Experimental Study of Multiscale Fresh Tea Leaf Sorting Device with Intelligently Controlled Drum–Axial Airflow Coupling Based on Response Surface Methodology

Abstract

This study describes a self-developed intelligently controlled drum–axial airflow coupled sorting device. Using the sorting rate as the evaluation index, single-factor tests were conducted to analyze the influence patterns of axial airflow startup time, drum rotational speed, and axial airflow velocity on the sorting effect. The Box-Behnken response surface design method was adopted to construct a quadratic regression model for the sorting rate, analyze the interaction between factors, and conduct parameter optimization and verification. All three test factors had an extremely significant effect on the sorting rate. Among them, the quadratic effect of axial airflow velocity was the strongest, and parameter fluctuations had the highest sensitivity to the sorting results. Significant coupling interaction between axial airflow startup time and drum rotational speed was observed. Through global optimization, the following optimal process parameter combination was obtained: axial airflow startup time, 6.5 s; drum rotational speed, 16 rpm; and axial airflow velocity, 7.5 m/s. Under these conditions, the measured average sorting rate reached 80.46%, with a relative error of only 1.03% compared with the model predicted value, indicating good model prediction accuracy. These results can provide a theoretical basis and technical support for the research and development of intelligent sorting equipment for multiscale fresh tea leaves and optimization of process parameters.