Fourier-filtering methods of interference-patterned spectra in multivariate calibration and prediction for sample identification and thickness determination

Éva Jeszenszky, László Kocsányi, Attila Barócsi, Péter Richter

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)233-240
Number of pages8
JournalMacromolecular Symposia
Volume265
Issue number1
DOIs
Publication statusPublished - May 1 2008

Keywords

  • Fourier-filtering methods
  • Infrared spectroscopy
  • Interference-patterned spectrum
  • Multivariate calibration
  • Plastics

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Organic Chemistry
  • Polymers and Plastics
  • Materials Chemistry

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