APPLICATION OF DEM-BASED ANALYSIS IN THE OPTIMIZATION OF SHOVEL DESIGN FOR THE 1JS-200 ROCK PICKER

To enhance the operational efficiency and structural design accuracy of rock-picking machinery, this study proposes a Discrete Element Method (DEM)-based approach for the optimization of the lifting shovel in the 1JS-200 rock picker. A coupling simulation model of the shovel-soil-rock system was established to analyze the dynamic interaction mechanisms between the shovel and mixed granular media. Key parameters influencing excavation performance-including forward speed, digging depth, and shovel angle-were optimized using a Box-Behnken Design (BBD) response surface methodology. Regression models were constructed for torque and rock excavation efficiency (REE), and the optimal combination was determined to be a forward speed of 0.5 m/s, a digging depth of 170 mm, and a shovel angle of 40°, under which the predicted REE reached 88.1% with a torque of approximately 386 N·m. To validate the simulation results, field tests were conducted under optimal parameter conditions. The experimental results showed that REE values fluctuated within 2%, and torque errors remained within 4% of the predicted values, confirming the accuracy and applicability of the model. This research provides a practical, data-driven design method for rock-picking implements and offers theoretical and technical support for improving rock separation efficiency, reducing structural wear, and advancing the intelligent development of agricultural machinery.