1127 results about "Ocean current" patented technology

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 a high-temporal-spatial-resolution refined flow field reconstruction method, device and equipment and a medium, and relates to the technical field of ocean current reconstruction, and the method comprises the steps: carrying out the normalization and temporal-spatial alignment of satellite remote sensing, buoy observation and numerical simulation data; based on the alignment data, performing rehearsal on the unstructured nested grid through an FVCOM model, and then dynamically encrypting the grid according to the flow field gradient and generating a background flow field; inputting the background flow field into a PINN-GAN combined framework, and outputting a refined flow field through physical constraint loss and double-discriminator adversarial training; and scheduling a calculation task by adopting a heterogeneous accelerator, verifying the reconstructed refined flow field in real time, and performing feedback optimization. Through generation of the background flow field and refinement reconstruction, the ocean current flow field with high temporal-spatial resolution can be reconstructed efficiently and accurately.

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 discloses a high-flow-resistance multi-point observation type fish school monitoring underwater robot based on multi-source data fusion. The high-flow-resistance multi-point observation type fish school monitoring underwater robot comprises a shell, a self-adaptive ocean current resistance system and an energy system. The self-adaptive ocean current resistance system comprises an ocean current information detection module and a PID control algorithm real-time regulation and control propeller module; the ocean current information detection module is used for collecting ocean current information in real time, including water velocity, direction and turbulence intensity; the control algorithm real-time regulation and control thruster module regulates and controls the power and direction of a thruster in real time by utilizing a PID control algorithm according to ocean current changes, and it is ensured that the underwater robot keeps stable in complex ocean currents; the telescopic multi-sensor fusion system collects multi-dimensional data of a fish school by combining a plurality of sensors, and performs fusion analysis on the data by using a deep learning algorithm, thereby realizing high-precision fish school identification and tracking. And an integrated ocean current-solar energy system enables the underwater robot to have long-time cruising ability.

The invention discloses an ocean current comprehensive monitoring system based on an ocean observation buoy, and relates to the technical field of ocean observation, the ocean current comprehensive monitoring system comprises a buoy main body module, a net buoyancy adjusting module, a motion state prediction module, a buoy deviation evaluation module, a buoy motion optimization module and a data transmission module, and the modules are in electric signal connection; the buoy main body module carries various sensors to collect physical parameters of the marine environment. Through cooperative work of the motion state prediction module and the buoy motion optimization module, the system can predict and adjust the motion state of the buoy so as to reduce data acquisition errors caused by environmental changes, so that the accuracy of data is improved, a solid data basis is provided for marine scientific research, and through the motion state evaluation module, the accuracy of the buoy is improved. The abnormal motion state of the buoy can be found in time, and the state of the buoy is rapidly adjusted through the motion optimization module, so that the continuity and accuracy of data are ensured.

The invention relates to the technical field of data processing, and discloses a wind wave flow prediction method and system based on meteorological simulation. The method comprises the following steps: performing atmospheric mode simulation on initial condition data and boundary condition data to obtain sea surface wind field data and atmospheric parameter data; performing post-processing and interpolation on the sea surface wind field data and the atmospheric parameter data to obtain wind wave model driving force field data; carrying out wind wave model coupling and simulation on the wind wave model driving force field data to obtain wind wave prediction result data; performing ocean current model coupling and simulation on the wind wave prediction result data and the wind wave model driving force field data to obtain ocean environment prediction result data; and performing data fusion and data assimilation processing on the marine environment prediction result data, the storm prediction result data and the storm model driving force field data to obtain storm flow prediction data, thereby improving timeliness and accuracy of storm flow prediction based on meteorological simulation.

The invention discloses an anti-scouring device for a seabed data center pile foundation and a building and assembling method, and belongs to the technical field of marine foundation protection. The device comprises a fixing structure, an inclination angle structure used for controlling the inclination angle and the inclination direction, a rotating structure used for controlling the rotating angle and an anti-scour structure, the tidal current direction and the seabed surface scouring and silting condition are detected in real time through a water flow sensor and a terrain scanner, and the inclination angle and the rotating angle of the device are dynamically adjusted through a control system; the scouring and erosion effects of ocean current on the pile foundation are reduced; the construction and assembly method comprises the steps of an anti-scour device design stage, block prefabrication, assembly, first-time qualification inspection, pile foundation construction, second-time qualification inspection, anti-scour device installation and seabed data center installation. The performance of the device under the simulated marine environment condition is kept consistent with that in the actual environment, the safety and reliability of marine pile foundation and seabed data are improved, and long-term stable operation is ensured.

The invention belongs to the technical field of unmanned ship tracking control, and discloses a self-adaptive path tracking control method and device for an unmanned ship. The method comprises the steps of monitoring position data in real time through a boundary judgment algorithm to ensure that a ship is always in a preset safe area; multi-source data of ocean currents, radiation, batteries and the like are synchronously collected, three constraint conditions of predicting a drifting track, a charging area and remaining endurance time are constructed, a global optimal path is dynamically generated by applying a path planning algorithm, and the shortest distance, low energy consumption and high charging benefits are balanced. For energy management, a multi-stage power threshold is preset to trigger a differential loss reduction strategy. In a control layer, calculating propeller control parameters in real time based on path deviation, course deviation and environment interference; through collaborative optimization of global path planning and local control, the autonomous navigation capability, the energy utilization efficiency and the task sustainability of the unmanned ship in a dynamic environment are improved, and the method is suitable for ocean monitoring, resource exploration and other scenes.

The invention relates to the technical field of data processing, and discloses an ocean current simulation method and system based on a three-dimensional temperature-salinity value. The method comprises the following steps: carrying out line calculation and adaptive mesh refinement processing on a three-dimensional temperature and salt field simulation model to obtain a model operation scheme; performing three-dimensional visualization processing on the three-dimensional temperature and salt field initial data set and the model operation scheme to obtain dynamic three-dimensional temperature and salt field visualization data, and analyzing the dynamic three-dimensional temperature and salt field visualization data to obtain three-dimensional structure data and evolution process data of the key ocean phenomenon; performing data assimilation processing on the multi-source real-time observation data, the three-dimensional structure data and the evolution process data to obtain a fusion data set; and performing ocean current prediction calculation on the fused data set to obtain a three-dimensional ocean current prediction field, and performing uncertainty quantitative analysis on the three-dimensional ocean current prediction field to obtain ocean current simulation probability distribution data. According to the invention, the accuracy and timeliness of ocean current simulation based on the three-dimensional temperature-salinity value are improved.

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.

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 discloses an energy consumption optimization path planning method for an underwater robot. According to the method, an ocean current model is established by using a Navier-Stokes equation, and complex water flow in the ocean is simulated; a mountain peak model is used for simulating complex submarine topography, and a sphere model is used for simulating random obstacles in the ocean; the outer layer of the path planner adopts a particle swarm optimization algorithm, the inner layer of the path planner adopts a sequential quadratic programming algorithm, and the optimal speed of each section of path can be obtained while path points are obtained; fitting path points by using a B-spline curve to generate a smooth path; and a special fitness function calculation mode is adopted, and a re-planning strategy is combined, so that the calculation efficiency of the algorithm is improved. According to the method, the optimal navigation speed of the robot in different environments can be calculated, the energy consumption of the planned path is reduced on the basis of ensuring the navigation time and safety of the robot, and the efficiency and robustness of path planning are effectively improved through a multi-algorithm combined double-layer path planner and a dynamic re-planning mechanism.

The invention discloses an AUV second-order sliding mode three-dimensional trajectory tracking control method based on a preset time disturbance observer, and belongs to the field of underwater vehicle control, and the method comprises the steps: building an AUV mathematical model containing external disturbance; designing a preset time interference observer by using a preset time stability theory; according to the dynamic model and the tracking error of the AUV control system, fusing preset time stability and a second-order sliding mode technology, and constructing a preset time second-order sliding mode trajectory tracking controller; and connecting the constructed interference observer and the trajectory tracking controller to the dynamic mathematical model of the AUV, and verifying the dynamic mathematical model of the AUV control system. According to the method, the preset time method is introduced, so that the AUV can quickly track the given expected trajectory, the accurate control of the three-dimensional trajectory of the AUV is realized, and the stability of the control performance of the system under the interference of external ocean current is ensured.

The invention relates to the technical field of ocean engineering construction, and discloses a construction positioning and SCADA visualization integrated intelligent arrangement method for an arrangement ship, which comprises the following steps: synchronously acquiring coordinates and attitude parameters of the arrangement ship through a Beidou positioning terminal and an inertial navigation device, and constructing a three-dimensional digital twinborn model of a construction scene in combination with submarine topography surveying and mapping data; analyzing boundary and gradient characteristics of the target arrangement area based on the model, and generating an initial arrangement path planning scheme; position deviation and ocean current flow velocity data are monitored in real time in the operation process, and the laying path is dynamically adjusted; and the position of the laying ship, the path adjustment record and the submarine topography change are displayed in real time through a visual interface of the SCADA system. According to the method, high-precision positioning, dynamic path optimization and full-process three-dimensional visual monitoring of the laying operation are realized, the problems of large positioning deviation and response lag of a traditional method are solved, and the construction precision and efficiency are remarkably improved.

The invention discloses a cable underwater robot trajectory tracking control method for coping with ocean current disturbance, and belongs to the technical field of underwater robot trajectory tracking, and the method comprises the following steps: S1, constructing a kinematics and dynamics model of a cable underwater robot, and simplifying the kinematics model of the cable underwater robot; s2, combining speed information of a Doppler velocimeter sensor, designing a super-spiral expansion state observer, and compensating a cable underwater robot system; designing a self-adaptive super-spiral expansion state observer by combining a self-adaptive law; and S3, designing a self-adaptive super-spiral integral terminal sliding mode controller based on the self-adaptive super-spiral expansion state observer. The real-time dynamic performance and stability of the underwater robot in sliding mode control are improved, the buffeting problem existing in sliding mode control is solved, it is ensured that under the condition of ocean current disturbance, the ROV can still achieve accurate trajectory tracking, and the robustness is very high.

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 discloses an AUV (Autonomous Underwater Vehicle) path planning and control integrated method for a complex marine environment, and provides an intelligent path control scheme integrating reinforcement learning and local obstacle avoidance mainly aiming at underwater navigation problems such as submarine topography fluctuation, frequent ocean current disturbance and uncertain dynamic obstacle distribution. According to the method, a realistic three-dimensional ocean grid environment is constructed, an improved Q-learning algorithm is utilized to complete global path planning, a group of optimal path point sequences are generated, and it is ensured that the AUV has the macroscopic navigation capability. Local obstacle avoidance is performed in combination with a three-dimensional dynamic window method (3D DWA), and sudden obstacles are dynamically avoided through speed sampling and trajectory prediction. A DDPG control strategy based on deep reinforcement learning is further introduced, end-to-end training of path planning and control execution is realized, and the system can directly output a control instruction according to a real-time sensing state. A cosine attenuation learning rate, a self-adaptive exploration mechanism, an energy consumption penalty function and a dynamic obstacle prediction and control action filtering technology are fused in the method, so that the intelligence of path planning, the stability of control output and the robustness of obstacle avoidance response are effectively improved. According to the invention, the autonomous navigation capability, the environmental adaptability and the safety task completion efficiency of the AUV in a complex marine environment can be obviously enhanced, and reliable intelligent control technical support is provided for underwater operation.

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 provides a coastal estuary suspended sediment drift prediction method, device and equipment, and relates to the technical field of target tracking, and the method comprises the steps: obtaining a sediment image of a target monitoring area through employing an unmanned plane to carry a synthetic aperture radar; preprocessing the sediment image, and extracting sediment feature information from the preprocessed sediment image; the sediment characteristic information comprises sediment distribution information, sediment concentration, sediment particle size, sediment drift speed, longitude and latitude of sediment diffusion range, sediment shape and sediment surface area; training a preset sediment drift prediction model based on the sediment characteristic information in a preset period, determining a wind power factor and an ocean current factor which influence sediment drift, and obtaining a target sediment drift prediction model; and inputting the sediment characteristic information at the current moment into the target sediment drift prediction model to obtain sediment drift prediction information. According to the method, airborne real-time monitoring and a coastal estuary sediment prediction model are combined, and the precision of sediment drift prediction is improved.

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 relates to a method and a system for detecting the sealing performance of a spherical underwater connector. The method comprises the following steps: injecting dry inert gas with the same working pressure into a sealing ring through a pressure measuring hole; 5-15-degree and 0.1-1Hz sinusoidal deflection motion is applied to the sphere, and the dynamic working condition that the underwater pipeline is impacted by ocean current for a long time is simulated through short-term limit periodic deflection motion; meanwhile, the pressure fluctuation amplitude delta P is recorded with the sampling frequency larger than or equal to 10 Hz, the first period delta P0 serves as the benchmark, delta Pn is measured regularly, and a delta P (t) curve is built; and determining a critical threshold value delta Pmax through an experiment, and calculating the duration of increasing the delta P0 to the delta Pmax according to the delta P (t) curve as the predicted service life. Through short-term limit dynamic loading and high-frequency monitoring, real-time state detection and long-term performance evaluation of the sealing ring are achieved, and the problem that sealing performance degradation under alternating stress cannot be predicted through traditional static detection is solved.

The invention discloses a semi-active wind-facing single-point mooring floating type fan, the semi-active wind-facing single-point mooring floating type fan comprises a floating type foundation, a fan body and an anti-flow rudder, the floating type foundation is used for floating in seawater, the floating type foundation comprises at least two stand columns, and the stand columns are connected with the fan body. Any two adjacent stand columns are connected through a connecting frame, the multiple stand columns comprise one first stand column and at least one second stand column, and a mooring rotor is installed at the bottom end of the first stand column. The number of the draught fan is at least one, and the draught fan is used for being installed at the top end of the second stand column. The number of the anti-flow rudders is at least one, the anti-flow rudders are used for being installed at the bottom end of the second stand column, and the anti-flow rudders are used for providing lifting force in the horizontal direction for the second stand column under the effect of ocean currents. According to the semi-active wind-facing single-point mooring floating type draught fan, the influence of the current load can be reduced, it is ensured that the draught fan is always aligned with the wind load, and the power production efficiency is improved.

The invention relates to the technical field of unmanned ship navigation control, and discloses an unmanned ship navigation state control method and system based on intelligent perception. Navigation environment information of multi-dimensional data is obtained, a multi-dimensional data fusion technology is adopted for construction of an environment state matrix, and discrete environment elements are converted into structured matrix expression. In the initial path generation stage, data acquisition value evaluation is fused, obstacle avoidance requirements are considered, and a high-value detection area is actively covered. In the path correction stage, a multi-objective cost function including energy consumption, threat degree and path length is constructed, and real-time path optimization in a dynamic environment is realized. In the propulsion control link, propulsion force and rudder angle parameters are calculated by integrating the attitude, the ship speed and the ocean current speed of the unmanned ship. According to the method, the contradiction among the real-time performance of dynamic obstacle avoidance, the data acquisition efficiency and the energy consumption optimization is solved through the cooperation of global-local double-layer path planning and the control of the propulsive force and the rudder angle of the unmanned ship.

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 deep sea temporary platform large-diameter steel casing dynamic response analysis method, and relates to the technical field of deep sea engineering, and the method comprises the steps: building a three-dimensional explicit dynamic coupling model according to the typhoon frequent generation characteristics of a target sea area and steel casing structure parameters; according to the three-dimensional explicit dynamic coupling model, the wave load is decomposed, the vibration hammer load effect, the ocean current load effect and the internal wave current load effect are integrated, and a comprehensive dynamic load set of the steel casing is determined. By establishing a precise model, integrating multi-source loads, identifying a risk area, monitoring stress in real time and optimizing design parameters based on data, self-adaptive matching of steel casing design and a complex marine environment is achieved, the structural safety of the deep sea temporary platform steel casing is effectively improved, and the cost is reduced.

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 discloses a method and system for optimizing nonlinear energy vibration absorber arrangement based on a particle swarm optimization algorithm, and belongs to the technical field of nonlinear energy vibration absorber arrangement method.According to design parameters of a nonlinear vibration absorber, the mass, damping coefficient and nonlinear rigidity parameters of the vibration absorber are determined, and according to physical characteristics and stress conditions of a stand pipe, the nonlinear energy vibration absorber arrangement is optimized. Establishing a coupling kinetic equation of the riser and the vibration absorbers, describing vibration behaviors under the action of ocean currents and waves, setting initial values of the number, the position and the speed of particles, defining a fitness function for evaluating the position quality of each particle, and calculating vibration responses of the riser system under different vibration absorber arrangement conditions through a time domain minimum residual value method. Taking the minimum vibration amplitude as a target, calculating the fitness value of the position of each particle, iteratively updating the position and speed of each particle according to the updating rule of the particle swarm algorithm, and gradually approaching the optimal solution.

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.