%0 Journal Article
%T 基于感性工学的运动鞋造型智能设计探究<br>Exploring the Intelligent Design of Sports Shoes Based on Kansei Engineering
%A 余铭丰
%A 吴珏
%J Design
%P 1028-1041
%@ ****-****
%D 2023
%I Hans Publishing
%R 10.12677/Design.2023.83126
%X 本文基于感性工学相关理论，结合生成式人工智能技术在产品造型设计中的应用方式及特点，提出了一种基于感性工学的产品造型智能设计方法，实现设计方案智能生成，为设计师提供灵感造型，拓展优化产品设计流程。首先，提取所研究产品的感性意象与造型样本，解构产品造型特征要素，构建形态要素编码表；其次，通过语义差异实验及数量化I类理论明确形态要素与感性意象间的映射关系，进行对应关系下的产品草图推演；最后，利用生成式人工智能将草图造型与意象词汇进行结合，实现设计方案的智能生成与优化。本研究将感性工学设计流程与生成式人工智能技术相结合，有效结合用户的感知意象需求，拓展造型设计空间，提升整体设计效率，为产品造型感性设计提供了新的思路与借鉴价值。<br />
Based on the theories related to kansei engineering, combined with the application and characteristics of generative artificial intelligence technology in product modeling design, we propose an intelligent design method for product modeling based on perceptual engineering to achieve intelligent generation of design solutions, provide designers with inspirational modeling, and expand and optimize the product design process. Firstly, we extract the perceptual imagery and modeling samples of the studied products, deconstruct the product modeling features and construct a morphological element coding table; secondly, we clarify the mapping relationship between morphological elements and perceptual imagery through semantic difference experiments and quantitative class I theory, and carry out product sketch derivation under the correspondence relation-ship; finally, we use generative artificial intelligence to combine sketch modeling and imagery vocabulary to realize the intelligent design solution Generation and optimization. The combination of kansei engineering design process and generative AI technology effectively combines the user’s perceptual imagery needs, expands the design space and improves the overall design efficiency, providing new ideas and values for the perceptual design of product shape.
%K 感性工学，产品造型设计，人工智能，形态分析<br>Kansei Engineering
%K Product Styling
%K Artificial Intelligence
%K Morphological Analysis
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=71600