Modeling and optimization of parameters of flow rate of paddy rice grains through the horizontal rotating cylindrical drum of drum seeder

Abstract

An experimental investigation was conducted to model the complex flow rate of paddy rice grains through the orifices on the circumference of the horizontal rotating cylindrical drum of a hand tractor drawn or self-propelled drum seeder using regression analysis and Artificial Neural Network (ANN). The dimensional analysis approach was followed to develop various dimensionless terms and study their effect on the flow rate. In the range of parameters studied, it was observed that the flow rate of paddy rice grains through the orifices of the drum increased with increase in Froude number and decreased with increase in orifice spacing to diameter ratio and drum fill ratio. A 4-9-5-1 neural network was found to predict the flow rate better than regression equation with overall mean absolute percentage relative error of 4.85%. Optimization technique based on Fast Non-dominated Sorting Genetic Algorithm (NSGA-II) was used to determine the levels of drum–grain-operating parameters for achieving the optimum flow rate to obtain the seed rate of 80 kg/ha with minimum deviation from its mean value with emptying of drum. The optimum drum configuration was found to be the one with 36 orifices of 6 mm diameter on its circumference. The drum was required to be initially filled to the extent of 53% of its total volume. Optimum speed of rotation of drum was 61 rpm which resulted in the forward speed of operation of 4.60–6.90 km/h if the forward speed of operation to peripheral speed of drum is in the range of 2:1 to 3:1. The outcome of the study will be useful for precise planting operation and the development of suitable systems for maintaining uniformity of seeding under field conditions.