THE USE OF ARTIFICIAL NEURAL NETWORKS TO ESTIMATE THERMAL RESISTANCE OF KNITTED FABRICS

Yıl 2015, Cilt: 25 Sayı: 4, 304 - 312, 01.12.2015

Asif Elahi Mangat Vladimir Bajzik Lubos Hes Funda Büyük Mazari

Öz

This study aims to develop a model for the prediction of thermal resistance of fleece fabric by using regression analysis and artificial neural network technique. Primarily fleece fabrics protect human body from heat loss during cold weather. Its second purpose is to absorb sweat from human skin. Fleece fabric is commonly used to make sweatshirts, trousers, and jackets for cold weather. Higher thermal resistance of fleece is one of the main demands of users. Many factors can influence the thermal resistance efficiency of fleece. We have used porosity, thickness of fabric, thermal conductivity of fabric, overall moisture management capacity, thermal absorptivity, percentage of cotton, and polyester and planner weight as independent variables for the prediction of thermal resistance of fleece fabric. We have found that there was a significant difference between regression and artificial neural network analysis in the selection of most significant factor. Nevertheless, both models are significant. Moreover, we have also found that there is a significant correlation between two most significant variables selected during regression analysis and artificial neural network. Keeping all these in view, we can say that both models are capable of finding the thermal resistance of fabric despite the fact that artificial neural network techniques give better explanations

Anahtar Kelimeler

Regression Analysis, Artificial Neural Network, Fleece Fabrics, Thermal Resistance

ÖRME FUTTER KUMAŞLARIN ISIL DAYANIMININ TAHMİNİ İÇİN YAPAY SİNİR AĞLARININ KULLANIMI

Öz

Kaynakça

• 1. Hes, L., Thermal properties of nonwovens. Congress Index 87Genf, 1987.
• 2. Garimella, S.V., Prediction of Thermal Contact Resistance. Electronic Cooling Magazine 2003(Novemeber ).
• 3. Bhattacharjee, D., and Kothari, V.K. , Measurement of Thermal Resistance of Woven Fabrics in Natural and Forced Convections. RJTA, 2008. 12(2): p. 39- 49.
• 4. Morris, G.J., Thermal Properties of Textile Materials. J. Text. Inst, 1953. 44: p. T449-T476.
• 5. Qian, X. and J. Fan, Prediction of Clothing Thermal Insulation and Moisture Vapour Resistance of the Clothed Body Walking in Wind. Ann. Occup. Hyg., 2006. 50,(8): p. 833-842.
• 6. Bhattacharjee, D., Ray, A., Kothari, V.K., , Air and water permeability characteristics of nonwoven fabrics (Abstract). Indian Journal of Fibre and Textile Research, 2004. 29: p. 122-128.
• 7. Fayala, F., Alibi, H., Benltoufa, S., Jemni, A. , Neural Network for Predicting Thermal Conductivity of Knit Materials. J. Engineered Fibres and Fabrics, 2008. 3: p. 53-60.
• 8. Luo, X., Hou, W., Li, Y., Wang,Z. , A Fuzzy Neural Network Model for Predicting Clothing Thermal Comfort, . Int. J. Computation and Mathematics with Applications, 2007. 53: p. 1840-1846.
• 9. Ullmann’s Fibers, ed. Fibers, 1. Survey. Vol. 1. 2008, Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
• 10. Sarle, W.S. Neural Networks and Statistical Models. in Nineteenth Annual SAS Users Group International Conference. 1994. SAS Institute Inc., Cary, NC, USA. 11. Orr,G.,NeuralNetworks,1999, http://www.ics.uci.edu/~mlearn/MLRepository.html.
• 12. Babu, V.J., et al, AC Conductivity Studies on PMMA-PANI (HCl) Nanocomposite Fibers Produced by Electrospinning. Journal of Engineered Fibers and Fabrics, 2011. 6(4): p. 54-59.
• 13. Mazari, A., Bal, K. and Havelka A., Prediction of needle heating in an industrial sewing machine. Textile Research Journal, DOI:10.1177/0040517515586160, 2015.
• 14. Mangat, M.M., Hussain, T., and Bajzik, V., Impact of Different Weft Materials and Washing Treatments on Moisture Management Characteristics of Denim. Journal of Engineered Fibers and Fabrics, 2012. 7(1): p. 38-49.
• 15. Mokhtari, F., et al, Compressibility Behaviour of Warp Knitted Spacer Fabrics Based on Elastic Curved Bar Theory. Journal of Engineered Fibers and Fabrics, 2011. 6(4): p. 23-33.
• 16. Mazari A., Havelka A. and Hes L. Experimental techniques for measuring sewing needle temperature, Tekstil ve Konfesiyon, 2014.1: p. 111-118.
• 17. Hes, L., Thermal comfort properties of textile fabrics in wet state, in Proc. Izmir Internat. Textile and Apparel Symposium2007: Cesme (Turkey).
• 18. Hes, L., Araujo, M. D., and Djulay, V. V. , Effect of Mutual Bonding of Textile Layers on Thermal Insulation and Thermal Contact Properties of Fabric Assemblies. Textile Research Journal, 1996. 66( 4): p. 245-250.
• 19. Hes, L., and Stanek, J. Theoretical and Experimental Analysis of Heat Conductivity for Nonwoven Fabrics, . in INDA-TEC Transactions, Philadelphia. 1989.
• 20. Hes, L., and Dolezal, I, New Method and Equipment for Measuring Thermal Properties of Textiles J. Textile Mach. Soc. Jpn, 1989(71): p. 806-812,.
• 21. Hes, L., Offermann, P., and Dvorakova, I. . The effect of underwear on thermal contact feeling caused by dressing up and wearing of garments. in Autex Conference,. 2001.
• 22. Yaman, N., M Şenol, F., Gurkan, P., Applying Artificial Neural Networks to Total Hand Evaluation of Disposable Diapers. Journal of Engineered Fibers and Fabrics, 2011. 6(1): p. 38-43.