Signal Decomposition for Monitoring Systems of Processes

Author:

Pavlenko Ivan12ORCID,Trojanowska Justyna3ORCID,Ivanov Vitalii45ORCID,Radchenko Svetlana5ORCID,Husár Jozef2ORCID,Mižáková Jana2ORCID

Affiliation:

1. Department of Computational Mechanics, Sumy State University, 116, Kharkivska St., 40007 Sumy, Ukraine

2. Department of Industrial Engineering and Informatics, Faculty of Manufacturing Technologies, Technical University of Košice, 1, Bayerova St., 080 01 Prešov, Slovakia

3. Department of Production Engineering, Poznan University of Technology, 5, M. Sklodowskej-Curie Sq., 60-965 Poznan, Poland

4. Department of Manufacturing Engineering, Machines and Tools, Sumy State University, 2, Rymskogo-Korsakova St., 40007 Sumy, Ukraine

5. Department of Automobile and Manufacturing Technologies, Faculty of Manufacturing Technologies, Technical University of Košice, 1, Bayerova St., 080 01 Prešov, Slovakia

Abstract

This article is devoted to the problem of signal decomposition into periodic and aperiodic components. According to the proposed approach, there is no need to evaluate the aperiodic component as a difference between the total signal of its periodic components. This research aims to create a general analytical approach that combines the Fourier and Maclaurin series methodologies into a single comprehensive series. As a result, analytical expressions for determining deposition coefficients were established for an aperiodic signal with a monoharmonic overlay. Recurrence relations were established to determine the coefficients of this series. These relations allow direct integrations of the obtained values of integrals to be avoided. The evaluated numerical values of the coefficients are also presented graphically and tabulated. It was proven that the values of these coefficients are universal numbers since they do not depend on the period/frequency of oscillations. The reliability of the proposed approach was confirmed by the fact that the evaluated coefficients are equal to the Fourier series coefficients in the case of a periodic signal. Also, for an aperiodic signal, these coefficients were reduced to the coefficients of the Maclaurin series. The usability of the proposed generalized analytical approach for signal decomposition is for control and monitoring systems of processes.

Funder

Slovak Research and Development Agency

Ministry of Education, Science, Research and Sport of the Slovak Republic

EU NextGenerationEU

Publisher

MDPI AG

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5. Zubrycki, P., and Petrovsky, A. (2007, January 3–7). Accurate speech decomposition into periodic and aperiodic components based on discrete harmonic transform. Proceedings of the 15th European Signal Processing Conference (EUSIPCO 2007), Poznan, Poland.

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