Dynamic signals filtration in high level noise condition

    Matsvei Hvozdzeu Info
    Maksim Karpovich Info

Abstract

To examine the opportunity of measuring bulk solids consumption the experimental setup was developed. The main problem was the presence of a non-harmonic signal at the output. Almost always there are some difficulties to build measuring circuits using non-harmonic signals. It is necessary to use one of the approximation methods to receive a wanted signal without noise. For this purpose, the local approximation method was chosen. The developed technique confirmed its positive aspects and allowed to solve the questions that were posed before the experimental setup.

Article in English.

Dinaminių signalų filtravimas esant aukšto lygio triukšmui

Santrauka

Biriųjų medžiagų išeigos matavimo galimybėms tirti buvo sukurta eksperimentinė įranga. Pagrindine problema buvo neharmoninis signalas matavimo įtaiso išėjime, apsunkinantis matavimo grandinių kūrimą. Naudingo signalo filtravimui nuo triukšmo būtina taikyti aproksimavimo metodus. Tyrimui pasirinktas lokalaus aproksimavimo metodas. Sukurta metodika patvirtino savo privalumus ir gebėjimus spręsti tiriamai eksperimentinei įrangai iškeltus uždavinius.

Reikšminiai žodžiai: filtravimas, trukdžiai, lokalaus aproksimavimo metodas.

Keywords:

filtration, noise, local approximation method

How to Cite

Hvozdzeu, M., & Karpovich, M. (2020). Dynamic signals filtration in high level noise condition. Mokslas – Lietuvos Ateitis Science – Future of Lithuania, 12. https://doi.org/10.3846/mla.2020.11487

Share

Published in Issue
May 13, 2020
Abstract Views
674

References

Getmanov, V. G., & Orlov, S. E. (2011). A way to use local and spline models for estimating the parametrical functions of a nonstationary waveform signals. Pattern Recognition and Image Analysis, 21(4), 677−680. https://doi.org/10.1134/S1054661811040079"> https://doi.org/10.1134/S1054661811040079

Hryniuk, D., Suhorukova, I., & Oliferovich, N. (2016). Adaptive smoothing and filtering in transducers. In 2016 Open Conference of Electrical, Electronic and Information Sciences (eStream 2016) (pp. 1−4), Vilnius, Lithuania.

Katkovnik, V., Egiazarian, K., & Astola, J. (2006). Local approximation in signal and image processing. SPIE Publications. https://doi.org/10.1117/3.660178"> https://doi.org/10.1117/3.660178

L’yung, L. (1991). Identifikatsiya sistem [Identification of systems]. Nauka Publishing (in Russian).

Oliferovich, N., Hryniuk, D., & Orobei, I. (2015). Measuring the speed of capillary soaking with adaptation regarding coordinates. In 2015 Open Conference of Electrical Electronic and Information Sciences (eStream 2015) (pp. 1−4), Vilnius, Lithuania. https://doi.org/10.1109/eStream.2015.7119495"> https://doi.org/10.1109/eStream.2015.7119495

Seber, G. A. F., & Lee, A. J. (2003). Linear regression analysis. J. Wiley & Sons Publications. https://doi.org/10.1002/9780471722199"> https://doi.org/10.1002/9780471722199

Tse, E., & Bar-Shalom, Y. (2003). An actively adaptive control for linear systems with random parameters via the dual control. IEEE Transactions on Automatic Control, 18(2), 109−117. https://doi.org/10.1109/TAC.1973.1100242"> https://doi.org/10.1109/TAC.1973.1100242

Wenk, C. J., & Bar-Shalom, Y. (2003). A multiple model of an adaptive dual control algorithm for stochastic systems with unknown parameters. IEEE Transactions on Automatic Control, 25(4), 703−710. https://doi.org/10.1109/TAC.1980.1102417"> https://doi.org/10.1109/TAC.1980.1102417

View article in other formats

CrossMark check

CrossMark logo

Published

2020-05-13

Issue

Section

Electronics and Electrical Engineering / Elektronika ir elektros inžinerija

How to Cite

Hvozdzeu, M., & Karpovich, M. (2020). Dynamic signals filtration in high level noise condition. Mokslas – Lietuvos Ateitis Science – Future of Lithuania, 12. https://doi.org/10.3846/mla.2020.11487

Share