14 results about "Wave parameter" patented technology

The application discloses a method for suppressing ghost waves of a streamer based on frequency-slowness domain continuation and ghost wave parameter optimization. Considering that ghost wave parameters vary with time and space and affect the ghost wave removal effect, first, the marine seismic data is divided by using a sliding time window to reduce the influence of the time variation of the ghost wave parameters; the delay time and amplitude difference coefficient of the ghost wave and the primary wave are enumerated alternately; the data in the time window is continued by using a frequency-slowness domain wave field continuation operator, and then the original marine seismic data is added and subtracted by the continued record; the sum of the absolute values of the products of the new records obtained by operation is taken as the target, the optimal ghost wave delay time and amplitude difference coefficient are iteratively searched, and then the ghost wave is suppressed; after the data in each window is suppressed, all the window data are integrated into a complete record. The method can effectively suppress the ghost wave, widen the frequency band and improve the resolution of the seismic data.

The invention discloses a sea-gas interface momentum flux calculation method coupled with sea wave data, and relates to the technical field of marine atmospheric boundary layer flux observation, and the method comprises the steps: carrying out the threshold screening and wild point removal processing of turbulence flux elements needed by the calculation based on a vortex correlation method, and carrying out the coordinate rotation of a three-dimensional wind speed; processing the obtained sea surface fluctuation data to obtain a sea wave spectrum and a wave parameter, and calculating a combined field peak parameter Qp based on the sea wave spectrum; on the basis of the Monin-Obhoff similarity theory, the Monin-Obhoff length, the atmospheric stability and the wind speed U10 of 10 meters on the sea are calculated; based on the data, the friction speed is split into a wind speed item and a wave mixing item for fitting, and finally the momentum flux is obtained. According to the method, key data such as the wave period and the wave direction of the sea waves are coupled into a calculation system, the Hendan peak parameter is introduced to represent the sea wave state, the influence of the sea waves on the momentum flux is comprehensively considered, the calculation precision is improved, and meanwhile the requirement for an observation instrument is lowered.

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 provides a method and system for determining the roll angle of a fishing ship under the action of waves, the method comprising: obtaining ship parameters of a target fishing ship and wave environment parameters of a target sea area; calculating dimensionless parameters according to the ship parameters and the wave environment parameters, the dimensionless parameters including relative ship speed, wave steepness, relative ship width and heading angle radian value; selecting a corresponding roll angle calculation model according to the length range of the target fishing ship; and substituting the dimensionless parameters into the selected roll angle calculation model to calculate the roll angle of the target fishing ship. The application can quickly and accurately calculate the roll angle of the fishing ship based on real-time sailing and wave parameters, realize risk warning and heading optimization, and significantly improve the safety and operation efficiency of the fishing ship sailing.

The invention discloses a self-adaptive rapid sea wave height simulation calculation method and device and a medium, and relates to the technical field of sea wave simulation calculation, and the method comprises the steps: obtaining a wave type and a wave parameter corresponding to a to-be-simulated wave; different processing strategies are adopted for different wave types to correct the initial grid matrix, and values are assigned to the corrected grid matrix; calculating a wave height matrix corresponding to the t moment based on the assigned grid matrix; executing a wave height processing process on the wave height matrix to obtain a final wave height matrix corresponding to the t moment; and when it is determined that t is smaller than the preset total duration T, t + dt is calculated, and the step of obtaining the wave parameters of the wave type corresponding to the to-be-simulated wave is executed. The method and the device are used for solving the problems of low simulation efficiency and low simulation result accuracy during sea wave height simulation in the prior art, the sea wave height simulation is adaptively and quickly completed, and the accuracy of the sea wave height simulation result is improved.

This application proposes a wave spectrum estimation method and apparatus based on dynamic dispersion factor, comprising the following steps: acquiring a continuous-time ADCP velocity sequence; acquiring the vertical velocity power spectrum based on the ADCP velocity sequence; acquiring the complex-valued frequency, wave number, and depth at different frequency points; using the complex-valued frequency, wave number, and depth corresponding to the same frequency point as a set of input vectors, and inputting multiple sets of input vectors in a batch manner into a pre-trained dynamic dispersion factor prediction model to obtain the dynamic dispersion factor; using the dynamic dispersion factor to correct the wave number at each frequency point to obtain the corrected wave number; and acquiring the wave spectrum of the ADCP velocity sequence based on the corrected wave number. This scheme uses complex-valued Transformer network modeling to predict the dynamic dispersion factor, thereby improving the accuracy of spectrum estimation and the stability of wave parameters under varying water depth conditions, providing better technical support for wave observation in complex waters such as nearshore and shallow waters.

The invention relates to the technical field of ocean, and provides a method and system for optimizing wave parameters based on inner and outer double-layer iteration. The method for optimizing the wave parameters based on inner and outer double-layer iteration comprises the following steps: constructing a wave model based on a wave mode taking a spectral energy balance equation as a core; the wave model comprises a plurality of empirical parameters and adjustment coefficients, namely to-be-optimized parameters, and then to-be-optimized parameter vectors are formed; searching an optimal parameter vector by using an inner and outer double-layer iterative optimization method, so that the error between the output wave data and the observation wave data of the wave model is minimum; the error between the output wave data and the observation wave data is represented by adopting a regularization error function, and the regularization error function is a normalized weighted mean square error introducing a priori constraint regularization term. According to the method, a wave model parameter optimization system with intelligent adjustment, closed-loop feedback and continuous evolution characteristics can be constructed, and the method can be widely applied to high-precision parameter optimization and automatic calibration of a wave mode.

The application is a wave absorbing device for an internal wave experiment water tank, belonging to the technical field of wave absorbing; comprising a water tank, a wave absorbing module, a buffer module, a power control module and a wave absorbing measuring instrument, the power control module is connected with the wave absorbing module through the buffer module; the wave absorbing measuring instrument is used to measure the related parameters of the waves in the water tank; the power control module is used to control the movement speed and direction of the buffer module; the buffer module drives the wave absorbing module to move; the wave absorbing module consumes the energy of the waves. The power control module controls the movement mode of the buffer module, and the wave absorbing mode of the wave absorbing module is adjusted in combination with the wave height, wave speed and other related wave parameters measured by the wave absorbing measuring instrument; the application has the advantages of simple operation, easy control, effective elimination of wave reflection, and is suitable for different types of water tanks and different wave states.

The invention provides a bulwark stress analysis method and system based on a large wave water tank, and relates to the technical field of water transportation engineering simulation tests. In order to solve the problems of poor stress analysis test scene coverage capability and poor analysis result precision in the prior art, the size of a wave water tank is determined according to actual wave parameters; specifically, the water tank is a large wave water tank with the length of 90 meters, the width of 3 meters and the height of 1.8 meters. A wave water tank is set to be a wave generation area and a wave absorption area, and a wave height measuring device is installed in the wave generation area; in the wave generation area, waves of various working conditions are generated, and initial wave parameters are measured according to a wave height measuring device; installing the breakwater model at a preset position of a wave generation area, and measuring wave parameters after the breakwater model is installed; and determining transmission coefficients of various working conditions according to the two wave parameters. The breakwater stress analysis method disclosed by the invention has relatively high scene coverage capability and relatively high analysis result precision.

The application discloses a wave in-situ calibration method based on a GNSS buoy and belongs to the field of wave in-situ calibration. The method comprises the following steps: obtaining buoy deviation data based on position and attitude data of the GNSS buoy under different sea conditions; constructing a deviation compensation model and a deviation sliding model based on the buoy deviation data; obtaining a deviation compensation result based on the deviation compensation model and the deviation sliding model, wherein the deviation compensation result comprises first deviation compensation and second deviation compensation; and fusing the deviation compensation result with GNSS positioning data to obtain a wave parameter estimation result.

The invention discloses a sea-gas interface momentum flux calculation method coupled with boundary layer meteorological conditions, and relates to the technical field of marine atmospheric boundary layer flux observation, comprising: performing threshold screening and outlier removal processing on turbulence flux elements required by vortex correlation method calculation, and performing coordinate rotation on three-dimensional wind speed; processing the obtained sea surface fluctuation data to obtain a sea wave spectrum and wave parameters; on the basis of the Monin-Obhoff similarity theory, the Monin-Obhoff length, the atmospheric stability and the wind speed U10 of 10 meters on the sea are calculated; based on the data, splitting the friction speed into a wind speed item and a wave mixing item for fitting, and finally obtaining momentum flux; on the basis of guaranteeing the flux calculation precision, the requirement for an observation instrument is lowered, accurate calculation of the momentum flux of the air-sea boundary layer is achieved, and the requirements for momentum flux data in the fields of marine meteorological research, weather forecast, marine resource development and the like are met.

The invention relates to the technical field of coast engineering protection, in particular to a beach erosion risk prediction method considering extreme storm conditions, comprising the following steps: S1, acquiring historical topographic data of a target beach and actually measured hydrodynamic data of historical storm; s2, on the basis of actually measured hydrodynamic data of historical stormy waves, performing statistical analysis to obtain wave parameters corresponding to extreme stormy wave conditions; s3, calculating the maximum climbing elevation of the wave on the beach; s4, downwards defining an effective erosion action range on the beach; s5, calculating to obtain the potential erosion amount of the beach shoulder under the extreme storm condition; and S6, according to the potential erosion amount of the beach shoulder and the beach stability parameters, generating an erosion risk level of the target beach. According to the method, the extreme storm parameters, the historical topographic data and the sediment characteristics are fused, the potential erosion amount of the beach is quantitatively calculated, the risk level is generated, and therefore scientific prediction and accurate division of the erosion risk of the beach are achieved.

The application provides a sea wave direction spectrum measurement method and system based on sea area measured characteristics, and relates to the technical field of ocean observation. The method comprises the following steps: obtaining a wave parameter set based on target sea area measured wave data; determining a direction concentration parameter value through regression analysis, including generating an initial direction concentration parameter based on a deep water wave steepness through a segmented regression model, and then calibrating based on an effective wave steepness; performing parameter correction on a plurality of preset direction distribution models based on the direction concentration parameter value to generate a candidate direction spectrum; and selecting a target direction spectrum according to the closeness of the candidate direction spectrum and a historical measured direction spectrum. The application improves the accuracy of direction spectrum measurement and the adaptability to sea area characteristics through measured data driving and segmented regression calibration.

The application relates to the technical field of marine engineering environment parameter calculation, and discloses a deepwater wave element calculation method suitable for long-period waves, which comprises the following steps: using global-scale ocean wave dynamics model output boundary wave parameters as boundary conditions; inputting the boundary conditions into a regional nearshore wave mathematical model to calculate and simulate parameters; comparing observed wave data with the simulated parameters, selecting a white cap dissipation coefficient with the minimum root mean square error, and feeding back the white cap dissipation coefficient to the model; using reanalysis wind field data to drive the regional nearshore wave mathematical model after the parameters are updated to generate a wave element set; extracting a wave element time sequence from the wave element set, screening and extracting annual extreme characteristic values according to a preset target period interval to generate an annual extreme sequence; fitting the annual extreme sequence by using a probability density curve, and outputting deepwater wave element return period extremes in combination with return period parameters. The application makes up for the defects of long-period swell energy loss in the open sea, and improves the accuracy of deepwater wave element extreme value calculation.