Research on the Adaptive Cleaning System of a Soybean Combine Harvester

Abstract

This study investigates the adaptive cleaning system of a soybean combine harvester, addressing the issue of low adaptability in matching the cleaning parameters of the air-and-screen cleaning device of domestic combine harvesters to varying soybean extract characteristics. This mismatch results in high cleaning loss and impurity rates during soybean machine harvesting. Through cleaning experiments, we examine the impact on soybean machine harvesting, where the cleaning loss rate accounts for approximately 10.08% of the total loss rate. The weight of the cleaning loss rate is lower than that of the impurity rate. Additionally, we establish a linear relationship between cleaning parameters and the corresponding cleaning loss rate and impurity rate. We design an adaptive control strategy workflow chart and integrate the adaptive cleaning system into the soybean combine harvester. Verification tests confirm the effectiveness of the adaptive control function. Comparative analysis reveals a reduction of 0.19% in cleaning loss rate and 0.98% in impurity rate compared to the air-and-screen cleaning device. The adaptive cleaning system significantly improves cleaning quality during soybean machine harvesting and enhances the intelligent capabilities of the air-and-screen cleaning device. The results provide practical insights and theoretical guidance for the development of high-quality, low-loss cleaning technology in soybean machine harvesting in China.