Yarn Appearance Research Articles

The model of ring-spun slub yarn based on random fiber arrangement and its application: Part 2 Prediction of morphology parameters for slub yarn and simulation of slub fabric

The morphology parameters of slub yarn include slub length, base length, the length of the transitional segment, slub multiple, slub linear density, base linear density, and average linear density of slub yarn. These parameters have an impact on the appearance of both slub yarn and its fabric. This paper aims to predict the morphology parameters of spun slub yarn by utilizing the model proposed in Part 1 for ring-spun slub yarns. Once the slub generation mode was known, slub yarn could be simulated with the morphology parameters. The simulated slub fabric was obtained by arranging the simulated slub yarn in the warp and weft directions. According to our study, the prediction accuracy of each morphology parameter was over 80% by comparing the simulated parameters with the measured ones of spun slub yarn. The CV (coefficient of variation) of the slub segment number per unit area was utilized to assess the distribution of slubs in the simulated fabric. This research can facilitate the development of slub yarn and its fabric, providing guidance for technicians to enhance production technology.

Development of multi-material hybrid yarns consisting of steel, glass and polypropylene filaments for fiber hybrid composites

With the increased use of fiber-reinforced composites (FRPs), the design of a new generation of composite structures with high stiffness and a ductile material behavior is required to cope with complex load scenarios and high damage tolerances. This can be achieved, in particular, by a combination of conventional FRPs, which possess high stiffness and strength, with metallic materials characterized by their high ductility and associated higher energy absorption capacity. Currently, there are no solutions for the hybridization of high-performance filament yarns, metal filament yarns or thermoplastic filament yarns at the micro level. Therefore, the aim of this paper is the hybridization of multi-fiber components intermixed at the micro scale. For this purpose, three hybridization processes were investigated. They are conventional air-jet technology, air-jet technology based on a modified air nozzle and an additional pre-spreading device and a process based on a newly developed multi-level-intermixing device. The effect of different processing parameters, such as air pressure, air nozzle and type of manufacturing, on the tensile properties, appearance and damage of multi-material hybrid yarn was analyzed. The results show that the developed multi-material hybrid yarns have high potential for use in composites with high requirements for crash and impact properties.

The model of ring-spun slub yarn based on random fiber arrangement and its application: Part 1. Study on the relationship between fiber distribution and the length of the transitional segment of slub yarn

In this paper, the research on the transitional segment of slub yarn mainly focuses on the length of the transitional segment. Slub yarn was simulated by randomly determining the fiber position with the Monte Carlo method according to the draft principle of ring spinning for slub yarn. The length of the transitional segment was obtained by determining its starting and ending position according to the mass curves of the simulated and real-spun slub yarns. According to the data analysis, the fiber length, acceleration and deceleration time on draft rollers’ velocity, and slub multiple affect the length of the transitional segment. Both the lengths of the left and right transitional segments are all equal. The maximum error rate of the simulated value to the measured value of the length of the transitional segment is approximately 12%. The empirical formula has been established to estimate the length of the transitional segment. Compared with those of the simulated and real spun slub yarns, the error rate of the length of the transitional segment calculated by the empirical formula is less than 10%. The research content of this paper provides a basis for studying the appearance and properties of slub yarn.

Enhancing the quality of elastane-cotton core yarn by compact spinning

The quest for highly stretchable fabrics with good aesthetic and functional properties has led researchers to constantly involve in mingling of natural and synthetic fibers. Elastane-cotton core yarns have an increasing demand due to their wear comfort and stretch-to-fit properties; therefore, efforts are still going on to optimize the yarn properties to meet the requirements for diversified applications. With a view to enhancing the appearance and performance characteristics of elastane-cotton core yarns, the present work was undertaken to manufacture them by exploiting the most modern and versatile pneumatic compacting mechanism, namely Suessen's EliTe compact spinning system. Elastane-cotton core yarns of different counts (20 tex, 30 tex and 60 tex) were produced with compact and conventional ring spinning system. The difference in morphology and physical properties of two types of yarns were compared after a thorough investigation by scanning electron microscope, evenness tester and strength tester. The results exhibited a noticeable decrease in hairiness, hairiness variation and neps values, especially seed-coat neps, for elastane-cotton compact core yarn. Unevenness & imperfection of compact core yarns were also found to be decreased that were reflected to the proportional enhancements in tenacity & elongation values. The overall observation reveals the potential of pneumatic compacting mechanism in obtaining elastane-cotton core yarn with superior structure and improved mechanical properties.

Evaluation of yarn appearance on a blackboard based on image processing

Yarn evenness and hairiness are the appearance characteristics of yarn, which affect textile processing and product quality. To evaluate yarn appearance economically and effectively, an image-processing method is proposed in this paper to analyze yarn appearance on a blackboard. Firstly, an image of a yarn blackboard is captured by the scanner. Then, the yarn core and hairy fibers are segmented from the captured image with image-processing algorithms. The coefficients of variation of the yarn diameter ( CVbd) and the hairiness index ( M) are respectively calculated based on the information about the yarn core and hairy fibers in the image. Finally, the results of the proposed method are compared with those from the Uster Tester. The experimental results demonstrate that yarn appearance can be objectively evaluated using yarn blackboard images. The test results of different yarn blackboards made from the same yarn are stable and consistent. The correlation coefficient between the proposed method and the Uster Tester is 0.98, which proves that the H value can be accurately predicted by the hairiness prediction model. A hairiness prediction model built by the M value is also proven to be accurate when used to predict the corresponding value of the Uster Tester. Compared with the existing yarn evenness and hairiness test methods, the proposed method is more economical and practical.

Yarn Performance of Texas Quality Upland Cotton Germplasm

Ring and rotor spinning predominate the cotton spinning market with ring spinning dominating globally while United States (U.S.) spinners prefer rotor because of its production speed and high automation level. Newer and faster spinning technologies such as “air jet” spinning, exemplified by Murata Vortex Spinning (MVS), are being deployed. Rotor spinning produces yarn five times faster than ring, and the MVS produces 100 % cotton yarn over 20 times faster than ring spinning. Fiber quality improvements will be necessary for Upland cotton to be competitive with other fibers on MVS. Texas A&M Agrilife Research has released improved fiber quality germplasm lines and cultivars that equal or exceed the fiber quality parameters associated with the New Mexico Acala germplasm pool, which is considered the elite quality among Upland breeding pools. Two improved quality Texas A&M germplasm lines were compared with Acala 1517-08 for High Volume Instrument (HVI) and Advanced Fiber Information System (AFIS) fiber quality parameters plus yarn strength and appearance parameters. These genotypes were grown in 2017 and 2019 at Weslaco, Texas under irrigated culture. The three genotypes were similar in all fiber quality measurements except lengh and fiber strength. TAM 06WE-621 and TAM KJ-Q14 produced stronger yarns with improved yarn appearance when spun on either ring or air jet spinning technologies. Data suggest that the Texas A&M quality germplasm pool can be used to develop Upland cotton cultivars that will produce fibers competitive for the emerging MVS technology.

Fabrication of Multilayered Nanofiber Scaffolds with a Highly Aligned Nanofiber Yarn for Anisotropic Tissue Regeneration.

Nanofibrous scaffolds were widely studied to construct scaffold for various fields of tissue engineering due to their ability to mimic a native extracellular matrix (ECM). However, generally, an electrospun nanofiber exhibited a two-dimensional (2D) membrane form with a densely packed structure, which inhibited the formation of a bulk tissue in a three-dimensional (3D) structure. The appearance of a nanofiber yarn (NFY) made it possible to further process the electrospun nanofiber into the desired fabric for specific tissue regeneration. Here, poly(l-lactic acid) (PLLA) NFYs composed of a highly aligned nanofiber were prepared via a dual-nozzle electrospinning setup. Afterward, a noobing technique was applied to fabricate multilayered scaffolds with three orthogonal sets of PLLA NFYs, without interlacing them. Thus the constituent NFYs of the fabric were free of any crimp, apart from the binding yarn, which was used to maintain the integrity of the noobing scaffold. Remarkably, the highly aligned PLLA NFY expressed strengthened mechanical properties than that of a random film, which also promoted the cell adhesion on the NFY scaffold with unidirectional topography and less spreading bodies. In vitro experiments indicated that cells cultured on a noobing NFY scaffold showed a higher proliferation rate during long culture period. The controllable pore structure formed by the vertically arrayed NFY could allow the cell to penetrate through the thickness of the 3D scaffold, distributed uniformly in each layer. The topographic clues guided the orientation of H9C2 cells, forming tissues on different layers in two perpendicular directions. With NFY as the building blocks, noobing and/or 3D weaving methods could be applied in the fabrication of more complex 3D scaffolds applied in anisotropic tissues or organs regeneration.

Design and development of a piezo-resistive sensor based on PEDOT: PSS applied to Sisal’s natural fiber for monitoring of 3D warp Interlock fabric

The aim of the current study is to develop and optimize a flexible sensor based on a natural sisal fiber. Based on this sensor yarn, different fibrous reinforcements of 3D warp interlock fabrics used in composite materials could be monitored. This natural yarn (Sisal) has been pre-coated with a layer of PVA solution which makes it possible to homogenize the surface of the yarn and serves as a substrate for the coating phase. A copper metal wire was used as a connecting device to the measurement acquisition system. Some Conductive Polymers Composite (CPC) based on PEDOT: PSS are compared and used as a coating layer in order to get the conductive appearance of the sensor yarn. A sensor calibration step was carried out which consists in testing the sensor yarn on a MTS traction bench while measuring their resistance variation simultaneously. The electromechanical behavior of the different types of sensors will be compared and discussed. Insertion of these developed sensors within 3D woven structures will be helpful for local monitoring and check the inner local elongation of the 3D warp interlock fabric during tensile tests.

Research on Yarn Diameter and Unevenness Based on an Adaptive Median Filter Denoising Algorithm

In this paper an adaptive median filtering denoising algorithm is proposed to measure yarn diameter and its unevenness. Images of nine different yarn samples were captured using one set of a self-developed yarn image acquisition system. Image separation of the background and yarn sections was conducted using a combination of adaptive median filtering, adaptive threshold segmentation and morphological processing. The noise-free yarn image was used for diameter detection of the subsequent yarn image and the discrimination of the yarn unevenness. Experimental results show that the testing data of yarn unevenness detection based on the adaptive median filter denoising algorithm is very consistent with the data using the traditional method. It is proved that the yarn detection method proposed, based on an adaptive median filter denoising algorithm, is feasible. It can be used to calculate yarn diameter accurately and measure yarn unevenness efficiently, so as to determine the quality of yarn appearance objectively.

A New Method to Evaluate Yarn Appearance Qualities Based on Machine Vision and Image Processing

For improving the efficiency, flexibility and robustness of yarn defect system, a new method is proposed to evaluate the quality of yarn by testing the yarn diameter, defects and hairiness based on machine vision and image processing technology. Firstly, the diameter image processing unit (DIPU) is defined and a series of sampling points are selected from moving yarn, and the DIPU corresponding to each sampling point is segmented from the captured yarn images. The average diameter of DIPU is used to represent the yarn diameter of the test points. In the extraction of yarn images, the DIPU is divided into definite foreground region, definite background region and unknown region according to the characteristics of gray-level projection distribution, and the unknown region is further processed with Poisson matting method, in which the yarn image and background image are completely separated by a defined connectivity classifier. After the yarn core is extracted by the classifier, the hairiness is divided by using image subtraction. Finally, in order to further evaluate the quality of yarn, the yarn defects were analyzed by the method of statistical methods.

The effect of different methods of weft yarn insertion in modern weaving looms on both functional and aesthetic properties of ladies summer fabrics

There is a deficiency in both aesthetic and functional properties of cotton yarns (carded, combed) and thus the fabrics produced from them (weaving, knitting, domestic fabrics) manufactured from the most spinning methods achieving the aesthetic and functional properties of yarns spinning. In order to contain the yarns on a fair number of dead, immature and short fibers, which are inflexible because these fibers are hollow with a few convolutions in it, which causes their conglomeration and cohesion with each other during the spinning process so-called Neps and hairiness. Which is detrimental to the appearance and regularity of both cotton yarns and fabrics especially after the final processing. In terms of functionality, these imperfections (IPI) reduce the tensile strength, elongation, uniformity of yarns, their resistance to wrinkle, friction due to the weakness of flexibility and softness, which leads to shortening the life span of fabrics produced from them. Increases such imperfections (IPI) clearly in both yarns and fabrics, especially with the low quality of current Egyptian cotton grades. Therefore, many developed countries and Echo specifications prohibit the increase of the formaldehyde ratio to 75 ppm and less so, in children's clothing especially those that have direct skin contact (low health properties and pollution of the environment) from one side, the final processing of cotton fabrics leads to deterioration of both physical, chemical and mechanical properties. These are : low tensile strength, elongation, abrasion resistance and friction due to deterioration of cellulose strength after processing due to high mechanical strength, loss of tensile strength From 30% to 60% as compared to untreated fabrics. Objectives; Studying the response of the structural structure of compact cotton gassed yarns (carded, combed) with a solution of sodium hydroxide in yarn hank form using yarn tension, and achieve the physiological comfort of the body through both functional and kinetic, thermal, tactile and psychological characteristics commensurate with the functional and aesthetic performance of external clothing and domestic fabrics using environmentally safe materials and free of formaldehyde. Methodology : the analytical and experimental methods. Results : The correlation coefficient was extracted and the regression line equation for the different relationships between the different gassed yarns count of the different types (carded, combed) after mercerizing process and : The yarn tensile strength, Breaking Elongation, Yarn Hairiness, Yarn Imperfection (IPI), Yarn T.P.I, yarn Humidity, Gassed yarn count before mercerizing. The yarn count of both carded compact cotton gassed yarns and combed compact cotton gassed yarns reduced by cotton count system after mercerizing process-using tension for many reasons. Yarn tensile strength increased for both carded compact cotton gassed yarns and combed compact cotton gassed yarns after mercerizing process-using tension for many reasons. Breaking elongation ratio of both carded compact cotton gassed yarns and combed compact cotton gassed yarns reduced after mercerizing process-using tension for many reasons. Yarn hairiness disappeared completely in carded compact cotton gassed yarns, especially in combed compact cotton gassed yarns after mercerizing process-using tension for many reasons.

Improving Cotton Yarn Appearance Grading System using Image Processing of Blackboard Yarn Winder in MATLAB

The existing paper is concerned with the improvement of the traditional cotton yarn appearance grading system with the help of computerized MATLAB image processing and fuzzy logic system. The complete system of this research comprises of yarn winder blackboard, digital camera for taking sample image, computer for processing and analyzing the sample quality by using MATLAB graphical user toolbox to facilitate the investment of algorithm during image processing and analyzing of yarn quality. Since in textile industry, mostly the cotton yarn appearance grading evaluation is principally based on labor-intensive assessment. This research used to solve the inherent limitations of the human visual inspection. The MATLAB image processing in graphical user toolbox integrates the image acquisition, digital image extraction, and yarn quality classification based on the sample yarn count and the ASTM (D2255) standard of yarn image of number of pixels. Totally this paper proposes the new method for cotton yarn appearance grading system by using matlab image processing methods and fuzzy logic systems to modify and improve the existing manual appearance grading system.

The effect of mercerization process on physical, chemical and mechanical properties of compact cotton gassed yarns.

There is a deficiency in both aesthetic and functional properties of cotton yarns (carded, combed) and thus the fabrics produced from them (weaving, knitting, domestic fabrics) manufactured from the most spinning methods achieving the aesthetic and functional properties of yarns "compact spinning". In order to contain the yarns on a fair number of dead, immature and short fibers, which are inflexible because these fibers are hollow with a few convolutions in it, which causes their conglomeration and cohesion with each other during the spinning process so-called "Neps" and hairiness. Which is detrimental to the appearance and regularity of both cotton yarns and fabrics especially after the final processing. In terms of functionality, these imperfections (IPI) reduce the tensile strength, elongation, uniformity of yarns, their resistance to wrinkle, friction due to the weakness of flexibility and softness, which leads to shortening the life span of fabrics produced from them. Increases such imperfections (IPI) clearly in both yarns and fabrics, especially with the low quality of current Egyptian cotton grades.

Analysis of the appearance of two-color cotton yarn by the double-channel spinning system

The main aim of this paper is to investigate the fiber distribution on the surface of a kind of novel two-color yarn spun by regulating the feeding ratio of two colored rovings on a modified ring spinning frame, which is named the double-channel spinning frame. The surface distribution ratio ( SDR) and the coefficient of variation of surface distribution evenness ( CV sd) of the two colored fiber strands in the yarns was used to quantify the fiber distribution feature along the yarns based on a purpose-made image acquisition device and the corresponding image processing method. The effect of the weight ratio, roving feeding position and spinning method on the mean SDR and CV sd were studied, and the testing results of the Z-twist and S-twist two-color yarns spun by a modified traditional ring spinning frame as well as the yarns spun by a modified compact spinning frame were compared with each other. The fibers of the left-hand roving are more likely to distribute in the surface of Z-twist yarn, while the fibers of the right-hand roving tend to distribute in the surface of S-twist yarn. Four linear fitting equations of the 19.4 tex Z-twist and S-twist two-color ring spun yarns and two-color compact spun yarns were developed to predict the relationships between the mean SDR and weight ratio of two colored fibers.

Comparative study of fiber trapping by filaments in conventional and diagonal sirofil systems

In this study, geometrical and theoretical analyses were conducted comparatively for fiber trappings by filaments in the left diagonal, conventional and right diagonal sirofil with right strand and left filament arrangement (denoted as LDS-RS-LF, CS-RS-LF and RDS-RS-LF, respectively)and left diagonal, conventional and right diagonal sirofil with right filament and left strand arrangement (LDS-RF-LS, CS-RF-LS and RDS-RF-LS, respectively). White filaments and blue rovings were used to produce conventional and diagonal sirofil yarns to validate the analysis. Online and offline fiber trapping capacity comparisons indicated that CS-RS-LF and CS-RF-LS had higher capacities of trapping fibers than LDS-RS-LF and RDS-RF-LS, respectively, and lower capacities than RDS-RS-LF and LDS-RF-LS, respectively. Yarn appearance and tensile properties results revealed that diagonal sirofils with improved fiber trappings increased yarn hairiness and tensile properties, while the ones with deteriorated fiber trappings decreased yarn hairiness and tensile properties. Sirofil yarn unevenness CVm decreased as the fiber trapping enhanced by RDS-RS-LF and LDS-RF-LS and increased as the fiber trapping weakened by LDS-RS -LF and RDS-RF-LS. This corresponded well to our theoretical hypotheses on fiber trappings by filaments in conventional and diagonal sirofil systems.

Research on the Modeling Method for Digital Weaving Based on the Information of Physical Yarns and Fabric Pattern

The modeling method of digital weaving is one of the key technologies in digital textile, which is considered a great value in the textile industry. Based on the real yarn image information and the specified weave structure, this paper presents a method to realize that modeling for digital weaving. The imaging system has been designed to extract the information of yarn appearance of geometry characteristic. The basic cycle matrix is used to represents weave structure and the weaving matrix is for modeling. Weaving matrix can be obtained by extending the basic cycle matrix. According to the weaving matrix, the weaving network is built by the selected number of warp and weft yarns and their order of arrangement. Then the physical yarn image is divided into a set of nodes and is filled to the weaving network. By extracting the connecting matrix and stress matrix of warp and weft yarns respectively, the visual processing units (VPU) can be built. Finally, all VPUs are drawn according to the corresponding shape and illumination model. Through image splicing for all VPUs according to their corresponding position in weaving network, the modeling of digital weaving can be realized. Experiments demonstrate the validity of the method proposed in this paper.

A review on the formation, causes, measurement, implications and reduction of neps during cotton processing

ABSTRACTNeps not only adversely affect the appearance of cotton yarns and fabric but are also usually associated with lower yarn strength, ends down in spinning and less-uniform yarn. Depending on the type and size of the nep, the appearance of dyed or printed fabrics is negatively influenced by the presence of these blemishes, which appear as white or dark spots on the surface, resulting in downgrading or rejection.Although neps have been identified as a major quality issue in cotton production and processing as far back as the late 1700s, no comprehensive review has been published on the formation, composition, measurement, consequences and ways to reduce the effects of neps, only a limited review has been published in 1999 [1]. Given the adverse effects on quality arising from neps, it was considered important to compile and publish a comprehensive and definitive review of published work and knowledge to date relating to cotton neps for this issue of Textile Progress.

An overview of the application of image processing technology for yarn hairiness evaluation

Purpose This paper aims to overview the current status of development and application of digital image processing technology used for the yarn hairiness evaluation. Design/methodology/approach Digital image processing technology is one of the new methods used for the yarn detection, which can be used for the digital characterization and objective evaluation of yarn appearance. The comparison between the traditional detection methods and this new developed method was made and analyzed. Findings Compared with the traditional methods, image-based methods have the advantages of being objective, fast and accurate. Therefore, it was proved that digital image processing techniques should be a new trend in terms of the yarn appearance evaluation.

A study on the influence of a surface-contacting spinning strand on yarn appearance during sirofil spinning

Ring spun yarn hairiness can be reduced by such methods as spinning with a contact surface and Z-twisting the staple strand in a “left diagonal” yarn path (denoted as LDP). Actually, the LDP method already exists in sirofil spinning technology. In this study, mechanism analysis of controlling and trapping staple fibers is conducted theoretically for sirofil spinning with a contact surface. Analysis reveals that contacting with a rubber surface leads to deformation of the straight sirofil spinning strand; this can better the tension and twist distribution on the right-hand component of the sirofil spinning triangle to improve LDP sirofil yarn appearance. Related experiments are also carried out to validate the theoretical analysis. Online pictorial investigation confirms the deformation of the straight sirofil composite yarn once it contacts with a rubber surface. Experimental results show that the lower weight loss and smoother appearance are bestowed upon LDP sirofil yarn spun with a rubber contact surface, which agrees well with corresponding theoretical analysis.

A New Measurement System of Yarn Appearance Based on Machine Vision

In this paper, a new yarn appearance measurement system based on machine vision is introduced. The yarn images are continuously captured by image acquisition system. To extract the main body of the yarn accurately, the yarn images are processed sequentially with threshold segmentation and morphological opening operation. Then the coefficient of variation (CV value) of diameter is calculated to characterize the yarn evenness. The measurement process achieves result (CV value) which can be compared with USTER evenness tester by image processing techniques. By comparing different methods which use different algorithms, a suitable method is chosen to be used in this new measurement system. Then a more accurate, more efficient and faster measurement system will meet requirements in the future.