Data analysis operations, FTIR

The primary function of the computer in FTIR instruments is to perform the Fourier transformation that converts an inter-ferogram to a recognizable spectrum. However, the availability of an on-line mini-computer has opened the door to routine data manipulations. In this section we will review procedures that have been or promise to be useful in coal characterization. Certain data analysis operations, such as numerical integration... 

The improvement in computer technology associated with spectroscopy has led to the expansion of quantitative infrared spectroscopy. The application of statistical methods to the analysis of experimental data is known as chemometrics [5-9]. A detailed description of this subject is beyond the scope of this present text, although several multivariate data analytical methods which are used for the analysis of FTIR spectroscopic data will be outlined here, without detailing the mathematics associated with these methods. The most conunonly used analytical methods in infrared spectroscopy are classical least-squares (CLS), inverse least-squares (ILS), partial least-squares (PLS), and principal component regression (PCR). CLS (also known as K-matrix methods) and PLS (also known as P-matrix methods) are least-squares methods involving matrix operations. These methods can be limited when very complex mixtures are investigated and factor analysis methods, such as PLS and PCR, can be more useful. The factor analysis methods use functions to model the variance in a data set. 

With regard to analysis, there could be a different set of operating parameters for the analyzer instrument that would result in improved calibration data. For example, for an FTIR spectrometer, one could decrease the spectral resolution to obtain a better spectral S/N for the same total scan time. Such a strategy could be advantageous if the spectral features being used for calibration have relatively low resolution. There could also be specific sets of instrument-operating parameters where the instrument response is noisy or unstable over time, in which case they can be changed to improve precision and stability of the analyzer data. 

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