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.
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References
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.
Jurs, P.C., and Isenhour, T.L., "Chemical Applications of Pattern Recognition,"Wiley-Interscience , NY, 1975.
3.
Leighton, R.R., "The Aspirin /Migraines Neural Network Software User's Manual," 6.0 ed. MITRE Corporation, McLean, VA, Oct. 1992.
4.
Liu, Y., Upadhyaya, B.R., and Naghedolfeizi, M. , Chemometric Data Analysis Using Artificial Neural Networks, Appl. Spectros.47, 1, 12-24 (1993).
5.
Lohninger, H. , and Stand, F., Comparing the Performance of Neural Networks to Well-established Methods of Multivariate Data Arialysis: The Classification of Mass Spectral Data, Fresenius J. Anal. Chem.344, 186-189 ( 1992).
6.
Meyer, M., and Weigelt, T., Interpretation of Infrared Spectra by Artificial Neural Networks, Anal. Chim. Acta265, 183-190 (1992).
7.
Miyata, Y., "A User's Guide to PlaNet Version 5.6 A Tool for Constructing, Running, and Looking into a PDP Network,"Computer Science Department, University of Colorado, Boulder, 1991.
8.
Munk, M.E., Madison, M.S., and Robb, E.W., Neural Network Models for Infrared Spectrum Interpretation, Mikrochim. ActaII, 505-514 (1991).
9.
Pedersen, J.L. , Chemometric Near Infrared Analysis of Textiles, Master's thesis, North Carolina State University, 1991.
10.
Robb, E.W., and Munk, M.E., A Neural Network Approach to Infrared Spectrum Interpretation, Mikrochim. Acta1, 131-155 (1990).
11.
Schierle, C. , and Otto, M., Comparison of a Neural Network with Multiple Linear Regression for Quantitative Analysis in ICP-Atomic Emission Spectroscopy , Fresenius J. Anal. Chem.3, 344, 190-194 ( 1992).
12.
Tanabe, K., Tamura, T., and Uesaka, H., Neural Network System for the Identification of Infrared Spectra, Appl. Spectros. 46(5), 807-810 (1992).
13.
Weigel, U., and Herges, R., Automatic Interpretation of Infrared Spectra: Recognition of Aromatic Substitution Patterns Using Neural Networks, J. Chem. Inf. Comput. Sci.32(6), 723-731 (1992).