Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Tytuł pozycji:

Conditions for increasing the recognition of degradation in thermal-flow diagnostics, taking into account environmental legal aspects

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
Źródło:
Journal of Power Technologies; 2023, 103, 1; 33-48
1425-1353
Język:
angielski
Prawa:
CC BY: Creative Commons Uznanie autorstwa 3.0 Unported
Dostawca treści:
Biblioteka Nauki
Artykuł
  Przejdź do źródła  Link otwiera się w nowym oknie
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.

Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies