Analysis of the Effect of Bivariate Fertilizer Discharger Control Sequence on Fertilizer Discharge Performance

Haoran Bu, Siyao Yu, Wancheng Dong, Lixin Zhang () and Yuanqing Xia ()
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Haoran Bu: School of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Siyao Yu: School of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Wancheng Dong: School of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Lixin Zhang: School of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Yuanqing Xia: Key Laboratory of Intelligent Control and Decision-Making for Complex Systems, School of Automation, Beijing Institute of Technology, Beijing 100081, China

Agriculture, 2022, vol. 12, issue 11, 1-15

Abstract: Fertilization stability is an important index for evaluating the operational performance of variable fertilizer dischargers. To study the influence law of the combination of fertilizer discharge wheel rotational speed n and opening L on the fertilizer discharge performance, this paper firstly constructs a fertilizer amount prediction model based on a radial basis function neural network (RBFNN) through a calibration test, and after verification, its determination coefficient reaches 0.99965 with a mean relative error (MRE) of 3.88%. Then the discrete element simulation software (EDEM) was used to simulate the fertilizer discharge process under different control sequences for each of the three target fertilizer application amounts. The simulation results show that at the target fertilizer discharge rate of 944.92 g/min, when the control sequence is 18.3 r/min and 25 mm, the uniformity coefficient of variation (CV) of fertilizer discharge is the smallest. In the other control sequences, σ was higher than 20%, the stability of fertilizer discharge was poor, and the phenomenon of broken strips appeared; under the target fertilizer discharge rate of 2101.47 g/min, σ was the smallest at (24.2 r/min, 45 mm) 4.34%; under the target fertilizer discharge rate of 3842.87 g/min, σ was less than 4% in all cases, and at the control sequence (44.7 r/min, 45 mm), σ reached a minimum of 2.01%. Finally, using the simulation results and the prediction model of fertilizer amount based on RBFNN, the optimization model of fertilizer discharge control sequence based on the differential evolutionary (DE) algorithm was established, and a bench test was conducted to verify the optimization results, which showed that the accuracy and uniformity of fertilizer discharge met the operational requirements.

Keywords: fertilization stability; RBFNN; control sequence; coefficient of variation; DE (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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