Signal filtering of potentiometric stripping analysis using Fourier techniques

• Published in: Analytica chimica acta Vol. 338; no. 3; pp. 167 - 178
• Main Authors: Chow, C.W.K., Davey, D.E., Mulcahy, D.E.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 20.02.1997
• Subjects: Fourier filtering; Multichannel potentiometric monitoring; Potentiometric stripping analysis; Potentiometric stripping analysis; Fourier filtering; Multichannel potentiometric monitoring
• ISSN: 0003-2670; 1873-4324
• DOI: 10.1016/S0003-2670(96)00441-2

Four filtering functions, rectangular, triangular, exponential and decay exponential for Fourier filtering have been compared in this study of potentiometric stripping analysis (PSA) data. The filtering procedure involves treating the potential coordinate as mathematically equivalent to a time coordinate to transform data to the frequency domain. After Fourier transformation, each method yielded signal-to-noise enhancement over the original data in the order, decay exponential > triangular > exponential > rectangular. Apart from the filtering functions, two different filtering procedures, conventional and reflectance, have been compared in this study. Peak area measurement was unaffected by the reflectance procedure, while an undesirable increase in peak area was observed in the conventional procedure. A linear peak area-concentration relationship was retained in all cases. The resolution of overlapping potential peaks, using copper and bismuth peaks as the example, was most improved using the rectangular filtering function and worst using the decay exponential filtering function. This is completely opposite to the results obtained in signal-to-noise enhancement study. Thus, a compromise between S N ratio enhancement and peak distortion has to be made, as the latter is always a trade-off in signal processing. With the use of a personal computer (PC) and commercial data acquisition systems, the original saved data can be stored. Selection of a particular type of filtering function to optimise the analytical signal can be achieved by applying various functions to the original signal, until a desirable output is obtained.