Abstract
The identification of the operational Wind Turbine (WT) dynamics is a challenging problem, due to both the complex dynamics and the non-stationarity of the vibration response. In this study the novel class of Generalized Stochastic Constraint (GSC) Time-dependent ARMA models is used for the identification of the non-stationary characteristics of acceleration vibration signals acquired in the tower top of an operating WT, in the fore-aft and lateral directions. The results demonstrate the improved performance of GSC-TARMA models compared to their conventional Smoothness Priors (SP) and Functional Series (FS) counterparts. The obtained models confirm the presence of cyclo-stationary and broader non-stationary behavior in WT vibration. The model based frozen time-varying modes of vibration are analyzed, and the modal components of the vibration accelerations are pictorially presented on the plane defined by the fore-aft and lateral axes.
Original language | English |
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Journal | Key Engineering Materials |
Volume | 569-570 |
Pages (from-to) | 587–594 |
ISSN | 1013-9826 |
DOIs | |
Publication status | Published - Jul 2013 |
Keywords
- Generalized stochastic constraint TARMA models
- Output-only modal analysis
- Time-varying Auto-Regressive Moving Average (TARMA) models
- Wind turbine vibration