HEURISTIC AND STATISTICAL ALGORITHMS FOR AUTOMATED EMISSION SPECTRAL BACKGROUND INTENSITY ESTIMATION

Two algorithms for the complete automation of background estimation in ICP emission spectroscopy are presented and evaluated. One of these a lgorithms is based on heuristic spectral interpretation, while the oth er is based on statistical spectral interpretation. These algorithms b oth address the weaknesses of the conventionally employed approaches o f blank subtraction in calibration and background estimation through i nterpolation from analyst-selected wavelengths adjacent to the analyte peak. In a rigorous evaluation with synthetic spectra, these algorith ms are characterized for performance in terms of accuracy, precision, and robustness. As a demonstration of the algorithms' performance with experimentally measured spectra, a determination of uranium in the pr esence of a calcium background interference is performed. These algori thms require no analyst interaction for their operation, and they esti mate the background for every spectrum measured.