Marine accidents often result in significant losses of human life, environmental damage, and property destruction. Additionally, ships and offshore plants are large-scale and complex systems, making safety assessments...Marine accidents often result in significant losses of human life, environmental damage, and property destruction. Additionally, ships and offshore plants are large-scale and complex systems, making safety assessments challenging. However, the advent of onboard electronic systems has made it possible to monitor and respond more effectively. These new technologies can enhance safety levels while reducing the workload on crews. In this paper, authors analyze recent accidents involving ships with high structures above the water, such as car carriers or RoPax vessels, and propose preventive safety indicators to help prevent similar accidents from recurring.展开更多
The hydrodynamic performance of a high forward-speed ship in obliquely propagating waves is numerically examined to assess both free motions and wave field in comparison with a low forward-speed ship.This numerical mo...The hydrodynamic performance of a high forward-speed ship in obliquely propagating waves is numerically examined to assess both free motions and wave field in comparison with a low forward-speed ship.This numerical model is based on the time-domain potential flow theory and higher-order boundary element method,where an analytical expression is completely expanded to determine the base-unsteady coupling flow imposed on the moving condition of the ship.The ship in the numerical model may possess different advancing speeds,i.e.stationary,low speed,and high speed.The role of the water depth,wave height,wave period,and incident wave angle is analyzed by means of the accurate numerical model.It is found that the resonant motions of the high forward-speed ship are triggered by comparison with the stationary one.More specifically,a higher forward speed generates a V-shaped wave region with a larger elevation,which induces stronger resonant motions corresponding to larger wave periods.The shoaling effect is adverse to the motion of the low-speed ship,but is beneficial to the resonant motion of the high-speed ship.When waves obliquely propagate toward the ship,the V-shaped wave region would be broken due to the coupling effect between roll and pitch motions.It is also demonstrated that the maximum heave motion occurs in beam seas for stationary cases but occurs in head waves for high speeds.However,the variation of the pitch motion with period is hardly affected by wave incident angles.展开更多
The maritime administrative department employs synthetic aperture radar (SAR) satellite remote sensing technology to obtain evidence of illegal discharge of ships. If the ship is discharged during navigation, it forms...The maritime administrative department employs synthetic aperture radar (SAR) satellite remote sensing technology to obtain evidence of illegal discharge of ships. If the ship is discharged during navigation, it forms a long dark wake on the SAR image due to the suppression of the Bragg wave by the oil fi lm. This study investigates key techniques for rapid detection of long ship wakes, thereby providing law enforcement agencies with candidate ships for possible discharge. This paper presents a rapid long ship wake detection method that uses satellite imaging parameters and the axial direction of the ship in images to determine the potential detection area of the wake. Then, the threshold of long ship wake detection is determined using statistical analysis, the area is binarized, and isolated points are removed using a morphological filter operator. The method was tested with ENVISAT Synthetic Aperture Radar and GF-3 SAR data, and results showed that the method was eff ective, and the overall accuracy of the decision reaches 71%. We present two innovations;one is a method that draws a Doppler shift curve, and uses the SAR imaging parameters to determine the detection area of the long wake to achieve rapid detection and reduce the image detection area. The other is where a classical linear fitting method is used to quickly and accurately determine whether the detected dark area is a long ship wake and realizes the twisted long ship wake detection caused by the sea surface flow field, which is otherwise diffi cult to detect by the traditional Radon and Hough transform methods. This method has good suppression performance for the dark spot false alarm formed by low speed wind region or upward flow. The method is developed for maritime ship monitoring system and will promote the operational application of maritime ship monitoring system.展开更多
The constant panel method within the framework of potential flow theory in the time domain is developed for solving the hydrodynamic interactions between two parallel ships with forward speed.When solving problems wit...The constant panel method within the framework of potential flow theory in the time domain is developed for solving the hydrodynamic interactions between two parallel ships with forward speed.When solving problems within a time domain framework,the free water surface needs to simultaneously satisfy both the kinematic and dynamic boundary conditions of the free water surface.This provides conditions for adding artificial damping layers.Using the Runge−Kutta method to solve equations related to time.An upwind differential scheme is used in the present method to deal with the convection terms on the free surface to prevent waves upstream.Through the comparison with the available experimental data and other numerical methods,the present method is proved to have good mesh convergence,and satisfactory results can be obtained.The constant panel method is applied to calculate the hydrodynamic interaction responses of two parallel ships advancing in head waves.Numerical simulations are conducted on the effects of forward speed,different longitudinal and lateral distances on the motion response of two modified Wigley ships in head waves.Then further investigations are conducted on the effects of different ship types on the motion response.展开更多
Aiming at defects such as low contrast in infrared ship images,uneven distribution of ship size,and lack of texture details,which will lead to unmanned ship leakage misdetection and slow detection,this paper proposes ...Aiming at defects such as low contrast in infrared ship images,uneven distribution of ship size,and lack of texture details,which will lead to unmanned ship leakage misdetection and slow detection,this paper proposes an infrared ship detection model based on the improved YOLOv8 algorithm(R_YOLO).The algorithm incorporates the Efficient Multi-Scale Attention mechanism(EMA),the efficient Reparameterized Generalized-feature extraction module(CSPStage),the small target detection header,the Repulsion Loss function,and the context aggregation block(CABlock),which are designed to improve the model’s ability to detect targets at multiple scales and the speed of model inference.The algorithm is validated in detail on two vessel datasets.The comprehensive experimental results demonstrate that,in the infrared dataset,the YOLOv8s algorithm exhibits improvements in various performance metrics.Specifically,compared to the baseline algorithm,there is a 3.1%increase in mean average precision at a threshold of 0.5(mAP(0.5)),a 5.4%increase in recall rate,and a 2.2%increase in mAP(0.5:0.95).Simultaneously,while less than 5 times parameters,the mAP(0.5)and frames per second(FPS)exhibit an increase of 1.7%and more than 3 times,respectively,compared to the CAA_YOLO algorithm.Finally,the evaluation indexes on the visible light data set have shown an average improvement of 4.5%.展开更多
Optical image-based ship detection can ensure the safety of ships and promote the orderly management of ships in offshore waters.Current deep learning researches on optical image-based ship detection mainly focus on i...Optical image-based ship detection can ensure the safety of ships and promote the orderly management of ships in offshore waters.Current deep learning researches on optical image-based ship detection mainly focus on improving one-stage detectors for real-time ship detection but sacrifices the accuracy of detection.To solve this problem,we present a hybrid ship detection framework which is named EfficientShip in this paper.The core parts of the EfficientShip are DLA-backboned object location(DBOL)and CascadeRCNN-guided object classification(CROC).The DBOL is responsible for finding potential ship objects,and the CROC is used to categorize the potential ship objects.We also design a pixel-spatial-level data augmentation(PSDA)to reduce the risk of detection model overfitting.We compare the proposed EfficientShip with state-of-the-art(SOTA)literature on a ship detection dataset called Seaships.Experiments show our ship detection framework achieves a result of 99.63%(mAP)at 45 fps,which is much better than 8 SOTA approaches on detection accuracy and can also meet the requirements of real-time application scenarios.展开更多
This study selected the Sino-US route data from the top 30 global container liner companies between December 1,2019,and December 29,2019,as the data source utilizing the complex network research methodology.It constru...This study selected the Sino-US route data from the top 30 global container liner companies between December 1,2019,and December 29,2019,as the data source utilizing the complex network research methodology.It constructs a Sino-US container shipping network through voyage weighting and analyzes the essential structural characteristics to explore the network’s complex structural fea-tures.The network’s evolution is examined from three perspectives,namely,time,space,and event influence,aiming to comprehens-ively explore the network’s evolution mechanism.The results revealed that:1)the weighted Sino-US container shipping network exhib-its small-world and scale-free properties.Key hub ports in the United States include NEW YORK NY,SAVANNAH GA,LOS ANGELES CA,and OAKLAND CA,whereas SHANGHAI serving as the hub port in China.The geographical distribution of these hub ports is uneven.2)Concerning the evolution of the weighted Sino-US container shipping network,from a temporal perspective,the evolution of the regional structure of the entire Sino-US region and the Inland United States is in a stage of radiative expansion and de-velopment,with a need for further enhancement in competitiveness and development speed.The evolution of the regional structure of southern China and Europe is transitioning from the stage of radiative expansion and development to an advanced equilibrium stage.The shipping development in Northern China,the Western and Eastern United States,and Asia is undergoing significant changes but faces challenges of fierce competition and imbalances.From a spatial perspective,the rationality and effectiveness of the improved weighted Barrat-Barthelemy-Vespignani(BBV)model are confirmed through theoretical derivation.The applicability of the improved evolution model is verified by simulating the evolution of the weighted Sino-US container shipping network.From an event impact per-spective,the Corona Virus Disease 2019(COVID-19)pandemic has not fundamentally affected the spatial pattern of the weighted Sino-US container shipping network but has significantly impacted the network’s connectivity.The network lacks sufficient resilience and stability in emergency situations.3)Based on the analysis of the structural characteristics and evolution of the weighted Sino-US con-tainer shipping network,recommendations for network development are proposed from three aspects:emphasizing the development of hub ports,focusing on the balanced development of the network,and optimizing the layout of Chinese ports.展开更多
In order to extract the richer feature information of ship targets from sea clutter, and address the high dimensional data problem, a method termed as multi-scale fusion kernel sparse preserving projection(MSFKSPP) ba...In order to extract the richer feature information of ship targets from sea clutter, and address the high dimensional data problem, a method termed as multi-scale fusion kernel sparse preserving projection(MSFKSPP) based on the maximum margin criterion(MMC) is proposed for recognizing the class of ship targets utilizing the high-resolution range profile(HRRP). Multi-scale fusion is introduced to capture the local and detailed information in small-scale features, and the global and contour information in large-scale features, offering help to extract the edge information from sea clutter and further improving the target recognition accuracy. The proposed method can maximally preserve the multi-scale fusion sparse of data and maximize the class separability in the reduced dimensionality by reproducing kernel Hilbert space. Experimental results on the measured radar data show that the proposed method can effectively extract the features of ship target from sea clutter, further reduce the feature dimensionality, and improve target recognition performance.展开更多
This paper focuses on the optimization method for multi-skilled painting personnel scheduling.The budget working time analysis is carried out considering the influence of operating area,difficulty of spraying area,mul...This paper focuses on the optimization method for multi-skilled painting personnel scheduling.The budget working time analysis is carried out considering the influence of operating area,difficulty of spraying area,multi-skilled workers,and worker’s efficiency,then a mathematical model is established to minimize the completion time. The constraints of task priority,paint preparation,pump management,and neighbor avoidance in the ship block painting production are considered. Based on this model,an improved scatter search(ISS)algorithm is designed,and the hybrid approximate dynamic programming(ADP)algorithm is used to improve search efficiency. In addition,the two solution combination methods of path-relinking and task sequence combination are used to enhance the search breadth and depth. The numerical experimental results show that ISS has a significant advantage in solving efficiency compared with the solver in small scale instances;Compared with the scatter search algorithm and genetic algorithm,ISS can stably improve the solution quality. Verified by the production example,ISS effectively shortens the total completion time of the production,which is suitable for scheduling problems in the actual painting production of the shipyard.展开更多
The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition...The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition can be influenced.For addressing this issue,a method for extracting ship targets with overlaps via the expectation maximization(EM)algorithm is pro-posed.First,the scatterers of ship targets are obtained via the target detection technique.Then,the EM algorithm is applied to extract the scatterers of a single ship target with a single IPP.Afterwards,a novel image amplitude estimation approach is pro-posed,with which the radar image of a single target with a sin-gle IPP can be generated.The proposed method can accom-plish IPP selection and targets separation in the image domain,which can improve the image quality and reserve the target information most possibly.Results of simulated and real mea-sured data demonstrate the effectiveness of the proposed method.展开更多
Investigating how COVID-19 has influenced Liquefied Natural Gas(LNG)is significant for benefits evaluation for shipping companies and safety management for sustainable LNG shipping in case of accidents.This paper prop...Investigating how COVID-19 has influenced Liquefied Natural Gas(LNG)is significant for benefits evaluation for shipping companies and safety management for sustainable LNG shipping in case of accidents.This paper proposes a quantitative method to model the impact of COVID-19 on global LNG shipping efficiency based on the spatiotemporal characteristics of behavior mining for LNG ships.The time cost for LNG carriers serving inside LNG terminals is calculated based on the status of LNG carriers specifically based on arrival and departure times.Then,the time series analysis method is employed to extract the statistical characteristics of the COVID-19 severity index and time cost for LNG carriers inside LNG terminals.Finally,the impact of COVID-19 on global LNG shipping is explored through the Vector Autoregressive Model(VAR)combined with the sliding window.The results demonstrate that the COVID-19 pandemic has a certain influence on the service time for LNG carriers with time lags worldwide.The impact is spatial heterogeneity on a large scale or small scale across global,countries,and trading terminals.It can be used for decision-making in energy safety and LNG intelligent shipping management under unexpected global public health events in the future.The results provide support for intelligent decision-making for safety management under unexpected public health events,such as reducing the seafarer’s explosion to risk events and taking efficient actions to ensure the shipping flow to avoid the energy supply shortage.展开更多
This study aims to investigate whether Corporate Social Responsibility(CSR)activities reduce supply chain disruptions by examining the impact of the Suez Canal obstruction on the Ever Given container ship in March 202...This study aims to investigate whether Corporate Social Responsibility(CSR)activities reduce supply chain disruptions by examining the impact of the Suez Canal obstruction on the Ever Given container ship in March 2021.This study conclude that the more responsible companies have higher returns and are less affected by this event than the less responsible companies;the less responsible companies have lower returns.The companies with better CSR have a lower impact on their supply chains when faced with disruptions in the supply chain.展开更多
The main challenge for container ports is the planning required for berthing container ships while docked in port.Growth of containerization is creating problems for ports and container terminals as they reach their c...The main challenge for container ports is the planning required for berthing container ships while docked in port.Growth of containerization is creating problems for ports and container terminals as they reach their capacity limits of various resources which increasingly leads to traffic and port congestion.Good planning and management of container terminal operations reduces waiting time for liner ships.Reducing the waiting time improves the terminal’s productivity and decreases the port difficulties.Two important keys to reducing waiting time with berth allocation are determining suitable access channel depths and increasing the number of berths which in this paper are studied and analyzed as practical solutions.Simulation based analysis is the only way to understand how various resources interact with each other and how they are affected in the berthing time of ships.We used the Enterprise Dynamics software to produce simulation models due to the complexity and nature of the problems.We further present case study for berth allocation simulation of the biggest container terminal in Iran and the optimum access channel depth and the number of berths are obtained from simulation results.The results show a significant reduction in the waiting time for container ships and can be useful for major functions in operations and development of container ship terminals.展开更多
Various structures such as marine structures age over time. In order to always maintain safety conditions, maintenance processes including inspection and repair should be implemented on them. Corrosion and fatigue cra...Various structures such as marine structures age over time. In order to always maintain safety conditions, maintenance processes including inspection and repair should be implemented on them. Corrosion and fatigue cracks are two main factors that reduce the ultimate strength of the ship's hull girder over time and thus increase the probability and risk of failure. At the time of inspection,the structural conditions must be checked so that, if necessary, the required repairs can be done on it. The main objective of this paper is to provide optimized maintenance plans of the ship structure based on probabilistic concepts with regard to corrosion and fatigue cracks. Maintenance activities increase the operational costs of ships; therefore, it is advisable to inspect and repair in the optimal times. Optimal maintenance planning of the ship structure can be conducted by formulating and solving a multi-objective optimization problem. The use of risk as a structural performance indicator has become more common in recent years. The objective functions of the optimization problem include minimizing the structure's lifecycle maintenance costs, including inspection and repair costs, and also minimizing the maximum risk of structural failure during the ship's life. In the following,to achieve better responses, reliability index has been added to the problem as the third objective function. The multi-objective optimization problem is solved using genetic algorithms. The proposed risk-based approach is applied to the hull structure of a tanker ship.展开更多
The transformation of parallel translation can improve the smoothness of discrete series sometimes. In this paper, for ship pitch, a method to modify the system error is proposed via the transformation of parallel tra...The transformation of parallel translation can improve the smoothness of discrete series sometimes. In this paper, for ship pitch, a method to modify the system error is proposed via the transformation of parallel translation, which can give the optimize parameters using the Method of Minimum Squares. The series in the method can fit white exponential law better, and then be applied in GM (1,1) very well. The numerical experiments imply that the method is practical, which make the ship pitch system model more accurate than GM ( 1,1 ).展开更多
Fine-grained recognition of ships based on remote sensing images is crucial to safeguarding maritime rights and interests and maintaining national security.Currently,with the emergence of massive high-resolution multi...Fine-grained recognition of ships based on remote sensing images is crucial to safeguarding maritime rights and interests and maintaining national security.Currently,with the emergence of massive high-resolution multi-modality images,the use of multi-modality images for fine-grained recognition has become a promising technology.Fine-grained recognition of multi-modality images imposes higher requirements on the dataset samples.The key to the problem is how to extract and fuse the complementary features of multi-modality images to obtain more discriminative fusion features.The attention mechanism helps the model to pinpoint the key information in the image,resulting in a significant improvement in the model’s performance.In this paper,a dataset for fine-grained recognition of ships based on visible and near-infrared multi-modality remote sensing images has been proposed first,named Dataset for Multimodal Fine-grained Recognition of Ships(DMFGRS).It includes 1,635 pairs of visible and near-infrared remote sensing images divided into 20 categories,collated from digital orthophotos model provided by commercial remote sensing satellites.DMFGRS provides two types of annotation format files,as well as segmentation mask images corresponding to the ship targets.Then,a Multimodal Information Cross-Enhancement Network(MICE-Net)fusing features of visible and near-infrared remote sensing images,has been proposed.In the network,a dual-branch feature extraction and fusion module has been designed to obtain more expressive features.The Feature Cross Enhancement Module(FCEM)achieves the fusion enhancement of the two modal features by making the channel attention and spatial attention work cross-functionally on the feature map.A benchmark is established by evaluating state-of-the-art object recognition algorithms on DMFGRS.MICE-Net conducted experiments on DMFGRS,and the precision,recall,mAP0.5 and mAP0.5:0.95 reached 87%,77.1%,83.8%and 63.9%,respectively.Extensive experiments demonstrate that the proposed MICE-Net has more excellent performance on DMFGRS.Built on lightweight network YOLO,the model has excellent generalizability,and thus has good potential for application in real-life scenarios.展开更多
The high coverage and all-weather capabilities of Synthetic Aperture Radar(SAR)image ship detection make it a widely accepted method for maritime ship positioning and identification.However,SAR ship detection faces ch...The high coverage and all-weather capabilities of Synthetic Aperture Radar(SAR)image ship detection make it a widely accepted method for maritime ship positioning and identification.However,SAR ship detection faces challenges such as indistinct ship contours,low resolution,multi-scale features,noise,and complex background interference.This paper proposes a lightweight YOLOv8 model for small object detection in SAR ship images,incorporating key structures to enhance performance.The YOLOv8 backbone is replaced by the Slim Backbone(SB),and the Delete Medium-sized Detection Head(DMDH)structure is eliminated to concentrate on shallow features.Dynamically adjusting the convolution kernel weights of the Omni-Dimensional Dynamic Convolution(ODConv)module can result in a reduction in computation and enhanced accuracy.Adjusting the model’s receptive field is done by the Large Selective Kernel Network(LSKNet)module,which captures shallow features.Additionally,a Multi-scale Spatial-Channel Attention(MSCA)module addresses multi-scale ship feature differences,enhancing feature fusion and local region focus.Experimental results on the HRSID and SSDD datasets demonstrate the model’s effectiveness,with a 67.8%reduction in parameters,a 3.4%improvement in AP(average precision)@0.5,and a 5.4%improvement in AP@0.5:0.95 on the HRSID dataset,and a 0.5%improvement in AP@0.5 and 1.7%in AP@0.5:0.95 on the SSDD dataset,surpassing other state-of-the-art methods.展开更多
Using the ‘theoretical hypothesis—empirical study—case verification' method, this paper studies the spatial distribution and differentiation of port & shipping service enterprises(PSSE), as well as the vari...Using the ‘theoretical hypothesis—empirical study—case verification' method, this paper studies the spatial distribution and differentiation of port & shipping service enterprises(PSSE), as well as the variation process and underlying mechanism in the Yangtze River Delta(YRD). First, through inductive and deductive reasoning, we propose the following hypothesis: the regional distribution of different types of PSSE would show different spatial agglomeration-decentralization tendency; and there would be distinct regional differentiation in the industrial structure of the enterprises. Second, based on data obtained from enterprises, empirical research is conducted using Gini coefficient and spatial interpolation simulation methods. Results show that: 1) The overall enterprise distribution is decentralized within a city. 2) Different types of enterprises show different spatial agglomeration-decentralization tendencies. At 3000 m×3000 m grid scale, there is an agglomeration tendency along seas and rivers in the spatial distribution of enterprises. Shanghai has been identified consistently as a hot spot. 3) There is significant regional differentiation in 12 port cities with respect to the industrial structures of enterprises. Finally, the transportization and the increase of shipping service demand, the globalization and the expansion of multinational corporate activities, the hierarchization and the cooperation among port cities as well as the decentralization and the behavioral difference between the central and local states can be seen as main driving mechanism of the spatial phenomenon.展开更多
The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship i...The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship inspection using data obtained from automatic identification system(AIS).The research also focuses on the integration of shipping database,AIS data,and others to develop a prototype for designing a real-time monitoring system of offshore platforms and pipelines.A simple concept is used in the development of this prototype,which is achieved by using an overlaying map that outlines the coordinates of the offshore platform and subsea gas pipeline with the ship’s coordinates(longitude/latitude)as detected by AIS.Using such information,we can then build an early warning system(EWS)relayed through short message service(SMS),email,or other means when the ship enters the restricted and exclusion zone of platforms and pipelines.The ship inspection system is developed by combining several attributes.Then,decision analysis software is employed to prioritize the vessel’s four attributes,including ship age,ship type,classification,and flag state.Results show that the EWS can increase the safety level of offshore platforms and pipelines,as well as the efficient use of patrol boats in monitoring the safety of the facilities.Meanwhile,ship inspection enables the port to prioritize the ship to be inspected in accordance with the priority ranking inspection score.展开更多
文摘Marine accidents often result in significant losses of human life, environmental damage, and property destruction. Additionally, ships and offshore plants are large-scale and complex systems, making safety assessments challenging. However, the advent of onboard electronic systems has made it possible to monitor and respond more effectively. These new technologies can enhance safety levels while reducing the workload on crews. In this paper, authors analyze recent accidents involving ships with high structures above the water, such as car carriers or RoPax vessels, and propose preventive safety indicators to help prevent similar accidents from recurring.
基金supported by the National Natural Science Foundation of China(Grant Nos.52271278 and 52111530137)the Natural Science Foundation of Jiangsu Province(Grant No.SBK2022020579)the Newton Advanced Fellowships by the Royal Society(Grant No.NAF\R1\180304).
文摘The hydrodynamic performance of a high forward-speed ship in obliquely propagating waves is numerically examined to assess both free motions and wave field in comparison with a low forward-speed ship.This numerical model is based on the time-domain potential flow theory and higher-order boundary element method,where an analytical expression is completely expanded to determine the base-unsteady coupling flow imposed on the moving condition of the ship.The ship in the numerical model may possess different advancing speeds,i.e.stationary,low speed,and high speed.The role of the water depth,wave height,wave period,and incident wave angle is analyzed by means of the accurate numerical model.It is found that the resonant motions of the high forward-speed ship are triggered by comparison with the stationary one.More specifically,a higher forward speed generates a V-shaped wave region with a larger elevation,which induces stronger resonant motions corresponding to larger wave periods.The shoaling effect is adverse to the motion of the low-speed ship,but is beneficial to the resonant motion of the high-speed ship.When waves obliquely propagate toward the ship,the V-shaped wave region would be broken due to the coupling effect between roll and pitch motions.It is also demonstrated that the maximum heave motion occurs in beam seas for stationary cases but occurs in head waves for high speeds.However,the variation of the pitch motion with period is hardly affected by wave incident angles.
基金Supported by the National Natural Science Foundation of China(No.41476088)the National High Resolution Project of China(No.41Y30B12-9001-14/16)+1 种基金the 2016 Key Projects for Marine Environmental Security(No.2016YFC14032)the research grants of the Second Institute of Oceanography,MNR(No.JT1307)
文摘The maritime administrative department employs synthetic aperture radar (SAR) satellite remote sensing technology to obtain evidence of illegal discharge of ships. If the ship is discharged during navigation, it forms a long dark wake on the SAR image due to the suppression of the Bragg wave by the oil fi lm. This study investigates key techniques for rapid detection of long ship wakes, thereby providing law enforcement agencies with candidate ships for possible discharge. This paper presents a rapid long ship wake detection method that uses satellite imaging parameters and the axial direction of the ship in images to determine the potential detection area of the wake. Then, the threshold of long ship wake detection is determined using statistical analysis, the area is binarized, and isolated points are removed using a morphological filter operator. The method was tested with ENVISAT Synthetic Aperture Radar and GF-3 SAR data, and results showed that the method was eff ective, and the overall accuracy of the decision reaches 71%. We present two innovations;one is a method that draws a Doppler shift curve, and uses the SAR imaging parameters to determine the detection area of the long wake to achieve rapid detection and reduce the image detection area. The other is where a classical linear fitting method is used to quickly and accurately determine whether the detected dark area is a long ship wake and realizes the twisted long ship wake detection caused by the sea surface flow field, which is otherwise diffi cult to detect by the traditional Radon and Hough transform methods. This method has good suppression performance for the dark spot false alarm formed by low speed wind region or upward flow. The method is developed for maritime ship monitoring system and will promote the operational application of maritime ship monitoring system.
基金supported by the National Natural Science Foundation of China(Grant Nos.52271278 and 52111530137)the Natural Science Found of Jiangsu Province(Grant No.BK20221389)the Newton Advanced Fellowships(Grant No.NAF\R1\180304)by the Royal Society.
文摘The constant panel method within the framework of potential flow theory in the time domain is developed for solving the hydrodynamic interactions between two parallel ships with forward speed.When solving problems within a time domain framework,the free water surface needs to simultaneously satisfy both the kinematic and dynamic boundary conditions of the free water surface.This provides conditions for adding artificial damping layers.Using the Runge−Kutta method to solve equations related to time.An upwind differential scheme is used in the present method to deal with the convection terms on the free surface to prevent waves upstream.Through the comparison with the available experimental data and other numerical methods,the present method is proved to have good mesh convergence,and satisfactory results can be obtained.The constant panel method is applied to calculate the hydrodynamic interaction responses of two parallel ships advancing in head waves.Numerical simulations are conducted on the effects of forward speed,different longitudinal and lateral distances on the motion response of two modified Wigley ships in head waves.Then further investigations are conducted on the effects of different ship types on the motion response.
文摘Aiming at defects such as low contrast in infrared ship images,uneven distribution of ship size,and lack of texture details,which will lead to unmanned ship leakage misdetection and slow detection,this paper proposes an infrared ship detection model based on the improved YOLOv8 algorithm(R_YOLO).The algorithm incorporates the Efficient Multi-Scale Attention mechanism(EMA),the efficient Reparameterized Generalized-feature extraction module(CSPStage),the small target detection header,the Repulsion Loss function,and the context aggregation block(CABlock),which are designed to improve the model’s ability to detect targets at multiple scales and the speed of model inference.The algorithm is validated in detail on two vessel datasets.The comprehensive experimental results demonstrate that,in the infrared dataset,the YOLOv8s algorithm exhibits improvements in various performance metrics.Specifically,compared to the baseline algorithm,there is a 3.1%increase in mean average precision at a threshold of 0.5(mAP(0.5)),a 5.4%increase in recall rate,and a 2.2%increase in mAP(0.5:0.95).Simultaneously,while less than 5 times parameters,the mAP(0.5)and frames per second(FPS)exhibit an increase of 1.7%and more than 3 times,respectively,compared to the CAA_YOLO algorithm.Finally,the evaluation indexes on the visible light data set have shown an average improvement of 4.5%.
基金This work was supported by the Outstanding Youth Science and Technology Innovation Team Project of Colleges and Universities in Hubei Province(Grant No.T201923)Key Science and Technology Project of Jingmen(Grant Nos.2021ZDYF024,2022ZDYF019)+2 种基金LIAS Pioneering Partnerships Award,UK(Grant No.P202ED10)Data Science Enhancement Fund,UK(Grant No.P202RE237)Cultivation Project of Jingchu University of Technology(Grant No.PY201904).
文摘Optical image-based ship detection can ensure the safety of ships and promote the orderly management of ships in offshore waters.Current deep learning researches on optical image-based ship detection mainly focus on improving one-stage detectors for real-time ship detection but sacrifices the accuracy of detection.To solve this problem,we present a hybrid ship detection framework which is named EfficientShip in this paper.The core parts of the EfficientShip are DLA-backboned object location(DBOL)and CascadeRCNN-guided object classification(CROC).The DBOL is responsible for finding potential ship objects,and the CROC is used to categorize the potential ship objects.We also design a pixel-spatial-level data augmentation(PSDA)to reduce the risk of detection model overfitting.We compare the proposed EfficientShip with state-of-the-art(SOTA)literature on a ship detection dataset called Seaships.Experiments show our ship detection framework achieves a result of 99.63%(mAP)at 45 fps,which is much better than 8 SOTA approaches on detection accuracy and can also meet the requirements of real-time application scenarios.
基金Under the auspices of National Natural Science Foundation of China(No.41201473,41371975)。
文摘This study selected the Sino-US route data from the top 30 global container liner companies between December 1,2019,and December 29,2019,as the data source utilizing the complex network research methodology.It constructs a Sino-US container shipping network through voyage weighting and analyzes the essential structural characteristics to explore the network’s complex structural fea-tures.The network’s evolution is examined from three perspectives,namely,time,space,and event influence,aiming to comprehens-ively explore the network’s evolution mechanism.The results revealed that:1)the weighted Sino-US container shipping network exhib-its small-world and scale-free properties.Key hub ports in the United States include NEW YORK NY,SAVANNAH GA,LOS ANGELES CA,and OAKLAND CA,whereas SHANGHAI serving as the hub port in China.The geographical distribution of these hub ports is uneven.2)Concerning the evolution of the weighted Sino-US container shipping network,from a temporal perspective,the evolution of the regional structure of the entire Sino-US region and the Inland United States is in a stage of radiative expansion and de-velopment,with a need for further enhancement in competitiveness and development speed.The evolution of the regional structure of southern China and Europe is transitioning from the stage of radiative expansion and development to an advanced equilibrium stage.The shipping development in Northern China,the Western and Eastern United States,and Asia is undergoing significant changes but faces challenges of fierce competition and imbalances.From a spatial perspective,the rationality and effectiveness of the improved weighted Barrat-Barthelemy-Vespignani(BBV)model are confirmed through theoretical derivation.The applicability of the improved evolution model is verified by simulating the evolution of the weighted Sino-US container shipping network.From an event impact per-spective,the Corona Virus Disease 2019(COVID-19)pandemic has not fundamentally affected the spatial pattern of the weighted Sino-US container shipping network but has significantly impacted the network’s connectivity.The network lacks sufficient resilience and stability in emergency situations.3)Based on the analysis of the structural characteristics and evolution of the weighted Sino-US con-tainer shipping network,recommendations for network development are proposed from three aspects:emphasizing the development of hub ports,focusing on the balanced development of the network,and optimizing the layout of Chinese ports.
基金supported by the National Natural Science Foundation of China (62271255,61871218)the Fundamental Research Funds for the Central University (3082019NC2019002)+1 种基金the Aeronautical Science Foundation (ASFC-201920007002)the Program of Remote Sensing Intelligent Monitoring and Emergency Services for Regional Security Elements。
文摘In order to extract the richer feature information of ship targets from sea clutter, and address the high dimensional data problem, a method termed as multi-scale fusion kernel sparse preserving projection(MSFKSPP) based on the maximum margin criterion(MMC) is proposed for recognizing the class of ship targets utilizing the high-resolution range profile(HRRP). Multi-scale fusion is introduced to capture the local and detailed information in small-scale features, and the global and contour information in large-scale features, offering help to extract the edge information from sea clutter and further improving the target recognition accuracy. The proposed method can maximally preserve the multi-scale fusion sparse of data and maximize the class separability in the reduced dimensionality by reproducing kernel Hilbert space. Experimental results on the measured radar data show that the proposed method can effectively extract the features of ship target from sea clutter, further reduce the feature dimensionality, and improve target recognition performance.
基金Sponsored by the Ministry of Industry and Information Technology of China(Grant No.MIIT[2019]359)。
文摘This paper focuses on the optimization method for multi-skilled painting personnel scheduling.The budget working time analysis is carried out considering the influence of operating area,difficulty of spraying area,multi-skilled workers,and worker’s efficiency,then a mathematical model is established to minimize the completion time. The constraints of task priority,paint preparation,pump management,and neighbor avoidance in the ship block painting production are considered. Based on this model,an improved scatter search(ISS)algorithm is designed,and the hybrid approximate dynamic programming(ADP)algorithm is used to improve search efficiency. In addition,the two solution combination methods of path-relinking and task sequence combination are used to enhance the search breadth and depth. The numerical experimental results show that ISS has a significant advantage in solving efficiency compared with the solver in small scale instances;Compared with the scatter search algorithm and genetic algorithm,ISS can stably improve the solution quality. Verified by the production example,ISS effectively shortens the total completion time of the production,which is suitable for scheduling problems in the actual painting production of the shipyard.
基金This work was supported by the National Science Fund for Distinguished Young Scholars(62325104).
文摘The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition can be influenced.For addressing this issue,a method for extracting ship targets with overlaps via the expectation maximization(EM)algorithm is pro-posed.First,the scatterers of ship targets are obtained via the target detection technique.Then,the EM algorithm is applied to extract the scatterers of a single ship target with a single IPP.Afterwards,a novel image amplitude estimation approach is pro-posed,with which the radar image of a single target with a sin-gle IPP can be generated.The proposed method can accom-plish IPP selection and targets separation in the image domain,which can improve the image quality and reserve the target information most possibly.Results of simulated and real mea-sured data demonstrate the effectiveness of the proposed method.
基金National Natural Science Foundation of China(No.42101429 and No.42371415)Young Elite Scientists Sponsorship Program by China Association for Science and Technology(CAST)(No.YESS20220491)+2 种基金Project of Education Department of Hainan Province(No.Hnjg2024-284)Open Fund of State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University(No.21S04)National Key Research and Development Program of China(No.2022YFC3302703).
文摘Investigating how COVID-19 has influenced Liquefied Natural Gas(LNG)is significant for benefits evaluation for shipping companies and safety management for sustainable LNG shipping in case of accidents.This paper proposes a quantitative method to model the impact of COVID-19 on global LNG shipping efficiency based on the spatiotemporal characteristics of behavior mining for LNG ships.The time cost for LNG carriers serving inside LNG terminals is calculated based on the status of LNG carriers specifically based on arrival and departure times.Then,the time series analysis method is employed to extract the statistical characteristics of the COVID-19 severity index and time cost for LNG carriers inside LNG terminals.Finally,the impact of COVID-19 on global LNG shipping is explored through the Vector Autoregressive Model(VAR)combined with the sliding window.The results demonstrate that the COVID-19 pandemic has a certain influence on the service time for LNG carriers with time lags worldwide.The impact is spatial heterogeneity on a large scale or small scale across global,countries,and trading terminals.It can be used for decision-making in energy safety and LNG intelligent shipping management under unexpected global public health events in the future.The results provide support for intelligent decision-making for safety management under unexpected public health events,such as reducing the seafarer’s explosion to risk events and taking efficient actions to ensure the shipping flow to avoid the energy supply shortage.
文摘This study aims to investigate whether Corporate Social Responsibility(CSR)activities reduce supply chain disruptions by examining the impact of the Suez Canal obstruction on the Ever Given container ship in March 2021.This study conclude that the more responsible companies have higher returns and are less affected by this event than the less responsible companies;the less responsible companies have lower returns.The companies with better CSR have a lower impact on their supply chains when faced with disruptions in the supply chain.
文摘The main challenge for container ports is the planning required for berthing container ships while docked in port.Growth of containerization is creating problems for ports and container terminals as they reach their capacity limits of various resources which increasingly leads to traffic and port congestion.Good planning and management of container terminal operations reduces waiting time for liner ships.Reducing the waiting time improves the terminal’s productivity and decreases the port difficulties.Two important keys to reducing waiting time with berth allocation are determining suitable access channel depths and increasing the number of berths which in this paper are studied and analyzed as practical solutions.Simulation based analysis is the only way to understand how various resources interact with each other and how they are affected in the berthing time of ships.We used the Enterprise Dynamics software to produce simulation models due to the complexity and nature of the problems.We further present case study for berth allocation simulation of the biggest container terminal in Iran and the optimum access channel depth and the number of berths are obtained from simulation results.The results show a significant reduction in the waiting time for container ships and can be useful for major functions in operations and development of container ship terminals.
文摘Various structures such as marine structures age over time. In order to always maintain safety conditions, maintenance processes including inspection and repair should be implemented on them. Corrosion and fatigue cracks are two main factors that reduce the ultimate strength of the ship's hull girder over time and thus increase the probability and risk of failure. At the time of inspection,the structural conditions must be checked so that, if necessary, the required repairs can be done on it. The main objective of this paper is to provide optimized maintenance plans of the ship structure based on probabilistic concepts with regard to corrosion and fatigue cracks. Maintenance activities increase the operational costs of ships; therefore, it is advisable to inspect and repair in the optimal times. Optimal maintenance planning of the ship structure can be conducted by formulating and solving a multi-objective optimization problem. The use of risk as a structural performance indicator has become more common in recent years. The objective functions of the optimization problem include minimizing the structure's lifecycle maintenance costs, including inspection and repair costs, and also minimizing the maximum risk of structural failure during the ship's life. In the following,to achieve better responses, reliability index has been added to the problem as the third objective function. The multi-objective optimization problem is solved using genetic algorithms. The proposed risk-based approach is applied to the hull structure of a tanker ship.
文摘The transformation of parallel translation can improve the smoothness of discrete series sometimes. In this paper, for ship pitch, a method to modify the system error is proposed via the transformation of parallel translation, which can give the optimize parameters using the Method of Minimum Squares. The series in the method can fit white exponential law better, and then be applied in GM (1,1) very well. The numerical experiments imply that the method is practical, which make the ship pitch system model more accurate than GM ( 1,1 ).
文摘Fine-grained recognition of ships based on remote sensing images is crucial to safeguarding maritime rights and interests and maintaining national security.Currently,with the emergence of massive high-resolution multi-modality images,the use of multi-modality images for fine-grained recognition has become a promising technology.Fine-grained recognition of multi-modality images imposes higher requirements on the dataset samples.The key to the problem is how to extract and fuse the complementary features of multi-modality images to obtain more discriminative fusion features.The attention mechanism helps the model to pinpoint the key information in the image,resulting in a significant improvement in the model’s performance.In this paper,a dataset for fine-grained recognition of ships based on visible and near-infrared multi-modality remote sensing images has been proposed first,named Dataset for Multimodal Fine-grained Recognition of Ships(DMFGRS).It includes 1,635 pairs of visible and near-infrared remote sensing images divided into 20 categories,collated from digital orthophotos model provided by commercial remote sensing satellites.DMFGRS provides two types of annotation format files,as well as segmentation mask images corresponding to the ship targets.Then,a Multimodal Information Cross-Enhancement Network(MICE-Net)fusing features of visible and near-infrared remote sensing images,has been proposed.In the network,a dual-branch feature extraction and fusion module has been designed to obtain more expressive features.The Feature Cross Enhancement Module(FCEM)achieves the fusion enhancement of the two modal features by making the channel attention and spatial attention work cross-functionally on the feature map.A benchmark is established by evaluating state-of-the-art object recognition algorithms on DMFGRS.MICE-Net conducted experiments on DMFGRS,and the precision,recall,mAP0.5 and mAP0.5:0.95 reached 87%,77.1%,83.8%and 63.9%,respectively.Extensive experiments demonstrate that the proposed MICE-Net has more excellent performance on DMFGRS.Built on lightweight network YOLO,the model has excellent generalizability,and thus has good potential for application in real-life scenarios.
基金supported by the Open Research Fund Program of State Key Laboratory of Maritime Technology and Safety in 2024the National Natural Science Foundation of China(Grant No.52331012)the Natural Science Foundation of Shanghai(Grant No.21ZR1426500).
文摘The high coverage and all-weather capabilities of Synthetic Aperture Radar(SAR)image ship detection make it a widely accepted method for maritime ship positioning and identification.However,SAR ship detection faces challenges such as indistinct ship contours,low resolution,multi-scale features,noise,and complex background interference.This paper proposes a lightweight YOLOv8 model for small object detection in SAR ship images,incorporating key structures to enhance performance.The YOLOv8 backbone is replaced by the Slim Backbone(SB),and the Delete Medium-sized Detection Head(DMDH)structure is eliminated to concentrate on shallow features.Dynamically adjusting the convolution kernel weights of the Omni-Dimensional Dynamic Convolution(ODConv)module can result in a reduction in computation and enhanced accuracy.Adjusting the model’s receptive field is done by the Large Selective Kernel Network(LSKNet)module,which captures shallow features.Additionally,a Multi-scale Spatial-Channel Attention(MSCA)module addresses multi-scale ship feature differences,enhancing feature fusion and local region focus.Experimental results on the HRSID and SSDD datasets demonstrate the model’s effectiveness,with a 67.8%reduction in parameters,a 3.4%improvement in AP(average precision)@0.5,and a 5.4%improvement in AP@0.5:0.95 on the HRSID dataset,and a 0.5%improvement in AP@0.5 and 1.7%in AP@0.5:0.95 on the SSDD dataset,surpassing other state-of-the-art methods.
基金Under the auspices of National Natural Science Foundation of China(No.41771139,41671132,41801111)Natural Science Foundation of Jiangsu Province(No.BK20171516)Natural Science Foundation of Zhejiang Province(No.LY18D010004)
文摘Using the ‘theoretical hypothesis—empirical study—case verification' method, this paper studies the spatial distribution and differentiation of port & shipping service enterprises(PSSE), as well as the variation process and underlying mechanism in the Yangtze River Delta(YRD). First, through inductive and deductive reasoning, we propose the following hypothesis: the regional distribution of different types of PSSE would show different spatial agglomeration-decentralization tendency; and there would be distinct regional differentiation in the industrial structure of the enterprises. Second, based on data obtained from enterprises, empirical research is conducted using Gini coefficient and spatial interpolation simulation methods. Results show that: 1) The overall enterprise distribution is decentralized within a city. 2) Different types of enterprises show different spatial agglomeration-decentralization tendencies. At 3000 m×3000 m grid scale, there is an agglomeration tendency along seas and rivers in the spatial distribution of enterprises. Shanghai has been identified consistently as a hot spot. 3) There is significant regional differentiation in 12 port cities with respect to the industrial structures of enterprises. Finally, the transportization and the increase of shipping service demand, the globalization and the expansion of multinational corporate activities, the hierarchization and the cooperation among port cities as well as the decentralization and the behavioral difference between the central and local states can be seen as main driving mechanism of the spatial phenomenon.
文摘The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship inspection using data obtained from automatic identification system(AIS).The research also focuses on the integration of shipping database,AIS data,and others to develop a prototype for designing a real-time monitoring system of offshore platforms and pipelines.A simple concept is used in the development of this prototype,which is achieved by using an overlaying map that outlines the coordinates of the offshore platform and subsea gas pipeline with the ship’s coordinates(longitude/latitude)as detected by AIS.Using such information,we can then build an early warning system(EWS)relayed through short message service(SMS),email,or other means when the ship enters the restricted and exclusion zone of platforms and pipelines.The ship inspection system is developed by combining several attributes.Then,decision analysis software is employed to prioritize the vessel’s four attributes,including ship age,ship type,classification,and flag state.Results show that the EWS can increase the safety level of offshore platforms and pipelines,as well as the efficient use of patrol boats in monitoring the safety of the facilities.Meanwhile,ship inspection enables the port to prioritize the ship to be inspected in accordance with the priority ranking inspection score.
