纺织学报 ›› 2017, Vol. 38 ›› Issue (02): 184-190.doi: 10.13475/j.fzxb.20161004207

• 管理与信息化 • 上一篇    

纱线截面压缩变形仿真与验证

  

  • 收稿日期:2016-10-17 修回日期:2016-11-14 出版日期:2017-02-15 发布日期:2017-02-27

Modeling and experimental study on yarn’s cross-section compression deformation

  • Received:2016-10-17 Revised:2016-11-14 Online:2017-02-15 Published:2017-02-27

摘要:

为了改进现有纱线条干均匀度测试仪在预测织物外观质量上的缺陷,对棉型平纹织物织造过程中的纱线截面面积、纱线截面周长、纤维空隙率、纱线压扁率, 纱线密度等纱线截面参数的变化建立分析模型并优选参数,并采用有限元分析和实验论证的方法,进一步分析织造过程中纱线截面面积及周长的变化。通过分析得出,在纱线到织物的织造变形过程中,纱线截面周长的变化远小于其截面面积的变化,纱线截面面积的变化率约是纱线截面周长变化率的2~3倍。通过对纱线截面椭圆长轴与其截面周长、截面面积分别进行相关性分析,得出纱线截面周长与椭圆长轴呈弱相关,纱线截面面积与长轴间无相关性。

关键词: 纱线条干均匀度, 纱线压扁率, 有限元分析, 图像处理

Abstract:

In order to overcome drawbacks of the conventional yarn evenness tester in predicting fabric appearance quality, this paper presents the characterization of the individual yarn deformation and its influence on the resulting quality of the fabric appearance. In the model, the yarn deformation parameters such as the cross-secional area, the yarn cross-sectional perimeter, the void ratio, the yarn flattening ratio f and yarn density were evaluated. Using mathematical modeling, the cross-sectional area and perimeter were presumed as the critical yarn cross-sectional parameters for predicting the fabric appearance quality. Then the finite element modeling (FEM) method and experiment verification were performed to analyze the variation of the cross-sectional area and perimeter in the process of weaving. The results show that the cross-sectional area varhes almost 2 to 3 times greater than the cross-sectional perimeter. The corrilation analysis among the major ellipse radius, the cross-sectional perimeter, and the cross-sectional area are further conducted. The findings reveal a weak correlation between amjor ellipse radius and cross-sictional perimeter, while major ellipse radirs and cross-sectional area are uncorrelated.

Key words: yarn evenness, yarn flattening ratio, finite element analysis, image processing

中图分类号: 

  • TS 101.9
[1] 陆奕辰 王蕾 唐千惠 潘如如 高卫东. 应用图像处理的纱线黑板毛羽量检测与评价[J]. 纺织学报, 2018, 39(08): 144-149.
[2] 王雯雯 高畅 刘基宏. 应用卷积神经网络的细纱断纱锭位识别[J]. 纺织学报, 2018, 39(06): 136-141.
[3] 何晓昀 韦平 张林 邓斌攸 潘云峰 苏真伟. 基于深度学习的籽棉中异性纤维检测方法[J]. 纺织学报, 2018, 39(06): 131-135.
[4] 王雯雯 刘基宏. 应用优化霍夫变换的细纱断头检测[J]. 纺织学报, 2018, 39(04): 36-41.
[5] 王传桐 胡峰 徐启永 吴雨川 余联庆. 改进频率调谐显著算法在疵点辨识中的应用[J]. 纺织学报, 2018, 39(03): 154-160.
[6] 牟新刚 蔡逸超 周晓 陈国良. 基于机器视觉的筒子纱缺陷在线检测系统[J]. 纺织学报, 2018, 39(01): 139-145.
[7] 王晓予 向军 潘如如 梁惠娥 高卫东. 服饰刺绣图案的自动提取与色块分割[J]. 纺织学报, 2017, 38(09): 120-126.
[8] 罗婷 纪峰 程隆棣 吉宜军 邓万胜. 双S曲线软牵伸纺纱技术[J]. 纺织学报, 2017, 38(07): 34-38.
[9] 马倩 王可 金利民. 三维角联锁机织复合材料的冲击破坏有限元模拟分析[J]. 纺织学报, 2017, 38(07): 63-68.
[10] 路凯 钟跃崎 朱俊平 柴新玉. 基于视觉词袋模型的羊绒与羊毛快速鉴别方法[J]. 纺织学报, 2017, 38(07): 130-134.
[11] 张继东 薛元 张杰 郭明瑞 魏晓婷 高卫东 . 应用混色纱纹理信息的纬编针织物模拟[J]. 纺织学报, 2017, 38(07): 148-154.
[12] 景军锋 张婉婉 李鹏飞. 应用显著性算法的纱线条干均匀度检测[J]. 纺织学报, 2017, 38(06): 130-135.
[13] 张宁 李忠健 潘如如 高卫东 韩要宾. 采用色纺纱图像的真实感色织物模拟[J]. 纺织学报, 2017, 38(05): 37-42.
[14] 韦平 张林 刘翔 王冬 苏真伟. 籽棉中异性纤维的双光源成像检测方法[J]. 纺织学报, 2017, 38(04): 32-38.
[15] 刘成霞 韩永华. 模拟实际着装的织物抗皱性测试方法[J]. 纺织学报, 2017, 38(03): 56-60.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!