• DocumentCode
    3352386
  • Title

    Mechanism of eggs classification based on machine vision system

  • Author

    Zhang, Ping ; Yu, Zhihong ; Han, Baosheng ; Jia, Chao ; Wang, Liang

  • Author_Institution
    Coll. of Mech. & Electr. Eng., Inner Mongolia Agric. Univ., Hohhot, China
  • fYear
    2010
  • fDate
    26-28 June 2010
  • Firstpage
    5718
  • Lastpage
    5720
  • Abstract
    This paper proposed a new method to solve the problems in the sorting and grading process of eggs,such as eggs friability, the low efficiency and the poor accuracy of the artificial classification. The crank-rocker mechanism with vacuum suctions was used to design a set of eggs grading hardware equipments based on machine vision system. The agency not only ensured the transmitting stability of eggs and matching with the equipment of eggs quality inspection based on machine vision system but also improved the efficiency and accuracy of sorting of eggs. Diameter and shape of the sucker, vacuum degree of micro-vacuum pump, pumping speed would directly affect the adsorption results through the calculation and analysis. Then the relevant parameters of the crank-rocker mechanism was determined, the convergence and matching with the egg-quality detecting equipment were completed through Pro / E virtual kinematics simulation.
  • Keywords
    agricultural products; computer vision; pattern classification; vacuum pumps; artificial classification; crank rocker mechanism; egg quality detecting equipment; eggs classification; eggs grading hardware equipments; eggs quality inspection; machine vision system; microvacuum pump; vacuum suctions; virtual kinematics simulation; Convergence; Hardware; Inspection; Kinematics; Machine vision; Pumps; Shape; Sorting; Stability; Vacuum systems; crank-rocker; egg; grading; machine vision system; pro/E simulation; vacuum suction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-7737-1
  • Type

    conf

  • DOI
    10.1109/MACE.2010.5535818
  • Filename
    5535818