Study of nonlinear analysis methods for spectral detection of mixed gases

Abstract

Data analytic methods are required in detecting gas concentrations using spectroscopic techniques, especially for absorption spectra of mixed gases. However the common analytic methods, such as multivariate linear regression, principal component regression etc. are limited to deal with non-linear and uncorrelated variables. In the case of multi-component gases, these methods are able to meet expected accuracy and reliability. In this paper, a simple and effective method is proposed.This method is based on spectral cases of single-component gases, it determines the concentration of each component using linear superposition principle of the spectra in Beer’s law. The experimental results show that the detection error of this method is less than 1% in the known gas mixture case and 3% in the unknown gas mixture case.