Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 63,
  • Issue 3,
  • pp. 338-343
  • (2009)

Improved Algorithm for Quantitative Analyses of Infrared Spectra of Multicomponent Gas Mixtures with Unknown Compositions

Not Accessible

Your library or personal account may give you access

Abstract

We present a major improvement of an algorithm based on a spectral library search for the quantitative analysis of multicomponent gas samples with unknown compositions. A quantitative spectral database of infrared spectra is used as a training set to compute regression coefficients. Concentrations are computed in the principal component space via principal component regression (PCR). In addition to previous algorithms, we introduce a rating for each candidate substance depending on the concentration found with PCR and a filter that removes candidates that are predicted with negative concentrations if their rating is below a certain threshold. Negative concentrations arise when the measured spectrum contains components that are not contained in the database. The PCR is recomputed until all candidates have a rating above the threshold. Then an adaptive filter "subtracts" the substance with the highest rating from both the measured spectrum and the library and appends it to a hit list. The iteration of this procedure directly produces a list of substances in order of descending importance (i.e., contribution to the measured absorbance) with their corresponding concentrations. The algorithm is tested on spectra of multicomponent surgical smoke samples. The four main components (water, methane, ethane, and ethene) are identified correctly (within the top 5 of the hit list) for an appropriate choice of the rating threshold. The algorithm describes the composition of the smoke sample correctly despite the presence of features in the spectrum that cannot be explained by the spectrum of any single substance present in the database.

PDF Article
More Like This
Constrained nonlinear method for estimating component spectra from multicomponent mixtures

Keiji Sasaki, Satoshi Kawata, and Shigeo Minami
Appl. Opt. 22(22) 3599-3603 (1983)

Estimation of component spectral curves from unknown mixture spectra

Keiji Sasaki, Satoshi Kawata, and Shigeo Minami
Appl. Opt. 23(12) 1955-1959 (1984)

Component spectra extraction from terahertz measurements of unknown mixtures

Xian Li, D. B. Hou, P. J. Huang, J. H. Cai, and G. X. Zhang
Appl. Opt. 54(30) 8925-8934 (2015)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved