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ISSN: 1023-5086

ru/

ISSN: 1023-5086

Scientific and technical

Opticheskii Zhurnal

A full-text English translation of the journal is published by Optica Publishing Group under the title “Journal of Optical Technology”

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Yarn break detection using optical method in real-time

For Russian citation (Opticheskii Zhurnal):

Qing Wang, Ran Huang, Changhou Lu, Wei Pan Yarn break detection using optical method in real-time (Определение обрыва нитей в реальном времени оптическим методом) [на англ. яз.] // Оптический журнал. 2017. Т. 84. № 5. С. 71–74.

 

Qing Wang, Ran Huang, Changhou Lu, Wei Pan Yarn break detection using optical method in real-time (Определение обрыва нитей в реальном времени оптическим методом) [in English] // Opticheskii Zhurnal. 2017. V. 84. № 5. P. 71–74.

For citation (Journal of Optical Technology):

Qing Wang, Ran Huang, Changhou Lu, and Wei Pan, "Yarn break detection using an optical method in real time," Journal of Optical Technology. 84(5), 342-345 (2017). https://doi.org/10.1364/JOT.84.000342

Abstract:

In the process of production of yarn, the breakage rate is an important index of the quality of yarn. In this paper, an optical method to detect the break of the moving yarns automatically in the weaving process is proposed. With a line laser illuminating the moving yarns, a linear CCD camera is used to capture the images. Then the original captured image is converted to a binary image, and the number of the connected component is calculated. By analyzing the connected component number, the yarn break is detected, and then the break yarn situation is obtained. Experiment works have been performed, and the results proved that the proposed method is effective.

Keywords:

optical method, yarn break, linear CCD camera, line laser, image processing

OCIS codes: 120.0120, 140.0140, 100.0100, 150.0150

References:

1. Gusarova N. Optical monitoring of yarn during its processing // Opt. Zh. 2001. V. 68. № 8. P. 88–92. [J. Opt. Technol. 2001. V. 68. P. 613–616]
2. Cherkassky A.E., Kit B.J. Computer simulation of yarn breakages in the ring spinning process. Part I: Model structure, investigation strategy, and experimental design // J. Text. Inst. 1997. V. 88. P. 29–46.
3. Sparavigna A., Broglia E., Lugli S. Beyond capacitive systems with optical measurements for yarn evenness evaluation // Mechatronics. 2004. V. 14. P. 1183–1196.
4. Millman M.P., Acar M., Jackson M.R. Computer vision for textured yarn interlace (nip) measurements at high speeds // Mechatronics. 2001. V. 11. P. 1025–1038.
5. Carvalho V.H., Belsley M.S., Vasconcelos R.M., Soares F.O. Automatic yarn characterization system: Design of a prototype // IEEE Sens. J. 2009. V. 9. P. 987–993.
6. Shlyakhtenko P.G., Nefedov V.P., Vetrova Yu.N., Rudin A.E., Sukharev P.A. A diffraction method of monitoring the angular distribution of the fibers in the structure of a flat fibrous material // Opt. Zh. 2012. V. 79. № 9. P. 96–100. [J. Opt. Technol. 2012. V. 79. P. 599–602]
7. Shlyakhtenko P.G., Kofnov O.V., Sukharev P.A. Method of determining the skewness of the weft thread in fabric // Opt. Zh. 2014. V. 81. № 2. P. 76–79. [J. Opt. Technol. 2014. V. 81. P. 111–113.]
8. Zhang J., Pan R.R., Gao W.D. Automatic inspection of density in yarn-dyed fabrics by utilizing fabric light transmittance and Fourier analysis // Appl. Opt. 2015. V. 54. P. 966–972.
9. Zhong P., Kang Z., Han S., Hu R., Pang J.Y., Zhang X.Y., Huang F.X. Evaluation method for yarn diameter unevenness based on image sequence processing // Textile Res. J. 2015. V. 85. P. 369–379.
10. Musa E. Line laser-based break sensor that detects light spots on yarns // Opt. Lasers Eng. 2009. V. 47. P. 741–746.