Journal of Textile Research ›› 2019, Vol. 40 ›› Issue (07): 169-173.doi: 10.13475/j.fzxb.20180602805

• Management & Information • Previous Articles     Next Articles

Wet-steaming dyeing prediction model of cotton knitted fabric with reactive dye based on least squares support vector machine

TAO Kaixin, YU Chengbing(), HOU Qi'ao, WU Congjie, LIU Yinfeng   

  1. College of Materials Science and Engineering, Shanghai University, Shanghai 200444, China
  • Received:2018-06-06 Revised:2019-03-25 Online:2019-07-15 Published:2019-07-25
  • Contact: YU Chengbing E-mail:ycb101@shu.edu.cn

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Abstract: Aim

ing at the problem of hard control and prediction of dyeing conditions on the color of dyed fabrics in the continuous wet-steaming dyeing of cotton knitted fabrics with reactive dye, the influences of sodium sulfate concentration, soda concentration, and steaming time on the color depth (K/S value) of the dyed fabrics were studied in the wet-steaming dyeing process of cotton knitted fabrics with Remazol golden yellow RGB. At the same time, based on least squares support vector machine (LS-SVM), using these factors as the input variables of the prediction model and the K/S value of fabric color depth as the output variable, a multi-factor model of K/S value was established to predict K/S value. The experiment results show that the correlation coefficient between the experimental value and the predicted value of the model is 0.999 6, and the mean relative error is lower than 1%, which indicates that the model has high accuracy. The modeling method can be applied to predict the K/S value of fabric, providing a basis reference for the optimization of the wet-steaming reactive dyeing process conditions for cotton knitted fabric.

Key words: wet-steaming dyeing, reactive dye, least squares support vector machine, multi-factor model, cotton knitted fabric

CLC Number: 

  • TP181

Tab.1

Experimental values and regression values of K/S for 40 groups of stained samples"

实验
号		 实验方案 K/S值 相对
误差/%		 支持
向量
α
X1 X2 X3 实验值 回归值
1 21.43 7.52 90 7.04 7.20 2.27 -219.14
2 42.86 7.52 90 9.05 8.72 3.65 448.78
3 64.29 7.52 90 10.43 10.39 0.38 49.94
4 85.71 7.52 90 11.61 12.16 4.74 -758.76
5 100.00 7.52 90 13.67 13.37 2.19 410.48
6 107.14 7.52 120 14.64 14.73 0.61 -128.82
7 125.00 7.52 120 16.93 16.57 2.13 491.39
8 150.00 7.52 120 18.57 18.91 1.83 -461.32
9 175.00 7.52 120 21.02 20.85 0.81 234.97
10 125.00 3.76 150 13.78 13.89 0.80 -157.38
11 125.00 9.40 150 17.96 17.47 2.73 677.28
12 125.00 15.04 150 16.92 16.82 0.59 142.89
13 125.00 20.68 150 17.29 17.28 0.06 17.35
14 125.00 26.32 150 18.56 18.56 0.00 -5.47
15 75.00 15.04 90 12.97 13.02 0.39 -61.72
16 75.00 15.04 120 12.40 12.31 0.73 125.05
17 75.00 15.04 150 14.19 14.24 0.35 -65.37
18 75.00 15.04 180 13.95 13.79 1.15 225.42
19 75.00 15.04 210 14.31 14.70 2.73 -535.14
20 75.00 15.04 240 15.62 15.61 0.06 18.85
21 150.00 3.76 180 19.62 19.57 0.25 66.16
22 150.00 9.40 180 19.24 19.17 0.36 90.16
23 150.00 15.04 180 19.58 19.46 0.61 160.72
24 150.00 20.68 180 19.73 19.86 0.66 -176.02
25 150.00 26.32 180 20.03 19.99 0.20 60.81
26 125.00 7.52 210 15.58 15.50 0.51 111.94
27 125.00 15.04 210 20.16 19.45 3.52 970.54
28 175.00 7.52 210 15.21 15.28 0.46 -102.52
29 175.00 15.04 210 18.37 18.70 1.80 -453.11
30 100.00 11.28 90 14.70 14.61 0.61 129.45
31 100.00 11.28 120 13.29 13.46 1.28 -239.28
32 100.00 11.28 150 15.45 15.43 0.13 20.94
33 100.00 11.28 180 13.57 13.86 2.14 -397.39
34 100.00 11.28 210 15.19 15.21 0.13 -21.57
35 100.00 11.28 240 14.50 14.51 0.07 -13.20
36 50.00 11.28 150 10.39 10.21 1.73 242.15
37 75.00 11.28 150 12.64 12.97 2.61 -450.50
38 125.00 11.28 150 16.80 17.42 3.69 -846.23
39 150.00 11.28 150 19.63 18.76 4.43 1187.46
40 175.00 11.28 150 18.80 19.38 3.09 -789.78

Tab.2

Comparison of model fitting regression performance"

(γ,σ2) 均方
误差		 均方根
误差		 R值 P值 平均相对
误差/%
A 0.069 4 0.263 4 0.996 8 <0.000 1 1.17
B 0.091 7 0.302 8 0.995 8 <0.000 1 1.41
C 0.001 1 0.033 2 0.999 9 <0.000 1 0.20
D 0.002 1 0.045 8 0.999 9 <0.000 1 0.28
E 0.006 8 0.082 5 0.999 9 <0.000 1 0.49

Tab.3

Comparison of model prediction performance"

实验
号		 实验方案 K/S值 相对
误差/
%		 (γ,σ2)
X1 X2 X3 实验值 预测值
1 35.71 6.77 108 7.91 8.033 1.55 A
2 78.57 9.02 140 12.83 12.655 1.36
3 92.86 15.79 170 14.94 14.810 0.87
4 128.57 13.54 205 17.10 17.212 0.65
5 157.14 22.56 82 19.41 19.695 1.47
1 35.71 6.77 108 7.91 8.014 1.31 B
2 78.57 9.02 140 12.83 12.674 1.22
3 92.86 15.79 170 14.94 14.900 0.27
4 128.57 13.54 205 17.10 17.178 0.46
5 157.14 22.56 82 19.41 19.597 0.96
1 35.71 6.77 108 7.91 15.183 91.95 C
2 78.57 9.02 140 12.83 15.183 18.34
3 92.86 15.79 170 14.94 15.183 1.63
4 128.57 13.54 205 17.10 15.197 11.13
5 157.14 22.56 82 19.41 15.183 21.78
1 35.71 6.77 108 7.91 15.068 90.49 D
2 78.57 9.02 140 12.83 15.068 17.44
3 92.86 15.79 170 14.94 15.068 0.86
4 128.57 13.54 205 17.10 15.175 11.26
5 157.14 22.56 82 19.41 15.068 22.37
1 35.71 6.77 108 7.91 15.215 92.35 E
2 78.57 9.02 140 12.83 15.215 18.59
3 92.86 15.79 170 14.94 15.215 1.84
4 128.57 13.54 205 17.10 15.265 10.73
5 157.14 22.56 82 19.41 15.215 21.61

Tab.4

Comparison of experimental K/S values and predicted K/S values"

实验
号		 实验方案 K/S值 相对
误差/%
X1 X2 X3 实验值 预测值
1 60.71 5.26 160 11.49 11.366 1.08
2 96.43 24.44 110 14.77 15.008 1.61
3 117.86 12.03 78 14.68 14.801 0.82
4 142.86 17.30 130 18.43 18.411 0.10
5 160.71 10.15 220 15.92 15.708 1.33
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