624 results about "Wind measurement" patented technology

The invention relates to the technical field of wind power generation, and discloses a wind power plant energy management method based on laser radar wind measurement, comprising the following steps: S1, deploying laser radar equipment, and collecting real-time data of wind speed, wind direction and turbulence intensity in a wind power plant; s2, constructing a three-dimensional dynamic model of a wind field, and modeling wind speed, wind direction and turbulence distribution in combination with laser radar data and historical meteorological data; s3, performing short-term prediction on the future wind speed by using the deep learning model, and outputting minute-level to hour-level wind energy prediction data; s4, optimizing a dynamic scheduling strategy of the wind turbine generator based on the prediction data; and S5, docking an energy storage system, optimizing charging and discharging behaviors of energy storage equipment, and realizing smooth power output. According to the invention, by fusing the laser radar wind measurement data, the deep learning prediction model and the intelligent optimization algorithm, high-precision wind condition monitoring, dynamic scheduling optimization and power output stability improvement of the wind power plant are realized.

The invention relates to the technical field of new energy power generation prediction, in particular to a new energy power prediction method fusing typhoon meteorological information and a micrometeorological prediction result, which comprises the following steps: collecting multi-source observations such as a satellite scatterometer, a radar wind profile and laser wind measurement, and unifying coordinates; constructing a mesoscale wind field by adopting four-dimensional variational assimilation, inferring a micrometeorological field by utilizing a spectrum embedding diffusion network, and generating a multi-scale meteorological field by frequency domain phase consistency fusion; probabilistic wind speed is sampled in the countercurrent model meeting the condition of mass and momentum conservation, an energy conservation graph neural network is input, the wake effect is coupled, and a unit power quantile value is obtained; the power probability is sent to a risk weighting model, the weight is adjusted in real time according to the peak load, the reserve capacity and the climbing rate risk, a dispatching power curve and uncertainty are output, and grid-connected power errors are used for periodically updating the weight and the parameters of the last layer of the reversible model. According to the invention, the safety acceptance margin of the power grid to new energy is obviously improved.

The invention relates to the technical field of wind power generation, and discloses a cross-scale wind power plant wind resource evaluation method based on a numerical mode, comprising the following steps: step 1, acquiring multi-source observation data of a target area; step 2, screening a WRF optimal configuration scheme adaptive to the regional terrain; step 3, through a WRF power downscaling method, generating annual scale wind resource data as initial wind resource data; 4, performing partition correction on the initial wind resource data to obtain wind measurement data; step 5, constructing a WRF-WFP model coupling the WRF mode and the wind power plant parameterized model; step 6, optimizing WRF lower boundary conditions; 7, simulating the atmospheric flow of the target area, and quantifying the wake flow evolution characteristics of the wind power plant; 8, constructing a wake flow analysis model; and step 9, formulating a collaborative productivity plan of the wind power plant group. The power generation capacity of the wind power plant to be developed can be accurately predicted, and a reliable basis is provided for scientific decision-making of resource distribution development and planning of the million-kilowatt wind power plant.

The invention relates to the technical field of wind power plant wake flow testing, and discloses a 3D scanning type laser radar planning method suitable for wind power plant wake flow testing, and the method comprises the steps: determining a wind power plant wake flow wind measurement region according to a wind measurement demand; determining a mainstream wind direction and a wind speed interval of the wind power plant wake flow wind measurement area based on the wind power plant wind resource data, and obtaining unit coordinates and unit parameters of wind turbine units in the wind power plant wake flow wind measurement area; according to the mainstream wind direction, the wind speed interval, the unit coordinates and the unit parameters, performing simulation calculation on the wake flow field of the wind turbine generator in the wake flow wind measurement area of the wind power plant to generate a wake flow area cloud picture; according to the method, the arrangement position of the 3D scanning type laser radar is determined based on the wake flow area cloud picture and the actual landform of the site, the situation that the arrangement position of the 3D scanning type laser radar is repeatedly adjusted for multiple times due to arrangement errors possibly occurring during arrangement according to experience can be avoided, and the wake flow testing efficiency is improved.

The invention discloses a radar detection blind area wind field fine reconstruction method based on anemograph collaborative networking, and the method comprises the specific steps: firstly, separating wind speed measurement deviation caused by vibration displacement in real time, eliminating vibration interference, carrying out the automatic diagnosis and restoration of data based on machine learning, and optimizing the integrity of wind speed data and the measurement continuity; secondly, an ultrasonic anemograph array optimization arrangement method oriented to global wind field sensing is established, time-space consistency calibration of multi-sensor data is achieved, and the precision and reliability of wind speed measurement are improved; and finally, carrying out data-physical fusion bridge flow field high-resolution intelligent reconstruction, and improving the data integrity of a complex flow field area. The reconstruction method effectively cooperates with the wind measurement laser radar and the anemograph, the advantages of high-frequency single-point measurement and wide-area space scanning of the wind measurement laser radar and the anemograph can be exerted, high-precision reconstruction of the global flow field of the bridge is expected to be achieved, and reliable support is provided for guaranteeing wind resistance safety of a large-span bridge.

The airport available runway monitoring and early warning system and method based on multi-source data fusion are high in real-time performance, good in forecasting effect and large in monitoring range. The system comprises a laser wind finding radar (1), a CFD numerical simulation module (2), a mesoscale weather forecast module (3), a machine learning model (4) and a system server (5). The method comprises the following steps that: a system server performs data assimilation by combining real-time wind shear detection data measured by a laser wind measurement radar and forecast data of a current time point output by a mesoscale weather forecast module, processes the assimilated data by applying a CFD numerical simulation module, and calculates the real-time wind shear detection data by combining terrain and building parameters near an airport; according to the method, real-time sub-meter gridding three-dimensional wind field data is generated, and a sub-meter three-dimensional wind field structure is reconstructed, so that future wind shear of an airport is forecast and early warned, and then available runway prediction is carried out. The method is applied to the technical field of wind field prediction and judgment.

The invention provides a three-dimensional wind field inversion method of a coherent wind lidar, and relates to the technical field of lidar wind measurement, and the method comprises the steps: building a mathematical model of a coherent wind lidar receiving echo signal, and determining an optimal target detection distance; under the optimal target detection distance, emitting a modulated laser detection signal to a target wind field, and processing echo signals which are received by a laser radar and are mixed at different frequencies to obtain an echo signal light field distribution condition; calculating the radial velocity of the wind in the wind field of the target based on the light field distribution condition of the echo signal; the elevation angle of the laser radar is fixed, the four orientations are scanned, radial wind speeds corresponding to the four orientations are obtained, the atmospheric three-dimensional wind field is inverted, and real-time atmospheric wind field three-dimensional detection with high temporal-spatial resolution and high wind measurement precision can be realized.

The invention discloses a multi-source data fusion wind power plant micro-siting dynamic evaluation method, relates to the technical field of wind power plant siting, and solves the problem that a mainstream method still depends on single anemometer tower data or static GIS analysis during wind power plant siting in the prior art. The method comprises the following steps: firstly, acquiring wind measurement data of multiple sources, unifying the wind measurement data of different sampling frequencies into a set time window, and realizing spatial scale alignment through an interpolation method; then obtaining a wind energy score according to the annual average wind speed and the main wind direction frequency, obtaining a suitability score according to the distance to the residential area or the main road, obtaining an environmental impact factor according to the noise and the ecological protection area, and constructing a target function based on the wind energy score, the suitability score and the environmental impact factor; and finally, combining a genetic algorithm and a real-time optimization model of a wake flow interference model, and dynamically adjusting the evaluation tendency according to the evaluation score of the fan layout inversion site, so that the evaluation result is more comprehensive, scientific and reasonable.

The invention provides a method, device and equipment for determining a buoyancy generation item of atmospheric turbulence kinetic energy and a storage medium, and the method comprises the steps: obtaining the wind speed at a plurality of moments through a wind measurement radar within a specified time length, and obtaining the buoyancy generation item of the atmospheric turbulence kinetic energy according to the wind speed at the plurality of moments; the dissipation rate and pulsation components corresponding to the wind speed in different coordinate axis directions are determined, a turbulence trend item, a shear generation item and a turbulence transmission item are determined according to the pulsation components corresponding to the different coordinate axis directions, and the wind speed is acquired by adopting a wind measurement radar, so that the spatial resolution and the data continuity of data are improved, and the detection range is expanded. And more accurate dissipation rate, turbulence trend term, shear generation term and turbulence transmission term are determined, so that the buoyancy generation term of the atmospheric turbulence kinetic energy can be more accurately deduced according to the dissipation rate, turbulence trend term, shear generation term and turbulence transmission term, and the accuracy of the buoyancy generation term is ensured.

The invention discloses a wind power plant unit load reduction optimization method and system based on cabin type laser radar real-time wind measurement, and relates to the technical field of wind power generation. Constructing a load estimation model; performing real-time detection on a blade root bending moment predicted value sequence and a tower bottom vibration acceleration predicted value sequence, constructing a multi-objective optimization function including blade root bending moment, tower bottom vibration acceleration and power generation power, and setting a dynamic weight coefficient of the multi-objective optimization function according to three-dimensional wind field prediction sequence data; obtaining an optimal control variable through a multi-objective genetic algorithm based on the multi-objective optimization function; and according to the optimal control variable and vertical wind shearing in the three-dimensional area, differential adjustment is conducted on the pitch angle of each blade, and a personalized variable pitch angle sequence of each blade is obtained. According to the method, by establishing the optimization objective function fusing the load and the power, multi-variable collaborative optimization is achieved, and the safety and the economical efficiency of wind power plant unit operation are remarkably improved.

The invention discloses a multi-sensor fusion meteorological data comprehensive analysis platform, and relates to the technical field of meteorological monitoring. The platform comprises a three-level sensing layer, a dynamic collaborative architecture and a meteorological data analysis layer. The third-level sensing layer works cooperatively through a ground total-factor meteorological station, an unmanned aerial vehicle cluster and a FY-4 satellite and is integrated with a bimodal ultrasonic wind measurement sensor, a miniature meteorological sounding cabin and an HRIT / LRIT data receiving module, so that multi-dimensional data acquisition from the ground to a 5km high altitude is realized; the dynamic collaborative architecture is based on an edge computing node and a cloud fusion module, adopts a lightweight LSTM (Long Short Term Memory) model to detect abnormity in real time, and dynamically optimizes the weight of multi-source data through Kalman filtering; and the meteorological data analysis layer is combined with the element coincidence index, the layering stability index and the risk assessment model to generate a graded early warning signal. According to the scheme, the problems of vertical data fault, low multi-source data fusion efficiency, early warning lag and the like in the traditional technology are solved, and the severe convective weather prediction precision is remarkably improved.

The invention relates to a wind shear wind speed extrapolation calculation method based on a neutral equivalent wind speed. The method comprises the following steps: (1) determining input wind speed measurement data; (2) classifying the atmospheric stability, and converting the wind speed at each moment into an equivalent wind speed in a neutral state; (3) performing extrapolation wind speed calculation according to the neutral equivalent wind speed; and (4) outputting an extrapolated wind speed result, and calculating wind shear. According to the method, the wind speed extrapolation error is effectively reduced, the wind speed extrapolation calculation is more accurate, and particularly, the method has outstanding performance in complex terrains or marine environments.

The invention discloses a radar wind measurement method and system based on terrain matching, relates to the technical field of radar control, and solves the problem of insufficient radar wind measurement precision under complex terrain conditions in the prior art. The method comprises the following steps: firstly, collecting time-space synchronous multi-source data and preprocessing the multi-source data, wherein the multi-source data at least comprises data of a laser radar, an unmanned aerial vehicle and a sensor network; then constructing a three-dimensional vortex adaptive function and combining smooth partitioning, performing grid division and setting an overlapping buffer region with a certain width between different regions; and finally, calculating a terrain complexity index, and when the terrain complexity index obtained through real-time calculation exceeds a threshold value, adjusting parameters of the radar. The radar wind measurement data error is effectively compensated, the accuracy of the wind measurement data and the generalization ability of the model are improved, the pertinence and efficiency of radar scanning are improved, more accurate wind field information is obtained, and compared with a traditional fixed scanning mode, the wind measurement precision is obviously improved.

The invention relates to the technical field of three-dimensional real-time wind speed measurement, and discloses a large-span roof three-dimensional ultrasonic anemometer and a measurement method thereof, and the method comprises the steps: building a three-dimensional coordinate system through laser ranging, and analyzing and compensating installation errors; an initial calibration coefficient is generated through a self-inspection and optimization algorithm, and the initial calibration coefficient is compared and analyzed with a standard instrument for initial calibration; ultrasonic pulse emission is controlled, full-path scanning and redundancy measurement of all axes are completed, signal quality is improved through multi-modal signal processing detection, and abnormal values are eliminated through weighted median values; the sound velocity is corrected based on real-time temperature data, the influence of humidity and air pressure on the sound velocity is adjusted through a nonlinear regression model, and a Reynolds stress correction term is introduced to compensate for sound wave path bending in an eddy current field; a three-dimensional turbulence intensity distribution diagram is constructed by fusing ultrasonic and LiDAR data, meteorological parameters are calculated, an extreme weather event is early warned by using a machine learning model, a visual three-dimensional wind speed field is provided through a cloud platform, and a potential risk area is identified.

The invention provides a measurement method of a shipborne three-dimensional scanning wind measurement laser radar, and the method comprises the steps: obtaining the attitude information of a ship through a combined inertial navigation system, and the attitude information comprises a heading angle, a pitching angle and a rolling angle; according to the attitude information and a coordinate transformation model between a preset radar coordinate system and a geographic coordinate system, determining an azimuth angle and a pitch angle of a laser beam of the shipborne three-dimensional scanning wind measurement laser radar in the geographic coordinate system; according to the azimuth angle and the pitch angle, controlling the shipborne three-dimensional scanning wind measurement laser radar to emit a laser beam, and receiving a reflection echo signal; and acquiring three-dimensional velocity component information of the wind field according to the reflection echo signal to obtain a three-dimensional wind field.

The invention discloses a laser radar-assisted wind power generation wind shear modeling method, and relates to the technical field of wind shear modeling, and the method comprises the steps: collecting the wind speed measurement data of a laser radar at a plurality of heights in a target fan region, and constructing a measurement volume integral operator matrix; constructing a unit induction field correction model based on large eddy simulation in combination with a gradient boosting tree; coupling the measurement volume integral operator with the unit induction field correction model, and obtaining a high-precision wind speed vertical section and a corresponding wind shear parameter through inversion; on the basis of the high-precision wind speed vertical section and the corresponding wind shear parameters, physical constraints are fused, a wind shear model is generated, and uncertainty evaluation is carried out; according to the wind shear modeling method, the problems that the measurement error of the laser radar is difficult to correct, the wind shear modeling lacks the physical constraint and the result credibility cannot be quantified are solved by constructing the volume measurement integral operator and the unit induction field correction model for coupling inversion and fusing the physical constraint and the Bayesian uncertainty evaluation method.

The invention discloses a Doppler differential interferometer imaging position drift monitoring method, which solves the problem of inaccurate wind speed measurement result caused by drift of an interferometer image surface due to temperature change and the like. According to the method, periodic grooves are etched in the grating diffraction surface of the interferometer, namely, groove patterns serve as scales, the drift distance of the interferometer to be monitored is calculated, Doppler differential interferometer image surface drift caused by temperature changes can be effectively monitored, then the drift monitoring result is used for correcting the imaging position drift of the interferometer, and the drift distance of the interferometer to be monitored is calculated. Therefore, the accuracy of Doppler phase measurement is improved, the wind measurement accuracy of the interferometer is improved, and sub-pixel monitoring of the imaging position drift of the interferometer is realized.

The invention discloses an acousto-optic radar wind measurement data correction system based on adaptive noise suppression, and relates to the technical field of data correction. Environmental parameters and acousto-optic radar system parameters are combined through a dynamic adjustment module to dynamically adjust a signal-to-noise ratio threshold; the echo signal quality analysis module inputs the frequency spectrum characteristic data and the dynamically adjusted signal-to-noise ratio threshold value into an echo quality model and judges whether the current echo signal is valid or not, if yes, interpolation is carried out by adopting a spatial smooth interpolation method, if yes, the dominant frequency of the echo signal is extracted, Doppler frequency shift is calculated, and according to the detection angle and the laying direction, the Doppler frequency shift is calculated; and calculating a radial wind speed, inverting a three-dimensional wind speed vector and carrying out physical consistency correction. According to the correction system, the dynamic adjustment module is introduced, real-time environment parameters and system operation parameters are combined, and a signal-to-noise ratio threshold value required by judgment is dynamically adjusted, so that a judgment basis can be intelligently self-adapted along with a measurement environment, and the accuracy and robustness of echo signal quality judgment are remarkably improved.

The invention discloses a yaw wind error compensation method and system based on wind measurement data, and relates to the technical field of wind power generation equipment control, and the method comprises the steps: setting a wind measurement point position, and collecting an original wind field data set; calculating an incoming flow and a cabin wind direction angle according to the original wind field data set; performing deviation calculation to obtain a yaw wind error angle; triggering a dual-channel compensation module, accumulating errors, constructing an error queue, and performing batch compensation to obtain a compensation result; yawing control parameters are called, the cabin attitude is analyzed according to the compensation result, the yawing control parameters are updated, and self-adaptive compensation of yawing to the wind error is achieved. The technical problems that in the operation process of the wind driven generator, due to wake flow, terrain, turbulent flow and other environmental factors and equipment loss, a traditional yaw system cannot accurately detect the wind direction and compensate the wind alignment error, the power generation efficiency is low, and the potential safety hazard of equipment is large are solved, and the purposes of accurately improving the wind alignment precision of a wind wheel and improving the power generation efficiency are achieved. The power generation efficiency is obviously improved; and the equipment operation safety is enhanced.

The invention relates to a floating platform-based wind measurement laser radar wind field inversion optimization method, system and device, and a medium, and the method comprises the steps: carrying out the PPI scanning through a laser radar, and obtaining the radial wind speed before correction; correcting the radial velocity component caused by the floating platform in the radial wind speed before correction for the first time; acquiring the real wind speed and wind direction at the preset position by using the mobile wind meter, and calculating the first radial wind speed corresponding to the azimuth angle of the mobile wind meter before laser radar correction according to the real wind speed and the real wind direction; performing RHI scanning at a preset position, and processing according to an RHI scanning result to obtain a second radial wind speed; based on the first radial wind speed and the second radial wind speed, carrying out second correction on the radial wind speed after the first correction; and based on the second correction result, performing inversion optimization on the sea surface wind field by adopting a VAP algorithm to obtain wind speed and wind direction data. The method can be widely applied to the technical field of remote sensing marine environment monitoring.

The invention provides a fire detection method, device and system for a wind generating set. The method comprises the following steps: acquiring each smoke concentration value and each wind speed measurement value in a cabin of the wind generating set by utilizing acquisition equipment; calculating a smoke average value and a smoke change rate when the acquisition equipment is determined to meet a self-inspection requirement according to the smoke concentration value and the wind speed measurement value; if the smoke average value is not smaller than an average value threshold value and the smoke change rate is not smaller than a change rate threshold value, generating fire alarm information; calculating a plurality of wind speed positioning compensation values according to each wind speed measurement value; according to all the smoke concentration values, a plurality of maximum peak values in all the smoke concentration values and all the wind speed positioning compensation values, fire positioning information is obtained through calculation; and executing preset fire-fighting operation according to the fire alarm information and the fire positioning information. The problem of fire positioning in a complex environment in the wind generating set is solved, fixed-point fire fighting is facilitated, fire detection accuracy and fire fighting efficiency are improved, and operation safety of the wind generating set is guaranteed.

The invention discloses an intermediate frequency self-calibration method and device for a wind measurement laser radar and a storage medium, and the method comprises the following steps: S1, a data collection system of a pulse laser wind measurement radar collects atmosphere return light signals, and forms a plurality of pulse signal sequences xi = {a0, a1,... am}, and the atmosphere return light signals comprise a signal sampling rate of mHz and a pulse repetition frequency of n; s2, according to the return light signals, a blind area segment in a pulse signal sequence xi = {a0, a1,... am} is searched, and am represents m return light signal data; compared with the prior art, the method uses the return light signal of the pulse laser radar to find the return light signal of the blind area section of the radar; the signals in the blind area are used for power spectrum estimation to obtain the intermediate frequency of the laser radar, so that the function of intermediate frequency self-calibration is achieved, and the fixed intermediate frequency after one-time calibration before delivery is avoided.

The invention relates to the technical field of airborne wind power measurement, and discloses an airborne wind measurement laser radar method and system. The method comprises the following steps: generating a scanning time sequence identifier and a path correction mark structure through scanning beat synchronization and stray light shielding processing; executing time-frequency demodulation and quality gating based on the back scattering signal to generate an observation wind speed initial value sequence; performing time alignment and motion compensation in combination with inertial navigation data, and generating a wind speed vector grid fragment through spatial interpolation and scanning geometric mapping; and finally, generating a configuration updating instruction structure through coordinate alignment and grid splicing. According to the invention, the precision and the anti-interference capability of wind field measurement in an airborne environment are effectively improved, and the data reliability and the system stability under a complex meteorological condition are remarkably enhanced through multi-source data fusion and a self-adaptive compensation mechanism.

The embodiment of the invention discloses a flow field and temperature field prediction method and device of an autoclave, equipment and a medium. The prediction method comprises the following steps: performing wind speed measurement on at least two transverse sections of the autoclave through a wind speed detection device arranged in the autoclave to obtain a wind speed measurement result of each transverse section; determining a wind speed distribution function of the autoclave according to the wind speed measurement result of the first cross section; according to the model simulation file of the autoclave and the wind speed distribution function, under preset flow field parameters of the autoclave, performing steady-state calculation on the autoclave to obtain a flow field distribution result of the autoclave; comparing the wind speed measurement result of the second cross section with the flow field distribution result; and when the wind speed comparison result meets the flow field prediction precision, taking the preset flow field parameter and the wind speed distribution function as the flow field prediction result of the autoclave. Wind speed distribution is detected through the wind speed detection device, so that preset flow field parameters are adjusted, and accurate simulation of wind speed distribution in the autoclave can be realized.

The invention provides a wind turbine generator clearance risk detection method and device based on wake flow influence, and relates to the technical field of wind turbine generator wake flow simulation, and the method comprises the steps: obtaining the wind measurement data of a target wind power plant, and obtaining the topographic data of the target wind power plant and the position information of each wind turbine generator in the target wind power plant; determining the associated wind turbine generator of each wind turbine generator according to the wind measurement data and the position information of each wind turbine generator, and establishing a simulation model of each wind turbine generator; based on the wind measurement data, the predicted wind speed of each wind turbine generator is determined through a preset speed fitting model, and based on the predicted wind speed, the simulation model of each wind turbine generator is calculated through a preset wake flow model, so that the distribution of the wind speed of each wind turbine generator in the target wind power plant along with the height is obtained. The clearance risk of the wake flow area unit can be effectively monitored, the potential safety hazard of the wind turbine unit is reduced, and the unit performance is improved.

The invention provides a high-precision three-dimensional ultrasonic wind speed measurement method and device, the method is applied to an ultrasonic transducer array, a plurality of transducers in the transducer array are arranged according to a non-orthogonal structure to form a plurality of acoustic measurement paths, and the specific steps are as follows: acquiring ultrasonic signals collected on the plurality of acoustic measurement paths; for each acoustic measurement path, determining a downwind and upwind propagation time difference of ultrasonic waves on the path based on cross-correlation operation and sine wave fitting; and calculating a three-dimensional wind speed vector based on the geometrical relationship of each acoustic measurement path and the corresponding propagation time difference, thereby achieving the technical effects of remarkably improving the anti-interference capability, greatly improving the measurement precision, remarkably improving the calculation speed, optimizing the spatial symmetry, enhancing the environmental adaptability and improving the measurement robustness.

The invention discloses a wind measurement radar attitude angle depolarization estimation and correction method, which comprises the following steps: acquiring original wind field data acquired by a wind measurement radar, including a horizontal wind speed, a horizontal wind direction and a vertical wind speed; performing quality control on the original wind field data, removing invalid samples and screening effective wind speed data; constructing an error model based on the ratio of the vertical wind speed to the horizontal wind speed, and establishing a mapping relation between the ratio and the horizontal wind direction; estimating the attitude deflection angle of the radar by adopting a robust fitting method, including data density weighting and robust fitting processing, so as to improve the estimation stability and the anti-interference capability; based on the estimated attitude deflection angle, performing coordinate transformation on a radar beam direction, correcting a wind field inversion result, and outputting corrected three-dimensional wind speed data; the wind speed measurement precision is improved.

The invention discloses a wind field measurement method, device and equipment and a storage medium, which are applied to the field of wind field measurement, wind field measurement is performed in a target area based on an unmanned aerial vehicle carrying a wind field measurement sensor to obtain first wind field data, and the first wind field data is corrected based on the three-dimensional speed of the unmanned aerial vehicle; performing wind field measurement in the target area based on the vertical wind measurement laser radar to obtain second wind field data, and deleting unmanned aerial vehicle turbulence interference data in the second wind field data; combining the second wind field data with the first wind field data in the non-radar blind area to obtain non-radar blind area wind field data; and determining the first wind field data in the radar blind area as radar blind area wind field data, and determining a target wind field of the target area based on the non-radar blind area wind field data and the radar blind area wind field data. The vertical wind measurement laser radar and the unmanned aerial vehicle system carrying the wind field measurement sensor are used for combined observation, combined analysis and calculation are carried out on data of the vertical wind measurement laser radar and the unmanned aerial vehicle system, and measurement accuracy is improved.

The utility model provides a wind direction and wind speed measuring device and a steel structure tower device. The wind direction and wind speed measuring device comprises a sampling main body, the sampling main body comprises a plurality of air inlets and at least two air channels, the plurality of air inlets are correspondingly communicated with the at least two air channels, openings of the plurality of air inlets face at least two different directions, and the at least two air channels are mutually independent and extend in different directions; the first temperature detection assemblies are arranged in the air ducts and used for collecting temperature information of at least two different positions in the extending direction of the air ducts. The second temperature detection assembly is arranged inside or outside the air duct and used for collecting environment temperature information. The humidity detection assembly is arranged inside or outside the air duct and used for collecting environment humidity information. The controller is used for calculating wind power data according to the temperature information and the humidity information, and the wind power data comprises wind direction and wind speed. The 360-degree omni-directional wind speed and wind direction measuring device is beneficial to measuring 360-degree omni-directional wind speed and wind direction, wide in measuring range, high in reliability, easy to maintain and high in measuring precision.

The invention discloses a device and a method for measuring the velocity field of an autoclave through hot-pressing wind speed. The device comprises a thermosensitive probe, a Wheatstone bridge, a lock-in amplifier, an NI multi-channel data acquisition card and a computer, the thermosensitive probe is used for instantaneously detecting the temperature of a placement point position and generating resistance fluctuation based on sensing temperature change; the Wheatstone bridge is formed by connecting a fixed resistor, a variable resistor and a thermosensitive probe, and is used for forming a series circuit with the lock-in amplifier; the lock-in amplifier is used for supplying power to the Wheatstone bridge and providing co-frequency voltage at the same time, so that resistance data of a thermosensitive probe in the Wheatstone bridge is converted into voltage data to be output; the NI multi-channel data acquisition card is used for acquiring in-phase component voltage signals output by the lock-in amplifier; the computer is used for processing the voltage data to obtain the average speed and the pulsation speed of the measurement point. According to the invention, the problems of limited precision, insufficient sensitivity and poor adaptability to the internal environment of the autoclave in the conventional gas speed measurement method are solved.