- Tytuł:
- ART-2 artificial neural networks applications for classification of vibration signals and operational states of wind turbines for intelligent monitoring
- Autorzy:
-
Barszcz, T.
Bielecki, A.
Wójcik, M
Bielecka, M. - Powiązania:
- https://bibliotekanauki.pl/articles/329678.pdf
- Data publikacji:
- 2013
- Wydawca:
- Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
- Tematy:
-
wind turbines
monitoring
ART neural network - Opis:
- In recent years wind energy is the fastest growing branch of the power generation industry. The largest cost for the wind turbine is its maintenance. A common technique to decrease this cost is a remote monitoring based on vibration analysis. Growing number of monitored turbines requires an automated way of support for diagnostic experts. As full fault detection and identification is still a very challenging task, it is necessary to prepare an “early warning” tool, which would focus the attention on cases which are potentially dangerous. There were several attempts to develop such tools, in most cases based on various classification methods. As the ART neural networks are capable to perform efficient classification and to recognize new states when necessary, they seems to be a proper tool for classification of vibration signals of bearing in gears in wind turbines. The verification of ART-2 networks efficiency in this task is the topic of this paper.
- Źródło:
-
Diagnostyka; 2013, 14, 4; 21-26
1641-6414
2449-5220 - Pojawia się w:
- Diagnostyka
- Dostawca treści:
- Biblioteka Nauki
Artykuł