涤纶机织拉毛产品的开发

通过比较针织拉毛产品和机织拉毛产品的工艺流程,讨论了两种织物的特点,叙述了涤纶机织拉毛产品的开发思路,提出了涤纶拉毛织物加工过程中的主要难点和解决这些难点的基本方法.     

铜氨纤维机织面料的生产

介绍了纯铜氨纤维机织物的浆纱、织造、前处理、染色、印花,以及后整理的加工技术和要点。铜氨纤维织物织造时应采用合理的浆纱工艺和边组织结构;前处理采用茶皂素卷装温堆、高温短蒸工艺;染色和后整理加工需严格筛选染料和柔软剂;每一加工工序均采用卷装方式,可获得手感柔软、悬垂性好、色泽饱满艳丽、色牢度佳的纯铜氨纤维机织高档服装面料。     

细旦丙纶丝机织面料的开发与研究

以细旦丙纶丝为原料，利用其良好的芯吸效应，开发新型机织舒适性面料，并就其中桑丙交织物与全真丝织物的主要性能进行了对比分析。     

用国产传统设备开发莱卡纬弹机织面料

介绍了在国产环锭细纱机和有梭织机上开发莱卡纬弹织物的技术关键与措施。     

Outlast空调纤维机织面料的染色

采用活性艳红KD-8B对Outlast空调纤维机织面料进行一浴法染色,探讨元明粉和碳酸钠用量、固色温度和固色时间对上染率和K/S值的影响。优化的染色工艺为:活性艳红KD-8B 3%(omf),元明粉40%(omf),平平加O 0.5%(omf),碳酸钠25%(omf),浴比1∶20,染色温度70℃,染色时间50 min,固色温度80℃,固色时间70 min。结果显示,Outlast空调纤维面料的耐洗色牢度、耐汗渍色牢度和耐摩擦色牢度达到4级以上,织物的经纬向强力均有所下降,能够满足服用要求。     

多层机织面料的开发

以双层平纹织物、三层平纹织物和不同组织、密度的双层织物为例,在分析多层织物常用组织结构及其接结原理的基础上,以双层影纹织物、凸条绉类织物、夹芯装饰双层织物等多个品种开发实例为论证,并结合原料、工艺、色彩、花纹等生产要素开发了风格用途各异的织物。通过充分利用多层结构的框架,结合各种生产要素,可开发出风格多样、新颖别致的机织面料花色品种。     

浅议机织面料生产中织物CAD技术的应用

加入 WTO以后的中国纺织企业面临着一个前所未有的机遇 ,也面临着更大的挑战。在信息化技术、数字化技术驱使下 ,各类纺织面料的计算机辅助设计系统和计算机辅助制造系统的发展突飞猛进。在机织物的设计与制造领域有越来越多的高等院校或科研院所从事织物 CAD/ CAM技术的研究与开发 ,也有越来越多的织造企业应用织物 CAD技术从事产品的设计与生产。我国纺织企业的信息化与国外同类企业的差距是相当大的 ,用信息化来提高企业的竞争力 ,用信息化来提高企业的效益成为共识。1　应用织物 CAD技术的效果织物 CAD是利用计算机辅助进行织物…     

吸湿发热机织面料的设计与性能

为开发一种具有优良的吸湿发热性能的机织面料,以改性聚丙烯腈纤维为原料,将该纤维与棉混纺作为外包纱,氨纶长丝为芯纱,制备了具有吸湿发热性能的包芯纱线。将试纺出的包芯纱织成平纹、2/1右斜纹、双层组织、蜂巢组织4种不同组织结构的面料,对所得面料进行透气性、透湿性、保暖性和吸湿发热性能测试,并分析了纤维配比及组织结构对织物吸湿发热性能的影响。结果表明：织造的16块面料均有不同程度的发热效果,随着改性聚丙烯腈纤维含量的增加,面料的发热效果变好。纤维含量相同时,蜂巢组织面料的发热效果较好。综合看来,改性聚丙烯腈纤维/棉80/20蜂巢组织面料的发热效果最好。     

汽车装饰面料的开发

汽车装饰面料的开发冰川集团武汉毛纺织厂余建忠一、概况随着九十年代经济的腾飞，传统产业用纺织的消费大大增加。纺织材料及加工方法有着重要的突破，在目前和令后相当一个时期内，纺织品的运用领域特别是在产业用布范围将有更大发展。随着国家产业结构的调整和人民生活...     

花式纱线机织产品的开发

花式线改变了纱线的结构,形成独特的产品风格,增加了织物的质感,具有鲜明的外观效应和丰富的色彩。花式纱线广泛应用于服装、装饰品及工业用品,因此花式纱线及其产品的开发有很大的现实意义。通过试织小样,阐述了其开发灵感来源、工艺参数以及开发产品时应注意的问题。     

Bias tensile strength behaviors of woven fabric: theoretical and experimental

This paper mainly focuses on the uniaxial bias extension behaviors of quartz plain weave fabrics. A series of bias extension tests are carried out on quartz plain weave fabrics with different widths to evaluate the strength behaviors. A portable microscope is adopted to capture and record informative resources on the sample surface. The tensile tenacity, load–displacement curves, width change history as well as Poisson’s ratio history of different sample widths are compared and analyzed. Also, a theoretical model is proposed to predict the critical width which is the maximum width without yarn failure in bias extension test. Theoretical prediction shows reasonable agreement with experiments. Tensile tests operated on three directions (warp, weft, and bias) reveal the significant mechanical difference is primarily caused by different failure mechanisms.     

Tensile characteristics and stress relaxation analysis of woven fabrics in terms of fabric direction

Abstract

Woven fabrics in various end uses are subjected to tensile loads in different directions, so investigation of the effect of fabric direction on the tensile behaviour and the stress relaxation performance of fabrics is important and needs to be considered. In this study, the tensile and stress relaxation properties of woven fabrics with five various weave structures have been analysed, in different directions. It was concluded that the tensile properties of fabrics such as Young’s modulus, breaking load and elongation and also the work of rupture were significantly affected by the fabric direction and weave structure. Moreover, it was determined that the fabric tensile stress relaxation (%) was considerably affected by the applied strain level, fabric direction and weave structure in the confidence range of 95% and it might well be expressed as a Gaussian function of sample direction.     

New computer geometric modeling approach with filament assembly model for woven fabric structures

This paper presents a new computer geometric modeling approach for three-dimensional woven fabric structures. Pierce’s geometry of the weave fabric of yarn from an arc abscissa (Peirce’s) model is presented. Then, new algorithms with a filament assembly model for a single yarn composed of many filaments by twisting along the crimp shape in the warp/weft is developed. The concept of a virtual location is used to simulate the fiber distributions in the yarn cross-section. Each cross-section is rotated along the yarn length by a pre-determined amount to allow for the yarn twist. The curve of each filament in each two successive cross-sections is approximated by NURBS and then each curve is created by sweeping a closed curve along the centerline of the yarn path. The method described is demonstrated by the CAD model of woven fabrics with plain and twill weaves. The simulated woven fabrics using this approach can demonstrate a wider variety and improved visual simulations of real woven fabric and can then be further generalized for different and more complicated fabrics. The method is necessary as an input to many computational models, such as modeling the mechanical properties or the heat transfer of fabrics or composite parts.     

应用频谱图的机织物纹理分析

利用傅里叶变换技术将空间域的纹理图像变换到频率域中,采用频谱图对机织物纹理信息进行分析。通过傅里叶变换技术得到机织物图像的频谱图,利用阈值分割曲线选取合适的阈值对频谱图进行分割,然后用邻域最大值的方法找到织物纹理的特征坐标点。根据坐标点与实际频率的关系计算机织物纹理的频率范围。实验结果表明,随着密度的增大织物纹理的频率增加,斜纹和缎纹的频率范围比平纹织物的大,常见机织物的纹理为中低频。     

An investigation into the effect of fabric structure on the compressional properties of woven fabrics

Lateral compression is one of the most important mechanical aspects of fabrics, which reflects their handle. Fabric compressional features depend on the compressional characteristics of constituent yarns and the fabric structure. In order to consider the effect of fabric structural parameters on its compressional properties, woven fabrics with five different weave patterns (plain, hopsack 2/2, twill 2/2, twill 3/1, warp rib 2/2) were produced with three different nominal weft densities (12, 15, 18 cm^?1). The compressional properties of produced fabrics were evaluated at different pressure values using a conventional fabric thickness tester. It was observed that increasing the weft density leads to decrease in the dissipated compression energy as well as the compressibility of the fabric, while the thickness recovery of the fabric increases. Moreover, the plain woven fabric exhibited the lowest dissipated compression energy and compressibility, while the highest thickness recovery. Besides, at the low pressure level, the fabrics with the lower weft densities demonstrate the higher thickness. By increase in the pressure level, the fabric thickness decreases by decreasing the weft density.     

机织物密度对字典学习纹理表征的影响

为探讨纺织品表观质量的客观、智能评定方法,使用不同密度的机织物图像,采用子窗口样本获取方式作为学习样本,以离散余弦字典作为初始学习字典,选择基于最小二乘的字典学习算法求解用于表征织物纹理图像的字典,再通过字典元素的线性组合对织物图像进行重构。以均方误差为指标,首先讨论织物图像灰度值分布对字典学习算法重构误差的影响,然后对图像灰度值进行标准化处理,在此基础上探讨织物经纬密度对重构图像误差的影响。实验结果发现,当字典个数等于9时,织物密度在150 ~ 360根/10 cm之间,随着织物密度的增加,平纹重构图像的均方误差先变大,以后不再增加,而斜纹重构图像的均方误差增大。     

Automatic recognition for striped woven fabric pattern

Three basic weaves and fancy woven fabrics can be recognized usually. But the recognition of the striped woven fabric pattern is a challenging work, because it contains two or more types of woven fabrics. A robust striped woven fabric pattern recognition method is presented in this paper, through which the striped woven fabric pattern could be segmented into three basic weaves and fancy woven fabrics based on Gray-Level Co-occurrence Matrix (GLCM). Firstly, scanning window is selected automatically by analyzing the characteristics of the striped woven fabric, and features are extracted in this window based on GLCM. Then we compute the correlation coefficient between the adjacent windows and complete the segmentation of striped woven fabric. At last, the segmented woven fabric patterns are recognized based on the approach of gradient histogram. According to the tests, we concluded that this method can segment and recognize the striped woven fabric patterns successfully, which can overcome the effects of thickness and color of yarns changing, and uneven illumination.     

A novel hybrid genetic and imperialist competitive algorithm for structure extraction of woven fabric images

The woven fabric is a flexible object and to specify its parameters, applying inflexible and ordinary methods of image processing ever have considerable errors. In this regards, proposing an adaptable method to fabric image properties is concentrated to detect the yarns position. In this research, a flexible algorithm is proposed containing two stages: first, the inexact ranges of fabric parameters are determined by preprocessing colored fabric images using wavelet transform and clustering methods. Then, the hybrid genetic and imperialist competitive algorithm is applied to optimize the obtained ranges and detect the yarns position. To achieve better results, the parameters of the hybrid ICA–GA are calibrated using the Taguchi method. Results indicate that in this new method, the error value of detecting structural fabric parameters has considerably decreased to 5% as compared with common gray-scale projection method. The proposed method is capable of detecting the exact yarns position in colored fabric images with uneven color intensity and low-density weave with mean precision value of 96.2%. In the fabric images with high density weaves, the mean precision value is more than 94.72%.