The Chinese Journal of Process Engineering >
Multi-variable Regression Analysis Applied to Process Optimization of Variable Temperature Drying on SiC Ultra-fine Powder Pellets#br#
Received date: 2017-01-13
Revised date: 2017-03-06
Online published: 2017-06-14
To reduce drying cost of the SiC ultra-fine powder pellets, variable temperature drying technology which had higher temperature at first and lower temperature afterwards was put forward. The temperature and wind velocity in the early and later period, together with conversion moisture content, were the main influencing factors during this process. These factors were studied by the L16(45) orthogonal experiment which using drying time and unit energy consumption as drying indexes. Multi-variable regression model combined with the weight value of each indexes were also used to fit the design conditions. The optimal parameters of variable temperature drying process were as follow: the temperature in the early period was 200℃, the wind velocity in the initial stage was 0.83 m/s, the transforming dry basis moisture content was 5%, the wind speed in the later period was 1.78 m/s, and the temperature in the later period was 140℃. Under these conditions, the drying time was 203 min and unit energy consumption was 65 MJ/kg.
Jun LI Shudong XU Hongchao ZHANG Lu WANG Peng LI . Multi-variable Regression Analysis Applied to Process Optimization of Variable Temperature Drying on SiC Ultra-fine Powder Pellets#br# [J]. The Chinese Journal of Process Engineering, 2017 , 17(3) : 600 -604 . DOI: 10.12034/j.issn.1009-606X.217114
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