159 results about "Wind gust" patented technology

The invention belongs to the technical field of wind power generation, and discloses a wind driven generator multi-drive variable pitch control method based on big data, which comprises the following steps of: constructing a multi-source data acquisition network covering an environment, a unit, a power grid and a driver, and combining preprocessing means such as denoising and standardization and feature extraction methods such as principal component analysis; high-quality input is provided for a short-term prediction model; the model can accurately pre-judge wind conditions and power requirements in the future 10-30 minutes, and is matched with a global optimization algorithm to dynamically adjust a variable pitch strategy, so that the wind driven generator can still keep stable power output under complex working conditions of gust, power grid fluctuation and the like, and particularly has outstanding performance in areas with unstable wind resources. According to mechanical coupling characteristics of the multi-drive variable pitch system, mechanical parameters such as a gear transmission gap and shafting rigidity are fully included in global optimization, and power output, mechanical fatigue and load distribution are balanced through a multi-objective optimization algorithm.

The invention provides a weather forecasting method and system for thunderstorm and gale. The method comprises the following steps: acquiring multi-source weather observation data in a past preset time period; inputting the multi-source meteorological observation data into a pre-trained progressive wind speed forecasting model to extract and fuse multi-scale spatial-temporal characteristics in the multi-source meteorological observation data, and sequentially generating average wind speed forecasting results covering a plurality of future time periods; inputting the average wind speed forecast result into a pre-trained gust mapping model, and performing nonlinear mapping to obtain gust wind speed forecast results corresponding to a plurality of future time periods; and based on the gust speed forecast result, whether thunderstorm and gale risks exist in the future time period is judged. In the mode, the multi-source meteorological observation data is acquired and prediction is performed in combination with the progressive wind speed prediction model and the gust mapping model, so that the accuracy of wind speed and gust prediction can be improved, the thunderstorm and gale risk can be identified in advance, and the disaster early warning and disaster prevention and reduction capabilities are further improved.

The invention provides a gust front wind shear identification method based on artificial intelligence, and the method comprises the steps: carrying out the noise filtering, missing value supplementary measurement, data smoothing, wind shear value calculation and sample screening extraction of collected radial speed data, and obtaining a gust front wind shear sample; performing coordinate system conversion, sample set division and data annotation on the basis of gust and front wind shear samples to obtain an expanded data set; designing and training a Mask R-CNN model architecture to obtain a gust and front wind shear identification model; and inputting the expanded data set into the gust and front wind shear identification model to carry out gust and front wind shear detection. According to the method, dependence on reflectivity factor data can be reduced, an identification model is constructed based on gust front radial speed data, gust front wind shear can be accurately identified, pixel-level segmentation and positioning of a wind shear area can be realized, and identification efficiency is improved.

A system and method for gust load reduction testing of an elastic full-aircraft model in a large low-speed wind tunnel, which belong to the technical field of wind tunnel test apparatuses. The system in the present invention comprises a gust generator and a supporting device that are mounted in a wind tunnel. The supporting device comprises a model sliding guide rail, mounting bases and a trolley, wherein the mounting bases are fixedly mounted at two ends of the model sliding guide rail, the trolley is mounted on the model sliding guide rail, an aircraft model is mounted on the trolley, two parallel sliding rails are mounted on each mounting base, a slider is mounted on each of the two sliding rails, the two sliders are connected by means of a slider connecting base, a lifting ring assembly plate is mounted on the slider connecting base, a plurality of first lifting rings are welded on the bottom face of the lifting ring assembly plate, second lifting rings are welded on the mounting base, springs are hooked between the first lifting rings and the second lifting rings, and a smooth shaft sleeve and a smooth shaft are mounted in the mounting base, one end of the smooth shaft being fixedly mounted in the slider connecting base by means of a bolt, and a limiting block being fixedly mounted at the other end of the smooth shaft. The present invention has a compact structure, involves simple installation and is low cost.

The invention discloses a thunderstorm and gale dynamic extrapolation forecasting method based on multi-task MSTA-ConvLSTM, and relates to the technical field of atmospheric sciences, and the method comprises the steps: constructing a multi-source fusion spatio-temporal data set and a gale process record file, and obtaining a data set; a thunderstorm gale nowcasting model based on an MSTA-ConvLSTM model is constructed; according to the method, a dynamic gating mechanism of lightning data is introduced, whether a lightning probability prediction task is started or not is intelligently judged according to the lightning activity intensity, thunderstorm, gale and co-evolution characteristics of the lightning process are considered, 0-3-hour high-temporal-spatial-resolution nowcasting is achieved, the limitation of traditional single-task forecasting is broken through, a multi-task learning structure is adopted, and the prediction efficiency is improved. The model is guided to recognize the lightning occurrence probability during main task gale prediction, and the overall perception capability of a severe convection system is improved; extreme sample learning is enhanced through a weighted loss function, and output is optimized in combination with a gust coefficient model, so that the forecasting precision and practicability are effectively improved.

The invention provides a non-linear flight control method and system for an anti-wind disturbance unmanned aerial vehicle. The method comprises the following steps: acquiring wind field disturbance characteristics in real time by using a preset meteorological radar; inputting the wind field disturbance characteristics into a preset aerodynamic disturbance prediction model to generate an aerodynamic torque fluctuation prediction value; preset dynamic filtering processing is applied to the amplitude characteristic of the aerodynamic torque fluctuation predicted value so as to generate a control instruction correction signal; and the control instruction correction signal is coupled with a preset nonlinear control law of an unmanned aerial vehicle flight control system, so that unmanned aerial vehicle attitude offset caused by wind disturbance is inhibited in real time, and unmanned aerial vehicle nonlinear flight control is carried out. According to the method, the composite defect of hysteresis and filtering mismatch of traditional linear control in a strong wind sudden change scene is overcome, stable attitude control of the unmanned aerial vehicle in low-altitude wind shear and gust sudden attack is realized, the anti-interference response speed of the unmanned aerial vehicle is remarkably improved, and the out-of-control risk of the unmanned aerial vehicle is greatly reduced.

The invention relates to the technical field of automatic detection and early warning of weather radar gust front, and discloses a weather radar gust front automatic identification system based on deep learning, which comprises a radar data acquisition and preprocessing module used for acquiring radar echo data from weather radar equipment, carrying out format conversion on the data, and sending the converted data to a server; the radar reflectivity is converted from a polar coordinate format to a Cartesian coordinate format, and meanwhile, normalization processing of the radar reflectivity value is carried out; and the feature extraction and region candidate generation module is used for performing feature extraction on the radar image by adopting a deep convolutional neural network and generating a target region candidate box through a region candidate network, and the region candidate network comprises a classification branch and a regression branch. According to the method, rapid and accurate gust front identification is realized through a deep learning target detection and mask segmentation technology, the stability and robustness of detection are remarkably improved, false alarms and missing alarms are effectively reduced through dynamic alarm threshold calculation and trend analysis, and the accuracy and timeliness of alarm are improved.

The invention relates to the field of wind power generation system management, in particular to a wind driven generator and compressed air energy storage energy management system dynamically matched with multiple wind conditions, and dynamic response is achieved by arranging a main storage unit and an auxiliary storage unit. In order to improve efficiency, the auxiliary storage unit is generally in a dormant state, and abnormal wind conditions possibly occurring in a future time period are predicted in a rolling mode by obtaining meteorological prediction data in real time. And once the abnormal wind conditions such as gust, turbulent flow and abnormal wind power decline possibly occur, the auxiliary storage unit is started immediately, and compressed air in the auxiliary storage unit is preheated. When the abnormal wind condition comes, the main storage unit and the auxiliary storage unit with opposite working states can be used for quickly responding to the power fluctuation of the wind driven generator caused by the abnormal wind condition, so that the fluctuation of grid-connected power is avoided.

The invention relates to a crane gust prevention method and equipment, electronic equipment and a computer storage medium, and belongs to the technical field of intelligent control, the crane gust prevention method comprises the following steps: acquiring wind speed information of the position of the crane and working state information of the crane, and constructing a multivariable time sequence vector; performing layer-by-layer feature extraction on the multivariable time sequence vector by adopting a multi-layer convolutional layer to obtain a multi-channel feature vector; the convolution kernel length of each convolution layer in the multiple convolution layers is increased in sequence; performing weighted summation on the multi-channel feature vectors based on a channel attention mechanism to obtain weighted feature vectors, and performing hidden feature extraction on the weighted feature vectors by adopting a long-short-term memory network to obtain hidden feature vectors; and identifying the multi-channel feature vector and the hidden feature vector by adopting a full connection layer to obtain an anti-gust control strategy of the crane. The anti-gust control of the crane can be realized.

The invention relates to the technical field of meteorological disaster monitoring and early warning and numerical forecasting fusion, in particular to an extreme gale weather forecasting method based on a weather forecasting large model, which comprises the following steps: acquiring a numerical weather forecasting three-dimensional physical field, a weather radar, a weather satellite and ground meteorological observation and assimilating the numerical weather forecasting three-dimensional physical field into a consensus field; time advances, sinking potential energy and cold pool diagnosis are obtained through a micro-downburst calculation program, coarse-resolution gust is formed through boundary layer similarity mapping and a hysteresis kernel, and a fine-scale base map is generated under cold pool frontal surface limitation through optimal transmission of advection constraint; the conditional diffusion probability generation model outputs pixel gust distribution and a threshold exceeding probability and extracts a wind damage polygon; radar, satellites, lightning and ground gust are fused, monotonous normalized flow calibration is used, parameters are updated through intersection-to-parallel ratio and shape-preserving coverage inspection and online amplitude limitation, and the credibility of spatial positioning, occurrence time and probability description is improved.

The invention relates to the technical field of path planning, in particular to a multi-unmanned aerial vehicle navigation path planning method and system based on multi-task parameters, and the method comprises the steps: obtaining a three-dimensional mapping space, determining a current wind speed, a current gust vector, a current rainfall capacity and an unmanned aerial vehicle task sequence, obtaining a plurality of historical fault groups, performing negative pheromone marking on the three-dimensional mapping space based on a preset initial pheromone concentration and a plurality of historical fault groups to obtain a negative marking space, and on the basis of the current wind speed, the current gust vector, the current rainfall, a pre-constructed optimized heuristic function, a pre-constructed path coordinate group sequence set and a negative marking space, carrying out optimized ant colony simulation on the jth task coordinate group to obtain an updated coordinate group sequence set, and generating a plurality of optimal paths by utilizing the updated coordinate group sequence set, and completing multi-unmanned aerial vehicle navigation path planning based on the plurality of optimal paths. According to the invention, the accuracy and reliability of path planning can be improved, and the safety when multiple unmanned aerial vehicles execute tasks at the same time is improved.

The invention belongs to the technical field of multi-rotor unmanned aerial vehicle control, and particularly relates to a multi-rotor unmanned aerial vehicle self-adaptive feedforward control method based on a mesoscopic wind field model. Comprising the following steps: firstly, based on a relaxation time model of a lattice Boltzmann method, establishing a mapping relation between a Knudsen number and turbulence intensity and thermal noise intensity of a macroscopic wind field, and realizing parameterized representation of a mesoscopic wind field; then, constructing a mesoscopic wind field model by synthesizing a real-time wind field containing average wind, turbulent flow, gust and thermal noise components; then, calculating the wind resistance according to the predicted wind speed, designing a self-adaptive gain mechanism fusing a real-time tracking error, an error wind direction included angle and a historical error trend, and generating a dynamic feedforward control quantity; and finally, combining the feedforward control quantity with a feedback control quantity based on gravity compensation to form a comprehensive wind resistance control law. Starting from the mesoscale, the disturbance suppression capability and trajectory tracking precision of the unmanned aerial vehicle in complex environments such as strong wind and turbulent flow are enhanced.

The invention relates to the field of unmanned aerial vehicle automatic landing control, and discloses an unmanned aerial vehicle wind-resistant landing control system which comprises an external wind-resistant structure module arranged on the periphery of an unmanned aerial vehicle landing area, and the external wind-resistant structure module adopts a fixed conical cover body design; the external windproof structure module guides external airflow into the landing area, and the size and the height of the top opening of the conical cover body are shown in the specification. A local low-wind-speed environment is constructed through the external windproof structure module, the wind speed of a landing area is effectively reduced, and the wind speed of the landing area is effectively reduced in combination with real-time estimation and accurate control of the environment perception and decision control module on the external wind speed and the tail-section attitude correction capability of the attitude correction and re-landing strategy module. The landing point alignment accuracy of the unmanned aerial vehicle under the condition of crosswind, gust or sudden wind direction change is remarkably improved, and horizontal drifting and landing failure caused by wind disturbance are effectively avoided.

The invention relates to the field of aerodynamics of wind turbine generators, and provides an axial and radial load measuring and calculating method and system based on a 2MW fan. The method comprises the following steps of: performing modeling analysis on key parts of a blade, a hub and a tower drum of a 2MW wind turbine generator, sorting wind speed data collected in a wind field to obtain wind speed distribution, wind speed height, wind speed extreme value and wind speed amplitude indexes related to a time domain, and classifying according to normal wind conditions, extreme gust, extreme coherent gust, extreme wind shear and hurricane; the method comprises the following steps: acquiring hub load data, establishing corresponding wind model data in Bladed, loading the corresponding wind model data into a fan model to obtain hub load data, acquiring spindle bearing load data according to a hub-spindle bearing load transfer coefficient, processing the data, comparing the processed data with theoretical calculation data, and feeding back the data to realize the measurement and calculation task of axial and radial loads of the fan.

The present invention discloses a method for forecasting short-term gusts, including the following steps: determining a forecast evaluation standard time period; obtaining four downscaled short-term gust forecast results based on different factor data and forecast model methods for different gust technical capture angles according to the determined forecast evaluation standard time period; then, performing real-time evaluation on the four short-term gust forecast results based on real-time monitoring data of the forecast evaluation standard time period, determining the weight of each short-term gust forecast result for the next forecast evaluation standard time period in an evaluation weight expression; then, outputting the short-term gust forecast result for the next forecast evaluation standard time period according to the evaluation weight expression and the weight of each short-term gust forecast result; and repeating the forecasting and evaluation steps to obtain the short-term gust forecast results for subsequent forecast evaluation standard time periods. The present invention can achieve more accurate and refined downscaled short-term gust forecasts.

The application belongs to the technical field of aircraft simulation, and particularly relates to a flight simulation method and device under gust load. The method comprises the following steps: S1, performing aircraft 1g level flight trimming to determine the aircraft trimming angle of attack and the aircraft trimming elevator deflection; S2, determining the aerodynamic force of the aircraft; S3, performing dynamic response solution on the aerodynamic force of the aircraft to obtain the aerodynamic angle of attack, the flight speed and the pitch angular velocity, and determining the normal overload of the aircraft after superimposing the flight speed on the wind speed of the vertical gust field; S4, obtaining the elevator deflection calculated by the stability augmentation system, superimposing the elevator deflection at a simulation moment to obtain the actual required elevator deflection; and S5, re-determining the aerodynamic force of the aircraft according to the flight speed, the pitch angular velocity, the aerodynamic angle of attack and the actual required elevator deflection until the simulation is completed. The application considers the role of the stability augmentation system in the determination of the aircraft gust load, and the simulation process is simple and has high precision.

The invention provides a wind driven generator control method and system and a server, and relates to the field of wind driven generator safety control, and the method takes a clearance radar as a safety hard constraint, obviously reduces the tower sweeping risk, can maintain the control reliability under the conditions of rain, fog, clutter and the like, reduces the unnecessary power limitation and shutdown occurrence probability, and improves the safety of the wind driven generator. The misjudgment rate of the wind driven generator in the clearance control process is greatly reduced; in addition, according to the method, wind measurement load shedding and clearance safety can be coupled in the control process of the wind driven generator, feedforward control can be carried out under the working conditions of gust, shearing, yaw errors and the like, and the load of the wind driven generator is reduced.

The present invention relates to the field of path planning technology, and is a multi-task parameter-based multi-UAV navigation path planning method and system, comprising: obtaining a three-dimensional mapping space, determining the current wind speed, current gust vector, current rainfall, and UAV task sequence, obtaining multiple historical fault groups, performing negative pheromone marking on the three-dimensional mapping space based on a preset initial pheromone concentration and the multiple historical fault groups to obtain a negative marking space, performing an optimized ant colony simulation on the j-th task coordinate group based on the current wind speed, current gust vector, current rainfall, a pre-constructed optimization heuristic function, a pre-constructed path coordinate group sequence set, and the negative marking space to obtain an updated coordinate group sequence set, generating multiple optimal paths using the updated coordinate group sequence set, and completing multi-UAV navigation path planning based on the multiple optimal paths. The present invention can improve the accuracy and reliability of path planning and enhance the safety of multiple UAVs when performing tasks simultaneously.

The invention discloses a straight-flow wind tunnel array system, and relates to the technical field of straight-flow wind tunnels. The system comprises a plurality of wind tunnel modules, and each wind tunnel module comprises a controller, a power section, an air inlet section, an expansion section and a stable section. According to the invention, the direct-current wind tunnel is miniaturized, standardized and modularized, the airflow speed (not lower than 40m / s) and the airflow quality of each small direct-current wind tunnel are kept, then the multiple standard modular small direct-current wind tunnels are quickly spliced and constructed into the wind tunnel array, and the rotating speed of each small direct-current wind tunnel can be independently controlled through a control program; the wind tunnel module is arranged in the wind tunnel module to realize natural wind field environments such as gust, tangential wind and abrupt change wind, the contraction section and the active grating are additionally arranged on the wind tunnel module, the contraction section generates stable wind speed close to 70 m / s-80 m / s in a slightly small test area, and the active grating can change the turbulence intensity of airflow in the test area so as to meet the requirements of various turbulence tests. And the wind tunnel array with higher wind speed, variable wind field and variable turbulence can be met.

The application discloses a feature parameter determination method and device, a controller, a medium and a product. The method comprises: acquiring multiple groups of feature parameters; wherein each group of feature parameters comprises: a recurrence period, an extreme coherent gust duration, a wind speed amplitude of an extreme coherent gust in the extreme coherent gust duration within the recurrence period, and a wind direction amplitude of the extreme coherent gust in the extreme coherent gust duration within the recurrence period; based on wind speed information at a wind turbine hub corresponding to each extreme coherent gust duration, obtaining an extreme coherent gust energy factor corresponding to each extreme coherent gust duration; selecting a first target extreme coherent gust energy factor meeting a first preset condition from each extreme coherent gust energy factor; and determining at least one group of feature parameters corresponding to the first target extreme coherent gust energy factor as target feature parameters affecting wind turbine load. The feature parameters that can affect the wind turbine load are accurately selected.

The invention discloses an atmospheric turbulence intensity and gust factor evaluation method, system and device based on a numerical weather forecast mode, and belongs to the technical field of wind resource evaluation. The method aims at solving the problems that the deviation between a WRF simulation result and actually measured data is large, and WRF output variables cannot be directly used for estimating turbulence intensity and gust factors. A machine learning method is combined to carry out multi-meteorological-element correction on wind speed and turbulence energy simulated by WRF, and then a prediction model for estimating turbulence intensity and gust factors according to parameters such as the wind speed and the turbulence energy is established. The turbulence intensity and the gust factor are accurately estimated. The method provides a more accurate and effective way for wind resource assessment, and has important practical significance for development and utilization of wind energy resources.

The invention discloses a ventilation window control method used in a gust environment. According to the method, crosswind, downwind, headwind and conventional states are judged by collecting the pressure of the left air inlet side, the pressure of the right air inlet side and the pressure of the tail end in real time, and side opening adjustment, unit number adjustment and rotating speed control are executed according to the different states. And in the crosswind state, the opening degree range is limited, side adjustment is carried out in the mode that the opening degree range is not smaller than the minimum stepping, and the left-right air volume ratio approaches the target coefficient. In a downwind or upwind state, the number of running machines is adjusted preferentially, and then the rotating speed is adjusted step by step, so that the tail end pressure returns to a tolerance range of a reference value. After an exit condition is met, freezing maintenance is carried out, and conventional ventilation is returned; and when the sensor is abnormal or the environment exceeds the limit, a degradation mode and bottom ventilation are entered, so that the stability and reliability of the system in a complex gust scene are improved.

The application discloses a load reduction control method and system of a wind turbine under extreme gust, comprising: through judging the current wind wheel speed deviation and the wind wheel speed deviation change rate, when exceeding the set threshold, superimposing an additional pitch rate on the pitch instruction; through judging the current cabin acceleration, when the cabin acceleration exceeds the threshold, after a delay period, the wind wheel speed is greater than the rated wind wheel speed and the wind wheel acceleration is greater than the threshold, superimposing the additional pitch rate on the pitch instruction; through judging the yaw error measured by the cabin wind vane, when the yaw error exceeds the yaw error threshold, reducing the set value of the wind wheel speed, i.e. reducing the impeller speed, to reduce the load of the wind turbine. The application can effectively reduce the component load of the wind turbine under extreme gust, and realize the lightweight design of the unit.

The invention discloses a variable-amplitude high-frequency gust generator in the technical field of wind tunnel test equipment, and the generator comprises a supporting frame, an amplitude driving device, an amplitude adjusting device, an amplitude biasing device and an amplitude conversion device, adjusts the amplitude through a worm transmission device, and achieves the amplitude driving through a planet wheel, a gear ring, an inner swing arm and an outer swing arm. The problem that in an existing wind tunnel test, a gust generator cannot achieve high-frequency and variable-amplitude motion is solved, the selection range of gust in the wind tunnel test is expanded, and the gust generator is compact in structure and easy and convenient to operate.

The present invention discloses a control method and system for preventing a wind turbine from overspeeding, which relates to the field of wind power generation technology, including correcting the obtained operating parameters through a compensation model and constructing an extreme gust prediction model; constructing a wind field simulation model based on the output of the extreme gust prediction model and judging whether to make adjustments; adjusting the blade angle of attack and yaw adjustment in the wind field simulation model, and summarizing the adjustment strategy. The present invention greatly improves the accuracy of the data by real-time monitoring of key operating parameters and introducing a compensation model to correct the measured values. Accurate data is the basis for effective analysis and prediction, especially under extreme weather conditions, such as the prediction of extreme gusts. This not only helps to improve the operating efficiency of the wind farm, but also significantly reduces the risks and losses caused by inaccurate data. Through the wind field simulation model and optimization algorithm, the optimal adjustment of the blade angle of attack and yaw angle under extreme gust conditions is achieved.

The invention relates to the technical field of wind power generation monitoring and control, and discloses an intelligent control system for a wind turbine generator, which comprises a high-precision rotary laser scanning module, an intelligent decision module, a self-adaptive scanning control module, a rapid pitch-variable execution mechanism and a system communication interface, the high-precision rotary laser scanning module is used for acquiring blade deformation data in real time and comprises a mechanical rotary scanning device and a sealing and positive pressure system. According to the method, the LSTM time sequence prediction capacity and the Q-learning online optimization capacity are combined, turbulence intensity changes are effectively adapted, accurate and self-adaptive control over complex turbulence working conditions is finally achieved, the overall response time is shortened from instruction generation to paddle action, extreme gust is coped with in time, the tower sweeping risk and the fatigue load are remarkably reduced, and the working efficiency is improved. And through accurate advanced control and rapid compensation, the power generation loss caused by turbulent flow and improper variable pitch is reduced, and the economic benefit is outstanding.

The present invention discloses a cam-driven sinusoidal gust generator, comprising a fixed-axis oscillating blade grid, a cam, a drive device for rotating the cam, and a cam follower in contact with the cam's working surface. The blade grid is used to generate gusts by swinging in wind experiments. The blade grid is fixedly connected to a rocker arm, which is sleeved with a slider. The slider and the cam follower are hingedly connected via a push rod. The rotation of the cam drives the cam follower to move, thereby driving the blade grid to swing via the push rod, slider, and rocker arm, generating sinusoidal gusts in a wind tunnel. The parameters for generating target sinusoidal gusts are obtained by designing the cam profile. The cam converts continuous rotational motion into reciprocating linear motion, enabling complex motion patterns to be achieved. By designing the cam's profile curve, the push rod is moved in anticipation, generating target sinusoidal gusts. Since the aerodynamic force in a low-speed wind tunnel is relatively small, the power required to drive the blades and the force transmitted by the cam are very small, meeting the requirements for long-term reciprocating operation.

In the world of small-scale wind power generation, we have yet to see the sight of mass-produced wind turbines in operation. As one way to create this world, a rotating tower came to mind, and we conceived of a vertical-axis spiral wind turbine with a strong frame that can withstand typhoons and gusts of wind, and blades attached to its spiral axis. [Solution] Inspired by the framework of a rotating tower, a lightweight and sturdy spiral wind turbine is constructed by attaching a cylindrical base 3 to the wind turbine's core 2, assembling a framework of multiple circular horizontal edges 5 and multiple spiral shafts 4 around the cylindrical base to form an elongated ellipsoid shape, attaching strip-shaped blades 10 to the spiral shafts, and using a thin plate-like structure with a wind vent hole 11 in the center of the blade, which can be easily attached to the spiral shaft using the hole in the blade, this vertical-axis spiral wind turbine, which can be manufactured by local industries, captures wind speed and converts it into rotational force, and delivers that energy to a power generation device that requires it via a belt 17 through a driving wheel 7, thus contributing to society.

The invention relates to the technical field of charging piles, in particular to an environment simulation testing device for a charging pile, which comprises a testing box body with an opening in the top, a charging gun is arranged on the inner side of the testing box body, and a spraying assembly for simulating rainwater weather is arranged on the top of one side of the testing box body in the width direction. Mounting blocks are horizontally and symmetrically arranged on the inner wall, provided with the spraying assembly, of the test box body, and a mounting frame is rotationally mounted between the mounting blocks through a rotating shaft and located below the spraying assembly; the two sides of the installation frame are provided with a fan simulating the wind environment and a wind power adjusting assembly adjusting the wind power blown by the fan to simulate the gust environment. By arranging a wind power adjusting assembly composed of a second driving motor, a driving wheel and a wind power adjusting wheel and adopting the design that ventilation grooves of different specifications are alternately arranged, stable wind power generated by the fan is periodically modulated.

The present invention relates to the field of aircraft control technology, and in particular to an airfoil gust mitigation feedforward control method based on circulation control technology, comprising: modifying the trailing edge shape of a NACA0012 airfoil, and arranging jet holes at the trailing edge to form a circulation controlled airfoil; performing a fluid simulation experiment on the circulation controlled airfoil based on the gust speed, and constructing a model in which the airfoil lift coefficient is disturbed by the gust speed; performing a fluid simulation experiment on the circulation controlled airfoil based on the jet momentum coefficient, and constructing a model in which the airfoil lift coefficient is controlled by the jet momentum coefficient; based on the above model, obtaining a gust mitigation feedforward control model in which the input is the vertical gust speed and the output is the jet momentum coefficient; using the gust mitigation feedforward control model to control the jet at the trailing edge, and completing the gust mitigation control of the circulation controlled airfoil; the present invention can improve the ability of an aircraft to resist a gust disturbance environment.