定量铺放自走式大葱联合收获机研制

为了提高大葱的机械化收获水平,该文结合大葱种植模式和农艺制度,设计了一种自走式大葱联合收获机。该机能够一次完成大葱的挖掘、抖土、喂入、夹持输送、二次去土清杂、收集、成堆铺放作业,主要由挖掘抖土装置、柔性夹持输送装置、收集卸料装置等关键部件组成。通过作业过程的理论分析和计算,确定了各关键部件参数。运用Box-Behnken中心组合试验方法,以整机前进速度、挖掘铲水平倾角、抖土频率、气缸伸缩周期作为试验因素,以大葱含杂率和损伤率为评价指标,开展了四因素三水平正交试验。通过Design-Export 8.0.6.1数据分析软件,建立各试验因素与评价指标的数学回归模型,分析各试验因素对大葱含杂率和损伤率的影响,并对试验因素进行参数优化。试验结果表明:影响大葱含杂率的各因素显著性顺序为整机前进速度>抖土频率>挖掘铲水平倾角>气缸伸缩周期,影响大葱损伤率的各因素显著性顺序为挖掘铲水平倾角>抖土频率>气缸伸缩周期>整机前进速度;最优工作参数组合为整机前进速度0.7 m/s,挖掘铲水平倾角35°,抖土频率4.3 Hz,气缸伸缩周期2.5 s,此时大葱含杂率的模型预测值为3.00%、损伤率为1.66%,田间试验的大葱含杂率为3.14%、损伤率为1.74%,与模型预测值的相对误差均小于5%。研究结果可为自走式大葱联合收获的结构完善和作业性能优化提供参考。

Development of quantitatively-laying and self-propelled green onion combine harvesters

Abstract: Green onion is an important cash crop in China, and the planting area is increasing year by year, but the harvest of green onions is mainly manual, the mechanized harvest level is less than 20%, which seriously restricts the development of the green onion production. In order to improve the level of the mechanization in green onion harvest, a quantitative laying and self-propelled combine harvester of green onion is designed by combining the planting mode and agronomic system of the green onion. The function of the quantitative laying and self-propelled green onion combine harvester includes digging, shaking, feeding, clamping and conveying, twice removing soil and cleaning, collecting and unloading. The machine is mainly composed of digging and shaking device, flexible clamping and conveying device, collecting and unloading device. According to the Agricultural Machinery Design Manual and the relevant test standards of harvesting machinery, the key parameters of the harvester are determined by theoretical analysis and calculation. In order to obtain the optimal working parameters and related theoretical references of the quantitative laying and self-propelled green onion combine harvester, the Box-Behnken central composite experimental design principle is used. The four-factor and three-level orthogonal experiments are carried out, taking the machine forward speed, the horizontal inclination of digging shovel, the frequency of soil shaking and the cylinder expansion cycle as the influence factors, and the impurities rate and the damage rate of green onion as the response indexes. Through the Design-Export 8.0.6.1 data analysis software, the mathematical regression models of the influence factors and the response indexes are established, and the influence of the machine forward speed, the frequency of soil shaking, the horizontal inclination of digging shovel and the cylinder expansion cycle on the impurities rate and the damage rate of green onion are analyzed, and the parameters are optimized. The field test results showed that the significant order of the factors that affect the impurity rate of green onion is as follows: the machine forward speed, the frequency of soil shaking, the horizontal inclination of digging shovel and the cylinder expansion cycle. The significant order of the factors that affect the damage rate of green onion is as follows: the frequency of soil shaking, the horizontal inclination of digging shovel, the cylinder expansion cycle and the machine forward speed. The optimal combination of the operation parameters is that the machine forward speed is 0.7 m/s, the horizontal inclination of the digging shovel is 35°, the frequency of soil shaking is 4.3 Hz and the cylinder expansion cycle is 2.5 s. In this case, the field verification tests are performed, the field verification and the test results show that the average impurities rate of green onion is 3.14%, the average damage rate of green onion is 1.74%, and the model prediction values of that are 3.00% and 1.66% respectively, the relative error between the prediction values and the field test values are less than 5%, the design is reliable. The research results can provide some reference for the optimal design and operation parameters optimization of self-propelled green onion combined harvester.