Unmanned aerial vehicle double-nozzle fog droplet particle size deposition prediction method

Abstract

The invention relates to an unmanned aerial vehicle double-nozzle fog droplet size deposition prediction method. The method comprises the steps of placing a single nozzle at different height positions; determining the spraying width range of a single sprayer at different heights; placing the double nozzles at different heights and different spacing positions; taking the center of the distance between the two nozzles as a zero point, and measuring the droplet volume pitch diameter VMD in the spray amplitude overlapping region at different heights, different distances and different horizontal positions at a first set distance on the left and right sides; determining a droplet volume pitch diameter value V10 accounting for 10% of the total volume of droplets; measuring the deposition amount in the spray width overlapping area; dividing all independent variables and dependent variables into a modeling set and a prediction set in a fixed proportion by taking the nozzle height, the distancebetween the two nozzles, the measured VMD and V10 as independent variables and the deposition amount of each measurement point as the dependent variables, and establishing an ELM model; and based on the ELM model, determining the droplet size deposition amount. According to the method, a high-precision quantitative modeling effect is obtained by adopting a machine learning method.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to a method for predicting the deposition amount of droplet particle size with dual nozzles of an unmanned aerial vehicle. Background technique [0002] Due to its low cost, high efficiency and strong mobility, drone spraying has been widely used in agricultural fertilization and spraying operations. However, compared with ground spraying, drone spraying is more susceptible to airflow and air movement conditions. It also has problems such as excessive droplet size distribution, difficult to control deposition, and obvious droplet drift. The distribution of deposition and its uniformity are important aspects of the spraying effect of the nozzle, which intuitively reflects the uniformity of the spraying of the nozzle, but the measurement requires complicated processing or a lot of time. The current method of drone spraying measurement Mainly water sensitive paper. The droplet volume ...

AI Technical Summary

Problems solved by technology

However, compared with ground spraying, drone spraying is more susceptible to airflow and air movement conditions, and there are still problems such as excessive droplet size distribution, difficult to control deposition, and obvious droplet drift.

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