Bingang Xu

Effects of Geometry of Ring Spinning Triangle on Yarn Torque Part I: Analysis of Fiber Tension Distribution

The geometry of the spinning triangle influences the distribution of fiber tension in the spinning triangle and fiber tensile stresses within the yarn and, thus, affects the component of yarn torque due to these stresses. In this study, a modified energy approach was adopted to study the distribution of fiber tension in the staple spinning triangle. The spinning triangle had an asymmetric geometry, unlike that studied by other researchers. A shape parameter was introduced in the analysis. The principle of minimum potential energy was applied to analyze three cases, that is, spinning triangle with uniformly distributed fibers, spinning triangle with fiber substrands and spinning triangle with buckled fibers. The effects of shape of spinning triangle on the fiber tension distribution at the spinning triangle were investigated. The results showed that the tension distribution of fibers at the spinning triangle became more uniform with the increase of the symmetry of the spinning triangle. In addition, as yarn twist increased, more tension of outer fibers was created and more compressive force developed on the central fibers in the spinning triangle. Compared with fiber tension distribution at the spinning triangle without fiber buckling, the fiber tensions distributed at the spinning triangle exhibited different shapes and had lower values with fiber buckling.

Theoretical Study of a Spinning Triangle with Its Application in a Modified Ring Spinning System

The spinning triangle is a critical area in the spinning process of staple yarns. Its geometry influences the distribution of fiber tension in the spinning triangle and the properties of spun yarns. In earlier theoretical models, the spinning tension of the yarn acting on the convergence point is assumed to be perpendicular to the nip line of front rollers. This assumption is reasonable in the study of the conventional ring spinning triangle, but may not be appropriate for modified ring spinning systems in which the yarn spinning tension has an obvious angle with the vertical axis perpendicular to the nip line. Thus in this paper a new theoretical model is proposed by considering the inclination angle of the spinning tension. Based on the principle of minimum potential energy, the theoretical model quantitatively describes the fiber tension distribution and its relationships with the spinning parameters, shape of the spinning triangle and the inclination angle of yarn spinning tension. As an application of the proposed method, spinning triangles of a modified ring spinning system were investigated under various spinning parameters. The fiber tension distributions in the spinning triangle both with and without fiber buckling were numerically simulated and the results were compared with those from our earlier model. In addition, the properties of spun yarns produced by the modified system were evaluated and analyzed.The spinning triangle is a critical area in the spinning process of staple yarns. Its geometry influences the distribution of fiber tension in the spinning triangle and the properties of spun yarns. In earlier theoretical models, the spinning tension of the yarn acting on the convergence point is assumed to be perpendicular to the nip line of front rollers. This assumption is reasonable in the study of the conventional ring spinning triangle, but may not be appropriate for modified ring spinning systems in which the yarn spinning tension has an obvious angle with the vertical axis perpendicular to the nip line. Thus in this paper a new theoretical model is proposed by considering the inclination angle of the spinning tension. Based on the principle of minimum potential energy, the theoretical model quantitatively describes the fiber tension distribution and its relationships with the spinning parameters, shape of the spinning triangle and the inclination angle of yarn spinning tension. As an application o...

Structure and Properties of Low Twist Short-staple Singles Ring Spun Yarns

Low twist singles ring yarns are desirable for their low residual torque, high bulk and softness, as well as high spinning productivity. However, conventional low twist ring yarns have very low strength and, thus, cannot be used. In this paper, a modification technique is described for producing singles ring yarns with a low twist and a relatively high strength simultaneously. A false twister was used to increase fiber migration and entanglement in the spinning triangle, leading to a reinforcement of yarn strength. The yarn cross sectional structure, fiber path and yarn surface were examined and yarn tensile and torsional properties were evaluated. The results revealed that the modified yarn had a structure and properties different from the conventional ring spun yarns. The fiber path modification was kept in the resultant yarn.

Effects of Geometry of Ring Spinning Triangle on Yarn Torque: Part II: Distribution of Fiber Tension within a Yarn and Its Effects on Yarn Residual Torque

This paper presents a theoretical analysis of fiber tension distribution within a ring spun yarn without relaxation. Yarn residual torque is determined on the basis of the translation of fiber tension at the spinning triangle, as presented in the first part of this series of papers, into the fiber tension within the yarn. The results from numerical simulations indicate that, with fiber buckling, the yarn exhibits a lower average fiber tension and, thus, a much reduced yarn residual torque than that without fiber buckling. Comparison with experiments confirmed that fiber buckling exists in ring yarns while the assumption of no fiber buckling is not realistic. Generally, a low yarn twist results in low average fiber tension in the yarn and, thus, a reduced yarn residual torque. A symmetrical spinning triangle leads to a slightly higher yarn residual torque than a right-angle spinning triangle when the yarn counts and twists are identical and fiber buckling occurs.

An Artificial Neural Network Model for the Prediction of Spirality of Fully Relaxed Single Jersey Fabrics

The present paper proposes an artificial neural network model for the prediction of the degree of spirality of single jersey fabrics made from 100 % cotton conventional and modified ring spun yarns. The factors investigated were the yarn residual torque as the measured twist liveliness, yarn type, yarn linear density, fabric tightness factor, the number of feeders, rotational direction and gauge of the knitting machine and dyeing method. The artificial neural network model was compared with a multiple regression model, demonstrating that the neural network model produced superior results to predict the degree of fabric spirality after three washing and drying cycles. The relative importance of the investigated factors influencing the spirality of the fabric was also investigated.

Techniques for Torque Modification of Singles Ring Spun Yarns

This article reports on a systematic study of various spinning techniques to produce torque-free singles ring spun yarns on a modified ring frame. The modification units, including optional fiber separation devices and a false twist device, were incorporated into the conventional ring spinning frame so that the balanced or reduced yarn residual torque could be achieved in one step. Three modification systems were proposed and two of them were investigated on a ring frame to produce pure cotton singles yarns. The spirality of the resultant single jersey knit fabrics was greatly reduced. Properties and performance characteristics of control and modified yarns, as well as their resultant fabrics, were evaluated, including yarn tensile properties, hairiness, evenness, snarling, burst strength, air permeability, handle, and pill resistances.This article reports on a systematic study of various spinning techniques to produce torque-free singles ring spun yarns on a modified ring frame. The modification units, including optional fiber separation devices and a false twist device, were incorporated into the conventional ring spinning frame so that the balanced or reduced yarn residual torque could be achieved in one step. Three modification systems were proposed and two of them were investigated on a ring frame to produce pure cotton singles yarns. The spirality of the resultant single jersey knit fabrics was greatly reduced. Properties and performance characteristics of control and modified yarns, as well as their resultant fabrics, were evaluated, including yarn tensile properties, hairiness, evenness, snarling, burst strength, air permeability, handle, and pill resistances.

Transfer-Printed PEDOT:PSS Electrodes Using Mild Acids for High Conductivity and Improved Stability with Application to Flexible Organic Solar Cells.

UNLABELLED Highly conductive, flexible, and transparent electrodes (FTEs) of PEDOT PSS films on plastic substrates have been achieved using strong acid treatments. However, it is rare to realize a performance attenuation of PEDOT PSS FTEs on plastic substrates and flexible optoelectronic devices because of strong acid residues in the PEDOT PSS matrix. Herein, we develop a feasible transfer-printing technique using mild acids. Because of a mild and weak property of these acids and less acid residues in PEDOT PSS matrix, the transferred PEDOT PSS FTEs exhibited a significant enhancement in stability, conductivity (3500 S cm(-1)), transparency, and mechanical flexibility on plastic substrates. Flexible organic solar cells with the FTEs also showed a remarkable enhancement in power conversion efficiency and stability in the ambient atmosphere. It is expected that the novel transfer-printing technique for making PEDOT PSS FTEs is also useful in many other types of flexible optoelectronic devices.

Automatic Measurement and Recognition of Yarn Snarls by Digital Image and Signal Processing Methods

In this paper, a computerized method has been proposed for automatic measurement and recognition of yarn wet snarls from an image of snarled yarn samples captured in a water bath. After image acquisition, image conversion and individual snarled sample extraction, the yarn profile function was extracted from the separated binary image. Fast Fourier Transform and Adaptive Orientated Orthogonal Projective Decomposition were then incorporated into a pattern recognition algorithm of yarn snarl features by treating the yarn profile function as a one-dimensional signal. In addition to the number of yarn snarl turns, the method was also accurate and efficient for the detection of yarn snarl height and width, which are unobtainable by the untwisting method. The effects of various factors on the yarn profile function were numerically examined, including distributions of yarn diameter and snarl, and the level of random noise.

Numerical analysis of the mechanical behavior of a ring-spinning triangle using the Finite Element Method

The purpose of this study is to investigate the quantitative relationships between the mechanical performance of a ring-spinning triangle and the spinning parameters by using the Finite Element Method (FEM). The constituent fibers in the ring-spinning triangle are considered as three-dimensional elastic beam elements with tensile, compressive, torsional, and bending capabilities. The accuracy of the proposed FEM model in calculating the fiber tension distribution of the spinning triangle has been validated by comparing it with earlier models and experimental data. Compared with the earlier models, some important theoretical factors ignored previously, including the fiber torsional strain and the frictional contact of fibers with the bottom roller, are considered in the current model. With the input of various spinning parameters, some essential factors of the spinning triangle, including the fiber tension distribution and fiber torsion distribution, are numerically examined and their quantitative relationships are discussed in detail.The purpose of this study is to investigate the quantitative relationships between the mechanical performance of a ring-spinning triangle and the spinning parameters by using the Finite Element Method (FEM). The constituent fibers in the ring-spinning triangle are considered as three-dimensional elastic beam elements with tensile, compressive, torsional, and bending capabilities. The accuracy of the proposed FEM model in calculating the fiber tension distribution of the spinning triangle has been validated by comparing it with earlier models and experimental data. Compared with the earlier models, some important theoretical factors ignored previously, including the fiber torsional strain and the frictional contact of fibers with the bottom roller, are considered in the current model. With the input of various spinning parameters, some essential factors of the spinning triangle, including the fiber tension distribution and fiber torsion distribution, are numerically examined and their quantitative relation...

Intelligent characterization and evaluation of yarn surface appearance using saliency map analysis, wavelet transform and fuzzy ARTMAP neural network

The evaluation of yarn surface appearance is an important routine in assessing yarn quality in textile industry. Traditionally, this evaluation is subjectively carried out by manual inspection, which is much skill-oriented, judgmental and inconsistent. To resolve the drawbacks of the manual method, an integrated intelligent characterization and evaluation model is proposed in this paper for the evaluation of yarn surface appearance. In the proposed model, attention-driven fault detection, wavelet texture analysis and statistical measurement are developed and incorporated to fully extract the characteristic features of yarn surface appearance from images and a fuzzy ARTMAP neural network is employed to classify and grade yarn surface qualities based on the extracted features. Experimental results on a database of 576yarn images show the proposed intelligent evaluation system achieves a satisfactory performance both for the individual yarn category and global yarn database. In addition, a comparative study among the fuzzy ARTMAP, Back-Propagation (BP) neural network, and Support Vector Machine (SVM) shows the superior capacity of the proposed fuzzy ARTMAP in classifying yarn surface qualities of the database.