多意象驱动下的方向盘造型设计研究  

RESEARCH ON INNOVATIVE DESIGN OF STEERING WHEEL SHAPE DRIVEN BY MULTIPLE IMAGES

作　　者：邓昭 孙贵川 DENG ZHAO;SUN GUICHUAN

机构地区：[1]湖北工业大学工业设计学院

出　　处：《设计》2025年第2期124-128,共5页Design

摘　　要：为了满足年轻群体对汽车方向盘多个意象的情感需求,文章结合感性工学、蛛网灰靶图决策模型和BP神经网络,提出了一种系统化的多意象设计方法。首先,通过感性工学构建各样本与目标意象的判断矩阵,得出目标群体对各样本的目标意象得分;其次,运用AHP方法确定各个目标意象在实际需求中的权重,接着结合目标意象得分和意象权重计算蛛网灰靶决策系数,以此代表多意象综合评分;再者,通过形态分析法构建设计元素空间,接着构建各样本设计元素组合与决策系数的关系矩阵,为得到最优设计元素组合提供输入数据;最后,利用BP神经网络预测所有组合的决策系数并排序,得到最优元素组合。最终,通过最优元素组合设计了一款针对年轻群体的汽车方向盘,通过验证说明了该方法的有效性和可实施性。In order to meet the emotional needs of young people for multiple images of automobile steering wheels,this paper proposes a systematic multiimage design method by combining perceptual engineering,spider web gray target diagram decision model and BP neural network.Firstly,the judgment matrix of each sample and the target image was constructed through perceptual engineering,and the target image score of the target group for each sample was obtained.Secondly,the AHP method was used to determine the weight of each target image in the actual demand,and then the decision coefficient of the spider web gray target was calculated by combining the target image score and image weight,so as to represent the comprehensive score of multiple images.Furthermore,the design element space was constructed by morphological analysis,and then the relationship matrix between the combination of design elements and the decision coefficient of each sample was constructed to provide input data for obtaining the optimal combination of design elements.Finally,the BP neural network was used to predict the decision coefficients of all combinations and rank them to obtain the optimal combination of elements.Finally,a car steering wheel for young people was designed through the optimal combination of elements,and the effectiveness and feasibility of the method were demonstrated through verification.

关 键 词：多意象设计方法 感性工学 汽车方向盘 蛛网灰靶决策 BP神经网络 

分 类 号：TB472[一般工业技术—工业设计]