纺织学报 ›› 2024, Vol. 45 ›› Issue (02): 238-245.doi: 10.13475/j.fzxb.20231006601

• 机械与设备 • 上一篇    下一篇

数据驱动与有限元仿真融合的纱线断裂强力分析方法

陶静1,2, 汪俊亮2(), 张洁2   

  1. 1.东华大学 机械工程学院, 上海 201620
    2.东华大学 人工智能研究院, 上海 201620
  • 收稿日期:2023-10-17 修回日期:2023-11-18 出版日期:2024-02-15 发布日期:2024-03-29
  • 通讯作者: 汪俊亮(1991—),男,副研究员,博士。主要研究方向为智能制造系统建模、运行分析与优化理论、计算机视觉与模式识别。E-mail:junliangwang@dhu.edu.cn
  • 作者简介:陶静(1999—),女,硕士生。主要研究方向为机器学习与智能纺纱。
  • 基金资助:
    国家自然科学基金面上项目(52275478);中国科协青年人才托举工程项目(2021QNRC001)

Data-driven finite element simulation for yarn breaking strength analysis

TAO Jing1,2, WANG Junliang2(), ZHANG Jie2   

  1. 1. College of Mechanical Engineering, Donghua University, Shanghai 201620, China
    2. Institute of Artificial Intelligence, Donghua University, Shanghai 201620, China
  • Received:2023-10-17 Revised:2023-11-18 Published:2024-02-15 Online:2024-03-29

摘要:

为揭示机器人运动速度等参数对纱线性能的影响规律,考虑纱线夹持长度与拉伸速度对断裂强力分布的影响,分析了动态环境下环锭纺细纱断裂强力的分布特征。首先设计拉伸实验对环锭纺细纱性能进行分析,并构建了环锭纺短纤纱本构模型表征其强伸性能。其次建立有限元仿真模型模拟短纤纱的断裂过程,揭示了纤维间载荷传播的规律和纱体结构演化的4个阶段模型。最后对纱线强力数据的统计特征进行分析,建立了其分布参数模型。结果表明,分布检验与威布尔分布相比,对数正态分布的拟合误差最小,残差平方和为0.000 6,进一步提高了动态环境下环锭纺细纱强力预测的可靠性。

关键词: 环锭纺, 细纱断裂强力, 有限元仿真, 分布参数模型, 对数正态分布

Abstract:

Objective In order to achieve robotized automatic thread jointing technology and the automated production of the whole process of spinning, the breaking strength of yarn was analyzed in this research. Aiming at the problem that yarns are easy to break under the influence of environmental factors, this study is proposed to analyze the influence of yarn clamping length and stretching speed on the breaking strength distribution, and simulate the characteristics of breaking strength distribution of ring-spun yarn under dynamic environment.

Method Tensile experiments were firstly carried out on a YG020A electronic single-yarn strength machine to analyze the performance of ring-spun spinning yarns, and a constitutive model for ring-spun staple fiber yarns was constructed to characterize their tensile properties. A finite element analysis simulation model was constructed based on the idealized parametric modeling of yarn geometry. The model was used to simulate the fracture process of staple fiber yarns at a constant tensile rate in order to understand the inter-fiber load propagation at the four stages of yarn tensile loading. The distribution parameter model was established based on the maximum likelihood estimation method to analyze the statistical characteristics of the yarn strength data, and further verified by using the Kmogorov-Smirnov test.

Results The results of yarn tensile experiments, showed that when the yarn stretching speed was low, the measured breaking strength of single yarns deviated from the constant-rate-of-extension (CRE) method within 6 cN, with an overall fluctuating. When the stretching speed was close to twice that of the CRE method, the measured breaking strength of single yarns showed a significant decrease. The effect of clamping length on yarn strength was not obvious. The load-displacement curves of the yarns in the tensile experiments was divided into three stages of the tensile deformation process of the yarns. In the first stage, the static friction between fibers accumulated rapidly, and the tension increases while the displacement was small. The second stage saw the relative displacement between fibers and deformation under stress, and the yarn elongates at a higher constant rate. In the third stage, fiber failure gradually appearred in the weak ring segments of the yarn until the yarn broke completely. During the yarn tensile fracture stage, the inner fiber stress was generally greater than that of the outer fiber. The fitting accuracy of distribution parameters, based on the maximum likelihood estimation method, indicates that the lognormal distribution model exhibits the smallest fitting error. And the residual sum of squares amounts to 0.000 6. The Kmogorov-Smirnov test p-value of the strength data sample was 0.068, which is greater than the significance parameter threshold of 0.05, confirming reliability for analyzing the statistical patterns of the strength at break data of single yarns using the lognormal distribution. According to the inverse cumulative distribution function corresponding to the quantile, when the confidence level was 0.98, the strength data fluctuation interval was [123.4,182.0].

Conclusion Due to the random distribution of fibers, the average yarn strength tends to decrease with the increase of stretching speed, while the yarn clamping distance has no significant effect on the average strength. The overall distribution of single yarn strength is more in line with the lognormal distribution compared to the Weibull distribution, showing a right skewness. When the confidence level is 0.98, controlling the weak ring tension below 123.4 cN will greatly reduce the probability of breakage.

Key words: ring-spun, yarn breaking strength, finite element simulation, distributed parameter model, log normal distribution

中图分类号: 

  • TP391.4

表1

拉伸实验参数设置"

组号 夹持长度/mm 拉伸速度/(mm·min-1)
A1 500 100
A2 500 200
A3 500 300
A4 500 400
A5 500 500
A6 500 600
A7 500 700
A8 500 800
B1 400 500
B2 300 500
B3 200 500

图1

不同实验参数数据统计分析"

图2

B3组3次拉伸输出载荷-位移曲线"

图3

理想环锭纺纱几何模型"

图4

纱线各段节点应力曲线图"

图5

纱线拉伸断裂过程仿真"

图6

分布拟合精度评价算法流程"

图7

最大似然估计法拟合各分布误差对比"

图8

强力数据对数正态分布概率密度-频率直方图"

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