HARMONIZATION OF CORRELATED CALIBRATION CURVES WITH AN APPLICATION TO THE ANALYSIS OF NATURAL GASES

During the analysis of natural gas by gas chromotography, the indicated response is affected systematically by varying environmental and instrumental conditions. Calibration data dispersion is attributed not only to random effects, but also to systematic measurement effects. The accuracy of the measurement results and consequently the usability of a calibration model are accordingly reduced. The model consists of a series of calibration curves, one for each component of the gas measured. When the systematic uncertainty component dominates, a correlated response behaviour between corresponding points on which the set of curves depends is observed. A model-based least-squares method is introduced that compensates for these effects. It incorporates correction parameters to account for the systematic uncertainty components, thus eliminating the correlation effects and reducing the calibration model uncertainty. Results are presented for calibration data modelled by straight-line functions. Generalizations are indicated.