72 results about "Ship motions" patented technology

This invention belongs to the field of ship formation control technology, specifically relating to a neural network-based anti-interference control method for multi-ship formations at sea. It utilizes neural networks to approximate and compensate for uncertainties in the model, while simultaneously constructing a disturbance observer to achieve effective estimation of coupled marine environmental disturbances. To overcome the problem of traditional observers' dependence on accurate models, this method parameterizes the ship motion equations and disturbance terms to establish a canonical model of the disturbance, and uses a disturbance filter to achieve exponential convergence estimation of the disturbance state vector, thus transforming the disturbance suppression problem into an adaptive control problem. Furthermore, this method fully considers input quantization, effectively reducing propeller wear and communication burden by slowing down the rate of change of actuator output. Compared with existing technologies, the anti-interference formation control strategy proposed in this invention can achieve online estimation and suppression of unknown disturbances without relying on any prior model dynamics knowledge.

The application discloses a wave field inversion method and device based on a wave inversion model and a medium, relates to the technical field of wave inversion, and comprises the following steps: obtaining to-be-processed parameters; inputting the to-be-processed parameters into the wave inversion model to obtain a wave field three-dimensional model through the wave inversion model; calculating a theoretical ship motion spectrum corresponding to the wave field three-dimensional model; obtaining a loss result based on an actual ship motion spectrum and the theoretical ship motion spectrum, and calculating a reconstruction error of the wave field three-dimensional model; iteratively optimizing model parameters of the wave inversion model based on the loss result and the reconstruction error until the loss result and the reconstruction error are both less than a preset threshold; and outputting the wave field three-dimensional model and wave field parameters by using the trained wave inversion model. The application is used to solve the problems of incomplete inversion results, poor precision and poor anti-interference ability in the prior art when the wave field inversion is performed, and realizes high-precision and high-reliability real-time inversion of the wave field.

The application belongs to the technical field of unmanned ship motion control, and specifically discloses an unmanned ship trajectory tracking control method based on state constraint planning and execution, which comprises the following steps: a second-order motion control model in a unified form is established for longitudinal tracking, heading tracking and lateral tracking of the unmanned ship respectively; based on a preset convergence time and a tracking error and a change rate in a current period, a polynomial trajectory satisfying terminal error and change rate of zero is planned online to obtain a polynomial planning acceleration; based on the polynomial planning acceleration and a system lumped nonlinear term estimated in the last period, an algebraic form control law is used to obtain control input in the current period; and based on the polynomial planning acceleration in the current period and the system lumped nonlinear term estimated in the last period, the system lumped nonlinear term estimated in the current period is obtained through recursive updating. Through the application, the trajectory tracking performance of the underactuated unmanned ship in the actual complex marine environment is effectively improved.

The application relates to the field of ship operation, in particular to an automatic weighted partial least square ship motion model parameter identification method. The method comprises the following steps: step 1, establishing a ship motion dynamics model; step 2, according to the ship motion dynamics model and ship motion, determining motion data, performing scaling processing on the motion data, and analyzing main components of the motion data; step 3, determining a weighting factor according to the normalized data and the analysis result of the main components of the motion data; step 4, designing a least square algorithm with the weighting factor; step 5, determining an upper and lower bound of an identification error; and step 6, identifying ship parameters by using the least square algorithm with the weighting factor and the ship motion dynamics model.

This invention proposes a real-time calculation method and system for six degrees of freedom of ships based on lidar point clouds, belonging to the field of shipbuilding technology. Addressing the shortcomings of existing ship monitoring technologies, which primarily rely on single-video surveillance and cannot analyze ship motion patterns or comprehensively grasp ship movement trends, this invention utilizes an iterative nearest-point point cloud matching algorithm. Through nearest-point search and singular value decomposition to solve for the optimal transformation matrix, iteratively optimizes the ship's position and attitude, finds the boundaries and centroids of feature data, obtains the main direction of ship motion, and continues iteratively calculating the optimal rigid body transformation between two point clouds. This further yields the core of the ship's motion in any two adjacent frames, achieving high-precision, real-time calculation of the ship's motion under six degrees of freedom (sway, pitch, heave, roll, pitch, and bow). Furthermore, it minimizes errors caused by sea conditions and human operation.

The application provides a ship mooring control method and system based on motion analysis, and relates to the technical field of ship mooring control. In view of the technical problems that the existing ship mooring control method mainly depends on position feedback, is easy to cause the single pendulum effect, has the resonance risk, has the response lag and has high energy consumption, the application adopts the fusion monitoring of ship motion state of stereovision and laser radar, constructs the mooring big data covering multiple ship types and multiple environment conditions based on the joint simulation of computational fluid dynamics and ship dynamics, optimizes the parameters of the PID control model with the ship displacement, speed and acceleration as inputs through the genetic algorithm, and finally realizes the closed-loop real-time adjustment of the cable tension relying on the high dynamic winch system. The method improves the control precision and stability of the mooring system, and the robustness and environmental adaptability in the face of complex environment.

This application relates to the field of computer graphics technology, and in particular to a marine visualization method and system for simulating ship motion. The method includes: generating an ocean height field based on a selected wave spectrum; acquiring viewpoint height and topographic information, and generating an ocean mesh model based on the viewpoint height, the topographic information, and the ocean height field; calculating ocean surface reflected light, ocean surface scattered light, and foam based on the ocean mesh model to obtain the ocean visualization result. This application can simulate ocean height fields and lighting effects under different sea conditions, and users can quickly adjust the simulation environment according to their needs. Visualizing marine elements can intuitively reflect changes in the marine environment, which is helpful for environmental monitoring and management. For example, visualization of data such as temperature and ocean currents can assist in scientific research and decision-making.

This invention belongs to the field of intelligent perception and simulation training technology for maritime navigation. It discloses a method and system for realistic training and evaluation of ship collision avoidance rules at sea. By constructing a hierarchical question bank, it generates scenario assembly lists and uniformly schedules ship motion simulation, 3D visual scenes, radar / AIS fusion display, and voice communication interaction. During training, it collects control inputs, motion states, target information, and communication records to form a traceable chain of evidence, and aligns sampling based on evaluation anchor points. An automatic scoring model is established based on result and process indicators, outputting an evaluation report with sub-scores, evidence location, a list of violations, and retraining suggestions. It is suitable for teaching, retraining, and assessment, improving the efficiency and achievement rate of collision avoidance decision-making training.

The application discloses a kind of test simulation equipment for simulating throwing anchor, dragging anchor in ship movement.The equipment includes water tank and track system, tow control system, anchor operating mechanism and data acquisition and processing system;Water tank and track system provide test water environment and the height of trailer (for simulating ship) from water surface, tow control system drives trailer to move along track, anchor operating mechanism controls anchor dropping position by receiving signal, realizes throwing anchor simulation, data acquisition and processing system monitors anchor chain stress in real time, captures anchor body into water and dragging process by high-speed camera, all data are integrated transmission to control computer by synchronizer, and after processing, output anchor dropping speed curve, anchor chain dragging force peak value and drag anchor trajectory and other parameters.The all test simulation elements of the application are controllable and known, easy to use, can play the role of improving the accuracy and test efficiency of ship throwing anchor, dragging anchor test simulation.

The application discloses a three-dimensional safety situation awareness method and system based on ship motion response, and the method comprises the following steps: acquiring ship data and environment data, wherein the ship data comprises distress ship data and rescue ship data, and inputting a ship motion model to acquire motion state parameters of the ship; inputting the motion state parameters into a three-dimensional dynamic ship field model, and outputting a final three-dimensional safety situation awareness result through coupling calculation of multidimensional danger degree factors. According to the four-degree-of-freedom nonlinear state space equation and the drift state space equation, the motion state parameters of the distress ship and the rescue ship are acquired, the motion state of the rescue ship and the distress ship in the three-dimensional space is accurately analyzed, the collision danger degree is calculated through the coupling calculation of the multidimensional danger degree factors, the collision danger degree calculation is fused with the time, space constraint and rolling influence, the collision risk in the rescue process can be accurately quantified, and the accuracy of risk assessment is provided.

This invention discloses a multi-point mooring and wave compensation system for engineering vessels. The system includes multiple winches symmetrically arranged around the vessel, mooring lines, attitude sensors, and a central control system. The central control system comprises a data acquisition module, a control decision module, and a drive control module. It can automatically identify the vessel's motion state, achieving constant tension control in conventional mooring mode and employing an impedance control strategy in wave compensation mode. The system is equivalent to a virtual spring-damped system with adjustable stiffness and damping coefficients. By dynamically adjusting the output torque and deployment / retraction speed of each winch, it actively compensates for the vessel's six degrees of freedom motion. This invention also discloses a corresponding control method and an engineering vessel incorporating this system. This invention achieves multi-point coordinated active wave compensation, improving the operational stability and safety of engineering vessels in harsh sea conditions.

This invention relates to an experimental apparatus and method for simulating ship motion under severe sea conditions, belonging to the field of ship wave load testing technology. It addresses the problem that existing severe sea condition wave load testing technologies are insufficient in simulating realistic waves under actual sea conditions, such as high wave heights, distorted waves, and breaking waves. The wave-generating system includes a wave-generating plate located at one end of a water tank and swinging along the length of the tank, and a driving component for driving the wave-generating plate's swing. The nonlinear wave generation system includes a wave-generating rod and several jet pipes. The wave-generating rod is arranged along the width of the water tank and slidably set along the height of the water tank via a height adjustment component. The jet pipes are all located at the bottom of the water tank. This invention enables the simulation of the water-air mixture flow field and accurate measurement of loads in distorted and nonlinear waves under severe sea conditions. It allows for a wide variety of experimental types and diverse functions, and can replace the expensive and costly towing tanks used for general ship models.

This invention provides a water level monitoring method, system, electronic device, and storage medium, relating to the field of ship safety monitoring technology. The method includes: acquiring water level status information uploaded by multiple water level monitoring terminals located at the bottom of the ship's fish hold; performing fusion analysis on the water level status information from each monitoring terminal to obtain water level distribution data at the bottom of the fish hold; and performing tiered alarm operations based on the water level distribution data. This invention, through a coherent design of multi-point monitoring, fusion analysis, and tiered response, systematically solves the problems of decreased monitoring accuracy and false alarms caused by ship motion interference, achieving more accurate and reliable monitoring of fish hold water levels.

The present application relates to the technical field of ship cabin intelligent lighting, and particularly relates to a ship cabin intelligent lighting system and a lighting brightness adjusting method thereof, the system comprising a data acquisition module, a data cleaning and estimation module, an illumination calculation module, a fuzzy neural network control module, an adjustable light LED lighting execution module, a human rhythm coordination module, and a fault self-diagnosis and redundancy switching module. The present application improves the accuracy of cabin brightness real value estimation and the system anti-interference ability in complex sea conditions, solves the problem of fixed light source illumination distribution change when the ship is rocking, ensures that each work plane in the cabin always obtains stable and suitable illumination, reduces visual discomfort caused by ship movement, responds faster, has smaller overshoot, and can balance energy saving and comfort targets, helps to adjust the biological clock of the crew, relieve sailing fatigue, improve the psychological and physiological health of long-term sea operation, avoids ship lighting failure, and is convenient for expansion and maintenance.

This invention relates to a real-time prediction method for ship motion that integrates dynamic analysis and data-driven approaches. The method includes the following steps: acquiring environmental and ship parameters; training a dynamic analysis model and a data-driven model based on the environmental and ship parameters; generating predicted values ​​from the data-driven model and the dynamic analysis model based on the trained dynamic analysis model and data-driven model; calculating the weights of the dynamic analysis model based on confidence scores, spatiotemporal scale scores, and stability scores; and weighting and fusing the predicted values ​​from the data-driven model and the dynamic analysis model using the dynamic analysis model weights to obtain a fused prediction output. Compared with existing technologies, this invention has the advantages of the physical interpretability of the fused dynamic model and the real-time prediction capabilities of data-driven approaches, providing auxiliary decision support for safe ship navigation.

A computer-implemented control system and method for dynamically managing airflow in an air lubrication system of a vessel are disclosed. Real-time sensor data including vessel motion, acceleration, and speed-through-water are processed by a controller executing a machine learning model to predict near-future sea-state conditions. The controller accesses and interpolates computational fluid dynamics (CFD) efficiency profiles to determine target airflow values and generate valve and compressor commands that modulate airflow to multiple outlets beneath the hull. Feedback from hull and pressure sensors is used to stabilize the air layer, while a learning-based prediction engine continuously refines CFD profiles to improve operational efficiency and reduce parasitic load. The system enhances vessel hydrodynamic performance and fuel economy under varying environmental conditions.

The application discloses a kind of unmanned ship multi-ship collision avoidance decision-making method and system based on reinforcement learning, it is related to ship autonomous obstacle avoidance technical field, the method comprises: establishing ship motion mathematical model, and determining current ship's own state vector based on the ship kinematics model;Construct the navigation decision-making mode under the multi-ship encounter situation;Collision risk assessment is carried out based on RVO algorithm and VO algorithm, and collision risk area is determined;BiGRU network model is trained through historical data;The current ship's own state vector, collision risk assessment vector, ship predicted collision time and the laser radar line input to the trained BiGRU network model in surrounding environment state perception, obtain the rudder angle of current ship.The application can solve the behavior decision-making problem under different complex environments, prevent the huge economic loss caused by ship collision, with high engineering practicability.

This application discloses a method, device, medium, and product for short-to-medium-term ship motion prediction based on a spatiotemporal fusion Informer model, relating to the field of ship motion prediction. The method includes: acquiring short-to-medium-term ship motion parameters, environmental parameters, and wave spectrum parameters to generate time-series data; performing spatial and positional encoding on the time-series data, and obtaining spatiotemporal fusion features based on the spatial and positional encoding results; constructing a spatiotemporal fusion Informer model by introducing a multi-head ProbSparse attention layer and a Distilling layer; and obtaining ship motion prediction results based on the spatiotemporal fusion features using the spatiotemporal fusion Informer model. This application can improve the efficiency and accuracy of short-to-medium-term ship motion prediction, providing key technical support for intelligent maritime aviation operation systems.

The invention provides a marine vibroseis synchronous correction and signal separation method and device. The marine vibroseis synchronous correction and signal separation method comprises the steps of obtaining an original seismic record, obtaining an actual measurement aliasing common detection point gather, and minimizing a predetermined objective function by embedding a prior model into an inversion iteration process in a plug-and-play mode to unmix and correct the actual measurement aliasing common detection point gather, obtaining available single-source seismic data; wherein the priori model comprises a plurality of denoising devices, each denoising device adopts a CNN structure, and the priori model is obtained by training a simulation aliasing common detection point gather obtained through forward modeling and a simulation single-source common detection point gather corresponding to the simulation aliasing common detection point gather through pseudo seismic data obtained through conversion of a natural image data set and pseudo seismic data with noise corresponding to the pseudo seismic data. According to the invention, the Doppler effect caused by ship motion can be effectively eliminated, the problem of aliasing of seismic data acquired by multiple seismic sources is solved, and the reliability and generalization ability of marine seismic data processing are improved.

This invention relates to the field of smart grid technology and discloses an electronic cabinet power prediction method and system for improving the stability of ship power grids. The method includes: synchronously acquiring inertial measurement data; extracting the actual microscopic disturbance acceleration and effective orthogonal interference acceleration based on the ship's motion state; deriving and predicting contact resistance and convective heat transfer coefficient based on this data; performing time integration on the heat change rate to obtain online extracted heat capacity and deriving and predicting semiconductor junction temperature; substituting quantum transition laws to predict parasitic leakage power; combining internal load power consumption and transient bus voltage to synthesize and predict the total destructive demand power; and finally using the rotor inertia state of the power grid for feedforward reduction to generate stabilization and remodeling execution commands. This invention mitigates hidden parasitic surges caused by wave turbulence, prevents the unauthorized draining of rotor kinetic energy, and improves the reliability of power grids on isolated island ships.

The application discloses a polar ship icing condition limit stability evaluation method and system, and the method comprises the following steps: obtaining ship data and environmental parameters, inputting a dynamic icing calculation model, and calculating the ship icing distribution; obtaining the ship stability righting lever curve according to the real-time motion state of the ship and the ship icing distribution, processing the ship stability righting lever curve, and obtaining the dynamic stability curve; calculating the limit dynamic inclination and the maximum dynamic inclination lever under different icing conditions based on the dynamic stability curve, and solving the limit wind speed and the wind scale that can be borne by the ship under different icing conditions according to the calculation results, and comprehensively evaluating and judging the limit stability of the polar ship. The application realizes the dynamic update of the icing distribution with the change of the ship motion state by obtaining the state change parameters corresponding to the ship at each time step based on the six-degree-of-freedom motion equation of the ship, and the total amount of flying spray is calculated by combining the sea wave spray and the wind-generated flying spray, so that the ship stability analysis combines the icing and the wind wave, and the accuracy and the reliability of the stability evaluation are improved.

The utility model provides a kind of for ship power positioning system controller's semi-physical testing device, comprising: host computer module, ethernet switch, real-time simulation module, power module, communication module, I / O module and analog load cabinet.Host computer module is used for test management, working condition configuration and data monitoring;Real-time simulation module is responsible for running ship movement and ocean environment model, communication module, I / O module are used for the generation and acquisition of multiple physical signals;Power module provides stable power supply with timing controllable;Analog load cabinet is used to simulate the load characteristics of actuator such as propeller.Each module is interconnected through standard interface, constitutes closed-loop test system, can simulate the ship movement and sensor signal under complex sea conditions, supports hardware-level fault injection, realizes the comprehensive verification of power positioning controller function, performance and reliability, with high simulation reality, comprehensive test coverage, good safety, strong scalability and other advantages.

A kind of ship model parameter online identification method and system based on bayesian estimation belong to ship model parameter identification neighborhood.Proposed to improve the precision of ship model parameter online identification.The technical points: the present application applies bayesian estimation theory to ship model parameter online identification, the posterior probability is obtained by likelihood function and parameter prior, the bayesian estimation result is obtained by maximum principle of posterior probability, then the data is weighted according to condition number and correlation coefficient, the precision of parameter identification is improved, the invention will be applied to real ship, and provide parameter basis for ship motion controller design and optimization.According to known online measurement data section, likelihood function is obtained;(according to bayesian maximum posterior theorem, the posterior probability is obtained by using prior and likelihood function, then the maximum value of posterior probability is obtained, the corresponding bayesian estimation result is obtained;The data is weighted according to condition number and correlation coefficient, the weighted posterior probability function is obtained, and the automatic weighting bayesian estimation method is obtained according to the above steps.

The application discloses an online ship motion prediction method based on an X-band navigation radar, and comprises the following steps: wave information of a sea area around a ship is monitored and recorded by a wave radar; complete wave field data and one-dimensional wave time history data in a specific direction are obtained through an inversion algorithm; six-degree-of-freedom motion time history data of the ship are combined, and are input into a neural network prediction model together, so that a future motion change trend of the ship is finally obtained. The ocean environment information is introduced into the prediction model, so that the model can better learn the excitation mechanism of the environmental factors on the ship motion, and the performance of the model is improved, and the training period is shortened.

The application relates to a ship detection and tracking method in a bridge area monitoring scene and belongs to the technical field of ship detection and tracking. Video streams in the bridge area monitoring scene are collected and labeled; on the basis of YOLOX, a DC2S module is used to replace a CSP module, a CBAM mixed attention module is added, a loss function is optimized, and a deformable multi-branch YOLOX network is constructed; a dataset is input into the deformable multi-branch YOLOX network for training, and a ship detection model is obtained; bridge area video images are input into the trained ship detection model for detection, and a ship detection result is output; Kalman filtering and a ResNet50-ibn network are used to extract ship motion and appearance features respectively; according to the confidence of the detection result and the extracted features, a ship detected in a current video frame is matched with a historical track, and a tracking result is output. The application can realize high-precision tracking of ships in the bridge area monitoring scene.

The application provides a ship navigation condition determination method based on a large language model, and belongs to the cross technical field of artificial intelligence and ship navigation decision-making. The application retrieves knowledge items and confidence score in a knowledge vector library by using a field adaptive embedding vector model, predicts ship motion amplitude and motion uncertainty interval by using a six-degree-of-freedom motion proxy model, inputs the knowledge items, the confidence score and the motion prediction result and environmental parameters into a large language model to generate a preliminary navigation condition evaluation text, introduces an illusion suppression function to calculate a credibility score value based on knowledge item coverage, motion uncertainty interval width and semantic consistency and triggers artificial review, and finally generates an optimized speed sequence by using a particle swarm optimization algorithm, so that the technical problem that a large language model is prone to fact error illusion when generating ship navigation condition evaluation, resulting in unreliable evaluation results, is solved.

A computer-implemented control system and method for dynamically managing airflow in an air lubrication system of a vessel are disclosed. Real-time sensor data including vessel motion, acceleration, and speed-through-water are processed by a controller executing a machine learning model to predict near-future sea-state conditions. The controller accesses and interpolates computational fluid dynamics (CFD) efficiency profiles to determine target airflow values and generate valve and compressor commands that modulate airflow to multiple outlets beneath the hull. Feedback from hull and pressure sensors is used to stabilize the air layer, while a learning-based prediction engine continuously refines CFD profiles to improve operational efficiency and reduce parasitic load. The system enhances vessel hydrodynamic performance and fuel economy under varying environmental conditions.

This invention relates to the fields of marine meteorology and navigation, and discloses a method for predicting meteorological factors for ship navigation based on marine meteorological information. This method is used to predict meteorological factors for ship navigation, assess navigation risks, and plan alternative routes. The method includes processing meteorological data and ship data for a target sea area to obtain historical meteorological time series and ship motion response sequences; constructing state vector trajectories of meteorological factors using historical meteorological data, establishing a dynamic model library, and obtaining the ship motion response function to meteorology based on meteorological and motion response data; generating deterministic meteorological factor prediction sequences by embedding the current meteorological state into the dynamic model; and constructing stochastic differential equations to generate probabilistic prediction distributions of meteorological factors. This invention integrates data-driven and physical constraints, providing more comprehensive navigation decision support.

The application provides a ship trajectory prediction method based on Bayesian optimization of directional inertia correction, comprising: acquiring a historical trajectory sequence of a ship containing time-sequentially arranged latitude and longitude coordinate points; calculating an instantaneous speed vector containing a latitude component and a longitude component based on the historical trajectory sequence of the ship; multiplying the latitude component of the instantaneous speed vector by the i-th power of an inertia attenuation factor to obtain a latitude direction correction speed for the i-th prediction step; multiplying the longitude component of the instantaneous speed vector by the product of the i-th power of the inertia attenuation factor and a directional inertia factor to obtain a longitude direction correction speed; wherein the inertia attenuation factor represents the exponential attenuation characteristic of the inertia of the ship movement with the prediction step, and the directional inertia factor represents the scale anisotropy of the longitude direction and the latitude direction in the earth spherical coordinate system; and sequentially calculating the predicted positions of a plurality of future prediction steps based on the latitude direction correction speed and the longitude direction correction speed to obtain a future trajectory sequence of the ship.