**13. References**

Ajayi, J.O. (1992). Fabric smoothness, Friction and handle, *Text. Res. J*. 62, 87-93


Pattern Weave m2,0 m1,1 m0,2 AN-anisotropy Twill 0.0020481 -0.0250585 0.229335 1

There exists a plenty of other roughness characteristics based on standard statistics or analysis of spatial processes which can be used for separation of noise and waviness (macro roughness). For evaluation of suitability of these characteristics it will be necessary to

For deeper analysis of SHV traces from KES device the rough signal registration and

The analysis of SHV can be more complex. The other classical roughness characteristics and topothesy can be computed as well and many other techniques of fractal dimension calculation can be included. The analysis can be extended to the chaotic models and autoregressive models. With some modifications it will be possible to use these techniques

The contact less measurement of fabric images by using of RCM device is useful for

This work was supported by the research project 1M4674788501 of Czech Ministry of

Ajayi, J.O. (1994). An attachment to the constant rate of elongation tester for estimating

Anonym, (1997). *ISO 4287: Geometrical product specification, GPS-surface texture, profile method - terms, definitions, and surface texture parameters*, Beuth Verlag, Berlin Beran, J. (1984).*Statistics for Long -Memory Processes*, Chapman and Hall, New York

Davies, S. (1999). Fractal analysis of surface roughness by using of spatial data, *J.R. Stat. Soc.*,

Eke, A. (2000). Physiological time series: distinguishing fractal noises from motions *Eur. J.* 

for characterization of the SHV or surface profiles obtained by other techniques.

Ajayi, J.O. (1992). Fabric smoothness, Friction and handle, *Text. Res. J*. 62, 87-93

surface irregularity of fabric, *Text. Res. J.*, 64, 475-476

Cox, D. R. (1984). *Statistics in Apparaisal*, Iowa State University, 55-74

description of relief in individual slices and in the whole fabric plane.

0.7671 0.0613 0.1506 0. 728

Krull, surface

Table 1. Surface moments and anisotropy of samples

digitalization by using of LABVIEW system is beneficial.

loops

compare results from sets of textile surfaces.

**11. Conclusion** 

**12. Acknowledgements** 

Education.

**13. References** 

61, 3-37

*Physiol*., 439, 403-415


Synthetic fiber industry has been enforced to make developments due to the increasing performance demand for textile products. One of the most important developments in synthetic fiber industry, is absolutely producing extremely fine fibers which are named as microfibers and nanofibers (Kaynak & Babaarslan, 2010). Until today, there is no exact definition for microfibers. But common opinion is defining a fiber finer than 1 dtex or 1 denier as microfiber (Leadbetter & Dervan, 1992; Bianchi & Maglione, 1993; Purane & Panigrahi, 2007; Basu, 2001; Mukhopadhyay, 2002; Falkai, 1991; Rupp & Yonenaga, 2000). 1 dtex polyester fiber has a fiber diameter of approximately 10 µm (Falkai, 1991). On the other hand, nanotechnology refers to the science and engineering concerning materials, structures and devices which at least one of the dimensions is 100 nanometers (0.1 µm) or less

Fabrics produced from microfilaments are superior to conventional fiber fabrics, due to their properties such as light weight, durability, waterproofness, windproofness, breathability and drapeability. Tightly woven fabrics produced from microfilament yarns have a very compact structure due to small pore dimensions between the fibers inside the yarns and between yarns themselves. These fabrics provide very good resistance against wind for different end uses such as parachutes, sails, wind-proof clothes, tents while serving light weight and high durability properties (Babaarslan & Kaynak, 2011). Wind resistance is usually assessed by measuring air permeability. This is the rate of air flow per unit area of fabric at a standard pressure difference across the faces of the fabric (Horrocks & Anand, 2004). Airflow through textiles is mainly affected by the pore characteristics of fabrics. The pore dimension and distribution in a fabric is a function of fabric geometry (Bivainyte & Mikucioniene, 2011). So, for woven fabrics, number of yarns per unit area, yarn linear density, weave type, fabric weight and fabric thickness are the main fabric parameters that affect air permeability (Fatahi & Yazdi, 2010; Çay & Tarakçoğlu, 2007; Çay & Tarakçoğlu, 2008; Turan & Okur, 2010). On the other hand, considering the yarn structure; yarn production technology, yarn diameter, yarn twist, hairiness, being staple or filament yarn, fiber fineness, fiber cross-section and yarn packing density are also important parameters (Turan & Okur, 2010). The pores of a fabric can be classified as pores between the fibers inside the yarns and between yarns themselves. The dimensions of the pores between the yarns are directly affected by the yarn density and yarn thickness. By increasing of the yarn density, the dimensions of the pores become smaller, thus the air permeability decreases.

**1. Introduction** 

(Ramakrishna, et al., 2005).

Hatice Kübra Kaynak1 and Osman Babaarslan2 *1Gaziantep University, Textile Engineering Department 2Çukurova University, Textile Engineering Department* 

*Turkey* 

Zhang, C. Gopalakrishnan, S. (1996). Fractal geometry applied to on line monitoring of surface finish *Int. J. Mach. Tools Manufact.,* 36, 1137-1150 **6** 

Hatice Kübra Kaynak1 and Osman Babaarslan2

*1Gaziantep University, Textile Engineering Department 2Çukurova University, Textile Engineering Department Turkey* 
