基于感性工学的瑶绣文化基因在新中式家具创新设计研究

陆建军; 郑丽霞; 黄子光

doi:10.19554/j.cnki.1001-3563.2026.14.039

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包装工程（设计栏目） ›› 2026, Vol. 47 ›› Issue (14) : 453-465. DOI: 10.19554/j.cnki.1001-3563.2026.14.039

设计研讨

基于感性工学的瑶绣文化基因在新中式家具创新设计研究

陆建军^1,*, 郑丽霞¹, 黄子光²

作者信息 +

Innovative Design of New Chinese-style Furniture Based on the Cultural Genes of Yao Embroidery from the Perspective of Kansei Engineering

LU Jianjun^1,*, ZHENG Lixia¹, HUANG Ziguang²

Author information +

文章历史 +

摘要

目的针对传统感性工学（KE）在处理新中式家具设计中复杂的文化符号与用户情感需求时,存在线性模型拟合度低、难以精准捕捉非线性映射关系的问题。同时为解决瑶绣文化基因提取与应用过程中主观性过强、缺乏量化数据支撑的现状。本研究引入机器学习算法,旨在构建一种基于PSO-SVR的设计模型。方法首先,应用文化基因理论对瑶绣纹样的形态、色彩及寓意进行解析与编码,提取核心设计因子;其次,在感性工学实验中,将筛选出的“感性意象词汇”与“家具形态样本”作为评价对象,利用语义差异法（SD）获取用户评价数据,通过因子分析将大量形容词归纳为关键感性意象维度,结合模糊层次分析法（FAHP）计算各意象权重的优先级;最后,以样本的二维形态特征参数为输入量,用户感性意象评分为输出量,应用粒子群算法（PSO）对支持向量回归（SVR）的核参数与惩罚因子进行全局寻优,构建瑶绣特征与感性意象映射的模型。结论本研究推导出最优化的新中式家具设计方案,将瑶绣标志性的几何纹样与图腾符号进行了转译与现代化设计,契合了现代消费者追求“简约”“雅致”的感性审美需求。

Abstract

To address the issues of low fitting degree of linear models and difficulty in accurately capturing nonlinear mapping relationships when traditional Kansei Engineering (KE) is applied to the design of new Chinese-style furniture, which involves complex cultural symbols and users' emotional demands, and to solve the problems of excessive subjectivity and lack of quantitative data support in the process of extracting and applying the cultural genes of Yao embroidery, the work aims to introduce machine learning algorithms to construct a design model based on PSO-SVR. Firstly, the cultural gene theory was applied to analyze and code the form, color and meaning of Yao embroidery patterns, extracting core design factors. Secondly, in the Kansei Engineering experiment, the selected "Kansei image words" and "furniture form samples" were used as evaluation objects. The semantic differential method (SD) was utilized to obtain user evaluation data, and factor analysis was employed to summarize a large number of adjectives into key Kansei image dimensions. The fuzzy analytic hierarchy process (FAHP) was then used to calculate the priority of each image weight. Finally, with the two-dimensional form feature parameters of the samples as input and the user's Kansei image scores as output, the particle swarm optimization (PSO) algorithm was applied to globally optimize the kernel parameters and penalty factors of support vector regression (SVR), thereby constructing a model for mapping the features of Yao embroidery to Kansei images. The work deduces an optimized design scheme for new Chinese-style furniture, translating and modernizing the characteristic geometric patterns and totem symbols of Yao embroidery, which meets the modern consumers' aesthetic demands for "simplicity" and "elegance".

导出引用1

陆建军, 郑丽霞, 黄子光. 基于感性工学的瑶绣文化基因在新中式家具创新设计研究[J]. 包装工程. 2026, 47(14): 453-465 https://doi.org/10.19554/j.cnki.1001-3563.2026.14.039

LU Jianjun, ZHENG Lixia, HUANG Ziguang. Innovative Design of New Chinese-style Furniture Based on the Cultural Genes of Yao Embroidery from the Perspective of Kansei Engineering[J]. Packaging Engineering. 2026, 47(14): 453-465 https://doi.org/10.19554/j.cnki.1001-3563.2026.14.039

中图分类号： TB482

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