Yarn Strength Research Articles

The Prediction Model of Cotton Yarn Intensity Based on the CNN-BP Neural Network

Yarn strength index is a heavy index of yarn quality, Yarn quality can be well controlled by predicting yarn strength index. Generally, multiple non regression algorithms, support vector machines (SVD) and BP neural network algorithms are generally used to predict yarn strength. This paper presents an algorithm to connect the convolution neural network (CNN) with the BP neural network, which is written as the CNN-BP algorithm. We use 20 sets of data to train CNN-BP algorithm, regression, V-SVD algorithm, and BP neural network. We tested CNN-BP algorithm, regression, V-SVD algorithm, and BP neural network with 5 sets of data. The CNN-BP neural network algorithm is the best in these four algorithms.

Numerical simulation of flow field in the twisting chamber of Murata vortex spinning based on the hollow spindle with different structures

The novel hollow spindle with spiral guide grooves is introduced into the manufacture of Murata vortex spun yarn for the sake of enhancing the vortex yarn’s strength. By means of numerical simulation, the airflow characteristics in the conventional twisting chamber and novel twisting chamber of Murata vortex spinning are obtained and compared in order to explain yarn formation for adoption of the novel hollow spindle. The airflow distribution near the spiral guide grooves is analyzed, and the influence of airflow changes caused by the groove structure on the movement of the free end fibers and the yarn strength is analyzed. The results show that the spiral guide grooves will influence the pressure and velocity distribution in the twisting chamber, especially near the areas of the guide grooves. The guide grooves can guide the swirling airflow moving down the conical cavity of the twisting chamber, resulting in increases of the tangential, axial, and radial velocities of airflow in the conical cavity. And it is expected to produce fiber migration in the yarn cross-section and the self-twist effect of wrapped fibers. These phenomena will strengthen the wrapping and twisting effect of the free end fibers and inter-fiber cohesive force of vortex spun yarn in the process of yarn formation, and finally improve the strength of vortex spun yarn due to adopting the novel hollow spindle.

Regularities in Variation of Support Functions of Physically Nonlinear Elastic-Visco-Plastic Law of Strain of Cotton Yarn

Support functions of the parameters variation of proposed physically nonlinear elastic-viscoplastic law of strain of cotton yarn are determined on the basis of the results of processing the experimental data on yarn tension to breakage. These functions allow us to determine the average values of nonlinear law parameters, which allow its use in practice in solving the applied problems of yarn mechanics and determining and evaluating the strength of cotton yarn.

Analyzing the Effect of Spinning Process Variables on Draw Frame Blended Cotton Mélange Yarn Quality

An investigation has been made to study the effect of important spinning process variables namely shade depth, ring frame spindle speed and yarn twist multiplier (TM) on various yarn quality parameters like unevenness, strength, imperfection, elongation at break and hairiness index of draw frame blended cotton melange yarn. Three factors Box and Behnken design of experiment has been used to conduct the study. The quadratic regression model is used to device the statistical inferences about sensitivity of the yarn quality parameters to the different process variables. The response surfaces are constructed for depicting the geometric representation of yarn quality parameters plotted as a function of process variables. Analysis of the results show that yarn strength of draw frame blended cotton melange yarn is significantly affected by shade depth and TM. Yarn unevenness is affected by shade depth and ring frame spindle speed. Yarn imperfection level is mainly influenced by the shade depth and spindle speed. The shade depth and yarn TM have shown significant impact on yarn hairiness index.

Effects of fiber types and blend ratios on Murata Vortex yarn properties

Murata Vortex spinning (MVS) system is one of the unconventional systems for yarn manufacturing. It is suitable for spinning of 100% cotton fibers, synthetic fibers, and cotton/synthetic fiber blends which are 1 inch or more in length. The production ranges are between Ne 15-60. Vortex yarn and fabrics have low hairiness, clear appearance, high resistance to pilling and abrasion. In this study, the vortex yarns with Ne 30 are produced in different blend ratios in Murata Vortex Spinner using carded cotton, viscose, modal, silver-added polyester (Flexsil-D2™), polyester, and nylon 6.6 fibers. Vortex spun yarns are tested to determine the yarn properties which are diameter, density, roundness (shape), unevenness, imperfection, Uster hairiness (H), Zweigle hairiness, tenacity, and elongation. The study reveals that the fiber type has quite significant effects on yarn properties. In terms of structural properties, cotton is the most negative fiber while regenerated cellulosic fibers are the most positive. As modal, nylon and polyester fiber increase yarn strength, nylon and viscose fiber increase breaking elongation. Viscose and modal reduce unevenness, imperfection and hairiness while polyester and nylon exhibit more negative effect on these properties.

Cotton Yarn Quality Prediction Based on Mind Evolutionary Neural Network

In order to forecast the quality of cotton yarn based on the cotton fiber indexes more accurately, a yarn quality forecasting model based on Mind Evolutionary Algorithm (MEA) was used to optimize the BP neural network prediction of yarn strength and yarn evenness. The model adopts the Mind Evolutionary Algorithm to complete the BP network weights and threshold optimization, giving full play to the advantages of this method in the field of global optimization. The results show that the BP neural network prediction model based on Mind Evolutionary Algorithm to optimize is superior to the single BP neural network prediction model.

Estimation of yarn strength based on critical slipping length and fiber length distribution

Yarn strength is composed of the total contributions made by all breaking and slipping fibers which are determined by critical slipping length lc. Though the definition of lc has been the focus of many research projects, it still remains unsolved. In this study, idealized assumptions were made on yarn structure, and lc was then estimated. At the same time, the actual contributions that breaking fibers and slipping fibers make to yarn strength were recalculated based on an idealized yarn structure, which was analyzed with the conditional probability method according to fiber length distribution. Then, yarn strength was computed by simulating random fiber arrangement in the yarn. It could be seen from calculated results that the critical slipping length declines as yarn twist multiplier increases. Meanwhile, as the twist multiplier increases, the calculated yarn strength rises to the highest point and then declines, which is in agreement with traditional spinning theory. Thus, the calculation of yarn strength based on critical slipping length could reflect the yarn breaking mechanism with a change in the yarn twist multiplier, and could be applied for further prediction of yarn strength.

A novel technique for coating polypropylene yarns with polytetrafluorоethylene

The article is devoted to an easy and effective method of giving polypropylene yarns the same extremely high chemical resistance as fluoropolymers yarns has. The method is based on the formation of an ultrathin, continuous and even coating of polytetrafluoroethylene on a surface of each filament forming yarn. The adhesion of a polytetrafluoroethylene coating to polypropylene is provided by applying of a diluted suspension of high-disperse polytetrafluoroethylene on a surface of a semi-hardened polypropylene yarn at the oiling stage. Later, the yarn is subjected to orientational stretching. In the process of stretching the coating becomes uniform and oriented thanks to an ability of polytetrafluoroethylene to pseudo-fluidity and a high coefficient of thermal expansion. The polypropylene yarn with a polytetrafluoroethylene coating gets an extremely high resistance to the influence of nitric acid and sodium hydroxide. Its frictional coefficient is close to the frictional coefficient of polytetrafluoroethylene and the strength is much higher than the strength of a common polypropylene yarn. The applied coating has a high resistance to the intensive abrasive action.

Design of an Electronic Chest-Band

In this study, an electronic chest strap prototype was designed for measuring fitness level, performance optimization, mobility and fall detection. Knitting technology is used for production by using highly elastic nylon yarn. In order to evaluate comfort performance of the garment, yarn strength and elongation, air permeability, moisture management and FAST tests (Fabric Assurance Fabric Testing) were carried out, respectively. After testing of textile part of the chest band, IMU sensors were integrated onto the garment by means of conductive yarns. Electrical conductivity of the circuit was also assessed at the end. Results indicated that the weight and the thickness of the product are relatively high for sports uses and it has a negative impact on comfort properties. However, it is highly stretchable and moisture management properties are still in acceptable values. From the perspective of possible application areas, developed smart chest band in this research could be used in sports facilities as well as health care applications for elderly and disabled people.

Running functional sport vest and short for e-textile applications

Sports garments with functional properties have become crucial as well as comfort properties since they improve the wearer performance. For this reason, sport vest and short having high elastic recovery with fall detection sensor, were designed and produced by using flat-bed knitting machine. Comfort properties of short and vest were tested with several test instruments and; tensile strength of elastomeric yarn, air permeability, moisture management, drape and objective handle (FAST tests) of garments were achieved. It was proved that short and vest samples have good comfort properties as a functional sport garment. It was also tested that fall-detection sensor can work efficiently by using a mobile phone application.

Effect of ecological surface treatment method on friction strength properties of nettle (urtica dioica) fibre yarns

Over the last few decades, more attention is given to lignocellulose based fibres as reinforcement material in the polymer composites owing to the environmental pollution caused by the extensive usage of synthetic and inorganic fibres. Developing new natural fibre reinforced composites is the focus of many researches nowadays. They are made from renewable resources and they have less environmental effect in comparison to inorganic fibre reinforced composites. The interest of consumers in eco-friendly natural fibres and textiles has increased in recent years. Unlike inorganic fibres, natural fibres present light weight, high strength/density ratio and are readily available, environmentally friendly and biodegradable. Many different types of natural fibres are exploited for the production of biodegradable polymer composites. The nettle (Urtica dioica L.) is a well-known plant growing on rural sites of Europe, Asia, and North America. Nettle plant contains fibre similar to hemp and flax. However, similar to other natural fibres, nettle fibres are poorly compatible with the thermoplastic matrix of composites, due to their hydrophilic character which reduces mechanical properties of nettle fibre reinforced thermoplastics. In order to improve the fibrematrix adhesion of the natural fibre reinforced composites, surface treatment processes are applied to the lignocellulose fibres. In this study nettle (urtica dioica) fibre yarns were treated with NaOH by using conventional, ultrasonic and microwave energy methods. After treatment processes tensile strength, elongation, friction strength and SEM observations of the nettle fibre yarns were investigated. All treatment processes were improved the tensile strength, elongation and friction strength properties of the nettle fibre yarns. Also higher tensile strength, elongation and friction strength properties were obtained from treated nettle fibre yarns which treated by using microwave energy method.

The effect of groove structure on performance of pneumatic spliced joint

The geometrical structure of splicing chamber has a significant influence on performance of spliced joint with respect to appearance and strength. The air characteristic inside splicing chambers with different structures, namely no groove, 1-mm-width groove, and 2-mm-width groove, were numerically investigated using CFD modeling technology. A spiral ratio of airflow, which is composed by velocity circulation indicating the circumference airflow and average velocity in axial direction, was extracted from the numerical results to describe the role of air flow on the joint forming. The splicing experiments were conducted on the corresponding chambers. The appearance of splicing joint was captured by an optical camera and the splicing strength was evaluated by a yarn strength test machine. The correlation between a spiral ratio of the velocity circulation to the axial average velocity and the performance of spliced joint was verified by analyzing the numerical results and experimental data. With the increase of groove width, the decrease of airflow in axial direction is more obvious than the circumference airflow, leading to larger spiral ratio. As a result, more filaments wrap around the opposite yarn stem and the diameter and strength of spliced joint increase.

Investigation of microcombing parameters in enhancing the properties of carbon nanotube yarns

Microcombing has been reported as a novel processing approach for reducing waviness and improving alignment of carbon nanotubes (CNTs), which effectively enhances the performance of materials made from CNT sheets. In this study, we have systematically investigated the effects of microcombing parameters on the properties of CNT yarns. It is found that the electrical and mechanical properties of CNT yarns first improved with increasing degree of microcombing and then degraded with over-combing. At the optimum degree of microcombing, the electrical conductivity, tensile strength, and Young's modulus of the CNT yarns were improved to 140%, 140%, and 230%, respectively, over those of uncombed yarns. The enhanced yarn properties were resulted from reduced nanotube waviness, improved CNT alignment and denser packing structure, which led to a more uniform yarn structure. On the other hand, over-combing degraded structural uniformity, resulting in lower electrical and mechanical properties. These observations are expected to help with future selection of microcombing parameters for producing high-quality CNT yarns and polymer-CNT composite yarns for superior electrical and mechanical properties.

Morphological and mechanical properties of drawn poly(l‐lactide) electrospun twisted yarns

In this study, the continuous twisted PLLA yarns were produced using an electrospinning device consists of two oppositely charged nozzles. The electrospinning process was performed at different twist rates. The electrospun twisted yarns were drawn at different extension ratios of 50% and 100% and their morphological and mechanical properties of post‐drawn yarns were investigated. The morphological studies at all twist rates shown that uniform and smooth fibers without any bead were formed. Increasing the twist rate up to 240 rpm resulted to a decrease in the average diameter of the fibers in the yarn structure. After uniaxially drawing of the yarns, the average diameter of fibers and thus the yarn diameter decreased. The post‐drawing process enhanced the crystallinity of the fibers in the yarn structure. Furthermore, by increasing the extension ratio, the tensile strength and modulus of yarns increased, while the elongation at break (%) decreased. POLYM. ENG. SCI., 58:1091–1096, 2018. © 2017 Society of Plastics Engineers

Investigation of the mechanical properties of lignin nanofibrous structures using statistical modeling

The growing use of nanomaterials, environmental concerns and related industrial applications have provided unique opportunities for the development of nanofibers from natural biopolymers such as lignin. The main purpose of this study was to develop a direct relationship between lignin single nanofiber, the aligned nanofiber mat and the twisted nanofiber yarn’s strength using the weakest link theory of strength and the statistical model proposed for parallel fiber bundles. Twisted yarn strength was obtained via in situ mechanical properties of yarn constituent nanofibers affected by the Weibull distribution parameters, fiber fragmentation phenomenon, and obliquity. The results showed that the estimated strength of the single nanofiber and the aligned nanofiber mat was in a good agreement with the experimental data. As it might be expected, the yarn’s estimated strength was found to be highly influenced by the fiber fragmentation phenomenon.

Influence of humidity, temperature, and annealing on microstructure and tensile properties of electrospun polyacrylonitrile nanofibers

This study investigates the microstructure and mechanical properties of electrospun nanofibers from polyacrylonitrile (PAN)‐dimethylformamide (DMF) solution at different relative humidity (RH) in the range from 14% to 60% and two different temperatures (20°C and 40°C). Nanofibers produced at low RH (22% or less at 20°C) exhibit relatively smooth surface and solid core, whereas at higher RH (30% or higher at 20°C) rough surface and porous core are observed. The resulting morphology is explained by means of H2O/DMF/PAN ternary phase diagram. At higher RH, the water diffusion into polymer‐solution jet brings thermodynamic instability into the system leading to separation of polymer‐rich phase and polymer‐lean phase, where the later contributes to porosity. Higher process temperature (40°C) yields larger miscibility area in the ternary phase diagram leading to formation of porous structure at relatively higher RH (40%). Tensile strength of nanofibrous yarns is found to vary from 80 MPa to 130 MPa depending on the processing temperature and RH. The amount of porosity is found to affect the tensile properties of nanofibers most significantly, although diameter and crystallinity play important role. Annealing is found to alleviate surface roughness and porosity and increase crystallinity. Tensile strength of nanofibrous yarns is found to improve by up to 25% after annealing. POLYM. ENG. SCI., 58:998–1009, 2018. © 2017 Society of Plastics Engineers

Study on the dynamics of chitosan/cotton fiber in an airflow around two rotating cylinders

To predict chitosan/cotton yarn properties in ring spinning, a particle-level simulation method has been used to simulate the dynamics of the fibers with different initial positions in three-dimensional airflow around counter-rotating cylinders. The results show that the fibers near the cylinder end-face can leave two cylinders’ nip and move around the top cylinder, thus form fly waste. It is good to entangle other fibers as this gives the fiber greater bending energy. Compared with cotton fiber, the axial-direction deflections of the tail-ends of chitosan fibers near the cylinder center are much greater, while their bending energies are much lower, thus forming a wide triangle zone and reduced fiber–fiber cohesion force and yarn strength. To demonstrate the simulation results, a series of spinning experiments are completed, which tally with the predictions.

A Grey Fuzzy Logic Approach for Cotton Fibre Selection

It is a well known fact that the quality of ring spun yarn predominantly depends on various physical properties of cotton fibre. Any variation in these fibre properties may affect the strength and unevenness of the final yarn. Thus, so as to achieve the desired yarn quality and characteristics, it becomes imperative for the spinning industry personnel to identify the most suitable cotton fibre from a set of feasible alternatives in presence of several conflicting properties/attributes. This cotton fibre selection process can be modelled as a Multi-Criteria Decision Making (MCDM) problem. In this paper, a grey fuzzy logic-based approach is proposed for selection of the most apposite cotton fibre from 17 alternatives evaluated based on six important fibre properties. It is observed that the preference order of the top-ranked cotton fibres derived using the grey fuzzy logic approach closely matches with that attained by the past researchers which proves the application potentiality of this method in solving varying MCDM problems in textile industries.

Study of Mechanical Properties of Wool Type Fabrics using ANCOVA Regression Model

The work has achieved a study on the variation of tensile strength for the four groups of wool fabric type, depending on the fiber composition, the tensile strength of the warp yarns and the weft yarns technological density using ANCOVA regression model. ANCOVA checks the correlation between a dependent variable and the covariate independent variables and removes the variability from the dependent variable that can be accounted for by the covariates. Analysis of covariance models combines analysis of variance with regression analysis techniques. Regarding design, ANCOVA models explain the dependent variable by combining categorical (qualitative) independent variables with continuous (quantitative) variables. There are special extensions to ANCOVA calculations to estimate parameters for both categorical and continuous variables. However ANCOVA models can also be calculated using multiple regression analysis using a design matrix with a mix of dummy-coded qualitative and quantitative variables.

Increasing the Strength of Single Filaments and Yarns of a Paraaramid Fiber by Their Processing with an Aqueous Suspension of Carbon Nanoparticles

The paper presents the results of increasing the strength and modulus of single filaments and yarns of a paraaramid fiber by their processing with an aqueous suspension of carbon nanotubes in the production process