Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/111293
Title: Turbine Diagnostics: Algorithms Adaptation Problems
Authors: Murmanskii, I. B.
Aronson, K. E.
Murmansky, B. E.
Zhelonkin, N. V.
Brodov, Y. M.
Issue Date: 2020
Publisher: WITPress
WIT Press
Citation: Turbine Diagnostics: Algorithms Adaptation Problems / I. B. Murmanskii, K. E. Aronson, B. E. Murmansky et al. // WIT Transactions on Ecology and the Environment. — 2020. — Vol. 246. — P. 19-27.
Abstract: Enterprises of energy equipment and operational utilities set sights on diagnostic systems. This is necessary for state control and maintenance planning of steam turbines. It is useful for digitalization purposes too. So far, some mathematical systems are already used. Algorithms for flow part, heat expansion systems, control systems, vibration-based diagnostics and auxiliary equipment have already been designed. We have designed algorithms just in principle. We met difficulties adapting them for the PT-75/80-90 turbine. Firstly, we should connect them to a single interface. Secondly, adaptation should include features of the equipment, its state (if not new), even operating conditions. Diagnostic signs for each turbine are the most important. We define them based on the operational data. When adapting the algorithms, we reconsider the signs list. We also estimate its coefficients of importance again. This requires experts to study designs, calculations, and modelling. We also analyzed a large amount of operational data at various power plants. To define the state we use tests. Adapting is based on the modes of a specific power station. Following this strategy, we adapt general algorithms for various turbines. © 2020 WIT Press.
Keywords: ALGORITHMS ADAPTING
BIG DATA
DIAGNOSTIC SYSTEM
DIGITALIZATION
MAINTENANCE
MONITORING
POWER PLANT
STATE CONTROL
STEAM TURBINE
VIBRATIONBASED DIAGNOSTICS
URI: http://hdl.handle.net/10995/111293
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85103762290
PURE ID: 21172822
ISSN: 1746-448X
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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