Szczegóły publikacji
Opis bibliograficzny
Operational condition monitoring of wind turbines using cointegration method / Phong B. DAO, Wiesław J. STASZEWSKI, Tadeusz UHL // W: Advances in condition monitoring of machinery in non-stationary operations : proceedings of the 5th international conference on Condition Monitoring of Machinery in Non-stationary Operations, CMMNO'2016, 12–16 September 2016, Gliwice, Poland / eds. Anna Timofiejczuk, [et al.]. — Cham : Springer International Publishing, cop. 2018. — (Applied Condition Monitoring ; ISSN 2363-698X ; vol. 9). — ISBN: 978-3-319-61926-2; e-ISBN: 978-3-319-61927-9. — S. 223–233. — Bibliogr., Abstr. — Publikacja dostępna online od: 2017-09-22
Autorzy (3)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 110145 |
|---|---|
| Data dodania do BaDAP | 2017-12-10 |
| DOI | 10.1007/978-3-319-61927-9_21 |
| Rok publikacji | 2018 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | 5th international conference on Condition Monitoring of Machinery in Non-stationary Operations |
| Czasopismo/seria | Applied Condition Monitoring |
Abstract
This paper presents a cointegration-based method for condition monitoring and fault detection of wind turbines. The proposed method is based on the residual-based control chart approach. The main idea is that cointegration is a property of some sets of nonstationary time series where a linear combination of the nonstationary series can produce a stationary residual. Then the stationarity of cointegration residuals can be used in a control chart as a potentially effective damage feature. The method is validated using the experimental data acquired from a wind turbine drivetrain with a nominal power of 2 MW under varying environmental and operational conditions. Two known abnormal problems of the wind turbine are used to illustrate the fault detection ability of the method. A cointegration-based procedure is performed on six process parameters of the wind turbine where data trends have nonlinear characteristics. Analysis of cointegration residuals—obtained from cointegration process of wind turbine data—is used for operational condition monitoring and fault/abnormal detection. The results show that the proposed method can effectively monitor the wind turbine and reliably detect abnormal problems.
