Modeling of yarn strength and its influencing factors in the pneumatic splicing process
Source abstract
Abstract
Yarn splicing strength is one of the most important indexes to evaluate yarn twist quality, and it determines final performance of the yarn. This paper establishes a prediction model of yarn splicing strength. The strength prediction model was used to predict the mechanical properties of yarn composed of different fibers during splicing. The effects of fiber properties, splicing and tensile strain on the splicing strength of yarn were described by using the characteristic parameters of the fiber and yarn. Finally, the interaction between parameters is analyzed by charts, and the optimal solution is obtained. The results show that the yarn splicing strength prediction model established by the mechanical analysis and geometric structure can reflect the mechanical state of the yarn in the pneumatic splicing chamber, and can be used to calculate the yarn splicing strength. Yarns with higher tensile modulus will obtain higher splicing strength under the action of lower twist and higher tensile stress. Therefore, the strength prediction model provides a theoretical basis for the study of the relationship among yarn strength and fiber properties, splicing, tensile strain and other parameters, and also provides guidance for the optimization of the modern spinning process. Furthermore, the influence of air pressure on the splicing strength is also discussed.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Textile materials and evaluations · Structural Analysis and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Donghua University, China
Funding
Shanghai Frontiers Science Center of Modern Texitile · Natural Science Foundation of Shanghai · National Natural Science Foundation of China
References (27)
Show source-provided references
1. Huang W. · 2017
2. 10.1177/004051751665410910.1177/0040517516654109 ↗
3. 10.4028/www.scientific.net/KEM.561.48310.4028/www.scientific.net/KEM.561.483 ↗
4. 10.4028/www.scientific.net/KEM.584.5010.4028/www.scientific.net/KEM.584.50 ↗
5. 10.1007/BF0290300010.1007/BF02903000 ↗
6. 10.1080/0040500070157047610.1080/00405000701570476 ↗
7. Moqeet A · Indian J Fiber Text · 2013 · 38 · 74
8. Berlin JCK · Indian J Fiber Text · 2018 · 43 · 499
9. Gegauff CM. · Bull Soc Industry Mulhouse · 1907 · 77 · 153
10. 10.1177/00405175510210030110.1177/004051755102100301 ↗
11. 10.1177/00405175500200010110.1177/004051755002000101 ↗
12. 10.1177/00405175520220100410.1177/004051755202201004 ↗
13. 10.1177/00405175650350120210.1177/004051756503501202 ↗
14. 10.1177/004051751774116010.1177/0040517517741160 ↗
15. Özkan İ · J Text Inst · 2014 · 105 · 1203
16. Dong KY · J Donghua Univ · 2005 · 31 · 88
17. Majumdar A · Indian J Fiber Text · 2005 · 30 · 19
18. 10.1007/s12221-008-0034-010.1007/s12221-008-0034-0 ↗
19. 10.1007/s12221-008-0122-110.1007/s12221-008-0122-1 ↗
20. 10.1177/0040517521102261910.1177/00405175211022619 ↗
21. 10.1177/004051751983773110.1177/0040517519837731 ↗
22. 10.1177/00405175920620120810.1177/004051759206201208 ↗
23. 10.1177/00405175930630090210.1177/004051759306300902 ↗
24. 10.1177/00405175510210030110.1177/004051755102100301 ↗
25. Zhang HW · Shanghai Text Sci Tech · 2011 · 1001
26. Zhao DR · 2020
27. Yang XL. · 2010