Linear Time Invariant Approximation for Subspace Identification of Linear Periodic Systems Applied to Wind Turbines
Résumé
In this paper, subspace identification for wind turbines and more generally rotating periodic systems are investigated. Previous works have stressed the difficulty of modeling such systems as Linear Time Invariant and thus to apply classical Stochastic Subspace Identification. Such works plead for periodic or augmented theories. In this paper, the classical SSI can be applied to recover modal information that is related to the eigenstructure of the instrumented system despite the system excitation being modeled as non-stationary.
| Origine | Fichiers produits par l'(les) auteur(s) |
|---|