Abstract

To improve the accuracy of discrete element simulation parameters for the mechanized picking and collection of pears, the study calibrated the simulation parameters of pears by the method of combining a physical experiment and simulation. Based on the intrinsic parameters of four kinds of pears (Snow pears, Crisp pears, Huangguan pears and Qiuyue pears), their simulation models were constructed by the Hertz-Mindlin with a bonding model. The simulation parameters between pears and the contact material (PVC, EVA foam material) were calibrated by the methods of free fall collision, inclined sliding and rolling, respectively. The experiments of pear accumulation angle were carried out. It was obtained to process the image of pears with Matrix Laboratory software. In order to determine the optimal value interval of influencing factors of the pear accumulation angle, the steepest ascent experiment was carried out. Considering the coefficient of collision recovery, the coefficient of static friction and the coefficient of rolling friction between pears, five-level simulation experiments of the pear accumulation angle were designed for each factor by the method of orthogonal rotation combination. The regression model of the error between the measured value and the simulated value of the pear accumulation angle was established, and the influence of three factors on the pear accumulation angle was analyzed. The results showed that the static friction coefficient and rolling friction coefficient between pears have significant effects on the pear accumulation angle. Therefore, the optimal model of minimum error was constructed according to constraint condition, and the coefficient of collision recovery, coefficient of static friction and coefficient of rolling friction between pears were obtained. The accumulation angle verification experiments were carried out by the method of bottomless barrel lifting. The results showed that the relative error between the simulated and measured accumulation angle of four kinds of pears were 1.42%, 1.68%, 2.19% and 1.83%, respectively, which indicated that the calibrated simulation parameters were reliable. The research can provide a basis for the design and parameters optimization of harvesting machinery of pears.

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