文献类型：期刊文献

英文题名：Research on Kansei Image Modeling Design of Nail Gun Products Based on Kansei Engineering

作者：Liu, Dashuai[1]; Zhang, Jie[1]

机构：[1] School of Art Design and Media, East China University of Science and Technology, Shanghai, 200237, China

年份：2022

起止页码：1

外文期刊名：2022 3rd International Conference on Intelligent Design, ICID 2022

收录：EI(收录号：20230113343415)

语种：英文

外文关键词：Cluster analysis - Engineering education - Eye movements - Image analysis - Industrial research - Semantics

摘要：In order to solve the problem that existing nail gun products' modeling can't meet the perceptual image needs of users, Kansei engineering (KE) is used to quantify the perceptual cognitive factors of consumers on nail gun products' modeling. And the corresponding relationship model between perceptual image cognition and modeling characteristics of nail gun products is established. Firstly, the samples of nail gun products and their Kansei image vocabulary are collected. Secondly, cluster analysis and KJ method are used to screen out representative samples. And then factor analysis and semantic difference method are used to screen out representative Kansei image vocabulary. Thirdly, the shape analysis method and the eye movement equipment are used to extract the shape design elements of the side profile of nail gun products. Finally, the correlation between linear design elements and perceptual image vocabulary is analyzed by using quantitative theory I, and their corresponding mathematical model for perceptual image prediction is constructed. So it provides theoretical methods and design reference for perceptual image form design of nail gun products. ? 2022 IEEE.