Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/90273
Title: Features of steam turbines diagnostics
Authors: Murmanskii, I.
Aronson, K.
Murmansky, B.
Sosnovskii, A.
Novosyolov, V.
Brodov, Y.
Issue Date: 2020
Publisher: EDP Sciences
Citation: Features of steam turbines diagnostics / I. Murmanskii, K. Aronson, B. Murmansky, A. Sosnovskii, et al. . — DOI 10.1051/e3sconf/202017801059 // E3S Web of Conferences. — 2020. — Iss. 178. — 1059.
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 system, control system, vibration-based diagnostics and auxiliary equipment are already designed. We designed algorithms just in principle. Adapting them, for the PT-75/80-90 turbine we met with difficulties. 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 operation 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. © The Authors, published by EDP Sciences, 2020.
Keywords: DIGITAL STORAGE
POWER PLANTS
STEAM TURBINES
DIAGNOSTIC SYSTEMS
ENERGY EQUIPMENTS
HEAT EXPANSION
MAINTENANCE PLANNING
OPERATING CONDITION
OPERATIONAL DATA
OPERATIONAL UTILITY
SPECIFIC POWER
AUXILIARY EQUIPMENT
URI: http://hdl.handle.net/10995/90273
https://elar.urfu.ru/handle/10995/90273
metadata.dc.rights: info:eu-repo/semantics/openAccess
cc-by
SCOPUS ID: 85089498104
PURE ID: 13683882
ISSN: 2555-0403
DOI: 10.1051/e3sconf/202017801059
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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