基于拖拉机姿态特征的意象认知研究

Image Cognition Based on Tractor Posture Features

中文关键词: 拖拉机姿态  意象  灰色关联分析

英文关键词: tractor posture  image  grey relational analysis

中文摘要:

      目的 挖掘拖拉机姿态与意象偏好的关系，进而指导拖拉机的造型设计。方法 采用多元尺度分析法和聚类分析法筛选拖拉机的姿态样本;运用形态分析法分解并标定典型样本的姿态特征，通过语词聚类实验构建拖拉机姿态的意象空间;结合语义差分法和问卷调研获取用户对典型拖拉机样本的意象偏好，运用灰色关联分析法得到拖拉机姿态特征与意象的关联。结果 得到拖拉机的8个典型姿态样本，获取了拖拉机姿态的四个语义维度下的五个代表性语义词对。明确了拖拉机姿态的特征框架和语义结构，归纳得到拖拉机姿态的意象认知规律。结论 拖拉机的姿态特征蕴含着意象信息，研究结果可以为设计师解读用户的意象认知提供参考。

英文摘要:

      The work aims to investigate the relationship between tractor posture and image preference, and then guide the design of tractor styling. Multivariate scaling analysis and cluster analysis were adopted to screen posture samples of tractors. The morphological analysis was employed to decompose and calibrate the posture features of typical samples, and the image space of tractor posture was constructed through lexical clustering experiments. By combining the semantic differential method and questionnaire survey, user image preferences for the typical tractor samples were obtained, and the correlation between tractor posture features and image was determined through grey relational analysis. Eight typical tractor posture samples were obtained and five representative semantic word pairs were extracted under four semantic dimensions of tractor posture. The characteristic framework and semantic structure of tractor posture were clarified, and the image cognition rules of tractor posture were inductively derived. Tractor posture features embody image information, and the research results can provide designers with references for interpreting user image cognition.