197results about "Measuring open water movement" patented technology

The invention relates to the technical field of hydrological monitoring, in particular to a multi-satellite collaborative hydrological monitoring system. The method comprises the following steps that a water level height measurement module obtains radar pulse recovery time delay data through a height measurement satellite and calculates the water level height, abnormal points are removed to generate river water level data, a water remote sensing module collects river water images through a remote sensing satellite to extract water boundary features, water area change data are deduced, and the water level height measurement module calculates the water level height. The meteorological wind shear analysis module obtains river channel meteorological data through a meteorological satellite, microwave scattering measurement and wind speed inversion are carried out, wind-induced shear stress parameters are generated, and the flow estimation module carries out section dynamic analysis and estimates the water flow in combination with river channel water level and water area data. And the flow correction module corrects the river water flow based on the wind-induced shear stress parameter and carries out real-time monitoring, and data are synchronously uploaded to the control terminal, so that comprehensive dynamic monitoring of the hydrological state of the river is realized. According to the invention, a more efficient multi-satellite collaborative hydrological monitoring system is realized.

The present disclosure provides an ice floe motion prediction method, a device, a storage medium, and an electronic device. In the method, the electronic device is configured to acquire a historical motion information sequence of ice floe in a to-be-navigated region, wherein the historical motion information sequence includes multiple pieces of historical motion information of the ice floe at different time points; invoke a motion prediction model to analyze a spatiotemporal relationship of the multiple pieces of historical motion information; and obtain motion prediction information of the ice floe in the to-be-navigated region.

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

The invention discloses a typhoon wave height prediction method based on a deep learning MOE-Transform model, and the method comprises the following specific steps: collecting historical typhoon data of a research region, and constructing a virtual typhoon data set in combination with a central pressure difference formula; processing the historical and virtual typhoon data sets through a Holland typhoon empirical model and a storm growth relation to obtain a wind field, an air pressure field and a significant wave height field; correcting the field data by using an error model on the basis of the ERA5 data set to form a typhoon space-time fusion database containing meteorological data, the significant wave height field and typhoon data; and training and testing the MOE-Transform model to obtain a typhoon wave significant wave height prediction model for typhoon wave height prediction. According to the method, the multi-task adaptability and generalization ability are improved, and the precision and timeliness of typhoon wave height prediction are improved.

The invention belongs to the technical field of sea wave height prediction, and discloses a multi-scale sea wave height prediction method and system based on a large language model, and the method comprises the steps: S1, carrying out the decoupling interaction based on an amplitude phase, and obtaining enhanced sea wave height data; s2, extracting based on multi-scale semantic information: constructing a feature pyramid structure for the enhanced sea wave height data, outputting sea wave self-encoding features of different scales, performing self-encoding on a lexicon of a large language model, outputting word vector features, and obtaining the multi-scale semantic information by using a cross-modal attention mechanism and a dynamic fusion mechanism; and S3, a step of large-scale language model prediction based on sea wave height domain cue word driving: inputting the multi-scale semantic information and the domain specific semantic features into a large-scale language model, and outputting prediction features. According to the method, sea wave complex spatial-temporal change information is effectively mined, and accurate prediction of the sea wave height is realized.

The invention relates to an unsteady-state sea wave direction spectrum estimation method. The method comprises the steps of S1, signal decomposition; s2, direction distribution calculation; s3, adaptively adjusting the time domain analysis step length; s4, performing nonparametric kernel estimation on the transient wavelet distribution probability; and S5, direction spectrum time domain adaptive reconstruction is carried out. In the time domain analysis process of wavelet analysis, a two-dimensional plug-in non-uniform bandwidth algorithm is adopted to determine a data-adaptive two-dimensional non-uniform and non-parametric kernel function, the probability of different wavelets in a wave number-direction space is analyzed, the lateral propagation sea wave energy in the non-main wave direction is estimated, and the wave energy in the non-main wave direction is obtained. Therefore, the precision and the anti-noise capability of the direction spectrum estimation method are improved. In the time domain analysis process of wavelet analysis, a sea wave signal fluctuation intensity detection algorithm based on the frequency-direction-wave number three-dimensional change rate of wave energy distribution is introduced, the time duration of sea wave signal sections is divided according to the fluctuation intensity, the time domain precision is adjusted, the calculation efficiency is improved, and meanwhile, the sea wave signals which rapidly change in the time domain are accurately captured. Measurement is avoided.

The invention relates to the technical field of port engineering construction, in particular to a tide wave joint test method and system based on multi-source data in port engineering construction. At present, the problems of insufficient data utilization, low test precision and the like exist in tide and wave joint test in port engineering construction. The method comprises the following steps: constructing a nested unstructured grid and dynamically configuring discrete parameters of a wave direction spectrum; a variation assimilation algorithm is adopted to optimize hydrodynamic parameters; solving a wave flow coupling equation to generate a combined field data set; the pile foundation stress is calculated in combination with an improved Morison equation, and a safety evaluation report is output through basin resonance characteristic analysis; the system sets corresponding modules to realize various functions based on the method. The device is mainly used for precise combined testing of tidal waves in port engineering construction so as to guarantee the safety of an engineering structure.

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 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 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.

The invention relates to a multi-signal fusion real-time deduction method for three-dimensional wave parameters along with a ship, and a deduction device consists of a state sensor, a one-way stress sensor, a vertical acceleration sensor, a shunt, a terminal junction box, a signal acquisition instrument, a host, analysis software, a signal transmission cable and the like. The deduction method comprises the processes of system state matrix discretization, transfer function calculation, Kalman filtering deduction model construction, convergence analysis, result comparison and the like, and three-dimensional time-frequency parameters of waves are deduced in real time through fusion analysis of ship motion and actual measurement data of a key position stress response sensor. Real-time information of surrounding waves can be provided for more sailing ships, more comprehensive reference basis can be provided for ship sailing and ship type optimization, and the method has practical significance and market value.

The embodiment of the invention provides a sea wave height determination method and device, a storage medium and electronic equipment, and the method comprises the steps: segmenting target point cloud data into a plurality of time sequence frames, and determining a wave crest region and a wave trough region of sea waves according to a local extreme point in the target point cloud data, each time sequence frame is used for indicating the sea surface shape at each moment; according to the wave crest area, the wave trough area and the multiple time sequence frames, a target sea wave contour model is fitted, and the target sea wave contour model is used for indicating the sea wave height and the three-dimensional shape of the sea wave at each time point; and determining the sea wave height at any time point based on the target sea wave contour model. According to the method, the problem that high-precision sea wave height data cannot be provided under complex sea conditions such as high storm waves and changeable tides in the prior art can be solved.

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 attitude self-adaptive wind wave calibration method for a typhoon landing path sea area, and relates to the field of ocean monitoring, and the method comprises the steps: obtaining attitude information, original wave height information and wind speed and direction information of a target buoy through a six-degree-of-freedom IMU, a micropressure array wave height meter and a three-axis ultrasonic wind speed sensor carried by the target buoy; compensating the original wave height information based on the attitude information and the wind speed and direction information to obtain compensated wave height information; based on remote sensing inversion data, a storm surge numerical forecasting model or historical tide level data, obtaining a storm surge lifting height of the current area, and taking the storm surge lifting height as a zero drift error of the micropressure array wave height meter; and outputting target wave height data based on the zero drift error and the compensated wave height information. According to the calibration mechanism of fusion compensation and multi-source correction provided by the method, the adaptability and practicability of a traditional buoy system under extreme meteorological conditions are remarkably improved.

A new GNSS-based real-time high-precision wave measurement method, wherein the GNSS phase, pseudo-range, Doppler frequency shift observations and broadcast ephemerides are collected by a GNSS receiver, and antenna carried by a sea surface carrier; the three-dimensional speeds of a carrier are acquired using an epoch difference of phase observations; and wave element information are then solved. The wave element information can also be obtained by integrating the speeds for a certain duration and removing a linear trend term to obtain a time-dependent displacement variations. No additional precise differential correction is needed, thereby saving on service costs and communication costs of precise differential corrections. High-precision wave element information is obtained in real time, and locally stored in a buoy or periodically returned by communication, thereby expanding the working range of GNSS-based ocean wave measurement.

The invention discloses a wetland ecological monitoring floating device based on an intelligent sensor, and relates to the technical field of ecological monitoring. The wetland ecological monitoring floating device based on the intelligent sensor comprises a floating seat, a processor, a shooting device and a sampling mechanism, the sampling mechanism comprises a liquid storage tank and a pump body, a right-angle plate is fixedly connected to the side of the top of the liquid storage tank, and a first strip-shaped hole and a second strip-shaped hole are sequentially formed in the surface of the right-angle plate; a sampling module is installed on the surface of the right-angle plate through a first strip-shaped hole and a second strip-shaped hole, the sampling module comprises a main pipe and an air cylinder, a bending frame is slidably installed on the surface of the right-angle plate through the first strip-shaped hole, a four-claw clamping piece is fixedly connected to the outer circle face of the main pipe, and a cylindrical protrusion is fixedly connected to the middle of the surface of the right-angle plate; the purpose of accurate monitoring is achieved, water sampling is convenient, soaking in water is avoided, and wetland ecology monitoring is accurate.

The embodiment of the invention provides a scanning type millimeter wave and sea wave measuring device and method. The system is applied to the technical field of marine environment monitoring and comprises a remote display control unit for data interaction with a remote communication unit; the remote communication unit is used for issuing the instruction information transmitted by the remote display control unit; the instruction information comprises a working parameter and an irradiation angle; the control unit is used for receiving the instruction information sent by the remote communication unit and controlling the radar unit to operate; the radar unit is used for transmitting corresponding radar transmitting signals according to the working parameters, rotating the two-axis turntable according to the irradiation angle so as to drive the transmitting antenna and the receiving antenna to face the sea surface, and calculating sea wave information according to the received sea surface echo signals; the clock synchronization unit is used for synchronizing timestamps into the control unit and the radar unit; the method has the advantages of reliable monitoring result, unattended operation and the like, and is of great significance to construction of a marine monitoring system.

The invention relates to the technical field of ocean monitoring, in particular to an ocean mesoscale vortex monitoring system and method based on radar images, and the system comprises a data collection module, a preprocessing module, a feature extraction and recognition module, a vortex verification module and a data analysis and storage module. The method comprises the steps of data acquisition and preprocessing, feature extraction and recognition, vortex verification and data analysis and storage. The weak feature recognition capability is improved through an improved edge detection algorithm and a multi-scale analysis method, false vortex false detection is reduced by utilizing priori knowledge and a machine learning algorithm, a data processing flow is optimized, and the computing resource demand of large-range monitoring is reduced. According to the method, the mesoscale ocean vortex can be accurately and efficiently monitored, powerful support is provided for ocean research and ocean resource management, and compared with a traditional method, the weak feature recognition accuracy, the false vortex false detection rate, the monitoring efficiency and the like are remarkably improved.

The invention relates to the technical field of flow field measurement, in particular to an ocean flow field measurement method and device, and provides the following scheme: the method comprises the following steps: collecting ocean environment parameters through a vertical sensor, determining an overlook angle of an inclination sensor based on an optimization algorithm, and generating a virtual Doppler measurement array through micro-amplitude scanning; inputting to a chaotic oscillator network to identify a Lyapunov exponent maximum direction, and determining a horizontal included angle of a second inclination sensor; furthermore, a frequency shift signal is collected, and the flow velocity and the flow direction are calculated by combining adjusting parameters, so that high-precision and high-adaptability flow field measurement is realized; the method has a dynamic response capability, and is suitable for direction structure identification and real-time flow direction calculation under complex sea conditions.

To perform presence confirmation of analysis data used by an analysis device before analysis.SOLUTION: A data output device, which includes a processor for executing a program and a storage device for storing the program, is communicably connected to a data source for storing first time-series data regarding a natural environment and an analysis device for inputting analysis target data from the data output device to execute analysis regarding the natural environment, and includes a recording section capable of recording the analysis target data. The processor executes: input processing of receiving an input of an analysis condition regarding the natural environment; first determination processing of determining whether first analysis target data corresponding to the analysis condition input by the input processing is present in the recording section; and first output processing of outputting the first analysis target data to the analysis device on the basis of a first determination result by the first determination processing.SELECTED DRAWING: Figure 3

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.

The embodiment of the invention provides a sea wave height prediction method and device, a storage medium and electronic equipment, and the method comprises the steps: fitting an autoregressive integrated moving average (ARIMA) model according to first height observation values of sea waves of a target region at a plurality of first time points of a first time period, predicting first height prediction values of the sea waves at a plurality of second time points in a second time period according to the ARIMA model; under the condition of determining that a nonlinear relationship exists in residual distribution corresponding to the ARIMA model, training a random forest model according to a residual corresponding to the ARIMA model and an environment variable of the target area in the first time period, and predicting second height prediction values of sea waves at a plurality of second time points in the second time period according to the trained random forest model; and according to the first height predicted value and the second height predicted value, determining a target height predicted value of the sea wave at a plurality of second time points of the second time period.

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.

The invention discloses a floating support installation vertical position determination method applying a laser swinger, relates to the field of ocean engineering, solves the problem of poor use effect of an existing floating support installation vertical position determination method, and comprises the following steps: S1, obtaining monitoring period type division data and a period draft average value; s2, floating installation influence factor monitoring is conducted on the first type of draught monitoring period and the second type of draught monitoring period, and monitoring period analysis data are obtained according to the monitoring result; and S3, according to the ship draught preliminary monitoring data and the monitoring period analysis data, floating height adjustment is conducted on the target ship in the first type draught monitoring period and the second type draught monitoring period. According to the method, the accuracy of floating height determination and the safety of ship navigation can be effectively improved.

The invention relates to the technical field of ocean observation and environment monitoring, in particular to an ocean two-dimensional flow field joint construction method based on SST and SAR, and the method comprises the steps: firstly, obtaining SST data and SAR data which are matched in time and space; then, the SST data are calculated through an MCC algorithm, the ocean surface temperature change is obtained, and the flow direction angle of the ocean flow field is obtained through inversion; sAR data are calculated through a DCA algorithm, and the radial speed of the ocean flow field is obtained through inversion; and finally, combining the flow direction angle and the radial speed of the ocean flow field through a vector synthesis method, and inverting a two-dimensional flow field vector of the ocean flow field. According to the method, the SST data and the SAR data are effectively combined and complemented, the limitation of a single remote sensing means is overcome, the unique advantages of different types of remote sensing data are fully utilized, and the spatial resolution and precision of an inversion result are improved; and the blank of sub-mesoscale ocean current data is effectively filled.

Systems and methods for determining varying phenomena in an environment. In an embodiment, an system includes a processor configured to receive a sequence of remote sensing data regarding an environment, wherein the environment comprises a target area where changes have occurred and a surrounding area where few or no changes have occurred; process the RS data to determine signals for the changes that have occurred in the target area and where no changes have occurred in the surrounding area, wherein the signals comprise reflected sunlight radiation or returned light or radiation of different wavelengths captured by the sensor; process the signals to determining environment data indicting varying phenomena in the environment, wherein the varying phenomena in the environment comprise changes in the physical characteristics of the target area and an amount of radiation captured by the RS data; and provide the environment data for display via a user device.

The invention belongs to the field of marine environment monitoring, and particularly relates to a method for synchronously measuring the drifting speed of floating objects on the sea surface and the flow speed of ocean currents on the peripheral surface layer, which comprises the following steps: manufacturing a drifting buoy, and enabling the drifting buoy to vertically float on the sea surface and be completely submerged in water through a steel bar counterweight; releasing the drifting buoy to a target position through the unmanned aerial vehicle; tracking and shooting drifting buoys and sea surface floating objects, and acquiring and storing image data containing positions of the drifting buoys and the sea surface floating objects; converting the relative positions of the pixels of the image data acquired by the unmanned aerial vehicle into latitude and longitude coordinates, and generating a TIFF file; after the unmanned aerial vehicle image of the TIFF file is subjected to geometric correction, the corrected TIFF file is transmitted to QGIS software, the drifting buoy position and the sea surface floating object position are marked, and the imaging moment is synchronously recorded; and calculating the sea surface floater drift speed and the peripheral surface ocean current flow velocity based on the position change at the adjacent moments. According to the scheme, the sea surface flow velocity of the near area of the sea surface floating object can be accurately measured, and the depth of the measured surface flow velocity is determined.

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.