98results about "Measuring open water movement" patented technology

The invention relates to a tide level obtaining method and system based on an OWC wave energy conversion device. The method comprises the following steps: constructing an energy loss prediction model in the air chamber; acquiring field incident wave energy, reflected wave energy, water potential energy increment, kinetic energy increment and pneumatic output energy at the current time period; inputting incident wave energy and reflected wave energy into the model to obtain predicted energy loss; and the tide level variation is solved based on the energy conservation relational expression, and the current tide level is calculated. The system comprises an energy loss prediction module, a wave energy acquisition module, a water body energy acquisition module, a pneumatic output acquisition module, an energy loss calculation module, a tide energy solving module and a tide level calculation module, which cooperatively realize the method. According to the scheme, an external tide gauge station is not needed, the local sea area tide level can be inversed in situ, at high frequency and with high precision, the method is suitable for an OWC-breakwater fusion scene, and cooperative operation of a port and ocean energy is supported.

The invention relates to the field of internal solitary wave prediction, and discloses an ocean internal solitary wave propagation prediction method based on an improved TimeXer model, and the method comprises the following steps: constructing the improved TimeXer model; remote sensing image data of a geostationary orbit satellite GK-2A and a polar orbit satellite are collected and preprocessed; extracting internal solitary wave parameters based on remote sensing image data, constructing an internal solitary wave prediction data set in combination with hydrological environment parameters, and training a model; and acquiring remote sensing image data of a geostationary orbit satellite GK-2A and a polar orbit satellite of a target sea area, preprocessing the remote sensing image data, inputting the remote sensing image data into the model which is tested to be qualified, and performing internal solitary wave prediction. According to the method disclosed by the invention, the precision and stability of propagation prediction of the solitary waves in the ocean can be effectively improved; by introducing an innovative module, the adaptability of the model to a complex marine environment is enhanced, and a reliable scheme is provided for accurate prediction of solitary waves in the ocean.

A method for measuring channel flow based on bionic eagle-eye vision and an apparatus thereof are provided. The method includes: acquiring a channel flowing video, and carrying out image frame interval extraction on the channel flowing video to obtain a target observation image; calculating an optical flow value of the target observation image, and calculating a surface flow velocity value of the target observation image in a world coordinate system based on position change information of the optical flow value of the target observation image between image frames and a spatial resolution of the target observation image; acquiring an average cross-section flow velocity based on a pre-trained surface cross-section flow velocity coupling model, and calculating the channel flow based on the average cross-section flow velocity and a cross-section water level value.

The invention discloses a buoy type wave observation method and device based on a GNSS and an accelerometer, and relates to the technical field of marine environment monitoring, and the method comprises the steps: collecting positioning data and inertial motion data, constructing a reference acceleration through the positioning data, carrying out the dynamic real-time zero offset compensation of the acceleration, correcting the attitude of a buoy according to the angular velocity information, and carrying out the real-time zero offset compensation of the acceleration. Wave motion parameters are calculated by using a multi-order spectral moment, a horizontal velocity component is extracted, the main wave direction of waves is estimated through a maximum entropy spectrum method, and the main wave direction and the wave motion parameters are jointly packaged and transmitted through a dual-mode communication link. Through multi-source synchronous acquisition, GNSS dynamic zero offset compensation, attitude correction, wave direction calculation and parameter inversion, the problem of low accuracy and reliability of observation data caused by long-term drifting of the wave observation buoy is cooperatively solved, and meanwhile, the maintenance difficulty and cost of the wave buoy are reduced. A core algorithm is realized through an edge processing architecture, so that the cost of a single buoy is greatly reduced, and possibility is provided for large-scale high-density networking.

A method includes converting, via a wavelet transform, (i) data associated with a prior ocean state forecast to wavelet space prior ocean state data and (ii) ocean observations to wavelet space observation data, and then filtering the wavelet space observation data. The method includes generating a correction value based on a difference between the wavelet space prior ocean state data and the filtered observation data, and determining a wavelet space increment value based on (i) the generated correction value, (ii) an error covariance associated with the prior ocean state forecast, and (iii) an error covariance associated with the ocean observations. The method includes converting, via an inverse of the wavelet transform, the wavelet space increment value to a physical space increment value, and generating a current ocean state forecast based on (i) the converted physical space increment value and (ii) a background state associated with the prior ocean state forecast.

This invention discloses a multi-scale time-frequency analysis method and system for ocean current meter signal processing, relating to the field of marine information processing. The method includes: S1: acquiring raw data and performing physical benchmark correction to obtain three-dimensional current velocity data and basic mass labels; S2: extracting first and second features from the three-dimensional current velocity data through spatiotemporal decoupling; S3: fusing and separating the three-dimensional current velocity data based on the first and second features to obtain an optimized set of flow field parameters, and generating the uncertainty of each parameter by combining the basic mass labels and error source information; S4: performing comprehensive quality assessment and grading based on the first and second features and the uncertainty, outputting a data product with mass labels and uncertainty information. By extracting spatiotemporal dual-dimensional features and using them to guide signal fusion and quality assessment, highly robust processing of ocean current data and end-to-end quality traceability are achieved, significantly improving the reliability of the data product.

The invention discloses an ocean current tracing device suitable for an ocean upper surface layer and a use method thereof, and belongs to the technical field of ocean observation, the ocean current tracing device comprises a spherical main body, and a control module, a power supply module and a buoyancy system are integrated in the spherical main body; the oil bag is arranged at the top of the spherical main body and is connected with the buoyancy system through an oil path; the buoyancy system changes the total volume of the device by filling oil into the oil bag or pumping oil out of the oil bag, and therefore buoyancy is adjusted to achieve floating or diving. The pressure sensor and the temperature sensor are arranged at the upper part of the spherical main body and are respectively used for detecting water depth and water temperature; and the positioning and communication antenna is arranged at the top of the spherical main body, is connected to the control module, and is used for acquiring position information and communicating with a shore-based system when floating to the sea surface. The device is compact and small in structure, can drift along with flow at the depth of 1-20 meters according to setting, floats upwards for communication and positioning at fixed time, and is suitable for offshore ocean current track observation.

This invention proposes an automated measurement and verification method for multi-source wave parameters based on neural networks. This method can quantitatively calculate and acquire wave elements, improving the accuracy of wave element measurement. The invention extracts video images frame by frame from nearshore monitoring videos, extracts the features of the buoy based on its motion state on the sea surface, and quantitatively calculates and acquires wave elements, mainly including effective wave period, effective wave height, and wave direction. Simultaneously, it acquires effective wave period, effective wave height, and wave direction information through the wave sensor built into the float, and calculates the wave direction using the float's Beidou module and anchor position. By comparing and verifying in-situ measurements from the float with non-contact measurements from a camera, the methods complement each other, improving the accuracy of wave element measurement.

The application discloses a typhoon wave height prediction method based on a deep learning MOE-Transformer model, and specific steps are as follows: the method steps are as follows: collecting historical typhoon data of a research area, combining a central pressure difference formula to construct a virtual typhoon data set; through a Holland typhoon empirical model and a wind wave growth relationship, processing the historical and virtual typhoon data set to obtain a wind field, a pressure field and an effective wave height field; taking an ERA5 data set as a benchmark, correcting the above field data by using an error model to form a typhoon space-time fusion database containing meteorological data, the effective wave height field and typhoon data; training and testing the MOE-Transformer model to obtain a typhoon wave effective wave height prediction model for typhoon wave height prediction. The method improves the multi-task adaptability and generalization ability, and improves the precision and timeliness of typhoon wave height prediction.

A tidal information display device for a movable body includes a position measurement module configured to detect a position of the movable body, a geographical information selection module configured to determine geographic information to be displayed on a display screen based on the detected position, a tidal information module configured to receive and store tidal information based on the detected position, and a tidal information display module configured to generate display data for displaying a graphical user interface (GUI) at a predetermined position on the display screen. The GUI is configured for showing the tidal information including at least one of: a present height of a tide, a high tide time, a low tide time, and a position of the tide.

Water buoys sense water characteristics and wirelessly transfer the water characteristics for delivery to a computer system. The computer system receives the water characteristics wirelessly transferred by the water buoys. The computer system receives a location and a user water condition preference transferred by a user communication device. The computer system processes the water characteristics, the location, and the user water condition preference, and in response, generates and transfers water condition information for the location for delivery to the user communication device.

A wave spectrum calculation method based on GNSS wave measuring buoy is provided, which includes: placing GNSS drift buoys in the sea, collecting buoy position data; then obtaining three-dimensional velocity data of ocean waves; performing high pass filtering on velocity data of a sliding window to remove noise signals and trend terms, retaining wave motion data; calculating a cross spectrum and wave direction spectrum. The present disclosure solves limitations of traditional GNSS measurement methods applied to ocean buoy wave measurement, such as limited observation distance, high cost, tedious measurement and average calculation accuracy, and a need for correction services. The measurement accuracy is high and no additional correction services are required, which is more suitable for wave measurement, the wave spectrum algorithm in this method can adapt to more complex observation environments and incorporate results of a velocity measurement algorithm into a matched wave spectrum algorithm.

In an approach for efficient flood water analysis from spatio-temporal data fusion and statistics, a processor classifies regular waters by using cartographic data in a first location. A processor generates a water stream network including a watershed based on elevation data. A processor performs statistical analysis of spectral information from a multi-spectral satellite imagery over water bodies including the regular waters and flood waters. A processor correlates the spectral statistics of the multi-spectral satellite imagery to kinetic energy of the flood waters using machine learning techniques and physical modeling. A processor builds a learning model based on the correlation between the spectral statistics and the flood waters with the kinetic energy. A processor estimates kinetic energy of flood waters in a second location using the learning model. A processor evaluates a flooding risk for the second location based on the estimated flood waters kinetic energy.

This disclosure relates to a wave monitoring method, apparatus, electronic device, and computer program product, belonging to the field of marine monitoring technology. The method includes: acquiring pre-monitoring wave information for a first number of pre-monitoring waves in each monitoring cycle; obtaining a dispersion coefficient of the pre-monitoring waves based on the pre-monitoring wave information; determining a target monitoring number of waves in the monitoring cycle based on the dispersion coefficient; acquiring monitoring wave information for the target monitoring number of waves; and obtaining wave monitoring results for the monitoring cycle based on the monitoring wave information. This disclosure, by adaptively determining the target monitoring number of waves in each monitoring cycle, can more rationally plan monitoring resources, improve monitoring efficiency, and reduce monitoring costs.

The application provides a sea surface wave field reconstruction method and device based on binocular stereo vision, comprising: collecting sea surface stereo images of an observation area based on a binocular image acquisition system at a preset frame rate; constructing an initial three-dimensional wave field by combining the sea surface stereo images with a semi-global matching algorithm; filling small-size holes in the initial three-dimensional wave field by combining a morphological closing operation to obtain a preliminarily filled three-dimensional wave field; and reconstructing large-size holes in the preliminarily filled three-dimensional wave field by combining a physical model of variational data assimilation to obtain a complete sea surface wave field. In a four-dimensional variational data assimilation framework, incomplete binocular vision observation data and a wave physical model are fused to solve the problem of large-scale data holes that cannot be handled by traditional optical methods, so that a complete three-dimensional wave field that is continuous in time and space and physically consistent is reconstructed.

The application relates to a sea area and island remote sensing information change monitoring method and system, and relates to the technical field of remote sensing monitoring, and comprises the following steps: acquiring remote sensing image time series of a target sea area and island, the remote sensing image time series comprising a plurality of remote sensing images, and each remote sensing image having a collection time stamp; collecting tide height information of the target sea area and island corresponding to each collection time stamp and water depth distribution information of a monitoring sea area where the target sea area and island are located; and correcting and processing each remote sensing image according to the tide height information corresponding to each collection time stamp and the water depth distribution information, to generate island boundary profile change time series. The application solves the problem that traditional sea area and island remote sensing monitoring uses a single moment image for analysis, cannot distinguish between real coastline changes and temporary boundary shifts caused by tides, and is interfered by shallow water area seabed reflection, thereby causing boundary extraction precision to decrease, causing large monitoring errors, and failing to meet the application precision requirements of sea area management, coastal zone protection and the like.

The invention discloses water conservancy detection alarm equipment, and relates to the technical field of water conservancy detection equipment, and the water conservancy detection alarm equipment is characterized in that the upper end of a to-be-detected dam is provided with a track frame, the upper end of the track frame is slidably provided with a base, an installation part is internally provided with a driving mechanism, and a slope adaptation mechanism is arranged between the driving mechanism and the base; a platform is arranged at the upper end of the slope adaptation mechanism, a depth detection mechanism is arranged in the platform, flow speed alarm mechanisms are arranged outside the two side walls of the base, and the two flow speed alarm mechanisms are driven by a driving mechanism to work; the lifting fence mechanism is driven by the flow speed alarm mechanism to work; the problem that only the water level can be detected in traditional dam detection is avoided, the flow velocity can be predicted in advance, the flow velocity alarm mechanism triggers siren sound through the driving mechanism, and early warning is given to detection personnel and pedestrians before the water level reaches a warning line.

The invention relates to the field of acoustic velocity measurement, in particular to a method for inverting a middle-deep ocean current velocity based on a methane plume acoustic form, and aims to solve the problems that an existing ADCP direct measurement method has space-time limitation and is high in cost, and an existing traditional bubble plume inversion method is low in precision due to the assumption that bubbles linearly move at a constant speed. The method specifically comprises the following steps: extracting a target plume space coordinate from screened multi-beam data; performing weighted fitting on the coordinates to obtain a three-dimensional trajectory curve; calculating curvature and identifying extreme points to divide ocean current horizon; determining the horizontal offset of each section; constructing and correcting a bubble rising kinetic model considering thermohaline correction and a hydrate shell effect, and obtaining the time required by bubbles to rise to the depth of each layer; and finally, calculating the speed and direction of the layered ocean current according to the ratio of the offset to the time. According to the invention, large-range, low-cost and high-precision indirect inversion of the middle-deep ocean current velocity can be realized.

The invention discloses automatic resetting equipment for an offshore wave acquisition module, which is characterized in that a sealed floating body shell adopts a tumbler type structure, the bottom of the sealed floating body shell is a lower shell, and the upper part of the sealed floating body shell is an upper shell adopting a cone frustum structure; the eccentric gravity reset mechanism comprises a driving motor, a transmission gear set and an eccentric balancing weight based on PID control, the eccentric balancing weight is installed at the bottom of the sealed cabin through an annular sliding rail, and a PID attitude control algorithm is preset in the central control unit. The central control unit controls the driving motor to rotate according to inclination angle data fed back by the attitude sensing and collecting unit, the eccentric balancing weight is driven to move to a specific phase and generate reverse restoring torque, and active restoring torque generated by the eccentric gravity resetting mechanism and buoyancy restoring torque of the sealing floating body shell act synergistically. The stability and efficiency of the wave energy conversion system are improved, the maintenance cost is reduced, and the safety risk is reduced.

Systems and methods for generating a phase-resolved ocean wave forecast with ensemble based data assimilation are disclosed. An example method includes receiving radar data corresponding to an ocean surface, and determining a surface elevation and a surface potential of a portion of the ocean surface. The example method also includes generating an ensemble of perturbed ocean surface data, and applying a phase-resolved nonlinear wave model to the ensemble of perturbed ocean surface data to generate a set of forecast ocean surface data. The example method also includes receiving a subsequent set of radar data corresponding to the ocean surface, and determining a subsequent surface elevation and surface potential of the portion of the ocean surface. The example method also includes combining, by applying an ensemble Kalman filter, the set of forecast ocean surface data with the subsequent surface elevation and surface potential to generate a phase-resolved ocean wave forecast.

Provided are a method and a system for constructing an ocean significant wave height retrieval model of spaceborne GNSS-R under high sea conditions, acquiring modeling data, auxiliary data and verification data; extracting characteristic variable parameters and auxiliary variable parameter of modeling data, and matching that extracted variable parameter in time and space; carrying out data quality control and data set division on the variable parameters after time-space matching; using the divided data set to construct and train the WaveMambaFormer model, and using the SHAP explainer to calculate the feature importance and global interpretation, so as to enhance the explainability of the WaveMambaFormer model; the significant wave height data of ERA5, WaveWatch III and Jason-3 are used as reference data to evaluate the retrieval performance of WaveMambaFormer model.

The invention belongs to the technical field of marine environment expansion, and discloses a ship-borne radar sea wave perception domain expansion method and system based on deep learning, and the method comprises the steps: building a sea wave perception domain step-by-step expansion model, and achieving the spatial feature modeling and limited range expansion of local observation data through a sea wave perception domain expansion sub-module, sea wave field information in a larger range is deduced step by step in a step-by-step expansion and residual connection mode; meanwhile, a sea wave continuity constraint mechanism is introduced, continuity constraint is applied to the junction of the expanded sea area and the original observation sea area, and it is ensured that the whole wave field keeps high precision in a large range and meanwhile has space continuity. Through the ship-borne radar sea wave sensing domain extension method based on deep learning, the real-time sensing ability of the ship-borne radar to a large-range sea area in a local environment can be remarkably improved, independent operation of a ship in a marine environment is supported, and then the ship navigation safety and the real-time sea wave sensing ability of ocean engineering application are remarkably improved.

The application relates to the field of internal solitary wave prediction, and discloses a marine internal solitary wave propagation prediction method based on an improved TimeXer model, which comprises the following steps: constructing an improved TimeXer model; collecting and pre-processing remote sensing image data of a stationary orbit satellite GK-2A and a polar orbit satellite; extracting internal solitary wave parameters based on the remote sensing image data, combining with hydrological environment parameters to construct an internal solitary wave prediction data set, and training a model; obtaining remote sensing image data of the stationary orbit satellite GK-2A and the polar orbit satellite of a target sea area, pre-processing the remote sensing image data, inputting the remote sensing image data into a qualified model, and performing internal solitary wave prediction. The method disclosed by the application can effectively improve the precision and stability of marine internal solitary wave propagation prediction; the model adaptability to complex marine environments is enhanced by introducing an innovative module, and a reliable scheme is provided for accurate prediction of marine internal solitary waves.

The application discloses a kind of offshore hydrographic data observation equipment installation platform, comprising: left and right angle driving device and front and rear angle driving device are installed in shell;One end of installation base is used to install angle driving shaft device;The other end is used to install data observation equipment;Angle driving shaft device includes middle shaft and intermediate mounting block, middle shaft is sleeved on intermediate mounting block, and both synchronous motion;Left and right angle motor is installed in shell;Left and right slide block is sleeved on left and right motor screw;One end of swing shaft is connected with left and right slide block, and the other end is connected with middle shaft;Front and rear slide block is sleeved on front and rear motor screw, one end of swing shaft is connected with front and rear slide block, and the other end is connected with intermediate mounting block.The application has automatic adjustment level, high load, height self-locking performance.

The purpose of the present disclosure is to provide a flooding prediction device, etc. that make it possible to accurately predict the occurrence of flooding of a river. A flooding prediction device comprises: at least one processor configured to acquire measurement data indicating the result of measurement based on irradiation laser light emitted and radiated onto a measurement target region including the water surface part of a river, and reflection laser light reflected by the region and received by the coherent light sensing device, generate three-dimensional point group model of the measurement target region by using the measurement data, generate, by using the measurement data and the three-dimensional point group model, water surface state information indicating the state of the water surface part in the measurement target region, and predict the occurrence of flooding of the river by using the water surface state information.

A water level monitoring system includes a sensor buoy with a GPS unit and RTK correction system for high-precision elevation measurements in bodies of water. The sensor buoy is easily deployable in existing facilities and can be used to survey bodies of water during site setup. The sensor buoy includes a float, geospatial positioning unit, wireless network interface, and / or power source such as a solar array. A coordination server may receive geospatial coordinates from the sensor buoy including elevation data and use site-specific depth and volume functions to calculate water levels. Automated alerts may be generated when water levels exceed thresholds and / or control infrastructure devices such as valves and pumps to prevent overflow conditions and improve operational efficiency. The sensor buoy may operates autonomously with adaptive data resolution, accuracy, and / or precision adjustment based on water level conditions and power management needs. Applications include monitoring and controlling wastewater lagoons, reservoirs, and / or agricultural operations.

The application belongs to the technical field of marine monitoring, and discloses a wave spectrum analysis method and system based on a laser radar.The method comprises the following steps: obtaining a plurality of concentric circles in the obtained wave field point cloud data; matching the discrete time domain signals of the wave height corresponding to the concentric circles and the derivative of the wave height with respect to time, and calculating the discrete values of the amplitude of the wave spectrum with respect to frequency; calculating unknown parameters in a directional spread function; and multiplying the discrete values of the amplitude of the wave spectrum with respect to frequency and the spread function to obtain the discrete values of the directional spectrum in frequency and direction, i.e., realizing the analysis of the wave spectrum. Through the application, the problem of realizing the analysis of the wave field spectrum and the directional spectrum by using point cloud data in the analysis of the wave field is solved.

A method and system for determining a limit scouring state of riverbed in downstream river channel of a reservoir group are provided. The method includes: collecting discharge data and cross-sectional prototype observation data of the downstream river channel of the reservoir group; establishing a correlation between discharge and a sediment carrying capacity indicator of a cross-section of a controlled hydrological station; calculating variation of the sediment carrying capacity indicator corresponding to dominant discharge; and determining and verifying the limit scouring state of the riverbed in the downstream river channel of the reservoir group. The method determines the limit scouring state of the riverbed in the river channel, and verifies the preliminary screening results based on the cross-section changes with the above determination, so as to provide technical support for mastering the development process of riverbed scouring and scouring trend prediction in the dam downstream river channel of the reservoir group.

A water buoy data system stabilizes an offshore vessel. Water buoys sense wind characteristics and water characteristics at a location of the vessel. The water buoys wirelessly transfer data messages that indicate the wind characteristics and water characteristics at the location of the vessel for delivery to a computer system. The computer system receives the data messages wirelessly transferred by the water buoys that indicate the wind characteristics and the water characteristics at the location of the vessel. The computer system determines wave forces based on the wind characteristics and the water characteristics at the location of the vessel. The computer system indicates the wave forces to control vessel engine thrusters to counter the wave forces and stabilize the vessel.

The invention relates to the technical field of marine surveying and mapping, in particular to a multi-station water level linear interpolation method and system considering the tidal propagation direction. The method comprises the steps of obtaining synchronous water level observation data of a plurality of tide stations; on the basis of the synchronous water level observation data, calculating the tide time difference between every two stations in the tide gauge stations; determining the propagation direction of the tide in the area where the tide stations are located according to the tide time difference relation and the position coordinates of the tide stations; on the basis of the tide propagation direction, tide direction projection corrections of the water level point to be solved relative to at least two known water level points are calculated; and utilizing the tide direction projection correction and the water level value of the known water level point to obtain water level data of the to-be-solved water level point through linear interpolation calculation. According to the method, while the advantage of high calculation efficiency of a linear interpolation method is maintained, the water level calculation precision and reliability in a complex tide propagation environment are remarkably improved, and thus the universality of the method is enhanced.