| Popis: |
Blade root bearing on a wind turbine (WTG) enables pitching of blades for power control and rotor braking and is a WTG critical component. As the size of modern WTGs is constantly increasing, this leads to relatively less rigid bearings, more sensitive to deformations, thus WTG operational reliability can be increased by continuous monitoring of blade bearing. High blade bearing friction is undesirable, as it may be associated with excessive heating of the surfaces, damage and/or inefficient operation. Thus, continuous observation of bearing friction level is crucial for blade bearing health monitoring systems. A novel algorithm for online monitoring of bearing friction level is developed combining physical knowledge about pitch system dynamics with state estimator, i.e. observer theory and signal processing assuming realistic sensor availability. Results show estimation of bearing friction torque required for condition monitoring, and a corresponding indicator signal which represents estimation of a relative friction coefficient. All data used in this work have been calculated using the aeroelastic code, LACflex applying a model of a generic multi-MW WTG. |
