OPTIMIZATION OF DESIGN-MODE PARAMETERS DISTRIBUTOR-MIXER OF FEEDS
The main indicators characterizing the working process of the feed distributor-mixer are the quality of mixing, the uniformity of feed delivery and the power of the working bodies of the unit. It is theoretically proved that the listed indicators depend on the density of the feed, which varies from the depth of its occurrence in the hopper of the dispenser, the specific resistance to the movement of the rake, which depends on the thickness of the separated layer, humidity and average length of the feed particles, the geometry of the fingers of the combing conveyor. The task of analytical studies of the feed dispenser-mixer includes: verification of theoretical provisions, identification of a number of physical quantities and coefficient values, as well as justification of optimal parameters and operating modes of the proposed dispenser. The search for the optimal combination of factors that affect the operation of the distributor-mixer of feed was carried out according to the method of planning a multifactorial experiment. Three parameters were selected as optimization criteria: uneven feed delivery (coefficient of variation) δ= 0.015%, specific power of the dispenser Nw=0.4 kWh/t and mixing quality υ=100%. In accordance with the task, the rational geometry of the fingers of the combing conveyor was revealed, the dependence of the specific resistance to the movement of the ore rake Р<sub>ud</sub>=270 N/m on the thickness of the separated layer ΔS=25mm, humidity W = 60% and the average length of the feed particles ℓ<sub>sr</sub>=106,5 mm was determined, the nature of the change in the density of the feed p on the depth of its occurrence in the dispenser hopper was determined, theoretical and analytical studies were carried out in order to optimize the main parameters of the dispenser. Analytical studies have determined the optimal parameters of the feed mixer distributor; we have clarified some theoretical dependencies using some physical quantities and coefficients. Using the method of planning a multi-factor experiment, the reliability of their results was evaluated in order to optimize them.