• DocumentCode
    569740
  • Title

    Research on Kansei Image in Kansei-Based Design System for CNC Machine Tools

  • Author

    Bo Chen ; Shengju Tang ; Zhang Pan ; Jiaxin Zhang ; Deke Guo

  • Author_Institution
    Eechatronic Eng. Coll., Southwest Pet. Univ., Chengdu, China
  • fYear
    2012
  • fDate
    17-19 Aug. 2012
  • Firstpage
    1220
  • Lastpage
    1223
  • Abstract
    In order to establish the perceptual function model of products, we use image semantics words to express the perceptual capabilities of CNC machine tools in the study of their image modeling design. Consider the complexity of the image information, users tend to use a relatively vague image word to express their expectations of the product, however, due to the ambiguity and uncertainty of the image information itself, the shape feature information of a product often requires the use of multiple images words to describe. In order to solve the correlation problem among them, this paper uses the principle of semantics associated of product, filters the user´s semantics, and obtains the representation semantic words to describe the shape characteristics of CNC machine tools and the correspondence between the relatively fuzzy images and the representation semantic words. This lays the foundation for the image design of CNC machine tools.
  • Keywords
    computational complexity; computerised numerical control; fuzzy set theory; machine tools; product design; CNC machine tools; fuzzy images; image information complexity; image modeling design; image semantics words; kansei image; kansei-based design system; perceptual function product model; representation semantic words; Analytical models; Computer numerical control; Correlation; Machine tools; Semantics; Shape; CNC machine tools; kansei engineering; modeling design; product image;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4673-2406-9
  • Type

    conf

  • DOI
    10.1109/ICCIS.2012.247
  • Filename
    6301337