DESIGN AND EXPERIMENT OF ARRAY-BASED FINGERPLATE DIFFERENTIAL FLOW SENSOR FOR RICE GRAIN MONITORING

Most existing grain flow sensors are designed for paddle-type elevators, with limited focus on applications in auger elevators. This paper addresses the yield monitoring needs during rice harvesting operations, specifically targeting auger-based outlets through experimental research. An array-type differential grain flow sensor was developed and an indoor test bench was constructed to evaluate its performance. The study compares the effectiveness of time-domain and frequency-domain differential processing, alongside various filtering methods, for pre-processing the sensor’s raw signals. Additionally, a grain flow regression model was built using the Random Forest algorithm. Experimental results demonstrated that the monitoring errors during field tests ranged from -6.42% to 8.23%, indicating that the sensor met the requirements for rice yield monitoring. This sensor provides valuable data for feed rate detection, speed regulation, and adjustments to the threshing and cleaning systems in combine harvesters, offering significant practical implications for the promotion and development of precision agriculture.