Detection of adulteration in hydrated ethyl alcohol fuel using infrared spectroscopy and supervised pattern recognition methods

TALANTA

卷:93

Article

Pimentel, Maria Fernanda²  Coelho Pontes, Marcio Jose¹ 

[1] Univ Fed Paraiba, Dept Quim, Lab Automacao & Instrumentacao Quim Analit Quimio, BR-58051970 Joao Pessoa, PB, Brazil

[2] Univ Fed Pernambuco, Dept Engn Quim, Recife, PE, Brazil

关键词: Hydrated ethyl alcohol fuel;    Infrared spectrometry;    Supervised pattern recognition methods;    Partial least squares - discriminant analysis;    Linear discriminant analysis;    Wavenumber selection;   

DOI  :  10.1016/j.talanta.2012.01.060

来源: Elsevier

【 摘 要 】

This paper proposes an analytical method to detect adulteration of hydrated ethyl alcohol fuel based on near infrared (NIR) and middle infrared (MIR) spectroscopies associated with supervised pattern recognition methods. For this purpose, linear discriminant analysis (LDA) was employed to build a classification model on the basis of a reduced subset of wavenumbers. For variable selection, three techniques are considered, namely the successive projection algorithm (SPA), the genetic algorithm (GA) and a stepwise formulation (SW). For comparison, models based on partial least squares discriminant analysis (PLS-DA) were also employed using full-spectrum. The method was validated in a case study involving the classification of 181 hydrated ethyl alcohol fuel samples, which were divided into three different classes; (1) authentic samples; (2) samples adulterated with water and (3) samples contaminated with methanol. LDA/GA and PLS-DA models were found to be the best methods for classifying the spectral data obtained in NIR region, which achieved a correct prediction rate of 100% in the test set, while the LDA/SPA and LDA/SW were correctly classified at 84.4% and 97.8%, respectively. For MIR data, all models (PLS-DA and LDA coupled with the SW, SPA and GA) employed in this study correctly classified all samples in the test set. (C) 2012 Elsevier B.V. All rights reserved.

【 授权许可】

Free