Additional Twists of Yarn Produced by System of Compact Spinning with Lattice Apron

Based on the flow simulation in the condensing zone of compact spinning with lattice apron and a bead-elastic rod dynamic model of the flexible fiber,trajectories of fibers with different negative pres...     

Mathematical Characterization of Twisted Yarn

Twist leads to yarn torsion,which influences the physical and mechanical properties of yarn or fabric directly.In this paper,according to the basic principle of space geometry,the space geometric model of yarn was established,then the linking number,twisting number,and writhing number of elastic rod model were defined.The reason of yarn snarling was analyzed based on the energy,and the relation between yarn snarling and yarn torsion was studied according to White formula.The results show when tow ends of yarn are fixed,the linking number is constant,which means the sum of twisting number and writhing number for yarn torsion deformation and bend deformation is constant.     

PBST/棉包芯纱的拉伸回复性能

通过对不同捻度和混纺比的PBST(聚丁二酸-共-对苯二甲酸丁二醇酯)与棉包芯纱拉伸回复性能的分析,探讨了捻度和混纺比对PBST包芯纱回弹性能的影响.在捻度相同、PBST纤维相同的条件下,PBST包芯纱的拉伸弹性回复性随着棉纤维的增加而减少;在纱线混纺比相同时、PBST包芯纱的拉伸弹性回复率随着捻度的增加呈先增后降的趋势.采用捻度为500捻/m和40/60的混纺比纺制PBST/棉包芯纱时,纱线的拉伸弹性回复性能较好,并且在小变形下,PBST包芯纱能保持良好的拉伸回复性.这对PBST包芯纱的开发和应用具有一定的参考价值.     

Quantitative Risk Assessment with Data Mining for Formaldehyde Content of Imported Textile

The assessment of potential risks posed by formaldehyde in clothing to consumers is of increasing concern worldwide,for free formaldehyde is harmful to human. Some papers focus on hazard and exposure assessment,using quantitative and semi-quantitative method, rather than assessment for the factors related to formaldehyde content. In order to perform early-warning research and risk management,the quantitative risk assessment is used to analyze the imported textile testing data and find the factors related to formaldehyde content. K-means algorithm is the core of the method. It can be concluded that the disqualified textiles have relations with main fiber components,fabric color,season month,and brand. Then the data in the same attribute are clustered by Kmeans algorithm. The different classes are defined as related danger level,respectively severe,moderate,and light.