WITHDRAWN: Structural optimization design of spiral-driven grain detection robot based on EDEM-RecurDyn
Qiang Yin, Xin Xia, Xiaopeng Liu, Yonglin Zhang, Shaoyun Song, Li Hui
- Year
- 2025
- Citations
- 1
Abstract
In order to replace the traditional grain condition measurement and control system to complete the grain condition detection operation inside the grain pile, design a robot that can drill into the inside of the grain pile and realize the grain condition detection operation inside the pile. According to the actual operation scenario, the overall structure and drive form of the grain detection robot are determined, and the torque balance equation of the spiral drive wheel in the grain pile is established based on the principle of ground science. Optimize the structural parameters of the spiral drive wheel using RecurDyn-EDEM coupled simulation, take the lift angle, height, number of spiral blades and the taper angle of the outer contour of the spiral drive wheel as the optimization target parameters, and take the speed, axial resistance magnitude, torsional resistance moment and propulsive efficiency as the evaluation indexes, and analyze the influence of different parameters on the motion performance of the spiral drive wheel. A test platform is built to test the torque and displacement of the helical drive wheel, and the difference between the simulated and experimental values under the same experimental conditions is compared to prove the high reliability of the simulation model, and to test the kinematic performance of the food situation detection robot. The simulation results show that the kinematic performance of the helical drive wheel is best when the helical lift angle of the helical drive wheel is 35°, the maximum height of the helical blades is 35mm, the taper angle of the outer contour of the helical drive wheel is 20°, and the number of the helical blades is 4 pieces. The kinematic performance test experiment shows that when the rotational speed of the spiral driving wheel is 30r/min, the prototype dives to about 460mm below the grain surface after 32s, with an average dive speed of about 14mm/s and an average slip rate of 78.21%. The comparison experiment proves the high reliability of the simulation model. The motion performance test experiment shows that the grain detection robot can drill into the internal operation of the grain pile, and subsequently can be equipped with a variety of sensors to complete such operations as temperature and humidity detection, cuttings, turning grain and so on.
Keywords
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