Grain Flow Measurement Method Based On Infrared Photoelectric Effect

Grain flow sensor is the core component of a combine harvester production measurement system.Photoelectric volumetric method is widely used for grain flow measurement at present.The accumulation shape of grain on the scraper plate of the elevator is an important factor affecting the measurement accuracy of photoelectric volumetric method.In order to reduce the measurement error of grain flow caused by irregular accumulation shape,this paper designs a grain thickness measurement sensor based on infrared photoelectric effect,introduces neural network modeling,develops a grain flow monitoring system,and carries out experimental verification on the elevator test bench.The main work includes the following aspects:1.Design of infrared photoelectric grain thickness measuring sensor.In order to obtain the change of grain thickness,a grain thickness measurement method based on infrared photoelectric effect is proposed.The infrared laser source and silicon photocell are selected as the transmitter and receiver of the sensor,and the I/V conversion processing circuit with T-network as the core is designed.According to the size of the scraper of the elevator,a grain thickness measurement test bench is designed,and the grain thickness measurement experiment is completed on the test bench.According to the relationship between output voltage and grain thickness,Gaussian function equation is established by least square fitting,and the effects of laser emission power,infrared wavelength,different varieties of rice and different moisture contents of the same variety of rice on the grain thickness measurement performance of the sensor are analyzed.2.Design of grain flow monitoring system.According to the structure of the combine harvester elevator,a single scraper grain flow measurement test bench is designed.The scraper is driven by a stepping motor,and the speed of the scraper is adjusted by a programmable controller of the stepping motor.A LED array photoelectric grain thickness measuring sensor is installed on the side plate of the test stand to measure the change of grain thickness in different sections during the lifting and transportation of the scraper,and an output signal acquisition system of the sensor is designed.3.Grain flow measurement method.The BP neural network is used to establish the functional relationship between the grain quality on the scraper and the output voltage signal of the sensor,to obtain the grain quality on each scraper,and to calculate the grain flow rate in combination with the elevator speed.The influence of different number of input neurons on the fitting error of neural network and the influence of different rice varieties and different sampling frequencies on the grain quality measurement performance of BP neural network were analyzed.The grain flow measurement test was carried out on the scraper elevator test bed.According to the test results,the influence of rice feeding amount on the grain flow measurement accuracy was analyzed and compared with the existing photoelectric volumetric measurement method.