Gotipamul R.L.,Textile and Engineering Institute |
Dayama P.,Textile and Engineering Institute |
Mohansundram M.S.,Textile and Engineering Institute |
Mali A.,Textile and Engineering Institute |
Sharma A.,Textile and Engineering Institute
Melliand International | Year: 2011
Fabric weave is expressed by weave factor and index of interlacement. The association between these factors was found to be r = 0.85, R2 = 0.72. The effect of these parameters on tensile, tearing and ballistic strength is also investigated. The tensile behavior of woven fabrics is known to be affected by its sett and construction. Hence, this work understands the dependence of the fabric weave and behavior of woven fabrics with reference to its strength. Experiments were conducted to study the effect of interlacing yarns, and their interlacement pattern on the, tensile, tearing and ballistic strength of fabric. A significant influence of the distribution of interlacement was also observed for all the twelve weaves. This experiment work showed that of these different weaves, plain weave has recorded the highest weave factor and Index of interlacement of the order of 1 in both the cases and the figuring structure indicated the lowest, proving that the type of weave affects the strength properties of the woven fabrics. The results are analyzed with the help of analysis of variance (Anova).
Jayashree V.,Textile and Engineering Institute |
Subbaraman S.,Textile and Engineering Institute
Melliand International | Year: 2011
The fabric defects such as warp break, double pick and localized microstructure defects; namely loose weft and thick place occurring in grey shirting fabrics woven on looms such as air-jet and rapier looms are becoming crucial for quality control. This paper discusses the application of DC suppressed Fourier power spectrum (DCSFPS) obtained from Fourier transform (FT) for the analysis of fabric images in terms of significant frequency contents and the periodicity of the woven fabric in order to identify the fabric faults. The analysis was carried out on real plain weave grey fabric of 3 different yarn counts by computing as many as 20 features from the marginals of DCSFPS which were used as inputs to the Neural Network (NN) implementing Levenberg-Marquardt Back-propagation algorithm (LMBP). The results of NN optimized with 20, 40 and 3 neurons in the input, hidden and output layer respectively for identification and classification of grey fabric defects are encouraging with NN converging in less than 20 iterations and giving classification accuracy of almost 100%.
Mhetre S.B.,Textile and Engineering Institute |
Karadbhajne A.K.,Textile and Engineering Institute
Journal of the Textile Association | Year: 2012
The effect of weaves & weft counts on the thermal comfort and tactile properties of polyester viscose blended fabrics have been studied by measuring the low stress mechanical properties on Kawabata Evaluation System. The thermal comfort has been studied by measuring the air permeability, thermal insulation & moisture vapour transfer properties of fabrics. The tactile properties have been studied by measuring the fabric mechanical & surface properties such as tensile, shear, bending, compression, surface roughness, surface friction and handle. The study shows that, KOSHI (stiffness) values are higher for 2/1 twill woven fabrics, NUMERI (smoothness) and FUKURAMI (fullness & softness) values are higher for 2/2 twill & 5 end satin, thus giving higher Total Hand Value (THV). Plain woven fabrics gives lower KOSHI, NUMERI & FUKURAMI, thus lower THV. Irrespective of the weave, fabrics woven using finer yarns helped in improving the surface smoothness. The air resistance is more for twill and satin woven fabrics. The air permeability & moisture transport rate is more for plain woven fabrics. Thermal insulation values are higher for 2/2 twill woven fabrics.