Research on the Measurement Method of Feeding Rate in Silage Harvester Based on Components Power Data

Fengzhu Wang, Jizhong Wang, Yuxi Ji, Bo Zhao, Yangchun Liu, Hanlu Jiang and Wenhua Mao ()
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Fengzhu Wang: State Key Laboratory of Soil Plant Machine System Technology, Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing 100083, China
Jizhong Wang: State Key Laboratory of Soil Plant Machine System Technology, Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing 100083, China
Yuxi Ji: State Key Laboratory of Soil Plant Machine System Technology, Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing 100083, China
Bo Zhao: State Key Laboratory of Soil Plant Machine System Technology, Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing 100083, China
Yangchun Liu: State Key Laboratory of Soil Plant Machine System Technology, Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing 100083, China
Hanlu Jiang: State Key Laboratory of Soil Plant Machine System Technology, Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing 100083, China
Wenhua Mao: State Key Laboratory of Soil Plant Machine System Technology, Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing 100083, China

Agriculture, 2023, vol. 13, issue 2, 1-15

Abstract: For existing problems, such as the complex interactions between a crop and a machine, the measuring difficulty and the limited measurement precision of the feeding quantity within the corn silage harvester, a method of feeding rate measurement based on key conditions data, working data cleaning, and multiple variate regression is proposed. Non-destructive rotation speed, rotation torque, and power consumption sensors are designed for the key mechanical components. The data conditions, such as rotating speed, rotating torque, power consumption, hydraulic pressure, and hydraulic flow for the key operation of parts including cutting, feeding, shredding, and throwing are monitored and collected in real-time during field harvesting. The working data are screened and preprocessed, and the Mann-Kendall boundary extraction algorithm is applied, as is multiple component time lag correction analysis, and the Grubbs exception detection method. Based on a Pearson correlation analysis results, one-factor and multiple-factor regression models are respectively developed to achieve an accurate measurement of the corn feeding rate. The field validation tests show that the working data boundary extraction results among the load-stabilizing components such as shredding roller and throwing blower are highly reliable, with a correct rate of 100%. The power monitoring data of the shredding roller and throwing blowers are significantly correlated with the crop feeding rate, with a max correlation coefficient of 0.97. The determination coefficient of the single-factor feeding rate model based on the shredding roller reaches 0.94, and the maximum absolute error of the multi-factor feeding rate model is 0.58 kg/s. The maximum relative error is ±5.84%, providing technical and data support for the automatic measuring and intelligent tuning of the feeding quantity in a silage harvester.

Keywords: feeding rate; silage harvester; power consumption; multi-variate fusion; Mann-Kendall; data screening (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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