Unmanned aerial vehicle test system

Abstract

An unmanned aerial vehicle test system, comprising: a wind field test platform, an electromagnetic test platform, a water environment test platform and a control platform. The wind field test platform is used for performing a wind field test on an unmanned aerial vehicle, the wind field test platform comprising a plurality of multi-fan matrices; the electromagnetic test platform is used for performing an electromagnetic environment test on the unmanned aerial vehicle; the water environment test platform is used for performing a water environment test on the unmanned aerial vehicle; by means of the wind field test platform, the electromagnetic test platform and the water environment test platform, the control platform is used for performing any one of a wind field test, an electromagnetic environment test and a water environment test or simultaneously performing a plurality of tests on the unmanned aerial vehicle, wherein the control platform communicates with the wind field test platform and the electromagnetic test platform, so as to construct a multi-physical field coupled test area (1) for the wind field test and the electromagnetic test.

Description

Unmanned Aerial Vehicle Testing System Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) testing technology, and more particularly to a UAV testing system. Background Technology

[0002] Unmanned aerial vehicles (UAVs) are a type of aircraft. With their widespread application in military, civilian, security, and logistics fields, UAVs often face diverse and complex interference factors in real-world environments, including multi-directional wind disturbances and other various interferences. Therefore, testing is necessary to improve UAV performance.

[0003] Existing drone testing systems are typically traditional wind tunnels, which primarily focus on aerodynamic testing and lack programmable multi-directional wind field capabilities, making it impossible to simulate the dynamic characteristics of drones during actual flight and the multi-source disturbance scenarios of sensors.

[0004] Therefore, how to realistically simulate wind field disturbances and how to superimpose various other disturbances during the simulated wind field to test drones have become urgent technical problems to be solved.

[0005] Application content

[0006] This application provides a drone testing system that can meet the different testing needs of drones.

[0007] This application provides a drone testing system, which includes: a wind field testing platform, an electromagnetic testing platform, a water environment testing platform, and a control platform.

[0008] The wind field testing platform is used to conduct wind field tests on drones, and the wind field testing platform includes multiple multi-fan matrices;

[0009] The electromagnetic testing platform is used to conduct electromagnetic environment testing on drones;

[0010] The water environment testing platform is used to conduct water environment tests on drones;

[0011] The control platform is used to perform any one of the following tests on the UAV, or multiple tests simultaneously, through the wind field test platform, electromagnetic test platform, and water environment test platform;

[0012] The control platform communicates with both the wind field test platform and the electromagnetic test platform to construct a test area with multi-physics coupling for wind field testing and electromagnetic testing.

[0013] Optionally, the wind field testing platform also includes a wind field monitoring unit, which includes an anemometer, pressure sensor, turbulence probe, temperature and humidity sensor, and PIV measurement device. The anemometer, pressure sensor, turbulence probe, temperature and humidity sensor, and PIV measurement device are respectively arranged in the test area to monitor the wind field data generated by the multi-fan matrix in real time. The wind field data includes airflow velocity, airflow distribution, environmental parameters, and turbulence parameters. The collected wind field data is transmitted to the control platform.

[0014] Optionally, the electromagnetic environment testing platform includes an electromagnetic emission execution module, a third acquisition module, and a safety protection module.

[0015] The control platform communicates with the multi-fan matrix, the electromagnetic emission execution module, and the third acquisition module. The electromagnetic emission execution module and the multi-fan matrix in the wind field test platform form a multi-physics field coupled test area. The third acquisition module and the safety protection module are set in the test area. The third acquisition module includes an electromagnetic field monitoring unit.

[0016] Optionally, the electromagnetic launch execution module includes:

[0017] The system comprises an alternating magnetic field emitting device, a static magnetic field emitting device, and an electromagnetic pulse emitting device. The alternating magnetic field emitting device includes several alternating magnetic field emitting units arranged above the test area. Each alternating magnetic field emitting unit is controlled by an independent circuit to generate alternating magnetic fields with different frequency bands and different emission modes. The static magnetic field emitting device includes several electromagnetic coils arranged above the test area. The current intensity of the electromagnetic coils is adjustable, generating a static magnetic field with adjustable magnetic field intensity. The electromagnetic pulse emitting device includes a high-energy EMP generator located below the test area, which instantaneously generates high-energy electromagnetic pulses at the flash level.

[0018] Optionally, the electromagnetic field monitoring unit includes an electromagnetic field strength sensor and a spectrum sensor. The electromagnetic field strength sensor and the spectrum sensor are respectively arranged in the test area to measure the electromagnetic field data generated by the electromagnetic transmission execution module. The electromagnetic field data includes the instantaneous and average field strength distribution, the transmission power of the electromagnetic transmission execution module and the validity of its interference waveform. The collected electromagnetic field data is transmitted to the control platform.

[0019] Optionally, the safety protection device includes a linkage protection unit and a pulse protection unit. The linkage protection unit includes multiple emergency stop switches and edge guardrails. The multiple emergency stop switches are respectively installed in the electromagnetic launch execution module and the multi-fan matrix. The edge guardrails are installed around the test area. The emergency stop switches interact with the control platform through a hardware and software interlocking mechanism. The pulse protection unit includes a shielded chamber and a safety chamber. The shielded chamber is made of metal plates surrounding the test area. The four walls, floor and top of the shielded chamber are all made of electromagnetic shielding materials. The shielded chamber is equipped with wave-absorbing material walls and wedge-shaped wave absorbers. The safety chamber is located away from the shielded chamber. The operator conducts UAV testing through remote monitoring from inside the safety chamber.

[0020] Optionally, the third acquisition module also includes a visual motion capture unit, which is set up in the test area. When a drone is detected entering a certain section of the test area, the visual motion capture unit transmits the drone trajectory information data to the control platform.

[0021] Optionally, the control platform may also include:

[0022] The system includes a sensor control unit, a fan matrix control unit, an electromagnetic emission control unit, and a host scheduling unit. The sensor control unit, fan matrix control unit, and electromagnetic emission control unit are connected to the third acquisition module and the multi-fan matrix electromagnetic emission execution module via a communication network. The sensor control unit transmits the wind field data of the multi-fan matrix and the electromagnetic field data of the electromagnetic emission execution module to the host scheduling unit.

[0023] Optionally, the upper-level scheduling unit includes a composite scenario script generation system. The composite scenario script generation system schedules fan matrix control commands and electromagnetic interference control commands on the same time axis and generates composite scenario scripts using customized AI scheduling algorithms. The control platform constructs a test environment in the test area by running the composite scenario scripts, which superimposes the required wind field airflow disturbances and the required electromagnetic interference.

[0024] Optionally, generate and run the drone test scenario script, and output fan matrix control commands, electromagnetic interference control commands, or wind field magnetic field superposition interference commands;

[0025] The system can either enable a multi-fan matrix to receive fan matrix control commands individually to generate a wind field, or enable an electromagnetic emission execution module to receive electromagnetic interference control commands to generate an electromagnetic field, or enable the multi-fan matrix and the electromagnetic emission execution module to simultaneously receive wind field magnetic field superposition interference commands to generate a multi-physics field that superimposes wind field and electromagnetic field.

[0026] Optional, a multi-point modeling module is used to sample the multi-point control signals and wind speed response of each fan, and generate a control signal wind speed fitting model and a control signal prediction model.

[0027] The control signal prediction module is used to establish the target wind speed function based on the time-varying airflow characteristics to be generated, discretely generate the target wind speed time series, generate the predicted control signal time series based on the control signal prediction model, and send the predicted control signal time series to each fan controller using the TCP protocol.

[0028] The wind speed feedback adjustment module includes a wind speed sensor for real-time measurement of actual wind speed, comparison with the target wind speed time series, and a PI / PID feedback adjustment algorithm to generate a compensation control signal, which is then superimposed with the initial multi-point control signal to output a dynamic multi-point control signal.

[0029] The control platform also includes:

[0030] The fan multi-point control module includes multiple fan controllers, which cache the predicted control signal time series as the local control signal time series. Each fan controller caches the predicted control signal time series sent in batches and outputs the initial multi-point control signal.

[0031] Optionally, the wind farm testing platform further includes:

[0032] The local synchronization execution module includes a local timer, which is used to synchronize the global clock via the NTP protocol and output the initial multi-point control signals synchronously at preset time points based on the local control signal time series.

[0033] Optionally, the multi-point modeling module is also used for:

[0034] After interpolating and fitting the sampled data, the control signal wind speed fitting model is obtained. Specifically, the control signal wind speed fitting model is V = f i (PWM), where V is the fan speed, PWM is the multi-point control signal, i is the fan number, and f is the fan speed. i The mapping relationship between the multi-point control signals of each fan and the fan speed is defined by the control signal prediction model as PWM = f i -1 (V).

[0035] Optionally, the control signal prediction module is also used to: confirm the time-varying airflow waveform change curve according to the time-varying airflow characteristics to be generated, the time-varying airflow waveform change curve includes sine wave, square wave and triangular wave, and establish the target wind speed function according to the time-varying airflow waveform change curve.

[0036] Optionally, when the time-varying airflow waveform is a sine wave, the target wind speed function for the continuous time variable t is V(t) = V 0,1 +A1sin(2πω1t+φ1), where V 0,1Let A1 be the sinusoidal reference wind speed, ω1 be the sinusoidal wave amplitude, φ1 be the sinusoidal wave period frequency, and φ1 be the sinusoidal wave phase angle. When the time-varying airflow waveform is a square wave, the target wind speed function is V(t) = V 0,2 +A2sgn[sin(2πω2t+φ2)], where sgn(x) is the sign function; when x>0, sgn(x)=1; when x=0, sgn(x)=0; when x<0, sgn(x)=-1, V 0,2 Let A2 be the square wave reference wind speed, ω2 be the square wave amplitude, φ2 be the square wave period frequency, and φ2 be the square wave phase angle. When the time-varying airflow waveform curve is a triangular wave, the target wind speed function is: In the formula, V 0,3 A3 is the reference wind speed for the triangular wave, T is the triangular wave amplitude, and modT represents the position of the time variable within one period.

[0037] Optionally, the control signal prediction module is also used for:

[0038] The target wind speed function is sampled at uniform time intervals Δt to obtain the target wind speed time series. Where k is the sampling point number, n is the total sequence length, k = 0, 1, 2, ..., n, V k V represents the target wind speed at the sampling point. k =V(kΔt); Substituting the target wind speed time series into the control signal prediction model, we obtain the predicted control signal time series. Among them, PWM 0，k =f i -1 (V k ).

[0039] Optionally, the control signal prediction module is also used for:

[0040] The predictive control signal time series is divided into multiple predictive control signal time segments, and the predictive control signal time segments are sent to each fan controller in batches using the TCP transmission protocol.

[0041] Each fan controller is also used to cache the predicted control signal time series segments locally and then reassemble them into a local control signal time series in sequence.

[0042] Optionally, the fan controller is also used for:

[0043] Pre-execution data is generated based on the time series of local control signals, waiting for synchronous trigger instructions;

[0044] The global clock is aligned via the NTP protocol over the network to establish a unified time base, and based on this unified time base, a synchronization trigger command is triggered at a preset time point using a local timer.

[0045] The pre-execution data is processed, and the initial multi-point control signal is output synchronously. The airflow speed of the multiple fans changes synchronously with the output of the initial multi-point control signal, which is f. i -1 (V k ).

[0046] Optionally, the wind speed feedback adjustment module is also used for:

[0047] Real-time measurement of actual wind speed V for each fan and each area meas Calculate the actual wind speed error ΔV = V k -V meas Based on the PI / PID feedback control algorithm, a compensated multi-point control signal ΔPWM is generated, which is then superimposed on the initial multi-point control signal to generate a dynamic multi-point control signal PWM. a PWM a =f i -1 (V k )+ΔPWM.

[0048] Optionally, the wind farm testing platform further includes:

[0049] The mounting frame and the two-dimensional cross-flow module are mounted on the frame. The mounting frame adopts a rectangular frame structure and is equipped with a two-dimensional cross-flow module. The two-dimensional cross-flow module includes several cross-flow axes arranged in a crisscross pattern. Each cross-flow axis is equipped with multiple flow blades. The longitudinally arranged flow blades and the transversely arranged flow blades form an air gap for air outlet. A fan is located directly behind the intersection of each longitudinally arranged flow axis and each transversely arranged flow axis. The external space directly in front of the two-dimensional cross-flow module forms a test area.

[0050] Optionally, the longitudinally arranged spoiler shafts and the transversely arranged spoiler shafts are arranged in layers, and multiple spoiler blades are arranged alternately along the axial direction of the spoiler shafts. The shape of the spoiler blades is square, rhomboid or X-shaped.

[0051] Optionally, an encoder is provided on the spoiler shaft. The encoder measures the rotation angle of the spoiler shaft in real time. Each spoiler shaft is connected to a servo motor. The servo motor is started or stopped so that the spoiler shaft is in a spoiler state or a guide state.

[0052] Optionally, the control platform is equipped with a spoiler shaft speed control module and a fan speed control module. The spoiler shaft speed control module controls the speed of each spoiler shaft individually, and the fan speed control module controls the speed of each fan individually.

[0053] Optionally, the control platform is also used for:

[0054] Obtain specific wind environment conditions for a preset application scenario, and obtain simulation instructions for those specific wind environment conditions;

[0055] The simulation command is updated into an execution command and transmitted to the spoiler shaft speed control module and the fan speed control module;

[0056] The fan speed control module receives and executes commands, controls each fan in zones, and sets it to be in a stationary state, a low speed state, or a high speed state according to a time sequence, thereby creating a wind field in the test area.

[0057] The deflector speed control module receives and executes commands, and controls each deflector in the two-dimensional cross deflector module in a zone. It sets the deflector in a guiding state or a deflector state according to a time sequence, thereby disturbing or guiding the airflow generated by the fan.

[0058] Obtain the time-varying curves of wind speed and turbulence intensity in the test area, and determine whether the wind wall can reproduce the specific wind environment conditions of the preset application scenario; if it can reproduce, the wind wall is applied to subsequent tests; if the specific wind environment conditions simulated by the wind wall have errors, return to S2, and re-update the simulation command to the execution command and transmit it to the turbulence shaft speed control module and the fan wind speed control module.

[0059] Optionally, the water environment testing platform includes a testing module and a first acquisition module.

[0060] The test module includes a water tank and a fixed frame installed at one end of the water tank, a wave generator installed at the other end of the water tank, and a fan matrix installed on the fixed frame;

[0061] The first acquisition module is used to transmit the collected water change data, wind field data, and UAV attitude data from the test module to the control platform.

[0062] The first acquisition module includes a sensor monitoring unit, an attitude monitoring unit, and an infrared capture system. The sensor monitoring unit is used to monitor water changes in the pool and wind field data of the multi-fan matrix. The attitude monitoring unit is used to capture the UAV and obtain UAV attitude images through the infrared capture system.

[0063] The control platform is also used to connect with the energy sensors installed on the UAV, so as to combine water change data and wind field data, and dynamically output test plans based on the UAV attitude data obtained by the infrared capture system and the UAV remaining energy information obtained by the energy sensors.

[0064] Optionally, a transparent observation window is provided on the side wall of the pool, a temperature control unit is installed inside the pool, multiple laser rangefinders are spaced apart along the length of the pool, a water pump is installed on the side wall of the pool, and a camera and a laser scanner are installed above the pool.

[0065] Optionally, the wave-making device includes hydraulic cylinders, a control platform is connected to the hydraulic cylinders, multiple hydraulic cylinders are provided, and the multiple hydraulic cylinders are spaced apart along the side wall of the pool away from the fixed frame. The telescopic ends of the multiple hydraulic cylinders are hinged with flaps, and the lower part of the flaps extends into the water.

[0066] Optionally, the sensor monitoring unit includes multiple ultrasonic anemometers, which are fixedly installed above the water tank at equal intervals.

[0067] The attitude monitoring unit also includes multiple visual markers set on the UAV;

[0068] The first acquisition module also includes an infrared capture system, which includes an infrared light source and an infrared camera. The infrared light source is used to emit infrared light to illuminate visual markers on the UAV, and the infrared camera is used to capture the infrared light reflected from the markers.

[0069] Optionally, the water environment testing platform also includes a display module.

[0070] The control platform is also used to analyze the acquired water body change data, wind field data, and UAV attitude data, and display them through the display module;

[0071] The control platform also includes a test mode generation module, which is used to pre-combine water change data and wind field data using a combination algorithm to generate multiple preset test schemes and store them as a set of preset test schemes.

[0072] Optionally, the control platform is also used for:

[0073] Output the current test plan and convert it into test instructions, which are then passed to the test module for the drone to conduct flight tests.

[0074] The system receives real-time drone attitude images from the infrared capture system, extracts the drone attitude images, and determines whether the drone has a tendency to exit or enter the water. If the drone has a tendency to exit or enter the water, the system obtains the drone attitude when crossing the medium through the infrared capture system, obtains the force and speed change data of the drone when flying across the medium, and stores and analyzes it. If the drone does not have a tendency to exit or enter the water, the system executes the acquisition command.

[0075] Obtain the remaining energy information of the drone, determine whether the remaining energy of the drone can support continuous cross-medium flight tests. If the drone has sufficient remaining energy, output a new test plan as the current test plan, so that the drone can carry out a new round of test experiments; otherwise, the test experiment ends.

[0076] The method in this application embodiment can perform wind field testing, water environment testing, and electromagnetic testing on the UAV individually, or it can perform multiple tests simultaneously, such as wind field testing plus water environment testing, or wind field testing plus electromagnetic testing, etc., which can meet the different testing needs of the UAV and increase the UAV's multi-scenario adaptability. Attached Figure Description

[0077] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0078] Figure 1 is a schematic diagram of the structure of the unmanned aerial vehicle testing system according to an embodiment of this application;

[0079] Figure 2 is a schematic diagram of the test area structure according to an embodiment of this application;

[0080] Figure 3 is a schematic diagram of the drone testing process according to an embodiment of this application;

[0081] Figure 4 is a flowchart illustrating the drone testing method according to an embodiment of this application;

[0082] Figure 5 is a schematic diagram of the structure of the wind field testing platform according to an embodiment of this application;

[0083] Figure 6 is a schematic diagram of the wind wall connection structure according to an embodiment of this application;

[0084] Figure 7 is a schematic diagram of several fan connection structures in an embodiment of this application;

[0085] Figure 8 is a schematic diagram of the connection structure of the two-dimensional cross-flow turbulence module in an embodiment of this application;

[0086] Figure 9 is a schematic diagram of the structure of the drone test platform according to an embodiment of this application;

[0087] Figure 10 is a schematic diagram of the connection structure of the test module in an embodiment of this application;

[0088] Figure 11 is an enlarged schematic diagram of region A in Figure 10;

[0089] Figure 12 is a schematic diagram of the test module cross-section in the side view of an embodiment of this application;

[0090] Figure 13 is a schematic flowchart of the drone testing method according to an embodiment of this application;

[0091] The components include: 1. Test area; 2. Multi-fan matrix; 21. Cellular unit; 3. Alternating magnetic field transmitter; 31. Static magnetic field transmitter; 32. Electromagnetic pulse transmitter; 4. Edge guardrail; 41. Shielded chamber; 42. Wave absorber.

[0092] Reference numerals: 601, mounting frame; 602, two-dimensional cross-flow spoiler module; 6021, servo motor; 6022, spoiler shaft; 6023, spoiler blades; 603, fan;

[0093] 101. Water tank; 111. Observation window; 102. Fan matrix; 103. Fixture; 104. Hydraulic cylinder; 105. Clapper; 112. Mounting cavity. Detailed Implementation

[0094] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0095] This application provides a drone testing system, which includes: a wind field testing platform, an electromagnetic testing platform, a water environment testing platform, and a control platform.

[0096] The wind field testing platform is used to conduct wind field tests on drones, and the wind field testing platform includes multiple multi-fan matrices;

[0097] The electromagnetic testing platform is used to conduct electromagnetic environment testing on drones;

[0098] The water environment testing platform is used to conduct water environment tests on drones;

[0099] The control platform is used to perform any one of the following tests on the UAV, or multiple tests simultaneously, through the wind field test platform, electromagnetic test platform, and water environment test platform;

[0100] The control platform communicates with both the wind field test platform and the electromagnetic test platform to construct a test area with multi-physics coupling for wind field testing and electromagnetic testing.

[0101] The method in this application embodiment can perform wind field testing, water environment testing, and electromagnetic testing on the UAV individually, or it can perform multiple tests simultaneously, such as wind field testing plus water environment testing, or wind field testing plus electromagnetic testing, etc., which can meet the different testing needs of the UAV and increase the UAV's multi-scenario adaptability.

[0102] The following section will detail various testing platforms and application scenarios where multiple testing platforms are used to test drones simultaneously.

[0103] In this embodiment, the wind field testing platform further includes a wind field monitoring unit, which includes an anemometer, pressure sensor, turbulence probe, temperature and humidity sensor, and PIV measurement device. The anemometer, pressure sensor, turbulence probe, temperature and humidity sensor, and PIV measurement device are respectively arranged in the test area to monitor the wind field data generated by the multi-fan matrix in real time. The wind field data includes airflow velocity, airflow distribution, environmental parameters, and turbulence parameters. The collected wind field data is transmitted to the control platform.

[0104] In this embodiment, the electromagnetic environment testing platform includes an electromagnetic emission execution module, a third acquisition module, and a safety protection module.

[0105] The control platform communicates with the fan matrix execution module, the electromagnetic emission execution module, and the third acquisition module. The electromagnetic emission execution module and the multi-fan matrix in the wind field test platform form a multi-physics field coupled test area. The third acquisition module and the safety protection module are set in the test area. The third acquisition module includes an electromagnetic field monitoring unit.

[0106] In this embodiment of the application, the electromagnetic launch execution module includes:

[0107] The system comprises an alternating magnetic field emitting device, a static magnetic field emitting device, and an electromagnetic pulse emitting device. The alternating magnetic field emitting device includes several alternating magnetic field emitting units arranged above the test area. Each alternating magnetic field emitting unit is controlled by an independent circuit to generate alternating magnetic fields with different frequency bands and different emission modes. The static magnetic field emitting device includes several electromagnetic coils arranged above the test area. The current intensity of the electromagnetic coils is adjustable, generating a static magnetic field with adjustable magnetic field intensity. The electromagnetic pulse emitting device includes a high-energy EMP generator located below the test area, which instantaneously generates high-energy electromagnetic pulses at the flash level.

[0108] In this embodiment, the electromagnetic field monitoring unit includes an electromagnetic field strength sensor and a spectrum sensor. The electromagnetic field strength sensor and the spectrum sensor are respectively arranged in the test area to measure the electromagnetic field data generated by the electromagnetic transmission execution module. The electromagnetic field data includes the instantaneous and average field strength distribution, the transmission power of the electromagnetic transmission execution module and the validity of its interference waveform. The collected electromagnetic field data is transmitted to the control platform.

[0109] In this embodiment, the safety protection device includes a linkage protection unit and a pulse protection unit. The linkage protection unit includes multiple emergency stop switches and edge guardrails. The multiple emergency stop switches are respectively installed in the electromagnetic launch execution module and the fan matrix execution module. The edge guardrails are installed around the test area. The emergency stop switches interact with the control platform through a hardware and software interlocking mechanism. The pulse protection unit includes a shielded chamber and a safety chamber. The shielded chamber is composed of metal plates surrounding the test area. The four walls, floor, and top of the shielded chamber are all made of electromagnetic shielding materials. The shielded chamber is equipped with wave-absorbing material walls and wedge-shaped wave absorbers. The safety chamber is located away from the shielded chamber. The operator conducts UAV testing remotely from the safety chamber.

[0110] In this embodiment of the application, the third acquisition module further includes a visual motion capture unit. The visual motion capture unit is set in the test area. When a drone is captured entering a certain section of the test area, the drone trajectory information data is transmitted to the control platform.

[0111] In this embodiment, the sensor control unit, fan matrix control unit, electromagnetic emission control unit, and upper-level scheduling unit are connected to the third acquisition module, fan matrix execution module, and electromagnetic emission execution module via a communication network. The sensor control unit transmits the wind field data from the fan matrix execution module and the electromagnetic field data from the electromagnetic emission execution module to the upper-level scheduling unit.

[0112] In this embodiment, the upper-level scheduling unit includes a composite scenario script generation system. The composite scenario script generation system schedules fan matrix control commands and electromagnetic interference control commands on the same time axis and generates composite scenario scripts using a customized AI scheduling algorithm. The control platform constructs a test environment in the test area by running the composite scenario scripts, which superimposes the required wind field airflow disturbances and the required electromagnetic interference.

[0113] In this embodiment of the application, the control platform is also used for:

[0114] Generate and run the drone test scenario script, and output fan matrix control commands, electromagnetic interference control commands, or wind field magnetic field superposition interference commands;

[0115] The fan matrix execution module can receive fan matrix control commands to generate a wind field independently, or the electromagnetic emission execution module can receive electromagnetic interference control commands to generate an electromagnetic field, or the fan matrix execution module and the electromagnetic emission execution module can simultaneously receive wind field magnetic field superposition interference commands to generate a multi-physics field superimposed with the wind field and electromagnetic field.

[0116] In this embodiment, please refer to Figures 1-2. Multiple multi-fan matrices, also known as fan matrix execution modules, include several fan units arranged in an array within the test area 1. These fan units are fixed together by a bracket to form a multi-fan matrix 2. Each fan unit is driven by an independent motor, enabling independent start-stop and speed adjustment. The multi-fan matrix 2 is divided into several independently controllable fan groups. By creating speed and phase differences between fan groups, various wind field modes can be generated. These wind field modes include gusts, pulses, rotating vortices, and laminar / turbulent flow switching. The wind field modes can be quickly switched or iteratively updated according to the test scenario requirements. For example, the test scenario of "sudden crosswind → turbulence → wind attenuation" can be simulated by updating the wind field mode through "gusts → rotating vortices → laminar / turbulent flow switching". By switching and updating the wind field mode, different geographical scenarios such as urban canyons, mountain airflows, and ocean wind fields can be simulated, as well as the disturbance scenarios of drones under extreme weather conditions such as storms and hurricane fronts. A honeycomb device 21 is set between the multi-fan matrix 2 and the test area 1 to rectify the wind field generated by the multi-fan matrix 2. The multi-fan matrix 2 can be expanded in scale according to the drone test requirements. In this embodiment, the multi-fan matrix 2 is a 40×40 fan array, with each fan unit having a power of 75W and a maximum wind speed of 14m / s.

[0117] Furthermore, the electromagnetic transmission execution module includes an alternating magnetic field transmitting device 3, a static magnetic field transmitting device 31, and an electromagnetic pulse transmitting device 32. The alternating magnetic field transmitting device 3 includes several alternating magnetic field transmitting units arranged above the test area 1. Each alternating magnetic field transmitting unit is controlled by an independent circuit to generate alternating magnetic fields of different frequency bands and different transmission modes. In this example, the alternating magnetic field frequency bands include 2.4GHz, 5.8GHz, millimeter waves, and microwaves. The 2.4GHz and 5.8GHz bands are used to interfere with the communication link of the UAV, causing signal interruption, delay, or packet loss. Millimeter waves and microwaves are used to interfere with high-frequency sensitive equipment such as radar and millimeter-wave sensing devices of the UAV, causing misjudgment, target loss, or positioning deviation. The alternating magnetic field transmission modes include directional transmission, omnidirectional transmission, and variable power transmission. The static magnetic field transmitting device 31 includes several electromagnetic coils arranged above the test area 1. The current intensity of the electromagnetic coils is adjustable to generate static magnetic fields with adjustable magnetic field intensity. In this embodiment, the magnetic field strength of the electromagnetic coil is adjustable from 0 to 50 mT. The test area 1 is spatially divided into several cubic cells, each cell serving as an independent partition. Interference waves can be generated in different partitions of the test area 1 through the alternating magnetic field transmitter 3 and the static magnetic field transmitter 31, causing deviations or distortions in the UAV's perception system. This simulates situations such as communication link interruption, navigation drift, and onboard hardware restart or failure under electromagnetic interference. This example uses a "following interference" strategy to trigger the interference waves, that is, when the UAV moves to a certain partition of the test area 1, the interference wave of that partition is triggered. The electromagnetic pulse transmitter 32 includes a high-energy EMP generator, which is located below the test area 1 and is used to instantaneously generate high-energy electromagnetic pulses at the flash level, thereby generating instantaneous high-energy pulse interference within the test area 1 to evaluate the extreme tolerance capability of the UAV's electronic system. This embodiment uses a "random pulse" strategy to trigger instantaneous high-energy pulse interference, that is, high-energy electromagnetic pulses are randomly generated within the test area 1 according to test needs to simulate sudden electromagnetic interference in the real environment.

[0118] Furthermore, the wind field monitoring unit includes an anemometer, pressure sensor, turbulence probe, temperature and humidity sensor, and PIV measurement device. The anemometer, pressure sensor, turbulence probe, temperature and humidity sensor, and PIV measurement device are respectively arranged in the test area 1 to monitor the wind field data generated by the fan matrix execution module in real time. The wind field data includes airflow velocity, airflow distribution, environmental parameters, and turbulence structure, and the collected wind field data is transmitted to the control platform.

[0119] Furthermore, the electromagnetic field monitoring unit includes an electromagnetic field strength sensor and a spectrum sensor, which are respectively arranged in the test area 1 to measure the electromagnetic field data generated by the electromagnetic emission execution module. The electromagnetic field data includes the instantaneous and average field strength distribution, the emission power of the electromagnetic wave and the effectiveness of its interference waveform, and transmits the collected electromagnetic field data to the control platform.

[0120] Furthermore, the control platform includes a sensor control unit, a fan matrix control unit, an electromagnetic launch control unit, and a host scheduling unit. The sensor control unit, fan matrix control unit, and electromagnetic launch control unit are respectively connected to the third acquisition module, the fan matrix execution module, and the electromagnetic launch execution module via a communication network. The sensor control unit transmits wind field data from the fan matrix execution module and electromagnetic field data from the electromagnetic launch execution module to the host scheduling unit. On one hand, the wind field monitoring unit acquires the current wind field data in real time and feeds it back to the fan matrix control unit. Based on the wind field data and according to the requirements of the UAV test scenario, the host scheduling unit adjusts the fan matrix control commands output to the fan matrix execution module in real time, thereby dynamically adjusting the speed and start / stop status of each fan unit to achieve control over the wind field environment. The system employs a closed-loop control mechanism of "real-time monitoring - data feedback - dynamic adjustment." On the other hand, the electromagnetic field monitoring unit acquires current electromagnetic field data in real time and feeds it back to the electromagnetic launch control unit. Based on this data, the upper-level scheduling unit adjusts the electromagnetic interference control command output to the electromagnetic field launch execution module in real time according to the "following interference" and "random pulse" strategies. This dynamically adjusts the power, angle, waveform, and switching status of each device in the electromagnetic launch execution module, achieving a closed-loop control of the electromagnetic field environment through "real-time monitoring - data feedback - dynamic adjustment." Through wind field closed-loop control and electromagnetic field closed-loop control, the test platform can repeatedly implement various complex interference scenarios, enabling UAVs to conduct repeated studies and comparative experiments under specified test scenarios. This ensures experimental accuracy while significantly improving the efficiency of repeated studies and comparative experiments.

[0121] Furthermore, the upper-level scheduling unit includes a composite scenario script generation system. This system first schedules the fan matrix control commands and electromagnetic interference control commands on the same time axis, and then uses a customized AI scheduling algorithm to generate a composite scenario script. By running the composite scenario script, the control platform can construct a test environment in test area 1 that superimposes the required wind field airflow disturbances and the required electromagnetic interference. For example, it can simultaneously activate local microwave interference at the moment of a sudden strong wind and randomly insert electromagnetic pulse interference in continuous turbulence, thereby enabling the test platform to perform integrated testing of multi-physics fields coupled with "airflow" and "electromagnetism".

[0122] Furthermore, the safety protection device includes a linkage protection unit and a pulse protection unit. The linkage protection unit is used to address the linkage risks that may arise when the electromagnetic launch execution module and the fan matrix execution module work together. It includes multiple emergency stop switches and edge guardrails 4. The multiple emergency stop switches are respectively installed inside the electromagnetic launch execution module and the fan matrix execution module. The edge guardrails 4 are installed around the test area 1. The emergency stop switches interact with the control platform through a hardware and software interlocking mechanism. Once the control platform detects that the UAV is out of control or has a collision risk, it can promptly cut off the relevant emergency stop switches. The pulse protection unit includes a shielded chamber 41 and a safety chamber, used to protect the electromagnetic launch execution module from potential collision risks. When the module emits high-energy electromagnetic pulses, to prevent adverse effects on the external environment and operators, the shielding chamber 41 is constructed of metal plates surrounding the test area 1. The four walls, floor, and top of the shielding chamber are all made of electromagnetic shielding material, forming a "cage" structure that can isolate most external electromagnetic waves from internal electromagnetic waves. The test area 1 is located within the "cage" structure. The inner walls of the shielding chamber 41 are equipped with wave-absorbing material walls and wedge-shaped wave absorbers 42 to reduce high-frequency reflections and standing waves, and to avoid the influence of secondary electromagnetic radiation. The safety chamber is located away from the shielding chamber 41. Operators conduct UAV tests through remote monitoring from inside the safety chamber, ensuring the personal safety of the operators.

[0123] Furthermore, the third acquisition module also includes a visual motion capture unit, which is set in the test area 1 to track the trajectory of drones and drone formations. When the visual motion capture unit detects a drone entering a certain section of the test area 1, it transmits the drone trajectory information data to the control platform. The control platform outputs local control commands for the fan matrix and local control commands for electromagnetic interference, triggering local pulsating wind fields and local electromagnetic interference in that section.

[0124] This application also provides a drone-based testing system, applied to the aforementioned testing system, as shown in Figure 3, including the following steps:

[0125] S301: The control platform generates and runs the UAV test scenario script, and outputs fan matrix control commands, electromagnetic interference control commands, or wind field magnetic field superposition interference commands.

[0126] S302: The fan matrix execution module receives the fan matrix control command to generate a wind field, or the electromagnetic emission execution module receives the electromagnetic interference control command to generate an electromagnetic field, or the fan matrix execution module and the electromagnetic emission execution module simultaneously receive the wind field magnetic field superposition interference command to generate a multi-physics field superimposed with the wind field and the electromagnetic field.

[0127] S303: The UAV is subjected to disturbance testing in a single wind field, a single electromagnetic field, or a multi-physics field. The disturbance test includes disturbance testing of the perception system, disturbance resistance testing of the flight control system, and multi-aircraft collaborative testing. Safety protection devices are used during the disturbance test.

[0128] The UAV perception system includes various navigation sensors, related communication links, and airborne hardware mounted on the UAV. The navigation sensors include GPS, magnetic compass, visual SLAM, and lidar. The flight control system anti-interference test requires the UAV to perform a designated flight mission within test area 1. The designated flight mission includes hovering, path tracking, and multi-UAV formation coordination. The multi-UAV coordination test includes UAV formation wake interference testing and network reliability testing of shared communication links.

[0129] S304: The wind field monitoring unit collects wind field data, the electromagnetic field monitoring unit collects electromagnetic field data, the visual motion capture unit collects UAV trajectory information data, and the control platform receives wind field data, electromagnetic field data and UAV trajectory information data, continuously adjusts the fan matrix control command or electromagnetic interference control command or wind field magnetic field superposition interference command and outputs it until the disturbance test ends.

[0130] S305: The third acquisition module and the UAV onboard system record UAV disturbance test data, including disturbance data of the perception system, disturbance resistance data of the flight control system, and multi-aircraft collaborative data.

[0131] The data includes: Perception system disturbance data, which includes data on abnormal situations such as communication link interruptions, navigation drift, and onboard hardware restarts or malfunctions experienced by the UAV in test area 1; and flight control system disturbance data, which provides experimental reference for improving anti-interference strategies and algorithms of the UAV perception system in complex multi-physics environments. Flight control system disturbance data includes attitude data, speed data, and flight control commands of the UAV when performing a designated flight mission in test area 1; and flight control system disturbance data, which can evaluate the flight control system's anti-interference capability in the flight control system disturbance test environment, verify the robustness and fault tolerance of the flight control system's anti-interference strategy, and subsequently use reinforcement learning or adaptive control algorithms for online or offline training to gradually optimize the UAV flight control system's anti-interference strategy. Multi-UAV collaborative testing includes UAV formation wake interference testing and shared communication link network reliability testing; and multi-UAV collaborative data, which allows operators to observe the collaborative actions of multiple UAVs quickly switching to an self-organizing network or backup navigation, thereby evaluating the distributed collaborative mechanism of the UAV formation and providing experimental reference for exploring more advanced distributed collaborative mechanisms.

[0132] Compared with existing technologies, this application has the following advantages: By integrating wind field disturbances and electromagnetic interference into an indoor test platform through a fan matrix execution module and an electromagnetic launch execution module, and through closed-loop control between the control platform and the third acquisition module, the fan matrix execution module, and the electromagnetic launch execution module, various complex or extreme environments can be flexibly reproduced, overcoming the limitations of traditional separate testing in wind tunnels and electromagnetic laboratories. The fan matrix execution module adopts modular fan units, and the electromagnetic launch execution module adopts pluggable electromagnetic launch units, allowing for flexible upgrades to the platform scale and frequency band range according to test requirements. The test platform is highly scalable and flexible, and by setting up a safety protection module, potential safety hazards and functional failures in practical applications are reduced. By running test scenario scripts, various complex interference scenarios can be repeatedly realized under the same or different experimental conditions, verifying the reliability of the UAV perception system, flight control system, and multi-UAV coordination and networking communication under both aerodynamic and electromagnetic interference. This significantly improves the efficiency of research and comparative experiments, while providing experimental references for improving UAV anti-interference strategies and distributed coordination mechanisms.

[0133] As shown in Figure 5, in this embodiment of the application, the wind field testing platform includes:

[0134] The multi-point modeling module is used to sample the multi-point control signals and wind speed response of each fan, and generate a control signal wind speed fitting model and a control signal prediction model.

[0135] The control signal prediction module is used to establish the target wind speed function based on the time-varying airflow characteristics to be generated, discretely generate the target wind speed time series, generate the predicted control signal time series based on the control signal prediction model, and send the predicted control signal time series to each fan controller using the TCP protocol.

[0136] The wind speed feedback adjustment module includes a wind speed sensor for real-time measurement of actual wind speed, comparison with the target wind speed time series, and a PI / PID feedback adjustment algorithm to generate a compensation control signal, which is then superimposed with the initial multi-point control signal to output a dynamic multi-point control signal.

[0137] The control platform also includes:

[0138] The fan multi-point control module includes multiple fan controllers, which cache the predicted control signal time series as the local control signal time series. Each fan controller caches the predicted control signal time series sent in batches and outputs the initial multi-point control signal.

[0139] In this embodiment of the application, the wind farm testing platform further includes:

[0140] The local synchronization execution module includes a local timer, which is used to synchronize the global clock via the NTP protocol and output the initial multi-point control signals synchronously at preset time points based on the local control signal time series.

[0141] In this embodiment of the application, the multi-point modeling module is also used for:

[0142] After interpolating and fitting the sampled data, the control signal wind speed fitting model is obtained. Specifically, the control signal wind speed fitting model is V = f i (PWM), where V is the fan speed, PWM is the multi-point control signal, i is the fan number, and f is the fan speed. i The mapping relationship between the multi-point control signals of each fan and the fan speed is defined by the control signal prediction model as PWM = f i -1 (V).

[0143] In this embodiment of the application, the control signal prediction module is further configured to: confirm the time-varying airflow waveform change curve according to the time-varying airflow characteristics to be generated, the time-varying airflow waveform change curve includes sine wave, square wave and triangular wave, and establish a target wind speed function based on the time-varying airflow waveform change curve.

[0144] In this embodiment of the application, when the time-varying airflow waveform curve is a sine wave, the target wind speed function of the continuous time variable t is V(t) = V 0,1 +A1sin(2πω1t+φ1), where V 0,1 Let A1 be the sinusoidal reference wind speed, ω1 be the sinusoidal wave amplitude, φ1 be the sinusoidal wave period frequency, and φ1 be the sinusoidal wave phase angle. When the time-varying airflow waveform is a square wave, the target wind speed function is V(t) = V 0,2 +A2sgn[sin(2πω2t+φ2)], where sgn(x) is the sign function; when x>0, sgn(x)=1; when x=0, sgn(x)=0; when x<0, sgn(x)=-1, V 0,2 Let A2 be the square wave reference wind speed, ω2 be the square wave amplitude, φ2 be the square wave period frequency, and φ2 be the square wave phase angle. When the time-varying airflow waveform curve is a triangular wave, the target wind speed function is: In the formula, V 0,3 A3 is the reference wind speed for the triangular wave, T is the triangular wave amplitude, and modT represents the position of the time variable within one period.

[0145] In this embodiment of the application, the control signal prediction module is further configured to:

[0146] The target wind speed function is sampled at uniform time intervals Δt to obtain the target wind speed time series. Where k is the sampling point number, n is the total sequence length, k = 0, 1, 2, ..., n, V k V represents the target wind speed at the sampling point. k =V(kΔt); Substituting the target wind speed time series into the control signal prediction model, we obtain the predicted control signal time series. Among them, PWM 0，k =f i -1 (V k ).

[0147] In this embodiment of the application, the control signal prediction module is further configured to:

[0148] The predictive control signal time series is divided into multiple predictive control signal time segments, and the predictive control signal time segments are sent to each fan controller in batches using the TCP transmission protocol.

[0149] Each fan controller is also used to cache the predicted control signal time series segments locally and then reassemble them into a local control signal time series in sequence.

[0150] In this embodiment of the application, the fan controller is further used for:

[0151] Pre-execution data is generated based on the time series of local control signals, waiting for synchronous trigger instructions;

[0152] The global clock is aligned via the NTP protocol over the network to establish a unified time base, and based on this unified time base, a synchronization trigger command is triggered at a preset time point using a local timer.

[0153] The pre-execution data is processed, and the initial multi-point control signal is output synchronously. The airflow speed of the multiple fans changes synchronously with the output of the initial multi-point control signal, which is f. i -1 (V k ).

[0154] In this embodiment of the application, the wind speed feedback adjustment module is also used for:

[0155] Real-time measurement of actual wind speed V for each fan and each area meas Calculate the actual wind speed error ΔV = V k -V meas Based on the PI / PID feedback control algorithm, a compensated multi-point control signal ΔPWM is generated, which is then superimposed on the initial multi-point control signal to generate a dynamic multi-point control signal PWM. a PWM a =f i -1 (V k )+ΔPWM.

[0156] Compared with the prior art, the beneficial effects of this application are:

[0157] In this embodiment, a control signal prediction model is established to predict multi-point control signals for any target wind speed; the global clock is aligned using the NTP protocol to synchronously trigger multi-point control signals at a preset time point, enabling precise coordinated control of multiple fans and achieving highly consistent output from multiple fans and synchronous generation of various complex time-varying airflows.

[0158] In this embodiment, based on real-time feedback adjustment of actual wind speed, a dynamically adjusted multi-point control signal is output to achieve dynamic and precise compensation for the airflow control of multiple fans, thereby counteracting fan performance degradation and ensuring long-term consistent output of multiple fans.

[0159] In this embodiment, by unifying the planning of control signals, aligning the network with the global clock and local cache, and synchronously executing the control signals, the reliance on real-time communication can be reduced while achieving precise collaborative control of multiple fans.

[0160] As shown in Figure 4, the method for applying the above system includes the following steps:

[0161] S501: Sample the multi-point control signals and wind speed response of each fan, establish a control signal wind speed fitting model, and back-calculate the control signal prediction model.

[0162] Specifically, after sampling the multi-point control signals and wind speed responses of each fan, a correlation database is established based on the sampled data, linking the multi-point control signals and corresponding wind speed responses of each fan. After data cleaning, deletion, and correction of outlier data in the correlation database, the control signal wind speed fitting model is obtained by careful interpolation and fitting. i (PWM), where V is the fan speed, PWM is the multi-point control signal, i is the fan number, and f is the fan speed. i This describes the mapping relationship between the multi-point control signals of each fan and the fan speed; the control signal prediction model is specifically PWM = f i -1 (V); By multi-point modeling and back-reasoning the control signal prediction model, it is possible to predict the multi-point control signal for any target wind speed of each fan.

[0163] S502: Establish the target wind speed function based on the time-varying airflow characteristics to be generated, discretize and generate the target wind speed time series, and generate the predictive control signal time series based on the control signal prediction model;

[0164] Specifically, based on the time-varying airflow characteristics to be generated, the time-varying airflow waveform curve is identified. This waveform includes sine waves, square waves, and triangular waves. A target wind speed function is then established based on this waveform curve. When the time-varying airflow waveform is a sine wave, the target wind speed function is V(t) = V 0,1 +A1sin(2πω1t+φ1), where t is a continuous time variable, V(t) is the target wind speed at different times, and V 0,1 Let A1 be the sinusoidal reference wind speed, ω1 be the sinusoidal wave amplitude, φ1 be the sinusoidal wave period frequency, and φ1 be the sinusoidal wave phase angle. When the time-varying airflow waveform is a square wave, the target wind speed function is V(t) = V 0,2 +A2sgn[sin(2πω2t+φ2)], where sgn(x) is the sign function; when x>0, sgn(x)=1; when x=0, sgn(x)=0; when x<0, sgn(x)=-1, V 0,2 Let A2 be the square wave reference wind speed, ω2 be the square wave amplitude, φ2 be the square wave period frequency, and φ2 be the square wave phase angle. The waveform curve represents the time-varying airflow of the square wave, where the wind speed jumps between its maximum and minimum values, characterizing abrupt wind speed disturbances. When the time-varying airflow waveform curve is a triangular wave, the target wind speed function is... In the formula, V 0,3 A3 is the reference wind speed for the triangular wave, T is the triangular wave amplitude, and modT represents the position of the time variable within one period.

[0165] The target wind speed function is sampled at uniform time intervals Δt to obtain the target wind speed time series. Where k is the sampling point number, n is the total sequence length, k = 0, 1, 2, ..., n, V k V represents the target wind speed at the sampling point. k =V(kΔt), where the selected time interval Δt in this embodiment is 10ms, meaning the target wind speed function is sampled every 10ms; the target wind speed time series is then input into the control signal prediction model to obtain the predicted control signal time series. Among them, PWM 0，k =f i -1 (V k By establishing a target wind speed function and generating a predictive control signal time series, it is possible to predict the control signal for any complex time-varying airflow waveform, thereby generating any complex time-varying airflow waveform.

[0166] S503: The predictive control signal time series is sent to each fan controller using the TCP protocol. Each fan controller caches the predictive control signal time series as its local control signal time series.

[0167] Specifically, when issuing the predictive control signal time series, the predictive control signal time series is first divided into multiple predictive control signal time segments. The TCP transmission protocol is used to send the predictive control signal time segments to each fan controller in batches. This ensures that the predictive control signal time segments reach each fan controller accurately while avoiding loss or delay of the predictive control signal time series due to network congestion. Each fan controller caches the predictive control signal time segments locally and then reassembles them into a local control signal time series. Each fan controller generates pre-execution data based on the local control signal time series and waits for the synchronization trigger command. By dividing the control command into pre-execution data and synchronization trigger command, each fan controller caches the pre-execution data in advance. The synchronization trigger command is decoupled from the pre-execution data and does not rely on the real-time network. This reduces the impact of real-time communication jitter during multi-fan airflow control and does not interrupt the control of each fan controller even if communication is momentarily interrupted.

[0168] S504: Synchronizes the global clock via the NTP protocol, and outputs the initial multi-point control signals synchronously at preset time points based on the local control signal time series using a local timer;

[0169] Specifically, the global clock is aligned via the NTP protocol over the network to establish a unified time base for each fan controller. Based on this unified time base, each fan controller triggers a synchronization command at a preset time point using a local timer. The NTP protocol is a network time synchronization protocol, which ensures the time alignment of coordinated airflow changes. Each fan controller executes pre-execution data and outputs an initial multi-point control signal. This initial multi-point control signal is output in the form of a predicted control signal time series, and the initial multi-point control signal is f. i -1 (V k Each fan controller can achieve millisecond-level synchronous control, adapting to the high-frequency wind speed changes required by time-varying airflow. The output error of each fan controller is within ±1%, meeting the high consistency output requirements of multi-fan airflow control.

[0170] S505: Real-time measurement of actual wind speed, comparison with target wind speed time series, generation of compensation multi-point control signal based on PI / PID feedback adjustment algorithm, superimposed with initial multi-point control signal to output dynamic multi-point control signal.

[0171] Specifically, each fan or area is equipped with a wind speed sensor to measure the actual wind speed V of each fan and area in real time. meas Calculate the actual wind speed error ΔV = V between the actual wind speed and the target wind speed at the sampling point. k -V measBased on the PI / PID feedback control algorithm, a compensated multi-point control signal ΔPWM is generated. After the compensated multi-point control signal is fed back to each fan controller, each fan controller superimposes the compensated multi-point control signal with the initial multi-point control signal to output a dynamic multi-point control signal PWM. a PWM a =f i -1 (V k +ΔPWM; Based on the error pattern between the actual wind speed and the target wind speed, it feeds back to each fan controller in real time and outputs a multi-point control signal that can be dynamically adjusted to achieve dynamic and precise compensation for the airflow control of multiple fans, thereby counteracting the performance degradation caused by fan motor aging or environmental disturbances and ensuring long-term consistent output of multiple fans.

[0172] In this embodiment of the application, the wind farm testing platform further includes:

[0173] The mounting frame and the two-dimensional cross-flow module are mounted on the frame. The mounting frame adopts a rectangular frame structure and is equipped with a two-dimensional cross-flow module. The two-dimensional cross-flow module includes several cross-flow axes arranged in a crisscross pattern. Each cross-flow axis is equipped with multiple flow blades. The longitudinally arranged flow blades and the transversely arranged flow blades form an air gap for air outlet. A fan is located directly behind the intersection of each longitudinally arranged flow axis and each transversely arranged flow axis. The external space directly in front of the two-dimensional cross-flow module forms a test area.

[0174] In this embodiment, the longitudinally arranged spoiler shafts and the transversely arranged spoiler shafts are arranged in layers, and multiple spoiler blades are arranged alternately along the axial direction of the spoiler shafts. The shape of the spoiler blades is square, rhomboid or X-shaped.

[0175] In this embodiment of the application, an encoder is provided on the turbulence shaft. The encoder measures the rotation angle of the turbulence shaft in real time. Each turbulence shaft is connected to a servo motor. The servo motor is started or stopped so that the turbulence shaft is in a turbulence state or a flow guiding state.

[0176] In this embodiment of the application, the control platform is equipped with a spoiler shaft speed control module and a fan speed control module. The spoiler shaft speed control module controls the speed of each spoiler shaft individually, and the fan speed control module controls the speed of each fan individually.

[0177] In this embodiment of the application, the control platform is further used for:

[0178] Obtain specific wind environment conditions for a predefined application scenario, and obtain the specific wind...

[0179] Obtain specific wind environment conditions for a preset application scenario, and obtain simulation instructions for those specific wind environment conditions;

[0180] The simulation command is updated into an execution command and transmitted to the spoiler shaft speed control module and the fan speed control module;

[0181] The fan speed control module receives and executes commands, controls each fan in zones, and sets it to be in a stationary state, a low speed state, or a high speed state according to a time sequence, thereby creating a wind field in the test area.

[0182] The deflector speed control module receives and executes commands, and controls each deflector in the two-dimensional cross deflector module in a zone. It sets the deflector in a guiding state or a deflector state according to a time sequence, thereby disturbing or guiding the airflow generated by the fan.

[0183] Obtain the time-varying curves of wind speed and turbulence intensity in the test area, and determine whether the wind wall can reproduce the specific wind environment conditions of the preset application scenario; if it can reproduce, the wind wall is applied to subsequent tests; if the specific wind environment conditions simulated by the wind wall have errors, return to S2, and re-update the simulation command to the execution command and transmit it to the turbulence shaft speed control module and the fan wind speed control module.

[0184] Compared with the prior art, this application has the following beneficial effects:

[0185] In this embodiment, an installation frame is included, on which a two-dimensional cross-flow turbulence module is installed. Fans are positioned directly behind the intersections of the longitudinally and transversely arranged turbulence axes within the two-dimensional cross-flow turbulence module. The two-dimensional cross-flow turbulence module and several fans are coordinated and controlled by a control platform to couple wind speed and turbulence intensity. The test area can be divided into zones according to experimental requirements. The control platform controls the operation of the two-dimensional cross-flow turbulence module and fans to achieve spatial regional turbulence intensity control and dynamically adjusts it according to time series. Multiple rotation modes are set for the turbulence axes, allowing them to rotate at a set speed or periodically open and close at a set frequency to form turbulence at different scales. This achieves active programmable turbulence control in space and constructs a complex wind field model with superimposed wind speed and turbulence gradients.

[0186] In this embodiment, an encoder is set on the spoiler shaft to control and monitor the rotation position of the spoiler blades in real time. When the spoiler shaft is in the flow guiding state, adjusting the relative position of the spoiler blades and the fan can guide and adjust the airflow direction. Several fans and two-dimensional cross spoiler modules work together to generate airflow that superimposes and interferes with each other, thereby forming a complex wind speed distribution field in the test area, which is suitable for simulating the atmospheric boundary layer or urban wind environment.

[0187] In this embodiment of the application, a complex wind field model is constructed by superimposing wind speed gradient and turbulence gradient.

[0188] Please refer to Figures 6-8. A wind field testing platform includes an installation frame 601 and a two-dimensional cross-flow disturbance module 2. The installation frame 601 adopts a rectangular frame structure, and the two-dimensional cross-flow disturbance module 2 is set on the installation frame 601. The external space directly in front of the two-dimensional cross-flow disturbance module 602 forms a test area.

[0189] The two-dimensional cross-flow scrambling module 602 includes several longitudinally and transversely arranged scrambling shafts 6022. The longitudinally arranged scrambling shafts 6022 and the transversely arranged scrambling shafts 6022 are arranged in layers. All longitudinally arranged scrambling shafts 6022 are located in the same layer, and the transversely arranged scrambling shafts 6022 are located in the same layer. Each scrambling shaft 6022 includes multiple fixedly arranged scrambling blades 23. The multiple scrambling blades 23 are arranged alternately along the axial direction of the scrambling shaft 6022. The shape of the scrambling blades 23 can be square, rhomboid, or X-shaped. Each scrambling shaft 6022 is driven individually by a servo motor 21 that passes through the mounting frame 601.

[0190] Specifically, two rows of deflector blades 23 are arranged opposite each other on each deflector shaft 6022. The two rows of deflector blades 23 are arranged alternately. The intersection of each longitudinally arranged deflector shaft 6022 and each transversely arranged deflector shaft 6022 is set as the intersection point. There is only one deflector blade 6023 between two adjacent intersection points. A fan 3 is arranged directly behind each intersection point. This arrangement can maximize the effect of the deflector blades 6023 on the airflow generated by each fan 3. However, the airflow generated by multiple fans 3 can pass through the same air gap, which can easily cause the airflow to overlap and interfere with each other.

[0191] A gap for airflow is formed between the longitudinally arranged baffle blades 6023 and the transversely arranged baffle blades 6023. A fan 3 is installed at each gap, and several fans 3 form a fan wall, or simply a wind wall. Several fans 603 face the test area. Each fan 603 is independently controlled by a drive motor, and the speed of each fan 603 can be set individually. The drive motor drives the blades of the fan 603 to rotate, generating airflow. Several fans 603 work together, and the airflow generated superimposes and interferes with each other, thus forming a complex wind speed distribution field in the test area.

[0192] An encoder is installed on the deflector shaft 6022, which measures the rotation angle of the deflector shaft 6022 in real time. The servo motor 21 is turned off or on to keep the deflector shaft 6022 in either a guiding or deflecting state. When the deflector shaft 6022 rotates, it is in a deflecting state, rotating periodically at a set speed or frequency to periodically disturb the airflow generated by the fan 603. When the deflector shaft 6022 is in a guiding state, the servo motor 21 can be used to adjust the deflector blades 6023 to a specific position to obstruct and guide the airflow generated by the fan 603. If the deflector blades 6023 and the fan 603 are in a deflecting state, the deflector shaft 6022 can be adjusted to a specific position to obstruct and guide the airflow generated by the fan 603. The airflow direction is vertical. Since the area of ​​the disturbance blade 23 is relatively small, it cannot completely block the fan 603. Part of the airflow generated by the fan 603 hits the disturbance blade 6023 and is blocked, thus changing the flow direction. A pressure gradient is formed around the disturbance blade 6023. When part of the airflow passes through the air gap of the disturbance blade 6023, it is affected by the air pressure and changes the flow direction. If the disturbance blade 6023 is parallel to the airflow direction generated by the fan 603, since the surface of the disturbance blade 6023 is consistent with the airflow direction, the airflow generated by the fan 603 can continue to flow smoothly along the baffle surface, and its airflow direction will not change significantly.

[0193] When the airflow generated by several fans 603 passes through the air gap of the two-dimensional cross-flow module 602, it will be blocked and guided by the rotating horizontal flow axis 6022 and the rotating vertical flow axis 6022, thus forming complex airflow disturbances. These airflow disturbances superimpose and intertwine to form a dense flow network, thereby changing the intensity and distribution of turbulence in the test area.

[0194] The control platform of this application embodiment can also input commands through a visual control device and visualize the output effect; the control module is equipped with a fan speed control platform, which individually controls the rotation speed of each fan 603, sets the fan 603 to be in a stationary or started state, and when the fan 603 is in the started state, it can be set to rotate at a low speed or at a high speed, thereby controlling the wind speed generated by each fan 603 in the test area.

[0195] The control platform is also equipped with a turbulence shaft speed control module, which independently controls the speed of the turbulence shaft 6022, setting the turbulence shaft 6022 to either a guiding state or a turbulence state. When the turbulence shaft 6022 is in the turbulence state, the intermittent mode of the turbulence shaft 6022 is adjusted, controlling the turbulence shaft 6022 to rotate at a set speed. The set speed can be set according to the test requirements. Alternatively, the turbulence shaft 6022 can be controlled to rotate periodically at a set frequency to generate pulsating turbulence of different frequencies and intensities. The set frequency period includes the start-up rotation period and the closing interval period of the turbulence shaft 6022, realizing dynamic, zoned, and reconfigurable turbulence control.

[0196] While maintaining the wind speed generated by the fan wind wall, the 6022 turbulence shaft can be adjusted to achieve high repeatability and fine control capability. It is suitable for multi-round, repeated comparative tests and is suitable for conducting fluid dynamics parameter sensitivity studies, model response evaluation, wind load, vibration and stability experiments, etc.

[0197] The control module operates in conjunction with the spoiler axis speed control module and the fan speed control module. The test personnel can input commands to the spoiler axis 6022 speed control module or the fan speed control module individually to adjust the speed of the spoiler axis 6022 in the two-dimensional cross spoiler module 602 or the speed of each fan 603, so as to achieve spatial decoupling of wind speed gradient and turbulence gradient, which can be used to conduct experimental simulation of the influence of specific variables. The test personnel can simultaneously input commands to the spoiler axis speed control module and the fan speed control module, so that the high wind speed area is combined with high disturbance to generate stronger turbulence, or the low wind speed area is kept with weak disturbance, to simulate the highly correlated "wind speed-turbulence" synergistic phenomenon in the atmosphere. The coupled control of wind speed gradient and turbulence gradient can realize the simulation of wind environment with the superposition of "wind speed gradient" and "turbulence gradient".

[0198] Among them, the spoiler axis speed control module and the fan wind speed control module need to have the ability to set partitions, schedule time and run automatic programs to simulate complex wind field structures and be suitable for various test models, such as UAV wind environment simulation, atmospheric boundary layer simulation and urban wind environment simulation.

[0199] Specifically, the test area can be divided into different regions according to the test requirements. The boundaries and parameters of the regions can be defined through a visual interface or parameter configuration file, dividing the area into upper layers, lower layers, boundary regions, etc. Independent parameters such as wind speed and turbulence intensity can be set for different regions. The wind speed and turbulence intensity of different regions can be dynamically adjusted by the two-dimensional cross-turbulence module 602 and fan 603 according to the time series to simulate the changes in wind speed and turbulence intensity over time. The control module can also be preset with a pre-set program that defines a complex wind field simulation process and automatically executes complex wind field simulation tasks.

[0200] Furthermore, the simulation of complex wind fields includes the simulation of vertical wind shear formed by controlling the upper fan 603 to rotate at high speed and the lower fan 603 to rotate at low speed; the simulation of turbulent gradient formed by controlling the upper spoiler axis 6022 to rotate at slow speed and the lower spoiler axis 6022 to rotate at fast speed; the simulation of local strong disturbance wind spots formed by controlling the rapid disturbance of the spoiler axis 6022 in a specific area; and the simulation of periodically changing the state of the spoiler blades 6023 to periodically disturb and simulate the pulsating turbulence in natural wind, such as sudden vortices and storm edge disturbances.

[0201] In one embodiment, the device described in this application is deployed in an urban building simulation environment to simulate the wind shear effect of an urban canyon.

[0202] The control module sets the upper fan 603 to high speed and outputs high wind speed, while the upper turbulence axis 6022 in the two-dimensional cross turbulence module 602 is set to rotate at low speed to maintain low turbulence. The lower fan 603 is set to low speed and outputs low wind speed, while the lower turbulence axis 6022 in the two-dimensional cross turbulence module 602 is set to high-speed disturbance to simulate turbulence caused by vehicle and pedestrian activities. By adjusting the speed of the fan 603 at different positions through the program, the wind shear intensity can be dynamically adjusted. By adjusting the speed of the turbulence axis 6022, the turbulence intensity can be dynamically adjusted.

[0203] The wind wall described in this application is used to simulate the vertical structure of the atmospheric boundary layer and to simulate the impact of different urban morphologies, such as buildings and vegetation, on the wind environment.

[0204] The control module sets the rotation speed of several fans 603 to increase layer by layer from bottom to top, simulating the speed gradient caused by the surface friction effect. That is, the wind speed near the ground is slowed down by buildings or vegetation, and the friction weakens as the height increases, so the wind speed increases. This artificially creates a wind speed gradient to simulate the typical wind shear phenomenon in the atmospheric boundary layer.

[0205] The control module sets the two-dimensional cross-turbulence module 602 to rotate at high speed on the lower turbulence axis 6022 and at low speed on the upper turbulence axis 6022. This conforms to the strong disturbance caused by rough elements such as buildings and vegetation near the ground, which generates high turbulence intensity. As the height increases, the disturbance weakens and the turbulence intensity decreases, simulating the vertical distribution characteristics of turbulence intensity.

[0206] An integrated turbulence-guided wind speed distribution control method, applied to the aforementioned integrated turbulence-guided wind speed distribution control wind wall, includes the following steps:

[0207] S6001: Obtain specific wind environment conditions for a preset application scenario and input simulation instructions for the specific wind environment conditions into the control module;

[0208] S6002: The control module updates the analog command into an execution command and transmits it to the spoiler shaft speed control module and the fan speed control module;

[0209] S6003: The fan speed control module receives and executes commands, controls each fan 603 in zones, and sets it to be in a stationary state, a low speed state, or a high speed state according to a time sequence to form a wind field in the test area.

[0210] S6004: The spoiler shaft speed control module receives and executes instructions, controls each spoiler shaft 6022 in sections, sets it to be in a spoiler state or a guide state according to a time sequence, and disturbs or guides the airflow generated by the fan 603.

[0211] S6005: Obtain the curves of wind speed and turbulence over time in the test area, and determine whether the wind wall reproduces the specific wind environment conditions of the preset application scenario; if the wind wall can simulate the real wind environment, then apply the wind wall to the subsequent test; if the specific wind environment conditions simulated by the wind wall have errors, return to S2 and re-adjust.

[0212] In this embodiment of the application, the water environment testing platform includes a testing module and a first acquisition module.

[0213] The test module includes a water tank and a fixed frame installed at one end of the water tank, a wave generator installed at the other end of the water tank, and a fan matrix installed on the fixed frame;

[0214] The first acquisition module is used to transmit the collected water change data, wind field data, and UAV attitude data from the test module to the control platform.

[0215] The first acquisition module includes a sensor monitoring unit, an attitude monitoring unit, and an infrared capture system. The sensor monitoring unit is used to monitor water changes in the pool and wind field data of the multi-fan matrix. The attitude monitoring unit is used to capture the UAV and obtain UAV attitude images through the infrared capture system.

[0216] The control platform is also used to connect with the energy sensors installed on the UAV, so as to combine water change data and wind field data, and dynamically output test plans based on the UAV attitude data obtained by the infrared capture system and the UAV remaining energy information obtained by the energy sensors.

[0217] In this embodiment, a transparent observation window is provided on the side wall of the pool, a temperature control unit is installed inside the pool, multiple laser rangefinders are spaced apart along the length of the pool, a water pump is installed on the side wall of the pool, and a camera and a laser scanner are installed above the pool.

[0218] In this embodiment of the application, the wave-making device includes hydraulic cylinders, a control platform is connected to the hydraulic cylinders, multiple hydraulic cylinders are provided, and the multiple hydraulic cylinders are spaced apart along the side wall of the pool away from the fixed frame. The telescopic ends of the multiple hydraulic cylinders are hinged with flaps, and the lower part of the flaps extends into the water.

[0219] In this embodiment of the application, the sensor monitoring unit includes multiple ultrasonic anemometers, which are fixedly installed above the water tank at equal intervals.

[0220] The attitude monitoring unit also includes multiple visual markers set on the UAV;

[0221] The first acquisition module also includes an infrared capture system, which includes an infrared light source and an infrared camera. The infrared light source is used to emit infrared light to illuminate visual markers on the UAV, and the infrared camera is used to capture the infrared light reflected from the markers.

[0222] In this embodiment of the application, the water environment testing platform further includes a display module.

[0223] The control platform is also used to analyze the acquired water body change data, wind field data, and UAV attitude data, and display them through the display module;

[0224] The control platform also includes a test mode generation module, which is used to pre-combine water change data and wind field data using a combination algorithm to generate multiple preset test schemes and store them as a set of preset test schemes.

[0225] In this embodiment of the application, the control platform is further used for:

[0226] Output the current test plan and convert it into test instructions, which are then passed to the test module for the drone to conduct flight tests.

[0227] The system receives real-time drone attitude images from the infrared capture system, extracts the drone attitude images, and determines whether the drone has a tendency to exit or enter the water. If the drone has a tendency to exit or enter the water, the system obtains the drone attitude when crossing the medium through the infrared capture system, obtains the force and speed change data of the drone when flying across the medium, and stores and analyzes it. If the drone does not have a tendency to exit or enter the water, the system executes the acquisition command.

[0228] Obtain the remaining energy information of the drone, determine whether the remaining energy of the drone can support continuous cross-medium flight tests. If the drone has sufficient remaining energy, output a new test plan as the current test plan, so that the drone can carry out a new round of test experiments; otherwise, the test experiment ends.

[0229] Please refer to Figures 9-13. The test module includes a water tank 101 and a fixed frame 103 installed at one end of the water tank 101. Wave-making equipment is installed at the other end of the water tank 101, and a fan matrix 102 is installed on the fixed frame 103.

[0230] The first acquisition module includes a sensor monitoring unit and an attitude monitoring unit. The sensor monitoring unit is configured to monitor water change data in the pool and wind field data of the fan matrix. The sensor monitoring unit includes an ultrasonic anemometer and a laser rangefinder. The laser rangefinder is arranged in the pool 101, and the ultrasonic anemometer is installed above the pool 101. The attitude monitoring unit includes an infrared capture system installed around the pool 101 to capture the UAV and acquire UAV attitude images. The first acquisition module transmits the acquired test data from the test module and UAV attitude data to the control platform.

[0231] The test data and UAV attitude images obtained by the control platform are displayed through the display module. The display module provides a host computer software interface or cloud API to facilitate viewing the real-time data collected during the test and the test process. The control platform dynamically allocates and prioritizes the hardware resources of the test module, such as the sensor monitoring units and infrared capture system deployed at corresponding positions in the water tank 101, to ensure the accuracy of sensor data acquisition and transmission. The platform also stores and analyzes the collected data and displays it in real time through the display module to assist testers in making quick judgments.

[0232] The water tank 101 is fixedly installed on the ground in a specific area. The length, width, and height of the water tank 101 can be adjusted according to the testing requirements. The inner wall of the water tank 101 is lined with corrosion-resistant stainless steel or composite materials. A transparent observation window 111 is provided on the side wall of the water tank 101 to facilitate the observation and recording of the underwater position and attitude of the UAV. Water with a specified salinity is introduced into the water tank 101 to simulate seawater. A temperature control unit is installed in the water tank 101 to regulate the water temperature, making the water temperature range from 5℃ to 35℃. A water flow pump is installed on the side wall of the water tank 101. The water flow pump generates a horizontal flow velocity of 0.1 to 1.0 m / s in the water of the water tank 101, and the water flow pump can continuously regulate the water flow velocity. The sensor monitoring unit also includes a flow meter, which is installed in the water tank 101 to monitor the water flow velocity.

[0233] The wave-making device includes hydraulic cylinders 104 and flaps 105. A control platform is connected to the hydraulic cylinders 104. The end walls at both ends of the upper part of the water tank 101 extend outwards to form mounting cavities 112. The side walls of the mounting cavities 112 are fixedly connected to the fixed ends of the hydraulic cylinders 104. Multiple hydraulic cylinders 104 and flaps 105 are provided. The specific number of hydraulic cylinders 104 and flaps 105 can be adjusted according to testing requirements, making the testing platform suitable for testing small or medium-sized cross-medium UAVs. Multiple hydraulic cylinders 104 are spaced apart along the side walls of the mounting cavities 112. Connecting ears are fixedly provided at the telescopic ends of the hydraulic cylinders 104. Mounting ears are fixedly provided on the upper part of the flaps 105 near the side of the hydraulic cylinders 104. The mounting ears on the multiple flaps 105 are respectively connected to the multiple hydraulic cylinders 104. The telescopic end connecting lug is hinged by a pin. The lower part of the flap 105 extends into the water. Multiple flaps 105 can move synchronously or individually through the hydraulic cylinder 104. By controlling the movement amplitude of the telescopic end of the hydraulic cylinder 104, the flaps 105 move against the water resistance, creating waves of different sizes in the pool 101. The sensor monitoring unit also includes a laser scanner and a camera. The wave pattern generated in the pool 101 can be obtained by scanning the water in the pool 101 with the laser scanner. A camera is also installed on the pool 101 to obtain the position of the flaps 105 in the pool 101 in real time. In this embodiment, the flaps 105 are set to simulate a wave height of 0.1 to 0.4 meters through the wave-making equipment, and the vibration frequency is adjusted to a sine wave or irregular wave of 0.5 to 2 Hz.

[0234] When the wave generated by the wave-making device is a sine wave, the control platform generates a sine wave signal, which drives the extension end of the hydraulic cylinder 104 to reciprocate according to a sine law, thereby driving the flapper 105 to disturb the water and form a sine wave.

[0235] When the wave generated by the wave-making device is an irregular wave, the control platform generates an irregular wave signal, controls the extension end of the hydraulic cylinder 104 to move, drives the flapper 105 to reciprocate in the water tank 101 to disturb the water, and obtains the position of the flapper 105 in real time to obtain the irregular water wave generated by the flapper 105. The irregular water wave can be decomposed into multiple simple harmonic waves of different frequencies and phases. After comparing the irregular water wave with the irregular wave signal, the movement of the hydraulic cylinder 104 is adjusted until the irregular water wave is close to the irregular wave signal, thus forming an irregular wave that simulates the real sea surface or water surface.

[0236] The mounting bracket 103 has a frame structure and can be made of aluminum alloy or carbon steel. The bottom of the mounting bracket 103 is fixed in the mounting cavity 112. The fan matrix 102 includes multiple fans arranged in a rectangular pattern. Each fan is individually controlled by a brushless DC motor. The control platform is electrically connected to the brushless DC motor and transmits adjustment signals to the brushless DC motor to perform single-point control of the fan, so that the fan matrix 102 creates a wind field on and above the water surface. The maximum power of each fan can be adjusted according to the test requirements. In this embodiment, the maximum power of the fan is set to 75W, and the wind speed adjustment range of each fan is set to 1m / s to 15m / s.

[0237] The control platform also includes a test mode generation module, which can pre-generate a variety of preset test schemes and store them as a set of preset test schemes. The fan matrix 102 controls the wind speed of the wind field generated above the water tank 101 through the control platform and stores the acquired wind field data as a wind field dataset. The control platform controls the wave height, wave shape, and water flow velocity of the water surface waves generated in the water tank 101 through wave-making equipment and stores the collected water change data as a water change dataset. The test mode generation module reads the wind field dataset and the water change dataset and uses a combination algorithm to generate a variety of preset test schemes, which facilitates real-time response and dynamic adjustment during UAV cross-media testing.

[0238] Specifically, the four parameters of wind speed, wave height, wave frequency, and current velocity are discretized using cluster analysis. Based on the actual distribution, intervals are divided, and wind speed, wave height, wave frequency, or current velocity are classified into three categories: low, medium, and high. All combinations of the four parameters are enumerated, and rules are set to select representative test scenarios. The selection rules include physical limitations, statistical frequency, extreme conditions, and industry engineering standards. Representative scenarios such as low wind-low waves-low current, medium wind-medium waves-medium current, high wind-high waves-high current, and high wind-low waves-low current are selected and stored as preset test schemes to simulate real sea or water surface environments.

[0239] The sensor monitoring unit includes multiple ultrasonic anemometers, which collectively detect the wind field distribution output by the fan matrix 102. These anemometers are spaced apart above the water tank 101 along its length and are supported and fixed above the water tank 101 by waterproof brackets. In this embodiment, the spacing between the ultrasonic anemometers is 50cm. Multiple laser rangefinders are also included, spaced apart along the length of the water tank 101. These rangefinders can detect changes in wave height at corresponding locations in the water tank 101. The sensor monitoring unit also includes a temperature sensor, a humidity sensor, and a water quality sensor. Since air temperature and humidity are relatively stable, temperature and humidity sensors are fixed near the fan matrix 102 to detect air temperature and humidity. Water quality sensors, temperature sensors, and humidity sensors are fixed in the water tank 101 using brackets, buoys, etc., to monitor water temperature, humidity, and water quality.

[0240] The attitude monitoring unit also includes multiple visual markers set on the UAV. The infrared capture system includes an infrared camera and an infrared light source. The infrared light source emits infrared light to illuminate the visual markers on the UAV, the infrared camera captures the infrared light reflected from the markers, and the control platform detects the position of the visual markers in the image. Combining the coordinate image information of multiple visual markers, the UAV's three-dimensional attitude is calculated using a computer vision algorithm employing the PnP algorithm. During testing, the UAV can freely perform climb, level flight, or descent. During the test, the infrared capture system acquires the UAV's attitude and transmits it to the control platform. When the infrared capture system detects that the UAV is about to leave or enter the water, it automatically executes a preset disturbance mode.

[0241] Among them, the preset disturbance modes include small fluctuations in fan speed and small vibrations of the flapping plate, which enhance the drone's ability to adapt to extreme uncertainties when flying across media.

[0242] Furthermore, the test module transmits instructions through the control platform to adjust the wave generator and fan matrix 102. The UAV conducts cross-medium flight tests under different test scenarios formed by different test schemes, executes preset disturbance modes, sets a reward function based on the UAV's cross-medium stability index, and trains through deep reinforcement learning to achieve adaptive test control based on flight feedback, supporting closed-loop optimization.

[0243] The test platform is also equipped with a preset safety protection mode. When the preset safety protection mode is executed, the drone's status or environmental parameters should meet the trigger conditions of the preset safety protection mode, such as low drone battery, sudden wind speed change, or wave height exceeding the set value. The control platform transmits a shutdown command to the wave generator and fan matrix 102 to stop the generation of wind and waves, thereby enabling the drone to resist interference from sudden failures or sudden environmental changes.

[0244] The control platforms all use industrial Ethernet or high-speed serial bus to connect brushless DC motors, water pumps, sensor monitoring units, and infrared capture systems.

[0245] The drone is equipped with a pressure sensor, accelerometer, torque sensor, and speedometer. The pressure sensor measures the hydrodynamic pressure distribution on the drone's surface, the accelerometer measures the drone's three-axis acceleration to assist in analyzing the impact of entering the water, the torque sensor measures three-dimensional force and torque for force analysis in complex flow fields, and the speedometer directly measures the relative velocity between the drone and the water flow. The control platform is connected to the pressure sensor, accelerometer, torque sensor, and speedometer on the drone to acquire real-time data on the force and velocity changes of the drone during cross-medium flight. The drone is also equipped with an energy sensor to collect information on the drone's remaining energy. Based on the drone's attitude and remaining energy information, the control platform can read the preset test scheme set pre-generated by the test mode generation module, select one of the preset test schemes for dynamic output, and convert the preset test scheme into test commands to be transmitted to the fan matrix 102 and wave generator, enabling the drone to conduct aerial, cross-medium, and underwater flight tests on this test platform.

[0246] Please refer to Figure 13. The drone testing method of this application embodiment is applied to the above-described drone testing system, and the specific steps include:

[0247] S1001: The control platform outputs the current test plan and converts the current test plan into test instructions, which are then transmitted to the test module for the UAV to conduct flight tests.

[0248] S1002-1: The infrared capture system acquires UAV attitude images in real time and transmits them to the control platform, which then extracts the UAV attitude images.

[0249] S1002-2 determines whether the drone has a tendency to exit or enter the water. If the drone has a tendency to exit or enter the water, proceed to S1003. If not, the infrared capture system executes the acquisition command.

[0250] S1003: After the UAV performs cross-medium flight, whether it enters or exits the water, the UAV attitude during the cross-medium flight is acquired by the infrared capture system and transmitted to the control platform. The control platform acquires and stores the force and speed change data of the UAV during the cross-medium flight.

[0251] S1004-1: The control platform acquires the remaining energy information of the drone.

[0252] S1004-2: Determine whether the UAV's remaining energy can support continuous cross-medium flight tests. If the UAV has sufficient remaining energy, proceed to S1001, where the control platform outputs a new test plan as the current test plan, enabling the UAV to conduct a new round of testing. If not, the test ends.

[0253] The method of this application embodiment simulates various wave patterns by setting up wave-generating equipment in a water tank to disturb the water and adjust the water flow velocity. The control platform regulates the fan matrix and adjusts the wind speed in real time to simulate real sea surface conditions. Through the first acquisition module, the test module, and the control platform, high-precision dynamic scene simulation is achieved, thereby providing a continuous cross-medium test environment for UAVs or drones with underwater-air cross-medium capabilities, from entering the water, exiting the water, to flying in the air, reducing R&D costs and improving the efficiency and accuracy of cross-medium flight tests.

[0254] The method in this application embodiment, by flexibly setting the size of the pool and different power and number of fans, makes the test platform suitable for small or medium-sized cross-medium UAVs; the control platform includes a test mode generation module, which can acquire different wind field datasets generated by the fan matrix and different wave data generated in the pool, and use a combination algorithm to generate a variety of preset test schemes, so that the control platform can dynamically adjust the cross-medium continuous test of the UAV according to the acquired UAV attitude and the remaining energy of the UAV, and realize closed-loop control test.

Claims

1. A drone testing system, comprising: The system includes: a wind field testing platform, an electromagnetic testing platform, a water environment testing platform, and a control platform. The wind field testing platform is used to conduct wind field tests on drones, and the wind field testing platform includes multiple multi-fan matrices; The electromagnetic testing platform is used to conduct electromagnetic environment testing on drones; The water environment testing platform is used to conduct water environment tests on drones; The control platform is used to perform any one of the following tests on the UAV, or multiple tests simultaneously, through the wind field test platform, electromagnetic test platform, and water environment test platform; The control platform communicates with both the wind field test platform and the electromagnetic test platform to construct a test area with multi-physics coupling for wind field testing and electromagnetic testing.

2. The system of claim 1, wherein, The wind field testing platform also includes a wind field monitoring unit, which includes an anemometer, pressure sensor, turbulence probe, temperature and humidity sensor, and PIV measurement device. The anemometer, pressure sensor, turbulence probe, temperature and humidity sensor, and PIV measurement device are respectively arranged in the test area to monitor the wind field data generated by the multi-fan matrix in real time. The wind field data includes airflow velocity, airflow distribution, environmental parameters, and turbulence parameters. The collected wind field data is transmitted to the control platform.

3. The system of claim 2, wherein, The electromagnetic environment testing platform includes an electromagnetic emission execution module, a third-party data acquisition module, and a safety protection module. The control platform communicates with the multi-fan matrix, the electromagnetic emission execution module, and the third acquisition module. The electromagnetic emission execution module and the multi-fan matrix in the wind field test platform form a multi-physics field coupled test area. The third acquisition module and the safety protection module are set in the test area. The third acquisition module includes an electromagnetic field monitoring unit.

4. The system according to claim 3, characterized in that, The electromagnetic launch execution module includes: The system comprises an alternating magnetic field emitting device, a static magnetic field emitting device, and an electromagnetic pulse emitting device. The alternating magnetic field emitting device includes several alternating magnetic field emitting units arranged above the test area. Each alternating magnetic field emitting unit is controlled by an independent circuit to generate alternating magnetic fields with different frequency bands and different emission modes. The static magnetic field emitting device includes several electromagnetic coils arranged above the test area. The current intensity of the electromagnetic coils is adjustable, generating a static magnetic field with adjustable magnetic field intensity. The electromagnetic pulse emitting device includes a high-energy EMP generator located below the test area, which instantaneously generates high-energy electromagnetic pulses at the flash level.

5. The system according to claim 4, characterized in that, The electromagnetic field monitoring unit includes an electromagnetic field strength sensor and a spectrum sensor. The electromagnetic field strength sensor and the spectrum sensor are respectively arranged in the test area to measure the electromagnetic field data generated by the electromagnetic transmission execution module. The electromagnetic field data includes the instantaneous and average field strength distribution, the transmission power of the electromagnetic transmission execution module and the validity of its interference waveform. The collected electromagnetic field data is transmitted to the control platform.

6. The system according to claim 5, characterized in that, The safety protection device includes a linkage protection unit and a pulse protection unit. The linkage protection unit includes multiple emergency stop switches and edge guardrails. The multiple emergency stop switches are respectively installed in the electromagnetic launch execution module and the multi-fan matrix. The edge guardrails are set around the test area. The emergency stop switches interact with the control platform through a hardware and software interlocking mechanism. The pulse protection unit includes a shielded chamber and a safety chamber. The shielded chamber is made of metal plates surrounding the test area. The four walls, floor and top of the shielded chamber are all made of electromagnetic shielding materials. The shielded chamber is equipped with wave-absorbing material walls and wedge-shaped wave absorbers. The safety chamber is located away from the shielded chamber. Operators conduct UAV tests remotely from the safety chamber.

7. The system according to claim 6, characterized in that, The third acquisition module also includes a visual motion capture unit, which is set up in the test area. When a drone is detected entering a certain section of the test area, the visual motion capture unit transmits the drone trajectory information data to the control platform.

8. The system according to claim 7, characterized in that, The control platform also includes: The system includes a sensor control unit, a fan matrix control unit, an electromagnetic emission control unit, and a host scheduling unit. The sensor control unit, fan matrix control unit, and electromagnetic emission control unit are connected to the third acquisition module and the multi-fan matrix electromagnetic emission execution module via a communication network. The sensor control unit transmits the wind field data of the multi-fan matrix and the electromagnetic field data of the electromagnetic emission execution module to the host scheduling unit.

9. The system according to claim 8, characterized in that, The upper-level scheduling unit includes a composite scenario script generation system. This system schedules fan matrix control commands and electromagnetic interference control commands on the same timeline and generates composite scenario scripts using a customized AI scheduling algorithm. The control platform then runs these composite scenario scripts to construct a test environment in the test area that superimposes the required airflow disturbances and electromagnetic interference.

10. The system according to claim 9, characterized in that, The control platform is also used for: Generate and run the drone test scenario script, and output fan matrix control commands, electromagnetic interference control commands, or wind field magnetic field superposition interference commands; The system can either enable a multi-fan matrix to receive fan matrix control commands individually to generate a wind field, or enable an electromagnetic emission execution module to receive electromagnetic interference control commands to generate an electromagnetic field, or enable the multi-fan matrix and the electromagnetic emission execution module to simultaneously receive wind field magnetic field superposition interference commands to generate a multi-physics field that superimposes wind field and electromagnetic field.

11. The system according to claim 1, characterized in that, The wind farm testing platform includes: The multi-point modeling module is used to sample the multi-point control signals and wind speed response of each fan, and generate a control signal wind speed fitting model and a control signal prediction model. The control signal prediction module is used to establish the target wind speed function based on the time-varying airflow characteristics to be generated, discretely generate the target wind speed time series, generate the predicted control signal time series based on the control signal prediction model, and send the predicted control signal time series to each fan controller using the TCP protocol. The wind speed feedback adjustment module includes a wind speed sensor for real-time measurement of actual wind speed, comparison with the target wind speed time series, and a PI / PID feedback adjustment algorithm to generate a compensation control signal, which is then superimposed with the initial multi-point control signal to output a dynamic multi-point control signal. The control platform also includes: The fan multi-point control module includes multiple fan controllers, which cache the predicted control signal time series as the local control signal time series. Each fan controller caches the predicted control signal time series sent in batches and outputs the initial multi-point control signal.

12. The system according to claim 11, characterized in that, The wind farm testing platform also includes: The local synchronization execution module includes a local timer, which is used to synchronize the global clock via the NTP protocol and output the initial multi-point control signals synchronously at preset time points based on the local control signal time series.

13. The system according to claim 12, characterized in that, The multi-point modeling module is also used for: The interpolation fitting is performed on the sampled data to obtain a control signal wind speed fitting model, and the control signal wind speed fitting model is V=f i (PWM), wherein V is the fan wind speed, PWM is the multi-point control signal, i is the fan index, f i is the mapping relationship between the multi-point control signal and the fan wind speed of each fan, and the control signal prediction model is PWM=f i -1 (V).

14. The system according to claim 13, characterized in that, The control signal prediction module is also used to: confirm the time-varying airflow waveform change curve according to the time-varying airflow characteristics to be generated, including sine wave, square wave and triangular wave, and establish the target wind speed function based on the time-varying airflow waveform change curve.

15. The system according to claim 14, characterized in that, When the time-varying airflow waveform is a sine wave, the target wind speed function for the continuous time variable t is V(t) = V 0,1 +A1sin(2πω1t+φ1), where V 0,1 Let A1 be the sinusoidal reference wind speed, ω1 be the sinusoidal wave amplitude, φ1 be the sinusoidal wave period frequency, and φ1 be the sinusoidal wave phase angle. When the time-varying airflow waveform is a square wave, the target wind speed function is V(t) = V 0,2 +A2sgn[sin(2πω2t+φ2)], where sgn(x) is the sign function; when x>0, sgn(x)=1; when x=0, sgn(x)=0; when x<0, sgn(x)=-1, V 0,2 Let A2 be the square wave reference wind speed, ω2 be the square wave amplitude, φ2 be the square wave period frequency, and φ2 be the square wave phase angle. When the time-varying airflow waveform curve is a triangular wave, the target wind speed function is: In the formula, V 0,3 A3 is the reference wind speed for the triangular wave, T is the triangular wave amplitude, and modT represents the position of the time variable within one period.

16. The system according to claim 15, characterized in that, The control signal prediction module is also used for: The target wind speed function is sampled at uniform time intervals Δt to obtain the target wind speed time series. Where k is the sampling point number, n is the total sequence length, k = 0, 1, 2, ..., n, V k V represents the target wind speed at the sampling point. k =V(kΔt); Substituting the target wind speed time series into the control signal prediction model, we obtain the predicted control signal time series. wherein PWM 0，k = f i -1 (V k ).

17. The system according to claim 16, characterized in that, The control signal prediction module is also used for: The predictive control signal time series is divided into multiple predictive control signal time segments, and the predictive control signal time segments are sent to each fan controller in batches using the TCP transmission protocol. Each fan controller is also used to cache the predicted control signal time series segments locally and then reassemble them into a local control signal time series in sequence.

18. The system according to claim 17, characterized in that, Fan controllers are also used for: Pre-execution data is generated based on the time series of local control signals, waiting for synchronous trigger instructions; The global clock is aligned via the NTP protocol over the network to establish a unified time base, and based on this unified time base, a synchronization trigger command is triggered at a preset time point using a local timer. The pre-execution data is used to synchronize the output of the initial multi-point control signal, and the airflow speed of the multi-fan changes synchronously with the output of the initial multi-point control signal. The initial multi-point control signal is f i -1 (V k ).

19. The system according to claim 18, characterized in that, The wind speed feedback adjustment module is also used for: Real-time measure actual wind speed V of each fan and each area meas , calculate actual wind speed error AV = V k - V meas , based on PI / PID feedback regulation algorithm, generate compensation multi-point control signal APWM, superimpose initial multi-point control signal to generate dynamic multi-point control signal PWM a , PWM a = f i -1 (V k )+ΔPWM.

20. The system according to claim 1, characterized in that, The wind farm testing platform also includes: The mounting frame and the two-dimensional cross-flow module are mounted on the frame. The mounting frame adopts a rectangular frame structure and is equipped with a two-dimensional cross-flow module. The two-dimensional cross-flow module includes several cross-flow axes arranged in a crisscross pattern. Each cross-flow axis is equipped with multiple flow blades. The longitudinally arranged flow blades and the transversely arranged flow blades form an air gap for air outlet. A fan is located directly behind the intersection of each longitudinally arranged flow axis and each transversely arranged flow axis. The external space directly in front of the two-dimensional cross-flow module forms a test area.

21. The system according to claim 20, characterized in that, The longitudinally arranged spoiler shafts and the transversely arranged spoiler shafts are arranged in layers, and multiple spoiler blades are arranged alternately along the axial direction of the spoiler shafts. The shape of the spoiler blades is square, rhomboid or X-shaped.

22. The system according to claim 21, characterized in that, An encoder is installed on the turbulence shaft, which measures the rotation angle of the turbulence shaft in real time. Each turbulence shaft is connected to a servo motor. The servo motor is turned on or off to put the turbulence shaft into a turbulence state or a flow guiding state.

23. The system according to claim 20, characterized in that, The control platform is equipped with a spoiler shaft speed control module and a fan speed control module. The spoiler shaft speed control module controls the speed of each spoiler shaft individually, and the fan speed control module controls the speed of each fan individually.

24. The system according to claim 23, characterized in that, The control platform is also used for: Obtain specific wind environment conditions for a preset application scenario, and obtain simulation instructions for those specific wind environment conditions; The simulation command is updated into an execution command and transmitted to the spoiler shaft speed control module and the fan speed control module; The fan speed control module receives and executes commands, controls each fan in zones, and sets it to be in a stationary state, a low speed state, or a high speed state according to a time sequence, thereby creating a wind field in the test area. The deflector speed control module receives and executes commands, and controls each deflector in the two-dimensional cross deflector module in a zone. It sets the deflector in a guiding state or a deflector state according to a time sequence, thereby disturbing or guiding the airflow generated by the fan. Obtain the time-varying curves of wind speed and turbulence intensity in the test area, and determine whether the wind wall can reproduce the specific wind environment conditions of the preset application scenario; if it can reproduce, the wind wall is applied to subsequent tests; if the specific wind environment conditions simulated by the wind wall have errors, return to S2, and re-update the simulation command to the execution command and transmit it to the turbulence shaft speed control module and the fan wind speed control module.

25. The system according to claim 1, characterized in that, The water environment testing platform includes a testing module and a first data acquisition module. The test module includes a water tank and a fixed frame installed at one end of the water tank, a wave generator installed at the other end of the water tank, and a fan matrix installed on the fixed frame; The first acquisition module is used to transmit the collected water change data, wind field data, and UAV attitude data from the test module to the control platform. The first acquisition module includes a sensor monitoring unit, an attitude monitoring unit, and an infrared capture system. The sensor monitoring unit is used to monitor water changes in the pool and wind field data of the multi-fan matrix. The attitude monitoring unit is used to capture the UAV and obtain UAV attitude images through the infrared capture system. The control platform is also used to connect with the energy sensors installed on the UAV, so as to combine water change data and wind field data, and dynamically output test plans based on the UAV attitude data obtained by the infrared capture system and the UAV remaining energy information obtained by the energy sensors.

26. The system according to claim 25, characterized in that, A transparent observation window is provided on the side wall of the pool. A temperature control unit is installed inside the pool. Multiple laser rangefinders are spaced apart along the length of the pool. A water pump is installed on the side wall of the pool. A camera and a laser scanner are installed above the pool.

27. The system according to claim 25, characterized in that, The wave-making device includes hydraulic cylinders, a control platform is connected to the hydraulic cylinders, and multiple hydraulic cylinders are provided. The multiple hydraulic cylinders are spaced apart along the side wall of the pool away from the fixed frame. The telescopic ends of the multiple hydraulic cylinders are hinged with flaps, and the lower part of the flaps extends into the water.

28. The system according to claim 27, characterized in that, The sensor monitoring unit includes multiple ultrasonic anemometers, which are fixedly installed above the water tank at equal intervals. The attitude monitoring unit also includes multiple visual markers set on the UAV; The first acquisition module also includes an infrared capture system, which includes an infrared light source and an infrared camera. The infrared light source is used to emit infrared light to illuminate visual markers on the UAV, and the infrared camera is used to capture the infrared light reflected from the markers.

29. The system according to claim 28, characterized in that, The water environment testing platform also includes a display module. The control platform is also used to analyze the acquired water body change data, wind field data, and UAV attitude data, and display them through the display module; The control platform also includes a test mode generation module, which is used to pre-combine water change data and wind field data using a combination algorithm to generate multiple preset test schemes and store them as a set of preset test schemes.

30. The system according to claim 29, characterized in that, The control platform is also used for: Output the current test plan and convert it into test instructions, which are then passed to the test module for the drone to conduct flight tests. The system receives real-time drone attitude images from the infrared capture system, extracts the drone attitude images, and determines whether the drone has a tendency to exit or enter the water. If the drone has a tendency to exit or enter the water, the system obtains the drone attitude when crossing the medium through the infrared capture system, obtains the force and speed change data of the drone when flying across the medium, and stores and analyzes it. If the drone does not have a tendency to exit or enter the water, the system executes the acquisition command. Obtain the remaining energy information of the drone, determine whether the remaining energy of the drone can support continuous cross-medium flight tests. If the drone has sufficient remaining energy, output a new test plan as the current test plan, so that the drone can carry out a new round of test experiments; otherwise, the test experiment ends.

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