Journal of Textile Research ›› 2022, Vol. 43 ›› Issue (07): 155-161.doi: 10.13475/j.fzxb.20210704507

• Apparel Engineering • Previous Articles     Next Articles

Study on sensory evaluation of performance of washed wool sweaters based on ridge regression method

ZHAO Xin1,2, WANG Caixia3, ZHOU Xiaopi3, DING Xuemei1,2()   

  1. 1. College of Fashion and Design, Donghua University, Shanghai 200051, China
    2. Key Laboratory of Clothing Design and Technology, Ministry of Education, Donghua University, Shanghai 200051, China
    3. Panasonic Appliance (China) Co., Ltd., Hangzhou, Zhejiang 310018, China
  • Received:2021-07-15 Revised:2022-04-04 Online:2022-07-15 Published:2022-07-29
  • Contact: DING Xuemei E-mail:fddingxm@dhu.edu.cn

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Abstract:

For clothing products, there is usually a collinearity relationship between different sensory properties evaluation. In order to obtain the relationship, 17 wool sweaters were used as the experimental objects, by using on-the-spot questionnaire survey, 9 specific sensory evaluations from 30 women assessors were obtained, which were then analyzed using the ridge regression method, so as to achieve the quantitative relationships among the overall impression and different sensory property evaluations of clothing. The weights of different sensory properties on the overall impression are sorted as flatness, elasticity, bulkiness, size proportion effect, neckline shape, hem shape, fuzz and pilling, damage, armhole joint shape. In addition, the accuracy of regression fitting between the predicted value from ridge regression equation and the actual surveyed value reaches 0.977. It does not only predict the consumers' sensory evaluation of product, but also help the enterprises to accurately focus on the consumers about products. In conclusion, ridge regression is proved to be a good method to study the quantitative relationship of sensory property evaluation with collinear relationship, and it can be widely used in kansei engineering of a variety of garments.

Key words: ridge regression method, wool sweater, washed appearance, overall impression, sensory evaluation, kansei engineering

CLC Number: 

  • TS941.12

Tab.1

Parameters of wool sweater"

成分 纱线线
密度/tex		 纱线
类型		 组织
结构		 面密度/
(g·m-2)		 厚度/
mm
羊毛 38.462 粗纺 纬平针 300 2.115

Fig.1

Photography of unwashed wool sweater with a score of 5. (a) Front; (b) Back"

Fig.2

Picture of washed wool sweaters"

Tab.2

Kendall's W test statistics"

样本量 协同系数 卡方 df 检验概率P值
30 0.6 230.317 12 0.000

Tab.3

Statistical value of sensory evaluation of wool sweaters"

编号 X1 X2 X3 X4 X5 X6 X7 X8 X9 Y
A-1 4.0 4.1 3.8 3.8 4.1 4.1 3.9 4.0 4.1 4.1
A-3 4.1 4.2 4.1 4.0 4.0 4.2 4.1 4.0 4.0 4.0
A-5 4.2 4.2 4.2 4.1 4.3 4.2 4.3 4.1 4.0 4.3
A-10 4.1 4.3 4.0 3.9 4.1 4.2 4.0 3.9 3.8 4.1
B-1 3.2 3.6 3.3 3.3 3.3 3.3 3.4 3.5 3.5 3.4
B-3 3.3 3.5 3.3 3.1 3.2 3.4 3.4 3.3 3.2 3.3
B-5 2.7 3.1 2.8 3.1 2.6 3.1 3.0 2.8 2.7 2.7
B-10 2.0 2.4 2.2 2.1 2.9 3.0 2.8 1.9 1.8 2.1
C-1 3.5 3.9 3.4 3.5 3.3 3.5 3.4 3.5 3.3 3.5
C-3 3.4 3.6 3.3 3.3 3.1 3.3 3.2 3.4 3.3 3.2
C-5 2.9 3.6 3.0 3.0 2.9 3.2 3.1 3.1 3.2 3.0
C-10 3.1 3.6 3.3 3.1 3.3 3.2 3.1 3.2 3.1 3.2
D-1 1.3 2.1 1.7 1.6 2.0 1.9 1.9 1.7 1.4 1.5

Tab.4

Fitting accuracy of linear regression using least square method"

R R2 调整后R2 标准估计的误差
1.000 0.999 0.997 0.042 29

Tab.5

Model of linear regression using least square method"

模型
参数		 非标准化 标准化 共线性统计量
系数 标准误差 系数 允差 膨胀因子VIF
(常量) -0.11 0.24
X1 0.82 0.29 0.91 0.00 424.30
X2 0.58 0.22 0.48 0.01 136.85
X3 -0.94 0.40 -0.84 0.00 525.54
X4 0.19 0.09 0.18 0.03 30.56
X5 0.73 0.17 0.61 0.01 79.87
X6 -0.44 0.30 -0.36 0.00 247.35
X7 0.35 0.35 0.27 0.00 292.16
X8 -1.28 0.75 -1.23 0.00 2 141.73
X9 0.97 0.46 1.02 0.00 959.66

Fig.3

Ridge trace map"

Tab.6

Fitting accuracy of ridge regression"

RMult R2 R A r j 2 标准差(SE)
0.997 0.994 0.977 0.118

Tab.7

Model of ridge regression"

模型参数 非标准化 标准化
系数 标准误差 系数
X1 0.109 0.020 0.120
X2 0.144 0.036 0.120
X3 0.118 0.022 0.105
X4 0.058 0.045 0.053
X5 0.178 0.044 0.150
X6 0.129 0.043 0.105
X7 0.129 0.030 0.098
X8 0.131 0.025 0.126
X9 0.119 0.028 0.126
常数 -0.434 0.176 0.000

Fig.4

Comparison between survey value and ridge regression predicted value of overall evaluation of wool sweaters"

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