3516 results about "Seabed" patented technology

The invention discloses a seabed karst stratum tunnel shield data monitoring and analyzing method and system. The method comprises the steps that shield construction mechanical parameters, karst stratum acoustic emission signals and seawater osmotic pressure data are synchronously collected; shield construction mechanical parameters, karst stratum acoustic emission signals and seawater osmotic pressure data are subjected to seepage-stress coupling constraint, a hydraulic connectivity strength index is generated through fracture network seepage tensor inversion, and the filler migration risk level is judged based on pore water pressure dynamic mutation characteristics. And fusing the cutterhead torque frequency spectrum characteristic and the propulsive force fluctuation characteristic to generate a shield disturbance entropy value. According to the method, the hydraulic connectivity index is generated through seepage stress coupling inversion, the grouting path and the rheological parameters are dynamically optimized based on the fracture probability field, shield tunneling, seepage sudden change and grouting prevention and control cooperation is achieved, and the problem of prevention and control disjunction is radically solved.

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 ocean holographic environment comprehensive digital twinning system, and relates to the technical field of ocean monitoring, the digital twinning system comprises a data layer, a model layer, an application layer, an environment layer, a governance layer and a service layer, multi-scale spatio-temporal data is used as a substrate, and a virtual-real mapping and intelligent simulation technology is used to simulate the ocean holographic environment comprehensive digital twinning system. A full-dimension virtual mirror image covering the seabed, the middle sea and the sea surface is constructed, and the system serves core scenes such as a supervisor, scientific research cooperation and ocean engineering. According to the digital twin system, a six-layer layered architecture is adopted, edge computing and cloud computing collaboration are combined, a data-model-service-governance-environment multi-dimensional collaboration system is formed, data-driven decision making and dynamic optimization are achieved, and the marine monitoring efficiency and accuracy are improved.

The invention discloses an end-to-end underwater three-dimensional reconstruction method and system based on an underwater imaging model, and belongs to the technical field of underwater image processing. According to the method, deep learning pose estimation is combined with an underwater imaging model; firstly, a multi-frame underwater image sequence is collected as input, a deep neural network is constructed, and the network mainly comprises two core sub-modules: a pose estimation network; secondly, a three-dimensional reconstruction network is adopted, dense point cloud or voxel reconstruction is completed according to the predicted pose and image content, pose estimation and the three-dimensional reconstruction process are integrated in the same system, and overall joint optimization is achieved; and in combination with a self-adaptive underwater imaging model, modeling is performed on physical processes such as underwater illumination attenuation and scattering, so that the reality sense and the accuracy of a reconstruction result are improved. According to the method, high-quality three-dimensional reconstruction of images in a complex underwater environment is realized, and the method can be widely applied to ocean engineering, underwater robots, submarine topography surveying and mapping and underwater cultural relic protection.

The invention discloses a submarine scoured pipeline stability early warning method based on artificial intelligence, and relates to the technical field of submarine pipeline protection, and the method comprises the steps: collecting and sorting submarine pipeline historical reconnaissance data and monitoring data of a target region; and constructing a seabed-submarine pipeline local fine three-dimensional hydrodynamic-sediment numerical model on the basis of a solution Navier-Stokes equation and a sediment transportation model. According to the method, the historical reconnaissance data, the monitoring data and the numerical model result are integrated, the coupling effect of various factors can be comprehensively considered, then the dynamic characteristics of seabed scouring are more comprehensively captured, key scouring factors influencing the stability of the pipeline are more accurately recognized, and meanwhile, the scouring process and result simulated by the numerical model are combined, so that the stability of the pipeline is improved. According to the method, the stress distribution and deformation conditions of the pipeline under different scour depths can be analyzed more accurately, then an early warning signal is sent out in advance, the risk that the pipeline is damaged due to scour is effectively reduced, and the reliability and accuracy of early warning are improved.

The invention provides a method and system for estimating the vertical bearing capacity of a steel pipe pile, and relates to the technical field of pile foundation engineering.The method comprises the steps that a static cone penetration test is conducted on a seabed stratum needing to be arranged for a steel pipe pile foundation, experimental data are obtained and subjected to normalization processing, soil behavior types are divided, and soil layer mechanical parameters are inverted; calculating side friction resistance and end resistance of the steel pipe pile based on the soil layer mechanical parameters to obtain initial static ultimate bearing capacity; historical equivalent cyclic load experimental data of waves in the construction sea area are obtained, an equivalent cyclic load reduction coefficient, a liquefaction reduction coefficient and a time-varying corrosion reduction coefficient are constructed, and a comprehensive time-varying reduction coefficient is constructed; the initial static ultimate bearing capacity is corrected based on the comprehensive time-varying reduction coefficient, the vertical bearing capacity of the steel pipe pile in the long-term service period is predicted, and the time-varying ultimate bearing capacity is obtained; setting an evaluation threshold according to the time-varying ultimate bearing capacity, dynamically adjusting a bearing capacity grading threshold interval, and outputting a bearing capacity grading evaluation result.

The invention discloses a heterogeneous sensor fusion method and system for dynamic covariance optimization, and the method comprises the steps: constructing a multi-source heterogeneous sensor network which comprises an underwater inertial navigation unit, a Doppler velocity sensor, an ultra-short baseline positioning system, a submarine topography matching device and a geomagnetic gradient detector; the method comprises the following steps: designing a distributed integrated navigation system by adopting a hierarchical fusion architecture, establishing a sensor confidence coefficient dynamic evaluation model based on online estimated error covariance matrix eigenvalue analysis, carrying out state prediction on a local filter level by applying Kalman filtering, and then carrying out measurement updating by adopting a novel variational Bayesian algorithm; a sensor autonomous switching and adaptive weighted dual-mode adjustment mechanism is developed on the main filter level, and self-healing improvement of navigation precision in a non-stationary environment is realized, so that the problems of dynamic reliability evaluation and fusion efficiency optimization in underwater multi-sensor multi-source navigation are solved.

The invention relates to the technical field of ocean exploration, in particular to a non-buried submarine pipeline identification method and system based on multi-beam point clouds, and the method comprises the steps: obtaining three-dimensional point cloud data of a submarine pipeline region, and carrying out the preprocessing of the obtained point cloud data; performing neighborhood construction based on the preprocessed point cloud data, setting a mask attention mechanism according to a neighborhood structure, performing geometric coding and feature enhancement by using an output result of the mask attention mechanism, performing decoding operation on the enhanced features, recovering feature representation of the complete point cloud, and performing suspended span height calculation and verification based on a segmentation result. According to the method, a decoding strategy combining reverse distance weighted interpolation and jump connection is adopted, enhanced features are accurately propagated to the original point cloud, the seabed datum plane is fitted through the reverse distance weighted interpolation, and the high-risk suspended cross area can be rapidly positioned.

The invention discloses a seabed target sonar detection method based on an adversarial network, and the method comprises the steps: S1, collecting deep sea sonar original data, and carrying out the preprocessing of the data, and obtaining a standardized sonar tensor; s2, taking the standardized sonar tensor as training input, and training an improved StyleGAN-3 model in combination with an environmental parameter vector; s3, calling the improved StyleGAN-3 model, and outputting a weak target feature tensor; s4, constructing a sonar detection network; s5, outputting an optimal detection parameter set; and S6, loading the optimal detection parameter set to the sonar detection network, performing target judgment on the weak target feature tensor, and outputting a target confidence value, a three-dimensional space positioning result and a target motion track. Compared with a traditional method, the method has the advantages that in a deep sea scene, the positioning error and the target trajectory loss rate are greatly reduced, the method has excellent online tracking and dynamic situation awareness capabilities, and a solid technical support is provided for ocean monitoring, security and emergency command application.

The invention relates to the technical field of earthquake prediction, in particular to a submarine seismic oscillation prediction method and device based on earthquake exploration, and the method comprises the following steps: selecting a monitoring region, collecting the submarine topographic data of the monitoring region, and drawing a topographic map; selecting a plurality of monitoring points according to the topographic map; geomagnetic field information, electric wave information, micro-seismic activity information and seabed deformation information of each monitoring point are collected and recorded; converting the collected information into acoustic signals and transmitting the acoustic signals to a sea surface buoy, and converting the acoustic signals into electric signals by the sea surface buoy and transmitting the electric signals to a ground data center; by optimizing site selection of monitoring points, integrating geomagnetic-electric wave-microseismic-deformation multi-source data, realizing high-efficiency data transmission by using an acoustic-electric staged communication chain, and finally realizing early recognition of earthquake precursor in combination with threshold analysis, the method can significantly improve the coverage range, data precision and early warning timeliness of seafloor earthquake monitoring, and has good application prospects. And a technical support is provided for marine geological disaster prevention and control.

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 relates to the technical field of unmanned ship control, and provides an unmanned ship cluster formation cooperative control method applying a large language model. According to the method, multi-source information such as unmanned ship operation data and marine environment data is collected, deep customization training is carried out based on a large language model, and by combining transfer learning and reinforcement learning technologies, the method has autonomous learning and intelligent decision-making capabilities. During task execution, the model receives unmanned ship states, task requirements and marine environment information in real time, intelligently judges task types, plans formation forms by using an optimization algorithm and reasonably allocates tasks. For example, in a seabed surveying and mapping task, an optimal formation scheme and an optimal surveying and mapping route are determined according to surveying and mapping area characteristics and unmanned ship performance, task progress and environment change are continuously monitored, and a cooperation strategy is rapidly adjusted. According to the method, the cooperative control capability of the unmanned ship cluster formation in the complex marine environment is effectively improved, and compared with a traditional method, the method has higher autonomous learning, intelligent decision making and dynamic cooperative capabilities.

The invention relates to the technical field of marine surveying and mapping and submarine topography modeling, and discloses a submarine topography and landform construction method based on multi-source water depth data fusion, which comprises a multi-source data acquisition module, a data preprocessing module, a feature extraction module, a fusion algorithm matching module, a three-dimensional modeling module and an uncertainty evaluation module. A historical submarine topographic map is converted into grid data, namely, submarine topography is discretized into digital representation of regular grid units, water depths of other sources are converted into the grid data, the precision of the water depths of different sources is evaluated by adopting a superposition comparison method, and an error distribution model is established to reasonably correct and fuse the water depth data of various sources. The innovation of the method lies in that topographic feature parameters including the gradient, the curvature matrix and the bionic optimization algorithm are introduced, the defect that a single algorithm is preset in a traditional method is overcome, and the precision of coral reef and fault zone complex areas is improved.

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 discloses a seabed foundation stability prediction method, system and device, and relates to the field of foundation stability prediction, and the method comprises the steps: dividing a target monitoring region into a plurality of monitoring sub-regions; collecting seabed data of each monitoring sub-area, wherein the seabed data comprises seabed slope stability data, seabed foundation safety data and seabed liquefaction data; according to the seabed data of each monitoring sub-region and a pre-trained seabed foundation stability evaluation model, obtaining a seabed foundation stability evaluation index of each monitoring sub-region; and according to the size relationship between the seabed foundation stability evaluation index of each monitoring sub-region and a preset seabed foundation stability threshold value, obtaining an evaluation result of the seabed foundation stability of each monitoring sub-region, thereby improving the accuracy of seabed foundation stability prediction.

The seabed imaging sonar comprises a receiving transduction module, the receiving transduction module comprises a receiving plate, an annular sealing block, a socket and a front cover, a first mounting opening is formed in the middle of the front cover, the annular sealing block is arranged at the edge of the first mounting opening, and the receiving plate is arranged at the first mounting opening; the annular sealing block is at least partially attached to the inner side face and the side edge of the receiving plate. The socket is arranged on the inner side face of the receiving plate and located in the middle of the annular sealing block. The shell is internally provided with a pressure balance cavity, the pressure balance cavity is filled with a compressible fluid medium, the side wall of the shell is provided with a second installation opening, the front cover is installed at the second installation opening, and the socket is located in the pressure balance cavity; and the piston assembly comprises a piston cylinder and a piston, the piston is movably arranged in the piston cylinder, and one end of the piston cylinder communicates with the pressure balance cavity so as to allow the compressible fluid medium to enter the piston cylinder.

The invention relates to a sea area island remote sensing information change monitoring method and system, and relates to the technical field of remote sensing monitoring, and the method comprises the steps: obtaining a remote sensing image time sequence of a target sea area island, the remote sensing image time sequence comprises a plurality of remote sensing images, and each remote sensing image has an acquisition timestamp; collecting tide height information corresponding to the target sea area island at each collection timestamp, and water depth distribution information of the monitored sea area where the target sea area island is located; and performing correction processing on each remote sensing image according to the tidal height information and the water depth distribution information corresponding to each acquisition timestamp, and generating an island boundary contour change time sequence. The invention solves the problems that the traditional sea area island remote sensing monitoring adopts a single-moment image for analysis, the real coastline change and temporary boundary offset caused by tide cannot be distinguished, the boundary extraction precision is reduced due to shallow water area seabed reflection interference, the monitoring error is large, and the monitoring precision is low. The application precision requirements of sea area management, coastal zone protection and the like cannot be met.

The invention belongs to the technical field of ocean remote sensing, and discloses an ICESat-2 shallow sea sounding signal extraction method and system, and the method comprises the steps: carrying out the data preprocessing based on the obtained ICESat-2 sounding data; constructing an elliptical neighborhood direction adaptive model based on submarine topographic features, and determining the orientation of an elliptical neighborhood; constructing an elliptical neighborhood size adaptive model considering the depth change, and determining the size of an elliptical neighborhood; refraction correction and tide correction are carried out, and water depth correction of the seabed photon points is completed. Through the density clustering algorithm, accurate detection of the underwater topography of the shallow sea water area is realized, and a new analysis thought is provided for shallow sea water depth detection. The submarine photon point extraction problem caused by non-uniform point cloud density and weak connectivity of the photon counting laser radar ICESat-2 is solved, the sounding precision is remarkably improved, and the long-term requirements of the marine surveying and mapping field on the high-precision and low-cost sounding technology are met.

The invention discloses a special-shaped steel pipe concrete pipe section hoisting dynamic pose control method, relates to the technical field of ocean engineering underwater pipeline installation, and mainly solves the problems of insufficient dynamic response and low space pose control precision when a special-shaped pipe section is hoisted in a complex water flow environment. The method comprises the steps that pipe section space pose design parameters are obtained, the pitch angle and the rolling angle of a pipe section are monitored in real time through an inclination angle sensor set, disturbance torque generated by real-time water flow force is calculated, sling length compensation amount is generated, and the take-up and pay-off speed of a chain block at each lifting point is independently adjusted; and meanwhile, adjusting mooring ropes moored on the two sides are pulled to control the horizontal rotation angle of the pipe section, the height of a lifting hook and tension of the mooring ropes are fed back and adjusted in cooperation with a floating crane positioning system, and finally accurate underwater in-position of the pipe section to the preset position of the seabed is achieved. The device is mainly used for hoisting and sinking operation of the special-shaped concrete filled steel tube section in the marine environment, water flow interference can be effectively resisted, and accurate butt joint and installation quality of a pipe section connector are guaranteed.

The invention discloses a wind wave-seabed-pile foundation-photovoltaic array multi-physics field coupling calculation system for an ocean photovoltaic power station. The system comprises a wave model construction module, a photovoltaic array wind load numerical simulation module and a multi-physics field coupling numerical model integration module. The wave model construction module is used for extracting wave elements and constructing a wave model; the photovoltaic array wind load numerical simulation module is used for performing photovoltaic array wind load numerical simulation based on the extracted wave elements and the constructed wave model; and the multi-physics field coupling numerical model integration module is used for carrying out multi-physics field coupling numerical model integration, solving and verification based on a numerical simulation structure. According to the method, the wind wave load, the seabed seepage field, the pile foundation stress field and the photovoltaic array wind field are cooperatively calculated by building the multi-field dynamic coupling model, and therefore the accuracy and reliability of offshore photovoltaic power station pile foundation bearing performance evaluation are improved.

The invention provides a data processing method for seabed-based monitoring equipment, which belongs to the technical field of electric digital data processing, and comprises the following steps: normalizing acquired data, removing abnormal values, extracting key features by using a singular value decomposition method, and segmenting by using a self-adaptive sliding time domain window to form time sequence data blocks. According to the method, a CUDA parallel processing flow is creatively used to construct a disorder matrix and a drift matrix, and a disorder mode feature vector, a drift principal component and an abnormal feature matrix are fused through a tensor decomposition technology to construct a seabed environment state tensor model. Meanwhile, a drift rule in a long-time sequence is learned by utilizing a deep sea environment perception attention network model, real-time monitoring data is corrected and compensated, and finally a seabed state evaluation standard is established by adopting a hierarchical clustering algorithm, so that the key technical problem that environment change and equipment drift in seabed monitoring data are difficult to distinguish is effectively solved.

The invention discloses a multifunctional experimental device capable of realizing a wind wave coupling effect, which comprises a deep water experimental area, a transition experimental area and a shallow water experimental area, and is characterized in that a lifting floating bottom mounted at the bottom of a water tank can simulate the elevation change from a deep sea to a shallow sea seabed; a wind generating system is assembled above the water tank and is matched with the flow guide arrays on the two sides to provide a high-quality wind field for the experimental water tank; the L-shaped wave maker can make multi-directional irregular waves, the wave flow experiment water tank and the wind making system are used for constructing a target joint field required by an experiment, and the whole process that the waves are gradually propagated from deep sea to shallow sea under the wind wave coupling effect can be achieved. The device has multiple functions of wind generation, wave generation, current generation and the like, has the function of simulating various load factors which mainly influence ocean engineering structures, and compared with an existing experimental device, the device can achieve the real wind and wave coupling effect, more truly and completely simulate the whole process of ocean wave propagation, and the experimental device has the advantages of being simple in structure and convenient to use. And a more accurate marine simulation environment is provided for experiments.

The invention discloses a marine ranching raising site selection method and system, applied to the field of data processing, and the method comprises the steps: obtaining seabed environment parameters of each target sea area; based on the time sequence change information of the submarine environment parameters, at least obtaining a temperature field distribution result and a biological field distribution result; determining full life cycle information of a to-be-bred object, and determining a corresponding growth demand parameter set; performing space-time matching analysis on the temperature field distribution result, the biological field distribution result and the growth demand parameter set, and calculating a comprehensive raising index corresponding to each target sea area; and obtaining a site selection decision result of each target sea area at least based on the shipping channel information, the ecological protection information and the corresponding comprehensive raising index of each target sea area. According to the marine ranching raising site selection method provided by the invention, scientific and effective marine ranching raising site selection can be realized by comprehensively considering seabed time sequence sensing data, biological image analysis and full life cycle requirements of cultured objects and combining a multi-objective optimization algorithm.

The invention discloses a crosslinked polyethylene insulated submarine power cable, which relates to the technical field of submarine power cables, is used for carrying out power transmission in a deep seabed, and comprises a cable body, and the cable body sequentially comprises an insulated outer protective layer, a tensile layer, an anti-corrosion layer, a steel tape armoring layer and an insulating layer from outside to inside, the interior of the insulating layer is formed by mutually winding a plurality of groups of conductor insulating shielding layers, the interior of the conductor insulating layer is formed by mutually winding a plurality of groups of conductor shielding layers, and a conductor water-blocking layer is arranged between the conductor insulating shielding layers and the conductor shielding layers; the conductor shielding layer is composed of a first conductor, a semiconductor water-blocking tape and a second conductor in sequence from outside to inside, and the cable solves the problems that when the cable is used in the seabed for a long time, the cable sheath is damaged due to long-term seawater corrosion, high-pressure seawater is diffused in the longitudinal direction through gaps existing in the cable, the long-distance cable is damaged, and the service life of the cable is prolonged. Therefore, the problem that the power cable is damaged and cannot transmit power is solved.

The invention discloses an ocean-ionized layer ultralow-frequency electromagnetic target detection simulation method based on ADI-FDTD and SIBC, and belongs to the field of computational electromagnetics. The ocean-ionized layer ultralow-frequency electromagnetic target detection simulation method comprises the following steps: introducing a frequency domain surface impedance boundary condition SIBC into an ADI-FDTD model; the ocean-ionosphere simulation model is used for carrying out ocean-ionosphere ultra-low frequency electromagnetic wave attenuation analysis on the ocean-ionosphere ultra-low frequency electromagnetic wave attenuation. According to the method, the frequency domain surface impedance boundary condition (SIBC) is combined with the ADI-FDTD method for the first time, so that the calculation space for analyzing the influence of the seabed on electromagnetic wave propagation is reduced. The calculation requirement is obviously reduced, and the efficiency is improved. In addition, the SIBC model based on the ADI-FDTD method can be used for simulating the scattering effect of electromagnetic waves on a high-conductivity and low-conductivity area interface.

The invention relates to a deep-ground well hole type flexible mining device and a using method thereof.The deep-ground well hole type flexible mining device comprises an equipment channel well communicated to a mining position, detection equipment and a flexible mining machine, and a power line of the flexible mining machine is connected with a power source outside the well; the flexible mining machine comprises a crushing device for excavating ores and an advancing driving device, the crushing device comprises an expansion arm, a crushing assembly and a crushing power assembly, the advancing driving device comprises a device body, and the device body and the expansion arm are connected in a hinged or rotary connection mode and can relatively move in at least two freedom degree directions. And the expansion arms and the device body are folded and unfolded, so that the flexible mining machine can be switched between a first state of passing through the equipment channel well and a second state of performing mining work. The mining operation can be carried out under the condition that personnel do not need to descend into a well, the mining requirements of a deep bottom layer and a seabed bottom layer can be met, and the mining difficulty and the mining cost are reduced.

The invention discloses a sea water area karst cave group transient electromagnetic collaborative investigation data processing method and system, and the method comprises the steps: transmitting a wide frequency spectrum excitation signal to the seabed through a shipborne transient electromagnetic transmitting system, and synchronously collecting a secondary field attenuation signal responded by a seabed medium through a pull-type receiving array, meanwhile, a distributed sensor network is arranged at a preset seabed node to collect background noise base data; performing motion attitude compensation on the secondary field attenuation signal to generate transient electromagnetic response data; constructing an adaptive filter based on the background noise base data, performing noise suppression processing on the transient electromagnetic response data, and outputting noise suppression data; and performing space-time alignment on the noise suppression data of the towed array and the seabed node data to form a three-dimensional space sampling data set. According to the method, high-precision fusion of deep and shallow detection data and quantitative evaluation of the stability of the karst cave are realized, and the detection reliability and the engineering risk early warning capability of the complex ocean karst area are remarkably improved.

The invention discloses a floating wind power platform self-energized carbon capture and deep sea sealing integrated system, which comprises a floating platform foundation, which comprises a plurality of buoy parts, and the buoy parts are integrated through connecting parts; the double-path carbon capture subsystem comprises an air carbon capture module and a seawater carbon capture module; the air carbon capture module introduces air into the adsorption module through negative pressure, and selectively adsorbs CO2 in the air; the seawater carbon capturing module is used for separating out CO2 from seawater in an electrochemical separation mode; the carbon sequestration subsystem is used for compressing, liquefying and sequestration the CO2 conveyed by the double-path carbon capture subsystem; and the wind power function subsystem comprises a wind power generation tower and power distribution equipment for supplying power to each subsystem. The platform is reasonable in configuration and high in function integration degree, has the advantages of wind energy driving, autonomous operation, continuous carbon capture, on-site storage and the like, is particularly suitable for deep and far sea areas without seabed pipe networks and far away from shore-based power grids, and can be used for application scenes such as wind power plant carbon compensation and ocean carbon removal.

The invention discloses an offshore wind turbine foundation scouring full-period intelligent monitoring method and system based on multi-source data fusion and a dynamic coupling model, and relates to the technical field of intelligent monitoring, and the method comprises the steps: deploying a multi-source monitoring module, and constructing a finite element model; carrying out load calculation and parameter inversion; and training full-cycle dynamic updating of the washout failure function model. According to the method, a self-adaptive Kriging-Bayesian method is adopted, a Bayesian inversion framework and a self-adaptive agent model are fused to solve optimal soil body parameters, full-period model dynamic updating based on dynamic monitoring data is achieved, a multi-fidelity deep kernel learning model is adopted, three types of data are fused into a training set, full-period intelligent monitoring of offshore wind turbine foundation scouring is achieved, and the method has the advantages of being simple in structure, convenient to operate and high in practicability. The dynamic identification of soil parameters is realized by combining a self-adaptive inversion framework with a displacement error closed-loop optimization mechanism, and the technical problem that a traditional static model cannot adapt to the spatial-temporal variability of seabed geology is solved.

The invention provides a tidal flat evolution prediction method and system based on a hybrid model, and relates to the field of dynamic geomorphology and artificial intelligence cross technology, and the method comprises the steps: constructing a tidal flat erosion and deposition evolution database under different scenes of a target coastal zone; constructing a landform prediction model through an artificial intelligence algorithm based on the database, and taking hydrodynamic characteristic data as input and seabed erosion and deposition variation as output; hybrid simulation is executed based on the physical mechanism model and the landform prediction model, and long-duration evolution prediction is realized by updating terrain boundary conditions through loop iteration; and the configuration service application module is used for receiving user input parameters through the interactive interface and outputting a visual result. According to the method, traditional hydrodynamic force-sediment-landform coupling calculation is decoupled into a physical mechanism and AI coordinated chain process, the calculation complexity is remarkably reduced, offline rapid calculation business of tidal flat evolution is achieved, and real-time technical support is provided for coastal zone planning and disaster prevention decision making.