journal article·2024-01Open access

Entropy-based analysis of tensile fracture behavior and mechanical properties in blended yarns

Laihu Peng, Yongyi Zhong, Yubao Qi, Xin Ru, Xudong Hu

Abstract

Internal structural changes in yarns directly affect yarn tensile fracture behavior. The acoustic emission (AE) technique plays a crucial role in dynamically monitoring the internal structural changes of stressed materials. In this paper, an acoustic emission signal analysis method during the whole process of yarn tensile fracture is proposed to study the yarn tensile fracture behavior and mechanical properties from the internal microscopic changes. Tensile fracture tests and acoustic emission tests were carried out to investigate the behavioral properties of yarns during the whole process of stretching from both macroscopic and microscopic perspectives and to compare the results with those of conventional acoustic emission amplitude analysis. The effects of the selection of key parameters of Shannon entropy (window width and bin width) and external noise on the yarn stretching behavior were investigated. The mechanical properties of different yarns were characterized by the entropy changes in different stretching stages compared with the analysis results of conventional mechanical property tests. The results show that compared with the AE amplitude, the Shannon entropy can extract the weak AE signal under high background noise and effectively characterize the yarn tensile fracture behavior. In addition, key parameters were shown to affect the yarn tensile fracture behavior. Further, the entropy change when the yarn is subjected to stretching reflects the change in mechanical properties of the yarn and the difference in mechanical properties of different yarns.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Textile materials and evaluations · 3D Shape Modeling and Analysis · Mechanical Behavior of Composites

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Zhejiang Key Laboratory of Modern Textile Equipment Technology, Zhejiang Sci-Tech University, Hangzhou, China

Longgang Research Institute, Zhejiang Sci-Tech University, Longgang, China

Funding

the Special Support Plan for High-Level Talents in Zhejiang Province: the Provincial Ten Thousand Talents Plan · the Science and Technology Department of Zhejiang Province · the Science and Technology Plan of Zhejiang Province

References (35)

Show source-provided references
1. Wu J · Trans Chin Soc Agric Eng · 2015 · 31 · 5
2. Li X · China Cotton · 2011 · 48 · 28
3. Li XH · China Cotton · 2021 · 48 · 28
4. Chen JF · J Zhejiang Sci-Tech Univ · 2013 · 30 · 649
5. 10.1080/00405000.2016.120489910.1080/00405000.2016.1204899 ↗
6. 10.1177/002199831771485610.1177/0021998317714856 ↗
7. 10.1016/j.sna.2015.03.02810.1016/j.sna.2015.03.028 ↗
8. 10.1016/j.jsv.2012.09.00810.1016/j.jsv.2012.09.008 ↗
9. 10.1088/1742-6596/305/1/01211910.1088/1742-6596/305/1/012119 ↗
10. 10.1016/j.conbuildmat.2014.04.10310.1016/j.conbuildmat.2014.04.103 ↗
11. 10.1080/00405000.2020.176167110.1080/00405000.2020.1761671 ↗
12. Xue YJ · J Hebei Univ Sci Technol · 2015 · 36 · 73
13. Wang J · 2016
14. 10.1080/00405000.2020.183423410.1080/00405000.2020.1834234 ↗
15. 10.3390/s2118622110.3390/s21186221 ↗
16. Jiao Y · J Hebei Univ Sci Technol · 2013 · 4 · 313
17. Geng RS · Nondestruct Test · 2002 · 24 · 6
18. Ge S · Wear · 2003 · 255 · 1068
19. Habib B · Wear · 2008 · 264 · 152
20. 10.1080/10589759.2023.223161110.1080/10589759.2023.2231611 ↗
21. 10.1016/j.neunet.2009.05.00310.1016/j.neunet.2009.05.003 ↗
22. Xu ZL · Materials Reports · 2014 · 28 · 56
23. 10.1002/j.1538-7305.1948.tb01338.x10.1002/j.1538-7305.1948.tb01338.x ↗
24. 10.1016/j.engfailanal.2021.10554710.1016/j.engfailanal.2021.105547 ↗
25. 10.3390/e1808028010.3390/e18080280 ↗
26. 10.1016/j.ymssp.2017.08.00710.1016/j.ymssp.2017.08.007 ↗
27. Tang P · 2017
28. Qiao Y · Computing Techn for Geophys and Geochem Explor · 2021 · 43 · 690
29. 10.1007/978-1-4419-7970-410.1007/978-1-4419-7970-4 ↗
30. Sturges H · J Am Stat Assoc · 1626 · 21 · 65
31. Helmut H · 2014
32. 10.13206/j.gjgs2107050110.13206/j.gjgs21070501 ↗
33. 10.1016/j.ymssp.2009.01.00810.1016/j.ymssp.2009.01.008 ↗
34. Knuth KH. Optimal data-based binning for histograms. ArXiv preprint arXiv:physics/0605197, 2013.
35. Hyndman RJ. The problem with Sturges’ rule for constructing histograms. Retrieved from: https://robjhyndman.com/hyndsight/sturges (1995).