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

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