Fully Automatic Weave Identification in Woven Fabrics Using Digital Image Processing

The paper presents an approach to model the behaviour of a representative volume design elements of pile warp woven fabrics. With the internal geometry of the built, the model computes overall parameters of the deformed pile warp woven fabrics, such as fibre volume fraction, porosity etc. The internal geometry is visualised and such properties as pore structure in typical cross-sections are analysed. The internal geometry description is further fed into flow modelling software, which allow computing local permeability and mechanical properties of the deformed the Loop of pile warp woven fabrics. This study aims at the structure of the geometrical characteristics of a warp pile woven fabrics structure by using the basic fabric parameters to find a suitable model that makes possible the prediction of weavability limited and suitable for their performance, and the evaluation of a three-dimensional plain pile warp woven fabrics geometrical model. Dimensional plain pile warp woven fabrics geometrical model. Loop lengths, realistic models based on a better approach of geometry and material properties will be created in order to investigate the numerical analysis performance of the performance properties of pile warp woven fabrics. Porosity, air permeability of a woven fabric on the base of its constructional parameters. Of the warp pile woven fabrics structure via module. As the constructional parameters of a woven fabric are considered: maximum and suitable setts of warp and weft yarns, diameters (or fineness) of warp and weft yarns and a type of weave. This research is focused on cloth warp pile woven fabrics structure of warp cotton and several types of weft. The evaluations of the geometrical model for three level of loop length (height, medium, low) are carried out by three methods of weft density. based on the comparison of the measured warp pile loop length of existing warp pile woven fabrics structure fabrics with the calculated values that result from the geometrical model. And controlled of the shape of the warp pile loop that result from the air permeability , thickness, porosity, test of the fabrics with the air permeability, thickness, porosity curves that are received from the simulation of the analysis. A correlation between calculated values of structural parameters and experimental; The suggested process makes possible prediction of ideal sett of weft for terry woven fabric in three densities (18) wefts with the rest of possible properties throw porosity and value of air permeability, wick-up of pile warp woven fabrics, to the materials types of weft which are: cotton, polyester, blended (cotton/polyester (50/50)) viscose rayon, which are characterised by their constructional parameters as are sett of piles warp and ground yarns, by diameters or fineness of cotton materials and by the plain of weave Keywords: weavability limited, geometrical pile fabric, permeability, porosity. geometrical Models,

The number of filaments in yarn cross-section, weave density, and weave type are considered the most important factors that affect the property of air permeability of multifilament woven fabrics. Microfilament yarns significantly affect the air permeability property of this type of fabric because of the low porosity between the filaments. This study deals with the development of a fuzzy logic model for predicting the air permeability of multifilament polyester woven fabrics produced from conventional and microfilament yarns. The polyester multifilament yarns used in this study were produced with three different microfilament fineness and two conventional filament fineness levels. The woven fabric samples used in this study were obtained in three weave types: plain, twill, and satin, and with five different weave densities. In accordance with the experimental test results, both regression analysis and fuzzy logic system were built. The air permeability results generated from the developed fuzzy model and the regression equations were compared with the experimental values. Satisfactory and accurate prediction results were obtained with the developed fuzzy logic model. The mean absolute error of the fuzzy model and regression analysis were found to be 2.32%, 12.59%, respectively. Therefore, it was confirmed that the fuzzy model was superior in predicting air permeability.

Several types of fabrics were laboratory-tested for their effectiveness in workers protection to pesticide-laden dust encountered in the agricultural environment. Of the applied less than 100 mesh dust, penetrations through knitted jersey and woven fabrics were greater than 87% and less than 5.8%, respectively. Treatment of woven fabrics with fluorocarbon polymers curtailed penetration by greater than 60%. Nonwoven fabrics allowed less than 0.5% dust penetration. Parathion mixed with 100-mesh sieved dust resulted in increasing "ppm" levels with decreasing particle size; extent of parathion conversion to paraoxon was independent of particle size for the sandy loam dust used.

Performance evaluation of textile materials is necessary to determine the use of an end-product. Woven and knitted materials are the most preferred manufacturing techniques due to their certain characteristics suitable for apparel and upholstery. The present study aims at determining the bending length, rigidity and modulus of fabrics through standardized test procedures to measure the draping behaviour of an end product. The results identified the phenomenon that specimens manufactured with woven fabrics were better in drapability compared with knitted fabrics. Moreover, it was identified that type of fiber also plays an important role in determining the stiffness of fabrics such as silk fiber showed excellent results. A comprehensive comparison was made between various types of fabrics. The study can be helpful for textile producers to make amendments to their construction parameters to present acceptable stiffness and draping qualities of fabrics to the end consumers.

This study prepares and explores the properties of three types of woven fabrics that have electromagnetic shielding effectiveness (EMSE), far infrared (FIR) emissivity, or both (EMSE/FIR). The EMSE woven fabrics use stainless steel (SS) staple blended yarn and the FIR woven fabrics use FIR polyester filaments. The woven fabrics are made with various structures, densities, lamination layers, and warp/weft arrangements in order to yield the optimum EMSE and FIR emissivity. The experimental results show that an increase in SS content slightly increases the EMSE at the frequency range between 300 and 600 MHz, but does not significantly increase the EMSE at a high frequency of between 2000 and 2200 MHz. However, using SS staple blended yarn for both the warp and the weft significantly increases the EMSE by between −8 and −16 dB. The FIR emissivity increases as a result of an increasing amount of FIR polyester filament and reaches the optimum, 0.88.

The research focuses on the influence of elastane (Spandex) incorporation in the weft direction of cotton fabrics, and the structural properties (fabric density, type of weave) on the thermal and water vapor resistance level. For that purpose, woven fabrics, in plain and twill weave with two different densities (17 and 20 yarns/cm) in the weft direction, were made from 100% cotton (conventional) and from a mixture cotton/elastane in the ratio 93.8%/6.2% (elastic fabric) intended for men’s shirts for the summer season. Thermal and water vapor resistance were determined with two novel methods, which were compared with the well-known Permetest method. The thermal resistance was calculated according to the thermal conductivity method which was established by the faculty research laboratory and with the Permetest, while the water vapor resistance was measured with the water cup method (developed by Professor D. Jaksic) and with the Permetest. The research results indicate that cotton fabrics in twill weave with elastane in the weft direction have higher thermal and water vapor resistance compared to conventional cotton fabrics. The reason lies in the higher yarn density of fabrics with elastane in the weft direction in twill weave (from 24 to 29–31 yarns/cm in the warp direction) compared to the plain weave (from 24 to 28 yarns/cm in the warp direction).

20 - Qualitative Evaluation of the Barrier Effect of Textiles in use

Fabric plays a significant role in our daily life. The physical characteristics and look of the cloth are determined by its weave in addition to its color and texture. Sometimes it is important to identify the fabric’s weave kind. Additionally, it could be necessary for the end user to verify the type of fabric weave. To identify the fabric’s weave type, a manual invasive technique is typically employed, which also necessitates a thorough understanding of the fabric weaving process. This article proposes an automatic recognition method that uses pixel-level information to identify color, weave, and density patterns which is a low-cost, non-invasive, image-processing-based method. Good quality camera is used to take the pictures of the fabric. First, the skew of the warp and weft threads is corrected using a technique based on the Hough transform. Second, projection of a brightness technique is used to identify the yarns and nodes in the improved images. The results of proposed method is used to compute the density. Proposed technique applied for three different yard dyed woven fabrics. In this method, warp density error is around 1%. Next, using the boundary information, each node’s type is determined. Knowing the kind of each node allows us to obtain the weaving pattern.

Nowadays, technical woven fabrics are broadly utilized as reinforcement of composites. Resin capacity of woven fabric is one of the main challenges in laminate fabrication. Resin diffusion during fabrication of the composite is extremely depended on fabric micro-morphology. The geometry of weave unit cell and its pore are fundamental factors in evaluating resin capacity and resin diffusion within fabrics. The main attempt of this study was obtaining an approach to evaluate resin capacity of a woven fabric via simulating pore shape and pore volume. For this purpose, four basic unit cells for all kind of weaves were simulated with the two shapes of tow cross-section: lens and racetrack. Afterwards, 3D shape and volume of their pores were simulated using this approach. The proposed approach is established on the base of initial data of fabric such as tow setts, tow titers, planar density and thickness of a technical fabric. To assess the simulation, three types of woven fabrics namely, plain, twill and satin were impregnated by epoxy resin using vacuum infusion process. The volume fractions of the matrix and fibers of real composites were compared with simulated ones. It was demonstrated that the approach with racetrack assumption led to high degree of convergence with experimental results. The maximum relative error of pioneered method to evaluate volume of the pore in this condition exceeded up to 1.43 %. Suitable correlation between volume fractions of the pore and void was observed in experimental data. It is experimentally demonstrated that the void volume fraction of composite will be increased with decrease of pore volume due to difficulty of wetting. In this paper, it is illustrated that the resin capacity of a woven fabric is a function of vacuum level in vacuum infusion process. For instance, resin capacity of a certain plain fabric could be reduced up to 10 % under 60 kPa (0.6 bar) of vacuum in contrast with steady state of fabric at room atmosphere.

This paper presents an experimental study of the seam performance of PET/nylon-elastane woven fabrics. In this study, plain and twill fabrics were woven with three different weft densities. Two different sewing threads were used during the sewing of the fabrics. Therefore, 12 samples having different specifications were obtained. For these fabrics, nylon-elastane air-covered yarn was used as the weft yarn and PET air-covered yarn was used as the warp yarn. Seam strength, seam slippage strength, sewing needle penetration force and seam efficiency were determined for these fabrics for seam performance. The purpose of this study was to identify the suitable sewing conditions in order to achieve good seam performance. This study also investigated the effects of weft density, weave type and sewing thread on the seam performance.

In this paper, we present a novel automatic method for woven textile structure recognition in fiber-level. This method is based on digital image analysis techniques. It allows automatic weft yarn and warp yarn crossed-area segmentation through a spatial domain integral projection approach. Secondly, by applying unsupervised fuzzy c-means clustering on multi-scale direction invariant texture features based on gray level co-occurrence matrix, we can classify detected segments into two clusters. Finally, using a fuzzy rule based analysis on texture orientation features, the yarn crossed-area states are automatically determined. To verify the validity of this method, a number of textile images are used. The samples we choose have different weave types: plain or twill, different fiber types and yarn counts. The recognition results match the actual structure of tested samples. A possible 3D representation of woven structure identified is also shown in this paper.

In the current era, rehabilitation and strengthening of reinforced concrete structures is a major need due to premature structural damage owing to various environmental effects, natural hazards and major modifications in the existing building use. Textile fabrics can be an economical and viable option in comparison to traditional strengthening techniques. Therefore, this study was planned to investigate the use of locally available textile fabrics for structural applications leading to economical and sustainable solutions. Sixteen fabrics were collected randomly from the local market and a series of tests including microscopic analysis, mass per unit area, ends and picks count, yarn number and uniaxial tensile strength were conducted to explore the most suitable textile fabric from strength and application aspects. Moreover, rectangular textile-reinforced mortar specimens were prepared incorporating those textile fabrics. Tested textile fabric specimens exhibited mass per unit area in the range of 117 to 1145 g/m2 depending on the fabric types. It was observed that tensile strength of the tested textile fabric depends on fiber composition, ends and picks count, yarn number and weave type. The greater the number of yarns in a fabric, the denser it will be and therefore it will be stronger in either direction (warp and weft). It was observed that the tensile strength in warp direction was higher than in weft direction due to the higher number of yarns in the warp direction. For instance, tested specimen TF16 showed ultimate tensile loads of 2890 and 2600 N in warp and weft directions, respectively. Furthermore, plain weave type fabric showed higher strength compared to that of the twill weave. It can also be argued that among the sixteen selected fabric specimens, plain weave fabric (i.e., glass) was found most suitable for textile-reinforced mortar applications due to adequate spacing and alternative movement of yarns, which leads to a stronger bond with the matrix and ultimately achieving higher tensile strength.

Experimental study on the performance of woven fabric rubber composite armor subjected to shaped charge jet impact

13 - Friction and other aspects of the surface behavior of woven fabrics

Assessment of digital image correlation for tensile characterization of fique woven textiles used as matrix-reinforcement