Development of quantitatively-laying and self-propelled green onion combine harvesters
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Abstract
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 horizontal inclination of digging shovel, the frequency of soil shaking, 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.
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