200 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 gust-oriented wind generating set anti-overspeed control method and device and a medium, and belongs to the field of wind generating set control. The method comprises the following steps: acquiring real-time wind speed data and generator speed data; determining whether to enter a gust mode of the wind generating set according to the real-time wind speed data; under the condition that the wind generating set enters the gust mode, the minimum pitch angle of operation of the wind generating set is adjusted to be the minimum pitch angle of operation of the gust mode; calculating generator speed acceleration according to the generator speed data; determining whether to enter an acceleration anti-overspeed control strategy according to the generator rotating speed data and the generator rotating speed acceleration; and under the condition that it is determined that the acceleration anti-overspeed control strategy is entered, the preset variable-pitch rate is superposed on the normal variable-pitch rate. The pitch angle of the wind generating set in operation is increased when the wind generating set enters the gust mode, so that the attack angle margin of the blade can be kept in a safe range, and after the acceleration overspeed prevention control strategy is entered, the preset variable pitch rate is superposed on the normal variable pitch rate.

The invention discloses a physical constraint minute hectometer gust fusion nowcasting method. The method comprises the following steps: establishing a forecasting grid; establishing a radar combined reflectivity data set, a ground instantaneous wind speed data set and a lightning density data set; constructing a model framework for convective gust nowcasting, performing model training, and generating a convective gust optimal nowcasting model in combination with the gust coefficient; a future convective gust nowcasting result is obtained; adopting a multi-grid variation assimilation method to fuse the numerical model gust forecast result and the convective gust nowcasting result to generate a physically constrained fused gust forecast result; and generating a meteorological initial value, and obtaining a corrected fusion forecast wind field by using a wind field rapid diagnosis model. According to the method, a hectometer-level fusion gust nowcasting technology integrating a high-resolution mode and deep learning nowcasting is adopted, the mixed gust forecasting capability is enhanced through mode physical constraint, and the spatial fineness level of a forecasting result is improved.

The invention discloses a device and a method for a low-speed wind tunnel gust or flutter half-mode test, belongs to the field of wind tunnel tests, and aims to solve the problems that an existing gust or flutter half-mode test device cannot realize complete release of heaving and pitching degrees of freedom and is difficult to share the two tests. The device comprises an overall frame, the overall frame is installed in a wind tunnel test section, two sliding rails are vertically arranged on the front end face of the overall frame, two sliding block sets are arranged on the left side and the right side of the rear end face of a tackle, the two sliding block sets are in sliding fit with the two sliding rails in a one-to-one correspondence mode, two spring seats are arranged at the top end of the overall frame, and horizontal shafts are arranged on the spring seats. The inner ring ends of the two clockwork springs are connected with the horizontal shafts of the two spring seats in a one-to-one correspondence manner, the outer ring ends of the two clockwork springs respectively droop to be connected with the pulley, and the model mounting seat is cylindrical and is in running fit with the pulley; the device can be used for a gust load retarding test and a body degree of freedom flutter test, and can be shared by the two tests.

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 wind turbine generator extreme wind condition load reduction optimization method and system, and the method comprises the steps: calculating a normal turbulent wind working condition, an extreme turbulent wind working condition and an extreme gust working condition of a wind turbine generator according to a load calculation standard of the wind turbine generator, and obtaining blade root limit load distribution results under different working conditions; according to a blade root limit load distribution result, a wind speed-blade root limit load threshold table is formulated, namely blade root limit load threshold conditions corresponding to different wind speeds are formulated, so that normal turbulent wind conditions and extreme wind conditions at specific wind speeds are distinguished; the control logic of the wind turbine generator under the extreme wind condition is optimized, that is, when the wind turbine generator is under the extreme wind condition, the actual measurement load value of the blade root is reduced by adding extra variable pitch actions; compared with the prior art, the blade root limit load under the extreme wind condition can be greatly reduced, and the safety of the wind turbine generator is 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.

The invention discloses a gust short-term weather forecast method. The method comprises the following steps: determining a forecast evaluation standard time period; according to the determined forecasting evaluation standard time period, four downscaling gust short-imminent forecasting results are obtained based on different factor data and a forecasting mode method for gust at different technical capture angles; according to the real-time monitoring data of the forecast evaluation standard time period, respectively performing real-time evaluation on the four gust short-term and imminent forecast results, and determining the weight of each gust short-term and imminent forecast result in the next forecast evaluation standard time period in the evaluation weight expression; according to the evaluation weight expression and the weight of each gust short-term and temporary weather forecast result, outputting and obtaining a gust short-term and temporary weather forecast result of the next forecast evaluation standard time period; and repeatedly executing the forecasting and evaluation steps to obtain a gust short-term weather forecasting result of each subsequent forecasting and evaluation standard time period. The downscaling gust short-term weather forecast method can realize more accurate and refined downscaling gust short-term weather forecast.

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 belongs to the technical field of aircraft simulation, and relates to a flight simulation method and device under gust load considering a downwash effect. The method comprises the following steps: S1, carrying out 1g level flight balancing on the aircraft, and determining a balancing attack angle of the aircraft and a balancing elevator skewness of the aircraft; s2, superposing the aerodynamic coefficient increment brought by the downwash angle of attack to the aerodynamic coefficient of the aircraft body, and determining the aerodynamic force of the aircraft; s3, dynamic response solving is conducted on aerodynamic force of the aircraft, the flight speed is obtained, the corrected speed of the aircraft is determined after the flight speed is superposed with the wind speed of the vertical gust field, and the aerodynamic attack angle and the flight Mach number are determined according to the corrected speed; and S4, re-determining the aerodynamic force of the aircraft according to the flight Mach number, the pitch angle speed, the aerodynamic angle of attack, the given wind speed of the vertical gust field and the elevator skewness, and circulating the steps until the simulation is finished. The method is simple in simulation process and high in precision, and meets the requirements of engineering practice.

The invention relates to the technical field of aircraft control, in particular to an airfoil gust retarding feedforward control method based on a circular rector control technology, which comprises the following steps: modifying the shape of the rear edge of an NACA0012 airfoil, and arranging jet holes in the rear edge to form a circular rector control airfoil; performing a fluid simulation experiment on the circular rector control airfoil based on the gust speed, and constructing a model of the airfoil lift coefficient disturbed by the gust speed; performing a fluid simulation experiment on the circular rector control airfoil based on the jet flow momentum coefficient, and constructing a model of which the airfoil lift coefficient is controlled by the jet flow momentum coefficient; based on the model, obtaining a gust slowing-down feedforward control model of which the input quantity is the vertical gust speed and the output quantity is the jet flow momentum coefficient; controlling jet flow of a trailing edge by adopting the gust slowing-down feedforward control model to complete gust slowing-down control of the circular rector control airfoil; the method can improve the ability of the aircraft to resist the gust disturbance environment.

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 provides a variable pitch control method of a wind generating set under a gust condition and the wind generating set, and the variable pitch control method comprises the following steps: determining the wind speed characteristic quantity of wind reaching an impeller of the wind generating set based on wind speed data; based on the wind speed characteristic quantity, a wind speed trend quantity is determined, and the wind speed trend quantity represents the cumulant of the change of the wind speed characteristic quantity within a preset time period before wind reaches the impeller; and in response to the wind speed trend quantity, indicating that the wind generating set is in a gust wind condition, performing variable pitch control on the wind generating set. According to the variable-pitch control method for the wind generating set under the gust wind condition and the wind generating set, the problem that safe operation of the wind generating set cannot be ensured due to the fact that the limit load of the wind generating set under the gust wind condition is increased is solved, the gust wind condition can be recognized, variable-pitch control is conducted on the wind generating set, and the wind generating set is more reliable. And the safety and the stability of the unit are ensured.

The invention 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, carrying out 1g level flight balancing on the aircraft, and determining a balancing attack angle of the aircraft and a balancing elevator skewness of the aircraft; s2, determining the aerodynamic force of the aircraft; s3, dynamic response solving is conducted on aerodynamic force of the aircraft, the aerodynamic attack angle, the flight speed and the pitch angle speed are obtained, and normal overload of the aircraft is determined after the flight speed is superposed with the wind speed of the vertical gust field; s4, acquiring the elevator skewness calculated by the stability augmentation system, and superposing the elevator skewness at the previous simulation moment to obtain the actually required elevator skewness; and S5, re-determining the aerodynamic force of the aircraft according to the flight speed, the pitch angle speed, the aerodynamic angle of attack and the actually required elevator skewness until the simulation is finished. The effect of the stability augmentation system in the determination process of the gust load of the aircraft is considered, the simulation process is simple, and the precision is high.

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 invention discloses an extreme coherent gust determination method and device, a controller, a medium and a product. The method comprises the steps that wind regime parameters of a wind power plant in a preset historical time period and the sampling frequency of the wind regime parameters are acquired; wherein the wind regime parameters comprise a wind speed amplitude and a wind direction amplitude; setting a gust duration based on the sampling frequency; based on the wind speed amplitude and the wind direction amplitude, determining a wind speed and wind direction scale factor in a preset historical time period, a wind speed and wind direction scale parameter corresponding to each gust duration in the preset historical time period, and a gust energy fitting parameter; and under the condition that the wind speed and wind direction scale factor and the wind speed and wind direction scale parameter in the target gust duration meet a preset corresponding relation and the gust energy fitting parameter in the target gust duration meet a preset condition, determining that the wind speed and wind direction in the target gust duration is an extreme coherent gust. Therefore, the extreme coherent gust can be accurately determined.

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.