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International Standard Serial Number:
ISSN 1001-4551
Sponsor:
Zhejiang University;
Zhejiang Machinery and Electrical Group
Edited by:
Editorial of Journal of Mechanical & Electrical Engineering
Chief Editor:
ZHAO Qun
Vice Chief Editor:
TANG ren-zhong,
LUO Xiang-yang
Tel:
86-571-87041360,87239525
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86-571-87239571
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No.9 Gaoguannong,Daxue Road,Hangzhou,China
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meem_contribute@163.com
Abstract: In order to study the conveying characteristics of viscous materials (taking wet coal particles as an example) in the conveying process of vertical screw conveyor, and to solve the multi-objective optimization problem of maximizing conveying efficiency and minimizing blade wear depth, based on discrete element method (DEM) and non-dominated sorting genetic algorithm (NSGA-II), the influence law of different conveying parameters on screw conveying characteristics was studied,and the parameters of vertical spiral conveying were optimized. Firstly, the influence of different screw speed, pitch and clearance on the vertical screw conveying characteristics was studied based on the DEM simulation. Then, the fitted regression model was subjected to analysis of variance (ANOVA), and the multiobjective model was optimally solved using the NSGA-II algorithm. Finally, the entropy weight method and grey relational method were applied for comprehensive evaluation to determine the optimal conveying parameters. The research results indicate that the average mass flow rate of coal increases with the increase of screw speed, pitch, or clearance, and the influence order of: screw speed > pitch > clearance. The maximum wear depth of blade increases with the increase of screw speed or clearance, with the increase of the pitch shows the first decrease after the increase, and the influence order of: screw speed > clearance > pitch. The optimal vertical screw conveying parameters is that screw speed (n) is 360 r/min, pitch(S) is 236.5 mm, and clearance (C) is 8.5 mm. The above research results provide a certain reference for the study of vertical screw conveying characteristics and equipment optimization design.
Key words: transport machinery; discrete element method (DEM); screw conveying characteristics; non-dominated sorting genetic algorithm (NSGAⅡ); entropy weight method; grey relational method