| Design and experiment of small narrow range segmented soybean harvester in hilly area |
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| DOI：10.7606/j.issn.1000-7601.2024.05.29 |
| Key Words: soybean harvester hilly and mountainous areas narrow and low loss segmented type design experiment |
| Author Name | Affiliation | | LUO Hongbo | School of Intelligent Manufacturing,Longdong University, Qingyang, Gansu 745000, China
School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an, Shaanxi 710048, China | | WANG Jianji | School of Intelligent Manufacturing,Longdong University, Qingyang, Gansu 745000, China | | LIAN Xiao | School of Intelligent Manufacturing,Longdong University, Qingyang, Gansu 745000, China | | GENG Baolong | School of Intelligent Manufacturing,Longdong University, Qingyang, Gansu 745000, China | | LI Feng | Qingyang Academy of Agricultural Sciences, Qingyang, Gansu 745000, China |
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| Abstract: |
| To solve the problems of lack of small suitable machines for soybean harvesting in hilly and mountainous areas and high loss and breakage rates, a small narrow\|width segmented soybean harvester in hilly and mountainous areas was designed. The device was mainly composed of plucking wheel, reciprocating cutting cutter, conveyor chain plate and other components. Based on the landform characteristics of hills and mountains, physiological characteristics of soybean plants, the dynamic behavior of equipment during harvesting and working, the rotation speed of plucking wheel, installation height, reciprocating speed of cutting table, cutter parameters and conveyor belt were optimized. Based on the response surface single factor test, the order of significance of the influence of each factor on the loss rate and crushing rate as follows: rotary speed of rotary wheel > cutting speed of cutter > rotary height of rotary wheel. Through parameter optimization analysis, it was determined that the optimal operation parameter combination of soybean harvesting rotary speed was 51 r·min-1, 78 cm rotary height and 1.5 m·s-1 cutter speed. The predicted loss rate was 1.57% and the damage rate was 1.4%. The experiment results showed that the loss of the whole machine decreased from the highest 2.21% to 1.60%, the damage rate decreased from the highest 2.03% to 1.35%, and the relative error between the measured value and the model optimization value of each index was less than 3%, meeting the requirements of relevant national standards. |
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