Unmanned aerial vehicle wind resistance performance test system and method based on multi-fan array ventilation wall

Abstract

The invention discloses an unmanned aerial vehicle wind resistance performance test system and method based on a multi-fan array ventilation wall. The system comprises a movable ventilation wall, an auxiliary test assembly and a data acquisition and analysis assembly. The auxiliary test assembly comprises a rainwater spraying module and a closed-loop wind control module, the rainwater spraying module is used for adjusting the rainfall intensity of the unmanned aerial vehicle flight test site, and the closed-loop wind control module is used for adjusting the wind speed of a fan unit in the control module; and the data acquisition and analysis assembly comprises a positioning base station and an inertia motion capture module and is used for acquiring positioning data and flight attitude data of the unmanned aerial vehicle so as to analyze the wind resistance of the unmanned aerial vehicle. The problems of dynamic response lagging and insufficient wind and rain coupling environment simulation capability in the traditional test technology can be effectively solved through precise synchronous control of the multi-fan array ventilation wall combined with the rainwater spraying module and the closed-loop wind control module and comprehensive data acquisition of the positioning base station and the inertia motion capture module.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) performance testing technology, specifically to a UAV wind resistance performance testing system and method based on a multi-fan array wind wall. Background Technology

[0002] With the increasing prevalence of drones in complex scenarios such as urban operations, disaster relief, and outdoor inspections, their wind resistance performance in non-stationary wind conditions such as transient winds, wind shear, and turbulence, as well as wind-rain coupling environments, has become a core element in ensuring operational safety and reliability. Therefore, there is an urgent need for high-precision, multi-scenario drone wind resistance testing technology. Currently, drone wind resistance testing mainly relies on traditional wind tunnel systems and their improved equipment, such as wind tunnel systems based on variable frequency fans and wind tunnel devices with integrated rainfall simulation functions. However, these existing technologies have significant shortcomings in practical applications. The fan speed regulation process relies on frequency converters, resulting in dynamic response lag, which significantly reduces the simulation accuracy of non-stationary wind fields and fails to effectively reproduce high-frequency turbulent fluctuations. Simultaneously, environmental simulation capabilities are limited; most devices lack precise synchronization mechanisms between wind speed and rainfall signals, making it difficult to realistically reproduce the wind-rain coupling effect under complex urban disaster scenarios. Furthermore, the testing process lacks unified standards; the industry has not yet established standardized wind resistance testing methods and quantitative evaluation systems, resulting in poor comparability and insufficient credibility of test data, failing to objectively and comprehensively reflect the wind resistance capabilities of drones in real-world complex environments. These problems severely hinder the performance verification and technology optimization of drones in diverse scenarios.

[0003] Therefore, those skilled in the art urgently need to develop a new technical solution to address the above problems. Summary of the Invention

[0004] To overcome the problems existing in related technologies, this invention discloses a test system and method for testing the wind resistance performance of unmanned aerial vehicles based on a multi-fan array wind wall.

[0005] According to a first aspect of the present invention, a wind resistance performance testing system for unmanned aerial vehicles (UAVs) based on a multi-fan array wind wall is provided. The system includes: a movable wind wall, auxiliary testing components, and data acquisition and analysis components.

[0006] The movable wind wall consists of 1,600 fan units, with four fan units forming an independent control module, and each control module is electrically connected to a switch.

[0007] The auxiliary testing components include a rain spray module and a closed-loop wind control module. The rain spray module is used to adjust the rainfall intensity at the UAV flight test site. The closed-loop wind control module is electrically connected to the switch and sends control commands to the corresponding control module through the switch. The control commands are used to adjust the wind speed of the fan unit in the control module.

[0008] The data acquisition and analysis components include a positioning base station and an inertial motion capture module. The positioning base station is deployed at the UAV flight test site to acquire the UAV's three-dimensional spatial positioning data in the test site. The inertial motion capture module is used to acquire the UAV's flight attitude data in real time, so as to analyze the UAV's wind resistance performance through the positioning data and flight attitude data.

[0009] Optionally, symmetrical moving modules are provided on both sides of the movable wind wall, and the moving modules include servo motors, casters, electrical boxes and connecting rods;

[0010] The electrical box is electrically connected to the servo motor and is used to send control commands to the servo motor. The servo motor transmits power to the caster wheel through a connecting rod.

[0011] Optionally, each fan unit is equipped with an independent industrial control board. One end of the industrial control board is connected to the drive component of the fan unit, and the other end is electrically connected to the switch. The control board is used to receive control commands transmitted by the switch and control the drive component through the control commands.

[0012] Optionally, the positioning base station is a UWB positioning base station, and there are 4 UWB positioning base stations deployed at the boundary of the UAV flight test site.

[0013] Optionally, the inertial motion capture module is used to collect the roll angle, pitch angle and yaw angle of the UAV during flight.

[0014] According to a second aspect of the present invention, a method for testing the wind resistance performance of a drone based on a multi-fan array wind wall is provided, applied to the drone wind resistance performance testing system described in the first aspect of the present invention, the method comprising:

[0015] Determine the target wind field that the wind wall needs to generate during the test, including wind shear wind field, turbulent wind field and time-varying wind field;

[0016] The wind speed of the wind wall is gradually increased using a step-by-step increasing method;

[0017] Based on the preset relationship between wind speed and rainfall intensity, the rainfall intensity at the UAV flight test site is adjusted by the rain spray module.

[0018] The positioning data of the UAV during flight is collected by the positioning base station, and the flight attitude data of the UAV is collected by the inertial motion capture module.

[0019] The wind resistance performance of the UAV is analyzed using the positioning data and flight attitude data, and a wind resistance performance test report of the UAV is generated.

[0020] Optionally, the step of analyzing the wind resistance performance of the UAV through the positioning data and flight attitude data includes:

[0021] Based on a point in time, the mapping relationship between the UAV's flight environment data and flight status data is determined. The flight environment data includes rainfall intensity and wind speed, and the flight status data includes positioning data and flight attitude data.

[0022] Determine the position offset between the positioning data and the standard position information at each time point;

[0023] The attitude deviation between the flight attitude data and the standard attitude information at each time point is determined. The attitude deviation is obtained by roll angle deviation, pitch angle deviation and yaw angle deviation.

[0024] Different test weights are assigned to the position offset and attitude deviation based on the flight environment data, and the wind resistance performance score of the UAV is obtained based on the position offset, attitude deviation and test weights.

[0025] Optionally, the step of assigning different test weights to the position offset and attitude deviation based on the flight environment data, and obtaining the wind resistance performance score of the UAV based on the position offset, attitude deviation, and test weights, includes:

[0026] The first test weight corresponding to the position offset is: , As the first test weight, For the first Wind speed at a given time point For the first Rainfall intensity at a given time point The rated maximum wind speed, The rated maximum rainfall intensity, The preset penalty factor;

[0027] The second test weight corresponding to the attitude deviation is: , As the second test weight;

[0028] The wind resistance performance rating of the drone is:

[0029] ,in, For wind resistance performance rating, Indicates the first There are n time points, where n is the total number of time points. For the first The position offset corresponding to each time point For the first The attitude deviation at each time point This is the maximum allowable threshold for position offset. This represents the maximum permissible threshold for attitude deviation.

[0030] Optionally, the first Position offset at each time point , This represents the offset in the forward and backward directions. This represents the offset in the left and right directions. This represents the offset in the vertical direction;

[0031] The first Attitude deviation at each time point , This is the roll angle deviation. For pitch angle deviation, This refers to the yaw angle deviation.

[0032] Optionally, the turbulent wind field increases the wind speed in a step-by-step manner as follows: 0.0-0.2 m / s, 0.3-1.5 m / s, 1.6-3.3 m / s, 3.4-5.4 m / s, 5.5-7.9 m / s, 8.0-10.7 m / s, 10.8-13.8 m / s, 13.9-17.1 m / s, 17.2-20.7 m / s, 20.8-24.4 m / s, 24.5-28.4 m / s, 28.5-32.6 m / s, and 32.7-36.9 m / s. After each increase in wind speed, the current wind speed will be maintained for five minutes.

[0033] The time-varying wind field increases the wind speed in a step-by-step manner as follows: 0.0-0.2 m / s, 0.3-1.5 m / s, 1.6-3.3 m / s, 3.4-5.4 m / s, 5.5-7.9 m / s, 8.0-10.7 m / s, 10.8-13.8 m / s, 13.9-17.1 m / s, 17.2-20.7 m / s, 20.8-24.4 m / s, 24.5-28.4 m / s, 28.5-32.6 m / s, and 32.7-36.9 m / s. After each increase in wind speed, the current wind speed will be maintained for 30 seconds.

[0034] The wind shear field increases the wind speed in a step-by-step manner as follows: 0.0-0.2 m / s, 0.0-0.2 m / s, 0.3-0.6 m / s, 0.7-1.5 m / s, 1.6-2.6 m / s, 2.7-3.3 m / s, 3.4-4.4 m / s, 4.5-5.4 m / s, 5.5-7.9 m / s, 8.0-10.7 m / s, 10.8-13.8 m / s, 13.9-17.1 m / s, and 17.2-20.7 m / s. After each increase in wind speed, the current wind speed will be maintained for 30 seconds.

[0035] In summary, this invention discloses a test system and method for the wind resistance performance of unmanned aerial vehicles (UAVs) based on a multi-fan array wind wall. It achieves rapid dynamic adjustment of wind speed through an independent control module of the multi-fan array wind wall, combined with precise synchronous control of a rain spray module and a closed-loop wind control module, and comprehensive data acquisition from a positioning base station and an inertial motion capture module. This effectively solves the problems of slow dynamic response and insufficient simulation capability of wind-rain coupled environment in traditional testing techniques, and has advantages such as fast dynamic response, realistic simulation of wind-rain coupled environment, and objective evaluation of wind resistance performance.

[0036] Other features and advantages disclosed in this invention will be described in detail in the following detailed description section. Attached Figure Description

[0037] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings:

[0038] Figure 1 This is a structural block diagram of a UAV wind resistance performance testing system based on a multi-fan array wind wall, according to an exemplary embodiment.

[0039] Figure 2 It is based on Figure 1 A schematic diagram of a movable windbreak is shown;

[0040] Figure 3 It is based on Figure 1 This diagram illustrates a dynamic correction of wind speed deviation.

[0041] Figure 4 It is based on Figure 1 A schematic diagram of an inertial motion capture module is shown.

[0042] Figure 5 This is a flowchart illustrating a method for testing the wind resistance performance of a drone based on a multi-fan array wind wall, according to an exemplary embodiment. Detailed Implementation

[0043] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present disclosure.

[0044] Figure 1 This is a structural block diagram illustrating a UAV wind resistance performance testing system based on a multi-fan array wind wall, according to an exemplary embodiment. Figure 1 As shown, system 100 includes: a movable windbreak 110, an auxiliary testing component 120, and a data acquisition and analysis component 130; the movable windbreak 110 consists of 1600 fan units, with every 4 fan units forming an independent control module, and each control module is electrically connected to a switch; the auxiliary testing component 120 includes a rain spray module 121 and a closed-loop wind control module 122. The rain spray module 121 is used to adjust the rainfall intensity at the UAV flight test site, and the closed-loop wind control module 122 is electrically connected to the switch, sending control commands to the corresponding control module through the switch. The control commands are used to adjust the wind speed of the fan units within the control module; the data acquisition and analysis component 130 includes a positioning base station 131 and an inertial motion capture module 132. The positioning base station 131 is deployed at the UAV flight test site to acquire the UAV's three-dimensional spatial positioning data in the test site, and the inertial motion capture module 132 is used to acquire the UAV's flight attitude data in real time, so as to analyze the UAV's wind resistance performance through the positioning data and flight attitude data.

[0045] For example, movable wind walls are used to simulate complex wind fields, such as... Figure 2 As shown, the system consists of 1600 fan units, with four fan units forming an independent control module. Each control module is electrically connected to a switch. This allows each independent control module to quickly respond to wind speed adjustment needs, avoiding the lag effect of traditional frequency converter speed control. The rain spray module can adjust the rainfall intensity through a high-pressure nozzle array, dynamically adjusting the rainfall intensity at the UAV flight test site according to a preset relationship. This ensures precise matching of wind speed and rainfall signals, enabling the system to reproduce wind and rain coupled scenarios and effectively overcoming the distortion problem caused by the single environmental simulation in existing technologies. The closed-loop wind control module can precisely adjust the wind speed through PID algorithm feedback control or fuzzy logic control, avoiding the lag effect of traditional frequency converter speed control and achieving accurate simulation of non-stationary wind fields such as wind shear and turbulence. The positioning base station is deployed at the UAV flight test site to acquire the UAV's positioning data in three-dimensional space, while the inertial motion capture module collects the UAV's flight attitude data in real time. By jointly analyzing positioning data and flight attitude data, the position stability and attitude control capability of the UAV in the wind field are quantified, and the wind resistance performance test score of the UAV is obtained.

[0046] Optionally, symmetrical moving modules are provided on both sides of the movable wind wall. The moving modules include servo motors, casters, electrical boxes, and linkages. The electrical boxes are electrically connected to the servo motors and are used to send control commands to the servo motors. The servo motors transmit power to the casters through the linkages.

[0047] For example, symmetrically arranged moving modules on both sides of the wind wall, combined with servo motors, casters, electrical boxes and linkages, enable the wind wall to move quickly and accurately to a designated position, thereby significantly improving the stability of movement and positioning accuracy.

[0048] Optionally, each fan unit is equipped with an independent industrial control board. One end of the industrial control board is connected to the drive component of the fan unit, and the other end is electrically connected to the switch. The control board is used to receive control commands transmitted by the switch and control the drive component through the control commands.

[0049] For example, control commands refer to digital signals generated by the closed-loop wind control module and sent through the switch, used to control each fan unit to independently adjust its wind speed according to test requirements. Specifically, each fan unit is equipped with an independent industrial control board, enabling precise wind speed control of a single fan unit. When simulating complex wind fields such as turbulence or wind shear, the wind speed at each point can be precisely adjusted to meet the test requirements of different wind field scenarios.

[0050] like Figure 3 As shown, the brushless motor + hot wire feedback closed-loop wind control system balances speed accuracy and dynamic response, with a frequency response ≥200kHz. It can analyze multiple types of eddy currents and dynamically correct wind speed deviations (accuracy ±0.05m / s) by controlling the motor in a closed loop through data acquisition equipment.

[0051] Optionally, the positioning base stations are UWB positioning base stations, with a total of 4 UWB positioning base stations deployed at the boundary of the UAV flight test site.

[0052] For example, such as Figure 4 As shown, four UWB positioning base stations are deployed at the boundary of the UAV flight test site. Based on the geometric principle of three-dimensional spatial positioning, a complete triangulation network is formed. By maximizing the spatial distribution distance between base stations, optimizing the geometric structure of positioning reference points, and reducing interference in the signal propagation path, uniform positioning coverage is provided throughout the test area.

[0053] Optionally, the inertial motion capture module is used to collect the roll angle, pitch angle and yaw angle during the flight of the UAV.

[0054] For example, the roll angle is the angle of rotation of the UAV around its longitudinal axis, which can be acquired using a gyroscope or accelerometer, and is used to reflect the stability of the UAV tilting left and right under strong winds. The pitch angle is the angle of rotation of the UAV around its lateral axis, which can be detected by an accelerometer in the inertial measurement unit, and is used to reflect the dynamic balance capability of the UAV in the forward and backward directions. The yaw angle is the angle of rotation of the UAV around its vertical axis, which can be acquired by combining a magnetometer and a gyroscope, and is used to reflect the directional control accuracy caused by wind disturbances. Specifically, by acquiring the roll angle, pitch angle, and yaw angle using a limited inertial motion capture module, the wind resistance performance of the UAV in different wind field environments was evaluated.

[0055] For example, in wind shear or turbulent wind fields, drastic changes in the roll angle may indicate insufficient lateral stability of the UAV; fluctuations in the pitch angle indicate the degree to which the UAV is affected by wind disturbances in the forward and backward directions; and deviations in the yaw angle can reflect the accuracy of the UAV's directional control in a quantitative way.

[0056] In addition, based on the roll angle, pitch angle, and yaw angle, roll angle deviation, pitch angle deviation, and yaw angle deviation can also be calculated for subsequent UAV performance testing.

[0057] Figure 5 This is a flowchart illustrating a method for testing the wind resistance performance of a drone based on a multi-fan array wind wall, according to an exemplary embodiment. Figure 5 As shown, the method applied to the wind resistance performance testing system for unmanned aerial vehicles includes:

[0058] In step 501, the target wind field to be generated by the wind wall during the test is determined. The target wind field includes wind shear wind field, turbulent wind field and time-varying wind field.

[0059] In step 502, the wind speed of the wind wall is gradually increased using a step-by-step increasing method;

[0060] In step 503, the rainfall intensity at the UAV flight test site is adjusted by the rain spray module according to the preset correspondence between wind speed and rainfall intensity.

[0061] In step 504, the positioning data of the UAV during flight is collected by the positioning base station, and the flight attitude data of the UAV is collected by the inertial motion capture module.

[0062] In step 505, the wind resistance performance of the UAV is analyzed by using positioning data and flight attitude data, and a wind resistance performance test report of the UAV is generated.

[0063] For example, by generating target wind field types using a wind wall and gradually increasing wind speed using a step-by-step method, while introducing a wind and rain synchronization control mechanism based on preset relationships, the standardization problem of wind resistance performance testing under complex wind conditions and wind-rain coupling environments is effectively solved. Addressing the simulation needs of non-stationary wind fields such as transient winds, wind shear, and high-frequency turbulence, the generation methods for wind shear wind fields, turbulent wind fields, and time-varying wind fields are clarified, significantly improving the accuracy of wind field dynamic response. Furthermore, through the multi-source data fusion analysis path of positioning base stations and inertial motion capture modules, an objective quantitative evaluation of UAV wind resistance performance is achieved, achieving high dynamic response, multi-scenario simulation capabilities, and a unified standardized testing process. The system achieves high-precision testing of UAV wind resistance performance through the coordinated operation of movable wind walls, auxiliary testing components, and data acquisition and analysis components.

[0064] Specifically, the turbulent wind field increases the wind speed in a step-by-step manner as follows: 0.0-0.2 m / s, 0.3-1.5 m / s, 1.6-3.3 m / s, 3.4-5.4 m / s, 5.5-7.9 m / s, 8.0-10.7 m / s, 10.8-13.8 m / s, 13.9-17.1 m / s, 17.2-20.7 m / s, 20.8-24.4 m / s, 24.5-28.4 m / s, 28.5-32.6 m / s, and 32.7-36.9 m / s. After each increase in wind speed, the current wind speed will be maintained for five minutes.

[0065] The time-varying wind field increases the wind speed in a step-by-step manner as follows: 0.0-0.2 m / s, 0.3-1.5 m / s, 1.6-3.3 m / s, 3.4-5.4 m / s, 5.5-7.9 m / s, 8.0-10.7 m / s, 10.8-13.8 m / s, 13.9-17.1 m / s, 17.2-20.7 m / s, 20.8-24.4 m / s, 24.5-28.4 m / s, 28.5-32.6 m / s, and 32.7-36.9 m / s. After each increase in wind speed, the current wind speed will be maintained for 30 seconds.

[0066] The wind speed in the shear wind field is increased in a stepwise manner as follows: 0.0-0.2 m / s, 0.0-0.2 m / s, 0.3-0.6 m / s, 0.7-1.5 m / s, 1.6-2.6 m / s, 2.7-3.3 m / s, 3.4-4.4 m / s, 4.5-5.4 m / s, 5.5-7.9 m / s, 8.0-10.7 m / s, 10.8-13.8 m / s, 13.9-17.1 m / s, and 17.2-20.7 m / s. After each increase in wind speed, the current wind speed will be maintained for 30 seconds.

[0067] For example, turbulent wind fields are complex wind environments characterized by randomness, unsteadiness, and multi-scale vortex properties. These can be simulated using specific wind speed sequences and durations to mimic the turbulent characteristics of real-world scenarios. Time-varying wind fields are dynamic wind environments where wind speed changes rapidly over time. These can be simulated using shorter durations (e.g., 30 seconds) to simulate instantaneous wind speed changes. Shear wind fields are wind environments where wind speed changes drastically in space or time. These can be simulated using unique wind speed sequences containing repeating low-speed segments and appropriate durations (e.g., 30 seconds) to mimic the low-speed buffering and abrupt wind speed jumps in the shear layer transition zone. Simulations of shear wind fields can employ repeating low-speed segments of 0.0-0.2 m / s to accurately characterize the stability of UAVs traversing the shear layer. By customizing stepped, incremental wind speed sequences and durations for different wind field types, the problem of lacking specific test parameters is solved, enabling the testing process to accurately match the dynamic characteristics of real-world wind conditions. The segmented design of the wind speed sequence is based on meteorological standard data to ensure that each wind speed interval covers the intensity of typical disasters, while the differentiated maintenance time is dynamically adjusted according to the physical characteristics of the wind field. Together, they construct a standardized testing framework, which improves the comparability of test results and the scene reproduction.

[0068] Optionally, the wind resistance performance of the UAV can be analyzed using positioning data and flight attitude data, including: determining the mapping relationship between the UAV's flight environment data and flight status data based on a time point, where the flight environment data includes rainfall intensity and wind speed, and the flight status data includes positioning data and flight attitude data; determining the position offset between the positioning data and standard position information at each time point; determining the attitude deviation between the flight attitude data and standard attitude information at each time point, where the attitude deviation is obtained through roll angle deviation, pitch angle deviation, and yaw angle deviation; assigning different test weights to the position offset and attitude deviation based on the flight environment data; and obtaining the UAV's wind resistance performance score based on the position offset, attitude deviation, and test weights.

[0069] For example, UWB positioning base stations 4 deployed at the boundary of the test site are used to acquire positioning data in three-dimensional space, while the inertial motion capture module is responsible for capturing flight attitude data. Flight environment data is introduced to establish a dynamic weight allocation mechanism based on the flight environment data, thereby improving the objectivity and comparability of the test results. By mapping the time point benchmark, the flight environment data and flight state data are dynamically correlated, so that environmental changes at each moment can be accurately captured and reflected in the test results. On this basis, the position offset is calculated based on the comparison between the positioning data and standard position information, quantifying the position stability of the UAV in three-dimensional space, while the decomposition of attitude deviation captures attitude disturbances in different directions at specific angles, avoiding the limitations of single index evaluation.

[0070] By dynamically adjusting test weights based on flight environment data, changes in wind speed and rainfall intensity can affect the evaluation weights of position offset and attitude deviation in real time. For example, the weight of position stability is increased in high-wind environments, while the weight of attitude control is enhanced under rainfall conditions. Ultimately, a wind resistance performance score is generated based on the weighted position offset and attitude deviation, achieving objective quantification and standardization of test results. This process not only solves the environmental response distortion problem caused by overall averaging in traditional methods but also significantly improves the comparability and credibility of test data.

[0071] Specifically, different test weights are assigned to position offset and attitude deviation based on flight environment data. Based on position offset, attitude deviation, and test weights, the wind resistance performance score of the UAV is obtained, including:

[0072] The first test weight corresponding to the position offset is: , As the first test weight, For the first Wind speed at a given time point For the first Rainfall intensity at a given time point The rated maximum wind speed, The rated maximum rainfall intensity, The preset penalty factor;

[0073] The second test weight corresponding to the attitude deviation is: , As the second test weight;

[0074] The drone's wind resistance rating is:

[0075] ,

[0076] in, For wind resistance performance rating, Indicates the first There are n time points, where n is the total number of time points. For the first The position offset corresponding to each time point For the first The attitude deviation at each time point This is the maximum allowable threshold for position offset. This represents the maximum permissible threshold for attitude deviation.

[0077] For example, different weights can be assigned based on the environment, such as in mild conditions (low wind speed, no rain or light rain). and Very small Close to 1 When the value is close to 0, the score depends primarily on the positional offset. In extreme environments, and It's very big. Decrease As the weather gets colder, the score depends more on attitude stability. In other words, under the impact of extreme wind disturbances and rain on the aircraft, maintaining attitude stability and preventing rollover are the primary safety objectives, taking precedence over precise position holding.

[0078] Specifically, the first Position offset at each time point , This represents the offset in the forward and backward directions. This represents the offset in the left and right directions. This represents the offset in the vertical direction;

[0079] No. Attitude deviation at each time point , This is the roll angle deviation. For pitch angle deviation, This refers to the yaw angle deviation.

[0080] For example, position offset refers to the difference between the actual position of the UAV and a preset standard position, which can be quantified by calculating the displacement deviation of the UAV in the forward, left, right, and up / down directions. This feature is introduced to accurately assess the spatial stability of the UAV in complex wind fields. Furthermore, attitude deviation refers to the angular change of the UAV relative to a standard attitude during flight, which can be decomposed into roll angle deviation, pitch angle deviation, and yaw angle deviation, aiming to comprehensively reflect the UAV's attitude control capability in different directions.

[0081] In summary, this invention discloses a test system and method for the wind resistance performance of unmanned aerial vehicles (UAVs) based on a multi-fan array wind wall. It achieves rapid dynamic adjustment of wind speed through an independent control module of the multi-fan array wind wall, combined with precise synchronous control of a rain spray module and a closed-loop wind control module, and comprehensive data acquisition from a positioning base station and an inertial motion capture module. This effectively solves the problems of slow dynamic response and insufficient simulation capability of wind-rain coupled environment in traditional testing techniques, and has advantages such as fast dynamic response, realistic simulation of wind-rain coupled environment, and objective evaluation of wind resistance performance.

[0082] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0083] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0084] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. A test system for the wind resistance performance of unmanned aerial vehicles (UAVs) based on a multi-fan array wind wall, characterized in that, The system includes: a movable windbreak, auxiliary testing components, and data acquisition and analysis components; The movable wind wall consists of 1,600 fan units, with four fan units forming an independent control module, and each control module is electrically connected to a switch. The auxiliary testing components include a rain spray module and a closed-loop wind control module. The rain spray module is used to adjust the rainfall intensity at the UAV flight test site. The closed-loop wind control module is electrically connected to the switch and sends control commands to the corresponding control module through the switch. The control commands are used to adjust the wind speed of the fan unit in the control module. The data acquisition and analysis components include a positioning base station and an inertial motion capture module. The positioning base station is deployed at the UAV flight test site to acquire the UAV's three-dimensional spatial positioning data in the test site. The inertial motion capture module is used to acquire the UAV's flight attitude data in real time, so as to analyze the UAV's wind resistance performance through the positioning data and flight attitude data.

2. The UAV wind resistance performance testing system based on a multi-fan array wind wall according to claim 1, characterized in that, Symmetrical moving modules are provided on both sides of the movable wind wall. The moving modules include servo motors, casters, electrical boxes, and connecting rods. The electrical box is electrically connected to the servo motor and is used to send control commands to the servo motor. The servo motor transmits power to the caster wheel through a connecting rod.

3. The UAV wind resistance performance testing system based on a multi-fan array wind wall according to claim 1, characterized in that, Each fan unit is equipped with an independent industrial control board. One end of the industrial control board is connected to the drive component of the fan unit, and the other end is electrically connected to the switch. The control board is used to receive control commands transmitted by the switch and control the drive component through the control commands.

4. The UAV wind resistance performance testing system based on a multi-fan array wind wall according to claim 1, characterized in that, The positioning base stations are UWB positioning base stations, and there are four UWB positioning base stations deployed at the boundary of the UAV flight test site.

5. The UAV wind resistance performance testing system based on a multi-fan array wind wall according to claim 1, characterized in that, The inertial motion capture module is used to collect the roll angle, pitch angle and yaw angle of the UAV during flight.

6. A method for testing the wind resistance performance of unmanned aerial vehicles (UAVs) based on a multi-fan array wind wall, characterized in that, The method, applied to the UAV wind resistance performance testing system according to any one of claims 1-5, comprises: Determine the target wind field that the wind wall needs to generate during the test, including wind shear wind field, turbulent wind field and time-varying wind field; The wind speed of the wind wall is gradually increased using a step-by-step increasing method; Based on the preset relationship between wind speed and rainfall intensity, the rainfall intensity at the UAV flight test site is adjusted by the rain spray module. The positioning data of the UAV during flight is collected by the positioning base station, and the flight attitude data of the UAV is collected by the inertial motion capture module. The wind resistance performance of the UAV is analyzed using the positioning data and flight attitude data, and a wind resistance performance test report of the UAV is generated.

7. The method for testing the wind resistance performance of a UAV based on a multi-fan array wind wall according to claim 6, characterized in that, The analysis of the UAV's wind resistance performance using the positioning data and flight attitude data includes: Based on a point in time, the mapping relationship between the UAV's flight environment data and flight status data is determined. The flight environment data includes rainfall intensity and wind speed, and the flight status data includes positioning data and flight attitude data. Determine the position offset between the positioning data and the standard position information at each time point; The attitude deviation between the flight attitude data and the standard attitude information at each time point is determined. The attitude deviation is obtained by roll angle deviation, pitch angle deviation and yaw angle deviation. Different test weights are assigned to the position offset and attitude deviation based on the flight environment data, and the wind resistance performance score of the UAV is obtained based on the position offset, attitude deviation and test weights.

8. The method for testing the wind resistance performance of a UAV based on a multi-fan array wind wall according to claim 7, characterized in that, The process involves assigning different test weights to the position offset and attitude deviation based on the flight environment data, and obtaining a wind resistance performance score for the UAV based on the position offset, attitude deviation, and test weights, including: The first test weight corresponding to the position offset is: , As the first test weight, For the first Wind speed at a given time point For the first Rainfall intensity at a given time point The rated maximum wind speed, The rated maximum rainfall intensity, The preset penalty factor; The second test weight corresponding to the attitude deviation is: , As the second test weight; The wind resistance performance rating of the drone is: ,in, For wind resistance performance rating, Indicates the first There are n time points, where n is the total number of time points. For the first The position offset corresponding to each time point For the first The attitude deviation at each time point This is the maximum allowable threshold for position offset. This represents the maximum permissible threshold for attitude deviation.

9. The method for testing the wind resistance performance of a UAV based on a multi-fan array wind wall according to claim 8, characterized in that, The first Position offset at each time point , This represents the offset in the forward and backward directions. This represents the offset in the left and right directions. This represents the offset in the vertical direction; The first Attitude deviation at each time point , This is the roll angle deviation. For pitch angle deviation, This refers to the yaw angle deviation.

10. The method for testing the wind resistance performance of a UAV based on a multi-fan array wind wall according to claim 6, characterized in that, The turbulent wind field increases the wind speed in a step-by-step manner as follows: 0.0-0.2 m / s, 0.3-1.5 m / s, 1.6-3.3 m / s, 3.4-5.4 m / s, 5.5-7.9 m / s, 8.0-10.7 m / s, 10.8-13.8 m / s, 13.9-17.1 m / s, 17.2-20.7 m / s, 20.8-24.4 m / s, 24.5-28.4 m / s, 28.5-32.6 m / s, and 32.7-36.9 m / s. After each increase in wind speed, the current wind speed will be maintained for five minutes. The time-varying wind field increases the wind speed in a step-by-step manner as follows: 0.0-0.2 m / s, 0.3-1.5 m / s, 1.6-3.3 m / s, 3.4-5.4 m / s, 5.5-7.9 m / s, 8.0-10.7 m / s, 10.8-13.8 m / s, 13.9-17.1 m / s, 17.2-20.7 m / s, 20.8-24.4 m / s, 24.5-28.4 m / s, 28.5-32.6 m / s, and 32.7-36.9 m / s. After each increase in wind speed, the current wind speed will be maintained for 30 seconds. The wind shear field increases the wind speed in a step-by-step manner as follows: 0.0-0.2 m / s, 0.0-0.2 m / s, 0.3-0.6 m / s, 0.7-1.5 m / s, 1.6-2.6 m / s, 2.7-3.3 m / s, 3.4-4.4 m / s, 4.5-5.4 m / s, 5.5-7.9 m / s, 8.0-10.7 m / s, 10.8-13.8 m / s, 13.9-17.1 m / s, and 17.2-20.7 m / s. After each increase in wind speed, the current wind speed will be maintained for 30 seconds.

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