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Detection of Remote Sensing Warp Tension during Weaving on Plain Twill and Satin Fabrics

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Treść / Zawartość
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Warianty tytułu
PL
Wykrywanie naprężenia osnowy za pomocą teledetekcji podczas wytwarzania tkanin o splotach skośnym i satynowym
Języki publikacji
EN
Abstrakty
EN
Warp tensions were measured while a machine was operating on a woven cotton fabric with three different woven patterns. This study was carried out with image analysis methods using a high speed camera. Three weave pattern types: plain, twill and satin were woven on the same weaving machine, and thus it could be understood how weave pattern differences affect warp tension. Each of these three weaves was woven in three weft densities: 20, 28 and 45 wefts per cm. These fabrics were able to be made on a weaving machine with an automatic dobby. It was aimed to investigate warp tension differences for three basic weave patterns while keeping all machine settings constant. The weave settings of the dobby were changed for plain, twill and satin weaves. Warp tension calculation was based on the warp elasticity theory. Warp elasticises were measured by image processing methods in MATLAB using a high-speed camera. It was aimed to improve upon the new method of warp extension measurement of fabric when the loom is in operation. It was observed that the warp tension in plain fabric was higher than for twill and satin under the same conditions.
PL
W pracy mierzono naprężenia osnowy podczas wytwarzania tkanin bawełnianych o trzech różnych wzorach. Badanie zostało przeprowadzone metodami analizy obrazu przy użyciu kamery. Na tej samej maszynie tkano trzy rodzaje wzorów splotu: gładki, diagonalny i satynowy, dzięki czemu zbadano wpływ rodzaju splotu na napięcie osnowy. Każdy z tych trzech splotów został utkany w trzech gęstościach wątku: 20, 28 i 45 wątków/cm. Celem pracy było zbadanie różnic naprężeń osnowy dla trzech podstawowych wzorów splotów, przy jednoczesnym zachowaniu stałych ustawień maszyny. Obliczenia naprężenia osnowy oparto na teorii sprężystości osnowy. Elastyczność osnowy mierzono metodami przetwarzania obrazu w programie MATLAB przy użyciu kamery. Celem badania było ulepszenie nowej metody pomiaru wydłużenia osnowy tkaniny podczas pracy krosna. Zaobserwowano, że naprężenie osnowy w tkaninie gładkiej było wyższe niż w przypadku diagonalu i satyny w tych samych warunkach.
Rocznik
Strony
35--39
Opis fizyczny
Bibliogr. 23 poz., rys., tab.
Twórcy
  • Pamukkale University, Faculty of Engineering, Department of Textile Engineering, Kinikli Campus, Denizli, Turkey
Bibliografia
  • 1. Ngan HYT, Pang GKH, Yung NHC. Motif-Based Defect Detection Forpat- Terned Fabric, 2008; 41(6): 1878-1894.
  • 2. Chan CH, Liu H, Kwan T, Pang G. Automation technology for fabric inspection system, Proceedings of Conference on Applications of Automation Science and Technology, City University of Hong Kong, November 1998, pp. 24-26.
  • 3. Chan CH, Pang GKH. Fabric Defect Detection by Fourier Analysis. IEEE Transactions on Industry Applications 2000; 36(5): 1743-1750.
  • 4. Bovik AC, Clark M. Multichannel Texture Analysis Using Localized Spatial Filters. IEEE Transactions on Pattern Analysis and Machine Intelligence 1990; 12(1): 55-73.
  • 5. Ping Zhong, Tao Ye, Yunlong Shi and Xinxing Tu. Research on Computer-Aided Analysis and Reverse Reconstruction for the Weave Pattern of Fabric. Textile Research Journal 2013; 83(3): 298-310.
  • 6. Kuo CFJ, Lee CJ, Tsai CC. Using a Neural Network to Identify Fabric Defects in Dynamic Cloth Inspection. Textile Research Journal 2003; 73, 3: 238 244, ISSN 0040-5175.
  • 7. Zhi YX, Pang GKH, Yung HCN. Fabric Defect Detection Using Adaptive Wavelet. IEEE International Conference on Acoustics, Speech, and Signal Processing 2001; 3697-3700.
  • 8. Zhi YX, Pang GKH, Yung HCN. Fabric Defect Detection Using Adaptive Wavelet. IEEE International Conference on Acoustics, Speech, and Signal Processing; 2001, 3697-3700.
  • 9. Unser M. Texture Classification and Segmentation Using Wavelet Frames. IEEE Transactions on Image Processing 1995; 4(11): 1549-1560.
  • 10. Todd Jackson A, Bell CA. Megapixel Resolution Portable CCD Electronic Still Camera. Proceedings of SPIE-The International Society for Optical Engineering 1991; 1448: 2-12.
  • 11. Yılmaz A. Kamera kullanılarak görüntü işleme yoluyla gerçek zamanlı güvenlik uygulaması, Yüksek Lisans Tezi, Haliç Üniversitesi Fen Bilimleri Enstitüsü Makine Mühendisliği Anabilim Dalı, 102, İstanbul, 2007.
  • 12. Ludwig HW, Gries T. Measurements Carried Out to Minimise Warp Tension Variations in Weaving Machines. Melliand Textilberichte. 2003; June 02: 55-58.
  • 13. Weinsdorfer H, Azarschab M, Murrweib H, Wolfrum J. Effect of the Selvedge and the Temples on the Running Performance of Weaving Machines and on the Quality of the Fabric. Melliand Textilberichte 1988; 35: 364-372.
  • 14. Bodnarova A, Bennamoun M, Latham S. Optimal Gabor Filters for Textile Flaw Detection. Pattern Recognition; 2002; 35, 2973-2991.
  • 15. Mak KL, Peng P, Lau HYK. Optimal Morphological Filter Design for Fabric Defect Detection. IEEE International Conference on Industrial Technology, Hong Kong, China, 2005; 799-804.
  • 16. Mak KL, Peng P, Lau HYK. A Real-Time Computer Vision System for Detecting Defects in Textile Fabrics. IEEE International Conference on Industrial Technology, Hong Kong, China, 2005; 469-474.
  • 17. Kaplan V, Dayık M. Detection Of Warp Elongation Using Image Processing In Plain Fabric, 15th International Materyal Sympossium in Denizli, 2014.
  • 18. Süle G. Influence of Warp Tension on Breaking Strength and Strain of Woven Fabrics. Textile and Apparel 2010; December – March.
  • 19. Türker E. Determination of Structural Parameters of Single-Colored Woven Fabrics by Using Image Processing Method. Textile and Apparel 2014; October – November.
  • 20. Milasius R, Rukuiziene Z. Inequality of Woven Fabric Elongation in Width and Change of Warp Inequality under Axial and Bi-axial Tensions. FIBRES &TEXTILES in Eastern Europe 2006; 14, 1(55): 36-38.
  • 21. Milasius R, Rukuiziene Z. Influence of Reed on Fabric Inequality in Width. FIBRESS & TEXTILES in Eastern Europe 2006; 14, 4(58): 44-47.
  • 22. Kaplan V. Dokuma Sırasında Çözgü Gerginliğinin Görüntü İşleme Yöntemiyle Belirlenmesi. Doktora Tezi, Süleyman Demirel Üniversitesi Fenbilimleri Enstitüsü Tekstil Mühendisliği Bölümü, 2014 Isparta.
  • 23. Kaplan V, Yildiz N, Dayik M, Turhan Y, Durur G. Detection of Warp Elongation in Satin Woven Cotton Fabrics Using Image Processing. FIBRES & TEXTILES in Eastern Europe 2016; 24, 4(118): 59-62. DOI: 10.5604/12303666.1183202.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-247c2daa-9719-4b5c-b02f-892a38e75621
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