338 results about "Ship motions" patented technology

The invention relates to a saline intrusion measurement method, system and equipment based on dynamic ship motion conditions and a medium, and aims to solve the technical problem that the salinity inversion precision is reduced due to spatial-temporal dislocation between particle image velocity measurement flow field data and plane laser-induced fluorescence concentration field data caused by ship six-degree-of-freedom motion. According to the method, future poses are predicted by collecting ship motion parameters and environment disturbance parameters, and space-time compensation parameters are generated in combination with a static calibration matrix; performing three-dimensional coordinate transformation and time synchronization on synchronously acquired original flow field and concentration field data by applying compensation parameters, and eliminating space-time deviation caused by ship movement; a three-dimensional salinity distribution field is calculated based on registration data fusion flow field diffusion characteristics and concentration field distribution; and meanwhile, the pose of the measuring equipment is dynamically adjusted through the closed-loop controller so as to optimize the data acquisition quality. According to the method, ship motion interference is effectively inhibited, and accurate characterization of saline invasion frontal surface spatial characteristics is guaranteed.

The invention relates to a ship automatic berthing safety control system, and belongs to the technical field of port ship operation safety control. The system comprises four core modules which are sequentially connected to form closed-loop control: a situation synchronous sensing module generates total-factor dynamic attitude information through space-time synchronization and data fusion of a ship-shore inertial unit; the digital twin deduction module performs real-time simulation based on a ship six-degree-of-freedom motion model, and predicts a ship motion track and berth acting force in a prospective manner; the safety decision and early warning module compares the prediction track with the safe berthing corridor through a track-berthing force coupling algorithm, and outputs a cooperative control strategy; and the multi-terminal cooperative execution module converts the strategy into an instruction and synchronously distributes the instruction to a tug, a navigation bridge and a wharf system. Automatic closed-loop control of the whole process from sensing, prediction, decision making to execution is achieved, and the safety, accuracy and operation efficiency of ship berthing are effectively improved.

The invention discloses a bridge ship collision early warning system based on artificial intelligence, and relates to the field of intelligent traffic infrastructure safety protection. The method is used for solving the problems of difficulty in multi-source data fusion and low risk identification accuracy in a complex water area. The method comprises the following steps: firstly, uniformly mapping a radar point cloud, an AIS signal and a visual trajectory to a coordinate system taking a pier as a center through a Lie group transformation algorithm, and constructing a ship motion state tensor; then, ship behavior characteristics are extracted through a space-time diagram convolutional network, and intention probability distribution and behavior deviation degree are output; thirdly, an orthogonal constraint variational auto-encoder is adopted to decouple the autonomous control behavior and the environment disturbance factor, and a collision risk quantized value is generated according to the norm ratio of the autonomous control behavior and the environment disturbance factor; and finally, constructing a dynamic alarm threshold value according to the behavior deviation degree and the disturbance characteristics, realizing graded early warning, and driving a behavior pattern library to update through a feedback mechanism to form a self-adaptive closed-loop early warning system.

The invention belongs to the technical field of marine environment monitoring, and discloses a multi-mode deep learning fused marine remote sensing sea wave parameter inversion method and system, and the method comprises the steps: obtaining three-degree-of-freedom motion time calendar data of a ship in a target region and spaceborne synthetic aperture radar (SAR) image data; preprocessing ship motion time calendar data and the SAR image data, and constructing time-space aligned multi-modal input data; and inputting the preprocessed multi-modal input data into a pre-trained sea wave parameter inversion model, and calculating to obtain an inversion value of the sea wave parameter. According to the method, an attention mechanism is innovatively used to realize adaptive alignment and complementation of heterogeneous information in two dimensions of space and time, and an attention module automatically allocates weights according to task correlation; through time-space collaborative feature enhancement, the model can stably extract characterization strongly related to target parameters even under complex sea conditions, so that the inversion precision and robustness of sea wave parameters are remarkably improved.

The invention relates to the technical field of logistics tracking, in particular to a shipping logistics tracking method. Comprising the following steps: detecting a signal interruption time point and duration to obtain a signal interruption interval; according to the signal interruption interval, the navigation speed, direction and position which are finally recorded before interruption of the ship are extracted from a historical navigation trajectory database, and an initial state vector is generated; predicting a future transportation path of the ship through the corrected position sequence, and generating a predicted path set; according to the prediction path set, constructing a ship motion track in the three-dimensional virtual scene, and generating a visual track model; obtaining a decision support view by combining the confidence coefficient of the reckoning position sequence; and updating a port scheduling plan in real time through a decision support view, and generating an optimized loading and unloading time sequence. According to the method, the problem that the calculation precision of the position of the ship is not high in a complex scene of signal interruption is solved, and the ship position precision and the prediction precision of a future transportation path are improved.

The invention relates to the technical field of waterway traffic inland ship berthing planning, in particular to a ship berthing pose planning method based on an end-to-end deep learning model, which comprises the following steps: acquiring environment and position information in a ship berthing process by adopting data sensing and sensing equipment, and acquiring a ship berthing pose based on GNSS (Global Navigation Satellite System), IMU (Inertial Measurement Unit) and VDR (Vessel Navigation Recorder) equipment which are deployed on a ship; obtaining complete motion state information of the ship in real time; constructing an end-to-end deep learning model, inputting the state of the current ship and berth into the end-to-end deep learning model to obtain a target rudder angle, a propulsion instruction and a ship heading, and generating a manipulation instruction sequence of the whole berthing process; and meanwhile, a dynamic correction mechanism of environment disturbance and motion feedback is introduced, environment disturbance information and ship motion feedback information are collected, and the adaptability to uncertain factors such as wind current in the berthing process is improved. According to the method, manual trajectory decomposition is not needed, and the more intelligent and comprehensive ship berthing pose planning method is achieved.

The invention discloses a hierarchical cooperative motion control method for a ship dynamic positioning and wave compensation embarkation system. The method comprises the following steps: acquiring historical motion data of a ship; the historical motion data of the ship are fused, and the current ship posture and speed are obtained; the prediction model generates a predicted value of the disturbance of the ship in the future preset time; extracting to obtain a low-frequency slow drift motion component; the total output force of the thruster is calculated, and the ship dynamic positioning system controls the thruster to work based on the total output force of the thruster so as to compensate the low-frequency slow drift motion component; a Stewart platform in the wave compensation embarkation system controls supporting legs to work based on the target lengths of the supporting legs so as to compensate low-frequency motion left after compensation of the ship dynamic positioning system and high-frequency motion which is not compensated; and residual disturbance after the Stewart platform is compensated is compensated through the gangway ladder. According to the invention, an energy distribution mode that low-frequency disturbance is compensated by a ship dynamic positioning system and high-frequency disturbance is compensated by a wave compensation embarkation system can be realized.

The invention provides a ship path tracking and rolling comprehensive control method and device based on a straight-wing propeller, belongs to the technical field of ship motion control, and solves the technical problem that path tracking and rolling control precision and efficiency of a ship are insufficient due to environmental disturbance. Constructing a four-degree-of-freedom ship motion equation, constructing a four-degree-of-freedom ship motion model with interference and measurement noise, reconstructing a ship motion state by adopting a Kalman filter, calculating a path tracking error by utilizing a self-adaptive sight guidance algorithm, and generating an expected course angle; determining a longitudinal thrust, a rolling stabilizing moment and a course control thrust; and the revolution speed and the rotation swing angle of the straight wing propeller are optimized, and the rotation swing angle is recalculated. The method is suitable for the ship provided with the straight-wing propeller, and high-precision path tracking and efficient rolling stabilization are achieved by controlling the revolution speed and the swing angle of the propeller.

The invention discloses a submarine cable construction ship extremely-short-term motion response prediction method and system, and relates to the technical field of ship motion control in ocean engineering. Comprising the following steps: acquiring six-degree-of-freedom time sequence data based on a ship-borne inertial measurement unit of a submarine cable construction ship, and constructing a data set; the data set is preprocessed; constructing a model CNN-RSBU-BiLSTM (Convolutional Residual Shrinkage-Bidirectional Long Short Term Memory) with fusion of the convolutional residual shrinkage; the model CNN-RSBU-BiLSTM is trained by means of the data set obtained after preprocessing is carried out on the model CNN-RSBU-BiLSTM; and inputting the six-degree-of-freedom time sequence data acquired and preprocessed in real time into the trained model, and outputting an extremely short-term six-degree-of-freedom motion response prediction result of the submarine cable construction ship. According to the method, the multi-scale feature extraction capability of the one-dimensional convolutional neural network, the noise reduction enhancement effect of the residual shrinkage building unit and the digging capability of the bidirectional long-short-term memory network on the time sequence dependency relationship are combined, so that accurate prediction of the extremely-short-term six-degree-of-freedom motion response of the submarine cable construction ship is realized, and the prediction accuracy is effectively improved.

The invention discloses an AIS information and video data fusion method. The method comprises the following steps: collecting and preprocessing AIS and video data; constructing a constant acceleration model to interpolate the AIS data, and projecting AIS latitude and longitude coordinates to a video pixel coordinate system to obtain a target trajectory; detecting a video ship by using a YOLOX model, and tracking through a MotionTrack algorithm to obtain a video trajectory; ship motion features of the tracks in the AIS and the video data are extracted respectively; constructing a comprehensive measurement function fusing the Euclidean distance, the course and the navigational speed similarity; performing data matching by adopting a Hungary algorithm to obtain a matching result of the AIS and the track in the video data; verifying a matching result through abnormal value elimination and category consistency verification; and according to a matching result, fusing and displaying the matched AIS information and the video image. The AIS information and the visual target information are comprehensively utilized, and the information matching result is determined by using multiple clues, so that the fusion accuracy is improved, and the precision and reliability of multi-source information fusion in maritime affair monitoring are improved.

The invention discloses a large ship autonomous berthing path planning method, and relates to the technical field of channel control. The method comprises the steps of collecting and processing data, establishing a ship motion model, setting a path planning target, selecting and solving an optimization algorithm, verifying and adjusting a path, obtaining hydro meteorological historical data and real-time sensing data of port wind, wave and flow, ship basic parameters and under-actuated dynamic characteristic data, and preprocessing the data. Obtaining a ship motion model; minimum berthing time, minimum energy consumption and maximum safety are set, and a comprehensive objective function is obtained; defining constraint conditions of kinematics, dynamics, port environment and collision avoidance; solving by using an optimization algorithm, performing dynamics simulation verification and collision detection verification on the planned path, adjusting parameters of the optimization algorithm, and modifying a target function or a constraint condition; according to the method, the optimal berthing path can be planned, the collision risk is effectively avoided, the safety and efficiency of large ship berthing are improved, and the method has universality and flexibility.

The invention relates to the field of drilling ship manufacturing, in particular to a data acquisition method and system of a driver for oil exploitation. Six-degree-of-freedom motion data of a ship motion reference unit, pressure data of a hydraulic cylinder of a marine riser tensioner, hook load data of a drill string hung by a top driving system, torque data and radial acceleration data are synchronously collected, and collected multiple paths of signals are aggregated to form synchronous multi-source vibration data flow. According to the method, multiple types of vibration, load and pressure signals are synchronously collected and aggregated and segmented under the unified time reference in the operation process of the drilling ship, so that the consistency of multi-source data on the time scale is ensured, and the real dynamic coupling relation can be reflected by subsequent calculation; in the signal processing stage, key acceleration and pressure fluctuation information are extracted, and the actual working state of the marine riser system is represented through dynamic response characteristics constructed by the peak position, the peak amplitude and the power spectral density.

The invention discloses a moored ship motion state prediction and anti-collision early warning system, particularly relates to the field of traffic control and anti-collision early warning, and is used for solving the problems that ship motion state accurate prediction and anti-collision scheduling response lag cannot be realized in existing port mooring operation. According to the system, ship trajectory, port operation and environment monitoring data are acquired in real time through a data acquisition module, and a fusion data stream with consistent time-space attributes is generated; constructing a space-time diagram structure by using a feature extraction module, extracting traffic flow dynamic features, and calculating a short-term conflict probability, a trajectory convergence risk value and a mooring risk value; the risk early warning module generates a collision risk index based on risk level mapping and triggers graded early warning; the mooring decision-making module sets a key control leg according to the early warning level and generates a dynamic decision-making scheme; the anti-collision scheduling module executes actual channel passing, speed adjustment and track change, and dynamic coordination and safety management and control of port mooring anti-collision are achieved.

The invention discloses six-degree-of-freedom wave compensation embarkation equipment suitable for complex sea conditions and a control method of the six-degree-of-freedom wave compensation embarkation equipment. The six-degree-of-freedom wave compensation embarkation equipment comprises a base platform fixed to an operation ship deck; a lower platform of the Stewart parallel mechanism is connected with the base platform, and an upper platform of the Stewart parallel mechanism is connected with the lower platform through six hydraulic cylinders; the embarkation gangway ladder system is mounted on the upper platform; the hydraulic servo driving system is used for driving the six hydraulic cylinders; the intelligent sensing system is used for collecting ship motion data and relative pose data of the target platform; the intelligent control system is electrically connected with the hydraulic servo driving system and the intelligent sensing system; wherein the intelligent control system is configured to execute a compound control algorithm based on a nonlinear extended state observer and nonlinear model predictive control so as to drive the hydraulic servo driving system and compensate ship motion. The embarkation equipment provided by the invention has the advantages of high precision, high stability and strong robustness, and can realize accurate and stable compensation of complex sea conditions.

The invention relates to the technical field of ship group intelligent control, and discloses a ship motion trail optimization control system based on deep learning, which comprises control devices deployed on ships, receiving navigation state information of adjacent ships through a ship automatic identification system, generating asymmetric virtual energy-saving potential fields, superposing the asymmetric virtual energy-saving potential fields to form a total potential field, and outputting the total potential field; according to the method, a ship group spontaneously forms a dynamic navigation manifold with relatively low overall energy consumption, and through the asymmetric potential field design of bow repulsive force and stern gravitational force, linkage course correction caused by traditional collision avoidance is converted into collaborative energy-saving motion, so that the energy-saving effect of the ship is improved. Meanwhile, navigation safety is ensured in combination with a post-arbitration mechanism, and environment self-adaptive compensation is achieved through micro-disturbance inversion ocean currents.

The invention relates to a transverse movement berthing control method considering main thrust idling, which comprises the following steps of: dividing transverse movement berthing control into a controller part and a thrust distribution part, designing a three-degree-of-freedom controller for ship movement by utilizing a nonlinear disturbance observer in the aspect of the controller, and calculating force and moment required for transverse movement of a ship; in the aspect of thrust distribution, the discontinuity of a main thrust idle speed area and rudder force is considered, a thrust action range is decomposed into nine action ranges according to the thrust state of double main thrusters, multi-domain switching logic is designed to complete thrust distribution of control force, and therefore closed-loop control over ship transverse moving berthing is achieved. A simulation result proves the effectiveness of the method.

The invention discloses an unmanned ship target tracking constraint control method based on an exponential time-varying performance function, and relates to the technical field of state tracking control, in particular to the technical field of performance constraint control, comprising the following steps: step (1), establishing an unmanned ship motion three-degree-of-freedom mathematical model; step (2): constructing an exponential time-varying function; (3) constructing an exponential time-varying performance function; (4) introducing a time-varying auxiliary function; (5) designing a transfer function; (6) designing a fixed time performance constraint heading controller based on an exponential time-varying performance function; (7) designing a fixed time performance constraint surging controller based on an exponential time-varying performance function; and (8) performing simulation verification. According to the method, mainly starting from the design of a novel time-varying performance function, the problem that the state error of the traditional performance function constraint control at the initial moment is limited by the performance boundary is solved, so that the transient performance and the steady-state performance of the state tracking error of the unmanned ship are remarkably improved; and the overall control performance of unmanned ship target tracking control is further improved.

The invention discloses a shipborne fixed-wing aircraft landing guidance law design method and system, and belongs to the field of aircraft guidance law design. The problems that the multi-coordinate system coupling effect of ship motion and aircraft dynamics is not fully decoupled and an existing method is weak in adaptability to non-stable sea conditions are solved. The method comprises the following steps: defining related coordinate systems including a world coordinate system, a landing coordinate system and a ship body coordinate system; calculating an ideal landing point height change value caused by ship deck movement in real time according to the position of the ideal position in the ship body coordinate system; utilizing a KOA-LSTM hybrid forecasting model to predict a motion heave value of a ship deck at a future critical moment; designing a compensation value for the longitudinal position deviation based on the predicted motion heave value, and carrying out dynamic compensation correction on the longitudinal guide instruction; and according to the compensated guide instruction and the real-time position of the aircraft, calculating the transverse and longitudinal deviation of the aircraft relative to the expected landing trajectory to form closed-loop control. The device is mainly used for offshore operation.

The invention relates to an unmanned ship dynamic channel modeling method in an offshore water surface environment, and the method comprises the steps: constructing a three-dimensional offshore water surface simulation scene which comprises a sea surface, a wharf facility, an unmanned ship cluster and a communication node; establishing a wireless channel propagation model based on a ray tracing method, and simulating a propagation mechanism of direct, reflection and diffraction paths; establishing a motion characteristic model of the unmanned ship under the action of waves, and obtaining six-degree-of-freedom pose data of the unmanned ship; generating multiple frames of scene copies in batches by adopting an intelligent batch processing dynamic reconstruction method; dynamically correcting an antenna pattern in each frame of scene copy according to the pose data so as to couple the influence of hull motion on antenna radiation characteristics; importing the corrected antenna pattern into the wireless channel propagation model to generate a dynamic channel response; simulation is executed, and channel data obtained through simulation are collected and analyzed. According to the method, the motion characteristics of the unmanned ship in waves and the wireless channel propagation mechanism can be accurately coupled, and the accuracy of dynamic channel prediction is improved.

The invention discloses a constant tension mooring control integrated simulation method and a digital prototype system. The system comprises an integrated simulation model, a three-dimensional visualization system, a QT interaction interface and an AQWA verification model. According to the integrated simulation model, sub-simulation models of ships, constant tension winch control, mooring and environment are constructed and integrated through OpenModelica, a multi-physics field coupled integrated simulation model is established, and integrated simulation of the constant tension mooring control system is achieved; the three-dimensional visualization system builds a three-dimensional virtual model of a ship, a winch, a mooring rope, a wharf and a marine environment based on a Unity 3D virtual engine, and three-dimensional visual dynamic display of a simulation result is realized; the QT interaction interface is combined with visual dynamic presentation, and ship motion, winch state and other parameters and control PID parameters are displayed in real time. According to the invention, joint dynamic analysis and control optimization of the ship mooring system in a complex marine environment are realized.

The invention provides an unmanned surface ship obstacle avoidance navigation path generation and tracking method and device. The method provided by the invention comprises the following steps: constructing a ship kinematics model according to navigation motion parameters of an unmanned surface ship; recognizing obstacles on the initial navigation path, and constructing a dangerous area; calculating a geometrical relationship between the initial navigation path and the dangerous area based on a ship kinematics model, and generating an obstacle avoidance navigation path; adjusting the obstacle avoidance navigation path based on the interaction relationship between the obstacle avoidance navigation path and the plurality of dangerous areas; detecting the curvature of the obstacle avoidance navigation path at the access port, and generating a tangent circle optimization path tangent to the boundary of the dangerous area at the access port based on the curvature to obtain an obstacle avoidance navigation optimization path; on the basis of a finite time theory and a ship kinematics model, an expected navigation heading angle is generated according to an obstacle avoidance navigation optimization path; and constructing a navigation tracking adjustment module, and driving the unmanned surface ship to track the obstacle avoidance navigation optimization path based on a navigation tracking instruction output by the ship kinematics model.

The invention belongs to the technical field of ocean forecasting and artificial intelligence crossing, and discloses a physical equation driven ocean wave spectrum intelligent forecasting method and system.The method comprises the steps that a spectrum balance equation is deconstructed and divided into a propagation item and a source item, and modeling is conducted on the propagation item and the source item; dividing the source item into different sub source items according to different physical mechanisms; source item subnets are constructed for different sub-source items, guide variables are embedded, and decoupling of a nonlinear physical process and construction of a high-fitting-degree multi-source driving expression mechanism are achieved; through multi-step ground pushing training and in combination with main peak offset constraint, energy conservation control and propagation gradient supervision, prediction strategy construction of long-term prediction stability and physical consistency is realized. For ship motion response and other engineering applications taking spectrum as input, the method avoids an information gap between single-element forecasting and spectrum-driven application, realizes seamless connection from environment forecasting to engineering calculation, and greatly improves the practicability of the application.

The invention provides a ship path planning and tracking control method based on an improved differential evolution algorithm, and the method comprises the steps: constructing a collision risk degree model, and improving the calculation precision of the collision risk degree through combining with parameters of a quaternary ship domain optimization model; determining a fitness function Fitness to evaluate the quality of the path points according to the constraints of the ship collision risk degree, the voyage, the steering angle, the international marine collision avoidance rule and the optimal collision avoidance distance; a self-adaptive cross factor dynamic adjustment strategy based on individual fitness and population statistical indexes is introduced, candidate path points are screened according to an improved differential evolution algorithm, and collision with obstacles and dynamic ships is avoided; and establishing a ship course motion mathematical model, taking the reference path as an input instruction of a ship motion control subsystem, and tracking a ship planning path by using an adaptive neural network controller. According to the invention, the ship collision avoidance path planning is more in line with the actual navigation, and the safety of the collision avoidance path and the accuracy of tracking control are improved.

The invention relates to the technical field of ocean engineering operation motion modeling and control, and particularly discloses a method and a system for calculating influence of dynamic response of a separation supporting device and a buffer coupling device on a ship pose in a floating support installation process. The method comprises the following steps: acquiring initial position information of a separation support device and a buffer coupling device at a previous moment; acquiring vertical position and attitude information of the dynamic positioning ship and the upper module; calculating the supporting force of the separation supporting device and the buffer coupling device at the current moment; calculating the vertical position and attitude information of the upper module and the dynamic positioning ship at the current moment based on the supporting force and the external ballast water load; outputting relevant parameters and judging whether the installation is completed or not. According to the method, a multi-degree-of-freedom coupling dynamic model is constructed, high-precision real-time simulation of device dynamic response and ship motion attitude in the continuous unsteady-state load transfer process is realized, key parameter monitoring and risk early warning are provided for floating mounting operation, and the operation safety and efficiency are improved.

The invention discloses an intelligent control method and system applied to a marine floating target, and the method comprises the steps: collecting target ship information and marine environment data in real time through a multi-mode sensor array, and carrying out the time-space alignment and fusion processing, and obtaining an environment state vector; based on the ship kinematics principle, wind and flow disturbance force is decomposed into resultant force and moment vectors under a ship body coordinate system; evaluating the danger degree of the current navigation environment through the dynamic risk index, carrying out navigation risk intelligent grading, and triggering a grading control strategy; a self-adaptive controller is designed based on the Lyapunov stability theory, anti-interference dynamic adjustment is carried out on the target ship, and track deviation caused by environmental interference is eliminated; when an obstacle or a high-risk sea condition is detected, intelligent obstacle avoidance and path re-planning are carried out, and an optimized path for avoiding the obstacle or a surge area is generated in real time; and calculating the minimum safety distance based on the ship dynamics model, and implementing a graded braking strategy to perform dynamic safety braking on the target ship.

The invention discloses a ship navigation trajectory smoothing method and related equipment. The method comprises the following steps: acquiring navigation data of a target ship; inputting the navigation data into a pre-constructed trajectory smoothing model to obtain a navigation trajectory of the target ship; wherein the trajectory smoothing model is constructed according to a plurality of navigation states of the ship. According to the method, the trajectory fluctuation under complex interference is remarkably reduced, high-robustness and low-delay trajectory optimization can be realized on the premise of keeping the motion state of the ship, and reliable data support is provided for autonomous navigation and sailing safety.

The invention discloses an intelligent paperless document system based on ship environment self-adaption and block chain evidence storage, and relates to the related technical field of ship data processing, and the system comprises a ship motion perception and correction module which carries out the dynamic compensation of multi-source sensor data based on a ship type physical model, and generates corrected sensor data; the causal inference and evidence chain module is used for constructing a causal graph model between a ship motion state and document parameters, executing causal inference based on a current motion state and sensor data, and generating a causal evidence chain; the document generation and verification module is used for dynamically selecting a document template according to the ship motion state; the block chain evidence storage and feedback module is used for packaging the document content, the motion context and the causal evidence chain abstract to generate composite evidence storage information, and implementing a hierarchical evidence storage strategy according to the credibility of the document; the accuracy and reliability of sensor data are ensured.

The invention discloses a channel scheduling method and a storage medium, and the method comprises the steps: building a network flow-discretization ship kinematics model based on channel parameters which comprise ship lock parameters and ship channel parameters; first real-time data of the ship arriving at the ship lock is obtained in real time, a queuing strategy is obtained, and the first real-time data comprises ship arrival time, departure port information and destination port information; generating a ship lock scheduling plan based on the network flow-discrete ship kinematics model and a queuing strategy; and if the ship leaves the ship lock, generating a ship lane scheduling plan based on the network flow-discretization ship kinematics model. According to the method, the channel topology is abstracted into the network flow model with capacity constraint, and discretization simulation is carried out on ship microcosmic motion in a superposition manner, so that multi-scale coupling of macroscopic scheduling and microcosmic behaviors can be realized, the channel congestion prediction error rate is reduced, and the scheduling efficiency is improved.

The invention provides a ship navigation risk quantification method under polar sea ice three-dimensional-time-lag velocity obstacle, and the method comprises the steps: collecting the data of a local sensor of a ship, and forming a ship motion state and ice block motion set; a three-dimensional-time-delay velocity obstacle model TDIVOD is constructed to process the ship motion state and the ice block motion set, and two three-dimensional binary mask graphs are generated and comprise a velocity obstacle domain and a feasible velocity domain; mapping the speed obstacle domain and the feasible speed domain into continuous quantitative indexes sensitive to polar navigation risks; designing an objective function for avoiding risk or angle change minimization according to the speed obstacle domain, the feasible speed domain and continuous quantitative indexes, calculating the objective function, and selecting a speed vector corresponding to a minimum value as an optimal avoidance speed vector; and carrying out navigation risk avoidance on the ship based on the optimal avoidance speed vector. The method provided by the invention has outstanding practical value and technical frontier in the multi-ice, multi-ship and high-uncertainty environment of the polar region.

The invention discloses a marine traffic flow probability prediction method based on multi-source AIS-meteorological data fusion, and belongs to the field of marine traffic safety management, and the method comprises the following steps: S1, obtaining a standardized multi-source data set; s2, fusing the dynamic statistical characteristics of the AIS ship and the meteorological environment characteristics through a ship motion transfer function, and constructing a space-time patch considering a short-term ship motion trend and a long-term sea condition trend; s3, based on the space-time patch, fusing patch Transform time sequence modeling and adaptive dynamic graph space correlation learning to obtain a space-time fusion feature; and S4, outputting the traffic flow state prediction value and the probability distribution of the traffic flow key indexes. The marine traffic flow probability prediction method based on multi-source AIS-meteorological data fusion breaks through the limitation that a traditional method is single in data dimension, insufficient in space-time correlation capture and lack of probability confidence, and high-precision probability prediction of the marine traffic flow under the complex sea condition is achieved.