The effects of intermingling process parameters and number of filaments on intermingled yarn properties

The aim of this study is to evaluate many parameters in intermingling process and to determine the effects of these parameters on yarn properties statistically. For this purpose, POY (partially oriented polyester yarn) filaments, which have 283?dtex linear density and four different filament numbers (34, 47, 68, 100) in cross-section, were used as raw material. Samples were produced at speeds of 150, 300, 450?m/min and pressures of 3, 5, 6?bar, respectively. Intermingled yarn’s strength, elongation, and the number of nips were tested and these features were evaluated as response (dependent) variables. Number of filaments in cross-section, intermingling speed, and intermingling pressure were taken as independent variables. General factorial design was applied by using Design Expert 6.0.1 and SPSS 15.0 software package, and therefore, the effects of selected independent variables on response variables were evaluated statistically. Results showed that the intermingling pressure and number of filaments have statistically significant effects on all the response variables. Moreover, it is observed that there is an interaction between pressure and the number of filaments. The intermingling speed on the other hand has no statistically significant effect.     

基于分数阶模型的纱线蠕变性能模拟与预测

针对现有纱线拉伸力学模型描述不准确问题,以分数阶微积分模型对纱线拉伸行为进行分析。首先,引入分数阶微积分理论改进的黏壶模型建立了分数阶纱线蠕变模型,使用XL-2型纱线强伸度仪对不同线密度及不同张力纱线进行蠕变实验,获得纱线蠕变的全过程曲线。通过对不同线密度下的试验曲线进行回归分析得到了模型参数以及蠕变模型参数与施加张力大小的变化关系。最后,利用不同模型对不同张力的纱线蠕变曲线进行拟合和预测。结果表明：分数阶纱线蠕变模型,相比于三元件模型、整数阶模型和Burgers模型,具有结构简单、参数少的特点,并且对纱线蠕变的拟合和预测也具备较高的精度。     

An approach to predict the tensile strength of a two-ply yarn from single filament yarn

It is considered that the strength of the ply yarn consisting of continuous filaments mainly depends on the properties of the single yarn and the cohesion forces among the single yarns, thus a mathematical model with relatively few parameters under given assumptions is established to predict the tensile strength of a two-ply yarn from single filament yarn. Relative relationships of the tensile force part and the interaction part are developed, respectively. The single yarn is tested to obtain fundamental data e.g. yarn strength and breaking elongation. After two strands of filament yarns are twisted into the ply yarns under different twist levels, the tensile strength, breaking elongation and structure parameters are measured or calculated for verifying the model later. Finally, the results show good agreement with the experimental values, and this model can be used to predict the performance of the finished strand yarns in actual productions.     

快时尚针织面料用混纺纱的设计与分析

根据目前快时尚服装面料的用纱需求,通过测试分析黏胶纤维、腈纶的物理力学性能,选取0.10、0.13和0.17 tex 3种不同线密度的纤维,与锦纶和PBT长丝进行配伍混纺,在相同的纺纱工艺条件下,设计试纺6种相同规格的混纺包芯纱,测试分析最终成纱的强伸度、毛羽指数和条干均匀度.结果表明:不同线密度的黏胶纤维、腈纶与锦纶...     

Using artificial neural networks with graphical user interface to predict the strength of carded cotton yarns

Artificial neural networks (ANNs) are used in prediction fields. Yarn strength is one of the most important properties, because it reflects the quality of the yarn. The prediction process of yarn strength is very important from the technology side because many of generated forces in the spun yarns could be given by yarn strength. Data were collected from the United Commercial Industrial Company, Damascus, Syria. Then, artificial neural network algorithm was architected. Several neural networks were architected one of these has been chosen, which contained acceptable network error rate. To deal easily with ANN, a simple graphical user interface has been created. This ANN has been tested on a new sample. Results were compared with the actual results as well as the relationship of Solovev which is allocated to predict the strength cotton yarn. ANN has given more acceptable results than Solovev’s relationship.     

Effect of polyester and elastane linear density on the physical and mechanical properties of dual-core-spun cotton yarns

ABSTRACT

The use of single-core elastic spun cotton yarns is well established in textiles and denim industry but interest in the use of dual-core-spun yarns has started to grow only recently. The aim of this study was to investigate the effect of polyester and elastane linear density on the physical and mechanical properties of dual-core-spun cotton yarns. Yarn samples were prepared on industrial-scale spinning machines using cotton as the sheath fibers and two different linear densities of polyester and three different linear densities of elastane filaments in the core. Statistical analysis of the results revealed that yarn tenacity, elongation, uniformity, and hairiness are significantly affected by the linear densities of both the polyester and elastane filaments in the core, with statistically significant interaction between them. Yarn imperfections (IPI), however, are affected mainly by the polyester denier, while the elastane linear density did not show statistically significant effect on the IPI. Regression equations for different yarn properties were also developed which showed fairly high values of coefficient of determination (R-sq).     

基于神经网络的精纺毛纱性能预测模型比较

为比较BP与RBF神经网络对精纺毛纱性能的预测能力,采集前纺与后纺的工艺参数作为输入节点,表征精纺毛纱性能的条干不匀率与断裂强力分别作为输出节点,采用软件计算工具中的反向传播(BP)神经网络、径向基(RBF)神经网络分别建立细纱条干不匀率与断裂强力的预测模型,从统计学角度反映2种模型的预测性能。实验结果表明,在输入样本数较大、输入维数较高、精度要求相同的情况下,RBF神经网络模型的训练速度明显快于BP神经网络模型,但BP神经网络模型的预测性能略优于RBF函数神经网络模型,特别是遇到异常样本时,BP神经网络模型表现出更强的容错能力。     

喷气涡流纺工艺对粘胶/涤纶包芯纱性能的影响

为获得更高强力的喷气涡流纺纱线,通过引入涤纶长丝制备喷气涡流纺粘胶/涤纶包芯纱。采用统计分析等方法研究了芯丝线密度、纺纱速度对喷气涡流纺粘胶/涤纶包芯纱强伸性、条干不匀和毛羽的影响规律,同时对比分析了不同纺纱条件下包芯纱的结构外观。研究结果表明：芯丝线密度、纺纱速度对喷气涡流纺粘胶/涤纶包芯纱各性能响应值有不同程度的影响;纺纱速度过高或过低均不利于包芯纱成纱的强伸性提高和条干均匀性改善,纺纱速度的增加会使毛羽H值增大;在一定范围内,增加芯丝线密度有利于包芯纱强伸性的提高,随芯丝线密度的增加,包芯纱毛羽H值减小;此外,选用较大的芯丝线密度和较高的纺纱速度时,纺制的包芯纱芯丝外露现象越明显。     

Dynamic analysis of spinning triangle geometry part 2: spinning triangle geometry and yarn quality

This paper examines empirical relationships between the geometrical parameters of the spinning triangle and the quality parameters of ring spun yarns. For this purpose, controlled variations in the geometry of the spinning triangle were induced using two existing modifications in the ring spinning process and by varying the yarn twist level. The geometrical parameters of the spinning triangle were measured using the clear rubber roller combined with digital image processing techniques as described in the first part of this study. The yarn quality parameters measured included yarn hairiness, strength, elongation and evenness. Yarn hairiness showed more noticeable sensitivity towards the physical shape of the spinning triangle than yarn tenacity, while yarn evenness and elongation were not significantly influenced by changes in spinning triangle geometry.     

绢丝/锦纶长丝sirofil复合纱成纱性能

 以锦纶低弹丝和绢粗纱为原料,纺制不同捻度、不同喂入间距的绢丝/锦纶长丝sirofil复合纱,测试了复合纱的强伸性能、条干不匀和毛羽。通过对实验结果进行方差分析发现,在实验范围内,复合纱成纱强度和断裂伸长率均随纺纱捻度的增加而增加,但纺纱两组分喂入间距对其影响不大;成纱捻度和两组分喂入间距对成纱的条干不匀CV值影响不显著;复合纱的毛羽指数随成纱捻度及两组分在前罗拉处喂入间距的增加均呈现下降趋势。由此得到实验范围内绢丝/锦纶长丝sirofil复合纱的优化纺纱工艺参数:捻度850捻/m,前罗拉喂入间距18 mm。     

An investigation on yarn engineering using artificial neural networks

Abstract

Engineering of spun yarns having specific tensile, evenness and hairiness characteristics is a long-cherished dream of spinning technologists. Selection of suitable raw materials at minimum cost and optimisation of process parameters are the two major tasks to be achieved to manufacture engineered yarn. Advent of high-speed fibre-testing machines and development of powerful modelling tools such as artificial neural network (ANN) have provided a great impetus in the yarn engineering research. This article demonstrates the feasibility of yarn engineering by developing a yarn-to-fibre ‘reverse’ model, using ANN. This approach is entirely different from the prevailing forward models, which predict the properties of final yarn using the fibre properties as inputs. The cost minimisation of cotton fibre mix was ensured by using the classical linear programming approach in combination with ANN. The engineered yarns demonstrated good agreement with the target yarn properties.     

变形纱条干均匀度与变形工艺参数的关系

由于条干均匀度是评价纱线外观特性的重要指标,与短纤维纱不同,变形纱线的表观条干均匀度和质量条干均匀度不相关。为最终达到空气变形纱线及其多重变形纱线结构和性能设计的目标,对长丝原料及几个关键变形工艺参数进行了初步的单因子试验。结果显示,异收缩空气变形纱的条干均匀度可以通过选择单、复丝线密度,空气变形加工和异收缩变形加工工艺参数的方法加以有效控制。空气变形加工工艺参数中的超喂率和喂入方式,异收缩变形加工工艺参数中的异收缩率、平均收缩率对成纱的条干CV值有显著影响。     

Effect of elastane linear density and draft ratio on the physical and mechanical properties of core-spun cotton yarns

The aim of this study was to investigate the effect of elastane linear density and draft ratio on the physical and mechanical properties of core-spun yarns. Twenty yarn samples were prepared on industrial scale in a spinning mill with two different yarn linear densities, each with different two elastane deniers and five draft ratios. It was found that core-spun yarn’s tenacity, elongation and hairiness are affected not only by the overall yarn linear density but also by the elastane linear density and the draft ratio. However, the effect of elastane linear density and draft ratio was not found to be statistically significant on the yarn mass variations and total imperfections, which are only affected by the overall yarn liner density. A statistically significant interaction for yarn elongation at break was found between the yarn liner density and the elastane linear density concluding that elastane linear density used in the core must be compatible with the overall yarn liner density for attaining the best yarn elongation.     

玄武岩纤维机织针织复合结构增强复合材料的拉伸性能

根据新型机织针织复合织物的结构特点,分别选用不同线密度的高强高模玄武岩纤维作为经纱、纬纱和针织纱编织织物,以其作为增强体,采用VARTM工艺制作玄武岩纤维/乙烯复合材料.为提供这种新型织物增强复合材料的应用依据,测试了复合材料的横向、纵向和斜向拉伸性能,并对各个方向的拉伸应力与应变特征曲线及其拉伸断裂形态进行分析,对比...     

芳砜纶/芳纶1313混纺纱性能研究

用芳砜纶与不同细度的国产芳纶1313纤维混纺开发消防服用机织面料用纱.实验结果表明:随着细度较小的芳纶1313纤维比例的增加,混纺纱条干CV值有一定的波动,成纱强度并没有随着芳纶1313纤维含量的增加而增高.混纺比例对成纱的断裂伸长影响不明显,芳砜纶/芳纶1313混纺纱的毛羽随着芳纶1313纤维含量的增加而增多.     

Prediction of yarn crimp in PES multifilament woven barrier fabrics using artificial neural network

This research was aimed to develop artificial neural network (ANN) models to predict yarn crimp in woven barrier fabrics. For ANN training, 52 polyester (PES) multifilament barrier fabrics were produced by varying weft yarn and filament fineness, yarn type, weft density, weave type, and loom parameters. The supervised training of neural network was performed using Matlab® ANN toolbox function ‘trainbr’ which is the incorporation of Levenberg-Marquardt (LM) optimization and automated Bayesian regularization into backpropagation. From modeling outcomes, it was observed that both warp and weft yarn crimp models have generalized well with excellent coefficient of determination and trivial mean absolute error when tested on novel data. Moreover, input rank analysis of optimized network provided important information about model stability with respect to input variables, and trend analysis elucidated the input-crimp behavior using different input levels.     

长丝喂入位置对赛络纺包芯纱结构与性能影响

针对赛络纺包芯纱纺制过程中,长丝不同喂入位置对纱线结构和性能的影响,分别纺制了涤纶长丝在左侧粗纱须条中心、两粗纱须条中间、右侧粗纱须条中心3种结构的短纤/长丝赛络纺包芯纱。对比分析了纱线截面、成纱质量、耐磨性能、拉伸断裂过程和纱线退捻特征。结果表明:3种包芯纱中涤纶长丝均在纱线中心附近,无明显漏丝,条干均匀,毛羽较少;左侧粗纱须条中心喂入纱线拉伸断裂曲线有多峰特征,两粗纱中间喂入纱线拉伸断裂曲线有密集波动特征;右侧粗纱须条中心喂入纱线初始弹性模量最高,拉伸断裂特征为阶梯性断裂,退捻最困难,且在退捻过程中部分纱段被反向加捻,纱线结构最稳定,耐磨性好,纱线强力最高。     

Characterization of fabric properties knitted from multifilament polyester textured yarns with various number of filaments

The purpose of this study is to investigate the physical and mechanical properties of fabrics knitted from textured polyester multifilament yarns with various numbers of filaments in the yarn cross-section. In this regard, some of the characteristics of yarns and fabrics, knitted from the mentioned yarns, were measured and analysed. Analysis of results showed that increasing the number of filaments in the yarn cross-section leads to a decrease in yarn’s diameter and abrasion resistance. Moreover, examining the properties of the weft-knitted fabrics revealed that increasing the number of filaments causes a rising trend in the compressibility and bursting strength of fabric. On the contrary, the thickness, air permeability and abrasion resistance decreases due to a growth in the number of filaments. A decline in the strength and elongation of yarns and fabrics produced from them is also another result of increasing the number of filaments in the yarn cross section.     

基于对抗神经网络和神经网络模型的筒子纱抓取方法

为提高筒子纱抓取和上纱过程的自动化和柔性化程度,应用单目视觉系统引导机器人完成上纱过程。采用工业相机获取单个筒子纱不同形态的数据信息,应用GAN(生成式对抗神经网络)对筒子纱数据集扩充,提高筒子纱数据集多样性。将所得的数据集加载到Faster R-CNN(更快速区域卷积神经网络)模型里进行训练,应用训练好的神经网络识别和定位筒子纱,引导机器人完成上纱任务。应用搭建的单目视觉系统实验平台对结果进行测试,结果表明,经过标定后的视觉系统可以完成多个筒子纱的抓取任务,以满足筒子纱上纱过程的自动化和柔性化要求。     

转杯复合纱的强伸性能

从理论和实验两方面对3种不同结构的棉/氨转杯复合纱的强伸性能进行了分析和比较。实验结果和理论分析均表明,转杯复合纱的强伸性能不仅受其组分拉伸性能的影响,还受到成纱方式的影响;包芯纱具有较高的断裂强力,其次是平行纱,而包缠纱的最低;对于断裂伸长而言,包缠纱最大,其次为包芯纱,平行纱最小。