Granular Material Spreading Performance Detection System For Agricultural Unmanned Aerial Vehicle And Operation Method Thereof

A material spreading performance detection system for an agricultural unmanned aerial vehicle, comprising:

• an unmanned aerial vehicle platform, configured to control motion and attitude of an unmanned aerial vehicle, wherein the attitude comprises a flight height, a heading angle, a pitch angle, and a roll angle;
• a sampling platform, configured to detect material spreading performance of the unmanned aerial vehicle according to the motion and attitude of the unmanned aerial vehicle to obtain material spreading performance parameters, wherein the material spreading performance parameters comprise particle distribution uniformity, a particle on-target impact force, a particle slot entry angle, particle mass, and micro-environment characteristic parameters of spread materials;
• and
• a control platform, wherein the control platform is configured to control collaborative operation of the unmanned aerial vehicle platform and the sampling platform, the control platform is configured to collect in real time, analyze, and display the material spreading performance parameters based on operations of detection process control, dynamic wind field modeling and particle trajectory calculation, and generate a chart and an analysis report for evaluating spreading performance of the agricultural unmanned aerial vehicle;
• the control platform comprises:
• an analysis module, configured to calculate material spreading performance indicators of the unmanned aerial vehicle according to collected material spreading performance parameters and environmental meteorological data, and generate the chart and the analysis report, wherein the material spreading performance indicators comprise spreading uniformity, material distribution, and a coverage rate;
• the analysis module comprises a dynamic wind field model and a particle trajectory calculation model, and is configured to perform fusion analysis on environment parameters and the material spreading performance parameters, wherein the dynamic wind field model is configured to construct a meteorological scene in an operation area in real time through wind speed, wind direction, humidity, and temperature data, and the particle trajectory calculation model is configured to calculate and predict landing positions of spread particles based on the dynamic wind field model, thereby evaluating influence of wind field interference on particle distribution;
• and
• the control platform is capable of further adjusting positions and density of sampling points through a sampling layout adaptive optimization mechanism and an environmental factor quantitative modeling mechanism.