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Registration Number

0224U032027, 0121U113500 , R & D reports

Title

Scientific foundations for the construction of distributed multi-level systems (RBRS) for control, management and diagnostics of technological objects and processes (including geographic information systems) based on the latest computer-integrated technologies and the industrial Internet of things

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Head

Zamikhovskyi Leonid M., Доктор технічних наук

Registration Date

12-07-2024

Organization

Ivano-Frankivsk National University of Oil and Gas

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 Object of research: theoretical and applied problems of developing methods of parametric diagnostics of the technical state of the gas pumping unit based on discriminant analysis, diagnostic signs of the vibration state of the gas pumping unit, single-frequency useful signal in information systems, inverter stations of cathodic protection of pipelines, simulation models of control systems of technological objects , physical and informational processes of controlling leaks from pipelines. Purpose of work: Development and implementation of hardware and software distributed systems of monitoring, control, management and diagnostics of objects and processes on the basis of the developed scientific foundations for their construction and modern information technologies at the objects of the oil and gas complex and industrial production. Research methods and equipment: methods of mathematical modeling and experimental research in diagnostic, control and management tasks; wavelet transform; methods of discriminant analysis; methods of evaluating characteristics; signal processing in real time; basic methods of systems theory and automatic control, methods of electromagnetic circuits and digital signal processing, mathematical methods of operations research; simulation modeling methods; methods of control of physical and informational processes. To solve the scientific and technical problem of designing a system for diagnosing the technical condition of a gas pumping unit, an analysis of existing methods of signal analysis and processing was carried out. Methods such as the Fourier transform, discriminant analysis methods, wavelet transform, artificial neural networks, discrete cosine transform, and autocorrelation functions are considered. The possibilities of each of the methods were studied, it was found that each of them can provide processing and analysis at the appropriate stage. It is shown that DCT and autocorrelation functions can be used for the initial processing

Product Description

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Ivaniuk Nataliia I.
Belei Oksana I.
Burda Myroslav Yo.
Voropaeva Anna A.
Eliiashiv Oleh M.
Zikratyi Serhii V.
Zamikhovska Olena L.
Zamikhovskyi Leonid M.
Kuzmyn Oleh V.
Levytskyi Ivan T.
Mohylin Vitalii B.
Nykolaichuk Mykola Ya.
Pavlyk Volodymyr V.
Pankiv Khrystyna V.
Pankiv Yurii V.
Striletskyi Yurii Yo.
Shtaier Lidiia O.

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2024-07-12