Dynamic signals filtration in high level noise condition
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.
Keyword : filtration, noise, local approximation method
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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
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
Seber, G. A. F., & Lee, A. J. (2003). Linear regression analysis. J. Wiley & Sons Publications. 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
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