Prediction of fabric compressive properties using artificial neural networks

• Autorzy: Gurumurthy B. R.
• Języki publikacji: EN

Abstrakty

EN

Data analysis relating to a fabric's compression properties can only be carried out when the limits of compression are known. The study of the compressibility of woven fabrics was initiated with Peirce, Kemp & Hamilton's approach to circular yarns and flattened yarns of a fabric under pressure. The fit of the pressure-thickness relationship is being improved using the exponential interpolation & extrapolation methods, as well as iterative methods such as the Marquardt algorithm for fitting the curves. Although there is a recent trend towards the automation of studying the structure-property relationship of textile fabrics, an objective and efficient method for predicting properties with a rapid prototype that outputs to sophisticated instruments such as the KES-FB3 is essential. This characterisation of data for fabric materials will help maintain companies' commercial experience and expertise. This established predicting model can provide guidance to fabric manufacturers, fashion designers and ?[makers-up] in fabric design, fabric selection and the proper use of fabrics. This approach will make online fabric sourcing more realistic. Fabric sourcing experts are now visiting supplier's websites for tracking fabrics. Overall, this approach provides an opportunity to generate a dynamic database of fabric properties, and hence may result in the development of new fabrics or the updating of existing fabrics to keep pace with fashion.

Słowa kluczowe

EN

compression energy; flattening factor; bulk density; specific volume

PL

energia kompresji; współczynnik spłaszczenia; gęstość objętościowa; objętość

• Wydawca: Lodz University of Technology, Faculty of Material Technologies and Textile Design
• Czasopismo: Autex Research Journal
• Rocznik: 2007
• Tom: Vol. 7, no. 1
• Strony: 19--31
• Opis fizyczny: Bibliogr. 13 poz.

Twórcy

autor

Gurumurthy B. R.

• Department of Textile Technology, Indian Institute of Technology, Hauz Khas, New Delhi 110 016

Bibliografia

• 1. B. Olofsson, ‘A general model of a fabric as a geometric- mechanical structure’, vol.55, No.11, Journal of the Textile Institute, Nov.1964.
• 2. B. Olofsson, ‘The setting of wool fabrics – a =tTheoretical study’- Journal of the Textile Institute, pp. 272-273.
• 3. Transactions, ’An extension of Peirce’s cloth geometry to the treatment of non-circular threads’, Journal of Textile Institute’, Pg.T44-T47.
• 4. E.H. Taibi, A. Hammouche, A. Kifani, ‘Model of the tensile stress-strain behaviour of fabrics’, Journal of the Textile Institute, pp. 582-586.
• 5. Masako Niwa, Mori lnoue, Sueo Kawabata, ’Objective evaluation of the handle of blankets’, Textile Research Journal, 71(8), pp. 701-710 (2001).
• 6. P.M. Taylor, D.M. Pollet, ‘Static low load lateral compression of fabrics’, Textile Research Journal, 72(11), pp. 983-990 (2002).
• 7. R.H. Gong, Y. Chen, ’Predicting the performance of fabrics in garment manufacturing with artificial neural networks’, Textile Research Journal, 69(7), pp. 477-482 (1999).
• 8. Dominique Dupuis, Georgi Popov, Pierre Viallier, ‘Compression of greystate fabrics as a function of yarn structure’, Textile Research Journal, 65(6), pp. 309-316 (1995).
• 9. J.Hu and A. Newton, ‘Low-load lateral compression of woven fabrics’, Journal of Textile Institute, vol.88, Part I, No.3, 1997, pp. 476-486.
• 10. H.T. Liu and L.Z. Sun, G. Wang and M.W. Vannier, ‘Analytic modelling of breast elastography’, Medical Physics, vol.30, No.9, September 2003, pp. 2340-2349.
• 11. Silva, Wilton. P and Silva, Cleide, M.D.P.S, 'Lab fit curve fitting software (Non-linear regression and treatment of data program) V 7.2.31 (1999-2005);available online at www.labfit.net
• 12. J.E. Booth, Principles of textile testing, Buttersworth, pp. 272-275.
• 13. Newton. A, ‘The comparison of woven fabrics by reference to their tightness’, Journal of Textile Institute, 1995, vol. 86, No.2, pp. 232-240.