Using Neural Networks and NIR Spectrophotometry to Identify Fibers

Author:

Jasper Warren J.1,Kovacs Eva T.1

Affiliation:

1. College of Textiles, North Carolina State University, Raleigh, North Carolina 27695, U.S.A.

Abstract

A qualitative nondestructive technique for fiber identification was developed using near infrared (NIR) spectroscopy. A neural network was trained to identify 17 different fiber types using the NIR absorbance spectra from a library of 390 samples. The neural network model was verified by testing untrained samples. It was not only able to identify single fibers, but was also able to correctly identify blends of fibers from fabrics for which it had not been trained.

Publisher

SAGE Publications

Subject

Polymers and Plastics,Chemical Engineering (miscellaneous)

Reference13 articles.

1. Ham, F.M., Cohen, G.M., and Cho, B., Improved Detection of Biological Substances Using a Hybrid Neural Network and Infrared Absorption Spectroscopy, in "Proc. IEEE International Conference on Neural Networks," vol. 1, IEEE, 1991, pp. 227-231.

2. Chemometric Data Analysis Using Artificial Neural Networks

3. Comparing the performance of neural networks to well-established methods of multivariate data analysis: the classification of mass spectral data

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