CN115683544A - Unmanned aerial vehicle rotor disturbance correction method and device - Google Patents

Abstract

The invention relates to a method and a device for correcting rotor wing disturbance of an unmanned aerial vehicle, wherein the method comprises the steps of constructing an unmanned aerial vehicle wind speed measurement simulation numerical model based on an environment flight envelope and unmanned aerial vehicle flight parameters; the environment flight envelope is used for setting the mapping relation of the flight parameters of the unmanned aerial vehicle in an environment scene; and setting simulation parameters in the unmanned aerial vehicle wind speed simulation numerical model and carrying out simulation experiments to obtain the estimated quantity of the flow-guiding disturbance influence of the rotation of the rotor of the unmanned aerial vehicle. According to the invention, fluid simulation under different flight envelope conditions is carried out on the unmanned aerial vehicle wind speed measurement system, the disturbance influence of the rotor wing of the unmanned aerial vehicle on the measurement of the anemoscope is estimated according to the difference between the wind speed analog value and the set value at the position of the anemoscope to obtain an estimated value, and then the estimated value is substituted into the unmanned aerial vehicle motion and attitude compensation algorithm to realize correction of the influence of the rotor wing disturbance on the measurement result of the anemoscope and the influence caused by the attitude, motion and acceleration of the unmanned aerial vehicle, so that a more accurate three-dimensional wind speed measurement result is obtained.

Description

Unmanned aerial vehicle rotor wing disturbance correction method and device

Technical Field

The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to a method and a device for correcting rotor disturbance of an unmanned aerial vehicle.

Background

In recent years, with the development and application of the unmanned aerial vehicle technology, the unmanned aerial vehicle can measure wind conditions in small areas, inside chemical plumes, near thunderstorms or volcanoes which are difficult to reach by a traditional observation method due to the advantages of flexible operation, strong mobility, easy deployment and the like, improves the space-time resolution of wind speed measurement, and is widely applied to low-level atmosphere research, including boundary layer research, turbulence research, cloud micro physical research, influence research of wind turbines on atmospheric structures and the like. Drones are mainly divided into fixed-wing and multi-rotor, the latter being more suitable for measuring wind speeds in small areas and in the vicinity of buildings. At present, an anemoscope (including a cup-type anemoscope, a hot-wire anemoscope and an ultrasonic anemoscope) or different types of sensors (including a pitot tube, a porous pressure probe and a laser radar sensor) are mainly fixed at a certain part of an unmanned aerial vehicle, and then spatial information of wind speed is acquired along with the movement of the unmanned aerial vehicle.

Among them, the accuracy of three-dimensional ultrasonic anemometers for measuring three-dimensional wind speed is relatively high, and some small ultrasonic anemometers have been commercialized and integrated on multi-rotor unmanned aerial vehicles for wind speed measurement. The integration method is generally to fix the anemoscope at a position above the surface of the unmanned aerial vehicle and on the central axis by means of a support rod, and although the method can acquire wind characteristics with high space-time resolution, the measured three-dimensional wind speed data still has certain uncertainty. Its uncertainty mainly derives from unmanned aerial vehicle's motion and attitude change influence and the rotatory drainage influence of unmanned aerial vehicle rotor etc. to former researcher has developed unmanned aerial vehicle's motion and attitude compensation algorithm and has rectified it, and to the rotatory drainage of unmanned aerial vehicle rotor disturb, fail to obtain accurate correction algorithm at present. At present, the main three correction methods cannot provide the reliability of the result. Firstly, the anemoscope is determined to be placed at a position away from the central axis above the surface of the unmanned aerial vehicle through a flow field simulation or actual measurement method, and the interference of the rotation of the rotor of the unmanned aerial vehicle on the measurement of the anemoscope can be treated as zero interference; secondly, under the windless condition, an anemometer arranged on the unmanned aerial vehicle is used for directly measuring the additional speed generated by the induced airflow of the rotor wing of the unmanned aerial vehicle, and further correcting the additional speed; thirdly, the unmanned aerial vehicle wind speed measuring platform is placed on a base capable of adjusting the angle in the wind tunnel, the flying attitude change of the unmanned aerial vehicle is simulated through the angle of the adjusting base, the difference between the controllable wind speed in the wind tunnel and the wind speed measured by the anemoscope at different simulation angles is evaluated, and then the wind speed measuring platform is corrected.

However, the above correction methods all have certain limitations. The first correction method is difficult to be applied to a large-scale multi-rotor unmanned aerial vehicle, and because the rotor wing diameter of the unmanned aerial vehicle is large, the requirements on the length and the material of a support rod of an anemoscope are high, and the requirements on safety and stability cannot be generally met; the second correction method cannot reproduce the interference of the rotation of the rotor wing on the anemoscope under different wind speeds and different postures of the unmanned aerial vehicle; the third correction method has the disadvantages that the use cost of the wind tunnel is high, the wind tunnel is difficult to popularize, the unmanned aerial vehicle is easy to be influenced by the ground reflected airflow when being close to the ground, and the situation that the unmanned aerial vehicle carries other loads to execute other detection tasks is difficult to reproduce. In summary, the existing method cannot provide the reliability and accuracy of the compensation correction result of the real unmanned aerial vehicle atmospheric three-dimensional wind measurement.

Disclosure of Invention

In view of this, the present invention provides a method and an apparatus for correcting rotor disturbance of an unmanned aerial vehicle, so as to solve the problem that the reliability and accuracy of the atmospheric three-dimensional wind measurement compensation correction result of a real unmanned aerial vehicle cannot be provided in the prior art.

In order to realize the purpose, the invention adopts the following technical scheme: a method of unmanned aerial vehicle rotor disturbance correction, comprising:

constructing an unmanned aerial vehicle wind speed measurement simulation numerical model based on the environment flight envelope and the unmanned aerial vehicle flight parameters; the environment flight envelope is used for setting the mapping relation of the flight parameters of the unmanned aerial vehicle in an environment scene;

setting simulation parameters in the unmanned aerial vehicle wind speed simulation numerical model and carrying out simulation experiments to obtain an estimated quantity of the flow-guiding disturbance influence of the rotation of the rotor wing of the unmanned aerial vehicle;

and correcting the rotation of the rotor of the unmanned aerial vehicle according to the estimated quantity.

Further, the environment scene comprises a flight height, a wind speed and a wind direction, an environment temperature and an air pressure;

the unmanned aerial vehicle flight parameters include inclination and rotor speed.

Furthermore, the unmanned aerial vehicle adopts a six-rotor unmanned aerial vehicle, a task load is carried below the six-rotor unmanned aerial vehicle, a support base is arranged on a propeller plane of the six-rotor unmanned aerial vehicle, and the support base is used for supporting an anemoscope;

the construction of the unmanned aerial vehicle wind speed measurement simulation numerical model comprises the following steps,

according to the size, weight and material of the six-rotor unmanned aerial vehicle, the anemoscope and the supporting base, establishing a simulation numerical model for describing the wind speed measurement of the unmanned aerial vehicle according to a preset three-dimensional simulation coordinate system according to a preset proportion;

the unmanned aerial vehicle wind speed measurement simulation numerical model simulates a peripheral flow field of an unmanned aerial vehicle in the real atmosphere in flight by using a computational fluid dynamics method under different environment flight envelopes, and separates anemoscope signal influence caused by rotor drainage.

Further, set up simulation parameter in unmanned aerial vehicle wind speed simulation numerical model, include:

setting a calculation domain according to the wingspan of the unmanned aerial vehicle; opening an automatic initial grid when setting a computational grid; the gravity parameter is that the added gravity in the Y coordinate direction is 9.81 m/s ² (ii) a The fluid parameters comprise fluid types and fluid characteristics, and are classified and set; respectively modifying the atmospheric pressure into a first preset value and a second preset value under a first preset height and a second preset height, and setting the atmospheric temperature as a fixed value; setting the speed and the aerodynamic angle according to different flight conditions, setting turbulence parameters as defaults, and setting relative humidity according to reference pressure and reference temperature values corresponding to a first preset height and a second preset height; setting the rotation direction of a rotor wing of the unmanned aerial vehicle; setting the rotating speed of a rotor wing according to each flight condition in the environmental flight envelope;

the simulation targets are the average values of total pressure, speed y and speed z respectively; and obtaining a simulated velocity of the anemometer, the simulated velocity comprising an average and an instantaneous acceleration integral of a velocity, a velocity x, a velocity y, and a velocity z of the volumetric target; the simulation speed of the volume target in the simulation coordinate system is converted into the simulation speed in the unmanned aerial vehicle body coordinate system, and then the converted simulation speed is subtracted by the corresponding set airspeed so as to estimate the flow guiding speed of the unmanned aerial vehicle rotor wing rotation.

Further, the wind direction comprises downwind, upwind and crosswind, obtain the estimation of the rotatory drainage disturbance influence of unmanned aerial vehicle rotor, include:

acquiring a flight data set of the unmanned aerial vehicle under the conditions of downwind and upwind;

carrying out nonparametric inspection on matched samples of the disturbance values of the flight data set at two altitudes, and determining the influence of different heights on the flow guiding speed of the unmanned aerial vehicle rotor wing in different directions;

mixing the drainage speeds under all downwind and upwind conditions under the first preset height and the second preset height respectively to be used as dependent variables, and performing regression fitting by taking the x direction of the set airspeed as an independent variable to obtain a regression equation of the drainage speed and the x direction of the set airspeed;

under the conditions of downwind and upwind, obtaining an estimated quantity of the influence of the drainage disturbance of the rotation of the rotor wing of the unmanned aerial vehicle according to the airspeed of the unmanned aerial vehicle in the x direction and a corresponding regression equation;

under the crosswind condition, the estimated quantity of the influence of the drainage disturbance of the rotation of the rotor of the unmanned aerial vehicle is obtained according to the linear relation between the x direction and the z direction of the drainage speed and the x direction of the set airspeed.

Further, correcting for drone rotor rotation based on the estimate comprises:

the wind speeds in the x, y and z directions at the simulated speed of the anemometer are corrected by subtracting the estimates.

The embodiment of the application provides an unmanned aerial vehicle rotor disturbance correcting unit, include:

the building module is used for building an unmanned aerial vehicle wind speed measurement simulation numerical model based on the environment flight envelope and the unmanned aerial vehicle flight parameters; the environment flight envelope is used for setting the mapping relation of the flight parameters of the unmanned aerial vehicle in an environment scene;

the experiment module is used for setting simulation parameters in the unmanned aerial vehicle wind speed simulation numerical model and carrying out simulation experiments to obtain an estimated quantity of the flow-guiding disturbance influence of the rotation of the rotor wing of the unmanned aerial vehicle;

and the correction module is used for correcting the rotation of the rotor of the unmanned aerial vehicle according to the estimated quantity.

By adopting the technical scheme, the invention can achieve the following beneficial effects:

the invention provides a method and a device for correcting rotor wing disturbance of an unmanned aerial vehicle, which are used for carrying out fluid simulation under different flight envelope conditions on an unmanned aerial vehicle wind speed measuring system, estimating disturbance influence of a rotor wing of the unmanned aerial vehicle on measurement of an anemoscope according to a difference between a wind speed simulation value and a set value at the position of the anemoscope, acquiring a correction algorithm for rotor wing drainage disturbance compensation of the unmanned aerial vehicle, and substituting the algorithm into a complete algorithm for motion and attitude compensation of the unmanned aerial vehicle, so as to correct the influence of rotor wing disturbance on a measurement result of the anemoscope and the influence of the attitude, motion and acceleration of the unmanned aerial vehicle, and further acquire a relatively accurate three-dimensional wind speed measurement result.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.

FIG. 1 is a schematic diagram illustrating steps of a method for correcting rotor disturbance of an unmanned aerial vehicle according to the present invention;

fig. 2 (a) is a schematic view of an unmanned aerial vehicle wind speed measurement system provided by the present invention;

fig. 2 (b) is a schematic view of a wind speed simulation numerical model of the unmanned aerial vehicle provided by the invention;

fig. 3 is a schematic structural diagram of the unmanned aerial vehicle rotor disturbance correction device of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without any inventive step, are within the scope of the present invention.

A specific method and apparatus for correcting rotor disturbance of an unmanned aerial vehicle provided in the embodiments of the present application are described below with reference to the accompanying drawings.

As shown in fig. 1, the method for correcting rotor disturbance of an unmanned aerial vehicle provided in the embodiment of the present application includes:

s101, constructing an unmanned aerial vehicle wind speed measurement simulation numerical model based on an environmental flight envelope and unmanned aerial vehicle flight parameters; the environment flight envelope is used for setting the mapping relation of the flight parameters of the unmanned aerial vehicle in an environment scene;

in some embodiments, the environmental scene includes a flight altitude, a wind speed, a wind direction, an ambient temperature, and a barometric pressure;

the unmanned aerial vehicle flight parameters include inclination and rotor speed.

In some embodiments, the unmanned aerial vehicle is a six-rotor unmanned aerial vehicle, a mission load is carried below the six-rotor unmanned aerial vehicle, and a support base is arranged on a propeller plane of the six-rotor unmanned aerial vehicle and used for supporting an anemoscope;

the construction of the unmanned aerial vehicle wind speed measurement simulation numerical model comprises the following steps,

according to the size, weight and material of the six-rotor unmanned aerial vehicle, the anemoscope and the support base, establishing a simulation numerical model describing wind speed measurement of the unmanned aerial vehicle according to a preset three-dimensional simulation coordinate system in a preset proportion;

the unmanned aerial vehicle wind speed measurement simulation numerical model simulates a peripheral flow field of an unmanned aerial vehicle in the real atmosphere in flight by using a computational fluid dynamics method under different environment flight envelopes, and separates anemoscope signal influence caused by rotor drainage.

Specifically, this application adopts a large-scale six rotor unmanned aerial vehicle as wind speed measurement platform, and it is equipped with 6 screws, and maximum flying speed is 18m/s. In order to simulate the situation that the unmanned aerial vehicle system executes the measurement task at the same time, a certain weight task load is carried below the unmanned aerial vehicle. This application is through supporting the base and arranging a small-size three-dimensional ultrasonic wave anemoscope frame in a certain height cm department in unmanned aerial vehicle screw plane top to furthest reduces the rotor drainage and shows as figure 2 (a) to wind speed measurement's influence. X of the anemometer _t -y _t -z _t The Coordinate axes are based on the center of the anemometer and are respectively parallel to the x-y-z Coordinate axes of a horizontal Coordinate System (Vehicle-carried North-East-Down Coordinate System) of the unmanned aerial Vehicle body.

According to the detailed size, weight and material of the unmanned aerial vehicle, the anemoscope and the supporting base, according to a one-to-one proportion and according to x _s -y _s -z _s The simulation coordinate system establishes a simulation numerical model describing the unmanned aerial vehicle wind speed measurement system as shown in fig. 2 (b). The application provides an unmanned aerial vehicle wind speed measurement simulation numerical model establishes at different environment flight envelopes to establish unmanned aerial vehicle flight parameter. Based on the simulation numerical model, the computational fluid dynamics method is used to simulate the flight of the unmanned aerial vehicle in the real atmosphere under different environment flight envelopesAnd a peripheral flow field in the line is separated, and anemometer signal influence caused by rotor drainage is separated.

It can be understood that the parameters of the simulated environment flight envelope in the present application mainly include flight altitude, wind speed and wind direction, and ambient temperature and air pressure. The environmental flight envelope setting needs to map various environmental scenes encountered by the unmanned aerial vehicle in real atmospheric flight. Because unmanned aerial vehicle mainly flies in the atmospheric boundary layer, set up unmanned aerial vehicle's simulation environment for two flight heights in height above sea level, three wind directions (for unmanned aerial vehicle's flight direction) of downwind, upwind and crosswind are simulated respectively under every flight height to set up four flight groundspeeds and set up six grades of airspeeds respectively to the groundspeeds of different grades according to actual wind speed and unmanned aerial vehicle's maximum anti-wind performance to different wind directions, regard as this as simulation environment flight parameter's envelope.

Unmanned aerial vehicle flight parameter mainly includes inclination theta and rotor rotational speed N, and the two need adjust in order to reach the above ground flying speed who sets for according to actual windage. According to the method, theta and N are determined through the gravity (including the air machine and the load condition) of the unmanned aerial vehicle under the specific flight condition and the stress analysis of the tension T and the wind resistance D under the flight envelope of the simulation environment, and the method is applied to simulation calculation.

S102, setting simulation parameters in the unmanned aerial vehicle wind speed simulation numerical model and carrying out simulation experiments to obtain an estimated quantity of the influence of the flow-guiding disturbance of the rotation of the rotor wing of the unmanned aerial vehicle;

when a simulation test is performed, the simulation parameters provided in the present application include a calculation domain, a calculation grid, a gravity parameter, a fluid parameter, an environmental parameter, a rotation region, a calculation target, and the like. According to the method, the wingspan of the unmanned aerial vehicle is set as a calculation domain. In order to take account of the computation time and the computation accuracy of the simulation system tool, an automatic initial grid option is opened when a computation grid is set, and an appropriate result accuracy level and a minimum gap size are set so as to capture a detailed part of the unmanned aerial vehicle. For the gravity parameter, the added gravity in the Y coordinate direction is 9.81 m/s ² The fluid type is set to air and the fluid characteristics are set to turbulent and laminar flow. At H ₁ ，H ₂ Atmosphere at two heightsThe pressure is modified to its measured atmospheric pressure value, respectively, and the atmospheric temperature is set to a fixed temperature at both elevations. The speed and aerodynamic angle (angle of attack and angle of sideslip) are set according to different flight conditions, the turbulence parameters are set as defaults, and the relative humidity is set according to reference pressure and reference temperature values for two altitudes. Set up unmanned aerial vehicle rotor direction of rotation, be respectively for contrary, clockwise in turn, set up the rotor rotational speed under every flight condition in the envelope according to the flight again. The simulation targets are respectively total pressure (P) _G ) Velocity (V) _G ) Speed y (V) _Gy ) And velocity z (V) _Gz ) An average value; and acquiring a simulated velocity of the anemometer including velocity (Vs), velocity x (Vs) of the volume target _x ) Speed y (Vs) _y ) And velocity z (Vs) _z ) Average and instantaneous acceleration integral. The simulated velocity (Vs) of the volumetric target in the coordinate system will be simulated _x ,Vs _y ,Vs _z ) Conversion to simulated velocity in unmanned aerial vehicle body coordinate Systemu _{x_sensor} ,u _{y_sensor} ,u _{z_sensor} ) Then the converted simulation speed (u _{x_sensor} ,u _{y_sensor} ,u _{z_sensor} ) Minus the corresponding set space velocity (u _{x_air} ,u _{y_air} ,u _{z_air} ) And then estimating the flow-inducing speed of the rotation of the rotor of the unmanned aerial vehicle (respectively

Indicated).

In the invention, in the flight simulation of the unmanned aerial vehicle, the flight conditions of the unmanned aerial vehicle under the conditions of downwind and upwind are regarded as a group of data, the Wilcoxon nonparametric test of a matched sample is carried out on the disturbance values of the group of data under two altitudes, and the situation that the unmanned aerial vehicle under the conditions of downwind and upwind under the two altitudes is found out

，

And

there was no significant difference. Therefore the disturbance of the unmanned aerial vehicle rotor to the anemometer has negligible height effect. But the cross-wind simulation dataset was examined using a paired sample Wilcoxon nonparametric test method, finding a separation between two elevations

，

The difference was not significant, but

The difference is significant. This shows that in the case of crosswind, the disturbance of the drone rotor in the x and z directions of the anemometer is not affected by the altitude, but in the y direction the altitude needs to be differentiated.

By setting all the conditions of downwind and upwind at two heights

，

And

are mixed as dependent variables respectively, tou _{x_air} Regression fitting was performed for the independent variables and found

，

And

and space velocity ofu _{x_air} ) Are respectively tightly arranged betweenThe relationship (2) of (c). Therefore, under the conditions of downwind and upwind, the disturbance value of the rotor rotation drainage of the unmanned aerial vehicle to the anemoscope can be estimated only according to the airspeed of the unmanned aerial vehicle in the x direction and the corresponding regression equation, and then the drainage influence of the rotation of the rotor of the unmanned aerial vehicle can be eliminated by subtracting the estimated value from the original speed measured by the anemoscope.

For the side wind situation, in order to

、

As a dependent variable, ofu _{x_air} Regression fitting is carried out for independent variables, and the drainage speed in the x and z directions of the rotor wing of the unmanned aerial vehicle are foundu _{x_air} In a linear relationship. Due to the side wind condition

Having a high degree of sensitivity and thus at different heights

Is a dependent variable of

) To in order tou _{x_air} Regression fitting was performed for the independent variables. Discovery

Andu _{y_air} have a quadratic relationship therebetween, however

Andu _{y_air} fitting cannot be completed, but although

And

system on siteThere are differences in the counts, but similar in the values, which are explained

The difference in different heights is small, and therefore

And

instead of the height ranges of 0-500 m and 501-1000 m

(each is separately noted as

And

). Thus, in the case of a crosswind, the wind speed in the x, y and z directions measured by the anemometer is subtracted byu _{x_air} Oru _{y_air} Estimated of

、

、

Corresponding regression value or

And (6) correcting.

And S103, correcting the rotation of the rotor of the unmanned aerial vehicle according to the estimated quantity.

Specifically, the interference of the unmanned aerial vehicle rotor rotation drainage of this application with the estimation to the anemoscope fuses in unmanned aerial vehicle's motion and gesture compensation algorithm, forms the complete compensation algorithm of unmanned aerial vehicle motion, gesture and rotor drainage disturbance. Below isThe motion and attitude compensation algorithm of the unmanned aerial vehicle is briefly described. In order to cope with the change of the flying speed, the unmanned aerial vehicle generates a large attitude change (including pitching and rolling) in a period of time, the attitude change interferes with the measurement of the anemometer, and therefore the attitude change speed needs to be compensated, and the calculation is carried out according to the change rate of the attitude angle and the rotation radius. In addition, the wind speed u measured under the horizontal coordinate system of the machine body is measured _x 、u _y And u _z Rotating to the ground coordinate system through Euler coordinate transformation to obtain true west wind, south wind and upwindU _west 、U _south AndU _up . Where it is necessary to user(pitch)Andr(roll)representing the rotation rates resulting from changes in the pitch and roll attitude of the drone, respectively. By pitching

And scrolling

The angular velocity is derived.

And (4) integrating the rotation drainage speed of the rotor wing of the unmanned aerial vehicle estimated by simulation-fitting in the step four into an unmanned aerial vehicle motion and attitude compensation algorithm for correction. According to the simulation result, the direct wind and the crosswind are respectively parallel to the x axis and the y axis of the anemoscope, and the unmanned aerial vehicle rotor wing drainage can measure the anemoscope under the two wind direction conditionsu _x 、u _y Andu _z the invention takes the wind in the real complex direction as the wind composed of the direct wind and the upwind and the crosswind, namely, the real wind is decomposed to the x direction and the y direction, and then the flow guiding speed of the unmanned aerial vehicle rotor wing simulated and fitted under the conditions of the direct wind and the upwind and the crosswind is respectively subtracted from the wind in the x direction and the y direction (the flow guiding speed of the unmanned aerial vehicle rotor wing is the same as the flow guiding speed of the wind in the forward wind and the crosswind in the y direction and the simulation-fitting speed of the unmanned aerial vehicle rotor wing under the conditions of the direct wind and the upwind and the crosswind in the cross direction)

、

And

) Thereby correcting it.

To sum up, the present invention first assumes the wind direction

Western-style wind

South wind

And upwind

Four variables, the next to

And

all are decomposed into forward and backward wind and side wind, and the measured wind speed (according to the conditions of the forward and backward wind and the side wind respectively) ((u _x 、u _y Andu _z ) Unmanned aerial vehicle rotor wing drainage speed (minus corresponding simulation-fitting) ((B))

、

And

)。

as shown in fig. 3, the present application provides an unmanned aerial vehicle rotor disturbance correcting unit, includes:

the building module 201 is used for building an unmanned aerial vehicle wind speed measurement simulation numerical model based on an environmental flight envelope and unmanned aerial vehicle flight parameters; the environment flight envelope is used for setting the mapping relation of the flight parameters of the unmanned aerial vehicle in an environment scene;

the experiment module 202 is used for setting simulation parameters in the unmanned aerial vehicle wind speed simulation numerical model and carrying out simulation experiments to obtain an estimated quantity of the flow-guiding disturbance influence of the rotation of the rotor wing of the unmanned aerial vehicle;

and the correction module 203 is used for correcting the rotation of the rotor of the unmanned aerial vehicle according to the estimated quantity.

The working principle of the unmanned aerial vehicle rotor wing disturbance correction device provided by the application is that the construction module 201 constructs an unmanned aerial vehicle wind speed measurement simulation numerical model based on an environment flight envelope and unmanned aerial vehicle flight parameters; the environment flight envelope is used for setting the mapping relation of the flight parameters of the unmanned aerial vehicle in an environment scene; the experiment module 202 sets simulation parameters in the unmanned aerial vehicle wind speed simulation numerical model and carries out simulation experiment to obtain an estimated quantity of the influence of the flow-guiding disturbance of the rotation of the rotor wing of the unmanned aerial vehicle; the correction module 203 corrects the rotation of the rotor of the drone according to the estimated quantity.

In summary, the invention provides a method and a device for correcting rotor disturbance of an unmanned aerial vehicle, which are used for carrying out numerical modeling on an unmanned aerial vehicle wind speed measurement system of a three-dimensional ultrasonic anemoscope, carrying out unmanned aerial vehicle flight simulation under different environmental conditions including wind speed and flight height, combining simulation results with means such as a statistical method and regression fitting, acquiring the influence of extra drainage generated by rotation of a rotor on anemoscope measurement data of the unmanned aerial vehicle under different wind speeds and different flight postures, and compensating and correcting the influence, thereby reducing the inaccuracy of wind speed measurement based on an unmanned aerial vehicle platform and the three-dimensional anemoscope. Aiming at the known method for measuring the three-dimensional wind speed on the unmanned aerial vehicle platform, the invention systematically describes various types of measurement interference, particularly constructs a brand-new complete compensation correction algorithm due to the influence of extra drainage generated by the rotation of a rotor wing, and obtains high-precision three-dimensional wind speed measurement on a highly unstable platform.

In addition, the complete compensation algorithm described by the invention is suitable for all types of unmanned aerial vehicle platforms, and can realize compensation and correction on the condition that other loads are mounted on the unmanned aerial vehicle. In addition, the invention has low cost and is easy to popularize.

It can be understood that the method embodiments provided above correspond to the apparatus embodiments described above, and corresponding specific contents may be referred to each other, which are not described herein again.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think of the changes or substitutions within the technical scope of the present invention, and shall cover the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims (7)

1. An unmanned aerial vehicle rotor disturbance correction method is characterized by comprising the following steps:

constructing an unmanned aerial vehicle wind speed measurement simulation numerical model based on the environment flight envelope and the unmanned aerial vehicle flight parameters; the environment flight envelope is used for setting the mapping relation of the flight parameters of the unmanned aerial vehicle in an environment scene;

setting simulation parameters in the unmanned aerial vehicle wind speed simulation numerical model and carrying out simulation experiments to obtain an estimated quantity of the flow-guiding disturbance influence of the rotation of the rotor wing of the unmanned aerial vehicle;

and correcting the rotation of the rotor of the unmanned aerial vehicle according to the estimated quantity.

2. The method of claim 1,

the environment scene comprises flight height, wind speed and direction, environment temperature and air pressure;

the unmanned aerial vehicle flight parameters include inclination and rotor speed.

3. The method according to claim 1 or 2, wherein the drone is a six-rotor drone, below which a mission load is piggybacked, a support base being provided on a propeller plane of the six-rotor drone, the support base being for supporting an anemometer;

the construction of the unmanned aerial vehicle wind speed measurement simulation numerical model comprises the steps of,

according to the size, weight and material of the six-rotor unmanned aerial vehicle, the anemoscope and the supporting base, establishing a simulation numerical model for describing the wind speed measurement of the unmanned aerial vehicle according to a preset three-dimensional simulation coordinate system according to a preset proportion;

the unmanned aerial vehicle wind speed measurement simulation numerical model is used for simulating a peripheral flow field of an unmanned aerial vehicle in the real atmosphere in the flight process by calculation under different environment flight envelopes, and anemoscope signal influence caused by rotor wing drainage is separated.

4. The method of claim 3, wherein setting simulation parameters in the unmanned aerial vehicle wind speed simulation numerical model comprises:

setting a calculation domain according to the wingspan of the unmanned aerial vehicle; opening an automatic initial grid when setting a computational grid; the gravity parameter is that the added gravity in the Y coordinate direction is 9.81 m/s ² (ii) a The fluid parameters comprise fluid types and fluid characteristics, and are classified and set; respectively modifying the atmospheric pressure into a first preset value and a second preset value under a first preset height and a second preset height, and setting the atmospheric temperature as a fixed value; setting the speed and the aerodynamic angle according to different flight conditions, setting turbulence parameters as defaults, and setting relative humidity according to the pressure and temperature values corresponding to the first preset height and the second preset height; setting the rotation direction of a rotor wing of the unmanned aerial vehicle; setting the rotating speed of a rotor wing according to each flight condition in the environmental flight envelope;

the simulation targets are the average values of total pressure, speed y and speed z respectively; and obtaining a simulated velocity of the anemometer, the simulated velocity comprising an average and instantaneous acceleration integral of a velocity, a velocity x, a velocity y, and a velocity z of the volumetric target; the simulation speed of the volume target in the simulation coordinate system is converted into the simulation speed in the unmanned aerial vehicle body coordinate system, and then the converted simulation speed is subtracted by the corresponding set airspeed so as to estimate the flow guiding speed of the unmanned aerial vehicle rotor wing rotation.

5. The method of claim 4, wherein the wind direction is comprised of downwind, upwind, and crosswind, and wherein said obtaining an estimate of the effect of a induced disturbance of rotor rotation of the drone comprises:

acquiring a flight data set of the unmanned aerial vehicle under the conditions of downwind and upwind;

carrying out nonparametric inspection on matched samples of the disturbance values of the flight data set at two altitudes, and determining the influence of different heights on the flow guiding speed of the unmanned aerial vehicle rotor in different directions;

mixing the drainage speeds under all downwind and upwind conditions under the first preset height and the second preset height respectively to be used as dependent variables, and performing regression fitting by taking the x direction of the set airspeed as an independent variable to obtain a regression equation of the drainage speed and the x direction of the set airspeed;

under the conditions of downwind and upwind, obtaining an estimated quantity of the influence of the drainage disturbance of the rotation of the rotor wing of the unmanned aerial vehicle according to the airspeed of the unmanned aerial vehicle in the x direction and a corresponding regression equation;

under the crosswind condition, the estimated quantity of the influence of the drainage disturbance of the rotation of the rotor of the unmanned aerial vehicle is obtained according to the linear relation between the x direction and the z direction of the drainage speed and the x direction of the set airspeed.

6. The method of claim 5, wherein said correcting for drone rotor rotation based on said estimate comprises:

wind speeds in different directions at the simulated speed of the anemometer are corrected by subtracting the estimated amount.

7. An unmanned aerial vehicle rotor disturbance correcting unit, its characterized in that includes:

the building module is used for building an unmanned aerial vehicle wind speed measurement simulation numerical model based on the environment flight envelope and the unmanned aerial vehicle flight parameters; the environment flight envelope is used for setting the mapping relation of the flight parameters of the unmanned aerial vehicle in an environment scene;

the experiment module is used for setting simulation parameters in the unmanned aerial vehicle wind speed simulation numerical model and carrying out simulation experiments to obtain an estimated quantity of the flow-guiding disturbance influence of the rotation of the rotor wing of the unmanned aerial vehicle;

and the correction module is used for correcting the rotation of the rotor of the unmanned aerial vehicle according to the estimated quantity.

Images