Extraction of terahertz wave parameters that characterize woollen clothes

IF 1.6 4区 工程技术 Q2 MATERIALS SCIENCE, TEXTILES Textile Research Journal Pub Date : 2024-08-22 DOI:10.1177/00405175241268786
Toa Yoshizumi, Kazuma Iwasaki, Sho Fujii, Tsuyoshi Kimura, Masaya Yamamoto, Gaku Manago, Jeongsoo Yu, Tadao Tanabe
{"title":"Extraction of terahertz wave parameters that characterize woollen clothes","authors":"Toa Yoshizumi, Kazuma Iwasaki, Sho Fujii, Tsuyoshi Kimura, Masaya Yamamoto, Gaku Manago, Jeongsoo Yu, Tadao Tanabe","doi":"10.1177/00405175241268786","DOIUrl":null,"url":null,"abstract":"Wool is a natural fiber with a high price, making it practical in the recycled fiber market. To reduce the cost of sorting fibers, terahertz waves have been used to extract parameters within the spectral information that is characteristic of wool fiber. Differences due to the specific surface shape (scale shape) and the terahertz measurement area were utilized for the identification. Characteristic features of wool content were observed between 19.4 THz and 19.8 THz by Fourier transform infrared spectroscopy measurements. At 19.5 THz, the reflectance decreased from 2.0% to 0.85% as the wool content increased. This is due to the scale shape of the wool surface causing scattering. Samples with more than 80% wool could be identified by 1.4% or less reflectance at this frequency. A mathematical expression for a reflectance that decreases as the wool content increases can be successfully expressed as an exponential function. In addition, a correlation between the surface structure of the sample and its anisotropy due to weaving to the polarized terahertz wave was confirmed. Due to the structural characteristics of the sample, there is an anisotropy of 45° or 90° which could be identified by a transmittance of 40%.","PeriodicalId":22323,"journal":{"name":"Textile Research Journal","volume":"1 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Textile Research Journal","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1177/00405175241268786","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, TEXTILES","Score":null,"Total":0}
引用次数: 0

Abstract

Wool is a natural fiber with a high price, making it practical in the recycled fiber market. To reduce the cost of sorting fibers, terahertz waves have been used to extract parameters within the spectral information that is characteristic of wool fiber. Differences due to the specific surface shape (scale shape) and the terahertz measurement area were utilized for the identification. Characteristic features of wool content were observed between 19.4 THz and 19.8 THz by Fourier transform infrared spectroscopy measurements. At 19.5 THz, the reflectance decreased from 2.0% to 0.85% as the wool content increased. This is due to the scale shape of the wool surface causing scattering. Samples with more than 80% wool could be identified by 1.4% or less reflectance at this frequency. A mathematical expression for a reflectance that decreases as the wool content increases can be successfully expressed as an exponential function. In addition, a correlation between the surface structure of the sample and its anisotropy due to weaving to the polarized terahertz wave was confirmed. Due to the structural characteristics of the sample, there is an anisotropy of 45° or 90° which could be identified by a transmittance of 40%.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
提取毛织衣物特征的太赫兹波参数
羊毛是一种天然纤维,价格昂贵,因此在回收纤维市场上非常实用。为了降低纤维分拣的成本,太赫兹波被用来提取羊毛纤维特征光谱信息中的参数。特定表面形状(鳞片形状)和太赫兹测量区域造成的差异被用于识别。通过傅立叶变换红外光谱测量,在 19.4 太赫兹和 19.8 太赫兹之间观察到了羊毛成分的特征。在 19.5 THz 时,随着羊毛含量的增加,反射率从 2.0% 下降到 0.85%。这是由于羊毛表面的鳞片形状造成了散射。羊毛含量超过 80% 的样品在此频率下的反射率为 1.4% 或更低,可以识别。反射率随羊毛含量增加而降低的数学表达式可以成功地表示为指数函数。此外,还证实了样品的表面结构与其在偏振太赫兹波下因编织而产生的各向异性之间的相关性。由于样品的结构特点,存在着 45° 或 90° 的各向异性,这可以通过 40% 的透射率来识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Textile Research Journal
Textile Research Journal 工程技术-材料科学:纺织
CiteScore
4.00
自引率
21.70%
发文量
309
审稿时长
1.5 months
期刊介绍: The Textile Research Journal is the leading peer reviewed Journal for textile research. It is devoted to the dissemination of fundamental, theoretical and applied scientific knowledge in materials, chemistry, manufacture and system sciences related to fibers, fibrous assemblies and textiles. The Journal serves authors and subscribers worldwide, and it is selective in accepting contributions on the basis of merit, novelty and originality.
期刊最新文献
A review of deep learning and artificial intelligence in dyeing, printing and finishing A review of deep learning within the framework of artificial intelligence for enhanced fiber and yarn quality Reconstructing hyperspectral images of textiles from a single RGB image utilizing the multihead self-attention mechanism Study on the thermo-physiological comfort properties of cotton/polyester combination yarn-based double-layer knitted fabrics Study on the relationship between blending uniformity and yarn performance of blended yarn
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1