Development of a mathematical regression model of the beet pulp pressing process carried out on a deep press extruder

Abstract

The article is devoted to the development of a mathematical regression model of the beet pulp  pressing process carried out on on a deep press extruder. The following parameters of beet pulp pressing were taken as initial ones: initial moisture content (before the extruder) and final moisture content (after the extruder); sugar content in the pulp before and after pressing; sugar content in the pulp; beet chips length before and after pressing; total biological contamination of sugar beet pulp; pulp acidity before and after pressing; acidity of the granulated pulp. The Fuzzy Logic Toolbox module included in the MatLab package is used to implement the proposed technique. The Surfase Viewer module is used to present the simulation results in a graphical form. Such studies were previously carried out with the CurveExpert 1.3 application package. The resulting equations adequately describe the change in the sugar content in the pulp and its nutritional value depending on the pulp acidity and moisture content, as well as the length of the sugar beet chips. The significance of the influence of each of the main technological parameters (acidity and moisture content of the beet pulp, the length of the beet chips) on the amount of sugar in the pulp and its nutritional value was determined in the work. The resulting quadratic dependences having sufficiently high coefficients R2, adequately describe the process of beet pulp pressing in a deep press extruder with an assessment of the influence of variable parameters on the content of residual sugar and feed units in beet pulp. The data obtained make it possible to objectively evaluate the work of a deep-pressing exstruder and justify the kinematic mode of the screws rotation, which allows minimizing the cost of finished products.