An approach to compensation of dust effects on seed flow sensors

Abstract

Optical seed mass flow sensors are widely used on seed drills and planters. An important challenge in these sensors is their malfunction in a dusty condition. Dust caused by soil and seeds may sit on the light elements and disrupt its function. In this study, an approach was developed to compensate this effect. A non-contact intelligent system with infrared diodes and a microcontroller with ARM architecture was built up to monitor the seed flow in the delivery tube of seed drills. At the hardware phase, a glass with a different radius of curvature was installed in front of the elements. The semi-cylindrical glass placement in front of the optical elements meant that the arrangement was sealed against dust. Besides, the fall of the seeds tangential to the glass during the sowing caused the glass to self-clean. However, the hardware configuration of the seed flow sensor with semi-cylindrical glass alone was not sufficient under adverse dusty conditions. A suitable algorithm was therefore developed and applied to compensate for the dust effect. In this case, instead of the level of output voltage, MS (mean of variances) of sensor outputs was calculated. The mass flow estimation model was obtained using multiple regression between the MS index of the seed flow sensor and digital scale data. Experiments were carried out using different types of seeds in several repetitions. In all tests, the correlation coefficient of the mass flow estimation model was obtained above 0.9. The results revealed that this system works correctly and precisely in dusty field conditions without having to clean the sensing elements.