DocumentCode
3105719
Title
Intelligent Operation Parameters Optimization for Screw Conveyor Based on PSO
Author
Cai, Jianghui ; Meng, Wenjun
Author_Institution
Mech. & Electron. Eng. Coll., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
fYear
2010
fDate
26-28 Sept. 2010
Firstpage
37
Lastpage
40
Abstract
Particle swarm optimization (PSO) is a population based stochastic optimization technique. As a result, PSO algorithm is widely used in mechanical engineering design field. Screw conveyors are used extensively in agriculture and processing industries for elevating and/or transporting bulk materials over short to medium distances. They are very effective for conveying dry particulate solids, giving good control over the throughput. Despite their apparent simplicity, the transportation action is very complex and designers have tended to rely heavily on empirical performance data. Intelligent operation parameters optimization for screw conveyor based on PSO is studied in this paper. This thesis takes a heavy driving drum of screw conveyor as an example, firstly, the optimization function is built up, then the operation parameter of screw conveyor is precision optimized with PSO algorithm, which offer a foundation to design more reasonable structure for driving drum in order to meet the application demands.
Keywords
conveyors; mechanical engineering; particle swarm optimisation; agriculture; heavy driving drum; intelligent operation parameters optimization; mechanical engineering design field; optimization function; particle swarm optimization; processing industries; screw conveyor; stochastic optimization; Algorithm design and analysis; Equations; Fasteners; Materials; Mathematical model; Optimization; Particle swarm optimization; Particle swarm optimization; parameters optimization; screw conveyor;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Aspects of Social Networks (CASoN), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-8785-1
Type
conf
DOI
10.1109/CASoN.2010.16
Filename
5636805
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