• DocumentCode
    523741
  • Title

    Research of Optimal Structural Design for Mechanical Products Based on Data Mining

  • Author

    Tao, Jing ; Yin, Niandong ; Yan, Shenghua ; Wu, Qingming

  • Author_Institution
    Sch. of Mech. & Electron. Eng., Huangshi Inst. of Technol., Huangshi, China
  • Volume
    2
  • fYear
    2010
  • fDate
    11-12 May 2010
  • Firstpage
    1047
  • Lastpage
    1050
  • Abstract
    Mechanical products normally consist of multi-parameter mechanisms. The uncertain factors resulted from the quantity of parameters and complicity of inter-relations shall give rise to problems of large dimensional arrays. Moreover, optimal models often contain functions of distinctive property, therefore feasible optimal methods are hard to find. On the basis of analyzing the optimal design methods and the data mining principles, a multi-level strategy of overall structural optimal design for mechanical products is put forth to bring out the structural optimal design rules of mechanical products based on the data mining principles which is demonstrated by the optimal structural design of the trolley frame of a gantry crane. The example shows that the data mining technology has fully tackled the issue of the optimal structural design of mechanical products.
  • Keywords
    data mining; optimisation; production engineering computing; structural engineering computing; data mining; distinctive property function; mechanical products; multiparameter mechanisms; optimal models; optimal structural design research; Data mining; Data processing; Design automation; Design methodology; Design optimization; Information filtering; Information filters; Intelligent structures; Mechanical products; Product design; data mining; multi-level strategy; optimal design; optimal models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-7279-6
  • Electronic_ISBN
    978-1-4244-7280-2
  • Type

    conf

  • DOI
    10.1109/ICICTA.2010.827
  • Filename
    5522991