126 results about "Internal wave" patented technology

The invention discloses an internal wave characteristic field information rapid prediction method based on deep learning, and belongs to the technical field of ocean internal wave detection. According to the method, rapid prediction is carried out on the basis of traditional numerical simulation data by using deep learning, so that the efficiency of inner solitary wave prediction is remarkably improved; through multi-channel coupling learning and an iterative prediction strategy, the inner wave field prediction achieves the effect of high precision and high efficiency. Meanwhile, in combination with high-resolution numerical mode data, the consistency of a model prediction result and a physical process is ensured, and rapid extension period prediction of a solitary wave characteristic field in the ocean is realized while low error and high relevancy are kept. The method is suitable for application scenes of real-time ocean internal wave monitoring and early warning and the like, and can be widely applied to the technical fields of ocean environment monitoring and early warning, intelligent ocean observation, ocean engineering safety and the like.

The invention relates to the field of ocean conductivity data processing, and discloses an Argo conductivity data correction method based on the influence of thermohaline internal waves, which comprises the following steps: installing a thermohaline depth sensor and an acoustic Doppler flow velocity profiler on an Argo buoy, sampling seawater in the vertical direction, and calculating the depth of the sampled seawater; acquiring temperature, salinity and flow velocity profile data of seawater; determining the upper and lower boundary depths of the thermohalocline and the thickness of the thermohalocline according to the acquired data, calculating the internal wave frequency and the internal wave number, and calculating the temperature internal wave amplitude, the salinity internal wave amplitude, the temperature internal wave phase and the salinity internal wave phase; establishing a conductivity data correction model according to the calculated parameters; and performing dynamic correction on the conductivity data by using the model. According to the method disclosed by the invention, the accuracy and the reliability of conductivity data can be remarkably improved, and support can be provided for research in many fields such as research on physical characteristics of the ocean thermocline and halocline, ocean ecological environment and ocean material circulation.

The invention relates to the technical field of ocean engineering surveying and mapping, and particularly provides an ocean engineering surveying and mapping terrain correction method based on multi-beam sounding. The method comprises the following steps: constructing a tremor-sound velocity coupling model through multi-source data synchronous acquisition, and generating a sound velocity dynamic correction term; fusing the static sound velocity profile, the internal wave disturbance term and the sound velocity correction term, and establishing a time-shifting sound velocity field of spatio-temporal evolution; realizing dynamic space homing calculation through a double-shaft decoupling rotation matrix based on a hull attitude and a time shifting sound velocity field; tunnel effect noise is suppressed by adopting an airspace adaptive filtering technology; the terrain deformation rate is calculated in combination with continuous cycle data, and a deformation threshold value is dynamically set through soil mechanical parameters to trigger graded safety early warning; and outputting the high-precision three-dimensional terrain model without the sound velocity error and the noise interference. According to the method, the problems of geological activity interference compensation deficiency, tunnel effect noise suppression insufficiency, large dynamic environment homing error and the like in traditional surveying and mapping are solved, and the reliability of complex sea area topographic survey is remarkably improved.

The invention discloses an ocean internal wave monitoring method based on deep learning, which belongs to the technical field of ocean internal wave monitoring, is used for ocean internal wave monitoring, and comprises the following steps: acquiring a flow velocity data set of an observed sea area, taking the flow velocity data set as an original data set, performing quality control on the original data set, and performing normal sequence and abnormal sequence distinguishing on the data after quality control. Dividing a training set, a verification set and a test set; constructing an ocean internal wave anomaly monitoring model, optimizing anomaly scores and reconstructing error parameters, monitoring flow velocity observation data of the sea area by using the trained ocean internal wave anomaly monitoring model, and identifying an ocean internal wave sequence; and performing internal wave mechanical characteristic analysis on the ocean internal wave sequence extracted by the ocean internal wave anomaly monitoring model, and outputting characteristics. According to the method, the behavior pattern of the normal flow velocity can be accurately captured by adopting the deep learning model, the anomaly detection of the internal wave flow is realized through the reconstruction error, the normal flow velocity and the internal wave flow velocity are effectively distinguished, and misjudgment and missed judgment caused by a traditional method are reduced.

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 relates to an internal solitary wave identification and amplitude inversion method in mode data based on machine learning, and belongs to the technical field of ocean observation. In combination with a Mask-RCNN and a variational auto-encoder, firstly, sea surface height data is preprocessed and imaged, texture features are extracted through a local binary pattern algorithm, a labeled data set is constructed, model training is performed, and internal solitary wave stripes and positions thereof are identified from the labeled data set; through extraction and processing of temperature field data, the temperature field at the water depth is inversed by using a variational auto-encoder; and extracting the amplitude of the internal solitary wave in the temperature field based on the internal wave identification result. According to the method, large-scale and refined ocean mode data can be efficiently and accurately processed, and the efficiency and accuracy of data processing are remarkably improved. The method has a wide application prospect, and especially in marine disaster early warning, marine scientific research and internal wave mechanics research, the automatic identification and amplitude extraction capability of internal waves can be greatly improved.

The invention belongs to the technical field of ocean remote sensing and deep learning, and particularly relates to an SAR image ocean internal wave automatic extraction method which comprises the following steps: step 1, collecting SAR image data of a target sea area, and preprocessing the image, including radiation correction and geometric correction; 2, marking internal wave signals in the preprocessed SAR image in a manual marking mode, generating a truth value image used for deep learning model training, matching a truth value with an original image, randomly selecting four fifths of the truth value image as a training set, and randomly selecting the rest one fifths of the truth value image as a test set; by adopting the alpha-balanced cross-entropy loss function and the online data enhancement technology, the precision and efficiency of extracting the internal wave signal from the SAR image are effectively improved, especially under the complex imaging condition, the internal wave signal can be accurately extracted, high-precision geographic positioning of the internal wave signal is achieved by combining geographic information, and the method has the advantages of being high in accuracy and high in accuracy. The method is suitable for ocean research and high-precision environment monitoring, and has a wide application prospect.

The invention discloses a side slope wave velocity change measurement method based on passive source space superposition. The method comprises the following steps: preprocessing original seismic data of a seismic station; calculating a nine-component cross-correlation function between the station pairs; cross-correlation is taken as reference cross-correlation in five days before superposition; calculating a signal-to-noise ratio between a cross-correlation function tail wave and reference cross-correlation, extracting a tail wave signal with a relatively high signal-to-noise ratio for each component, and measuring wave velocity change through a straining method; dividing different sub-station network areas according to station layout, and superposing wave velocity changes obtained by each tail wave on different components of different rays; carrying out thermoelastic strain correction on the wave velocity change to obtain a wave velocity change diagram; calculating response coefficients of seismic waves with different frequencies at different depths; and obtaining an underground medium four-dimensional wave velocity change graph. According to the invention, new technical means and scientific basis are provided for constructing an underground shallow internal wave velocity change real-time monitoring system and researching and preventing landslide geological disasters.

The invention provides an ocean internal wave data acquisition method, medium and system, and belongs to the technical field of ocean hydrological observation.The ocean internal wave data acquisition method comprises the steps that an acoustic Doppler flow velocity profiler is used for acquiring water body movement data, a temperature-salinity-depth profiler is used for acquiring seawater parameters, and meanwhile a satellite altimeter and drifting buoy data are combined. Performing time-frequency analysis on the water body motion data, and obtaining internal wave candidate data by using band-pass filtering; and constructing an internal wave mathematical equation set comprising a hydromechanics basic equation, buoyancy frequency, a frequency dispersion relation and the like, and verifying and screening out effective data. And inputting the effective data into a pre-trained classification model to determine an internal wave type, finally extracting a key waveform segment through a preset extraction equation set, and generating and outputting internal wave characteristic waveform data. According to the method, multi-source observation data and a mathematical physical model are combined, identification, classification and feature extraction of the ocean internal waves are realized, and the problem that a data acquisition method capable of effectively extracting effective signals of the ocean internal waves and accurately identifying the features of the internal waves is lacked at present is solved.

The invention belongs to the field of near-inertia internal wave modeling, and particularly relates to a near-inertia internal wave modeling method based on a reverse echo observation array, which comprises the following steps: arranging a reverse echo measurement device array in an observation area, and acquiring echo signals from the seabed to the sea surface; performing data cleaning and band-pass filtering on the signals, and extracting near-inertia internal wave signals; calculating the depth and the relative vorticity of a mixed layer by combining historical temperature-salinity data; calculating a wind input energy flux by using the wind stress data; calculating a net level energy flux by adopting a boundary integration method; judging whether the boundary energy flux influence is smaller than a threshold value or not, and if not, adjusting array layout; and finally establishing a multivariable linear model containing wind energy input, mixed layer depth, relative vorticity and energy flux. According to the method, the temporal-spatial resolution and prediction precision of near-inertia internal wave modeling are effectively improved, the problems that in a traditional method, the boundary effect is remarkable, and multi-factor comprehensive modeling is insufficient are solved, and the method is suitable for long-term efficient monitoring of a large-range marine environment.

The invention provides an ocean internal wave feature detection method based on AUV fixed-depth navigation, and relates to the technical field of ocean exploration, ocean background profile data are collected when an AUV sinks, and actually measured temperature and actually measured depth data are collected when the AUV is fixed depth; the method comprises the following steps: correcting actually measured temperature and actually measured depth data according to ocean background profile data, converting a water body temperature time sequence of an AUV depth-keeping navigation time period into a water body fluctuation time sequence, retaining a low-frequency signal in water body displacement fluctuation by using an LMD (Local Mean Decomposition) method, and determining the amplitude and wavelength of an internal wave.

The invention belongs to the technical field of marine instruments, and particularly relates to an offshore real-time internal wave observation system and method based on three anchors, and the system comprises a three-anchor fixing frame system, a real-time internal wave observation system and a shore station terminal system. Wherein the real-time internal wave observation system is fixed in the three-anchor fixing frame system in a sliding connection manner, and the real-time internal wave observation system moves up and down along the three-anchor fixing frame system and cannot rotate in the horizontal direction under different sea surface heights, so that the stability of an observation environment is ensured; the real-time internal wave observation system is used for collecting real-time observation data and sending the real-time observation data to the shore station terminal system for processing; and the shore station terminal system is used for analyzing according to the received real-time observation data and detecting whether internal waves exist so as to judge whether to provide early warning. According to the invention, the complete measurement of the internal solitary wave in the ocean can be realized for a long time, the time resolution and the space resolution are very high, and good data are provided for the research of the internal wave.

The invention discloses a motion information constrained SAR (Synthetic Aperture Radar) ocean internal wave amplitude inversion method and system, and belongs to the field of synthetic aperture radar signal processing and the technical field of ocean remote sensing application. The method comprises the following steps: acquiring a time sequence SAR image with clear wave characteristics in a research area and preprocessing the time sequence SAR image; extracting an internal wave phase velocity from the preprocessed time sequence SAR image; selecting an SAR image profile which passes through the internal wave and is vertical to the crest line, and calculating the peak-to-peak distance of the internal wave; determining a possible interval of the internal wave amplitude by combining the internal wave phase velocity and the peak-to-peak distance; and searching the optimal fitting of the SAR image section and the theoretical section to determine the internal wave amplitude and the upper layer depth. According to the method, the robustness of internal wave amplitude inversion is improved, and support is provided for engineering application of SAR ocean internal wave amplitude inversion.

The invention provides an ocean internal wave flow field inversion method and device, and is applied to the technical field of ocean remote sensing application. The method comprises the following steps: acquiring a synthetic aperture radar (SAR) single-view complex image, and determining a Doppler centroid frequency grid of the SAR single-view complex image; determining a first sea surface radial flow velocity according to the Doppler centroid frequency grid, and determining the first sea surface radial flow velocity as a distance dimension component of a two-dimensional ocean internal wave surface flow field; determining an internal wave propagation direction according to the SAR single-view complex image, and determining an azimuth dimension component of the two-dimensional ocean internal wave surface flow field according to the internal wave propagation direction and the first sea surface radial flow velocity; and inputting the distance dimension component and the azimuth dimension component into an IIDopRIM model for iterative operation so as to output a second sea surface radial flow velocity and an azimuth flow field, and obtaining an ocean internal wave two-dimensional flow field according to the second sea surface radial flow velocity and the azimuth flow field.

The invention discloses a marine environment spring layer characteristic diagnosis data processing method, and aims at complex dynamic characteristics of a land frame edge sea spring layer to realize accurate diagnosis through multi-source data cooperation and an intelligent algorithm. The method comprises the following steps: acquiring and preprocessing field observation, remote sensing, sonar, terrain and tidal ocean current data; extracting spatio-temporal characteristics based on a CNN-LSTM hybrid network, and generating a dynamic spring layer threshold; fusing multi-source data by adopting an improved D-S evidence theory, and constructing a three-dimensional spring layer characteristic field; predicting an internal wave in combination with an attention mechanism model, and optimizing a preorder model by using sonar data. The method breaks through the limitation of a fixed threshold value, realizes spring layer dynamic identification, three-dimensional reconstruction and internal wave prediction, improves the diagnosis precision of a complex sea area, and provides key technical support for underwater detection, engineering safety and environmental research.

The invention discloses an internal wave electromagnetic response numerical simulation method based on a layered ocean model. The method comprises the following steps: acquiring geomagnetic field parameters; calculating distribution characteristics of seawater conductivity along with depth, and dispersing the distribution characteristics into a layered ocean conductivity model; an internal wave mechanical model is constructed, internal wave velocity field distribution is established through characteristic parameters of internal waves, and dynamic input is provided for electromagnetic field response calculation; substituting the internal wave velocity field and the geomagnetic field into a Maxwell equation set, and constructing an internal wave induction electromagnetic field control equation; and applying tangential electric field continuity and normal current continuity conditions on a layered interface, and performing discrete and iterative solution on an equation by adopting a finite difference method to obtain distribution characteristics of the electric field and the magnetic field at different depths and frequencies. According to the method, the problem of insufficient precision caused by a uniform conductivity hypothesis is solved, and application limitation caused by an ideal geomagnetic field hypothesis is avoided, so that accurate simulation of internal wave induction electromagnetic response under a complex ocean condition can be realized.

The invention discloses a marine ranch internal wave frequency receiver with a waterproof structure, and belongs to the technical field of marine internal wave monitoring, the marine ranch internal wave frequency receiver comprises an inner shell used for mounting a frequency receiving module and a power supply, an outer shell is fixedly mounted on the outer side of the inner shell, and the upper end of the inner shell penetrates through the top of the outer shell; the top opening of the inner shell is fixedly connected with a sealing cover; the floating and sinking adjusting assembly is mounted in a cavity between the inner shell and the outer shell; the floating adjusting piece is arranged on the outer side of the upper end of the inner shell in a sleeving mode, and the lower end of the floating adjusting piece is fixedly connected with a linkage connecting plate; and the air storage bag is embedded in the outer side of the upper part of the inner shell, and a sealing air bag is also embedded in the inner side of the inner shell. According to the marine ranch internal wave frequency receiver with the waterproof structure, secondary locking and sealing of the cover body can be realized by utilizing a seawater buoyancy effect, effective water prevention is realized, and attachments on the outer side of the shell can be automatically cleaned in a floating and sinking adjustment process.

According to the method, a universe control equation set comprising a control equation, a free surface, upper and lower layer fluid interface continuity, structure-fluid interface continuity and fluid interface and seabed constraint conditions is constructed, and a vertical-horizontal decoupling modal analysis technology is combined, so that a multi-body radiation coupling model of the bottom-supported cylindrical array with relative motion between columns is provided; an intrinsic mode expansion technology is adopted to synchronously represent a joint radiation mechanism of a surface gravity wave and an internal wave, potential function space transformation and mode matching under a multi-column coordinate system are realized through a Graf addition theorem, and a radiation matrix coupling model considering a bottom-supported boundary constraint is constructed. According to the method, the wave-column coupling effect of the density layered interface can be accurately analyzed, a multi-column interference energy transfer path is quantified, and the modal truncation error is remarkably reduced.

The invention discloses an ocean internal wave prediction method based on satellite remote sensing data, and the method comprises the steps: firstly obtaining a multi-source satellite remote sensing image of a target sea area, and building a multi-source satellite remote sensing internal wave crest line data set; and then constructing an internal wave numerical model, performing internal wave numerical simulation calculation by adopting the internal wave numerical model in a computational domain range of each two-dimensional section, further obtaining an internal wave generation statistical data set, finally constructing an internal wave generation statistical model, and obtaining an initial internal wave crest line. On the basis, matching an internal wave crest line of the remote sensing image with an initial internal wave crest line to obtain corresponding initial crest line information, an initial arrival time field and generation moments of N two-dimensional sections at a generation source of the Lusong strait, and finally constructing an internal wave initial arrival time error statistical model. And correcting the initial arrival time field to obtain a corrected arrival time field, thereby constructing an internal wave propagation model and realizing prediction of an internal wave crest line.

The invention relates to the technical field of ocean resource development, in particular to a method for calculating vortex-induced vibration of a deep-sea mining riser under the action of internal waves. According to the method, velocity and acceleration distribution characteristics of a flow field are determined according to wave parameters such as amplitude and wavelength of ocean internal waves, and load input is provided for calculation of vortex-induced vibration of the deep-sea mining riser; the ocean internal wave flow field has remarkable particularity, is different from uniform flow and typical shear flow, and is unsteady non-uniform shear flow; based on the particularity of an ocean internal wave flow field, vortex-induced load distribution on a deep-sea mining riser under the action of a traditional wake flow vibrator model is obtained by improving the traditional wake flow vibrator model; according to the geometric nonlinear problem caused by the large slenderness ratio of the deep-sea mining super-long riser and the weak constraint characteristic of the deep-sea mining riser, the rigid body displacement and the elastic deformation of the riser are separately calculated by adopting a co-rotation coordinate method, so that the calculation efficiency is improved to meet the actual engineering requirements; the invention discloses a calculation method for vortex-induced vibration of a deep-sea mining riser under the action of ocean internal waves.

The invention belongs to the technical field of ocean internal wave research, and discloses an internal wave automatic detection method and system based on a neural network. The method comprises the following steps: selecting a research sea area and collecting ocean internal wave SAR image data based on frequencies of internal waves generated in different sea areas and an available quantity of disclosed SAR radar image data; extracting an internal wave original image based on the obtained ocean internal wave SAR radar image, and cutting the original image into a gray level image; based on each cut grayscale image, automatically marking the ocean internal wave bright and dark fringes by using an improved Canny edge detection algorithm, and outputting a result as an image; and constructing a training data set on the basis of an edge detection result and the cut internal wave SAR image, and then realizing intelligent identification of internal wave stripes on the basis of a CycleGAN model. According to the invention, accurate and efficient identification of internal wave bright and dark stripes can be realized.

The invention relates to the technical field of deep sea communication and ocean observation, in particular to a long-term stable real-time communication system based on domestic satellites under high sea conditions. Comprising a submerged buoy body, the submerged buoy body is provided with a communication floating body module, a multi-source domestic satellite communication module, a low-power-consumption control module and a data processing module which are electrically connected in sequence, and an intelligent sensing module and an underwater data access module which are respectively connected with the data processing module; the device further comprises a main floating body. The system can be widely applied to deep-sea subsurface buoy platforms, marine environment monitoring stations, deep-sea scientific investigation equipment and other scenes, realizes real-time transmission of hydrodynamic and biogeochemical multi-element synchronous observation data at the water depth of 0-6000 meters, and supports research on the dynamic process of isolated waves, near-inertia internal waves and the like in the ocean and safety guarantee of the marine environment.

The invention discloses a wave absorbing impeller assembly and device and a method for rapidly eliminating internal waves thereof.The wave absorbing impeller assembly comprises a driving impeller and a wave absorbing impeller which are coaxially arranged, and the driving impeller and the wave absorbing impeller float in a water body in the mode of being perpendicular to the transmission direction of the internal waves; water body internal waves are utilized to drive the driving impeller to rotate so as to drive the wave absorbing impeller to rotate, the wave absorbing impeller rotates to generate a vertical breaking internal wave ordered flow field, and the purpose of wave absorbing is achieved. The wave-absorbing impeller assembly and device have the technical advantages that energy dissipation of internal waves is faster, the efficiency of eliminating the internal waves is higher, and disturbance to density stratification of a water body is smaller.

The application belongs to the technical field of marine environment monitoring and early warning, and specifically relates to a multi-channel internal wave flow early warning system and an early warning measurement method, which comprises the following steps: a buoy body is fixedly arranged through a fixed anchor, and a marine profile comprehensive detection module synchronously collects multi-dimensional profile data such as flow velocity, temperature and salinity. A main control unit is embedded with a mixed driving early warning model, a phase velocity of an internal wave is solved based on a physical model, a nonlinear correction is performed through a machine learning residual correction module, a high-precision internal wave phase velocity is obtained, and then early warning time, shear flow and displacement amplitude are calculated and an alarm level is determined. Alarm information is redundantly sent to a shore station receiving system through a ground mobile communication link and a satellite communication link of a multi-channel communication module, and the shore station receiving system regularly updates the machine learning model by taking measured data as incremental samples. The application realizes high-precision and low-delay early warning of internal wave flow, has high communication reliability, and is suitable for marine engineering, underwater vehicles and safety guarantee of offshore operations.

This invention relates to the field of marine observation data processing technology, specifically a method for quality control and evaluation of real-time communication mooring data, comprising the following steps: data preprocessing to obtain preprocessed data; multi-dimensional anomaly identification of the preprocessed data, removing anomalies to obtain data to be verified; multi-node spatiotemporal synchronization verification of the data to be verified to obtain synchronized data; adaptive consistency verification of the synchronized data using an internal wave mode; checking the presence of internal wave data observation signals on the synchronized data after consistency verification; and data quality level evaluation. This invention solves the data deviation problem caused by resetting the coefficients of inductively coupled sensors, achieving dual quality control of real-time data and post-corrected data; it constructs a data quality evaluation system adapted to deep-sea real-time communication moorings, quantifies data quality levels, and provides a basis for data reliability in marine scientific research.

This invention discloses an intelligent identification and positioning method for ocean internal waves based on multi-source remote sensing imagery, belonging to the field of marine remote sensing technology. The key technical solutions include the following steps: determining the geographical location and time range of the target sea area; collecting multi-temporal high-resolution remote sensing image data from synthetic aperture radar (SAR) and optical satellite imagery; labeling the internal wave features of the preprocessed multi-temporal high-resolution remote sensing image data to generate ground truth images; using a trained deep convolutional neural network model to perform pixel-level analysis on the input remote sensing images to extract ocean internal wave features and generate binarized images of the internal wave features; and converting the extracted binarized images of the internal wave features into corresponding latitude and longitude locations based on the geographical location information of the original remote sensing images. This achieves high-precision geographic positioning of internal waves, is suitable for marine research and high-precision environmental monitoring, and has broad application prospects.

The present invention discloses a hybrid power generation device with built-in pendulum wave energy in a floating wind turbine platform, belonging to the technical field of offshore wind power generation; it includes a semi-submersible platform, the semi-submersible platform includes a plurality of buoys, connecting rods and mounting rods, a base is provided at the bottom of the buoy, the buoys are divided into an upper buoy and a lower buoy, a wave energy device is provided inside the buoy, a wind turbine is provided on the top surface of the semi-submersible platform, the buoys are connected by an inclined connecting rod, and the mounting rod and the buoys are connected by an intermediate connecting rod and an inclined support rod. The present invention adopts the above structure, and the semi-submersible platform is set on the sea surface to float unstably with the sea surface. With the help of the up and down displacement caused by the unstable floating, the pendulum rod in the internal wave energy device drives the hydraulic cylinder to move up and down to generate electricity. The inertial device is provided to generate electricity, which can absorb the displacement of the floating semi-submersible platform, thereby solving the problem of low stability and safety of offshore wind turbine power generation.

The present application discloses a method for separating wake internal waves and volume internal waves of a vehicle, which relates to the technical field of ship and ocean engineering. The method includes: obtaining a time cloud map of the internal wave height along the target direction induced by the vehicle during navigation; extracting the propagation speed of the internal wave along the target direction at different frequencies; determining a first critical frequency point for dividing the propagation speeds of the internal waves at all frequencies into two groups; and using the first critical frequency point to separate the internal waves into volume internal waves and wake internal waves along the target direction, so as to further separately extract the fluctuation characteristic parameters of the wake internal waves and the volume internal waves subsequently. This method can distinguish the characteristics of volume internal waves and wake internal waves, realize the separation of volume internal waves and wake internal waves, and has important application value for the detection and tracking of the internal wave wake of the vehicle.

The application relates to a SAR image ocean internal wave stripe segmentation method, equipment and a storage medium, the method comprises the following steps: step S1, acquiring an ocean internal wave SAR image, and performing feature extraction on the ocean internal wave SAR image by adopting Gabor transformation to obtain a feature image; step S2, stripe segmentation is performed on the feature image by using a K-means clustering algorithm, the bright / dark stripes in the ocean internal wave are separated from the background, and the regions where the dark / bright stripes are located are automatically judged according to the inter-class difference; step S3, a minimum circumscribed rectangle of the bright / dark stripe contour is constructed, and the dark / bright stripe position is obtained by translating a set distance along the normal direction of the long side of the minimum circumscribed rectangle. Compared with the prior art, the method has better bright / dark stripe segmentation effect on the SAR image with strong ocean internal wave characteristics, can better identify the bright or dark stripe features with large differences from the background, and has the advantages of strong robustness and high accuracy.

This invention provides a porous wave-damping plate for aquaculture cages, specifically belonging to the field of wave-damping technology for aquaculture cages. It comprises a porous plate, wave-damping buoys, and a hollow cavity structure, forming a highly efficient energy dissipation system. The alternating openings on the surface of the porous plate allow waves to pass through. When waves impact the plate, seawater enters the hollow cavity and drives the internal wave-damping buoys to generate minute movements and collisions, thereby significantly reducing wave height and impact force. This directly protects the fish in the cage from the impact of violent water currents. The invention includes a plate body, which is detachably and fixedly installed on the outside of the cage. The plate body is a hollow plate-like structure with through holes on both the front and back sides, and the cavity of the hollow plate-like structure is filled with several wave-damping buoys for dissipating wave energy. It includes multiple plate bodies, which are spliced ​​together to form a wave-damping plate assembly. The upper end of the plate body is provided with a tenon, and the lower end of the plate body is provided with a mortise. Adjacent plates are interlocked and positioned by the tenon and mortise.