Flexible strain sensors that mimic the properties of human skin have recently attracted tremendous attention. However, integrating multiple functions of skin into one strain sensor, e.g., stretchability, full-range motion response, and self-healing capability, is still an enormous challenge. Herein, a skin-like strain sensor was presented by the construction of hierarchically structured carbon nanofibers (CNFs), followed by encapsulation of elastic self-healing polyurethane (PU). The hierarchical sensing structure was composed of diversified CNFs with orientations from highly aligned to randomly oriented, and their different fracture mechanisms enabled the resultant strain sensor to successfully integrate key sensing properties including high sensitivity (gauge factor of 90), wide sensing range (∼80% strain), and fast response (52 ms). These properties, combined with high stretchability (870%) and excellent stability (>2000 cycles), allowed the sensor to precisely detect full-range human motions from large joint motions to subtle physiological signals. Moreover, the strain sensor had spontaneous self-healing capability at room temperature with high healing efficiencies of 97.7%, while the healing process could substantially be accelerated by the natural sunlight (24 h → 0.5 h). The healed sensor possessed comparable stretchability, sensing performance, and accurate monitoring ability of subtle body signals with the original sensor. The biomimetic self-healing functionality along with skin-like sensing properties makes it attractive for next-generation wearable electronics.

Developing multifunctional triboelectric nanogenerators (TENGs) with special intelligence is of great significance for next‐generation self‐powered electronic devices. However, the relevant work on the intelligent TENGs, especially those spontaneously responsive to external stimuli, is rarely reported. Herein, an intelligent TENG with thermal‐triggered switchable functionality and high triboelectric outputs is developed by designing a movable triboelectric layer, which is driven by a two‐way shape memory polyurethane. The resultant TENG device can be spontaneously switched on/off in response to the environmental temperature change, i.e., switching on at 0 °C and off at 60 °C. At the “on” state, the developed TENG exhibits excellent triboelectric performance with a maximum output power density of 5.15 W m −2 at a pressure of 30 kPa due to the unique advantages of micro‐/nanofiber triboelectric surfaces. Furthermore, the great potential of the switchable TENG in intelligent wearable electronic applications is demonstrated, which can serve as not only the sensing element for monitoring human movement and physical condition in a cold environment but also the thermal‐driven switch for turning on/off the heating function on demand. The intelligent “on–off” switchable TENG combined with excellent triboelectric performance may provide new opportunities for future self‐powered wearable electronics.

In view of shortcomings of existing wear resistant yarns that could not take into account wear resistance and wearability,based on filament and staple fiber composite spinning technology,double filament wrapped yarn with different twist direction was produced which realized reticular cross binding structure on double twister.By studying twist matching scheme of yarn and double twist,it was determined when twist of spun yarn was 110 twists/10 cm and twist of double twist yarn was 50 twists/10 cm,reticular binding effect of the yarn was the best and indexes of yarn were reached the best.By testing wear resistance and moisture absorption ＆ quick drying of the woven fabric,the results showed that the yarn had excellent wear resistance and moisture absorption ＆ quick drying performance which meet requirements of the national standard. It is considered that the yarn can be used for wear resistant fabrics,moisture absorption ＆ quick drying fabrics and other related products.

织物作为柔性电磁屏蔽材料的基材之一,由于其轻薄、良好的表面贴服性和大量的网格化结构被广泛应用.目前,织物电磁屏蔽材料的制备方法主要有:利用物理或化学方法将导电涂料附着于纱线或织物表面;将金属纤维与常规纤维混纺后进行织造或利用金属丝与普通纱线交织.然而,简单的织物结构不能充分发挥材料的电磁屏蔽性能.对电磁屏蔽纱线和织物结构及其电磁屏蔽性能的研究现状进行了总结和展望,认为电磁屏蔽纺织品结构的创新应用还不完善,电磁屏蔽纺织品结构应多样化,如导电纱线中金属丝可以从顺直状态转变为螺旋状或圆弧状等,织物可以从二维到三维,单层到多层,丰富结构在提升电磁屏蔽性能的同时,也要综合考虑服用性能.

Wearable strain sensors have made great progress in sensing performance, stretchability and durability. However, practical applications of these sensors are still quite challenging because they are incapable of detecting multi-degree-of-freedom strains due to the interference of multidirectional strains. Herein, a high-sensing performance, direction-aware and transparent strain sensor is reported based on antimony-doped tin oxide oriented nanofiber (ATO-ONF) films prepared by electrospinning. The monolayer ATO-ONF strain sensor shows remarkable anisotropic sensing performance, namely GFs of 250 and 1.2 for the nanofiber orientation and its transverse directions, suggesting the realization of the unidirectional sensing capability of the strain sensor, i.e., only responding to strains along the nanofiber direction. In addition, this strain sensor also exhibits high transparency with a light transmittance of ~ 80%, and excellent sensing performance including high sensitivity, high linearity, low hysteresis, good repeatability and durability (> 2000 cycles). Based on these superior sensing properties, the direction-aware biaxial strain sensor is designed by orthogonally stacking ATO-ONF films, by which the predicted magnitude and direction of the tensile strains agree well with those of the actual strains. Furthermore, the multi-degree-of-freedom applications of direction-aware strain sensors in human motion monitoring and human-machine interaction are demonstrated, showing a great application potential in next generation wearable electronics.

"新工科"建设是当前全国高校专业建设的重要方向和内涵建设内容之一.作为传统工科专业的纺织工程专业,如何利用"新工科"专业建设契机打造适应新时代工科人才培养需要的人才培养模式是当前专业建设探索的重点.分析比较目前工科人才培养中"3+1""书院制""卓越工程师""创新班"等人才模式的优势及存在的问题,对纺织工程专业"新工科"人才培养模式进行了探讨,并提出了相关建议.

In order to improve the accuracy and applicability of computer color matching algorithm for color spunyarns, a full-spectrum color matching algorithm was proposed based on the classical Stearns Noechel optical theoretical model, aiming at the problems that it is difficult to minimize error in calculated color difference value and that in matching relative deviation. The sensitivity coefficient of human visual characteristics to reflected light at different wavelengths was determined by exploring human visual characteristics, and it was introduced into the color matching algorithm for weighted calculation to predict the monochrome fiber mixing ratio. The color matching effect was evaluated by predicting the color difference value, the relative deviation value of the ratio and the Euclidean distance. Results show that the color matching algorith with Poisson distribution introduced to the human eye sensitivity coefficient is optimal, with the average prediction color difference value being 0. 29 and all within 1, the ratio of the average relative deviation value being minimal 0. 612, Euclidean distance average being 0. 087 which is relatively small. When using the improved color matching algorithm, the prediction of the color difference value can be achieved through one calculation, leading to a small color difference with higher accuracy. With the improved algorithm, computer assisted color matching for color spunyarns can be primarily achieved.

现在对织物的结构和性能要求越来越高,一方面从原材料如纤维纱线的角度进行研究,另一方面对织物结构的研究也备受关注.三向织物(triaxial woven fabric,TWF)是一种各向异性差异得到改善的织物结构,其各向同性较强,力学性能较高.文章首先介绍了三向织物的结构,其次总结了三向结构织物在力学性能方面的应用进展,接着介绍了三向织物复合材料的性能特点,最后介绍了有限元模拟在分析织物和织物复合材料性能研究中的作用,并提出三向织物在未来的发展趋势.

纺织机械占地面积大、使用成本高,并存在一定的危险性,在高校专业教育中实践教学难以展开.针对这些问题,本文以DSRo-21型数字式小样毛纺粗纱机为研究对象,制作并开发数字化小型粗纱机虚拟仿真模型,分析小型粗纱机主要机构和工作原理,采用Creo 4.0软件建立数字化小型粗纱机的实体模型,并应用DVS 3D虚拟现实软件平台对数字化小型粗纱机模型进行虚拟仿真,同时加入粗纱机整体及主要零部件的装配展示以及主要机构运行的展示功能.结果 表明,将虚拟仿真技术引入到纺织工程专业实践教学中的可行性,解决纺织机械的学习在学校中难以展开的问题,探索纺织工程专业数字化教学新思路.

为探索针织物热舒适性设计的评估和优化新思路,提供一种有效预测针织物热阻和表面温度变化的方法,对织物系统一维热传递进行有限元模拟.基于对织物试样尺寸测量得到的几何结构参数,利用三维建模软件Rhino建立纬编针织物的几何模型,并考虑织物周围静止空气,构成织物系统的三维模型;借助ABAQUS有限元分析软件,根据模拟环境设置载荷及边界条件,求解模拟数值,得到织物系统温度分布云图和热流图.最后将仿真结果和试验结果对比,对数值模拟结果进行验证.结果 表明:织物外表面温度的模拟值与试验热阻值相对误差为2.62％,两者吻合度较高,证明有限元仿真的可行性;相同针织物规格下,羊毛和腈纶针织物热阻相差不大,并且大于棉针织物.

Textile-based electronics characterizing easy integration into textile garments and good wearability have received considerable attentions. However, it is still a huge challenge to integrate multiple functions into single electronic device, especially for those having different even opposite requirements in electrical properties. In this work, an anisotropic electrically conductive composite was prepared by encapsulating conductive knitted fabric (CKF) into polyurethane (PU). Based on anisotropic electrical conductivity, i.e., extremely low and stable resistivity in the coursewise direction and significant variation of resistivity in the walewise direction during tensile strains, the composite could efficiently integrate the electro-heating and strain-sensing functions that required opposite electrical properties. When applied for electro-heating applications in the coursewise direction, the CKF/PU composite exhibited fast thermal response, ultrahigh electric-thermal conversion (140 degrees C at 4 V), and stable electrothermal performance under a large strain (40%) or after long-term use (>1000 stretching cycles). When applied for strain-sensing applications in the walewise direction, the composite showed good sensing performances, including high sensitivity (GF of -8.1 at a 5% strain), low hysteresis, good reproducibility and stability (>1000 cycles), which enabled the device as a wearable sensor to accurately detect human joint movements and subtle motions. Furthermore, the self-healing function was exploited for the CKF/PU electronic device, by which the abnormal sensing property could be fully repaired at human body temperature. This work may shed new light on the future development of high-performance multifunctional wearable electronics with the anisotropic conducting feature.

为更好地了解筒状纬编针织物抵抗拉伸变形的能力,基于对织物试样尺寸测量得到的几何结构参数,借助Rhino 3D建模软件建立了纬编针织物线圈模型和筒状纬编针织物模型;同时利用有限元分析软件ABAQUS在单位线圈和筒状织物2个方面研究了筒状纬编针织物的纵向拉伸性能;对织物拉伸过程进行有限元模拟和实验验证,并对针织物拉伸过程中纱线形变和应力分布进行探讨,将有限元仿真结果和拉伸实验结果进行对比分析.结果表明:筒状针织物纵向拉伸时,发生线圈转移和纱线伸长现象,其形变和应力变化的有限元分析结果描述准确,应力-应变数值计算结果与实验结果的差异在8％以内,证明有限元仿真的可行性.

为降低企业生产成本,通过对生产工艺参数进行调整,提出一种织机效率预测模型.该模型将主成分分析与BP神经网络结合,先用主成分分析法对影响织机效率的众多因素进行预处理,降低原变量的维数,消除原变量之间的相关性.然后再将经过预处理的主成分作为神经网络的输入,这样不仅简化网络结构,还能提高网络稳定性.经过仿真,结果表明,PCA-BP比BP神经网络相关系数高;十万纬经停仿真,PCA-BP比BP神经网络预测误差减小了11.28％;织机效率仿真,PCA-BP比BP神经网络预测误差减小了64.92％.

本文对工程教育认证背景下的纺织科学与工程专业课程考核体系进行研究和分析,并针对性的进行了考核方式改革探索,建立了纺织科学与工程专业课程考核系统.这种新型的纺织科学与工程专业课程考核体系更侧重于过程考核,方式多样化有助于提高学生学习积极性和学习能力,也使得使课程考核方式更加实用.

为推动由中国纺织科学研究院绿色纤维股份有限公司生产的全自主知识产权Lyocell纤维系列产品——希赛尔纤维的优化和开发应用,对希赛尔纤维的基础性能进行测试分析并进行初步的纱线开发.通过力学拉伸和摩擦性能测试、质量比电阻和标准回潮率测试、电镜扫描等手段对希赛尔纤维性能进行表征和分析,接着设计三因素三水平的正交试验纺制纯纺纱,并对各纱线的力学性能、毛羽、条干进行测试和分析,确定希赛尔纤维细纱工序中的最优参数搭配.结果表明:希赛尔纤维性能优异;纺纱最优工艺为后驱牵伸倍数为1.15,捻系数为3.50,隔距块号数为2.50,其纱线质量良好,在理论上希赛尔纤维已经可以与棉、粘胶等其他纤维共同应用于纺织品的织制与使用.

为准确预测纺织厂织布车间的织机效率,提出利用BP神经网络、主成分分析结合BP神经网络(PCA-BP)、遗传算法改进BP神经网络(GA-BP)3种模型预测织机效率,并将GA-BP预测模型与传统BP神经网络和PCA-BP预测模型的预测结果进行对比分析.结果表明:GA-BP对原始数据的拟合度最好,相关系数为0.94687,比BP增加了6.42％,比PCA-BP增加了2.61％;GA-BP、PCA-BP、BP这3种网络十万入纬的经停仿真值与期望值间的平均误差分别为0.3412、0.3031、0.2341,误差百分率分别为8.63％、7.67％、5.92％,不同网络结构下织机效率仿真预测值与期望值间的平均误差分别为3.0109、2.6884、2.1189,误差百分率分别为3.51％、3.13％、2.47％;3种模型的预测准确度顺序由大到小为GA-BP、PCA-BP、BP.

如何加快适应新经济对工科人才培养的要求是近年来传统工科升级改造的主要动力.天津工业大学非织造材料与工程专业经过10余年的建设,已经形成较为完善的专业课程设置和人才培养体系,毕业生受到企业的普遍欢迎,专业建设获得行业的广泛认可.通过分析总结天津工业大学非织造材料与工程专业建设经验,为纺织工程专业“新工科”建设提供示范和借鉴.

This work demonstrated heat- and light-responsive supramolecular networks having high toughness, shape memory and self-healing properties. The supramolecular networks were composed of covalent and transient crosslinks that were formed by crystalline poly(ethylene glycol) (PEG) and poly(e-caprolactone) (PCL) and by 2-ureido-4-pyrimidone (UPy) supramolecular moieties. The resultant supramolecular networks realized exceptional mechanical performance such as tensile stress of 7.2 MPa and toughness of 25.2 MJ m(-3). By utilizing the light-to-heat conversion capability of UPy moieties, the polymer films could be heated up to similar to 63 degrees C under UV light irradiation, which was sufficient to activate the temperature-dependent shape memory and self-healing properties. Consequently, supramolecular polymers were responsive to the heat as well as the light irradiation, and the latter resulted in faster and desirable shape memory effect. Furthermore, the direct heating and the photoeffect heating could enable the self-healing of the damage via dynamic reversibility of UPy units. It is noteworthy that the light-induced healing allowed remote activation, on-demand treatment, faster self-healing (1 min) and higher healing efficiency (86%) in comparison with direct heating. The tough self-healing materials enabled the fabrication of durable strain sensors with high toughness and electrical healing ability, indicating their great potentials in the flexible electronic field.

为提高色纺纱计算机配色的准确性和实用性,以Stearns-Noechel模型为基础,对配色算法进行改进.改变Stearns-Noechel模型中最优参数的确定方法,对参数M进行循环赋值,选择色差最小时对应的M值为最优参数预测配方,在此基础上,将人眼视觉特性以代码表示并用于色纺纱的配色,通过比较标准样与拟合样的色差大小判断配色效果.结果表明:按照前人固定最优参数预测配方,平均拟合色差为1.02,中位数为1.08;对参数M循环赋值后预测配方,平均拟合色差为0.477,中位数为0.46,配色效果得到提高;基于人眼视觉特性预测配方,平均拟合色差为0.201,中位数为0.125,配色效果得到进一步提高.

研究原液着色纤维混色规律.设计了不同比例的三种原液着色纤维进行混色,采用多元回归的方法建立了明度、彩度和色相与单色纤维比例含量的数学模型.同时对该模型进行回归显著性检验以及预测集数据预测.结果表明:建立的数学模型,其决定系数R 2几乎均大于0.9,方程F显著性检验和回归系数t检验结果均为极显著;利用建立的多元回归方程对预测集样本颜色进行预测,64％的样本满足色差要求.认为:采用该数学模型,多数样本基本可以实现一次配色成功,少数样本可以通过进一步修色来达到色差要求.