5264 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 provides a manifold constraint-based sonar imaging reverberation elimination method and system, and is applied to the field of imaging data processing. According to the method, the time domain waveform of the echo signal is collected in real time, whether the irregular reflection peak value is detected or not is judged, potential interference and reflection in the underwater environment can be rapidly recognized, and particularly, in the complex underwater environment, non-target objects (such as seabed obstacles or sundries) possibly cause irregular reflection signals, so that the interference and reflection in the underwater environment can be rapidly recognized. Meanwhile, the underwater propagation characteristics of sound waves can be accurately modeled by collecting the reflection path of the echo signal and predicting the propagation parameters of the reverberation signal. And accurate background data can be provided for the propagation modeling of the reverberation signal through the pre-recorded information of submarine topography, geological characteristics, sound wave propagation characteristics and the like.

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.

An identification method of seabed weak echoes in airborne LiDAR bathymetry and a system thereof are provided, which belong to the technical field of marine surveying and mapping. The method includes: dividing sea area laser pulses into surface-seabed pulses or seabed-undefined pulses based on preprocessed data; using two-stage local maximum method to determine potential seabed echo positions of ALB waveforms and pre-generate seabed points; defining an ellipsoid neighborhood related to density and extracting spatial features of a pre-generated point cloud; constructing a BP neural network to identify seabed points in the pre-generated point cloud, and optimizing the identification result of the seabed points based on a laser pulse echo sequence and point cloud density.

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 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 provides a method for evaluating the stability of an offshore wind power pile foundation under the coupling action of submarine landslide and wind wave impact load, and develops a finite element model of pile-soil interaction under the action of complex lateral load. Based on an established seabed landslide impact load quantification formula, the lateral load of the single pile under the coupling action of the seabed landslide, wind, wave and flow in the complex environment is given. And finally, carrying out single pile stability analysis under the action of complex lateral load, and discussing the stability of the single pile foundation by considering the sediment strength of different sea areas at the same time. Through the technical scheme of the invention, the method can judge the stability evaluation of the single pile foundation under the action of the wind wave current load and the potential landslide load in the research area, provides reference for site selection of offshore wind power, establishment of the offshore wind power and the like, and reduces the economic loss caused by the instability of the offshore wind power.

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 data center design and construction method for connecting a subsea tunnel and a subsea pipe gallery, and belongs to the technical field of subsea data center construction. The subsea tunnel and the subsea pipe gallery are connected through a special connecting structure, and meanwhile, a design method and a construction method for connecting the subsea tunnel and the subsea pipe gallery for connecting the coast and the seabed are provided; according to the data center built by the method, coast and seabed personnel and materials can be transferred through connection of the subsea tunnel and the subsea pipe gallery, and the problem that connection and transfer of the subsea data center and shore-based resources are difficult is solved.

The invention discloses a geological survey whole-process data aggregation system for ancient marine environment evolution, and relates to the technical field of marine geological survey. The data management platform is in communication connection with a data acquisition module, a data preprocessing module, a data integration module, a data space-time interpolation module, a data quality evaluation module, an evolution analysis module and a result display module, and all the modules are in electric signal connection. By integrating deep-sea sediment, seabed rock, marine organism fossil and ocean surface environment parameter multi-source data, the data integration and processing capacity is improved, the evolution of the ancient ocean environment is simulated and predicted by utilizing the constructed random forest model, a comprehensive and deep analysis result is provided, and the analysis efficiency is improved. Not only is the evolution rule and trend of the ancient marine environment disclosed, but also a scientific basis can be provided for future environmental protection and resource management.

The invention discloses a submarine pipeline stability discrimination method based on submarine scour mechanism analysis, and relates to the technical field of submarine facility protection, basic data of a target sea area are obtained, and the basic data comprise geological information of an area where a submarine pipeline is located, hydrological information of a sea area near the pipeline and pipeline information; performing feature analysis on the basic data of the target sea area, and extracting feature data related to water flow scouring, wave scouring and soil particle movement; according to the method, the risk area which is easily influenced by scouring around the pipeline is accurately identified through seabed scouring mechanism analysis, and then key monitoring and early warning are performed on the risk area, so that protection measures are strengthened in a targeted manner, and the influence of scouring on the stability of the pipeline is dynamically evaluated through continuous monitoring and analysis; the problems of pipeline deformation and stress concentration caused by scouring can be found in time, a maintenance strategy is adjusted according to the problems, the pertinence of safety protection is improved, resources can be effectively saved, and the maintenance cost is reduced.

An environment multi-parameter monitoring base station capable of being used for long-term seafloor work is laid to the seafloor through a mother ship in a cable mode, energy is supplied through a dissolved oxygen seawater battery, long-term seafloor environment in-situ monitoring operation is carried out through carried universal and special instruments and equipment, a shore-based instruction is received to adjust a monitoring strategy, and the monitoring base station is used for monitoring the seafloor environment. Monitoring data is transmitted back to the shore-based laboratory in real time; the monitoring base station comprises a rack system, a monitoring system, a control system, a communication system, an energy supply system and a laying and recycling system; the monitoring system is used for completing in-situ monitoring operation on the influence of a seabed biochemical environment and benthos by adopting a general monitoring instrument and an extended special instrument; and the communication system is used as a signal transmission medium to perform parallel and uplink and downlink data transmission and instruction issuing so as to realize networking between the base station and each node around the base station and interaction and communication between the base station and a water surface buoy or a ship.

Anchoring system for floating platform (100) that eliminates pitching and rolling movements of the floating platform (100), by means of several anchoring lines (200) attached to the seabed (5), which are supported by several rotary fixing means (2, 3) or pulleys of the floating platform (100) and are all joined together in a common counterweight (1) hanging from the platform (100). Each anchoring line (200) comprises sublines (200d, 200c) (direct, crossover or diagonal), which keep the counterweight (1) always in correspondence with the central axis (300) of the floating platform (100). It also eliminates the pendulum movement of the counterweight (1) and is valid for floating platforms (100) with an odd number of protruding structural arms (12). The system is applicable to any type of floating platform (100), although it is particularly suitable for floating platforms that support offshore wind turbines and marine leisure platforms.

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 a method and a system for determining the elevation of an offshore wind turbine foundation scouring analysis datum plane, and the method comprises the steps: carrying out three-dimensional modeling through seabed three-dimensional point cloud data, analyzing the thickness of shallow sludge through high-frequency and low-frequency sounding data, and obtaining stratum distribution through combining with shallow profile data; calculating a theoretical scouring depth based on the water flow data, and reconstructing a three-dimensional grid data model; calculating and screening a suitable area through a terrain gradient factor, and constructing a seabed base plane calculation data set; and calculating the average elevation of each fan basic area as the datum level elevation of scouring analysis. According to the method, refined reconstruction of the regional landform of the offshore wind turbine foundation is realized, the accuracy and scientificity of determining the elevation of the reference surface are improved, reliable data support is provided for stability evaluation and design optimization of the offshore wind turbine foundation, the structural safety risk caused by scouring is remarkably reduced, and the economic benefit is improved. And the overall safety and economic benefits of the offshore wind power plant are improved.

The invention discloses a method for detecting the biological enrichment microplastic degree of bivalve mollusks in a deep sea extreme environment. According to the method, biocenosis is sampled to acquire a community structure representing a biological bed layer, then morphological characterization statistics is carried out to classify age stage data of shellfish individuals, a multivariate factor analysis method is used to obtain the shellfish individuals with the largest contribution degree in each classification age stage, then tissue-divided micro-plastic extraction is carried out, and the classification age stage data of the shellfish individuals with the largest contribution degree is obtained. The method comprises the following steps: reducing the form of seabed micro-plastics, carrying out process identification on full-size micro-plastics, tracing the duration of adsorbing the micro-plastics by each shellfish monomer by virtue of a carbon-14 dating method, and constructing a seabed shellfish dynamic enrichment curve by splicing the life of each shellfish; and finally amplifying to the whole shellfish bed layer to deduce the microplastic enrichment rate and historical accumulation amount of the whole extreme ecosystem. The method provides a scientific basis and a technical support for formulating an effective marine environment protection strategy and clarifying a marine micro-plastic source-sink relationship.

The invention relates to the field of image processing, and discloses a shooting data-based deep sea polymetallic nodule coverage rate distribution diagram compiling method, which comprises the following steps of S1, obtaining seabed shooting data of deep sea polymetallic nodules, and performing preprocessing; s2, constructing a semantic segmentation data set of the polymetallic nodule; s3, training the semantic segmentation data set by using the improved semantic segmentation neural network model; s4, analyzing the new camera data based on the trained model to obtain a segmentation result of the polymetallic nodule; and S5, according to a segmentation result, compiling a polymetallic nodule resource coverage rate distribution map. According to the invention, the YOLOv7-PMN (YOLOv7for Polymetal Nodules) model has an excellent image processing capability, and high-precision tuberculosis identification and segmentation can be realized in a complex seabed environment.

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 a long-endurance AUV (Autonomous Underwater Vehicle) and seabed data center fused intelligent cooperative monitoring method. According to the method, real-time monitoring, data transmission and intelligent feedback of a marine environment are realized through cooperative work of an autonomous underwater vehicle (AUV) and a submarine data center (UDC). The AUV is provided with a long-endurance gliding mode and a buoyancy adjusting system, long-time monitoring tasks can be executed with low energy consumption, and real-time transmission of data is ensured through a wireless communication module and a submarine cable communication system. Through an intelligent path planning algorithm and an external environment forecasting system, the AUV can autonomously adjust a navigation path to adapt to a complex and changeable marine environment. And meanwhile, the AUV has the functions of monitoring and maintaining the external structure of the seabed data center in real time, so that the stability and the operation efficiency of the data center are effectively improved. The system has the advantages of long endurance, high real-time performance, high autonomy and intelligent maintenance, and is suitable for large-scale marine environment monitoring and data center management.

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.