An accurate unmanned aerial vehicle spraying droplet deposition verification device and a CFD model verification method thereof

Abstract

The application discloses a precise unmanned aerial vehicle spraying droplet deposition verification device and belongs to the technical field of agricultural equipment. The device can obtain unmanned aerial vehicle spraying droplet deposition results under different experimental conditions, and the experimental data can help train and verify a computational fluid dynamics (CFD) model, so that the CFD model can be used for analyzing droplet drift characteristics. The device comprises a device support, an unmanned aerial vehicle simulation spraying system, a spraying time control system, a deposition measurement device and a measurement environment control system. The application can obtain spraying experimental deposition under set experimental parameters (including a blade form of an unmanned aerial vehicle blade simulation system, a blade rotating speed, an environmental temperature and humidity, a wind wall wind speed, a height of a nozzle, a horizontal position of the unmanned aerial vehicle blade simulation system, a size of a deposition surface, a roughness, a spraying flow and a spraying time length and the like). The application greatly reduces experimental costs, and experimental data can truly reflect an unmanned aerial vehicle spraying droplet deposition process.

Description

Technical Field

[0001] This invention belongs to the field of agricultural equipment technology, specifically relating to a precise drone spray droplet deposition verification device. Background Technology

[0002] Unmanned aerial vehicle (UAV) spraying systems are a modern agricultural technology that combines UAVs (unmanned aerial vehicles) with agricultural spraying equipment for spraying pesticides, fertilizers, or other liquid chemicals in farmland. This technology has been widely adopted in agriculture because it offers the following advantages:

[0003] 1. Precision and efficiency: Drones can spray chemicals with high precision, ensuring that each area is treated appropriately, thereby improving crop productivity.

[0004] 2. Reduced labor costs: Compared with traditional manual spraying methods, drones can reduce labor costs because no manual operation is required.

[0005] 3. Avoid human contact: Some chemicals are harmful to the human body, and using drones can reduce farmers' exposure risks.

[0006] 4. High controllability: The drone spraying system can adjust the spray volume, altitude and speed in real time according to needs.

[0007] Rotor speed refers to the rotational speed of a drone's rotor (usually a propeller or blade). Rotor speed has a significant impact on the drone's stability, lift, and maneuverability. Rotor speed can be used to adjust the drone's lift, which is crucial for flight altitude and stability. By adjusting the rotor speed, the drone can control its forward or downward speed. Changes in rotor speed affect the drone's maneuverability, enabling various maneuvers such as ascent, descent, turning, and hovering.

[0008] Droplet drift is the most prominent problem in pesticide spraying. Solving droplet drift requires continuous experimentation and verification; however, the experimentation costs are high and it pollutes the environment. Currently, droplet deposition is mainly measured using water-sensitive paper, which has the following problems:

[0009] 1. The high cost of water-sensitive paper means that it needs to be replaced every time a test is conducted, which is very wasteful.

[0010] 2. The measurement accuracy of water-sensitive paper is problematic. Current technology estimates the droplet size based on the reaction imaging of water-sensitive paper, which results in a large error.

[0011] 3. The spray time control for sedimentation measurement in UAV spray simulation has a large error compared to the experiment, making it difficult to effectively control the duration.

[0012] Furthermore, when measuring the spraying time, some droplets drift in the space after the spraying stops and then fall. However, in the transient simulation calculation, the deposition amount is only calculated as the cumulative value of droplets falling on a certain plane, without calculating the droplets that fall in the space afterward. Therefore, there will be a large error between the measurement and simulation results.

[0013] Computational fluid dynamics (CFD) is a numerical simulation method used to study phenomena such as fluid flow, heat transfer, and mass transport. CFD models can be used to analyze droplet drift characteristics in drone-based pesticide spraying systems and verify deposition rates. Once a CFD model is built and numerical simulations are performed, it generates simulation results, such as droplet distribution and deposition patterns. These results can be used to validate actual observation data and further analyze droplet drift characteristics to ensure the efficiency and accuracy of pesticide spraying or other droplet transport processes.

[0014] When using drones for pesticide spraying, the downwash field generated by the drone rotors affects droplet drift. These factors should be combined with other parameters in a computational fluid dynamics (CFD) model to simulate and analyze the performance of the drone spraying system. Summary of the Invention

[0015] To address the problems in the prior art, this invention proposes a precise verification device for drone spray droplet deposition.

[0016] The technical solution of the present invention is as follows:

[0017] This invention first provides a precise verification device for drone spray droplet deposition, comprising:

[0018] Device support;

[0019] The drone simulation spraying system is installed on the top of the device support to simulate the working environment of drones and spray pesticides. It includes a drone propeller simulation system and a variable-height spraying device. The drone propeller simulation system is movably installed on the device support, and the spraying device is located below the drone propeller simulation system for pesticide spraying.

[0020] A spray time control system is used to control the spraying time of a spraying device;

[0021] A deposition measurement device, located below the spray device, is used to quantitatively determine the deposition of droplets. The deposition measurement device has a deposition surface.

[0022] Measurement and environmental control systems are used to detect and control environmental parameters.

[0023] According to an embodiment of the present invention, the UAV propeller simulation system includes a propeller support, a plurality of replaceable propellers disposed on the propeller support, and a guide rail system; the guide rail system includes an X-axis guide rail and a Y-axis guide rail, the X-axis guide rail being horizontally fixed to the top of the device support; the Y-axis guide rail is connected to the X-axis guide rail via an X-axis slider, and the entire Y-axis guide rail is movable along the X-axis; a Y-axis slider is disposed on the Y-axis guide rail and is movable along it, and the top of the propeller support is connected to the Y-axis slider; replaceable propellers are uniformly installed on the propeller support.

[0024] According to an embodiment of the present invention, the spraying device includes a pesticide storage tank, a flow pump and a nozzle connected sequentially by pipes; wherein the height of the nozzle is adjustable and is always located below the UAV propeller simulation system.

[0025] According to an embodiment of the present invention, the spray timing control system includes upper and lower shielding discs, a disc reciprocating movement device, and a timer; wherein, the timer is an infrared sensing timer, comprising an infrared emitting and receiving tube disposed at the nozzle, which emits infrared light of a certain frequency. When the infrared light irradiates the upper shielding disc and is diffusely reflected and received by the infrared emitting and receiving tube, the infrared sensing timer stops timing; if the infrared emitting and receiving tube does not receive a laser signal, timing continues; the disc reciprocating movement device is used to drive the upper and lower shielding discs to perform reciprocating synchronous movement; wherein, the height distance between the upper shielding disc and the nozzle is 0.5-1 cm; the height distance between the lower shielding disc and the deposition surface of the deposition measurement device is 0.5-1 cm.

[0026] According to an embodiment of the present invention, the deposition measurement device is an analytical balance, which is provided with a replaceable deposition surface; the analytical balance measures the amount of drug deposition on the deposition surface.

[0027] According to an embodiment of the present invention, the measurement environment control system includes:

[0028] Temperature and humidity sensors are used to detect ambient temperature and humidity data;

[0029] Humidifiers are used to regulate ambient humidity.

[0030] Air conditioning is used to regulate ambient temperature;

[0031] Wind walls are used to simulate natural wind.

[0032] The control center is used to control the humidifier and air conditioner to maintain the ambient temperature and humidity at the set values ​​based on the monitoring data of the temperature and humidity sensors; the control center is also used to control the operation of the wind wall, the drone simulation spraying system, the spray time control system and collect the measurement data of the deposition measurement device.

[0033] The present invention also provides a CFD model verification method based on the aforementioned UAV spray droplet deposition verification device, which includes the following steps:

[0034] S1. Select the blade type of the UAV blade simulation system as needed, and set the required blade speed, ambient temperature and humidity, and wind speed of the wind wall; adjust the nozzle height and the horizontal position of the UAV blade simulation system to the required simulation requirements; adjust the size and roughness of the deposition surface; set the spray flow rate and spray duration;

[0035] S2. The control center controls the humidifier, air conditioner, wind wall, UAV propeller simulation system, spray device, and spray time control system to work according to the set values ​​in S1. Among them, the wind wall simulates the required natural wind, the UAV propeller simulation system simulates the required UAV downwash flow field, the spray device sprays pesticides, and the spray time control system achieves high-precision spray time control.

[0036] S3. The control center collects measurement data from the sedimentation measurement device and calculates the experimental sedimentation amount;

[0037] S4. Pass the obtained experimental deposition amount and the parameters set in S1 to the CFD model. The CFD model simulates the deposition amount according to the set parameters. If the difference between the simulated deposition amount and the experimental deposition amount is less than the set range, the CFD model is successfully verified and can be used to analyze the droplet drift characteristics; otherwise, the CFD model verification fails. Adjust the parameters of the CFD model and repeat S4 until the verification is successful.

[0038] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0039] (1) The present invention adopts a dual verification method of a motor-driven reciprocating shielding disc and an infrared sensor timing, which overcomes the inconsistency of shielding time in manual operation and thus achieves precise control of the total duration of fog droplet deposition.

[0040] (2) The present invention adopts a combination of a reciprocating shielding disk and an infrared induction timer to overcome the problem that the continuous falling of mist droplets in the space during the spraying process affects the total amount of deposition and causes the simulation calculation results to be distorted, thereby enabling accurate verification of the deposition amount calculated by the CFD model.

[0041] (3) By adopting the method of automatically generating geometric models and automatically setting simulation parameters, the repetitive labor problem of manual modeling is overcome, thereby solving the problem of CFD simulation calculation of UAV spraying process under multiple factors, especially the influence of temperature and humidity on spray deposition. Attached Figure Description

[0042] Figure 1 A schematic diagram of the overall structure of the drone spray droplet deposition verification device;

[0043] Figure 2 A schematic diagram of a reciprocating double-layer shielding disk;

[0044] Figure 3 This is a schematic diagram of the variable height nozzle device;

[0045] Figure 4 This is a schematic diagram of the guide rail system.

[0046] Figure 5 Flowchart for verifying the CFD model. Detailed Implementation

[0047] The present invention will be further described and illustrated below with reference to specific embodiments. The embodiments described are merely examples of the content of this disclosure and do not limit the scope of the invention. The technical features of each embodiment in the present invention can be combined accordingly, provided that there is no mutual conflict.

[0048] The UAV spray droplet deposition verification device provided by this invention can obtain the spray experimental deposition volume under set experimental parameters (including the blade type, blade rotation speed, ambient temperature and humidity, wind wall speed, nozzle height, horizontal position of the UAV blade simulation system, deposition surface size, roughness, spray flow rate, and spray duration, etc.), which can then be used to construct, train, and verify computational fluid dynamics (CFD) models. If the deposition volume obtained by the constructed and trained CFD model under multiple sets of preset experimental parameters is close to the deposition volume obtained by the verification device of this invention, then the CFD model is considered to be usable for subsequent UAV droplet drift characteristic analysis (i.e., successful verification). If the deposition volume obtained under one or more sets of preset experimental parameters differs significantly, the CFD model needs to be adjusted until the adjusted model successfully passes verification.

[0049] Computational fluid dynamics (CFD) is a numerical simulation method used to study phenomena such as fluid flow, heat transfer, and mass transport. CFD model building is a well-known technique in the field. The initial model building for a CFD model used to analyze the droplet drift characteristics of unmanned aerial vehicles (UAVs) generally includes the following process:

[0050] 1. Geometric Modeling: To build a CFD model, it is first necessary to create a single-blade spray geometry model, including the blades and the deposition surface.

[0051] 2. Discrete Mesh: After establishing the geometric model, it needs to be discretized into a finite number of discrete elements or meshes. These meshes will be used to describe the physical properties of airflow and droplet transport.

[0052] 3. Physical parameter setting: Provide the necessary physical parameters for the CFD model, such as air temperature and humidity, wind speed, and fog droplet properties. These parameters will be used to simulate the required environmental conditions.

[0053] In addition, CFD models should consider the following influencing factors to more accurately simulate droplet drift characteristics:

[0054] 1. Environmental parameters: The model needs to consider ambient temperature, humidity, wind speed and wind direction, as these factors affect the transport and deposition of fog droplets.

[0055] 2. Nozzle height and direction: The height and direction of the nozzle affect the location and direction of droplet release. These parameters should be included in the model.

[0056] 3. Spray flow rate and spray duration: The flow rate and spray duration of the spray device will affect the number and speed of droplet release, so they should also be taken into account.

[0057] 4. Deposition surface characteristics: The size and roughness of the deposition surface have a significant impact on the droplet deposition rate. These characteristics should be included in the model.

[0058] CFD simulation calculations: Geometric and physical parameters are modified using the generated journal file. Running the journal file automatically generates the corresponding mesh and CFD model. This model uses mathematical equations and computational methods to simulate airflow, droplet transport, and deposition. The model considers all the above parameters and performs numerical simulations based on them to predict droplet behavior and deposition rates.

[0059] Once the model is built and numerical simulations are performed, it will generate simulation results, such as droplet distribution and deposition. These results can be used to validate actual observation data and further analyze droplet drift characteristics to ensure the efficiency and accuracy of pesticide spraying or other droplet transport processes.

[0060] like Figure 1-4 The diagram shown is a schematic representation of the drone spray droplet deposition verification device constructed according to the present invention. The device mainly includes: a device support frame, a drone simulated spraying system, a spray time control system, and a deposition measurement device. The device support frame serves as the supporting structure for the entire device.

[0061] The drone simulation spraying system is installed on top of the device support to simulate the working environment of drones and spray pesticides. It includes a drone propeller simulation system and a spraying device. The drone propeller simulation system is movably installed on the device support, and the spraying device is located below the drone propeller simulation system for pesticide spraying.

[0062] Among them, such as Figure 1As shown, the spraying device includes a pesticide storage tank, a flow pump, and a nozzle connected sequentially by pipes; wherein the height of the nozzle is adjustable and it is always located below the drone propeller simulation system.

[0063] like Figure 4 As shown, the UAV propeller simulation system includes a propeller support, several replaceable propellers mounted on the propeller support, and a guide rail system. The guide rail system includes an X-axis guide rail and a Y-axis guide rail. The X-axis guide rail is horizontally fixed to the top of the device support. The Y-axis guide rail is connected to the X-axis guide rail via an X-axis slider, and the entire Y-axis guide rail can move along the X-axis. A Y-axis slider that can move along the Y-axis guide rail is provided on the Y-axis guide rail, and the top of the propeller support is connected to the Y-axis slider. Replaceable propellers are evenly mounted on the propeller support.

[0064] The spray time control system of the present invention is used to control the spray time of a spraying device. For example... Figure 2 and 3 As shown, the spray timing control system includes upper and lower shielding discs, a disc reciprocating movement device, and a timer. The timer is a normally closed inductive timer located at the nozzle. The infrared inductive timer includes a pair of infrared emitting and receiving tubes. The emitting tubes emit infrared light of a certain frequency. When the detection direction encounters an obstacle (shielding disc), the infrared light is diffusely reflected back and received by the receiving tubes, causing the infrared inductive timer to start or stop timing. The disc reciprocating movement device drives the upper and lower shielding discs to reciprocate synchronously. The height distance between the upper shielding disc and the nozzle is 0.5-1 cm; the height distance between the lower shielding disc and the deposition surface of the deposition measurement device is 0.5-1 cm.

[0065] The deposition measurement device is located below the spray device and is used to quantitatively determine the deposition of droplets. The deposition measurement device has a deposition surface. In this embodiment, the deposition measurement device is an analytical balance, which is provided with a replaceable deposition surface. The analytical balance measures the amount of drug deposited on the deposition surface.

[0066] The measurement and environmental control system is used to detect and control environmental parameters. It includes: a humidifier for regulating ambient humidity, a temperature and humidity sensor for detecting ambient temperature and humidity data, an air conditioner for regulating ambient temperature, a windbreak for simulating natural wind, and a control center. The control center controls the humidifier and air conditioner based on the monitoring data from the temperature and humidity sensor to maintain the ambient temperature and humidity at set values. The control center also controls the operation of the windbreak, the drone-simulated spraying system, and the spray timing control system, and collects measurement data from the deposition measurement device.

[0067] In a specific example of the present invention, such as Figure 1The wind wall 11, composed of 3x6 individual 12cm*12cm high-powered fans, simulates natural wind, producing a stable and uniform breeze with adjustable speed. It can also generate a stepped wind with a speed gradient to simulate natural wind. The reciprocating double-layer shielding disc 1 helps to precisely control the drone's spraying time. The variable-height nozzle device 2 adjusts the nozzle height. The drone propeller 10 has an adjustable center position, manually adjustable via the moving guide rail 9, allowing for manual adjustment of the relative position of the propellers and providing a high degree of freedom to simulate various drone downwash flow fields. The analytical balance 3 transmits the spray quality difference to the controller in a timely manner; the humidifier 4 regulates the ambient humidity; the flow pump 5 provides flow to the nozzles; the control center 6 collects information and issues control commands; the temperature and humidity sensor 7 detects the ambient temperature and humidity and feeds it back to the control center; the air conditioner 8 regulates temperature and humidity, working in conjunction with the humidifier to adjust the ambient temperature and humidity. The drone propeller 10 can provide different downwash flow fields.

[0068] like Figure 2 In the preferred embodiment, the reciprocating double-layer shielding disc 1 has a specific structure where one end of the rocker arm 1-8 is connected to the motor 1-9, and the other end of the rocker arm 1-8 is provided with a rolling bearing 1-7. The connecting rod 1-6 has a sliding groove inside along its length, and the rolling bearing 1-7 is fitted inside the connecting rod 1-6 and can slide along the sliding groove. The connecting rod 1-6 is perpendicularly connected to the rack 1-2, and the connecting rod 1-6, rack 1-2, support rod 1-4, and disc 1-5 are fixedly connected. The sliding bearing 1-3 and gear 1-1 are fixed. Motor 1-9 drives rocker arm 1-8 to rotate, rolling bearing 1-7 drives connecting rod 1-6 to reciprocate, rack 1-2 meshes with gear 1-1 and reciprocates through sliding bearing 1-3; connecting rod 1-6, rack 1-2, support rod 1-4, and blocking disc 1-5 reciprocate left and right under the action of rocker arm 1-8, with a reciprocating distance of 35cm. The disc diameters are 15cm and 20cm, the disc height is 3cm, and the wall thickness is 0.5cm. Rack 1-2 slides left and right along the direction of sliding bearing 1-3, and the sliding distance limit is exactly the limit of the reciprocating disc stroke; gear 1-1 meshes tightly with rack 1-2.

[0069] The speed of the reciprocating disk is adjusted by controlling the current through pulse width modulation. The speed is fastest when it is withdrawn or blocked. Its motion stroke function is: X=ksin(ωt+α)X represents the motion stroke, k represents the motion speed, ω represents the angular velocity, α represents the initial angular velocity, and t represents the time in seconds.

[0070] like Figure 3The variable-height spray device 2 can adjust the nozzle height and spray flow rate, and also includes an infrared sensor timer 2-6. The infrared sensor timer 2-6 contains an infrared emitting and receiving tube located at the nozzle. It emits infrared light of a certain frequency. When the infrared light shines on the upper shielding disc, it undergoes diffuse reflection and is received by the receiving tube, at which point the infrared sensor timer stops. That is, when the infrared light shines on the shielding disc, the timer stops; when the infrared light leaves the disc, the timer starts; and when it returns to the disc, the timer ends. The fixed base 2-1 mainly serves to fix the hollow rod 2-2. Tightening the switch 2-3 helps adjust the extension distance of the movable rod 2-4. The movable rod 2-4 is fixedly connected to the infrared sensor timer 2-6 and the nozzle 2-5. The pipe 2-7 connects to the nozzle 2-5. The movable rod 2-4 can move up or down to adjust the height of the nozzle 2-5.

[0071] Figure 4 The movable guide rail 9 enables adjustment of the drone propeller's forward, backward, left, and right planar positions, allowing for manual adjustment as needed. The X-axis guide rail 9-2 is horizontally fixed to the top of the device bracket; the Y-axis guide rail is connected to the X-axis guide rail 9-2 via an X-axis slider 9-1, and the Y-axis guide rail 9-3 can move along the X-axis; a Y-axis slider 9-4 is mounted on the Y-axis guide rail 9-3, and the top 9-5 of the propeller bracket is connected to the Y-axis slider 9-4; replaceable propellers are evenly installed on the propeller bracket, and the drone's planar coordinates are precisely positioned in conjunction with the drone connecting rod 9-5.

[0072] Figure 5 To verify the CFD model flowchart, the following steps were taken: First, the blade geometry and position information, deposition surface size, and other parameters were input into the modeling software's journal file (file 1) to automatically complete the modeling and mesh generation. Then, the mesh was imported, and parameters such as blade rotation speed, temperature and humidity, wind wall velocity, nozzle spatial position, spray flow rate, deposition surface roughness, ambient temperature, humidity, and spray duration were written into the computational fluid dynamics software's journal file (file 2). Iterative calculations were then performed. The simulated deposition volume was compared with the average of three measured deposition volumes, and the error was checked to see if it was less than 8%. If it was greater than 8%, the geometric mesh was optimized, and other relevant parameters such as the turbulence model were adjusted. If it was less than 8%, the CFD model was established, and more simulations were performed under different environmental conditions based on this model.

[0073] Example 1:

[0074] Set the wind speed of the wind wall to 1 m / s, the drone propeller speed to 2500 rpm, and the reciprocating time of the disc to 3 seconds. At this time, the disc is positioned below the nozzle. Turn on the flow pump. After 2 seconds when the nozzle flow stabilizes, the double-layer shielding disc motor turns on. The disc quickly moves away from below the nozzle, then slows down and quickly reciprocates back to below the nozzle. The induction timer performs timing calibration, and the flow pump turns off. The timer transmitted the specific time (2.95s) and the measured weight of the fog droplets (0.72g) to the control center. Then, the geometric data, including the UAV propeller center position (0,0,0.85) and propeller spacing (0.25m), were input into the modeling software's journal file 1. Running journal file 1 automatically generated the geometric structure and exported the mesh model. Next, the following parameters were transmitted to the CFD model via the computational fluid dynamics software's journal file 2: temperature 299K, relative humidity 66.5%, nozzle height 0.65m, flow rate 0.105kg / s, rotation speed 2500rpm, boundary wind speed 1m / s, calculation time 2.95s, and deposition surface size 11cm*11cm with a roughness Ra = 0.055mm. The calculated deposition amount was 0.68g. Comparison with the deposition amount calculated by the control center showed an error of 5.56%, less than 8%, indicating successful verification. The model used is suitable for analyzing fog droplet drift characteristics.

[0075] Example 2:

[0076] Set the wind speed of the wind wall to 2 m / s, the drone propeller speed to 2700 rpm, and the disk reciprocating time to 3 seconds. At this time, the disk is positioned below the nozzle. Turn on the flow pump. After the nozzle flow stabilizes for 2 seconds, the double-layer shielding disk motor turns on, and the disk quickly moves away from below the nozzle. Then, it slows down and quickly reciprocates back to below the nozzle. The normally closed inductive timer performs timing calibration, and the flow pump turns off. The timer transmitted the specific time 3.15s to the control center, and the measured weight of the droplet deposition 0.45g was also transmitted to the control center. Then, the geometric data such as the z-center position of the UAV blades (0,0,0.85) and the blade spacing 0.30m were input into the journal file 1 of the modeling software. Running journal file 1 automatically generated the geometric structure and exported the mesh model. Then, the temperature 296K, relative humidity 55.8%, nozzle height 0.75m, flow rate 0.105kg / s, rotation speed 2700rpm, boundary wind speed 2m / s, calculation time 3.15s, and deposition surface size 10cm*10cm, roughness Ra=0.025mm were transmitted to the CFD model through the journal file 2 of the computational fluid dynamics software for calculation. The calculated deposition amount was 0.53g. The difference between the deposition amount calculated by the control center and the actual deposition amount was 17.7%, which is greater than 8%. The local mesh of the UAV propeller rotation area was optimized and the CFD model was recalculated. The deposition amount was calculated to be 0.47, with an error of 4.4%, which is less than 8%. This means that the model used is suitable for analyzing droplet drift characteristics.

[0077] The above-described embodiments are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. Those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A precise UAV spray droplet deposition verification device, characterized in that... include: Device support; The drone simulation spraying system is installed on the top of the device support to simulate the working environment of drones and spray pesticides. It includes a drone propeller simulation system and a spraying device that can change height. The drone propeller simulation system is installed on the device support in a movable manner, and the spraying device is located below the drone propeller simulation system for pesticide spraying. A spray time control system is used to control the spraying time of a spraying device; A deposition measurement device, located below the spray device, is used to quantitatively determine the deposition of droplets. The deposition measurement device has a deposition surface. Measurement and environmental control systems are used to detect and control environmental parameters; The spray timing control system includes upper and lower shielding discs, a disc reciprocating movement device, and a timer. The timer is an infrared sensor timer, comprising an infrared emitting and receiving tube positioned at the nozzle. It emits infrared light of a specific frequency. When the infrared light shines on the upper shielding disc, diffuse reflection occurs, and the light is received by the infrared emitting and receiving tube, at which point the infrared sensor timer stops. If the infrared emitting and receiving tube does not receive a laser signal, timing continues. The disc reciprocating movement device drives the upper and lower shielding discs in synchronous reciprocating motion. The height distance between the upper shielding disc and the nozzle is 0.5-1 cm; the height distance between the lower shielding disc and the deposition surface of the deposition measurement device is 0.5-1 cm.

2. The precise UAV spray droplet deposition verification device according to claim 1, characterized in that, The aforementioned UAV propeller simulation system includes a propeller support, several replaceable propellers mounted on the propeller support, and a guide rail system. The guide rail system includes an X-axis guide rail and a Y-axis guide rail. The X-axis guide rail is horizontally fixed to the top of the device support. The Y-axis guide rail is connected to the X-axis guide rail via an X-axis slider, and the entire Y-axis guide rail can move along the X-axis. A Y-axis slider that can move along the Y-axis guide rail is provided on the Y-axis guide rail, and the top of the propeller support is connected to the Y-axis slider. Replaceable propellers are evenly mounted on the propeller support.

3. The precise UAV spray droplet deposition verification device according to claim 1, characterized in that, The spraying device includes a pesticide storage tank, a flow pump, and a nozzle connected sequentially by pipes; wherein the height of the nozzle is adjustable and is always located below the drone propeller simulation system.

4. The precise UAV spray droplet deposition verification device according to claim 1, characterized in that, The deposition measurement device is an analytical balance, which is equipped with a replaceable deposition surface; the analytical balance measures the amount of drug deposition on the deposition surface.

5. The precise UAV spray droplet deposition verification device according to claim 1, characterized in that, The measurement environment control system includes: Temperature and humidity sensors are used to detect ambient temperature and humidity data; Humidifiers are used to regulate ambient humidity. Air conditioning is used to regulate ambient temperature; Wind walls are used to simulate natural wind. The control center is used to control the humidifier and air conditioner to maintain the ambient temperature and humidity at the set values ​​based on the monitoring data of the temperature and humidity sensors; the control center is also used to control the operation of the wind wall, the drone simulation spraying system, the spray time control system and collect the measurement data of the deposition measurement device.

6. A CFD model verification method based on the UAV spray droplet deposition verification device of claim 5, characterized in that... Includes the following steps: S1. Select the blade type of the UAV blade simulation system as needed, and set the required blade speed, ambient temperature and humidity, and wind speed of the wind wall; adjust the nozzle height and the horizontal position of the UAV blade simulation system to the required simulation requirements; adjust the size and roughness of the deposition surface; set the spray flow rate and spray duration; S2. The control center controls the humidifier, air conditioner, wind wall, UAV propeller simulation system, spray device, and spray time control system to work according to the set values ​​in S1. Among them, the wind wall simulates the required natural wind, the UAV propeller simulation system simulates the required UAV downwash flow field, the spray device sprays pesticides, and the spray time control system achieves high-precision spray time control. S3. The control center collects measurement data from the sedimentation measurement device and calculates the experimental sedimentation amount; S4. Pass the obtained experimental deposition amount and the parameters set in S1 to the CFD model. The CFD model simulates the deposition amount according to the set parameters. If the difference between the simulated deposition amount and the experimental deposition amount is less than the set range, the CFD model is successfully verified and can be used to analyze the droplet drift characteristics; otherwise, the CFD model verification fails. Adjust the parameters of the CFD model and repeat S4 until the verification is successful.

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