A total of 456 IR transmission spectra from the Paint Data Query (PDQ) database that spanned 22 General Motors assembly plants and served as a training set cohort were transformed into ATR spectra by the simulation algorithm. These search prefilters were formulated using the fingerprint region (1500 cm neg¹ to 500 cm neg¹). Both the transformed ATR spectra (training set) and the experimental ATR spectra (validation set) were preprocessed for pattern recognition analysis using the discrete wavelet transform, which increased the signal-to-noise of the ATR spectra by concentrating the signal in specific wavelet coefficients. Attenuated total reflection spectra of 14 clear coat samples (validation set) measured with a Nicolet iS50 Fourier transform IR spectrometer were correctly classified as to assembly plant(s) of the automotive vehicle from which the paint sample originated, using search prefilters developed from 456 simulated ATR spectra. The ATR simulation (transformation) algorithm successfully facilitated spectral library matching of ATR spectra against IR transmission spectra of automotive clear coats in the PDQ database. (publisher abstract modified)
Development of Infrared Library Search Prefilters for Automotive Clear Coats From Simulated Attenuated Total Reflection (ATR) Spectra
NCJ Number
253361
Journal
Applied Spectroscopy Volume: 72 Issue: 6 Dated: 2018 Pages: 886-895
Date Published
2018
Length
11 pages
Annotation
In the current study, a previously published study featuring an attenuated total reflection (ATR) simulation algorithm that mitigated distortions in ATR spectra was further investigated to evaluate its efficacy in improving the searching of infrared (IR) transmission libraries; and search prefilters were developed from transformed ATR spectra to identify the assembly plant of a vehicle from ATR spectra of the clear coat layer.
Abstract