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Wyświetlanie 1-2 z 2
Tytuł:
Monitoring the gas turbine start-up phase on a platform using a hierarchical model based on multi-layer perceptron networks
Autorzy:
Niksa-Rynkiewicz, Tacjana
Witkowska, Anna
Głuch, Jerzy
Adamowicz, Marcin
Powiązania:
https://bibliotekanauki.pl/articles/32898208.pdf
Data publikacji:
2022
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
industrial gas turbine
start-up monitoring
artificial neural network
hierarchical system
Opis:
Very often, the operation of diagnostic systems is related to the evaluation of process functionality, where the diagnostics is carried out using reference models prepared on the basis of the process description in the nominal state. The main goal of the work is to develop a hierarchical gas turbine reference model for the estimation of start-up parameters based on multi-layer perceptron neural networks. A functional decomposition of the gas turbine start-up process was proposed, enabling a modular analysis of selected parameters of the process. Real data sets obtained from observations of the turbo-generator set located on a North Sea platform were used.
Źródło:
Polish Maritime Research; 2022, 4; 123-131
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Conditions for increasing the recognition of degradation in thermal-flow diagnostics, taking into account environmental legal aspects
Autorzy:
Drosińska-Komor, Marta
Głuch, Jerzy
Brzezińska-Gołębiewska, Katarzyna
Piotrowicz, Michał
Ziółkowski, Paweł
Powiązania:
https://bibliotekanauki.pl/articles/41181077.pdf
Data publikacji:
2023
Wydawca:
Politechnika Warszawska, Instytut Techniki Cieplnej
Tematy:
steam turbine
genethic algorithm
diagnostic
coal-fired power plant
efficiency analysis
turbina parowa
algorytm genetyczny
diagnostyka
elektrownia węglowa
Opis:
The ever-increasing demand for electricity and the need for conventional sources to cooperate with renewable ones generates the need to increase the efficiency and safety of the generation sources. Therefore, it is necessary to find a way to operate existing facilities more efficiently with full detection of emerging faults. These are the requirements of Polish, European and International law, which demands that energy facilities operate with the highest efficiency and meet a number of restrictive requirements. In order to improve the operation of steam power plants of electric generating stations, thermal-fluid diagnostics have been traditionally used, and in this paper a three-hull steam turbine, having a high-pressure, a medium-pressure and a low-pressure part, has been selected for analysis. The turbine class is of the order of 200 MW electric. Genetic algorithms (GA) were used in the process of creating the diagnostic model. So far, they have been used for diagnostic purposes in gas turbines, and no work has been found in the literature using GA for the diagnostic process of such complex objects as steam turbines located in professional manufacturing facilities. The use of genetic algorithms allowed rapid acquisition of global extremes, that is efficiency and power of the unit. The result of the work undertaken is the possibility to carry out a full diagnostic process, meaning detection, localization and identification of single and double degradations. In this way 100 % of the main faults are found, but there are sometimes additional ones, and these are not perfectly identified especially for single time detection. Thus, the results showed that with a very high success rate the simulated damage to the geometrical elements of the steam turbine under study is found.
Źródło:
Journal of Power Technologies; 2023, 103, 1; 33-48
1425-1353
Pojawia się w:
Journal of Power Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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