• 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