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Position: Home > Articles > Mathematical model of feeding rate and processing loss for combine harvester Transactions of the Chinese Society of Agricultural Engineering 2011,27 (9) 18-21

联合收割机喂入量与收获过程损失模型

作  者：
陈度;王书茂;康峰;祝青园;李晓华
单  位：
洛阳中收机械装备有限公司;厦门大学物理与机电工程学院;中国农业大学工学院;北京林业大学工学院
关键词：
收割机;喂入;数学模型;收获损失
摘  要：
为了研究联合收割机喂入量与收获过程损失率之间的关系,该文对联合收割机喂入量和收获损失的影响因素进行了详细分析,采用3种模型试验研究了喂入量与收获过程损失的关系,基于新疆-2A型联合收割机的试验样本建立了基于幂函数、指数函数和二次函数的关系模型,其中二次函数模型具有较高准确性,其决定系数R2=0.826,并利用喂入量控制试验装置进行验证。试验表明,当喂入量在0.3～4.1 kg/s的范围内时,收获过程损失率实测值与二次函数模型计算值的绝对偏差范围为0.04%～0.91%,吻合较好,说明所建立的二次函数模型具有良好的准确性。该模型可作为预测试验用样机收获过程损失的有效工具。
译  名：
Mathematical model of feeding rate and processing loss for combine harvester
作  者：
Chen Du1,Wang Shumao1,Kang Feng2,Zhu Qingyuan3,Li Xiaohua4 (1.College of Engineering,China Agricultural University,Beijing 100083,China;2.School of Technology,Beijng Forestry University,Beijing 100083,China;3.School of Physics and Mechanical and Electrical Engineering,Xiamen University,Fujian 361005,China;4.Luoyang Zhongshou Machinery Equipment Co.,Ltd.,Henan 471000,China)
关键词：
harvesters,feeding,mathematical models,processing loss
摘  要：
To investigate the relationship between feeding rate and harvest loss of combine harvesters, the paper intensively analyzed the factors that influenced feeding rate and harvest loss for combine harvester. The mathematical model between feeding rate and processing loss was established using three functions (power, exponential and quadratic) based on field test samples of Xinjiang-2A combine harvester. The model based on quadratic function showed the highest accuracy and its coefficient of determination was 0.826. Validation experiment was conducted to verify developed model through feeding rate controllable equipment. The results showed that when the feeding rate was between 0.3-4.1 kg/s, the absolute deviation between measured processing loss and calculated value was in the range of 0.04%-0.91%. It indicated that the developed quadratic model was accurate. It is concluded that the developed model could be capable of predicting the processing loss for the tested machine.

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