Advanced gas turbines health monitoring systems

Adamowicz, M.; Żywica, G.

doi:10.29354/diag/89730

Artykuł - szczegóły

Tytuł artykułu

Advanced gas turbines health monitoring systems

Autorzy

Adamowicz M. , Żywica G.

Wybrane pełne teksty z tego czasopisma

http://www.diagnostyka.net.pl/

Identyfikatory

DOI

10.29354/diag/89730

Warianty tytułu

Zaawansowany system monitorowania stanu technicznego w turbinach gazowych

Języki publikacji

Abstrakty

An overview of science papers in the field of machine diagnosis has exposed increasing efforts in developing accurate and reliable engine health monitoring systems. Attempts have been made in both diagnostics and prediction of system faults. Essential limitations of the standard monitoring system are discussed in this paper as well as arguments for implementation of the Advanced Gas Turbine Health Monitoring Systems. Examples of implementation are discussed and a comparison between “Enhanced Arrangement” and “Standard Arrangements” is carried out. The individual system components are implemented today using very different methods. Performance degradation of gas turbines is described here with an approach of Condition Based Maintenance and it was shown how the classification method can help to improve equipment operation. The review of signal processing methods was carried out to present strengths and shortcomings of individual methods.

Przegląd literatury w dziedzinie diagnostyki maszyn wykazuje duże zainteresowanie środowiska naukowego opracowaniem niezawodnych i precyzyjnych metod oceny stanu technicznego napędów turbinowych. Prace te mają najczęściej na celu opracowanie systemów służących do bieżącej diagnostyki uszkodzeń pojawiających się podczas pracy jak i prognozowania przyszłych defektów. W artykule przeprowadzono ocenę najczęściej stosowanych metod diagnostycznych jak również omówiono zastosowanie „Zaawansowanego systemu monitorowania stanu technicznego turbin gazowych”. Przedstawione zostało porównanie standardowego i zaawansowanego układu diagnostyczno-sterującego. Indywidualne metody diagnostyczne zostały opisane wraz z przykładami zastosowania. Wykazano, że spadek sprawności turbiny gazowej jest ściśle związany z jej stanem technicznym, który może być stale monitorowany. Oceniono również wpływ metod klasyfikacji uszkodzeń na wykrywalność stopnia degradacji.

Słowa kluczowe

monitoring gas turbine vibrations artificial neural networks predictive model

monitorowanie turbina gazowa wibroakustyka sieci neuronowe model predykcyjny

Wydawca

Polskie Towarzystwo Diagnostyki Technicznej

Czasopismo

Diagnostyka

Rocznik

2018

Tom

Vol. 19, No. 2

Strony

77--87

Opis fizyczny

Bibliogr. 42 poz., rys.

Twórcy

autor

Adamowicz M.

adamowicz_marcin@solarturbines.com

Solar Turbines Europe S.A.

autor

Żywica G.

gzywica@imp.gda.pl

Institute of Fluid Flow Machinery, Polish Academy of Sciences, Fiszera, 14, 80-231 Gdansk, Poland

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-8fdfece9-60cc-4930-87de-3938a8a07f3c