Quantitative analysis of textile delusterant based on terahertz spectral and data fusion strategies

太赫兹辐射 织物 融合 传感器融合 计算机科学 材料科学 遥感 人工智能 光电子学 地质学 复合材料 语言学 哲学
作者
Xianhua Yin,Huicong Chen,An Li,Wei Mo
出处
期刊:Infrared Physics & Technology [Elsevier BV]
卷期号:125: 104293-104293 被引量:7
标识
DOI:10.1016/j.infrared.2022.104293
摘要

• Spectral data fusion and partial least squares were used to determine the delusterant content in textiles. • High-level data fusion was the most effective way to model the quantification of delusterant. • It lays the valuable foundation for the testing of textile additives. Titanium dioxide is a delusterant and an important component in the manufacturing of polyester fiber. For the need of fast, accurate and nondestructive detection of matting agents in textiles, a quantitative analysis method based on terahertz absorption spectroscopy and derivative spectroscopy, combined with chemometrics and data fusion strategy is proposed. This experiment was used two spectra for fusion. The terahertz absorption spectra were obtained in the band of 0.2–1.9 THz by optical parameter extraction. The derivative spectrum was derived from the first-order derivative of the absorption spectrum. Partial least squares (PLS) and data fusion were used to construct a prediction model for titanium dioxide concentration in polyester fiber. Low-level data fusion was the direct combination of two spectral data; The successive projections algorithm (SPA) and Monte Carlo uninformative variable elimination (MCUVE) were employed by mid-level data fusion for feature selection, after which the feature variables were fused; multiple linear regression was used for fusion by high-level data fusion. The prediction accuracy of the high-level data fusion model is higher than that of other models, which the correlation coefficient of cross-validation (Rcv) and correlation coefficient of prediction (Rp) are 0.9229 and 0.9227. The mean relative error (MRE) is 0.2654. The results show that terahertz spectroscopy combined with chemometric methods and high-level data fusion strategies can achieve rapid, accurate and non-destructive detection of titanium dioxide in polyester fiber, which can lay the theoretical foundation for terahertz spectroscopy detection methods for textile additives.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
珏神关注了科研通微信公众号
2秒前
3秒前
3秒前
健壮的大开完成签到,获得积分10
3秒前
cc完成签到 ,获得积分10
3秒前
molihuakai的应助被大海采纳,获得10
4秒前
Lucas的应助被仁爱嫣采纳,获得10
4秒前
5秒前
three完成签到,获得积分10
5秒前
henry完成签到,获得积分10
5秒前
Hinata完成签到,获得积分20
6秒前
7秒前
zkz完成签到,获得积分10
8秒前
西啃发布了新的文献求助10
8秒前
9秒前
周灿发布了新的文献求助10
9秒前
科研小小白完成签到,获得积分10
10秒前
10秒前
DW的应助被科研通管家采纳,获得10
10秒前
在水一方的应助被科研通管家采纳,获得10
10秒前
10秒前
领导范儿的应助被科研通管家采纳,获得10
11秒前
爆米花的应助被科研通管家采纳,获得10
11秒前
科研通AI2S的应助被科研通管家采纳,获得10
11秒前
今后的应助被科研通管家采纳,获得10
11秒前
11秒前
传奇3的应助被科研通管家采纳,获得10
11秒前
xueyu发布了新的文献求助10
11秒前
11秒前
11秒前
12秒前
12秒前
细腻慕儿完成签到 ,获得积分10
12秒前
13秒前
李一诺完成签到 ,获得积分10
13秒前
14秒前
maoxinnan完成签到,获得积分10
15秒前
猪崽崽发布了新的文献求助10
15秒前
仁爱嫣发布了新的文献求助10
16秒前
16秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
Acceptability of Printed Boards 600
The Dawn of Philology 520
Organizational Behavior 510
Production Logging: Theoretical and Interpretive Elements 400
A primer on partial least squares structural equation modeling (PLS-SEM) (4th ed.) 310
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 有机化学 化学工程 内科学 物理 生物化学 复合材料 催化作用 细胞生物学 人工智能 心理学 无机化学 基因 遗传学
热门帖子
关注 科研通微信公众号,转发送积分 7823258
求助须知:如何正确求助?哪些是违规求助? 9349804
关于积分的说明 20554969
捐赠科研通 7415898
什么是DOI,文献DOI怎么找? 3333921
关于科研通互助平台的介绍 2479313
邀请新用户注册赠送积分活动 2354039