Fiber differentiation method

A fiber identification and fiber technology, which is used in measuring devices, material analysis by optical means, instruments, etc., can solve the problems of high-level structure damage information of fibers, reduction, and unrealized identification.

Inactive Publication Date: 2019-06-04
NISSENKEN QUALITY EVALUATION CENT
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] Therefore, in these methods, there is a problem in that variations in identification results due to differences in the experience and know-how of the inspectors of the respective inspection institutions are generated
These operations are cumbersome, and in addition, there is a problem that the high-order structure of the fiber is destroyed by crushing and the amount of information decreases.
[0016] On the other hand, in the discrimination method of the following Non-Patent Document 1, although the possibility of discrimination is suggested, accurate discrimination has not yet been realized.
In addition, in the identification method of the following non-patent document 2, it mainly suggests the possibility of obtaining the mixing rate of cotton-polyester blended fabrics as different fibers, and does not propose the identification of the same type of different fibers or the identification of the mixing rate.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Fiber differentiation method
  • Fiber differentiation method
  • Fiber differentiation method

Examples

Experimental program
Comparison scheme
Effect test

no. 1 approach 》

[0133] In the present first embodiment, discrimination between individual single fibers is performed for plural types of single fibers. For example, the identification of natural fibers and regenerated fibers in cellulose fibers, the identification of cotton and hemp, the identification of flax and ramie in hemp, the identification of regenerated fibers, and the identification of cupro ammonia silk and lyocell etc. for explanation. It should be noted that, in the first embodiment, discrimination is performed according to the degree of fitting of the score of the measured fiber to the equiprobable ellipse of the score of the discriminant model.

[0134] (1) Discriminant model preparation process

[0135] In the first embodiment, when performing identification of a combination of fibers to be identified, for example, cotton and hemp, these fibers are used as comparison fibers to obtain an absorption spectrum. It should be noted that various corrections can also be performed on...

Embodiment 1

[0176] The present embodiment 1 carries out the discrimination between each single fiber of the above-mentioned first embodiment, according to the identification flow chart (referring to image 3 ) to identify multiple measured fibers. It should be noted that each fiber to be tested was confirmed to be cellulosic fiber in pre-identification such as microscopy.

[0177] (1) Discriminant model preparation process

[0178] In Example 1, first, 73 natural fibers including 27 cotton, 25 flax, and 21 ramie fibers were prepared as single fibers of known fiber types. In addition, 109 regenerated fibers including 48 rayon, 30 cupro, and 31 lyocell were prepared as single fibers whose fiber types are known. A total of 182 of these single fibers were used as comparative fibers in Example 1. In addition, 73 pieces of cotton and hemp (flax and ramie) and 40 pieces of some regenerated fibers (14 pieces of rayon, 13 pieces of cupro, and 13 pieces of lyocell) were used at room temperature....

no. 2 approach 》

[0240] In this second embodiment, as in the above-mentioned first embodiment, discrimination among individual fibers is performed for a plurality of types of individual fibers. For example, the identification of natural fibers and regenerated fibers in cellulose fibers, the identification of cotton and hemp, the identification of flax and ramie in hemp, the identification of regenerated fibers, and the identification of cupro ammonia silk and lyocell etc. for explanation. It should be noted that, in the second embodiment, the discrimination is performed based on the probability density of the normal distribution of the scores of the measured fibers with respect to the score group of the discriminant model.

[0241] (1) Discriminant model preparation process

[0242] Each operation of the discriminant model preparation step in the second embodiment is basically the same as that in the above-mentioned first embodiment. First, the absorption spectrum of each group of comparison...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

Provided is a fiber differentiation method in which a differentiation operation is relatively simple and objective and it is possible to differentiate fibers of the same category but different type without relying on the experience or know-how of an inspector, and in which it is possible to achieve high differentiation accuracy by making variation in differentiation accuracy resulting from combinations of differentiated fibers as small as possible. For two or more types (two or more groups) of fibers of the same category but different type that are to be differentiated, a plurality of single fibers having known fiber types are prepared as comparison fibers, and the absorption spectrums of the comparison fibers are determined through the irradiation of the same with infrared rays or near infrared rays. On the basis of the resulting spectral data X, discriminant analysis is carried out to determine an axis w on which groups are separated from each other and each group is clustered, and adiscriminant model is created from the obtained score plot. Next, a fiber having an unknown fiber type is made to be a fiber under inspection, a score determined from spectral data Y for the fiber under inspection determined in the same way as when the discriminant model was created is inserted into the discriminant model, and the fiber type of the fiber under inspection is identified by determining, through comparison, which group the fiber under inspection belongs to.

Description

technical field [0001] The present invention relates to a fiber identification method for identifying the type of fiber used in fiber products, woven fabrics, and the like. In particular, it relates to a fiber identification method for identifying the same type of different fibers classified into the same type of cellulose fibers, protein fibers, and the like. Background technique [0002] A large number of fiber products are circulated in the market for a wide range of uses. In addition, today when the production and consumption of fiber products are deployed globally, in order to ensure the safety and reliability of transactions during the import and export of fiber products, fiber-related inspection agencies in various countries conduct fiber identification. [0003] In these inspection agencies, such as the inspection agency in Japan, based on JIS L 1030-1 (Test method for mixing rate of fiber products - Part 1: Fiber identification) and JIS L 1030-2 (Test method for mi...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G01N21/3563
CPCG01N21/3563
Inventor 高柳正夫吉村季织斋藤健吾安藤健菅野麻奈美
Owner NISSENKEN QUALITY EVALUATION CENT
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products