Journal of Textile Research ›› 2022, Vol. 43 ›› Issue (04): 160-166.doi: 10.13475/j.fzxb.20210502307

• Machinery & Accessories • Previous Articles     Next Articles

Drawing frame modeling design based on Kansei image

DUAN Jinjuan1(), XUAN Aiqi1, YUAN Bo2, LI Na'na3   

  1. 1. School of Mechanical Engineering, Tiangong University, Tianjin 300387, China
    2. Department of Aeronautical and Automotive Engineering, Loughborough University, Leicestershire LE11 3TU, UK
    3. School of Textile Science and Engineering, Tiangong University, Tianjin 300387, China
  • Received:2021-05-11 Revised:2022-01-04 Online:2022-04-15 Published:2022-04-20

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Abstract:

Based on Kansei engineering and quantification theory I (QTI), the proposed paper took the drawing frame as an example to carry out design and experimental research in order to meet users' perceptual needs for textile machinery modeling and improve modeling design efficiency and optimize recommendation. Representative samples and Kansei antonym words of the drawing frame were selected and determined, and the users' Kansei evaluation data were obtained through experiments. Based on QTI, the mapping models between Kansei image of the drawing frame and the modeling design elements were established. Taking the "cumbersome-simplicity" semantic dimension as an example, modeling design recommendation strategies were obtained. Through design practice and user evaluation, the accuracy and reliability of the correlation model were verified. The results show that the drawing frame correlation model based on Kansei engineering and QTI has prediction accuracy and reliability, and it can provide designers with more accurate and specific design strategy recommendations, improve design efficiency and users' satisfaction.

Key words: Kansei image, quantification theory I, drawing frame, textile machinery, modeling design

CLC Number: 

  • TH122

Fig.1

Figures of representative drawing frame samples"

Fig.2

Drawing frame modeling category division step"

Fig.3

Kansei image evaluation questionnaire"

Tab.1

Mean value of Kansei evaluation of representative samples"

感性意
向词对		 样本感性意象评价均值
1 2 3 … 22 23 24
突兀-协调 4.47 4.13 4.53 … 5.67 4.03 2.90
冰冷-亲和 3.63 3.57 3.53 … 5.03 2.80 2.70
流线-几何 5.03 5.27 4.87 … 4.50 4.97 4.30
轻巧-沉稳 5.43 3.53 4.90 … 4.77 4.53 3.60
保守-现代 3.97 4.77 4.10 … 4.80 3.30 3.77
灵动-机械 5.20 4.17 5.17 … 4.10 5.60 5.63
模块-整体 4.67 3.73 3.93 … 5.03 3.97 3.37
危险-安全 4.63 4.20 4.37 … 5.33 4.77 3.37
繁琐-简约 3.57 4.93 3.50 … 5.13 4.13 3.83
粗糙-精密 4.00 4.40 4.00 … 5.00 3.50 3.40

Tab.2

Classification of modeling feature categories and response matrix of representative samples"

项目 类目 样本编码
1 2 3 … 22 23 24
车头前
盖(A)		 近似梯形(A1) 0 0 0 … 0 0 0
斜面切角(A2) 0 1 1 … 0 0 0
弧面切角(A3) 1 0 0 … 1 0 0
弧面+斜切角(A4) 0 0 0 … 0 1 1
车头外侧
罩壳(B)		 近似矩形(B1) 0 0 1 … 0 0 0
矩形切角(B2) 1 0 0 … 1 0 0
阶梯式(B3) 0 0 0 … 0 1 1
无罩壳(B4) 0 1 0 … 0 0 0
通风口
(C)		 条形(C1) 1 0 1 … 0 0 0
方形阵列(C2) 0 0 0 … 0 1 0
双列条形(C3) 0 0 0 … 1 0 0
特殊造型(C4) 0 1 0 … 0 0 0
操作
面板(D)		 单管支架式(D1) 0 0 1 … 0 1 1
嵌入式(D2) 1 1 0 … 1 0 0
脚踏(E) 盒式脚踏(E1) 0 1 0 … 1 0 0
层板式脚踏(E2) 1 0 1 … 0 1 1
下墙面造
型(F)		 箱体(F1) 1 0 0 … 1 0 0
箱体+格栅(F2) 0 0 0 … 0 1 0
箱体半开放(F3) 0 1 1 … 0 0 1
管架开放式(F4) 0 0 0 … 0 0 0

Tab.3

Statistical table of multi-correlation coefficient and determination coefficient"

序号 感性意象词对 复相关系数 决定系数
1 突兀-协调 0.797 0.635
2 冰冷-亲和 0.741 0.549
3 保守-现代 0.806 0.650
4 灵动-机械 0.850 0.722
5 模块-整体 0.846 0.716
6 危险-安全 0.831 0.691
7 繁琐-简约 0.977 0.954
8 粗糙-精密 0.781 0.609

Tab.4

Statistical table of partial correlation coefficient and standard coefficient"

设计项目 偏相关系数 要素类目 标准系数
车头前盖(A) 0.877 近似梯形(A1) 0.370
斜面切角(A2) 0.554
弧面切角(A3) -0.694
弧面+斜切角(A4) -0.221
车头外侧罩壳(B) 0.959 近似矩形(B1) -1.253
矩形切角(B2) 0.028
阶梯式(B3) 1.155
无罩壳(B4) 0.158
通风口(C) 0.930 条形(C1) 0.352
方形阵列(C2) -1.077
双列条形(C3) 0.546
特殊造型(C4) -0.634
操作面板(D) 0.420 单管支架式(D1) 0.064
嵌入式(D2) -0.156
脚踏(E) 0.917 盒式脚踏(E1) 1.016
层板式脚踏(E2) -0.339
下墙面造型(F) 0.889 箱体(F1) 0.145
箱体+格栅(F2) 0.539
箱体半开放(F3) -0.243
管架开放式(F4) 0.127
复相关系数R 0.966
决定系数R2 0.934
常数项 4.232

Fig.4

Evaluation samples of drawing frame schemes. (a) Programme 1; (b) Programme 2; (c) Sample 6; (d) Sample 13; (e) Sample 16"

Tab.5

Users' Kensei image evaluation"

评价样本编号 方案1 方案2 样本6 样本13 样本16
评价均值 4.93 4.00 3.20 4.87 4.20
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