Work

Optimization and Experiment of a Subsoiling Mechanism for Hilly and Mountainous Farmland Based on the Discrete Element Method

Year: 2025

Type: article

Abstract: In response to the poor soil loosening effect of the previous bionic four-bar deep loosening mechanism, this study optimized the bionic motion trajectory according to agronomic requirements, established a trajectory synthesis optimization model of the Stephenson III six-bar mechanism, and solved it using an improved differential evolution algorithm to design a six-bar deep loosening mechanism achieving the optimized trajectory. Based on the Box–Behnken experiment, a regression model of the mechanism’s process parameters and performance indicators was established, and multiple indicators were integrated into a single objective via a satisfaction function. The optimal process parameters obtained were: entry angle 99.61°, shovel distance 185 mm, forward speed 0.29 m/s, and input speed 5π rad/s. A comparative simulation using the Discrete Element Method (DEM) showed that, compared to the bionic four-bar mechanism, the six-bar mechanism reduces resistance by 9.91%, increases soil-breaking capacity by 4.23%, reduces shallow disturbance by 14.43%, increases deep disturbance by 29.54%, and improves overall disturbance effect by 42.71%, verifying the effectiveness of agronomic-driven bionic trajectory optimization. Indoor soil tank experiments measured an average resistance of 258.83 N, with a relative error of 8.67% compared to the simulation result (281.32 N). The experiments and simulations were consistent in soil-breaking layer range, soil layer disturbance range, and soil discharge state, validating the model and the six-bar deep loosening mechanism.

Source: AgriEngineering

DOI: 10.3390/agriengineering7100349

Authors: Lei Zhang, Haolong Chen, Yibin Zhai, Jianneng Chen

Institution: Zhejiang Sci-Tech University

Language: English

Topic: Soil Mechanics and Vehicle Dynamics

Subfield: Civil and Structural Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $1,930