Research on Optimization of Digging Shovel Parameters for a Garlic Harvester Based on Soil Damage Evolution
Year: 2025
Type: article
Abstract: The digging mechanism is the component of garlic harvesters that consumes the most energy. Consequently, there are theoretical gaps in the design of resistance reduction. These gaps are due to the complexity of the interaction dynamics between the shovel and the soil, and the insufficient understanding of the evolution patterns of soil damage. To address these challenges, this study develops a finite element model of the shovel–soil system using damage mechanics to characterize nonlinear interaction mechanisms under operational loading conditions. The methodology integrates three critical phases: (1) soil damage evolution analysis was employed to identify key damage parameters for model calibration; (2) systematic finite element simulations were used to evaluate the effects of system variables—entry angle, shovel blade bevel angle, forward speed, and vibration frequency—on forward resistance; (3) orthogonal experimental optimization of these parameters was carried out. Key results include the following: (i) A nonlinear relationship was identified between variables (entry angle, forward speed, and vibration frequency) and resistance reduction. Furthermore, the threshold for optimal performance was determined. The optimal parameters were identified as an entry angle of 20°, a forward speed of 0.39 m/s, and a frequency of 2.6 Hz. (ii) Validation through soil bin experiments, demonstrating strong agreement between simulated and measured load–displacement responses, confirming the predictive accuracy of the model. The research presented in this paper may offer insights into the principles of low-resistance designs for underground fruit harvesting.
Source: Agronomy
Authors: Rundong Zhou, Jianxi Ding, Yongjian Wang, Hua Li, Yuqing Li, Yanyan Ge, Xiao Yin
Institution: Nanjing Agricultural University
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $3,137
Funder: Government of Jiangsu Province
OpenAlex ID: W4408923553
