Optimization design and experiment of ginger rhizome separation device based on EDEM-RecurDyn software

根茎 计算机科学 分离(统计) 生物 植物 机器学习
作者
Wei Li,Weihua Li,Jin Cheng,Rui Hou,Jialin Hou,Yuhua Li
出处
期刊:Smart agricultural technology [Elsevier]
卷期号:12: 101382-101382
标识
DOI:10.1016/j.atech.2025.101382
摘要

During the separation of ginger rhizomes from stems, ginger stems are prone to brittle fracture due to stress concentration. To enhance ginger harvesting efficiency and minimize breakage, this study focused on the development of a low-degree-of-freedom cutting mechanism with dual-clamping. This device primarily consists of differential-speed dual chains, a cutting blade, an electric motor, a stem disposal mechanism, a drive shaft, and a support frame. Based on comprehensive mechanical testing of ginger stems—including creep, stress relaxation, puncture, and shear tests—the key mechanical and physical properties of the primary harvesting sections were determined. Utilizing an EDEM-RecurDyn co-simulation algorithm, an interaction model between the stems and the cutting blade was established. Key operational parameters investigated were blade rotational speed, cutting angle, and stem base cutting distance (the distance from the stem-rhizome junction to the cutting point), with stem cutting completeness rate and breakage rate serving as the evaluation metrics for harvesting quality. Regression models correlating these metrics with the operational parameters were developed, enabling the determination of the optimal operating parameters for the rhizome-stem separation device. The optimized parameters are as follows: blade rotational speed of 190 r/min, cutting angle of 8.8°, and stem base cutting distance of 9.5 cm. Field trials demonstrated that the optimized separation device significantly mitigated brittle fracture incidents and markedly reduced blockages. Under optimal conditions, the cutting completeness rate reached 94.9%, while the breakage rate was reduced to 4.49%. These experimental results align closely with the predictions derived from the regression model optimization. This research provides a theoretical foundation for the design of ginger rhizome-stem separation devices.

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