Signal selective amplification: A solution for an improved detection of amphetamines with QCL equipped portable GC-IRAS spectrometers

Author

Praisler, Mirela ; Ciochina, Silviu ; Stoica, Atanasia ; Dumitriu, Luminita

Author_Institution

Dept. of Chem., “Dunarea de Jos” Univ. of Galati, Galati, Romania

fYear

2014

fDate

17-19 Oct. 2014

Firstpage

909

Lastpage

914

Abstract

In this article we are presenting a signal selective amplification method that was used for improving the automatic detection of amphetamines based on their infrared absorptions recorded in the narrow spectral window in which the QCL source of a new portable GC-IRAS spectrometer is emitting (1550-1330 cm^-1). The expert system developed for class identity assignment is based on Principal Component Analysis (PCA) and distinguishes the amphetamines according to their toxic effect (stimulant and hallucinogenic amphetamines). The detection efficiency and accuracy was evaluated by using Cluster Analysis (CA).

Keywords

chromatography; drugs; expert systems; gas sensors; infrared detectors; infrared spectra; infrared spectrometers; pattern clustering; portable instruments; principal component analysis; quantum cascade lasers; statistical analysis; toxicology; CA; PCA; QCL equipped portable GC-IRAS spectrometer; class identity assignment; cluster analysis; expert system; gas chromatography; hallucinogenic amphetamine detection; infrared absorption recording; infrared absorption spectroscopy; narrow spectral window; principal component analysis; quantum cascade laser; signal selective amplification method; stimulant; toxic effect; wave number 1550 cm^-1 to 1330 cm^-1; Absorption; Compounds; Databases; Dispersion; Drugs; Principal component analysis; Quantum cascade lasers; Principal Component Analysis; amphetamines; detection optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

System Theory, Control and Computing (ICSTCC), 2014 18th International Conference

Conference_Location

Sinaia

Type

conf

DOI

10.1109/ICSTCC.2014.6982535

Filename

6982535