Simulation of draft force of winged share tillage tool using artificial neural network model

An artificial neural network (ANN) model, with a back propagation learning algorithm, was developed to predict draft requirements of two winged share tillage tools in a loam soil. The input parameters to the 3–7–1 ANN model were; share width, working depth and operating speed. The output from the network was the draft requirement of each tillage tool. The developed model predicted the draft requirements of the winged share tillage tools with a mean relative error of less than 7% and mean square errors of less than 0.05, when compared to measured draft values. This result indicates that the ANN model had successfully learnt from the training data set to enable correct interpolation and could be used as an alternative tool for modeling soil-tool interaction under specific experimental conditions and soil types

Design, fabrication and evaluation of horizontal rotary separator of olive oil (Three-Phase Decanter)

Olive is one of the strategic products in Iran, and due to the significant cultivation area of this product, oil companies should be equipped with suitable processing equipment. Unfortunately, despite the high capacity of olive in Iran, oil companies are equipped with imported machines. In this study, the construction and evaluation of the Three-counter device of Iran has been developed. The machine has three oil, water and olive pulp outputs. In order to evaluate the machine, the amount of moisture content and fat extracted from the machine was checked at 2500 and 3500 rpm and 30 and 45% water content. Also, four different samples Manzallina, Fishemi, Kalamata and Oily were used in this experiment. The main components of the machine include an electric motors chassis, machine axis, spiral conveyor and compartment. The evaluation of the device showed that the highest and lowest moisture and fat were obtained at 2500 and 3500 rpm, respectively, with a moisture content of 45 and 30%, respectively. The highest moisture content of the device was for the Manzanilla sample with 54.2% and the lowest for the Fishemi sample with 30.12%. Also, the highest and lowest amount of fat output of pulp that measured, was for oily samples (11.2%) and Kalamata (5.4%), respectively.