On the question of process control combined grain drying
Автор: Afonkina V.A., Zakhakhatnov V.G., Mayerov V.I., Popov V.M.
Журнал: Инженерные технологии и системы @vestnik-mrsu
Рубрика: Машиностроение
Статья в выпуске: 1, 2016 года.
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A large part of the grain produced in the South Urals has high humidity and needs to be dried before storage. Drying is an energy-intensive process and is about 70 % of the total energy consumption for post-harvest processing of grain. Modern grain drying equipment, implements high-convection drying, and heat provides cost 5 350-5 500 kJ per 1 kg of evaporated moisture, which is well above the theoretical calculations. Combined drying, which involves high-temperature drying step and aeration enables to reduce heat costs up to 30 %. To control the combined drying process it is necessary that final grain moisture relates to such parameters of high-temperature drying and aeration as the initial moisture content, the temperature of grain and the time subsequent aering. The paper describes the said relation as a mathematical model of the second order obtained experimentally for wheat. The model has been derived from the implementation of Box-Benkin plan for three factors - the initial grain moisture, temperature and time of grain heating and aering. The experiment was conducted for a 200 mm thick fixed grain bed. We also have got a model relating energy consumption to the said parameters. The model of the final grain moisture within the variation of factors can be used to create a control algorithm for combined drying. Taking as the set parameters final moisture, initial moisture and grain heating temperature, a microcontroller calculates the time for active aering necessary to obtain final grain moisture and an unloading mechanism provides the necessary time through regulating the discharge rate. The model makes it possible to calculate the energy usage for drying at different values of initial moisture, temperature and time of grain heating and aering.
Combined drying, moisture content, experiment, model, management
Короткий адрес: https://sciup.org/14720196
IDR: 14720196 | DOI: 10.15507/0236-2910.026.201601.032-039