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Fourier‐Filtering Methods of Interference‐Patterned Spectra in Multivariate Calibration and Prediction for Sample Identification and Thickness Determination
Author(s) -
Jeszenszky Éva,
Kocsányi László,
Barócsi Attila,
Richter Péter
Publication year - 2008
Publication title -
macromolecular symposia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.257
H-Index - 76
eISSN - 1521-3900
pISSN - 1022-1360
DOI - 10.1002/masy.200850526
Subject(s) - interference (communication) , fourier transform , calibration , optics , materials science , spectral line , physics , mathematics , mathematical analysis , computer science , statistics , telecommunications , channel (broadcasting) , astronomy
Summary: Determining the thickness or identification of polymer materials with building a multivariate calibration model is based on the near infrared spectral information of the material. The spectrum of a thin plastic sheet is modulated by the interference of multiply reflected beams from the boundary surfaces and causes a disturbing signal component. On one hand, this yields unidentifiable samples or introduces large errors in the sample prediction set. On the other hand, interference‐patterned spectra have to be excluded from the calibration set. Fourier‐transformation of an interference‐patterned spectrum vs. wave number leads to a Fourier‐spectrum as a function of the optical path length (OPL) containing a well recognizable interference peak. After replacing these interference‐components and performing an inverse Fourier‐transformation, the spectra can be used for calibration or prediction. Two types of replacing were studied: the spline‐interpolation on Fourier‐ spectrum vs. OPL and a novel method based on linear approximation between Fourier‐spectra and thickness values. The effectiveness of each filtering method was tested on low‐density polyethylene and polypropylene sheets.