Updating of a Wind Turbine Model for the Evaluation of Methods for Operational Monitoring Using Inertial Measurements

Rotor blades with embedded sensors are envisioned to provide estimators for the operational deflection of the blade for current control systems, monitors of fatigue accumulation for reduced operation and maintenance costs, and observers for next generatio n smart adaptive wind turbines. Smart adaptive wind turbines will have active aerodynamic load control devices distributed on the rotor blade to control s mall time constant loading associated with turbulence an d unattached flow to improve performance and reduce fatigue. The prospect of this technology is to inc rease energy capture at low wind speeds and decrease maintenance costs by shedding loads at high wind speeds. In addition to controls applications, the se nsored rotor blades will provide estimates of the accumula ted fatigue cycles that can be used to predict when rotor blade maintenance may be needed. This capability can be used to reduce downtime and repair costs because scheduled maintenance is typically less expensive t han unscheduled maintenance. A reliable sensor-based operational monitoring method is a critical component in the smart turbine envisioned by this research . The following work focuses on the development of a lumped parameter model of a wind turbine, using the NREL FAST to MSC.ADAMS© translator, that will be used to study and validate operational monitoring methods based on inertial measurements. The model produced by the FAST to ADAMS translator is shown to have a mismatch with experimentally acquired natural frequencies. Therefore, the ADAMS model is updated by a component analysis of the tower and rotor blades and by the development of a calibrated flexible beam element representation of the low speed shaft. A modal analysis of the resulting model is then compar ed with an experimental modal analysis of the wind turbine. Lastly, turbine models in FAST, rigid low speed s haft ADAMS, and flexible low speed shaft ADAMS are simulated in three wind conditions, one of which is 8 m/ s wind with 0.2 vertical wind shear and IEC Class B t urbulence intensity, for initial investigations of the relationship between wind conditions and simulation-based model frequency content.

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