To address the challenge of imprecise detection and control of fertilizer application rates caused by high granular flow during fertilization operations, a parallel diversion detection method with real-time application rate regulation is proposed. The mechanism of uniform distribution of discrete particles formed by high-throughput aggregated granular fertilizer was elucidated. Key components including the uniform fertilizer tube, sensor detection structure, six-channel diversion cone disc, and fertilizer convergence tube underwent parametric design, culminating in the innovative development of a six-channel parallel diversion detection device. A multi-channel parallel signal detection method was studied, and a synchronous multi-channel signal acquisition system was designed. Through calibration tests, relationship models were established between the measured flow rate of granular fertilizer and voltage, as well as between the actual flow rate and the rotational speed of the fertilizer discharge shaft. A fuzzy PID control model was constructed in MATLAB2023/Simulink. Using overshoot, response time, and stability as evaluation metrics, the control performance of traditional PID and fuzzy PID was compared and analyzed. To validate the control system’s precision, device performance tests were conducted. Results demonstrated that fuzzy PID control reduced the time required to reach steady state by 66.87% compared to traditional PID, while overshoot decreased from 7.38 g·s−1 to 1.49 g·s−1. Divergence uniformity tests revealed that at particle generation rates of 10, 20, 30, and 40 g·s−1, the coefficient of variation for channel divergence consistency gradually increased with rising tilt angles. During field operations at 0–5.0° tilt, the coefficient of variation for channel divergence consistency remained below 7.72%. Bench tests revealed that the fuzzy PID control system achieved an average accuracy improvement of 3.64% compared to traditional PID control, with a maximum response time of 0.9 s. Field trials demonstrated detection accuracy no less than 92.64% at normal field operation speeds of 3.0–6.0 km·h−1. This system enables real-time, precise detection of fertilizer application rates and closed-loop regulation.
Ding et al. (Fri,) studied this question.