Agricultural UAV material spreading performance detection system and operation method

Abstract

The present invention relates to the fields of agricultural production and drone control technology, and provides a system for detecting the material spreading performance of an agricultural drone and its operating method. The system comprises: a drone platform for controlling the drone's motion and posture; a sampling platform for detecting the drone's material spreading performance based on the drone's motion and posture, and obtaining material spreading performance parameters; the material spreading performance parameters include particle distribution uniformity of the spread material, particle impact force, particle entry angle, particle quality, and microenvironmental characteristic parameters; and a control platform for real-time collection, analysis, and display of the material spreading performance parameters based on detection process control, dynamic wind field modeling, and particle trajectory calculation, and generating charts and analysis reports to evaluate the agricultural drone's spreading performance. The system of the present invention implements intelligent control of the operation process, improving the efficiency and accuracy of agricultural drone material spreading performance detection.

Description

Technical Field

[0001] The present invention relates to the field of agricultural production and unmanned aerial vehicle (UAV) control technology, and in particular to a material spreading performance detection system for an agricultural UAV and an operation method thereof. Background Art

[0002] With the rapid development of modern agriculture, especially the advancement of precision agriculture technology, agricultural drones have become an important tool in farmland operations, showing significant advantages in spreading materials such as fertilizers, feed or seeds. Compared with traditional ground machinery, agricultural drones have the advantages of flexible operation, strong terrain adaptability and less damage to crops, which greatly improves the efficiency and accuracy of agricultural production. With the widespread application of drones in agriculture, the evaluation and testing of their operating performance has also become crucial.

[0003] In related technologies, manual sampling is usually used to test the material spreading performance of agricultural drones. The operation steps are complicated and time-consuming, and it is difficult to meet the testing needs of new operating modes of agricultural drones. At the same time, traditional manual point sampling methods have significant limitations in the detection of uniformity of spreading particles and analysis of spreading effects, and lack comprehensive testing of multi-dimensional environmental factors. It is impossible to conduct comprehensive and continuous monitoring of the operating effects within the drone's spreading range, resulting in low accuracy of fertilization effect test results. Summary of the Invention

[0004] The present invention provides an agricultural drone material spreading performance detection system and an operating method thereof, which are used to solve the problems that the existing technology uses manual sampling to detect the material spreading performance of agricultural drones, which is complicated and time-consuming. The traditional manual point sampling method has significant limitations in the detection of spreading particle uniformity and the analysis of spreading effects, and lacks comprehensive detection of multi-dimensional environmental factors, resulting in low accuracy of fertilization effect evaluation results. The system improves the efficiency and accuracy of agricultural drone material spreading performance detection.

[0005] The present invention provides a material spreading performance detection system for an agricultural UAV, comprising:

[0006] A UAV platform is used to control the movement and attitude of the UAV, including flight altitude, heading angle, pitch angle, and roll angle;

[0007] A sampling platform for detecting the material spreading performance of the drone based on the drone's motion and posture, and obtaining material spreading performance parameters; wherein the material spreading performance parameters include particle distribution uniformity of the spread material, particle target force, particle entry angle, particle mass, and microenvironment characteristic parameters;

[0008] A control platform, the control platform being used to control the coordinated operation of the UAV platform and the sampling platform; the control platform sampling, analyzing, and displaying the material spreading performance parameters in real time based on the operations of detection process control, dynamic wind field modeling, and particle trajectory calculation, and generating charts and analysis reports to evaluate the spreading performance of the agricultural UAV;

[0009] The control platform also adjusts the location and density of sampling points through a sampling layout adaptive optimization mechanism and an environmental factor quantitative modeling mechanism.

[0010] According to the present invention, a system for detecting the material spreading performance of an agricultural UAV is provided, wherein the UAV platform comprises:

[0011] A UAV motion control module is installed in the middle area of the UAV platform, and is used to control the motion and attitude state of the UAV;

[0012] A material cleaning and recovery module is installed at the bottom of the UAV platform. The material cleaning and recovery module is used to control the telescopic rod and brush to recover the ground-spread materials according to the cleaning instructions; wherein, the cleaning instructions are based on the control platform to obtain the size of the test area, the spreading coverage range and the distribution information of the remaining materials, so as to realize the recovery of all the spread materials in the test area.

[0013] According to the present invention, a system for detecting the material spreading performance of an agricultural UAV is provided, wherein the sampling platform comprises:

[0014] Multiple sampling unmanned vehicles, each of which is equipped with GNSS positioning and lidar-assisted perception functions, and collects the material spreading performance parameters according to the navigation route;

[0015] A networking collaboration module, wherein the plurality of sampling unmanned vehicles are respectively communicatively connected to the networking collaboration module, and the networking collaboration module is used to achieve collaborative operation and path obstacle avoidance among the plurality of sampling unmanned vehicles by sharing the real-time position data and sampling status information of each sampling unmanned vehicle;

[0016] The sampling track network supports circular, square, and custom shape layouts and is arranged around the sampling platform according to any of the following sampling layout setting principles:

[0017] Sampling points are evenly distributed along the radius with the UAV platform as the center to form a circular or radial track, and the radius of the circular track and the number of sampling points are determined according to the UAV spreading width and particle distribution variability;

[0018] Sampling points are arranged in a uniform grid in regular plots; the horizontal and vertical spacing corresponding to each sampling point is set according to the spreading width and the size of the working area;

[0019] For irregular plots or complex terrain, sampling tracks can be flexibly arranged according to the shape of the farmland, terrain changes and crop growth characteristics;

[0020] During the sampling process, meteorological parameters such as wind speed, wind direction, humidity and temperature are monitored in real time, and the density of sampling points is dynamically adjusted based on the spreading uniformity data.

[0021] The environmental monitoring module is used to collect meteorological parameters within the drone's operating area and, through the collaboration of a dynamic wind field model and a particle trajectory calculation model, to detect the application trajectory in real time to assess the impact of meteorological parameters on particle distribution; the meteorological parameters include wind speed, wind direction, humidity, temperature, and air pressure.

[0022] According to the agricultural UAV material spreading performance detection system provided by the present invention, each sampling unmanned vehicle includes:

[0023] Chassis; the chassis includes a power system, a navigation system, a suspension structure and a shock absorbing structure;

[0024] A material particle collecting device, wherein the chute of the material particle collecting device adopts a double-layer structure, and the top layer of the double-layer structure is a reversible V-shaped guide plate;

[0025] A material spreading performance detection module, comprising an optical sensor, a piezoelectric sensor, and an angle sensor, for collecting information on particle distribution uniformity, particle quality, and spreading rate;

[0026] The material recovery device is installed at the bottom of the sampling unmanned vehicle. The material recovery device is used to store material particle samples and has automatic weighing and spectral analysis functions.

[0027] According to the present invention, a system for detecting the material spreading performance of an agricultural UAV is provided, wherein the control platform includes:

[0028] Detection process control module, used to set, adjust and control various parameters in the entire test process in real time;

[0029] The analysis module is used to calculate the drone's material spreading performance indicators based on the collected material spreading performance parameters and environmental meteorological data, and generate charts and analysis reports; material spreading performance indicators include spreading uniformity, material distribution, and coverage;

[0030] The analysis module includes a dynamic wind field model and a particle trajectory calculation model, which are used to integrate and analyze environmental parameters with material spreading performance parameters. The dynamic wind field model is used to construct the meteorological scene in the working area in real time through wind speed, wind direction, humidity and temperature data; the particle trajectory calculation model is used to calculate and predict the landing point of the spreading particles based on the dynamic wind field model to evaluate the impact of wind field interference on particle distribution.

[0031] A visualization module is used to display material spreading performance parameters, the charts and the analysis reports, and supports real-time monitoring and historical data backtracking.

[0032] The present invention also provides an operating method of an agricultural UAV material spreading performance detection system, which is applied to the agricultural UAV material spreading performance detection system, comprising:

[0033] The sampling platform detects the material spreading performance of the drone based on the drone's motion and posture, and obtains material spreading performance parameters; wherein the material spreading performance parameters include particle distribution uniformity of the spread material, particle target force, particle entry angle, particle mass, and microenvironment characteristic parameters;

[0034] Based on the control platform, material spreading performance parameters are sampled, analyzed, and displayed in real time according to the detection process control, dynamic wind field modeling, and particle trajectory calculation operations. Graphs and analysis reports are also generated to evaluate the spreading performance of agricultural drones.

[0035] The control platform also adjusts the location and density of sampling points through a sampling layout adaptive optimization mechanism and an environmental factor quantitative modeling mechanism.

[0036] According to the operating method of the agricultural UAV material spreading performance detection system provided by the present invention, after generating the chart and analysis report, the method further includes:

[0037] The material spreading coefficient of variation and the material spreading root mean square error were calculated based on the material spreading performance parameters, and the evaluation results of the agricultural UAV material spreading operation were calculated using the following formula:

[0038] ;

[0039] in, Evaluation results of agricultural drone material spreading operations, CV is the coefficient of variation of the material spreading, RMSE is the root mean square error of spreading the material; W 1 and W 2 is the weight coefficient, and the value range of the weight coefficient is 0 to 1, and W 1 + W 2 =1, the value of F is between 0 and 1, with 1 representing the best fertilization effect and 0 representing the worst.

[0040] The present invention also provides an operating method of an agricultural UAV material spreading performance detection system, wherein the control platform performs real-time sampling, analysis, and display of material spreading performance parameters based on detection process control, dynamic wind field modeling, and particle trajectory calculation operations, including:

[0041] Based on the wind speed, wind direction, humidity and temperature parameters collected by the environmental monitoring module of the agricultural drone material spreading performance detection system, a dynamic wind field model is established within the operation area to simulate the wind field changes at different heights and in different areas;

[0042] The material spreading performance detection module of the agricultural drone material spreading performance detection system obtains parameters such as the initial velocity, release height, and spreading angle of the particles, providing basic input for particle trajectory prediction; and calculates the air resistance of the spread particles when they move in the air. The magnitude of the air resistance is related to the particle shape, velocity, and air density.

[0043] Predict the particle trajectory and theoretical landing point under windless conditions based on the particle's initial velocity, spreading angle, and release height;

[0044] Based on the wind speed and direction data provided by the dynamic wind field model, the theoretical trajectory of the sprayed particles is corrected to reflect the actual interference of the wind field on the particle landing point. The correction takes into account the wind speed, wind direction angle and particle flight time.

[0045] Combining the theoretical trajectory and wind field interference correction results, the actual landing point of the particles in the operating area is predicted;

[0046] Spreading uniformity is expressed by the ratio of the standard deviation of particle density to the mean value, which reflects the uniformity of the distribution of the spread particles. Spreading coverage is determined by the ratio of the particle coverage area to the operating area, which is used to evaluate the coverage completeness of the spreading operation.

[0047] By comparing the predicted landing point with the measured data provided by the sampling platform, the prediction model is calibrated and relevant parameters are corrected to generate a spreading performance test report. The report content includes information on spreading uniformity, coverage rate and wind field interference impact.

[0048] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the operating method of the agricultural UAV material spreading performance detection system as described in any one of the above-mentioned methods is implemented.

[0049] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the operating method of the agricultural UAV material spreading performance detection system as described in any one of the above is implemented.

[0050] The agricultural UAV material spreading performance detection system and operation method provided by the present invention control the movement and posture of the UAV by setting a UAV platform; set a sampling platform to collect material spreading performance parameters; set a control platform to generate fertilization instructions according to the material spreading performance parameters, so as to instruct the UAV platform to collect, analyze and display the material spreading performance parameters in real time based on detection process control, dynamic wind field modeling and particle trajectory calculation, and generate charts and analysis reports, thereby realizing intelligent control of the operation process and improving the efficiency and accuracy of the material spreading performance detection of the agricultural UAV. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 This is one of the structural schematic diagrams of the agricultural UAV material spreading performance detection system provided by the present invention.

[0053] Figure 2 This is the second structural schematic diagram of the agricultural UAV material spreading performance detection system provided by the present invention.

[0054] Figure 3 Schematic diagrams of four sampling layouts of the sampling unmanned vehicle provided by the present invention.

[0055] Figure 4 It is a structural schematic diagram of the sampling unmanned vehicle provided by the present invention.

[0056] Figure 5 This is one of the flow charts of the operating method of the agricultural UAV material spreading performance detection system provided by the present invention.

[0057] Figure 6 This is the second flow chart of the operating method of the agricultural UAV material spreading performance detection system provided by the present invention.

[0058] Figure 7 It is a structural schematic diagram of the electronic device provided by the present invention.

[0059] Reference numerals:

[0060] 100. UAV platform; 110. UAV motion control module;

[0061] 120. Material cleaning and recovery module; 200. Sampling platform; 210. Sampling unmanned vehicle;

[0062] 211. chassis; 212. material particle collection device; 213. material spreading performance detection module;

[0063] 214. Material recovery device; 220. Network coordination module; 230. Sampling track network;

[0064] 240, environmental monitoring module; 300, control platform; 310, detection process control module;

[0065] 320. Analysis module; 330. Visualization module. DETAILED DESCRIPTION

[0066] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0067] The following combination Figures 1-6 The present invention describes an agricultural UAV material spreading performance detection system and an operation method thereof.

[0068] Figure 1 This is one of the structural diagrams of the agricultural UAV material spreading performance detection system provided by the present invention, such as Figure 1 The agricultural UAV material spreading performance detection system includes: a UAV platform 100, a sampling platform 200 and a control platform 300.

[0069] The UAV platform 100 is used to control the movement and attitude of the UAV, where the attitude includes flight altitude, heading angle, pitch angle, and roll angle.

[0070] In this embodiment, the UAV platform 100 simulates the spreading effects of different types of agricultural UAVs under various operating conditions by precisely adjusting the flight altitude and posture of the UAV.

[0071] The sampling platform 200 is used to detect the material spreading performance of the drone based on the movement and posture of the drone and obtain material spreading performance parameters; wherein, the material spreading performance parameters include but are not limited to the particle distribution uniformity of the spread material, the particle target force, the particle entry angle, the particle mass and the microenvironment characteristic parameters.

[0072] In this embodiment, the sampling platform 200 includes a particle distribution detection module, a particle impact force and incident angle detection module, a particle quality detection module, and a microenvironment detection module.

[0073] In this embodiment, the particle distribution detection module is located above the particle collection trough and is used to collect the dynamic changes and distribution of particles in the collection trough in real time; specifically, the particle distribution detection module includes an optical sensor and a high-resolution image sensor. After the particles enter the collection trough, the high-resolution image sensor captures the distribution image of the particles, and the control platform 300 analyzes the particle density based on the distribution image through an image processing algorithm to provide data support for the evaluation of spreading uniformity and coverage; the optical sensor is used to measure the dynamic changes in the material sedimentation process; the optical sensor adopts an array-type optical sensor; the array forms a cross-measurement area by arranging multiple sensor units, which can accurately capture the movement state of material particles in three-dimensional space.

[0074] In this embodiment, a particle impact force and incident angle detection module is installed on the top surface of the collection tank, and is used to detect in real time the impact force and incident angle of the particles when they hit the collection tank; specifically, the particle impact force and incident angle detection module includes multiple piezoelectric sensors and angle sensors. When the spread particles hit the collection tank, the piezoelectric sensor detects the impact force, and the angle sensor measures the angle at which the particles enter the tank body, and feeds back the data to the control platform 300.

[0075] In this embodiment, the particle quality detection module is used to accurately measure the mass of the collected and spread particles. The particle quality detection module includes a bottom weighing sensor (for detecting the weight of the particles) and a spectrum analysis sensor (for detecting the composition of the particles).

[0076] In this embodiment, the particle quality detection module is used to accurately measure the mass of the collected scattering particles, including a bottom weighing sensor (detecting the weight of the particles) and a spectral analysis sensor (detecting the composition of the particles); it is arranged at the drop port of the inclined slide; after the single-number scattering particles fall into the collection trough, the top "V"-shaped guide plate automatically flips to guide the particle material to the bottom inclined slide, and the bottom slide further guides the material flow to the particle quality detection module, and the particle quality detection module can detect the mass and composition of the material collected by each slide respectively.

[0077] Figure 2 This is the second structural diagram of the agricultural UAV material spreading performance detection system provided by the present invention. Figure 2 In the embodiment shown, the microenvironment detection module is used to detect in real time the temperature and humidity, wind speed and direction, and spreading scene images in the environment near the sampling unmanned vehicle 210, and provide data for the environmental impact analysis of the spreading effect; the microenvironment detection module includes a temperature and humidity sensor, a three-dimensional ultrasonic wind speed and direction sensor, and an image sensor. These sensors are installed around the unmanned vehicle chassis 211, covering multiple directions; the microenvironment detection module collects three-dimensional wind speed and direction data, combined with particle distribution and target angle, to analyze the impact of wind on the distribution of spread materials.

[0078] The UAV platform 100 and the sampling platform 200 are electrically connected to the control platform 300 respectively.

[0079] The control platform 300 is used to control the coordinated operation of the UAV platform 100 and the sampling platform 200; the control platform 300 performs real-time sampling, analysis and display of material spreading performance parameters based on the operations of detection process control, dynamic wind field modeling and particle trajectory calculation, and generates charts and analysis reports to evaluate the spreading performance of the agricultural UAV.

[0080] The control platform also adjusts the location and density of sampling points through the sampling layout adaptive optimization mechanism and the environmental factor quantitative modeling mechanism.

[0081] In this embodiment, the control platform 300 is the core control and data processing module of the agricultural drone material spreading performance detection system, which can realize the automated management, data analysis and multi-dimensional correlation analysis of the agricultural drone fertilization process.

[0082] In this embodiment, the control platform 300 is used to set, adjust and control various parameters throughout the entire test process in real time, ensuring the coordinated operation of the drone platform 100 and the sampling platform 200 and accurately executing the preset test tasks.

[0083] In this embodiment, the control platform 300 manages the drone's ascent, altitude, and attitude adjustments through a backend system to meet the test plan's requirements. This module dynamically adjusts the drone's operating parameters, such as the amount of material being spread, based on real-time environmental conditions and mission requirements, ensuring precise and consistent operation.

[0084] The agricultural UAV material spreading performance detection system provided by the embodiment of the present invention controls the motion state of the UAV by setting up a UAV platform; sets up a sampling platform to detect the material spreading performance of the UAV and obtains material spreading performance parameters; sets up a control platform to generate fertilization instructions according to the material spreading performance parameters to instruct the UAV platform to control the UAV to perform fertilization operations according to the target height and target posture. The UAV spreading parameters can be dynamically adjusted according to the collected data, realizing intelligent control of the operation process, and improving the efficiency and accuracy of the material spreading performance detection of the agricultural UAV.

[0085] exist Figure 2 In the illustrated embodiment, the UAV platform 100 includes: a UAV motion control module 110 and a material cleaning and recovery module 120 .

[0086] The UAV motion control module 110 is installed in the middle area of the UAV platform 100 . The UAV motion control module is used to control the motion and attitude state of the UAV.

[0087] In this embodiment, the UAV motion control module 110 is located at the center of the UAV platform 100 to ensure uniform coverage and acquisition of the test area.

[0088] In this embodiment, the UAV motion control module 110 includes a telescopic module, a UAV fixed platform, and a body parameter detection module; the telescopic module is used to adjust the flight altitude of the UAV; the UAV fixed platform is used to adjust the flight attitude angle of the UAV; the body parameter detection module is used to detect the body attitude changes, body vibration frequency, rotor speed, broadcast disk speed and other body parameter data of the test UAV.

[0089] In this embodiment, the above-mentioned drone fixed stand is suitable for different models of agricultural drones. According to the preset flight altitude and flight attitude angle, the telescopic module and the drone fixed stand can be controlled to adjust the drone movement in real time to simulate the spreading conditions of the agricultural drone under different operating conditions; at the same time, the control platform 300 can collect data such as the body attitude, body vibration frequency, rotor speed, and broadcast disk speed of the test drone in real time through the body parameter detection module matched with the stand.

[0090] The material cleaning and recovery module 120 is installed at the bottom of the UAV platform 100. The material cleaning and recovery module 120 is used to control the telescopic rod and the brush to perform material recovery operations according to the cleaning instructions; the cleaning instructions are based on the control platform to obtain the size of the test area, the spreading coverage range and the remaining material distribution information to achieve the recovery of all the spread materials in the test area.

[0091] In this embodiment, the material cleaning and recovery module 120 includes a telescopic rod and a brush; after the agricultural drone material spreading test is completed, the material cleaning and recovery device automatically unfolded by the material cleaning and recovery module 120 cleans the site, and the telescopic rod and brush device ensure the efficiency and non-interference of material collection; the control platform 300 automatically controls the operation and retraction of the brush according to the cleaning progress and area size, thereby realizing automatic recovery of materials.

[0092] Specifically, the telescopic rod can automatically adjust its length according to the size of the test area, and its maximum length can cover the entire test area; the brush device is made of soft material and has sufficient rigidity to effectively clean material particles on the ground; during the test, the material cleaning and recovery device is in a retracted state, and the brush is tightly attached to the telescopic rod body and does not interfere with the test operation; when the test is over, the control platform 300 controls the telescopic rod to automatically operate through control instructions, adjusting it to an appropriate length to ensure that the entire test area is covered during cleaning. The brush on one side of the telescopic rod will automatically pop out from the retracted state with the help of elastic force when extended, and resume the cleaning function.

[0093] In this embodiment, the material cleaning and recovery device implements the following steps for cleaning the material:

[0094] (1) Extending the telescopic rod: Upon receiving the control command sent by the control platform 300, the telescopic rod gradually extends from the bottom of the platform until it reaches the radius of the test area. The brush automatically pops out as the telescopic rod extends and begins to enter the cleaning state.

[0095] (2) Start cleaning: When the telescopic rod reaches the target length, the material cleaning and recovery device moves in a circular motion around the center of the UAV platform 100, and the brush sweeps the material particles on the ground along a circular trajectory, gradually pushing the scattered materials to the designated concentrated area.

[0096] (3) Material recovery: After cleaning, the material particles are concentrated in one area for easy recycling by test personnel. This automated cleaning method reduces material waste, improves material recovery efficiency, and prevents materials from being scattered throughout the test site.

[0097] In this embodiment, each unit of the drone motion control module 110 is electrically connected to the control platform 300, enabling highly automated operation. The control platform 300 allows testers to control the lift and attitude adjustment of the agricultural drone under test, as well as the activation time, cleaning range, and cleaning frequency of the cleaning device, ensuring that the test site is cleaned immediately after each test. Furthermore, the control platform 300 uses sensors to monitor the operating status of each device, ensuring that the telescopic rod does not become stuck or malfunction during the cleaning process. If an obstacle is encountered during the cleaning process, the system automatically pauses the cleaning process and provides feedback to the operator, prompting them to address the problem. This improves the safety of the cleaning process and ensures the long-term stable operation of the equipment.

[0098] In this embodiment, the control platform 300 supplies power to the tested agricultural drone through the drone motion control module 110. The test personnel can remotely start or cut off the power supply of the drone through the control platform 300, making the entire test process safer and more controllable.

[0099] The agricultural drone material spreading performance testing system provided by the embodiment of the present invention controls the lifting and posture adjustment of the tested agricultural drone through the drone motion control module, and cleans the test site immediately after each test through the material cleaning and recovery module, thereby ensuring the cleanliness and efficiency of the test site.

[0100] exist Figure 2 In the illustrated embodiment, the sampling platform 200 includes: multiple sampling unmanned vehicles 210, a networking coordination module 220, a sampling track network 230 and an environmental monitoring module 240.

[0101] Each sampling unmanned vehicle 210 has autonomous navigation capabilities.

[0102] Each sampling unmanned vehicle 210 is equipped with GNSS positioning and lidar-assisted perception functions, and collects the material spreading performance parameters according to the navigation route.

[0103] In this embodiment, the navigation route is obtained by comprehensive analysis and calculation by the sampling platform 200 based on the operating parameters of the sampling unmanned vehicle 210, the material spreading performance parameters and the meteorological data.

[0104] In this embodiment, the unmanned sampling vehicle 210 can operate along a fixed path or flexibly plan a sampling trajectory based on an autonomous navigation system. It can also dynamically adjust the sampling frequency, sampling time, and sampling area distribution. Furthermore, the particle collection device 212 automatically opens and closes under the control of the sampling platform 200 to ensure the accuracy and consistency of the sampling performed by the unmanned sampling vehicle 210, optimizing the sampling effect.

[0105] In this embodiment, the sampling unmanned vehicle 210 can automatically perform preset tasks according to the test task requirements, and the control platform 300 can dynamically adjust the operating parameters of each device according to environmental changes during the test process to ensure the smooth progress of the test and improve the adaptability of the system.

[0106] Multiple sampling unmanned vehicles 210 are respectively communicated with the networking collaboration module 220. The networking collaboration module 220 is used to share the real-time location data and sampling status information of each sampling unmanned vehicle 210 to achieve collaborative operation and path obstacle avoidance between multiple sampling unmanned vehicles 210.

[0107] In this embodiment, the networking collaboration module 220 is used for communication networking between multiple sampling unmanned vehicles 210 and to achieve collaborative operations; through networking, multiple sampling unmanned vehicles 210 can share real-time location data and status information, thereby ensuring the synchronization and coordination of the sampling process.

[0108] In this embodiment, the networking collaboration module 220 is connected to the control platform 300, and the control platform 300 realizes global monitoring and command functions through the data sent by the networking collaboration module 220; and the operator can use the control platform 300 to set the path, sampling frequency, sampling area allocation, etc. of the sampling unmanned vehicle 210 through the networking collaboration module 220, and monitor the working status of the sampling unmanned vehicle 210 in real time.

[0109] The sampling track network 230 supports circular, square and custom shape layouts and is arranged around the sampling platform according to any of the following sampling layout setting principles.

[0110] Sampling points are distributed equidistantly along the radius with the UAV platform as the center to form a circular or radial track. The radius of the circular track and the number of sampling points are determined according to the UAV's spreading width and particle distribution variability.

[0111] Sampling points are arranged in a uniform grid in regular plots; the horizontal and vertical spacing corresponding to each sampling point is set according to the spreading width and the size of the working area;

[0112] For irregular plots or complex terrain, sampling tracks can be flexibly arranged according to the shape of the farmland, terrain changes and crop growth characteristics;

[0113] During the sampling process, meteorological parameters such as wind speed, wind direction, humidity and temperature are monitored in real time, and the density of sampling points is dynamically adjusted based on the spreading uniformity data.

[0114] The environmental monitoring module is used to collect meteorological parameters within the drone's operating area and, through the collaboration of a dynamic wind field model and a particle trajectory calculation model, to detect the spreading trajectory in real time to assess the impact of meteorological parameters on particle distribution; meteorological parameters include wind speed, wind direction, humidity, temperature, and air pressure.

[0115] In this embodiment, the sampling track network 230 is used to generate the movement path of the sampling vehicle within the test area; the sampling track network 230 supports the following three path implementation methods: (1) setting a fixed path through electromagnetic induction lines; (2) realizing flexible path planning through an autonomous navigation system; and (3) setting a fixed path by installing a shaped track.

[0116] The sampling track network 230 can be designed in circular, square, or other custom shapes to accommodate diverse testing requirements. Layoutd around the test bench, with the bench as its center, the sampling track network 230 can form various geometric tracks as needed to ensure coverage of the entire test area. This flexible track shape design enables multi-angle and multi-position fertilization data collection, enhancing the comprehensiveness and diversity of the data. Furthermore, the sampling track network 230 provides flexible path selection to accommodate diverse experimental layouts, providing richer support for precise spreading performance testing.

[0117] The environmental monitoring module 240 is used to collect meteorological parameters within the drone operation area and to detect the spreading trajectory in real time through the collaboration of a dynamic wind field model and a particle trajectory calculation model to evaluate the impact of meteorological parameters on particle distribution; the meteorological parameters include wind speed, wind direction, humidity, temperature and air pressure.

[0118] In this embodiment, the environmental monitoring module 240 includes multiple meteorological monitors distributed around the sampling platform 200, which can collect and analyze meteorological data (such as wind speed, wind direction, humidity, temperature, etc.) in the test environment in real time. These meteorological parameters directly affect the effectiveness of drone fertilizer application and other material spreading; the control platform 300 compares and analyzes the fertilization effects under different meteorological conditions based on meteorological data; through the analysis of key factors such as wind speed, wind direction, and humidity, it can help researchers evaluate the distribution of materials under different environmental conditions, optimize the amount and uniformity of fertilizer application, and ensure the reliability and repeatability of the test results.

[0119] Figure 3 The four sampling layout diagrams of the sampling unmanned vehicle provided by the present invention are as follows: Figure 3 In the illustrated embodiment, multiple sampling unmanned vehicles (marked by small black squares in the figure) can be evenly and symmetrically arranged on the sampling platform and surround the drone platform (marked by black circles in the figure) to quickly and fully collect material spreading performance parameters of the drones on the drone platform; Figure 3 It includes a circular cross-symmetrical sampling platform (upper left), with the drone platform as the center, and multiple sampling unmanned vehicles are arranged at equal intervals in the horizontal and vertical directions; it also includes a square cross-symmetrical sampling platform (upper right), with the drone platform as the center, and three rows and three columns of sampling unmanned vehicles are arranged at equal intervals in the horizontal and vertical directions; it also includes a square cross-symmetrical sampling platform (lower left), with the drone platform as the center, and sampling unmanned vehicles are arranged at equal intervals in the horizontal, vertical and oblique directions; it also includes a square symmetrical sampling platform (lower right), with the drone platform as the center, and multiple sampling unmanned vehicles are arranged on the left and right sides of the square.

[0120] The agricultural UAV material spreading performance detection system provided by the embodiment of the present invention collects material spreading performance parameters by setting up multiple sampling unmanned vehicles to simulate the material spreading effects under different operating conditions; a networking collaboration module is set up to realize the collaborative operation between multiple sampling unmanned vehicles, and a sampling track network is set up around the sampling platform to generate a variety of geometric paths for the sampling unmanned vehicles to collect data; an environmental monitoring module is set up to collect meteorological data in the environment surrounding the UAV, which can adapt to different test requirements, realize comprehensive coverage of sampling by the sampling unmanned vehicles in the test area, and improve the efficiency and quality of collecting material spreading performance parameters.

[0121] Figure 4 This is a schematic diagram of the structure of the sampling unmanned vehicle provided by the present invention. Figure 4 In the illustrated embodiment, each sampling unmanned vehicle includes: a chassis 211 , a material particle collection device 212 , a material spreading performance detection module 213 and a material recovery device 214 .

[0122] In this embodiment, the chassis 211 of the sampling unmanned vehicle serves as the core carrier of the entire system, and has the comprehensive capabilities of autonomous navigation, obstacle avoidance, precise positioning and stable operation, ensuring the efficient execution of the sampling task.

[0123] The chassis 211 includes a power system, a navigation system, a suspension structure, and a shock absorbing structure.

[0124] In this embodiment, the power system is electrically driven; the navigation system is composed of GNSS, lidar, and visual sensors, and achieves high-precision positioning and real-time obstacle avoidance through multi-sensor fusion; the chassis 211 also integrates a variety of sensor modules, which can complete path planning and precise position control within the sampling area; the suspension structure and shock absorption structure can help the sampling unmanned vehicle adapt to complex terrain and achieve smooth driving.

[0125] In this embodiment, the chassis 211 of the sampling unmanned vehicle moves autonomously along a preset path or a path planned intelligently in real time, ensuring the smooth completion of the sampling task while guaranteeing the accuracy and safety of the sampling path.

[0126] The chute of the material particle collecting device 212 adopts a double-layer structure, and the top layer of the double-layer structure is a flippable V-shaped guide plate.

[0127] In this embodiment, the material particle collecting device 212 is installed above the chassis 211 to collect the spread material particles for subsequent detection and analysis.

[0128] In this embodiment, the material particle collecting device 212 includes a collecting trough and a protective cover.

[0129] In this embodiment, the collection trough comprises a chute and a trough frame. The chute utilizes a double-layer design (top and bottom layers). The top layer features a set of neatly arranged, automatically reversible "V"-shaped guide plates that guide the granular material to the inclined chute on the bottom layer. The bottom chute further guides the material toward the bottom of the trough, ensuring smooth flow. This double-layer design ensures that the granular material is quickly and smoothly transported to the material spreading performance parameter detection device for accurate testing and data collection.

[0130] In this embodiment, the trough frame serves as the main frame of the collection trough, and its shape is preferably a square or rectangular shape of equal size to ensure uniform collection of materials; the protective cover is set on both sides of the outside of the collection trough and has an automatic opening and closing function. Before each material collection, the protective cover automatically opens to allow the spread particles to enter the collection trough smoothly. After the collection is completed, the protective cover is immediately closed to prevent particles from the external environment from interfering with the collected samples; in addition, the "V"-shaped guide plate in the collection trough has an automatic flipping function, which can quickly flip and clean the collected particles after the collection is completed, ensuring that the next collection is not affected and avoiding interference with the sample by external particles; the protective cover remains closed in the default state to prevent interference with the equipment by external particles during vehicle driving or waiting.

[0131] The material spreading performance detection module 213 includes an optical sensor, a piezoelectric sensor and an angle sensor. The material spreading performance detection module is used to collect particle distribution uniformity, particle quality and spreading amount.

[0132] In this embodiment, the material spreading performance detection module 213 includes the above-mentioned particle distribution detection module, particle targeting force and incident angle detection module, particle quality detection module and microenvironment detection module, which will not be repeated in this embodiment.

[0133] The material recovery device is installed at the bottom of the sampling unmanned vehicle. The material recovery device is used to store material particle samples and has automatic weighing and spectral analysis functions.

[0134] In this embodiment, the material recovery device 214 has a classification storage function and is equipped with an automatic conveying device or a conveyor belt. The inspected particles are automatically introduced into the storage box for classification storage through the conveying system, thereby realizing material recovery and subsequent processing.

[0135] The agricultural UAV material spreading performance detection system provided by the embodiment of the present invention improves the accuracy and safety of the sampling path by setting each sampling unmanned vehicle including a chassis, sets a material particle collection device to improve data collection efficiency, sets a material spreading performance detection module to realize comprehensive analysis of multi-dimensional parameters such as particle distribution density, quality, target force, environmental conditions, etc., to evaluate the impact of different spreading conditions on the operation effect, and sets a material recovery device to realize material recovery and reprocessing, thereby reducing manpower and time costs and improving the efficiency of material spreading performance detection.

[0136] exist Figure 2 In the illustrated embodiment, the control platform 300 includes a detection process control module 310 , an analysis module 320 , and a visualization module 330 .

[0137] The detection process control module 310 is used to set, adjust and control various parameters in the entire test process in real time.

[0138] In this embodiment, the detection process control module 310 is used to set, adjust, and control various parameters throughout the entire test process in real time, ensuring the coordinated operation of the drone platform 100 and the sampling platform 200 and accurately executing the preset test tasks. The detection process control module 310 specifically includes the following functions:

[0139] (1) UAV control: The control platform 300 manages the drone's lift, flight altitude, and attitude adjustment to meet the test plan's requirements. The detection process control module 310 can dynamically generate corresponding fertilization instructions based on real-time environmental conditions and task requirements to adjust the drone's operating parameters, such as the amount of material to be spread, to ensure the accuracy and consistency of the operation.

[0140] (2) Control of the sampling platform 200: The detection process control module 310 controls the movement path of the autonomous sampling vehicle. It can set a fixed path or flexibly plan the sampling trajectory based on the autonomous navigation system, and can dynamically adjust the sampling frequency, sampling time point and sampling area distribution. At the same time, the material collection device of the sampling platform 200 is automatically opened and closed under the control of this module to ensure the accuracy and consistency of sampling and optimize the sampling effect.

[0141] (3) Automated task scheduling: The detection process control module 310 can automatically execute preset tasks according to the test task requirements, and dynamically adjust the operating parameters of each device according to environmental changes during the test process to ensure the smooth progress of the test and improve the applicability of the agricultural drone material spreading performance detection system.

[0142] The analysis module 320 is used to calculate the material spreading performance indicators of the drone based on the collected material spreading performance parameters and environmental meteorological data, and generate charts and analysis reports; the material spreading performance indicators include spreading uniformity, material distribution and coverage; the analysis module 320 includes a dynamic wind field model and a particle trajectory calculation model, which are used to integrate and analyze environmental parameters with material spreading performance parameters, wherein the dynamic wind field model is used to construct the meteorological scene in the working area in real time through wind speed, wind direction, humidity and temperature data; the particle trajectory calculation model is used to calculate and predict the landing point of the spreading particles based on the dynamic wind field model to evaluate the impact of wind field interference on particle distribution.

[0143] In this embodiment, the analysis module 320 is used to receive, process, and analyze various data from the drone and sampling platform 200 in real time, ensuring the accuracy, comprehensiveness, and multidimensionality of the data and providing a scientific basis for subsequent analysis. The analysis module 320 specifically includes the following functions:

[0144] (1) Real-time data collection: The analysis module 320 collects various parameters such as fertilizer uniformity, particle quality, and spreading area coverage through the communication network with the drone, sampling platform 200, and operation station, and transmits these data to the control platform 300 in real time;

[0145] (2) Data analysis and feedback: The analysis module 320 conducts in-depth analysis of the collected raw data, such as evaluating the uniformity of spreading, material distribution and coverage, and generates charts and analysis reports based on the results for reference by test personnel.

[0146] In this embodiment, the material spreading performance index of the UAV includes the material spreading coefficient of variation ( Coefficient of Variation, CV ) and the root mean square error of material spreading ( Root Mean Square Error, RMSE ), the corresponding calculation formula for the agricultural drone material spreading operation evaluation effect F is as follows:

[0147] ;

[0148] in, W 1 and W 2 is the weight coefficient (its value range is 0 to 1, and W 1 + W 2 =1), the value of F is between 0 and 1, with 1 representing the best fertilization effect and 0 representing the worst.

[0149] For example, when testing the fertilization of agricultural drones, you can set W 1 = W 2 =0.5, and the evaluation formula for the fertilization effect is:

[0150] ;

[0151] in, for CV The maximum value of for RMSE The maximum value of CV and RMSE When both are close to their respective maximum values, the F value is close to 1, indicating that the fertilization effect is the best; when CV and RMSE When both are close to 0, the F value is close to 0, indicating the worst fertilization effect.

[0152] In this embodiment, the coefficient of variation of material spreading is an indicator to measure the relative discreteness of data. The sampling unmanned vehicle 210 collects the material particle quality data at different sampling points and calculates the coefficient of variation of material spreading by combining the coefficient of variation. CV , specifically expressed by the following formula:

[0153] ;

[0154] in, is the sample standard deviation, is the sample mean; this embodiment calculates the coefficient of variation of different sample points CV , to illustrate the uniformity of material spreading. The lower the CV value, the smaller the discrete degree of the data and the better the uniformity of fertilization.

[0155] In this embodiment, the material spreading root mean square error RMSE The deviation between the actual amount of fertilizer applied at a certain location and the target amount of fertilizer applied is used to evaluate the platform test, reflecting the average level of prediction error; combined with the root mean square error calculation RMSE , expressed by the following formula:

[0156] ;

[0157] in, For the observations (actual values), For the predicted values (target values), is the sample size; RMSE The smaller it is, the closer the predicted value is to the actual value, and the higher the accuracy of the model or method. RMSE The lower the value, the better the fertilization uniformity.

[0158] (3) The analysis module 320 also has an intelligent feedback function, which can dynamically adjust the operating parameters of the system based on the analysis results to optimize the spreading effect and sampling accuracy.

[0159] The visualization module 330 is used to display at least one of the material spreading performance indicators, charts, and analysis reports.

[0160] In this embodiment, the visualization module 330 is used by the data processing module to present the analyzed data in a visual form on the user interface, so that users can intuitively view the test results, such as fertilizer uniformity, particle distribution, etc., and facilitate the storage and management of long-term data, providing data support for subsequent analysis and trend comparison.

[0161] The agricultural drone material spreading performance detection system provided by the embodiment of the present invention improves the accuracy and consistency of the drone's fertilization operation through the detection process control module; by setting up an analysis module to receive, process and analyze various types of data from the drone and sampling platform in real time, the accuracy, comprehensiveness and multidimensionality of the data are improved; by setting up a visualization module, the analyzed data is presented in a visual form on the user interface to help users intuitively view the test results, and long-term data can also be used to provide data support for subsequent analysis and trend comparison.

[0162] The following describes the operating method of the agricultural UAV material spreading performance detection system provided by the present invention. The operating method of the agricultural UAV material spreading performance detection system described below and the agricultural UAV material spreading performance detection system described above can be referenced to each other.

[0163] Figure 5 This is one of the flow charts of the operating method of the agricultural UAV material spreading performance detection system provided by the present invention, such as Figure 5 As shown, the method includes the following steps:

[0164] Step 510: Detect the material spreading performance of the drone based on the sampling platform according to the movement and posture of the drone, and obtain material spreading performance parameters; wherein the material spreading performance parameters include the particle distribution uniformity of the spread material, the particle target force, the particle entry angle, the particle mass and the microenvironment characteristic parameters.

[0165] In this step, the sampling platform includes a particle distribution detection module, a particle impact force and incident angle detection module, a particle quality detection module and a microenvironment detection module.

[0166] In this embodiment, the particle distribution detection module is located above the particle collection trough and is used to collect the dynamic changes and distribution of particles in the collection trough in real time; specifically, the particle distribution detection module includes an optical sensor and a high-resolution image sensor. After the particles enter the collection trough, the high-resolution image sensor captures the distribution image of the particles, and the control platform analyzes the particle density based on the distribution image through an image processing algorithm, providing data support for the evaluation of spreading uniformity and coverage; the optical sensor is used to measure the dynamic changes in the material sedimentation process; the optical sensor adopts an array-type optical sensor; the array forms a cross-measurement area by arranging multiple sensor units, which can accurately capture the movement state of material particles in three-dimensional space.

[0167] In this embodiment, a particle impact force and incident angle detection module is installed on the top surface of the collection tank, and is used to detect in real time the impact force and incident angle of the particles when they hit the collection tank; specifically, the particle impact force and incident angle detection module includes multiple piezoelectric sensors and angle sensors. When the spread particles hit the collection tank, the piezoelectric sensor detects the impact force, and the angle sensor measures the angle at which the particles enter the tank body, and feeds back the data to the control platform.

[0168] In this embodiment, the particle quality detection module is used to accurately measure the mass of the collected and spread particles. The particle quality detection module includes a bottom weighing sensor (for detecting the weight of the particles) and a spectrum analysis sensor (for detecting the composition of the particles).

[0169] Specifically, the particle quality detection module is arranged at the lower drop of the inclined slide; after the single-number scattering particles fall into the collection trough, the top "V"-shaped guide plate automatically flips over to guide the particle material to the bottom inclined slide, and the bottom slide further guides the material to flow toward the particle quality detection module, and the particle quality detection module can detect the quality and composition of the material collected by each slide respectively.

[0170] In this embodiment, the microenvironment detection module is used to detect in real time the temperature and humidity, wind speed and direction, and spreading scene images in the environment near the unmanned vehicle, and provide data for the environmental impact analysis of the spreading effect; the microenvironment detection module includes temperature and humidity sensors, three-dimensional ultrasonic wind speed and direction sensors, and image sensors. These sensors are installed around the chassis of the unmanned vehicle, covering multiple directions; the microenvironment detection module collects three-dimensional wind speed and direction data, combined with particle distribution and target angle, to analyze the impact of wind on the distribution of spread materials.

[0171] Step 520: Based on the control platform, material spreading performance parameters are sampled, analyzed, and displayed in real time according to the operations of detection process control, dynamic wind field modeling, and particle trajectory calculation, and charts and analysis reports are generated to evaluate the spreading performance of the agricultural drone; among them, the control platform also adjusts the location and density of sampling points through the sampling layout adaptive optimization mechanism and the environmental factor quantitative modeling mechanism.

[0172] In this step, the motion state of the drone (including agricultural drones) includes the altitude of the drone's ascent and descent, as well as its posture. For example, the motion state of the drone includes the drone's flight speed, heading angle, pitch angle, and roll angle.

[0173] In this embodiment, the UAV platform simulates the spreading effects of different types of agricultural UAVs under various operating conditions by precisely adjusting the flight altitude and posture of the UAV.

[0174] In this embodiment, the control platform is the core control and data processing module of the agricultural drone material spreading performance detection system, which can realize the automated management, data analysis and multi-dimensional correlation analysis of the agricultural drone fertilization process.

[0175] In this embodiment, the control platform is used to set, adjust and control various parameters throughout the entire test process in real time, ensuring the coordinated operation of the drone platform and the sampling platform and accurately executing the preset test tasks.

[0176] In this example, the control platform manages the drone's ascent, descent, altitude, and attitude adjustments through a backend system to meet the test plan's requirements. This module dynamically adjusts the drone's operating parameters, such as the amount of material being spread, based on real-time environmental conditions and mission requirements, ensuring precise and consistent operation.

[0177] The operating method of the agricultural UAV material spreading performance detection system provided by the embodiment of the present invention is to set up a UAV platform to control the motion state of the UAV; set up a sampling platform to detect the material spreading performance of the UAV and obtain material spreading performance parameters; set up a control platform to generate fertilization instructions according to the material spreading performance parameters to instruct the UAV platform to control the UAV to perform fertilization operations according to the target height and target posture. The UAV spreading parameters can be dynamically adjusted according to the collected data, thereby realizing intelligent control of the operation process and improving the efficiency and accuracy of the material spreading performance detection of the agricultural UAV.

[0178] Figure 6 This is the second flow chart of the operating method of the agricultural UAV material spreading performance detection system provided by the present invention. Figure 6 In the illustrated embodiment, a method for operating an agricultural drone material spreading performance detection system includes the following steps:

[0179] Step 610: Fix the UAV to the platform and check the working status of the flight control system and the spreading device;

[0180] Step 620: Select a circular, square, or customized sampling track, and set the sampling point location and density based on operational requirements.

[0181] Step 630: Set the flight altitude, flight attitude, and spreader speed parameters; at the same time, start the dynamic wind field model to monitor the wind field changes in the operating area;

[0182] Step 640: Start the spreading operation, and the sampling unmanned vehicle moves along the track network to collect particle distribution and meteorological data in real time;

[0183] Step 650: Calculate spreading uniformity, coverage, and particle distribution based on the collected material spreading performance parameters and meteorological data through the analysis module of the control platform, generate charts and analysis reports, and display the analysis results through the visualization module;

[0184] Step 660: Start the material cleaning and recovery module through the control platform to recover the residual particles on the ground and guide the sampling unmanned vehicle back to the initial position;

[0185] Step 670: Control the UAV platform through the control platform to guide the UAV to land in the recovery area, save the relevant test data and shut down the system.

[0186] In some embodiments, a material cleaning and recovery module is installed at the bottom of the drone platform; after generating a fertilization instruction based on the material spreading performance parameters, the method also includes: based on the material cleaning and recovery module, controlling the telescopic rod and the brush to perform material recovery operations according to the cleaning instruction; wherein, the cleaning instruction is determined based on the control platform according to the size of the area to be cleaned and the cleaning progress.

[0187] In this embodiment, the material cleaning and recovery module includes a telescopic rod and a brush; after the agricultural drone material spreading test is completed, the material cleaning and recovery device automatically unfolds the material cleaning and recovery module to clean the site, and the telescopic rod and brush device are used to ensure the efficiency and non-interference of material collection; the control platform automatically controls the operation and retraction of the brush according to the cleaning progress and area size, thereby realizing automatic recovery of materials.

[0188] Specifically, the telescopic rod can automatically adjust its length according to the size of the test area, and its maximum length can cover the entire test area; the brush device is made of soft material and has sufficient rigidity to effectively clean material particles on the ground; during the test, the material cleaning and recovery device is in a retracted state, and the brush is tightly attached to the telescopic rod body and does not interfere with the test operation; when the test is over, the control platform controls the automatic operation of the telescopic rod through control instructions, and adjusts it to an appropriate length to ensure that the entire test area is covered during cleaning. The brush on one side of the telescopic rod will automatically pop out from the retracted state with the help of elastic force when extended, and resume the cleaning function.

[0189] In this embodiment, the material cleaning and recovery device implements the following steps for cleaning the material:

[0190] (1) Extending the telescopic rod: When receiving the control command sent by the control platform, the telescopic rod gradually extends from the bottom of the platform until it reaches the radius of the test area. The brush automatically pops out as the telescopic rod extends and begins to enter the cleaning state.

[0191] (2) Start cleaning: When the telescopic rod reaches the target length, the material cleaning and recovery device moves in a circular motion around the center of the UAV platform. The brush sweeps the material particles on the ground along a circular trajectory, and gradually pushes the scattered materials to the designated concentrated area.

[0192] (3) Material recovery: After cleaning, the material particles are concentrated in one area for easy recycling by test personnel. This automated cleaning method reduces material waste, improves material recovery efficiency, and prevents materials from being scattered throughout the test site.

[0193] In this embodiment, each unit of the drone's motion control module is electrically connected to a control platform, enabling highly automated operation. The control platform allows testers to control the drone's lift and fall, attitude adjustment, and the activation time, cleaning range, and frequency of the cleaning device, ensuring the test site is cleaned immediately after each test. Furthermore, the control platform monitors the operating status of each device through sensors, ensuring the telescopic rod does not become stuck or malfunction during the cleaning process. If an obstacle is encountered during the cleaning process, the system automatically pauses the cleaning process and provides feedback to the operator, alerting them to address the problem. This improves the safety of the cleaning process and ensures the long-term stable operation of the equipment.

[0194] In this embodiment, the control platform supplies power to the tested agricultural drone through the drone motion control module. The test personnel can remotely start or cut off the power supply of the drone through the control platform, making the entire test process safer and more controllable.

[0195] The operating method of the agricultural UAV material spreading performance detection system provided by the embodiment of the present invention uses a material cleaning and recovery module to clean the test site immediately after each test, thereby ensuring the cleanliness and efficiency of the test site.

[0196] In some embodiments, the control platform includes an analysis module and a visualization module; after generating a fertilization instruction based on the material spreading performance parameters, the method further includes: calculating the material spreading performance index of the drone based on the material spreading performance parameters and the meteorological data in the environment surrounding the drone based on the analysis module, and generating charts and analysis reports based on the material spreading performance index; wherein the material spreading performance index includes at least one of spreading uniformity, material distribution and coverage rate; and based on the visualization module, displaying at least one of the material spreading performance index, chart and analysis report.

[0197] In this embodiment, the analysis module is used to receive, process, and analyze various data from drones and sampling platforms in real time, ensuring the accuracy, comprehensiveness, and multidimensionality of the data and providing a scientific basis for subsequent analysis. The analysis module specifically includes the following functions:

[0198] (1) Real-time data collection: The analysis module collects various parameters such as fertilizer uniformity, particle quality, and spreading area coverage through the communication network with the drone, sampling platform, and operation station, and transmits these data to the control platform in real time;

[0199] (2) Data analysis and feedback: The analysis module conducts in-depth analysis of the collected raw data, such as evaluating the uniformity of spreading, material distribution and coverage, and generates charts and analysis reports based on the results for reference by test personnel.

[0200] In this embodiment, after generating the chart and analysis report, the following steps are further included:

[0201] Obtaining the coefficient of variation of material spreading CV and material spreading root mean square error RMSE , and the following formula is used to calculate the evaluation results of agricultural drone material spreading operations:

[0202] ;

[0203] in, W 1 and W 2 is the weight coefficient, and the value range of the weight coefficient is 0 to 1, and W 1 + W 2 =1, the value of F is between 0 and 1, with 1 representing the best fertilization effect and 0 representing the worst.

[0204] In this embodiment, the material spreading performance index of the UAV includes the material spreading coefficient of variation ( Coefficient of Variation, CV ) and the root mean square error of material spreading ( Root Mean Square Error, RMSE ), the corresponding calculation formula for the agricultural UAV material spreading operation evaluation effect F is shown in the above formula.

[0205] For example, when testing the fertilization of agricultural drones, you can set W 1 = W 2 =0.5, and the evaluation formula for the fertilization effect is:

[0206] ;

[0207] in, for CV The maximum value of for RMSE The maximum value of CV and RMSEWhen both are close to their respective maximum values, the F value is close to 1, indicating that the fertilization effect is the best; when CV and RMSE When both are close to 0, the F value is close to 0, indicating the worst fertilization effect.

[0208] In this embodiment, the coefficient of variation of material spreading is an indicator to measure the relative discreteness of data. The sampling unmanned vehicle collects the material particle quality data at different sampling points and calculates the coefficient of variation of material spreading by combining the coefficient of variation. CV , specifically expressed by the following formula:

[0209] ;

[0210] in, is the sample standard deviation, is the sample mean; calculate the coefficient of variation of different sample points to indicate the uniformity of material spreading. The lower the CV value, the smaller the degree of dispersion of the data and the better the uniformity of fertilization.

[0211] In this embodiment, the material spreading root mean square error RMSE The deviation between the actual amount of fertilizer applied at a certain location and the target amount of fertilizer applied is used to evaluate the platform test, reflecting the average level of prediction error; combined with the root mean square error calculation RMSE , expressed by the following formula:

[0212] ;

[0213] in, For the observations (actual values), For the predicted values (target values), is the sample size; RMSE The smaller it is, the closer the predicted value is to the actual value, and the higher the accuracy of the model or method. RMSE The lower the value, the better the fertilization uniformity.

[0214] (3) The analysis module also has an intelligent feedback function, which can dynamically adjust the operating parameters of the system based on the analysis results to optimize the spreading effect and sampling accuracy.

[0215] In this embodiment, the visualization module is used by the data processing module to present the analyzed data in a visual form on the user interface, so that users can intuitively view the test results, such as fertilizer uniformity, particle distribution, etc., and facilitate the storage and management of long-term data, providing data support for subsequent analysis and trend comparison.

[0216] The operating method of the agricultural drone material spreading performance detection system provided by the embodiment of the present invention improves the accuracy and consistency of the drone's fertilization operation through the detection process control module; by setting an analysis module to receive, process and analyze various types of data from the drone and sampling platform in real time, the accuracy, comprehensiveness and multidimensionality of the data are improved; by setting a visualization module, the analyzed data is presented in a visual form on the user interface to help users intuitively view the test results, and long-term data can also be used to provide data support for subsequent analysis and trend comparison.

[0217] In some embodiments, a method for operating an agricultural drone material spreading performance detection system can comprehensively detect the performance of agricultural drones in material spreading operations such as fertilizing, sowing, and spreading feed; the method specifically includes the following steps:

[0218] (1) UAV installation and debugging: First, fix the UAV to be tested on the fixture of the UAV motion control module to avoid data deviation caused by vibration or external force during the test; after installation, debug the UAV through the control platform, check the operating status of the body and spreading device, and ensure the stability and accuracy of the spreading operation at different heights and angles.

[0219] (2) Layout and setting of sampling platforms: According to the test requirements, an appropriate number of sampling unmanned vehicles are arranged in the test area, and the sampling track network and the path of each sampling unmanned vehicle are planned through the control platform to ensure full coverage of the fertilization area; the sensors on the sampling unmanned vehicles are calibrated through the sampling platform to achieve accurate measurement of material particle quality and spreading uniformity; the data collected by the sampling unmanned vehicles are transmitted to the background detection and analysis system in real time to provide support for subsequent data processing.

[0220] (3) Adjustment of working height and angle: Before starting the spreading operation, the control platform adjusts the flight height and attitude angle of the UAV through the UAV motion control module to simulate the spreading effect under different working conditions; during the test, the control platform can automatically adjust the flight parameters of the UAV according to real-time meteorological data (such as wind speed, humidity, etc.) to evaluate the impact of environmental factors on the spreading effect and provide data support for the optimization of spreading under different conditions.

[0221] (4) Fertilization parameter detection: After the UAV starts operating, multiple sampling unmanned vehicles move along the set trajectory to monitor the material spreading amount at each sampling point in real time; the sensors on the sampling vehicles transmit the collected data (including particle distribution, spreading amount, spreading speed, etc.) to the control platform in real time, and generate intermediate reports to evaluate the spreading effect under different flight parameters and environmental conditions, and can dynamically adjust the spreading path and parameters according to the data to ensure accurate spreading.

[0222] (5) Data analysis and report generation: After the test, the control platform conducts a comprehensive analysis of the collected spreading data, meteorological environment data and related parameters, and generates a detailed analysis report; the report includes spreading uniformity, operation efficiency, the impact of environmental factors on spreading effect, etc., providing a scientific basis for the comprehensive evaluation of the UAV spreading operation performance and supporting parameter optimization in precision agriculture operations.

[0223] (6) Cleaning the test site: After the report is generated, start the material cleaning and recovery module. The telescopic rod of the material cleaning and recovery module is extended to the edge of the test area, and the elastic brush is unfolded. The scattered particulate materials are cleaned up through circular motion and pushed to the designated recovery area to ensure that the site is clean and tidy, which is convenient for the smooth progress of the next test.

[0224] (7) Material and drone recovery: After the cleaning is completed, the material cleaning and recovery module is reset, and the material particles in the recovery area are centrally processed; and the drone motion control module is controlled to land and recover the drone under test.

[0225] In some embodiments, real-time sampling, analysis, and display of material spreading performance parameters based on the control platform according to detection process control, dynamic wind field modeling, and particle trajectory calculation operations include:

[0226] (1) Dynamic wind field modeling: Based on the wind speed, wind direction, humidity and temperature parameters collected by the environmental monitoring module of the agricultural drone material spreading performance detection system, a dynamic wind field model is established within the operating area to simulate the wind field changes at different heights and within different areas;

[0227] (2) Obtaining particle motion parameters: The material spreading performance detection module of the agricultural UAV material spreading performance detection system obtains parameters such as the initial velocity, release height, and spreading angle of the particles, providing basic input for particle trajectory prediction; and calculates the air resistance of the spread particles when they move in the air. The size of the air resistance is related to the particle shape, velocity, and air density;

[0228] (3) Particle trajectory prediction: Based on the initial velocity, spreading angle, and release height of the particles, the particle trajectory and theoretical landing point under windless conditions are predicted;

[0229] (4) Wind field interference correction: Based on the wind speed and direction data provided by the dynamic wind field model, the theoretical trajectory of the sprayed particles is corrected to reflect the actual interference of the wind field on the particle landing point. The wind speed, wind direction angle and particle flight time are comprehensively considered during the correction.

[0230] (5) Prediction of the landing point of the granules: combining the theoretical trajectory and the wind field interference correction results to predict the actual landing point of the granules in the operation area;

[0231] (6) Calculation of spreading uniformity and coverage rate; spreading uniformity is represented by the ratio of the standard deviation of particle density to the mean value, which is used to reflect the uniformity of the distribution of the spread particles; spreading coverage rate is determined by the ratio of the particle coverage area to the operating area, which is used to evaluate the coverage integrity of the spreading operation;

[0232] (7) Calibration of prediction results and generation of analysis report: By comparing the predicted landing point with the measured data provided by the sampling platform, the prediction model is calibrated and the relevant parameters are corrected to generate a spreading performance test report. The report content includes information on spreading uniformity, coverage rate and wind field interference impact.

[0233] Figure 7 Schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 7 As shown, the electronic device may include: a processor 710, a communications interface 720, a memory 730, and a communications bus 740. The processor 710, the communications interface 720, and the memory 730 communicate with each other via the communications bus 740. The processor 710 may invoke logic instructions in the memory 730 to execute a method for operating an agricultural drone material spreading performance testing system. The method includes: using a sampling platform to detect the drone's material spreading performance based on the drone's motion and posture, and obtaining material spreading performance parameters. The material spreading performance parameters include particle distribution uniformity, particle impact force, particle entry angle, particle quality, and microenvironmental characteristic parameters. The control platform, based on detection process control, dynamic wind field modeling, and particle trajectory calculation, performs real-time sampling, analysis, and display of the material spreading performance parameters, generating charts and analysis reports to evaluate the agricultural drone's spreading performance. The control platform also adjusts the location and density of sampling points through a sampling layout adaptive optimization mechanism and an environmental factor quantitative modeling mechanism.

[0234] Furthermore, the logic instructions in the aforementioned memory 730 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0235] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the operation method of the agricultural UAV material spreading performance detection system provided by the above methods, the method including: based on the sampling platform, detecting the material spreading performance of the UAV according to the movement and posture of the UAV, and obtaining material spreading performance parameters; wherein, the material spreading performance parameters include the particle distribution uniformity of the spread material, the particle target force, the particle entry angle, the particle quality and the microenvironment characteristic parameters; based on the control platform, according to the detection process control, dynamic wind field modeling and particle trajectory calculation operations, the material spreading performance parameters are sampled, analyzed and displayed in real time, and charts and analysis reports are generated to evaluate the spreading performance of the agricultural UAV; wherein, the control platform also adjusts the sampling point position and density through the sampling layout adaptive optimization mechanism and the environmental factor quantitative modeling mechanism.

[0236] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0237] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0238] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. An agricultural drone material spreading performance detection system, characterized in that: include: A UAV platform is used to control the movement and attitude of the UAV, including flight altitude, heading angle, pitch angle, and roll angle; A sampling platform for detecting the material spreading performance of the drone based on the drone's motion and posture, and obtaining material spreading performance parameters; wherein the material spreading performance parameters include particle distribution uniformity of the spread material, particle target force, particle entry angle, particle mass, and microenvironment characteristic parameters; A control platform, the control platform being used to control the coordinated operation of the UAV platform and the sampling platform; the control platform sampling, analyzing, and displaying the material spreading performance parameters in real time based on the operations of detection process control, dynamic wind field modeling, and particle trajectory calculation, and generating charts and analysis reports to evaluate the spreading performance of the agricultural UAV; The control platform includes: The analysis module is used to calculate the drone's material spreading performance indicators based on the collected material spreading performance parameters and environmental meteorological data, and generate charts and analysis reports; material spreading performance indicators include spreading uniformity, material distribution, and coverage; The analysis module includes a dynamic wind field model and a particle trajectory calculation model, which are used to integrate environmental parameters with material spreading performance parameters for analysis. The dynamic wind field model is used to construct a meteorological scene in the operating area in real time using wind speed, wind direction, humidity, and temperature data. The particle trajectory calculation model is used to calculate and predict the landing point of spreading particles based on the dynamic wind field model to evaluate the impact of wind field interference on particle distribution. The control platform also adjusts the location and density of sampling points through a sampling layout adaptive optimization mechanism and an environmental factor quantitative modeling mechanism.

2. The agricultural UAV material spreading performance detection system according to claim 1 is characterized in that: The UAV platform includes: A UAV motion control module is installed in the middle area of the UAV platform, and is used to control the motion and attitude state of the UAV; A material cleaning and recovery module is installed at the bottom of the UAV platform. The material cleaning and recovery module is used to control the telescopic rod and brush to recover the ground-spread materials according to the cleaning instructions; wherein, the cleaning instructions are based on the control platform to obtain the size of the test area, the spreading coverage range and the distribution information of the remaining materials, so as to realize the recovery of all the spread materials in the test area.

3. The agricultural UAV material spreading performance detection system according to claim 1, characterized in that: The sampling platform comprises: Multiple sampling unmanned vehicles, each of which is equipped with GNSS positioning and lidar-assisted perception functions, and collects the material spreading performance parameters according to the navigation route; A networking collaboration module, wherein the plurality of sampling unmanned vehicles are respectively communicatively connected to the networking collaboration module, and the networking collaboration module is used to achieve collaborative operation and path obstacle avoidance among the plurality of sampling unmanned vehicles by sharing the real-time position data and sampling status information of each sampling unmanned vehicle; The sampling track network supports circular, square, and custom shape layouts and is arranged around the sampling platform according to any of the following sampling layout setting principles: Sampling points are evenly distributed along the radius with the UAV platform as the center to form a circular or radial track, and the radius of the circular track and the number of sampling points are determined according to the UAV spreading width and particle distribution variability; Sampling points are arranged in a uniform grid in regular plots; the horizontal and vertical spacing corresponding to each sampling point is set according to the spreading width and the size of the working area; For irregular plots or complex terrain, sampling tracks can be flexibly arranged according to the shape of the farmland, terrain changes and crop growth characteristics; During the sampling process, wind speed, wind direction, humidity and temperature meteorological parameters are monitored in real time, and the sampling point density is dynamically adjusted based on the spreading uniformity data; The environmental monitoring module is used to collect meteorological parameters within the drone's operating area and, through the collaboration of a dynamic wind field model and a particle trajectory calculation model, to detect the application trajectory in real time to assess the impact of meteorological parameters on particle distribution; the meteorological parameters include wind speed, wind direction, humidity, temperature, and air pressure.

4. The agricultural UAV material spreading performance detection system according to claim 3 is characterized in that: Each sampling unmanned vehicle includes: Chassis; the chassis includes a power system, a navigation system, a suspension structure and a shock absorbing structure; A material particle collecting device, wherein the chute of the material particle collecting device adopts a double-layer structure, and the top layer of the double-layer structure is a reversible V-shaped guide plate; A material spreading performance detection module, comprising an optical sensor, a piezoelectric sensor, and an angle sensor, for collecting information on particle distribution uniformity, particle quality, and spreading rate; The material recovery device is installed at the bottom of the sampling unmanned vehicle. The material recovery device is used to store material particle samples and has automatic weighing and spectral analysis functions.

5. The agricultural UAV material spreading performance detection system according to claim 1, characterized in that: The control platform includes: The detection process control module is used to set, adjust and control various parameters throughout the entire test process in real time. The analysis module is used to calculate the drone's material spreading performance indicators based on the collected material spreading performance parameters and environmental meteorological data, and generate charts and analysis reports. Material spreading performance indicators include spreading uniformity, material distribution and coverage rate. A visualization module is used to display material spreading performance parameters, the charts and the analysis reports, and supports real-time monitoring and historical data backtracking.

6. An operating method of an agricultural drone material spreading performance detection system, applied to the agricultural drone material spreading performance detection system according to any one of claims 1 to 5, characterized in that: include: The sampling platform detects the material spreading performance of the drone based on the drone's motion and posture, and obtains material spreading performance parameters; wherein the material spreading performance parameters include particle distribution uniformity of the spread material, particle target force, particle entry angle, particle mass, and microenvironment characteristic parameters; Based on the control platform, material spreading performance parameters are sampled, analyzed, and displayed in real time according to the detection process control, dynamic wind field modeling, and particle trajectory calculation operations. Graphs and analysis reports are also generated to evaluate the spreading performance of agricultural drones. The control platform also adjusts the location and density of sampling points through a sampling layout adaptive optimization mechanism and an environmental factor quantitative modeling mechanism.

7. The operating method of the agricultural UAV material spreading performance detection system according to claim 6, characterized in that: After generating the chart and analysis report, the method further includes: The material spreading coefficient of variation and the material spreading root mean square error were calculated based on the material spreading performance parameters, and the evaluation results of the agricultural UAV material spreading operation were calculated using the following formula: ； in, Evaluation results of agricultural drone material spreading operations, CV is the coefficient of variation of the material spreading, RMSE is the root mean square error of spreading the material; W 1 and W 2 is the weight coefficient, and the value range of the weight coefficient is 0 to 1, and W 1 + W 2 =1, the value of F is between 0 and 1, with 1 representing the best fertilization effect and 0 representing the worst.

8. The operating method of the agricultural UAV material spreading performance detection system according to claim 6, characterized in that: The real-time sampling, analysis and display of material spreading performance parameters based on the control platform according to the detection process control, dynamic wind field modeling and particle trajectory calculation operations include: Based on the wind speed, wind direction, humidity and temperature parameters collected by the environmental monitoring module of the agricultural drone material spreading performance detection system, a dynamic wind field model is established within the operation area to simulate the wind field changes at different heights and in different areas; The material spreading performance detection module of the agricultural drone material spreading performance detection system obtains the initial velocity, release height, and spreading angle parameters of the particles, providing basic input for particle trajectory prediction; and calculates the air resistance of the spread particles when they move in the air. The magnitude of the air resistance is related to the particle shape, velocity, and air density. Predict the particle trajectory and theoretical landing point under windless conditions based on the particle's initial velocity, spreading angle, and release height; Based on the wind speed and direction data provided by the dynamic wind field model, the theoretical trajectory of the sprayed particles is corrected to reflect the actual interference of the wind field on the particle landing point. The correction takes into account the wind speed, wind direction angle and particle flight time. Combining the theoretical trajectory and wind field interference correction results, the actual landing point of the particles in the operating area is predicted; Spreading uniformity is expressed by the ratio of the standard deviation of particle density to the mean value, which reflects the uniformity of the distribution of the spread particles. Spreading coverage is determined by the ratio of the particle coverage area to the operating area, which is used to evaluate the coverage completeness of the spreading operation. By comparing the predicted landing point with the measured data provided by the sampling platform, the prediction model is calibrated and relevant parameters are corrected to generate a spreading performance test report. The report content includes information on spreading uniformity, coverage rate and wind field interference impact.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the operating method of the agricultural UAV material spreading performance detection system according to any one of claims 6 to 8 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the operating method of the agricultural UAV material spreading performance detection system according to any one of claims 6 to 8 is implemented.

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