Technological Monitoring in the Management of the Distillation-Rectification Plant

Vasii Kyshenko , Igor Korobiichuk , Katarzyna Rzeplińska-Rykała

Abstract

The analysis of time series of the process variables was conducted by methods of nonlinear dynamics, which allowed to determine the randomness values that are based on the depth of an object prediction. The filtering of the time series was obtained experimentally, using wavelet analysis. Defined the fractal properties of chaotic information flow, correlation dimension and the Hurst parameter were defined. The intensity of the impact of a technological parameter value on the process using Kohonen maps was identified.
Author Vasii Kyshenko - National University of Food Technologies Kiev Ukraine
Vasii Kyshenko,,
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, Igor Korobiichuk (FM / IACR)
Igor Korobiichuk,,
- The Institute of Automatic Control and Robotics
, Katarzyna Rzeplińska-Rykała - Industrial Research Institute for Automation and Measurements PIAP
Katarzyna Rzeplińska-Rykała,,
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Pages165-174
Publication size in sheets0.5
Book Szewczyk Roman, Zieliński Cezary, Kaliczyńska Małgorzata (eds.): Automation 2019: Progress in Automation, Robotics and Measurement Techniques, Advances in Intelligent Systems and Computing, vol. 920, 2019, Springer International Publishing, ISBN 978-3-030-13272-9, [978-3-030-13273-6], 727 p., DOI:10.1007/978-3-030-13273-6
Keywords in Englishmonitoring, distillation-ractification facility, data mining, wavelet analysis, neural networks, uncertainty
DOIDOI:10.1007/978-3-030-13273-6_17
URL https://link.springer.com/chapter/10.1007/978-3-030-13273-6_17
Languageen angielski
Score (nominal)0
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