STUDY OF THE PROCESS OF LOADING AND LEVELING A HEAP OF ALFALFA SEEDS ONTO A DRYER CONVEYOR

Аннотация

This article presents in detail the results of a study conducted to determine the optimal combination of factors selected to determine the minimum coefficient of unevenness of loading and leveling of quail seed mixtures in conveyor dryers during the loading process into the dryer. In addition, the expressions for determining the regression coefficient, calculating the Fisher and Student tests, the results of statistical evaluation of the regression coefficient (vi), and the results of comparing the absolute value of the regression coefficient and their confidence intervals (∆vi) arepresented. Key words: unevenness, magnitude, leveling, pile, dryer, factor, screening experiment, planning, regression coefficient, criteria, optimal value, interval calibration. Introduction: The most important thing when drying the seed heap of forage crops in a conveyor dryer is the uniformity of the material leveling over the entire area of ​ ​ the conveyor, since the heap is distributed in a loosened layer of uniform density and thickness. The creation of such a layer increases the efficiency of drying, reduces drying time, fuel consumption, energy intensity oftheprocess and increases theproductivity ofthe dryer. The most important thing when drying the seed heap of forage crops in a conveyor dryer is the uniformity of the material leveling over the entire area of ​ ​ the conveyor, since the heap is distributed in a loosened layer of uniform density and thickness. The creation of such a layer increases the efficiency of drying, reduces drying time, fuel consumption, energy intensity of the process and increases the productivity of the dryer. Since the energy costs are low when using a finger working element to level the pile, the unevenness of the material leveling was chosen as the optimization parameter, which largely determines the value of the economic efficiency indicatorofthe proposed loader. Materials and methods: A comprehensive study of the technological process of the loader involves taking into account all factors that affect the course and final results of the process under study. The main course and final results of the process under study. The main requirementsfor theset of factors understudy are that they must becontrolled andmanageable. After conducting a screening experiment and selecting the most significant factors to bring them closer to the area of ​ ​ ​ ​ the optimal combination and finding the best conditions for the http://www.internationaljournal.co.in/index.php/jasass 291 Volume 15Issue 05, May 2025 Impact factor: 2019: 4.679 2020: 5.015 2021: 5.436, 2022: 5.242, 2023: 6.995, 2024 7.75 following studies, we used the method of steep ascent along the response surface, based on movement from a certain point onthesurface in thedirection of theoptimum[1,2,3]. To find the optimal combination of the selected factors with a minimum value of the unevenness of the heap leveling on the conveyor of the dryer, an experiment was conducted, including 8 experiments, constituting a semi-replica of the full factorial experiment of type 23, and a program of steep ascent along the response surface was also carried out. The experiment was conducted in triplicate in a randomized order. The planning matrix for such an experiment was constructed usingawell-known method [2,3]. Results and discussions. Based on the results of the experiment, regression coefficients were calculated andstatistically assessed based onthedependence [3]. N N N У и x У x x У iи и iи ij и в = и=1 ; в = и=1 ; в = и=1 о N i N ij N N К ( У -У )2 iи и S 2 S2 = и=1 i=1 ; S = у ; ±Dв =± tS у N(m -1) вi N i вi where У - averagevalue ofthe optimizationparameter inthe experiment; и N -number ofexperiments (number ofrows inthe experiment matrix); x , x -values ​ ​ offactors in thei-th experiment; iи ij m - number of repetitions of one experiment (one row of the plan matrix); У -values ​ ​ ofthe optimizationcriterion inparallel experiments (in theith line); iи S -squared error of theregression coefficient; вi t-tabular value t- criterion forthenumber ofmean freedom, withwhich itwas determined S2 ; у S2 -variance characterizingtheerrors of experiments inthe design matrix. у в = 12,54; в = 0,84; в = +1,52; в =+ 0,82; в = +1,50; о 4 5 8 45 в =-0,38; в =+ 0,18; S2 = 0,6365; S = 0,957; 48 58 у LF S =0,2827; Dв =± 2,12; 0,2817 = 0,5995. вi i After determining the regression coefficients, their significance was checked. The data for calculating the significance of the regression coefficients were used from the table, which presents an algorithm for calculating the adequacy of representing the experimental results by a first-degree polynomial. Comparing the absolute values ​ ​ of the regression coefficients (вi) with the absolute value of their confidence interval (∆вi), we come to the conclusion that not only linear effects, but also theirpaired interactions have asignificant impact onthe optimizationcriterion.. http://www.internationaljournal.co.in/index.php/jasass