92 results about "Surface winds" patented technology

The invention belongs to the technical field of ocean data processing, and discloses a GNSS-R and scatterometer combined same-orbit time sequence sea surface wind speed inversion method and system, and the method comprises the following steps: obtaining historical satellite data of ocean surface wind, carrying out the preprocessing of the historical satellite data, and obtaining the preprocessed data, constructing a training sample set in combination with the reference wind speed and the surge auxiliary data; constructing an initial wind speed inversion model by using a plurality of single-moment multi-frequency information fusion modules and multi-moment interactive attention enhancement modules, and training the initial wind speed inversion model by using the training sample set to obtain a same-orbit time sequence sea surface wind speed inversion model; and obtaining a time delay-Doppler correlation power diagram, GNSS-R observation parameters, scatterometer parameters and effective wave height of storm and surge, and completing sea surface wind speed inversion by using the same-orbit time sequence sea surface wind speed inversion model to obtain sea surface wind speed prediction data.

The invention discloses an aircraft environment monitoring method and system integrated with a semiconductor sensor. The method comprises the steps that S10, a semiconductor sensor array deployed on the surface of an aircraft is used for collecting temperature, humidity, air pressure, gas concentration and surface wind speed data in real time; s20, performing format standardization and error correction on the collected original environment data through a multi-channel data fusion engine, and constructing a unified input vector; s30, calculating a multi-dimensional fluctuation amplitude value of the input vector in the flight mission time window, and judging whether to trigger a high-frequency monitoring mode or not based on the value; s40, performing convolution fitting on the fluctuation amplitude value and a historical trend curve, and calculating a real-time environment disturbance index for updating a steady-state control parameter of the aircraft; s50, dynamically adjusting a control surface response strategy of the aircraft according to the disturbance index and synchronously generating a safety prompt level; and S60, uploading whole-process monitoring and response data to a ground monitoring center for intelligent optimization of model retraining and subsequent task planning.

The invention relates to the technical field of meteorological data processing, in particular to a progressive wind speed field depth downscaling method and device fusing multi-source data and space-time perception, electronic equipment and a storage medium. Multi-scale topographic features are introduced and self-adaptive fusion is performed, so that the wind field reconstruction precision in a complex topographic region is improved; a progressive multi-stage downscaling network architecture is adopted, large-multiple stable downscaling from the kilometer level to the hectometer level is effectively achieved, and error accumulation is controlled; reconstruction is carried out by utilizing a network trained through physical constraint loss, it is ensured that the divergence and the vorticity of an output wind field conform to the aerodynamics law, the physical rationality and the scientific credibility of a result are enhanced, and therefore an efficient solution is provided for obtaining a near-ground wind field with high resolution and high physical credibility.

The invention discloses a wind wave and surge extraction method and system based on a GNSS and an anemometer. The method comprises the following steps: respectively obtaining water level height data and wind data detected by a buoy for multiple times according to a reference time sequence and a detection time sequence; the buoy water level height data and the wind data are subjected to data preprocessing, the water level height and the wind data are preprocessed, and the preprocessed water level height and the preprocessed wind data are obtained; calculating the water level height and the wind data in unit time by using the preprocessed water level height and the wind data according to a segmented interpolation function, and calculating wave height data under a corresponding detection time sequence according to the water level height and the wind data in the unit time; feature set classification is carried out according to wind speed grades, IFFT is carried out after screening, and final wind wave and surge data are obtained, the water surface wind wave and surge data extraction precision is effectively improved, and low-cost and long-time-efficiency water surface wind wave and surge detection can be achieved.

The invention provides a ground-based laser radar near-surface wind field modeling method and system based on data fusion, and relates to the technical field of wind field modeling, and the method comprises the steps: firstly carrying out the multiple scanning of a target terrain region through a ground-based laser radar, so as to obtain an observation data set; acquiring land surface temperature data matched with the three-dimensional point cloud data in a space-time manner, and fusing the land surface temperature data with the three-dimensional point cloud data to generate a coupling data set; generating initial wind field feature vectors at different moments based on the coupling data set; the vectors are processed through a long-short-term memory network, and target wind field feature vectors are generated; inputting the target vector into a wind field inversion model constructed based on a high-order Taylor expansion polynomial, and calculating three-dimensional wind field data and turbulence characteristic data; and finally, constructing a near-ground wind field model of the target terrain area according to the data through a self-adaptive interpolation algorithm. According to the invention, the precision and accuracy of complex terrain near-surface wind field modeling are improved.

The invention discloses a train surface wind pressure prediction model training method, a train surface wind pressure prediction method and a related device.The train surface wind pressure prediction model training method comprises the steps that a training set is adopted to train a preset hybrid model till a first loss function value of the preset hybrid model meets a training stop condition, and a target prediction model is obtained; wherein the preset hybrid model comprises a first preset model and a second preset model, the first preset model is used for predicting and obtaining first predicted wind pressure data corresponding to the failure pressure measuring point based on the training sample, and the second preset model is used for predicting and obtaining the failure pressure measuring point based on the graph structure information and the first predicted wind pressure data. And predicting to obtain second predicted wind pressure data corresponding to the failure pressure measuring point. Thus, information from different models can be integrated, the overall prediction performance can be improved, the second preset model can help predict or interpolate missing values through the graph structure by using graph structure information, and therefore, the target prediction model can be applied to any scene to predict wind pressure data, and the application universality is improved.

The invention discloses a wind tunnel test aerodynamic force and displacement signal phase difference correction method based on self-excited vibration characteristics. The method comprises the following steps: independently collecting structure surface wind pressure and vibration displacement signals; integrating the wind pressure signal to obtain a self-excitation aerodynamic force time history; identifying the vibration frequency and the total damping ratio of the system from the displacement signal; filtering the aerodynamic force time history to extract a fundamental frequency component; based on a structural dynamic balance principle, establishing an analytic relational expression between an aerodynamic force out-of-phase component coefficient and total damping of the system; and carrying out iterative time translation on the aerodynamic force time history by taking the displacement signal as a reference until the out-of-phase component of the aerodynamic force time history meets the analytic relationship, so as to determine and correct the system delay. The invention further discloses a wind tunnel test aerodynamic force and displacement signal phase difference correction system based on the self-excited vibration characteristic and a storage medium. According to the method, electric triggering and physical transmission delay can be compensated with high precision without additional hardware, and the pneumatic parameter identification reliability is effectively improved.

The invention discloses a method for calculating wind resistance power loss under oil injection lubrication of a spiral bevel gear pair, and belongs to the field of aero-engine power transmission systems. The method comprises the following steps: constructing a gear tooth surface equation of the spiral bevel gear pair based on a Cartesian coordinate system; establishing a spiral bevel gear pair parameter model provided with an oil injection lubrication system; calculating tooth surface wind resistance power loss, large and small end surface wind resistance power loss, front and rear conical surface wind resistance power loss, tooth crest circumferential surface wind resistance power loss, tooth groove and tooth root wind resistance power loss and pump flow wind resistance power loss of the spiral bevel gear pair; and all the wind resistance power losses are added to obtain the total wind resistance power loss of the spiral bevel gear pair under oil injection lubrication. According to the method, a special analytical model is established for each region, regional modeling can be more suitable for an actual flow field, and the wind resistance power loss of the spiral bevel gear pair can be accurately calculated.

The invention discloses an anti-storm liftable floating type photovoltaic system which comprises a floating body structure, a photovoltaic panel is installed above the floating body structure, and the lower portion of the floating body structure is connected with a gravity anchor located on the seabed through an anchor chain; the winch is connected with the floating body structure through a steel wire rope and can drive the floating body structure to descend to the position below the sea level. The device can adapt to the deep sea environment and can well cope with severe environments such as strong wind, and the winch can be used for driving the floating body structure to sink to the seabed so as to avoid sea surface storm waves; a traditional floating photovoltaic device depends on a weighted base or rigid anchoring, the wind resistance is limited, and the application sea area range (such as a typhoon high-incidence area) is remarkably expanded by dynamically adjusting the position of a floating body; by sinking to a safe depth, the floating body avoids a typhoon strong wind area, the wind load is reduced, and the photovoltaic panel is prevented from being turned over, torn or collided with the fan tower drum.

The invention relates to the technical field of communication equipment, in particular to a directional antenna and a control method thereof.The directional antenna comprises a main body, a rotating mechanism, an antenna and a wind speed sensing mechanism, a control center is arranged in the main body, the rotating mechanism is rotatably arranged on the upper surface of the main body, and the side face of the rotating mechanism is an inclined face forming an included angle with the rotating axis; the antenna is vertically arranged on the side face of the rotating mechanism, the wind speed sensing mechanism is located on the upper surface of the body, and the wind speed sensing mechanism is in signal connection with the control center. The antenna has the advantages that the directional antenna is convenient to carry, and the antenna has high stability in a severe environment.

The invention discloses a conditional diffusion method for reconstructing multi-source meteorological data for tropical cyclones. The conditional diffusion method comprises the following steps: acquiring an infrared radiation brightness set, a polarization correction temperature set and a sea surface wind speed of different tropical cyclones in a specified historical period; constructing a polarization correction temperature reconstruction model based on the conditional diffusion model; the input of the polarization correction temperature reconstruction model is an infrared radiation brightness temperature set, and the output target is a polarization correction temperature set; carrying out transfer learning on the trained polarization correction temperature reconstruction model to form a sea surface wind speed reconstruction model; the input of the sea surface wind speed reconstruction model is an infrared radiation brightness temperature set, and the output target is the sea surface wind speed. Therefore, the mapping relation from the infrared radiation brightness temperature to the multi-source meteorological data is established through generative deep learning of conditional diffusion, so that the multi-source meteorological data with the temporal-spatial resolution the same as that of geostationary orbit observation is reconstructed, and good performance is shown on various meteorological indexes and computer vision indexes.

The invention provides an indirect type air cooling tower flow guiding device and an air cooling tower, the indirect type air cooling tower flow guiding device comprises an outlet flow guiding device and a tower bottom flow guiding device, the outlet flow guiding device comprises a plurality of flow guiding plates, the multiple flow guiding plates are evenly arranged at the top of an outlet of a tower body along the circumference, and flow passing holes are formed in the flow guiding plates in a penetrating mode; the tower bottom guide device is arranged in the middle of the bottom of the tower body. The flow guide plate is arranged at the top of the outlet of the tower body, and the flow passing hole is formed in the flow guide plate, so that crosswind can be guided, and strong crosswind interference can be reduced. The tower bottom flow guide device is arranged in the middle of the tower bottom to form resistance to transverse wind, so that the wind speed distribution on the outer surface of the heat exchanger finned tube bundle is more uniform. Through the synergistic effect of the outlet flow guide device and the tower bottom flow guide device, damage of crosswind to an aerodynamic field in the tower is reduced, and the problems of uneven heat exchange and low efficiency are avoided, so that the heat exchange efficiency is improved.

The present invention discloses a wind tunnel test system for measuring the surface wind speed of a stack, comprising: a stack model to be measured, which is used to obtain the surface wind speed based on a probe; and a wind flow field system, which is used to simulate natural wind and perform tests on the stack model to be measured based on the natural wind to obtain the surface wind speed of the stack model to be measured. The present invention also discloses a wind tunnel test method for measuring the surface wind speed of a stack, comprising: constructing a wind flow field system, blowing air on the stack model to be measured through the wind flow field system, and obtaining the wind speed data of each surface of the stack model to be measured; obtaining a plurality of wind speed ratios based on the wind speed data of each surface of the stack model to be measured; performing weighted averaging on the area of each surface based on the plurality of wind speed ratios to obtain a comprehensive wind speed ratio; obtaining a wind speed influence coefficient based on the comprehensive wind speed ratio, and calculating the surface wind speed of the stack based on the wind speed influence coefficient.

The invention relates to a near-surface wind field downscaling method based on deep learning, and the method comprises the following steps: S1, obtaining site data, wind field data and topographic data, and outputting wind field and topographic total high-dimensional features by a feature extraction module; s2, inputting the total high-dimensional features of the wind field and the terrain into a multi-scale feature fusion module, and outputting multi-scale fusion features; s3, outputting a first near-surface wind field grid prediction value; s4, a second full-connection prediction module outputs a second near-surface wind field grid prediction value; and S5, obtaining adaptive weighted analysis data, inputting the adaptive weighted analysis data into the adaptive weighted network, and obtaining a final surface wind field grid prediction value based on the first weight and the second weight. Compared with the prior art, the near-surface wind field downscaling method has the advantages of improving the accuracy and efficiency of near-surface wind field downscaling and the like.

The invention provides a cooling tower surface high-risk area identification method based on a wind tunnel pressure measurement test, and aims to provide a cooling tower surface high-risk area identification method which is objective, quantitative and integrates average and fluctuating wind pressure effects. Comprising the steps of data acquisition, gridding, negative pressure area preliminary screening, comprehensive risk index calculation and result output. The core lies in the definition of a comprehensive risk index, the index combines an average local shape coefficient and a pulsation local shape coefficient, and the comprehensive risk index is formed through a mathematical function. According to the method, the defects that in the prior art, subjective experience is relied on, and fluctuating wind pressure contribution is neglected are overcome, so that automatic and precise recognition of the wind-induced high-risk area on the surface of the cooling tower is achieved, and a more scientific basis is provided for wind resistance design.

The application belongs to the technical field of desertification prevention, and particularly relates to a compound grass-sand barrier construction method and system based on a 'grape' shape, which comprises the following steps: S1: using GPS, a drone and other tools to survey and map the topography of the sand land to be treated, combining historical meteorological data to determine the main wind direction, and planning the sand barrier laying area and 'grape' unit layout; S2: preparing sand barrier construction materials, the materials comprising one or more of straw, corn stalks, reeds and sand willow branches, and screening and processing are performed to ensure the material quality; the 'grape' type cluster net structure design achieves the effect of efficiently interfering with and shunting near-surface wind-sand flow; the 'grape' type sand barrier unit is distributed in a cluster shape by a plurality of small grass bundles, and is connected into a net structure by short grass belts, and this design more effectively interferes with, shunts and guides the wind-sand flow than the uniform grid-shaped grass checkerboard, thereby improving the comprehensive performance of wind erosion prevention and sand burial prevention.

The application discloses an in-vehicle wind noise prediction method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a side window surface wind noise time domain signal of a model vehicle at different wind speeds; processing the side window surface wind noise time domain signal to determine a side window surface wind noise average sound pressure level increment; using a predetermined wind noise correlation to determine an in-vehicle noise sound pressure level increment associated with the side window surface wind noise average sound pressure level increment; wherein the wind noise correlation is obtained by difference technology and curve estimation regression analysis according to the side window surface wind noise and the in-vehicle wind noise of a base vehicle; and determining the in-vehicle wind noise according to the in-vehicle noise sound pressure level increment. According to the technical scheme, the in-vehicle wind noise can be predicted through the wind noise correlation, the prediction reliability is high, the method is simple and easy to use, and the time consumption is short.

This invention discloses a method, system, and storage medium for identifying the surface wind pressure aerodynamic derivative that quantifies the contribution of aerodynamic instability to geometric shapes. The method includes: simultaneously acquiring the surface wind pressure time history and vibration displacement time history of the structural cross-section; processing the displacement signal to obtain the vibration frequency, amplitude, and phase difference; processing the wind pressure signal to obtain the wind pressure coefficient amplitude and phase difference at each measuring point; based on the theory of self-excited aerodynamics, establishing an explicit analytical formula through harmonic coefficient matching, and calculating the surface wind pressure aerodynamic derivative at each measuring point; analyzing the aerodynamic derivative at each measuring point, evaluating the contribution of each surface region to the overall aerodynamic derivative, and identifying key aerodynamic regions that excite or suppress self-excited vibrations. This invention degrades traditional macroscopic aerodynamic derivatives to spatial micro-elements, establishing a spatial mapping analytical closed chain between local wind pressure and aerodynamic derivatives, realizing spatial visualization and quantitative traceability of aerodynamic stability contributions, and providing a direct basis for targeted optimization of wind resistance for complex cross-sectional structures.

The application relates to a building shape optimization method, which comprises the following steps: in a first case, determining an optimized first value of a first parameter of a target building according to the value of a first index of the target building under a first candidate value of the first parameter, the first index comprising the following first index items: a roof average wind pressure coefficient, an average wind pressure coefficient difference between a windward surface and a leeward surface, and building heating energy consumption; and in a second case, determining an optimized second value of a second parameter of the target building according to the value of a second index of the target building under a second candidate value of the second parameter, the second index comprising the following second index items: a proportion of detection points with a surface wind speed less than a non-snow accumulation wind speed, a proportion of detection points with a roof wind speed less than the non-snow accumulation wind speed, and a proportion of detection points with a ground wind speed less than the non-snow accumulation wind speed.

The application discloses a kind of marine robot cluster tracking optimization control methods for non-cooperative target, first for the marine robot system working in water surface environment, respectively establish linearization marine robot cluster dynamics model and the dynamics model of non-cooperative target;Then construct state tracking error system;Design finite time sliding mode control protocol, simultaneously solve the equivalent state tracking error system that moves on sliding surface;Next define the performance index function of marine robot cluster system, design distributed state feedback nominal optimization control protocol, ensure that performance index function meets global Nash equilibrium;Finally, using Hurwitz stability theory proves that distributed state feedback nominal optimization control protocol can ensure the asymptotic stability of equivalent state tracking error system.The method of the application can realize the optimization tracking control of marine robot cluster system to non-cooperative target with uncertain control strategy under the interference of complex marine environment water surface wind wave.

The invention relates to a local surface layer wind field fusion and nowcasting method, and belongs to the technical field of meteorological wind field fusion and forecasting. According to the method, the wind shear index calculated by a 90-meter anemometer tower is utilized to fill up a wind profile at the height of 90 meters above a surrounding automatic station, Barnes step-by-step corrected wind field fusion is carried out in combination with WRF-LES large eddy simulation, a convolutional neural network model is established between a large eddy simulation data set and a fused wind field data set, model parameters are obtained, and the wind field fusion is realized. And the parameters are used in WRF-LES real-time forecast to obtain proximity correction forecast of the near-earth wind field. According to the method, the local anemometer tower and encrypted automatic station data are fully applied, WRF-LES modeling is integrated, the method can be used for forecasting a local wind field, and the corresponding algorithm and process are suitable for wind field forecasting of wind power, low-altitude economy and the like.

The invention relates to the technical field of airflow optimization, in particular to an airflow optimization method of a shell drying system. The method comprises the following steps that environmental parameters in a shell drying cabin are obtained through experimental testing, and data analysis is conducted on the environmental parameters through standard deviation and variable coefficients; establishing a CFD simulation model based on a Navier-Stokes equation, and setting and initializing the CFD simulation model to identify steady-state distribution data of wind speed, temperature and humidity on the surface of the shell; based on a CFD simulation model, a local airflow insufficient area is determined, and the number of fans and the air supply angle are optimized; a brand-new dry environment wind field vector airflow organization and adjustment device, a centralized rotating wheel dehumidification system and an automatic air volume control strategy are introduced; and the optimized shell drying system is subjected to experimental verification again. According to the airflow optimization method of the shell drying system, the wind field vector airflow organization and adjustment device and the centralized rotating wheel dehumidification system are combined with an automatic air volume control strategy, and accurate control over airflow and humidity is achieved.

The invention belongs to the technical field of wind load experiment testing, and particularly discloses a modularized equivalent wind load experiment testing system which is characterized by comprising a wind load simulation module, a data acquisition and processing module, a model fixing and supporting module, a control system module and a function extension module. The wind load simulation module is used for adjusting wind load strength and wind speed and realizing 0-360-degree wind direction adjustment; the data acquisition and processing module is used for monitoring physical quantities such as displacement and strain of the experimental model and wind speed, wind pressure and the like of a wind field, and processing to generate an experimental result and an analysis report; the model fixing and supporting module is used for fixing the experimental model and adjusting the levelness and perpendicularity of the experimental model; the control system module is used for setting experiment parameters, controlling experiment start and stop and process monitoring and realizing data transmission between modules; the function extension module is used for measuring wind pressure distribution on the surface of the model, displaying the flow state of a wind field and monitoring vibration response of the model; all the modules are connected and transmit data through standard interfaces.

The present invention relates to the technical field of bridge construction, and specifically refers to a real-time measurement method and system for the posture of prefabricated piers in water. A ruler and a measuring target are arranged on the prefabricated pier, and a reference target and an industrial camera are installed on the steel casing around the installation position of the prefabricated pier; during the hoisting process of the prefabricated pier, the scale of the corresponding ruler is obtained by the industrial camera, and the verticality of the current prefabricated pier and the elevation of the top surface of the prefabricated pier are obtained based on the three-dimensional coordinates of the ruler scale and the industrial camera; the image information along the plane of the corresponding reference targets and measuring targets in the same group is obtained by the industrial camera, and the horizontal coordinates of the prefabricated pier are determined based on the plane image information and the coordinates of the reference targets. The real-time measurement method for the posture of prefabricated piers in water of the present application can be completely unaffected by the interference of wind and waves on the water surface, and completely relies on machine vision to perform measurements during the lowering and installation of the prefabricated pier. The overall measurement accuracy is extremely high, and the measurement method is very simple.

The invention provides a bluff body steel box girder temperature field determination method based on convective heat transfer coefficient correction. The method comprises the following steps: S1, analyzing section wind field characteristics of the bluff body steel box girder based on CFD software; s2, constructing an influence model of the aspect ratio uniform section parameter change on the steel box girder wind field, performing regression analysis on a calculation result, and establishing a calculation formula and a value suggestion quantity of each surface wind speed correction coefficient of the bluff body steel box girder under the condition of different aspect ratios; s3, respectively establishing steel box girder thermal analysis models before and after convective heat transfer coefficient correction; s4, the accuracy of the convective heat transfer coefficient correction method in bluff body steel box girder temperature field simulation is checked through bridge field actual measurement temperature data; s5, analyzing a bluff body steel box girder temperature field change rule under the condition of different aspect ratios, and finally establishing a bluff body steel box girder temperature field determination method suitable for different section parameters; the accuracy and reliability of the bridge temperature field analysis result can be improved.

The invention discloses a photovoltaic module temperature distribution prediction method and device, a terminal and a medium, and the method comprises the steps: carrying out the grid processing of a to-be-predicted photovoltaic module, and endowing each grid with an initial preset temperature; acquiring surface wind speed distribution of the photovoltaic module through wind speed field simulation based on the environment wind speed; respectively calculating each heat transfer coefficient of each grid by combining the air humidity, the temperature, the surface wind speed and the preset temperature so as to construct a front and back surface heat loss equation # imgabs0 # of each grid; respectively constructing an absorption heat equation # imgabs1 # of each grid; respectively constructing a side heat transfer equation # imgabs2 # of each grid; and establishing a heat balance equation to solve the temperature of each grid, taking the current temperature solving result of each grid as the corresponding preset temperature, carrying out iterative calculation until a preset termination condition is met, and outputting the finally solved temperature of each grid. According to the invention, the spatial resolution of temperature field prediction is improved, and higher-precision photovoltaic module temperature distribution prediction is realized.

The application belongs to the technical field of bridge wind resistance engineering, and discloses a numerical simulation method of bridge structure wind load under the action of tornado based on CFD, which comprises the following steps: referring to the geometric configuration of a tornado laboratory simulation device, a CFD calculation domain model of a three-dimensional tornado generator is established, a speed inlet boundary condition is constructed by using Doppler radar observation data of a real tornado, and a three-dimensional tornado wind field is obtained by numerical solution; a vortex ratio is controlled by an inflow angle, and a tornado intensity is controlled by an inlet wind speed. The numerical simulation method of bridge structure wind load under the action of tornado based on CFD aims to solve the problem that in the existing numerical simulation method of tornado wind field based on CFD, an idealized analytical wind field is used as a boundary condition to drive the generation of a wind field, and there is a lack of quantitative mapping relationship between control parameters and wind field structure characteristic quantities, so that the bridge structure surface wind pressure coefficient cannot be systematically obtained under the working conditions of multiple radial positions and wind direction angles.

The present invention discloses a method for calculating a high-resolution surface wind erosion index, which comprises the following steps: step 1, selecting high-resolution remote sensing data; step 2, preprocessing data; step 3, removing snow; step 4, calculating the normalized vegetation index; step 5, calculating the surface wind erosion intensity; step 6, post-processing data. The present invention can perform refined display and seasonal update of the surface wind erosion index in river valleys and other areas, and has certain positive significance in the numerical simulation and forecasting of regional high-resolution sandstorm weather.

This invention discloses a method for predicting the spatial distribution of algal blooms in lakes based on near-surface wind vectors and a Bi-GRU-Attention model. The invention employs Empirical Orthogonal Function (EOF) analysis to extract the dominant mode of algal bloom spatial distribution and time coefficients that represent the temporal variation characteristics of algal bloom spatial patterns. Then, a bidirectional gated cyclic unit model based on an attention mechanism is constructed to extract key dynamic features from the wind vector time series and identify wind periods that significantly contribute to the formation of algal bloom spatial distribution patterns. Finally, the time coefficients of the dominant mode of algal bloom spatial distribution are predicted using the wind vector time series state, and the spatial distribution of algal blooms is reconstructed by combining the corresponding spatial modes. This invention provides a new approach for the study of wind-driven algal bloom spatial distribution.

The present application relates to a kind of tidal flat complex underlying surface wind turbine SAR identification method, comprising: generating annual SAR time series composite image;The mean value of each pixel in the preset backscattering coefficient interval of the composite image is calculated, and high backscattering value image is generated;High backscattering value image is binarized and segmented;The morphological processing is carried out to the binarized image to enhance high backscattering target;Multi-scale screening mechanism based on geometric features is established;Difference spatial resolution processing is implemented, and wind turbine point vector data is output.The beneficial effects of the present application are: the present application effectively improves the identification precision of tidal flat and open sea wind turbine, and provides reliable technical support for fine evaluation and management of offshore wind power resources.