Optimization and experimental analysis of sweet potato ship-shaped transplanting trajectory using particle swarm algorithm

The mechanization of ship-shaped transplanting is currently an urgent problem that should be solved. The movement trajectory of the transplanting mechanism is the key technology to perform ship-shaped transplanting. In this study, a ship-shaped transplanting trajectory was built and a mathematical model of a four-link transplanting mechanism was developed based on the requirements of the sweet potato transplanting agronomic technology. The particle swarm optimization algorithm was used, with the length of the four-bar mechanism and the installation angle of the fixed bar serving as the variables to optimize. The objective was to minimize the deviation of the ship-shaped transplanting trajectory, yielding an iterative optimization solution. The MATLAB simulation results showed that the penalty factors of different proportions in the adaptive particle swarm optimization algorithm affected the transplanting trajectory. The optimal penalty factor parameters are α=0.6, β=0.4. They ensure that the transplanting trajectory fulfills the agronomic requirements, and limit the deviation in the return trajectory of the mechanism. The sizes of the optimized four-bar mechanism were 110, 312, 245, 160, 360, and, 160 mm. The determined installation angle was 100°. The results of the field experiments demonstrated that the optimized four-bar transplanting mechanism can better fulfill the agronomic technical requirements of sweet potato ship-shaped transplanting. For a transplanting speed of 0.2 m/s, the average qualified rates of insertion depth, insertion length, and tail height were equal to 94.00%, 93.83%, and 91.67%. The results obtained in this study provide a theoretical basis and technical support for studying and developing sweet potato ship-shaped transplanting machinery.