Generalized stochastic constraint TARMA models for in-operation identification of wind turbine non-stationary dynamics

Luis David Avendaño-Valencia, Spilios D. Fassois

Research output: Contribution to journalConference articleResearchpeer-review

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 languageEnglish
JournalKey Engineering Materials
Volume569-570
Pages (from-to)587–594
ISSN1013-9826
DOIs
Publication statusPublished - Jul 2013

Keywords

  • Generalized stochastic constraint TARMA models
  • Output-only modal analysis
  • Time-varying Auto-Regressive Moving Average (TARMA) models
  • Wind turbine vibration

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