attitude angles and structural data, it is possible to achieve real-time monitoring of the skeleton strength. Through the means of this straightforward case study, the key technologies are supported and can be applied to far more complex inquiries. [ABSTRACT FROM AUTHOR]

The retracting and releasing cables were the only link between the submarine exploration equipment and the ship, had the functions of power, information transmission and load-bearing, and were widely used in all kinds of launch and recovery systems. The safety and reliability of retracting-releasing cables were of the core functional requirements. Therefore, conducting experiments on mechanics properties of retracting-releasing cables was the foundation of retracting-releasing cable research. Starting from the types and failure modes of ocean winches and retracting-releasing cables, the state of experimental studies of the mechanics properties of retracting-releasing cables was systematically summarized, and an outlook on future research directions was provided. Firstly, the functions of ocean winches and retracting-releasing cables were categorized, followed by a detailed analysis of the forms and reasons for their failures. Secondly, the operating conditions, mechanics performance requirements of retracting-releasing cables, and experimental researchs current status were described. Lastly, the research directions for the mechanics properties of retracting-releasing cables in ocean detection equipment were discussed, including the impact and mechanism of extreme operating environments on mechanics properties of synthetic retracting-releasing cables, the behavior and mechanism of synthetic retracting-releasing cable damage under multiple load couplings, and the technology and integrated simulation devices for retracting-releasing cable mechanics properties. [ABSTRACT FROM AUTHOR]

The paper proposes an innovative methodology of Human Cognitive Reliability-Cognitive Reliability and Error Analysis Method (HCR-CREAM) coupled with A search and genetic algorithm (GA) to tackle ship cabin equipment layout considering human factor reliability optimization with the goal of minimizing human error probability (HEP) subjected to practical requirements. After establishing the mathematical model of cabin equipment inspection tasks in ship cabin equipment layout problem through HCR-CREAM and equipment geometric simplification, a method of the horizontal movement based on minimum distance is presented to avoid the equipment overlapping, then A search is used for planning inspection paths and GA with selection, crossover, and mutation operators is applied to solve equipment layout results. A case of equipment layout in a certain ship engine room has been taken to carry out parameter sampling experiments by Latin Hypercube for GA. The results show the solution effect of GA is less affected by its parameter variation. And through the comparison with the initial equipment layout, the indicators influencing the HEP of the optimized result have been improved, thus significantly reducing HEP. [ABSTRACT FROM AUTHOR]

Electric motors are indispensable electrical equipment in ships, with a wide range of applications. They can serve as auxiliary devices for propulsion, such as air compressors, anchor winches, and pumps, and are also used in propulsion systems; ensuring the safe and reliable operation of motors is crucial for ships. Existing deep learning methods typically target motors under a specific operating state and are susceptible to noise during feature extraction. To address these issues, this paper proposes a Resformer model based on bimodal input. First, vibration signals are transformed into time–frequency diagrams using continuous wavelet transform (CWT), and three-phase current signals are converted into Park vector modulus (PVM) signals through Park transformation. The time–frequency diagrams and PVM signals are then aligned in the time sequence to be used as bimodal input samples. The analysis of time–frequency images and PVM signals indicates that the same fault condition under different loads but at the same speed exhibits certain similarities. Therefore, data from the same fault condition under different loads but at the same speed are combined for cross-domain motor fault diagnosis. The proposed Resformer model combines the powerful spatial feature extraction capabilities of the Swin-t model with the excellent fine feature extraction and efficient training performance of the ResNet model. Experimental results show that the Resformer model can effectively diagnose cross-domain motor faults and maintains performance even under different noise conditions. Compared with single-modal models (VGG-11, ResNet, ResNeXt, and Swin-t), dual-modal models (MLP-Transformer and LSTM-Transformer), and other large models (Swin-s, Swin-b, and VGG-19), the Resformer model exhibits superior overall performance. This validates the method's effectiveness and accuracy in the intelligent recognition of common cross-domain motor faults. [ABSTRACT FROM AUTHOR]

Lifeboats are life-saving equipment used when it is necessary to abandon a ship or, in some ships, for man-overboard situations (to collect persons from water). Every seafarer onboard a ship has a task related to lifeboat operation in an emergency. In order to master and practise the assigned tasks, be ready to react at any moment, and efficiently use life-saving equipment and appliances, seafarers on ships perform drills at prescribed intervals. Effective drill performance is of paramount importance, as it improves safety and enables crew members to practise lifeboat operations. However, although their primary role is life-saving, lifeboat drills have resulted in numerous accidents, causing injuries and fatalities, besides equipment damage. Therefore, it is necessary to prevent such unwanted events and discover their root causes. As the human factor is considered a significant cause of marine accidents, this paper aims to quantify human error probability (HEP) during lifeboat drills. In addition, because lifeboat drill accident data are scarce, this study adopted the Success Likelihood Index Method (SLIM) for human reliability analysis (HRA). Based on expert judgments, the tasks with the highest probability of human error and factors significantly influencing human performance during lifeboat drills are identified. According to the study results, the recovery of the lifeboat is the most hazardous phase with the highest HEP. In addition, the BN-SLIM is adopted to estimate the probability of human error during the recovery of the lifeboat. The task with the largest HEP is confirming the release lever is properly rested and hooks locked (HEP = 4.5%). Furthermore, the design and condition of equipment and Crew Competence are identified as the most important Performance-Shaping Factors (PSFs) that affect crew members' performance. The BN-SLIM model was verified utilising a sensitivity analysis and validated by analysing real-life lifeboat drill accidents that occurred during lifeboat recovery. The results confirmed that the model could be used to analyse lifeboat accidents and for proactive preventive measures because most influencing factors are recognised, and acting on them can significantly reduce the HEP of the overall task, improve lifeboat safety, and save lives at sea. [ABSTRACT FROM AUTHOR]

The deep-sea connector is a signal transmission equipment that ensures the normal operation of marine equipment, and the normal operation of the deep-sea connector largely depends on the sealing performance of the O-ring. Therefore, the problem that the deep-sea high- pressure environment causing O-ring deformation and seriously affecting the sealing performance of O-ring was analyzed. Firstly, based on the theory of structural deformation, the influence of environmental pressure on the deformation of the seal structure and the compression amount of the O-ring was theoretically analyzed. Then a nonlinear dynamic seal model of the O-ring was established by the finite element method, the influence of model grid division on the accuracy of the simulation results was analyzed and studied, and the relationship curve between the structural deformation and environmental pressure was analyzed. Finally, the effects of material properties, environmental pressure and sealing structure size on the performance of dynamic seals were studied and analyzed. The research results show that when the actual value of the grid is 47 745, and the measured value is 21 685, 37 934 and 50 707, the error of the simulation results is less than 2% . The curve trends of the deformation of seal structure and the compression of O-ring are basically consistent with the theoretical values. The change of material properties and environmental pressure will affect the dynamic sealing performance. In the sealing structure size, increasing the groove fillet radius can enhance the dynamic sealing performance of the O-ring. The research results can provide reference and theoretical support for the design and optimization of O-ring under deep-sea high-pressure environment. [ABSTRACT FROM AUTHOR]

As more and more new power electronics with high switching frequencies are used in power-electronic equipment on ships and other platforms, the wideband radiation that power-electronic equipment gives off could affect sensitive equipment on the platform. Therefore, it is crucial to accurately model and characterize its wideband radiation properties to predict the wideband field distribution near such equipment. The traditional equivalent dipole method is commonly used to model power-electronic equipment at a single frequency. It is difficult to apply this method to wideband applications, and the precision of equivalent dipole array modeling at each frequency is insufficient. Additionally, acquiring the near-field phase data necessary for comparable modeling through practical measurement is frequently difficult. To solve the above problems, this paper proposes an equivalent dipole hybrid modeling method for power-electronic equipment's broadband radiation characteristics. Starting with the near-field data at finite frequency points in a wideband, the method employs a global optimization algorithm to find the best equivalent dipole array, which characterizes the power-electronic equipment's radiation characteristics. Furthermore, the interpolation technique is used to predict the wideband radiation properties of power-electronic equipment. Finally, test and numerical examples demonstrate the method's accuracy and effectiveness. [ABSTRACT FROM AUTHOR]

For conducting scientific research at depths in the ocean, deep-sea probes are essential pieces of equipment. The cylindrical shell is the most sensible and rational packaging structure for these detectors. New technical challenges for enhancing the pressure resistance and lightweight design of the pressure-resistant cylindrical shell arise from the need to ensure that the detector packaging structure can withstand the immense water pressure at tens of thousands of meters in the underwater environment, while simultaneously reducing the detector packaging structure's self-weight. This article examines the detection system's deep-sea pressure-resistant cylindrical shell. To address the issue of the pressure-resistant shell's insufficient ability to counteract the overall instability caused by the inability to form unstable half-waves in the radial direction when the ring rib pressure-resistant shell experiences it, a design method for the ribs inside the unequal-stiffness pressure-resistant cylindrical shell is suggested. The shell's instability pressure increases by 9.65 MPa following the stiffness adjustment. Simultaneously, in order to attain even more lightweight optimization, the optimal inner rib section was obtained by applying the orthogonal topology optimization method, which also reduced the weight by 106.8 g and effectively improved the compression stability of the high-pressure cylindrical shell structure. Based on this, key optimization variables were found by performing sensitivity analysis on the cylindrical shell structure's parameters. Then, with lightweighting as the primary objective, the high-pressure-resistant cylindrical shell's optimal structural parameters were found using a multi-objective optimization process using the second-generation fast non-dominated genetic algorithm (NSGA-2). This resulted in a weight reduction of 1.2492 kg, or 17.26% of the original pressure-resistant shell. This has led to the development of a lightweight, highly pressure-resistant method for packaging marine exploration equipment structures. [ABSTRACT FROM AUTHOR]

A built-in wave energy converter (BI-WEC) is a type of WEC that is fully encapsulated within a floating body that is easy to integrate and promotes reliability. Significant advantages in integration and reliability make BI-WECs a promising pathway to achieve an in situ power supply for massive distributed marine equipment (such as ships, buoys, or USVs). A comprehensive review of the recent advances in built-in wave energy converters can help address the most relevant issues in BI-WEC development. This study enumerates recent progress on BI-WECs (energy capture, power take-off, and control) and summarizes the characteristics of various designs. Different design philosophies and technical pathways can be better understood through the classification and analysis offered by this study. This review helps to form a basic understanding of BI-WEC development to achieve in situ power sustainability for a large amount of distributed marine equipment in long-term sustained marine operations. [ABSTRACT FROM AUTHOR]

The comprehensive trade-off among reliability, maintainability, availability and life cycle cost should be solved in the overall design of warship equipment. Maintainability analysis and comprehensive trade-off of naval ships equipment based on the PROMETHEE method are proposed. In the method, the evaluation model of alternatives set is formed through the analysis of maintainability-related factors, the determination of target attribute and related attribute weight of alternatives, the selection of attribute priority function and threshold. And carry out calculation and analysis, form the ranking of alternatives. Combined with the calculation and analysis of specific examples, the evaluation results of six groups of alternatives are obtained, and the optimal scheme is determined. The research provides an effective theoretical basis for maintainability analysis and comprehensive trade-off of system overall design. It guides the implementation and decision of the project. It's suitable for the comprehensive trade-off problem of multi-objective relationships to find the optimal solution. [ABSTRACT FROM AUTHOR]

Marine diesel engines are the preferred power equipment for ships and are the most important component among the numerous electromechanical devices on board. Accidents involving these engines can potentially cause immeasurable damage to the vessel, making fault detection in marine diesel engines crucial. This design enables the detection and reporting of faults in marine diesel engines at the earliest possible time through the computation of convolutional neural networks, which is of great significance for ensuring the safe navigation of ships. For this functionality, the Xilinx ZYNQ-7000 XC7Z010 is selected as the main control chip, and the LoRa wireless network is used as the transmission module. The FreeRTOS embedded operating system is ported, with sensor data collection completed on the PS side of the ZYNQ chip and algorithm acceleration calculations on the PL side. Data are then transmitted to the host computer via the LoRa module paired with a custom protocol. Experimental test results show that the program provides stable data transmission, with each module of the algorithm generally accelerating by more than 95% and an accuracy rate of 92.86%. Additionally, the host computer can display the received data in real time. The custom protocol's header also allows for precise judgments about the completeness and origin of messages, facilitating the expansion of other SOC's message uplink and the host computer's message downlink. [ABSTRACT FROM AUTHOR]

In the study, the authors investigated the effects of picosecond laser ablation on the surface topographies of MONEL® alloy 400, used in the manufacturing of marine equipment components (such as pumps, valves, fixtures and fasteners). The experimental methodology involved preparing the material through grinding, polishing, and cleaning before subjecting it to picosecond laser ablation using specific parameters. The laser processing was carried out to create square ablated cavities on the alloy surface. The impact of the laser treatment on the surface condition of the alloy was assessed through profilometry analysis. The results provide insights into the surface topographies of the laser-treated MONEL® alloy 400 samples, offering valuable information for potential applications in marine industries [ABSTRACT FROM AUTHOR]

The products made of advanced materials are the buzz amid material scientists as they possess enhanced mechanical properties, leading to development of material such as Duplex Steel 2205. The material being hard and having high strength, machinability along with stringent environmental regulations is a challenge keeping in view the wide range of applications that the material caters like pressure vessels, marine equipment and heat exchanger. The current experimental investigation of flank wear and surface roughness was predicted through ANN model and experimentally evaluated under dry-turning conditions using carbide-tipped inserts. Dry turning was performed by selecting the speed levels of 103, 134, and 174 m/min; feed rate (FR) levels of 0.12, 0.15, and 0.18 mm/rev; and depth of cut (DOC) levels of 0.5, 1.0, and 1.5 mm. Experiments were designed using Taguchi-L9 model, optimum cutting speed (134 m/min), feed (0.12 mm/rev), and DOC of (1.0 mm) resulted in least Ra values. The regression model created on the experimental data is in 95% conformance for surface roughness and flank wear. Optimal machining parameters indicate that cutting speed have greatest significance on machining trailed by feed and DOC. [ABSTRACT FROM AUTHOR]

Lead-based reactor nuclear power has the advantages of inherent safety, compact size, light weight, long service life, and high efficiency, and it is widely applied to advanced marine equipment, unmanned underwater vehicles, and deep-sea space stations for energy and power purposes. Conducting research on lead-based reactor marine nuclear power is key to the technological innovation of energy and power for marine equipment in China. This study clarifies the application scenarios and development demands of marine nuclear power, summarizes the development status of lead-based reactor nuclear power from the aspects of technical characteristics, representative applications, and research status, and analyzes corresponding key technologies including nuclear fuel and cladding materials, key components in the primary loop, coolant processes and oxygen control, and advanced power generation technologies. Moreover, the study explores the development challenges for lead-based reactor marine nuclear power and proposes there feasible technical routes: low-temperature lead-based reactor marine nuclear power, high-temperature and high-efficiency lead-based reactor marine nuclear power, and integrated natural-circulation lead-based reactor marine nuclear power. Furthermore, we propose the following suggestions to promote the leapfrog development of marine nuclear power in China:(1) strengthening research and development (R&D) of specialized technologies for the lead-based reactor marine nuclear power and accelerating the deployment of demonstrative projects; (2) incorporating lead-based reactors into the country's major energy strategies and creating a standards system; (3) establishing national joint R&D centers and creating new models for technological innovation and industrial development.

Marine equipment is an important measure to support China’s construction of a marine power, as stated in the report of the Chinese Communist Party’s 20th National Congress on “developing the marine economy, protecting the marine ecological environment, and accelerating the building of a marine power”. In recent years, China’s marine equipment industry has developed rapidly, but there are still some problems. The industry is large but not strong enough. And the basic theoretical innovation and core key technologies are difficult to meet the needs of national strategic development. Based on Schumpeter’s innovation theory, this paper investigates the innovative ability of product innovation, process innovation, demand innovation, supply chain innovation and production organization innovation in China’s marine equipment manufacturing industry, and on the basis of summing up three kinds of innovative drive modes, put forward seven developing paths for the development of China’s marine equipment manufacturing industry.

To achieve the failure warning of marine systems and their equipment (MSAE), the threshold is one of the most prominent issues that should be solved first. In this study, a fusion model based on sparse Bayes and probabilistic statistical methods is applied to determine a new and more accurate adaptive alarm threshold. A multistep relevance vector machine (RVM) model is established to realize the parameter reconstruction in which the internal uncertainties caused by the degradation process and the external uncertainty caused by the loading, environment, and disturbances were considered. Then, a varying moving window (VMW) method is employed to determine the window size and achieve continuous data reconstruction. Further, the model based on Johnson distribution systems is utilized to complete the transformation of the residual parameters and calculate the adaptive threshold. Finally, the proposed adaptive decision threshold is successfully involved in the actual examples of the peak pressure and exhaust temperature of marine diesel engines. The results show that the proposed method can realize the continuous health condition monitoring of MSAE, successfully detect abnormal conditions in advance, achieve an early warning of failure, and reserve sufficient time for decision-making to prevent the occurrence of catastrophic disasters. [ABSTRACT FROM AUTHOR]

Marine high-end equipment reflects a country's comprehensive national strength. The safety assessment of it is very important to avoid accident either from human or facility factors. Attribute structure and assessment approach are two key points in the safety assessment of marine high-end equipment. In this paper, we construct a hierarchical attribute structure based on literature review and text mining of reports and news. The hierarchical attribute structure includes human, equipment, environment and management level. The correlations among these attributes are analyzed. The assessment standards of attributes are described in details. Different evaluation grades associated with attributes are transformed to a unified one by the given rules. As for the assessment approach, the evidential reasoning approach is applied for uncertain information fusion. Group analytical hierarchical process is used to generate attribute weights from a group of experts, where process aggregation method and result aggregation method are combined in a comprehensive way. The importance of expert is computed by the uncertainty measure of expert's subjective judgment. A drilling platform is finally assessed by the proposed attribute structure and assessment approach to illustrate the effectiveness of the assessment framework. [ABSTRACT FROM AUTHOR]

The visual monitoring of ship-engine-room equipment is an essential component of ship-cabin intelligence. In response to issues such as imbalanced quantities of different categories of engine room equipment and severe occlusion, this paper presents improvements to YOLOv8-M. Firstly, the introduction of the SPPFCSPC module enhances the feature extraction capabilities of the backbone extraction network. Subsequently, improvements are implemented in the neck network to create GCFPN, facilitating further feature fusion, and introducing the Dynamic Head module, which fuses the deformable convolution, in the part of the detection head, so as to improve the performance of the network. Finally, the FOCAL EIOU LOSS is introduced, while mitigating the impact of dataset imbalance through class-wise data augmentation. In this paper, the ship cabin equipment dataset and the public dataset MS COCO2017 are evaluated. Compared with YOLOv8-M, the mAP50 of GCD-YOLOv8 is improved by 2.6% and 0.4%, respectively. [ABSTRACT FROM AUTHOR]

A ship equipment pedestal is a structure that connects power equipment to a hull. It must have a high load-bearing capacity and the ability to withstand large impact loads. In this paper, a novel structure with a positive-negative Poisson's ratio is proposed. The deformation mechanism and mode of this structure under quasistatic compression loading are analysed via numerical simulation. Based on this new structure, a multicellular pedestal is designed, and its bearing capacity and impact resistance are analysed. The structural parameters of the pedestal are optimized. An experiment is conducted to evaluate the impact resistance of the pedestal model, which confirms that the proposed multicellular pedestal exhibits excellent impact resistance. [ABSTRACT FROM AUTHOR]

Specialized epoxy resin, capable of achieving room-temperature profound curing and sustaining prolonged exposure to high-temperature environments, stands as a pivotal material in modern high-end manufacturing sectors including aerospace, marine equipment fabrication, machinery production, and the electronics industry. Herein, a silicon-hybridized epoxy resin, amenable to room-temperature curing and designed for high-temperature applications, was synthesized using a sol–gel methodology with silicate esters and silane coupling agents serving as silicon sources. Resin characterization indicates a uniform distribution of silicon elements in the obtained silicon hybrid epoxy resin. In comparison to the non-hybridized epoxy resin, notable improvements are observed in room-temperature curing performance, heat resistance, and mechanical strength. [ABSTRACT FROM AUTHOR]

Purpose: In response to the difficulty of dynamic vibration absorber (DVA) to realize the broadband vibration reduction of large marine mechanical equipment, an air spring dynamic vibration absorber (ASDVA) was proposed, then its damping and vibration absorption performance were studied. Methods: A piecewise integral method was used to identify the damping, and the modal tests were carried out to determine the vibration absorption frequency. Subsequently, the effects of the air pressure and the orifice opening on the vibration absorption frequency and damping were analyzed. A single-degree-of-freedom (SDOF) system model was established to analyze the influence of the damping on the vibration absorption performance, and then relevant vibration absorption performance tests were carried out. Results: The piecewise integral method is accurate in identifying the damping. The changes of the air pressure and the orifice opening affect not only the vibration absorption frequency, but also the damping. In particular, the damping reaches a maximum value at a certain orifice opening, and the vibration absorption frequency will jump from the low frequency to the higher frequency. The increase of the damping reduces the vibration absorption effect, but broadens the vibration absorption bandwidth. Conclusion: By properly adjusting the air pressure and the orifice opening, the ASDVA can obtain appropriate vibration absorption frequency and damping, thus achieving good broadband vibration reduction effect. [ABSTRACT FROM AUTHOR]

The development of the marine equipment industry has formed a global collaborative pattern, with a long industrial chain and wide coverage, which is highly susceptible to international interference. This paper analyzed the development needs of China's marine equipment industry chain from three levels, including responding to changes in international forms, building a new dual cycle development pattern, and high-quality development of the marine equipment industry. By preliminarily constructing a graph of the marine equipment industry chain, it analyzed the degree of independent and controllability of the marine equipment industry chain from six aspects, including raw materials, research and development design, supporting facilities, final assembly and construction, ship and sea service, and operation and maintenance. It was proposed to carry out key core technology research and iterative upgrades targeting weak links in the industry chain, such as high-end product research and development design, key technologies for specialized matching equipment, and strengthen fundamental and forward-looking technological research in response to the development trend of ships, and enhance the soft power of China's marine equipment industry chain in response to the field of ship and sea service.

The task of automatically and intelligently diagnosing faults in marine equipment is of great significance due to the numerous duties that shipboard professionals must handle. Incorporating automated and intelligent systems on ships allows for more efficient equipment monitoring and better decision-making. This approach has attracted considerable interest in both academia and industry because of its potential for economic savings and improved safety. Several fault diagnosis methods are documented in the literature, often involving mathematical and control theory models. However, due to the inherent complexity of some processes, not all characteristics are precisely known, making mathematical modeling highly challenging. As a result, fault diagnosis often depends on data or heuristic information. Fuzzy logic theory is particularly well suited for processing this type of information. Therefore, this paper employs fuzzy models to diagnose faults in a marine pneumatic servo-actuated valve. The fuzzy models used in fault diagnosis are obtained from the data. These fuzzy models are identified for the normal operation of the marine pneumatic servo-actuated valve, and for each fault, predicting the system’s outputs from the inputs and outputs of the process. The proposed fault diagnosis framework analyzes the discrepancy signals between the outputs of the fuzzy models and the actual process outputs. These discrepancies, known as residuals, help in detecting and isolating equipment faults. The fault isolation process uses an intelligent decision-making approach to determine the specific fault in the system. This method is applied to diagnose abrupt faults in a marine pneumatic servo-actuated valve. The approach presented was used to detect and diagnose three very important faults in the operation of a marine pneumatic servo-actuated valve. The three faults were correctly detected and isolated, and no errors were detected in this detection and isolation process.

Marine microplastics have become a pernicious global pollution issue. As field surveys to determine microplastic abundance in the marine environment and/or biota become more common, it is important to refine collection techniques to minimize contamination of samples. However, most contemporary sampling equipment is fabricated with plastic components. Microplastic contamination during sample collection can be minimized from the onset by employing techniques that are plastic-less or with minimal plastic-to-sample contact. Here we describe plastic-less equipment and techniques for field sampling of water, sediment, and organisms. Some of these are traditional designs that predate the plastic era and can be revived or repurposed for microplastic sampling. Others are self-developed and fabricated using materials such as metal, wood, silk, and cork. For relatively small costs in time and funds, it is possible to greatly reduce, or eliminate, plastics from the field sampling process. [ABSTRACT FROM AUTHOR]

The electromagnetic detection method is the main method of marine oil and gas resource exploration, and the marine electromagnetic transmitter is the key equipment of marine electromagnetic detection systems. At present, the power factor of the controllable source circuit of the electromagnetic transmitter is low, energy cannot be fed back, and the capacitance of the filter capacitor is large, which results in a large volume of the electromagnetic transmitter and high maintenance costs. Thus, a cascaded H-bridge controllable source circuit combined with active power decoupling technology is introduced in this paper. First, the topological structure and working principle of the controllable source circuit of the electromagnetic transmitter are analyzed, and an improvement plan is proposed for the existing problems of the controllable source circuit. Second, the working principle of the improved controllable source circuit is analyzed, and the advantages of the improved scheme are expounded. Then a control strategy based on linear active disturbance rejection control (ADRC) is proposed, and a linear ADRC controller is designed. Simulation results show that the improved controllable source circuit reduces the capacitance value, improves the power factor, reduces the volume of the underwater towing body, and reduces the maintenance cost of the system. The proposed control strategy makes the DC voltage have better anti-disturbance performance, and improves the reliability of the electromagnetic transmitter in deep sea exploration. [ABSTRACT FROM AUTHOR]

In today's highly competitive industry, product development and manufacturing processes are becoming increasingly complex while the environment in which engineers work has changed. The development and advancement of digital collaboration software that integrates design, development and product lifecycle management is increasingly prevalent in shipbuilding. Namely, the high degree of integration of the ship structure design process with information related to the construction and equipment of the ship is directly related to the level of competitiveness of the shipbuilding project company or shipyard. The need for faster design and quick and accurate control of product quality in the early stages of ship design has encouraged the development and implementation of the latest generation of collaborative software, which has powerful capabilities for managing and improving the process of ship design, construction and exploitation. This paper will describe a "smart" modelling technique based on parametric modelling, the application of user-defined feature (UDF) functionality, the definition of Component family and relevant coding for selected elements of ship equipment in the modern shipbuilding, Industry 4.0 ready, platform 3D EXPERIENCE, to increase efficiency and quality when modelling repetitive elements of ship hull equipment. [ABSTRACT FROM AUTHOR]

The universal application of the hub-and-spoke maritime network makes feeder line network key to restricting the quality and efficiency of maritime transportation. However, container liner routes in feeder line network are susceptible to the changes in shipment demand and international fuel prices. Therefore, based on the hub-and-spoke maritime network, this article constructs a robust optimization model of container liner routes in feeder line network. Under the capacity and time constraints, routes optimization and ship equipment under uncertain environment are analysed. An improved tabu search algorithm was designed based on the characteristics of the model. The example analysis proves that the model can still ensure the robustness of routes under uncertain environment, which is more applicable than the deterministic model. [ABSTRACT FROM AUTHOR]

Marine monitoring equipment such as Argo profiling buoys and underwater gliders are important devices for oceanographic research and marine resource exploration. In this study, a novel mobile buoy capable of vertical profiling motion like Argo profiling buoys and sawtooth gliding motion like underwater gliders is proposed. The proposed mobile buoy can switch between the two motion modes with controllable wings. To verify the feasibility of the proposed mobile buoy, a fluid–multibody coupling model considering multibody dynamics and hydrodynamics was developed to investigate the dynamic response. A scaled-down buoy prototype was fabricated and the feasibility of the two motion modes was experimentally investigated in a laboratory tank. The experimental results agree well with the results of numerical simulation. This work can be helpful for the design and analysis of this kind of mobile buoy. [ABSTRACT FROM AUTHOR]

This study explores strategies to enhance the efficiency of marine technical equipment through the adoption of lowsulfur marine fuels. The investigation incorporates a comprehensive analysis, encompassing enthalpy change calculations and thermal efficiency estimates at various temperature differentials. These calculations shed light on the impact of the specific heat capacity of low sulfur marine fuels, a crucial factor in understanding combustion characteristics. Furthermore, provides an assessment of the efficiency of converting heat to mechanical energy, offering valuable insights for optimizing equipment performance. The outcomes of this research contribute to a broader strategy aimed at bolstering the environmental sustainability and efficiency of marine propulsion systems. By scrutinizing the utilization of low sulfur marine fuels, the study seeks to inform decision-making processes by pinpointing temperature ranges that maximize efficiency. The findings also highlight areas with potential for improvement in the performance of marine diesel engines. This holistic approach is integral to fostering advancements in both environmental responsibility and operational effectiveness within the maritime industry. [ABSTRACT FROM AUTHOR]

Because of the importance of maintaining safety at sea, great training efforts are required to ensure that operators act safely in any ship. In such context, ship manoeuvring simulators are used to ease operators' learning experience. On the one hand, it may assist in the education of new operators by simulating equipment interfaces in a controlled and predictable scenario; on the other hand, it may simulate non-conventional scenarios to train advanced operators under stresses. As modelling spurious phenomena that yields marine equipment malfunctions is significantly complex, low-fidelity solutions have been proposed to the task. Likewise, the current work is concerned with the development of a low-fidelity radar module to train experienced operators under non-typical conditions. Particularly, this paper describes the radar implementation from the TPN-USP Manoeuvring Simulation Center and presents how simple additional effects may be modelled with considerable simplifications to ensure real-time performance. The implementation may be replicated in any ship manoeuvring simulator based on the game engine Unity3D. [ABSTRACT FROM AUTHOR]

Maintenance of rotating machinery is crucial for extending the lifespan and increasing the reliability of equipment onboard ships. Presently, breakdown and preventive methodologies are used for the maintenance of equipment. Further, dataloggers collect critical machinery parameters, and parameter data is used for real-time parameter monitoring. The availability of such extensive monitoring data has also led to the adoption predictive maintenance methodologies in the industry, wherein machine learning-based analysis of recorded data is used to predict impending defects and prompt required maintenance. In this paper, we propose a predictive maintenance system that records data through a network of sensors installed over multiple electrical motor pump sets onboard the ship and uses statistical analysis to detect equipment degradation. Our system has been deployed onboard a ship to undertake real-time predictive maintenance of electrical motor pump sets used in firemain, AC plants, stabilizers, steering pumps and other auxiliary engine room machinery. [ABSTRACT FROM AUTHOR]

South China Sea is the largest sea of China with over 70 percent of it being deep-sea area, which is rich in deep-sea resources, particularly oil, gas, and mineral resources. Besides, high temperature, high humidity, and high salinity are the major features that distinguish South China Sea from other sea areas. Therefore, it is of strategic significance to study marine equipment suitable for resource exploitation in South China Sea. This study first reviews the development status and trend of major marine resource exploitation equipment both in China and abroad, examines the development demand for and key technologies of resource exploitation equipment for South China Sea, and proposes the development goals and ideas for the equipment. Furthermore, several suggestions are proposed from the perspective of equipment and industry development. Specifically, a key technology research and development (R&D) center and an emergency rescue center for deep-sea oil and gas development, a R&D center for deep-sea mineral resource exploitation equipment, a deep-sea aquaculture demonstration and experimental area, and a national deep-sea comprehensive test site in the South China Sea are proposed to be built relying on Hainan Province, thus to gradually establish a national deep-sea science and technology innovation center, a national deep-sea engineering equipment support base, and a national deep-sea science and technology industry center.