Journal of Textile Research ›› 2022, Vol. 43 ›› Issue (12): 75-81.doi: 10.13475/j.fzxb.20210607107

• Textile Engineering • Previous Articles     Next Articles

Prediction of pore dimension in composite nonwovens based on image simulation and support vector machine

JIN Guanxiu1(), ZHU Chengyan2   

  1. 1. Zhejiang Industry Polytechnic College, Shaoxing, Zhejiang 312000, China
    2. College of Textile Science and Engineering (International Silk Institute), Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
  • Received:2021-06-24 Revised:2022-09-04 Online:2022-12-15 Published:2023-01-06

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Abstract:

In order to study the influence of nonwoven compounding on pore dimension in composite nonwovens between before and after compounded, the nonwoven webs was modeled based on the use of digital images taking into considerations of fiber number, the average fiber diameter and the variation coefficient of fiber diameter served as the model variables. Thus the image model of composite nonwoven was then obtained by superimposing two compound elements. The pore size percentage difference (Er) and the average pore size variation coefficient (Mv) of two compound elements were used to characterize the pore dimension of nonwoven before compounded. Furthermore, the pore size composite index (IP) and pore size variation coefficient composite index (IV) were used to characterize the pore dimension after compounding. The test results show that there is a complex non-linear relationship on pore dimension between before and after compounding. Er and Mv were used as the inputs of support vector machine model to predict IP and IV, respectively. The results indicate that the mean absolute percentage errors of the above two predictions are only 1.84% and 1.92%, respectively. The verification experiment result further confirms the high prediction accuracy of the support vector machine model.

Key words: composite nonwoven, pore size, pore size variation coefficient, digital image simulation, support vector machine

CLC Number: 

  • TS171

Tab.1

Modeling Scheme for compound element"

复合单元编号 n d/μm Vd/%
A 24 10 10
B 24 10 30
C 24 20 10
D 24 20 30
E 36 10 10
F 36 10 30
G 36 20 10
H 36 20 30

Fig.1

Simulating result of compound element using digital image processing technology"

Tab.2

Measuring results of pore size and its variation coefficient for all compound elements"

复合单元编号 孔径/μm 孔径变异系数/%
A 32.9 85.39
B 28.2 45.31
C 34.9 96.53
D 31.7 52.30
E 22.0 74.56
F 24.5 39.75
G 21.6 78.66
H 21.3 49.04

Tab.3

Composite scheme of superimposing two compound elements"

复合图
像编号		 复合
单元1		 复合
单元2		 复合图
像编号		 复合
单元1		 复合
单元2
1# A B 15# C E
2# A C 16# C F
3# A D 17# C G
4# A E 18# C H
5# A F 19# D E
6# A G 20# D F
7# A H 21# D G
8# B C 22# D H
9# B D 23# E F
10# B E 24# E G
11# B F 25# E H
12# B G 26# F G
13# B H 27# F H
14# C D 28# G H

Fig.2

Simulation on superimposing two compound elements"

Tab.4

Measuring results of pore size and its variation coefficient for all composite images"

复合图
像编号		 孔径/
μm		 孔径变异
系数/%		 复合图
像编号		 孔径/
μm		 孔径变异
系数/%
1# 12.9 140.65 15# 11.1 144.10
2# 12.7 196.72 16# 12.9 135.21
3# 13.1 163.23 17# 11.2 143.58
4# 10.2 132.76 18# 13.5 112.80
5# 14.2 116.82 19# 13.2 91.02
6# 10.1 131.49 20# 15.8 46.09
7# 13.0 97.57 21# 12.7 100.23
8# 12.5 166.76 22# 14.4 41.56
9# 15.3 67.15 23# 10.9 109.64
10# 12.2 94.80 24# 8.6 158.53
11# 15.5 50.27 25# 9.6 133.69
12# 12.1 101.79 26# 10.4 113.51
13# 13.8 42.75 27# 12.8 55.69
14# 12.8 187.31 28# 9.3 147.38

Tab.5

Pore dimension of images before and after compounded"

复合图像编号 Er/% MV/% IP IV 复合图像编号 Er/% MV/% IP IV
1# 16.67 65.35 0.457 4 1.647 1 15# 58.64 85.55 0.504 5 1.492 8
2# 6.08 90.96 0.386 0 2.037 9 16# 42.45 68.14 0.526 5 1.400 7
3# 3.79 68.85 0.413 2 1.911 6 17# 61.57 87.60 0.518 5 1.487 4
4# 49.55 79.98 0.463 6 1.554 7 18# 63.85 72.79 0.633 8 1.168 5
5# 34.29 62.57 0.579 6 1.368 1 19# 44.09 63.43 0.600 0 1.220 8
6# 52.31 82.03 0.467 6 1.539 9 20# 29.39 46.03 0.644 9 0.881 3
7# 54.46 67.22 0.610 3 1.142 6 21# 46.76 65.48 0.588 0 1.274 2
8# 23.76 70.92 0.443 3 1.727 5 22# 48.83 50.67 0.676 1 0.884 6
9# 12.41 48.81 0.542 6 1.283 9 23# 11.36 57.16 0.495 5 1.470 5
10# 28.18 59.94 0.554 5 1.271 5 24# 1.85 76.61 0.398 1 2.015 4
11# 15.10 42.53 0.632 7 1.109 5 25# 3.29 61.80 0.450 7 1.793 1
12# 30.56 61.99 0.560 2 1.294 1 26# 13.43 59.21 0.481 5 1.443 0
13# 32.39 47.18 0.647 9 0.871 7 27# 15.02 44.40 0.600 9 1.135 6
14# 10.09 74.42 0.403 8 1.940 4 28# 1.41 63.85 0.436 6 1.873 6

Tab.6

Optimized parameters and prediction accuracy of SVM model"

预测参数 优化后的结构参数 U/%
W FP ε
IP 67 2 600 0.001 1.84
IV 69 2 800 0.002 1.92

Tab.7

Composite scheme of nonwoven samples"

试样编号 复(叠)合单元
T1 S1+M1
T2 S1+M2
T3 S2+M1
T4 S2+M2

Tab.8

Test results of pore size and its variation coefficient for composite nonwovens before and after compound (superimposed)"

试样编号 孔径/
μm		 孔径变异系数/
%
复(叠)合前 S1 26.5 105.83
S2 30.9 76.40
M1 19.8 16.32
M2 14.1 25.81
复(叠)合后 T1 10.3 173.84
T2 9.7 160.12
T3 14.2 69.17
T4 12.3 66.10

Tab.9

Pore dimension of nonwovens before and after compounded (superimposed)"

试样编号 ErT/% MVT/% IPT IVT
T1 12.39 63.60 0.472 5 1.642 6
T2 33.88 67.82 0.530 1 1.513 0
T3 33.49 48.89 0.651 4 0.905 4
T4 59.02 53.11 0.672 1 0.865 2

Tab.10

Results of verification experiment%"

试样编号 孔径复合指数 孔径变异系数复合指数
T1 3.72 0.39
T2 3.73 1.51
T3 0.85 0.49
T4 1.83 4.67
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