15-25

UDC 519.688
DOI: 10.15350/2306-2819.2017.4.15

TECHNOLOGY OF DETECTION, RESOLUTION AND ESTIMATION
OF CHROMATOGRAPHIC PEAK PARAMETERS, BASED ON OPTIMAL
SIGNAL PROCESSING METHODS

A. A. Rozhentsov, A. A. Baev, A. M. Hannanov
Volga State University of Technology,
3, Lenin Square, Yoshkar-Ola, 424000, Russian Federation
E-mail: RozhencovAA@volgatech.net

ABSTRACT

Introduction. The increase in requirements for chromatographic equipment characteristics needs the use of new approaches to signal processing, providing the rise of probabilities of the correct peaks detection, the increase in accuracy of estimates of their characteristics, especially when measuring trace amounts of matter under conditions of low signal/noise ratios. The approaches, used during chromatographic signal processing are often empirical and they don’t allow realizing the equipment potential to the full. In this respect, the approaches, approved during the processing of radio signals as well as during the solution of tasks of parameter detection, resolution and estimation are of great interest. The purpose of the article is the research on the possibility of their application when processing chromatographic signals. To achieve this, the following tasks are solved: 1) the survey of noise characteristics of chromatographic signals; 2) the analysis of peak detection algorithms; 3) the determination of major characteristics of peaks of the chromatogram section, based on its autocorrelation function; 4) the development of filter calculation algorithms for the analysis of chromatograms. Results. The improved algorithm of peak borders determination that solves the problem, typical of peak area estimation methods, used nowadays, was developed. The obtained results show the possibility of the introduction of the technology of detection, resolution and estimation of chromatographic peak parameters, based on optimal signal processing methods, to the software of commercial equipment. The practical significance of the work is that the suggested approach surpasses the algorithms, applied everywhere today and based on normal noise distribution and convolution with hybrid Gaussian functions.

KEYWORDS

Gaussian function; baseline drift suppression; correlation analysis; iterative spike removal

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ACKNOWLEDGMENT

Results were obtained within the framework of the state task of the Ministry of Education and Science of the Russian Federation, project № 8.8017.2017/8.9.

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For citation: Rozhentsov A. A., Baev A. A., Hannanov A. M. Technology of Detection, Resolution and Estimation of Chromatographic Peak Parameters, Based on Optimal Signal Processing Methods. Vestnik of Volga State University of Technology. Ser.: Radio Engineering and Infocommunication Systems. 2017. No 4 (36). Pp. 15-25. DOI: 10.15350/2306-2819.2017.4.15