COMPARATIVE ANALYSIS OF FILTRATION METHODS IN EXPERIMENTAL STUDY OF DYNAMIC PROPERTIES OF OBJECTS

Authors

  • M. I. Gorbilchuk Ivano-Frankivsk National Technical University of Oil and Gas, 15 Karpatska Street Ivano-Frankivsk Ukraine, 76019
  • M. I. Kogutyak Ivano-Frankivsk National Technical University of Oil and Gas, 15 Karpatska Street Ivano-Frankivsk Ukraine, 76019
  • V. S. Borun Ivano-Frankivsk National Technical University of Oil and Gas, 15 Karpatska Street Ivano-Frankivsk Ukraine, 76019

DOI:

https://doi.org/10.31471/1993-9981-2020-2(45)-66-81

Keywords:

overclocking characteristic, controller, smoothing window, simulation experiment, digital filter.

Abstract

The condition for successful application at the local level of control of industrial controllers and programmable logic controllers is the presence of integrated software for automatic tuning of the parameters of the control algorithm. The dynamic properties of an object are most often determined by the results of an active experiment directly on the object through an identification procedure based on pre-processed data.

The main technologies of time series filtering are analyzed and the system of indicators for their comparison is selected. A series of simulation experiments to obtain overclocking characteristics with different degrees of addition of additive barriers to entry and exit are planned and conducted. Simple engineering algorithms of exponential, median, moving average simple and weighted and other window filters are investigated for the efficiency of smoothing in the mode of off-line and on-line processing of the obtained data on the indicators of relative root mean square and integral mean deviation from the baseline. methods.

Based on the results of the research, conclusions are drawn about the real effectiveness of on-line filtering, recommendations for their practical use on the hardware platforms of local controls and the low level of smoothing of off-line methods in a limited experimental sample. The directions of further researches in the direction of application of more difficult filtering algorithms for signals with a high level of interference are established.

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References

Steven W. Smith. The Scientist and Engineer's Guide to Digital Signal Processing. Second Edition. San Diego, California: California Technical Publishing. 1999. P. 297.

Digital signal processing : a practical approach / Emmanuel C. Ifeachor, Barrie W. Jervis.Wokingham, England ; Reading, Mass. : Addison-Wesley, 1993. 760 p.

Brown G. Robert, Smoothing, Forecasting and Prediction of Discrete Time Series. – N.Y.: Dover Phoenix Editions, 2004. 480 p.

Savitzky A., Golay M.J.E. Smoothing and Differentiation of Data by Simplified Least Squares Procedures // Anal. Chem. 1964. 36 р. 1627–1639. doi:10.1021/ac60214a047.

Astola J.,Kuosmanen P.Fundamentals of digital filtering. Boca Raton (USA): CRC Press LLC.1997. 276 p.

Nelineynaya filtratsiya signalov./ S.K.Abramov, V.I. Kortunov, V.V. Lukin.-Ucheb.posobie.-Harkov:Nats.aerokosm.un-t «Hark. aviats.in-t», 2007. 78 s.

Kalman R.E. A New Approach to Linear Filtering and Prediction Problems // J. Basic Eng. 1960. 82. P. 35–45. doi:10.1115/1.3662552.

Rabiner L., Gould B. Teoriya i primenenie tsifrovoy obrabotki signalov. M.:Mir, 1978. 838s.

Malla S. Veyvletyi v obrabotke signalov. M.: Mir, 2005. 671 s. .

Kolmogorov A.N. Interpolirovanie i ekstrapolirovanie statsionarnyih sluchaynyih posledovatelnostey // Izv. AN SSSR. Ser. Matem. 1941. 5. S. 3–14.

Wiener N. The Extrapolation, Interpolation and Smoothingof Stationary Time Series, New York: Wiley, 1949. 176 p.

Uidrou B., Stirnz S.D. Adaptivnaya obrabotka signalov./Per. s angl. pod red. Shahgildyana V.V. M.: Radio i svyaz, 1989. 440s.

Sayed A.H. Fundamentals of adaptive filtering. – NJ, Hoboken: John Wiley and Sons, Inc., 2003.- 1168 p

Diniz P.S.R. Adaptive filtering algorithms and practical implementation. Third edition. – New York, Springer Science + Business Media, 2008. 627 p.

Perry J. Kaufman Smarter Trading: Improving Performance in Changing Markets — McGraw-Hill, Inc., 1995, 257 p. — ISBN 0-07-034002-1

Kalambet Yu.A., Kozmin Yu.P., Samohin A.C. Filtratsiya shumov. Sravnitelnyiy analiz metodov// Analitika. # 5/2017(36), s. 88-101.

Oppenheim, Alan V., Ronald W. Schafer, and John R. Buck. Discrete-Time Signal Processing. Upper Saddle River, NJ: Prentice-Hall, 1999. 870 p.

Published

2020-12-28

How to Cite

Gorbilchuk, M. I., Kogutyak, M. I., & Borun, V. S. (2020). COMPARATIVE ANALYSIS OF FILTRATION METHODS IN EXPERIMENTAL STUDY OF DYNAMIC PROPERTIES OF OBJECTS. METHODS AND DEVICES OF QUALITY CONTROL, (2(45), 66–81. https://doi.org/10.31471/1993-9981-2020-2(45)-66-81

Issue

Section

METHODS AND DEVICES FOR THE TECHNOLOGICAL PARAMETERS CONNTROL