Journal of Applied Science and Engineering

Published by Tamkang University Press


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Yun-Fei Fu1, Jie Gong1, Zheng Peng1, Ji-Hua Li1, Si-Dong Li1, Pu-Wang Li This email address is being protected from spambots. You need JavaScript enabled to view it.1 and Zi-Ming Yang This email address is being protected from spambots. You need JavaScript enabled to view it.1

1Agricultural Product Processing Research Institute at Chinese Academy of Tropical Agricultural Sciences, Chinese Agricultural Ministry Key Laboratory of Tropical Crop Products Processing, Zhanjiang 524001, P.R. China


Received: July 31, 2015
Accepted: November 22, 2015
Publication Date: June 1, 2016

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The aim of this study is to minimize the specific energy consumption of the screw wash-sand machine. Let the diameter of the screw structure, pitch, diameter of the screw axis, blade thickness, installation angle, and the speed of the screw axis be the design variables, and take the minimum specific energy consumption as the optimization objective. According to the complexity of the optimization problem in this study, the fruit fly optimization algorithm (FOA) is used to execute the optimization design of the screw wash-sand machine. The non-stationary multi-stage assignment penalty function is adopted to cope with the constrained optimization problem. To judge the stability and reliability of the optimal solution and find the sensitive factors of the optimization design, the sensitivity analyses of the objective function and constraint conditions to the design variables are carried out. By simulation, the optimized structure parameters of the screw wash-sand machine and the data of the objective sensitivity and constraint sensitivity are obtained. The simulation results show that the specific energy consumption decreases by 4.59%; the diameters of the screw structure and screw axis are sensitive factors of the optimization design.

Keywords: : Fruit Fly Optimization Algorithm, Non-stationary Multi-stage Assignment Penalty Function, Wash-sand Machine, Sensitivity Analysis, Specific Energy Consumption


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