702 results about "Marine currents" patented technology

A path planning method for a multi-unmanned-aerial-vehicle collaborative maritime search. The method comprises: acquiring and analyzing related ocean current information of a region to be searched, and establishing an ocean current model on the basis of the obtained ocean current information (step 1); on the basis of the region to be searched, a command and control center establishing a grid map by taking a grid cell as a unit, and then establishing a target probability map on the basis of the related ocean current information of the region to be searched, prior target information and the grid map, wherein the target probability map provides the probability of a prior target being present in any grid cell (step 2); if there is an obstacle in the region to be searched, the obstacle being represented by an irregular polygon, generating a segmentation line for region division by taking a vertex of the irregular polygon as one end point of the segmentation line and also meeting a limiting constraint condition for region division, so as to divide the region to be searched into Nr sub-regions, and the command and control center allocating a sub-region to each unmanned aerial vehicle on the basis of the performance of the unmanned aerial vehicle by using a static allocation strategy (step 3); after the sub-region is allocated to each unmanned aerial vehicle, the command and control center planning a cross-regional shortest path for each unmanned aerial vehicle and using a path planning method to plan an unmanned aerial vehicle coverage path, so as to implement a single-region shortest-time coverage path (step 4); and monitoring the endurance state of each unmanned aerial vehicle during the process of executing a search task, and if it is found that the endurance capability is insufficient, recalling the unmanned aerial vehicle, and if a target is found or the search task is completed, recalling the unmanned aerial vehicle and returning to target coordinates (step 5).

The invention discloses a marine environment dynamic monitoring system based on cooperation of artificial intelligence and multi-source remote sensing, relates to the technical field of marine environment monitoring, and realizes multi-dimensional monitoring of a sea surface state by receiving multi-source data of a plurality of monitoring ends. Chlorophyll concentration mutation is detected in real time by setting sliding window difference, a subsequent processing flow is dynamically triggered, and the response speed of sudden events (such as red tide) is increased; aI is utilized to predict clock offset, interpolation reconstruction, weighted fusion and ocean current compensation technologies are combined, and space-time asynchronous errors of multi-source data are remarkably reduced; and generating a data cube fusing the backscattering coefficient, the temperature field and the chlorophyll gradient, and calculating a diffusion velocity field, thereby providing high-precision decision support for marine disaster early warning. The limitation of a traditional single data source is broken through, efficient cooperation of multi-modal data is driven through artificial intelligence, and the real-time performance, the accuracy and the dynamic analysis capability of marine environment monitoring are improved.

The invention provides an underwater vehicle multi-source information fusion accurate navigation method and system. The method comprises the following steps: firstly, acquiring inertial navigation data, DVL data and ocean current information of an underwater vehicle and observation information of a distance between the underwater vehicle and a beacon, and preprocessing the inertial navigation data, the DVL data and the ocean current information; then, establishing a state model according to the kinematics principle of the underwater vehicle, and establishing an observation model by combining various types of information; carrying out fusion processing on the state model and the observation model by adopting a self-adaptive Kalman filtering algorithm; and finally, estimating the current position of the underwater vehicle according to the fused state vector, comparing the current position with a preset target position to calculate a deviation, and correcting the deviation by adjusting a rudder angle and the rotating speed of a propeller. According to the method, multi-source information is integrated, innovation is carried out on construction of a state model and an observation model and position estimation and deviation correction, adaptive Kalman filtering is adopted, and the method has the advantages that the navigation precision is improved, the ocean current influence is considered, adaptive adjustment is realized, and real-time navigation is realized.

The invention discloses a seabed tracked robot path planning method and system based on reinforcement learning, and the method comprises the steps: obtaining environment data in real time through multiple sensors, extracting submarine topography three-dimensional features, obstacle distribution and ocean current dynamic parameters in combination with a neural network, and carrying out the combined feature extraction; establishing a seabed environment simulation model, and synthesizing various landform training data by using an adversarial generation technology; a hierarchical reinforcement learning framework is designed, a global layer collaboratively optimizes a long-distance path through a distributed agent, a local layer designs a high-frequency control strategy, and the global and local strategies realize multi-dimensional collaborative optimization through a dynamic weight adjustment mechanism; model parameters in a dynamic environment are updated in real time through an online optimization module, and a simulation strategy is quickly deployed to an entity robot through transfer learning. According to the invention, a neural network feature extraction and multi-level reinforcement learning collaborative autonomous decision-making system is constructed, and a high-reliability and low-energy-consumption autonomous operation solution is provided for a deep sea operation scene.

The invention discloses an error correction system and method for marine environment observation data. The error correction system comprises a data acquisition module, a compensation modeling module, an error analysis module, a data compensation module, a data fusion module and a feedback optimization module. The data acquisition module acquires ADCP flow measurement, GPS, IMU, temperature, pressure and water quality monitoring data. And the error analysis module detects a drift error by using Kalman filtering and a hidden Markov model, and analyzes an environmental error based on a long short-term memory network. The data compensation module optimizes a compensation model and improves data precision. And the data fusion module fuses multi-sensor data by adopting a particle filter and a Bayesian optimization algorithm. The feedback optimization module dynamically adjusts the weight of the compensation model according to the error correction data, and improves the adaptability of the system. According to the invention, the accuracy of ocean current monitoring data is improved, and more reliable data support is provided for underwater environment research.

The invention relates to a buried end cable wear prediction method and system based on multi-physics field coupling simulation, and belongs to the field of cable wear prediction. The method comprises the following steps: collecting and preprocessing hydrological environment data; carrying out three-dimensional ocean flow field modeling and fluid-solid coupling analysis; cable dynamic response simulation; cable and support structure contact modeling: applying the dynamic response of the cable to modeling of a contact area, and establishing a time-varying contact model by adopting an improved Hertz contact theory; abrasion loss calculation, wherein a dynamic Archard abrasion model is adopted to calculate the local abrasion volume; and fusing and visualizing multi-physics field data. Through a Navier-Stokes equation and a fluid-structure interaction algorithm, ocean current dynamic pressure, shear stress and cable mechanical response are interacted in real time, and the defect that a traditional static load model ignores fluid-structure bidirectional coupling is overcome; an improved Hertz contact model is adopted, the contact radius and the slip speed are introduced, and the over-underestimation problem of a traditional static contact hypothesis on abrasion loss prediction is solved.

The invention discloses a deep and far sea unmanned aerial vehicle monitoring and management platform based on multi-sensor fusion, and relates to the technical field of unmanned aerial vehicle marine monitoring. The intelligent analysis module is used for receiving the fusion data after time-space alignment and the real-time ocean current data, optimizing the moving path of the unmanned aerial vehicle according to the received data, evaluating the resource development possibility, obtaining an analysis result and transmitting the analysis result; an anti-interference communication module; an energy management module; and dynamically adjusting an energy distribution strategy. The module combines the task priority weight and the environment energy consumption weight, optimizes the energy use efficiency, prolongs the endurance time of the unmanned aerial vehicle, and ensures the smooth completion of the task. Particularly in a complex marine environment, navigation errors are corrected in real time through a quantum navigation error compensation model, the positioning precision is improved, and the moving path of the unmanned aerial vehicle is optimized in combination with real-time ocean current data and an ocean flow field cost function.

The invention discloses a submarine cable detection method and device and a nonvolatile storage medium. The method comprises the following steps: acquiring the position of a fault point under the condition that a submarine cable is detected to have a fault; determining a first target search range corresponding to the position of the fault point based on the fault positioning response time, the submarine cable routing information processing time and the ocean current speed; determining a fault probability of each routing section of the submarine cable in the first target search range based on the submarine cable depth data, the water depth data and the environment data in the first target search range; and sorting the fault probabilities of the routing segments to obtain a routing segment sequence, and scheduling the patrol ship to perform fault detection based on the routing segment sequence. According to the method and the device, the technical problems of low response speed and low processing efficiency caused by inaccurate positioning and large range of the fault range propagated by the fault point when the submarine cable is identified to have a fault when the submarine cable is monitored in the related technology are solved.

A wind and wave response modeling and ocean current inversion method based on machine learning relates to the technical field of artificial intelligence and ocean information services, and comprises the following steps: (1) data acquisition; (2) data processing; (3) constructing a data set; (4) establishing a sea surface flow velocity inversion model by using a particle swarm optimization machine learning algorithm; and (5) obtaining an optimal sea surface flow velocity inversion model through testing and case analysis. Aiming at ocean and Doppler frequency shift characteristics of the sea surface, the invention provides a particle swarm optimization XGBoost model wind wave Doppler contribution prediction method for the first time, and the wind wave Doppler contribution estimation precision and speed can be effectively improved.

The invention relates to the technical field of ocean information processing, in particular to a mesoscale vortex space-time characteristic analysis method and device based on a neural network, and the method comprises the following steps: obtaining the type, vortex center position, vortex intensity and temperature and sound velocity abnormal characteristics of each layer of mesoscale vortex according to the ocean current three-dimensional speed data of a target region; and the trained neural network predicts the vortex center position, vortex intensity and temperature and sound velocity abnormal characteristics of the mesoscale vortex at the future moment according to the type, vortex center position, vortex intensity and temperature and sound velocity abnormal characteristics of the mesoscale vortex at each layer at the historical moment. The problems that in the prior art, small-scale vortexes or rapidly-changing vortex characteristics are difficult to capture, large-scale data processing requirements are difficult to meet, and robustness is poor are solved.

The invention discloses an AUV (Autonomous Underwater Vehicle) path tracking method based on predicted line-of-sight angle guidance, which comprises the following steps: acquiring a real-time navigation state through inertial navigation, acoustic positioning and DVL fusion, introducing a fixed time disturbance predictor to estimate a sideslip angle and an ocean current velocity component on line, adaptively adjusting a line-of-sight distance according to transverse error-navigational speed-curvature, and tracking the path of the AUV. Calculating a predicted line-of-sight angle and outputting an expected heading; and then a propeller and a control surface are driven by adopting a fixed time feedback control law, so that track and attitude error fixed time convergence of the under-actuated AUV under the conditions of strong time-varying ocean current and large sideslip is realized. The method does not need a side thruster or an ocean current prior model, is simple in algorithm structure, is suitable for a high-speed high-curvature track, and has the advantages of high speed, high steady-state precision, low energy consumption and high robustness.

The invention further provides an unmanned ship collision avoidance method and device based on the DBSCAN algorithm, and the method comprises the following steps: 1, collecting ship data, and training a six-degree-of-freedom ship motion model through a neural network; step 2, acquiring a wind speed by using a wind speed sensor, and acquiring ocean current information by using an ocean current sensor; step 3, acquiring speed and position information of other ships by using AIS / radar; step 4, collecting ship captain driving information, establishing a ship driving model, and predicting the future motion state of the ship; 5, performing risk analysis on other ships by using a DBSCAN algorithm, and calculating ship collision risks; step 6, according to the step 5, performing corresponding collision avoidance behaviors aiming at the risk; and 7, judging an action execution condition, and returning a reward value and a result. According to the technical scheme, the collision avoidance capability of the unmanned ship can be improved, the generalization capability is good, and the efficiency of collision avoidance and safe navigation of the unmanned ship on the water surface is improved on the whole.

The invention relates to the field of offshore floating type wind power, in particular to an automatic buoyancy adjusting system and method for a floating type draught fan platform, the adjusting system comprises a buoyancy device which is fixedly installed on a stand column or a buoyancy box, the buoyancy device comprises a semi-flexible shell, and at least one air bag is arranged in the semi-flexible shell; the volume of the air bag is determined through the following steps that S1, real-time motion data and environment data of the floating type draught fan platform are obtained; and S2, whether the current posture of the floating type fan platform is stable or not is evaluated by analyzing the real-time motion data and the environment data, and if not, the size of an air bag is adjusted by inflating and deflating. By arranging the buoyancy device, buoyancy can be flexibly adjusted according to sea conditions, heaving, trim and rolling motions of the floating fan platform under the action of waves, wind loads and ocean currents are remarkably reduced, the platform can adapt to rapid changes of the sea conditions in a short time, and impact of stormy waves on the platform is reduced.

The invention discloses a polar region sea area ice area route dynamic planning method based on multi-source data, and the method comprises the following steps: obtaining sea ice, ocean current and wind field historical data of a target channel sea area, and carrying out the preprocessing; inputting a preprocessing result into a constructed sea ice forecasting model to obtain a sea ice concentration and sea ice thickness distribution forecasting result of a planning day; combining the forecast result with ocean current and wind field forecast data, and utilizing a pre-established random forest navigational speed reasoning model to obtain target channel sea area planning daily navigational speed space distribution data; and carrying out route planning with minimum time cost through an improved A * algorithm to obtain a dynamic planning result of the target channel sea area route. The invention relates to the technical field of ship navigation in a sea ice area, and relates to the technical field of ship navigation in the sea ice area, a polar sea area navigation speed background field is deduced according to a fitting relationship through random forest modeling and fitting of the relationship between the navigation speed and sea ice, ocean current and a wind field, and dynamic route planning with minimum time cost is carried out.

The invention provides a single-point mooring floating type fan platform capable of actively yawing, and belongs to the technical field of offshore wind power. The problem that the aerodynamic efficiency of an impeller is reduced due to the fact that a fan platform needs to bear multiple coupling effects of ocean currents and waves and the fan platform deviates from the best windward direction due to the hydrodynamic force coupling effect when an included angle is formed between the ocean current direction and the wind direction under the action of the complex ocean environment is solved. The system comprises a wind turbine generator, a mast type tower, a platform foundation, a single-point mooring device and a flow guide device, the edge of the platform foundation is connected with the single-point mooring device and can rotate by 360 degrees around the single-point mooring device. The flow guiding device is installed at the edge position of the platform foundation and arranged opposite to the single-point mooring device, the horizontal section of the flow guiding device is in a symmetrical streamline shape, and the flow guiding device is provided with a driving device which drives the flow guiding device to rotate in the horizontal direction and adjusts the acting force of ocean current on the fan platform. The power generation device is mainly used for improving the power generation efficiency of the mast type tower offshore wind turbine platform.

The invention relates to the technical field of course early warning, and discloses an intelligent course early warning system for a ship. According to the system, navigation data of all time points of a ship, image data of all time points of a navigation area and meteorological data of all time points of the navigation area are obtained through a multi-dimensional data module and are classified to form a data set, and an intelligent evaluation module identifies and monitors abnormal targets in the data set through an image processing technology. The multi-dimensional data of the abnormal target is comprehensively evaluated, if the abnormal target does not exist in the monitoring data set, the change speed of the seawater color is analyzed, the corresponding abnormal data set is generated, the accuracy of comprehensively evaluating the abnormal target is high, the intelligent evaluation module analyzes the monitoring index in the ship navigation process in real time, and the real-time monitoring safety is high. According to the method, the danger degree of the abnormal target in the short-distance range of the ship body, the change degree of ocean current in the navigation area and the safety of the ship navigation state are judged, corresponding early warning signals and navigation suggestions are generated, and real-time monitoring and early warning are more timely and effective.

The invention discloses an L-shaped wind wave flow-earthquake simulation system and method suitable for a high gravity field, the simulation system comprises a model box, a wind generation system, an L-shaped wave generation system, a flow generation system and a vibration seabed model, and the model box is used for accommodating and installing each system and is arranged on a rotating arm of a centrifugal machine in an up-and-down swinging manner; the wind generation system is used for forming horizontal airflow circulation, the L-shaped wave generation system is used for generating waves, the flow generation system is used for generating flow, and the vibration seabed model is used for researching interaction between a maritime work structure and seabed soil under various sea conditions. The simulation system can reproduce sea wind, wave, ocean current and earthquake scenes in a high gravity field.

The invention discloses a virtual electronic channel design method and system based on an AIS (automatic identification system) technology, and the method comprises the steps: carrying out the precise correction of the position of a ship through multi-source data fusion in combination with AIS and GNSS (global navigation satellite system) data, generating a continuous and smooth virtual channel, and achieving the real-time dynamic correction of the channel through an environment adaptation correction term and a Kalman filtering algorithm. The influence of ocean current, wind speed, tide and other factors on the channel is dealt with. The system transmits updated virtual navigation channel data to a ship terminal and a port management center in real time in a low-delay manner through a VHF data link and a 5G edge computing technology, so that safe navigation of the ship under the condition of no physical navigation mark is ensured. In addition, the system can dynamically adjust the channel path, improves the emergency response capability of the port, and keeps the efficient operation of the port. The method is suitable for ship navigation and safety guarantee in extreme environments such as freezing and typhoon, and has a wide application prospect in sea areas which are susceptible to typhoon, such as frozen ports in northern China, East China Sea and the like.

The invention discloses an optimal heading control method for a digital-analog cooperative driven AUV (Autonomous Underwater Vehicle) in a three-dimensional unknown environment, which comprises the following steps of: firstly, establishing a three-dimensional six-degree-of-freedom kinematics model and a dynamics model of an under-actuated AUV in an unknown time-varying ocean current environment, and designing a sliding mode controller; secondly, designing a compensation scheme of a PPO reinforcement learning algorithm according to interference force suffered by the sliding mode controller in a three-dimensional unknown ocean current environment, constructing a state space, an action space, a reward function, an actor network and an evaluator network, and training the AUV; and after training is completed, reinforcement learning outputs disturbance force compensation in sliding mode control in real time according to the position and speed of the under-actuated AUV under the influence of the current three-dimensional unknown time-varying ocean current, and a sliding mode controller outputs a final control quantity. According to the method, the precision and robustness of sliding mode control in a complex ocean current environment are improved, and environment optimal heading positioning control of the autonomous underwater vehicle in a three-dimensional space is realized.

The invention relates to the field of ocean current remote sensing, and relates to a vector flow inversion method combining a single-station ground wave radar and a satellite-borne SAR, and the method mainly comprises the steps: calculating the frequency deviation of a first-order Bragg peak of the ground wave radar, carrying out the inversion of the sea surface radial flow of the ground wave radar, and carrying out the inversion of the sea surface radial flow of the SAR through employing a Doppler centroid anomaly method; interpolating a ground wave radar radial flow result to an SAR data grid through bilinear interpolation; inverting a single-station vector flow based on a ground wave radar radial flow result, projecting single-station vector flow data with high confidence coefficient to an SAR range direction, calculating a difference mean value of a projection flow velocity and an SAR radial flow velocity, and further calibrating the SAR radial flow; and combining a ground wave radar radial flow result with the calibrated SAR radial flow to invert a vector flow. According to the method, the defect of ocean current observation through a single means is overcome, high-precision inversion of the combined vector flow is achieved, and the method has important significance on ocean environment monitoring, disaster forecasting, shipping safety and the like.

The invention discloses a floating fan mooring load calculation method and system based on coupling simulation, and the method comprises the steps: obtaining the actual parameters of a floating fan, and constructing a first simulation model and a second simulation model in Charm3D and OpenFAST; collecting real ocean current data and configuring ocean current data of each time step length; inputting ocean current data into the two simulation models in real time, and inputting overall dynamic response data of the floating fan from the first simulation model into the second simulation model to obtain motion information of the floating fan; inputting the motion information of the floating fan into the first simulation model from the second simulation model to obtain new overall dynamic response data of the floating fan, and inputting the overall dynamic response data of the floating fan into the second simulation model again for simulation until the simulation period is finished; and mooring load data in the overall dynamic response data of the floating fan at each moment are obtained, and the time domain process of the mooring load of the floating fan is obtained. According to the method, the mooring load of the floating fan under the real ocean current condition of the open sea can be accurately calculated.

The invention discloses an offshore wind power cable line fault early warning method and system, and relates to the technical field of cable line fault early warning, and the method comprises the following steps: laying a three-dimensional distributed optical fiber temperature array along an offshore wind power cable, and monitoring the cable thermal field space distribution in combination with an active acoustic dispersion imaging technology; acquiring initial evolution trajectory data of the edge high-temperature region; and on the basis of the initial evolution trajectory data, constructing a coupling relationship among the ocean current parameter, the sediment disturbance characteristic and the cable heat conduction parameter, forming an ocean current-sediment-heat conduction coupled digital twin model, and dynamically correcting a virtual scene of the cable burial depth in the model through a recursive filtering algorithm. Through combination of thermal field monitoring, digital twin modeling and intelligent intervention, accurate early warning and dynamic response of offshore wind power cable faults are realized, the operation and maintenance efficiency is improved, system self-optimization and cross-scene migration are supported, and the safety and intelligent level of cable operation are significantly enhanced.

The invention relates to the technical field of ocean engineering and hydrological observation equipment, and discloses a self-powered hydrological detection device self-adaptive to seabed erosion and deposition changes, comprising a self-powered system comprising a vertical shaft eccentric helical blade, a rotor cross bar and a rotor vertical shaft, the bottom of the rotor vertical shaft is connected with a power generation module, and the bottom of the rotor vertical shaft is connected with a power supply module; the two rotor cross rods are sequentially arranged on the outer wall of the rotor vertical shaft from top to bottom, the outer walls of the three vertical shaft eccentric spiral blades are installed on the rotor cross rod triangles respectively, and the power generation module is electrically connected with an energy management unit. Through linkage control of the terrain adaptability system and the LSTM prediction model, on one hand, dynamic adjustment of the anchoring depth of the support can be achieved, and instrument displacement or burying is avoided; on the other hand, overall lifting and oblique movement of the device can be achieved, and equipment recovery and detection position conversion are facilitated; and meanwhile, an ocean current-temperature difference complementary power generation and intelligent energy storage system is adopted, so that five-year maintenance-free continuous power supply is realized.

The invention discloses a net cage state simulation method and system and a removable storage medium, and relates to the technical field of aquaculture, and the net cage state simulation method comprises the following steps: employing a two-dimensional plate unit to carry out simulation analysis on a thin-wall structure of a net cage body, and simulating the acting force of waves and ocean currents on the thin-wall structure; performing simulation analysis on the net rack structure and the netting structure of the net cage body by adopting a Morison model, and simulating the acting force of waves and ocean currents on the net rack structure and the netting structure; and utilizing a neural network model to evaluate local area deformation conditions and stress conditions of the net cage body under different sea conditions. According to the technical scheme, by combining different simulation methods and cooperating with the neural network model, the accuracy of net cage state simulation is improved, the performance of the net cage body under different marine environment conditions is evaluated, the method has the advantages of being short in period and low in cost, and the net cage body can be optimized and iterated in the design stage.

The invention provides an ocean current interference resistant fault-tolerant control method and system for a robot multi-motor propulsion system, and the method comprises the steps: inputting the actual and expected position error and speed error of an underwater robot into a self-adaptive backstepping sliding mode path tracking controller, and obtaining the thrust needed by tracking motion; introducing a propeller weight matrix representing the fault degree of the propeller into a weighted pseudo-inverse method, optimizing the propeller weight matrix by adopting an intelligent algorithm to obtain an optimal propeller weight matrix, and performing thrust distribution on thrust required by tracking motion through the weighted pseudo-inverse method to obtain a thrust distribution result; according to the operation and thrust distribution results of the multiple motors, the parameters of all the motors are adjusted in a self-adaptive mode through a multi-motor fault-tolerant control strategy; and each motor remotely controls the underwater robot based on the parameters after self-adaptive adjustment, and obtains the actual position and speed of the underwater robot at the current moment for loop closing.

The invention discloses a marine environment risk identification method based on big data, and the method comprises the steps: constructing a terrain prediction model based on initial static terrain and dynamic sediment migration data, and correcting the terrain data in real time; predicting topographic change in combination with corrected data and information such as weather and ocean current, and constructing an ocean environment numerical model; calibrating the model by using measured data, and judging whether to simulate or not according to real-time monitoring parameters; analyzing a simulation result, dividing a risk area, and determining a grid risk level; according to the scheme, through real-time terrain correction, accurate change prediction and dynamic model calibration, the marine environment prediction accuracy and real-time response capability are greatly improved, and scientific and efficient technical support is provided for coastal risk prevention and control, resource management and decision making.

The invention discloses a multi-energy coordination and monitoring platform for offshore oil and gas development, which relates to the technical field of multi-energy coordination and comprises a floating platform main body, and a solar power generation array (1), a sub power generation system (2), a main power generation system (3) and a water turbine cross beam (4) which are positioned on the floating platform main body, the floating platform main body adopts a hexagonal modular structure; the solar power generation array (1) comprises a plurality of monocrystalline silicon photovoltaic panels which are uniformly distributed on the floating platform main body; the sub power generation systems (2) are positioned at six vertexes of the floating platform main body; the main power generation system (3) is located in the center of the floating type platform body. And the water turbine cross beams (4) are uniformly distributed on the periphery of the floating platform main body. By comprehensively utilizing renewable energy sources such as solar energy, wind energy, wave energy and ocean current energy, stable and sustainable energy supply can be provided for the offshore oil and gas platform, and various pain points of a traditional energy supply mode are overcome.

The invention relates to the technical field of underwater construction engineering, and discloses an underwater foundation horizontal bearing capacity evaluation method which comprises the following steps: acquiring the geometric dimension and material physical and mechanical properties of a foundation, geological information of a seabed soil sample, ocean current observation data and design wave elements; the maximum scouring depth around the foundation is determined according to ocean current observation data, wave elements and sediment mechanical properties; establishing a foundation-soil body three-dimensional bearing model, and substituting the foundation and soil body mechanical properties and the scouring size to obtain the foundation bearing capacity under each foundation diameter, burial depth, scouring depth and sediment property; according to the relationship between the foundation diameter, the burial depth, the scouring depth and the sediment property and the foundation bearing capacity, a correlation model is established, and the residual value of the foundation bearing capacity after scouring is calculated according to the correlation model. Based on the pile foundation bearing characteristic and the pile-soil interaction mechanical theory, the analysis method has the advantages of being clear in theory, wide in application range, high in reliability and the like. Analysis results are accurate and reliable, influence factors are comprehensively considered, and the method is more scientific.

The invention discloses a real-time ocean simulation method and system based on sensing data, and relates to the technical field of ocean information engineering and intelligent sailing. A graph neural network is combined with a multi-head attention mechanism to carry out data fusion, importance of different sensors and data time steps is dynamically weighted, and real-time ocean simulation is realized. According to the method, the quality difference and missing conditions of heterogeneous data are adaptively processed, the deviation and noise influence in the fusion process are reduced, meanwhile, physical consistency constraints such as mass conservation and boundary non-penetration are introduced, the physical rationality and smoothness of an output ocean current field are guaranteed, non-physical artifacts are avoided, and the reliability and practicability of a result are enhanced; a streaming updating mechanism allows a graph structure and model parameters to be rapidly and incrementally updated when new data arrives, data processing and assimilation delay are greatly reduced, and nearly real-time ocean current forecasting is realized, which is crucial to a ship autonomous navigation system, and accurate ocean current information can be timely provided to support dynamic path planning and risk avoiding decision making.

The invention discloses a water surface unmanned ship control method and system under path tracking, and relates to the technical field of attitude control, and the method comprises the steps: building a kinetic model of a water surface unmanned ship; establishing a path tracking error equation for describing a system error of the unmanned surface ship relative to an expected path under a Serret-Frenet coordinate system; constructing a path tracking controller based on a linear active disturbance rejection controller; inputting the system error and a water surface unmanned ship control signal into a fuzzy RBF neural network, and outputting an optimal control parameter of a path tracking controller by taking minimization of the system error as a target; updating a path tracking controller according to the optimized control parameters; and re-estimating external disturbance by using the updated path tracking controller, outputting a control signal for optimizing the water surface unmanned ship, and controlling the water surface unmanned ship to advance along an expected path. According to the invention, the attitude control precision under strong ocean current and changeable weather is improved, and the path tracking precision of the water surface unmanned ship is greatly improved.