Dynamic Measurement of Foam-Sized Yarn Properties from Yarn Sequence Images

Open access


Unlike the normal sizing method, the foam sizing had been proven to be a low-add-on technology. To investigate the effect of foam sizing, film thickness, sized-yarn evenness, and size penetration rate were necessary to evaluate the performances of foam-sized yarns. However, the conventional image analysis of sized-yarn cross sections primarily relied on artificial testing with a low efficiency. This paper proposed a novel dynamic method to measure the sized-yarn properties including film thickness, sized-yarn evenness, and size penetration rate based on yarn sequence images captured from a moving yarn. A method of dynamic threshold module was adopted to obtain threshold for segmenting yarns in the sequence images. K-means clustering algorithm was applied to segment pixels of the images into yarn and background. To further remove burrs and noise in the images, two judgment templates were carried out to extract the information of yarn core. The film thickness, sized-yarn evenness, and size penetration rate were measured based on the yarn core of each frame in sequence images. In order to compare with the experimental results of the dynamic method, the yarn properties of the same samples were tested by static and artificial testing. Results revealed that the proposed method could efficiently and accurately detect the film thickness, sized-yarn evenness, and size penetration rate.

[1] W. Perkins, R. Walker, Foam Sizing, Textil. Res. J. 9 (1982) 547-554.

[2] K. Lu, X. Zhang, Y. Zhao, Z. Wu, Removal of color from textile dyeing wastewater by foam separation, J. Hazard. Mater. 182 (2010) 928-932.

[3] H. Yu, Y. Wang, Y. Zhong, Z. Mao, S. Tan, Foam properties and application in dyeing cotton fabrics with reactive dyes, Color. Technol. 130 (2014) 266-272.

[4] J.Y. Bae, J.E. Joo, Y.J. Lee, M.S. Han, S.H. Kim, Fabrication of biodegradable polylactide foam for algal bloom control, Fiber. Polym. 3 (2002) 159-168.

[5] W.H. Lee, S.W. Lee, T.J. Kang, K. Chung, J.R. Youn, Processing of polyurethane/polystyrene hybrid foam and numerical simulation, Fiber. Polym. 21 (2015)134-146.

[6] K. Baker, G. Bryant, J. Camp, B. Kelsey, Foam Finishing Technology, Textil. Res. J. 52, (1982) 395-403.

[7] C. Namboodri, M. Duke, Foam Finishing of Cotton-Containing Textiles, Textil. Res. J. 49 (1979) 156-162.

[8] C. Namboodri, Foam Sizing of Cotton and Blend Yarns: Slashing Trials, Textil. Res. J. 2 (1986) 87-92.

[9] J. Trauter, R. Vialon, Aspects of Foam Sizing, Textiletrieb. 104 (1986) 33-41.

[10] J. Trauter, R. Vialon, State of Foam Sizing, Textil. Asia. 18 (1987) 97.

[11] S. Vernekar, Foam Sizing-Perspectives and Limitations, Manmade Textil. In. India. 35 (1992) 51-52.

[12] D. J. Shah, R. S. Gandhi, Technique of Foam Sizing, J. Ind. Text. 10 (1990) 184-185.

[13] W. Beck, Foam Technology in Yarn Sizing, Textil. Praxis. Int. 623 (1989).

[14] W.D. Gao, X.R. Fan, J.L Liu, J.X. Zhang, L. Du, Technology Study of Foam Sizing, Cot. Textil. Tech. 42 (2014) 1-5.

[15] Y. Lu, J. Zhang, J. Liu, W. Gao, Sizing effects of foamsizing and yarn pre-wetting combined process, J. Textil. Res. 12 (2014) 47-51.

[16] B.G. Xu, C.M. Murrells, X.M. Tao, Automatic measurement and recognition of yarn snarls by digital image and signal processing methods, Text. Res. J. 78 (2008) 439-456.

[17] Z.J. Li, R.R. Pan, W.D. Gao, Formation of digital yarn black board using sequence images Text. Res. J. 2016 (86) 593-603.

[18] Y. Guo, Tao X M, Xu B G, Choi K F, Hua T and Wang S Y 2010 A continuous measurement system for yarn structures by an optical method Meas. Sci. Technol. 21 115706-115720

[19] J. Feng, B.G. Xu, X.M. Tao, J. Feng, B.G. Xu, Dynamic measurement and modelling of flexible yarn dynamic behaviour on a moving cylindrical solid structure, Meas. Sci. Technol. 23 (2012) 286-286.

[20] A. Shams Nateri, F. Ebrahimi, N. Sadeghzade, Evaluation of yarn defects by image processing technique, Optik, 125 (2014) 5998-6002.

[21] A. Sengupta, S. Roy, S. Sengupta, Development of a low cost yarn parameterisation unit by image processing, Measurement 59 (2015) 96-109

[22] M. Eldessouki, S. Ibrahim, J. Militky, A dynamic and robust image processing based method for measuring the yarn diameter and its variation, Text. Res. J. 84 (2014) 1948-1960.

[23] J. Zhang, B. Xin, X. Wu, Density measurement of yarn dyed woven fabrics based on dual-side scanning and the FFT technique, Meas. Sci. Technol. 25 (2014) 1-17.

[24] J. Liu, H. Jiang, X. Liu, Z. Chai, Automatic measurement for dimensional changes of woven fabrics based on texture, Meas. Sci. Technol. 25 (2014) 015602.

[25] P. Zhong, Z. Kang, S. Han, R. Hu, J. Pang, X. Zhang, Evaluation method for yarn diameter unevenness based on image sequence processing, Text. Res. J. 85 (2015) 369-379.

[26] B. Zhu, J. Liu, R. Pan, S. Wang, W. Gao, Fabric seam detection based on wavelet transform and CIELAB color space: A comparison, Optik, 126 (2015) 5650–5655.

[27] S. Behtaj, S. Sadri, H. Tavanai, Objective yarn bulk measurement through image analysis, J. Text. Inst. 102 (2011) 1094-1100.

[28] A. Fabijańska, L. Jackowska-Strumiłło, Image processing and analysis algorithms for yarn hairiness determination, Mach. Vis. Appl. 23 (2012) 527-540.

[29] Z. Li, R. Pan, J. Zhang, B. Li, W. Gao, W. Bao. Measuring the unevenness of yarn apparent diameter from yarn sequence images, Meas. Sci. Technol. 27 (2016) 1-10.

Autex Research Journal

The Journal of Association of Universities for Textiles (AUTEX)

Journal Information

IMPACT FACTOR 2017: 0.957
5-year IMPACT FACTOR: 1.027

CiteScore 2017: 1.18

SCImago Journal Rank (SJR) 2017: 0.448
Source Normalized Impact per Paper (SNIP) 2017: 1.465


All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 202 202 19
PDF Downloads 112 112 11