甘薯联合收获机高度自适应集薯装置设计与优化

甘薯收获是甘薯生产中用工量最多、劳动强度最大的环节。为了解决甘薯联合收获机集薯环节存在伤薯率高、自动化程度低等问题，该研究开展了高度自适应集薯装置的机械结构设计与控制系统搭建。系统及结构设计充分考虑物料物理性状及作业过程中的运动学与力学特性，通过新的集薯方式以满足落薯高度自适应、集薯装筐和自动卸料换筐等作业要求。通过落薯高度自适应功能减小并控制薯块下落的高度达到有效减少甘薯伤薯率与破皮率的目的。在单因素试验分析结论的基础上，以清选平台转速、落薯机构转速和落薯设定高度为试验因素，开展三因素三水平Box-Benhnken试验，以伤薯率、破皮率、微破率和损伤率为试验指标建立多元回归方程并进行响应面分析。回归模型进行多目标优化后获得装置最优工作参数组合为：清选平台转速108.07 r/min、落薯机构转速74.75 r/min、落薯设定高度18.15 cm。对优化结果进行验证试验，试验结果为：伤薯率0.39%、破皮率0.54%、微破率22.93%和漏薯率0.54%，各评价指标与模型预测值相近。研究结果可为甘薯联合收获机高度自适应集薯装置进一步设计与优化提供参考。

Design and optimization of the height self-adjusting device for sweet potato combined harvesters

Abstract: Sweet potatoes have been one of the most favorite root vegetables in the world. However, manual harvesting cannot fully meet large-scale production in recent years, due to the high costing and labor intensity. It is a high demand for a low injury rate and high-level automation during collecting sweet potatoes in a combine harvester. In this study, the mechanical structure and control system were designed and constructed for the highly adaptive sweet potato collecting device. Full consideration was also given to the physical properties of materials, the kinematic and mechanical characteristics of the operation. A series of operations were then realized, including the self-adaptative dropping height, collecting potatoes, loading baskets, as well as automatically unloading and changing baskets using innovative potato collection. The height of the falling potato block was real-time adjusted to effectively reduce the sweet potato damage and broken skin, according to the adaptive function. The three-factor three-level Box-Benhnken test was conducted to explore the influencing factors on the sweet potato quality during the collecting operation after the single-factor test. Multiple regression equations were established to obtain the optimal combination of working parameters. The response surface analysis was carried out with the test indexes of injury rate, skin break rate, micro-break rate, and damage rate. The results showed that: The peeling rate of sweet potato depended mainly on the interactive effect between the rotational speed of the dropping device and the dropping height of the sweet potato. The missing rate of sweet potato depended on the interactive effect between the rotational speeds of the cleaning platform and the dropping device. The dropping height of the sweet potato posed a highly significant effect on the injured and peeling rate of the sweet potato. There was no significant effect of the rest factors on the test index. After multi-objective optimization of the regression model, the optimal combination of working parameters was obtained as follows: the rotation speed of the cleaning platform was 108.07 r/min, the rotation speed of the sweet potato dropping mechanism was 74.75 r/min, and the dropping height of the sweet potato was 18.15 cm. A field test was conducted to verify the optimization. The test results were as follows: The damage, peeling, micro-peeling, and missing rates of sweet potato were 0.39%, 0.54%, 22.93%, and 0.54%. Anyway, better consistence was achieved between the evaluation and prediction of the model. The findings can provide a strong reference to further design and optimize the highly adaptive harvester for the sweet potato.