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Fatigue Usage Monitoring in Wind Turbines using Sparse Vibration Measurements



As the size of wind turbines continues to grow upwards of 10MW and the tendency to move offshore gains momentum, maintenance and repair operations become more difficult and costly. One consequence of the increased size and harsh operational environment is the increased potential for fatigue failure of structural components. Development of structural health monitoring systems capable of tracking fatigue damage is desirable. This type of system can be coupled with control mechanisms to simultaneously maximize generation and minimize operational loads which lead to fatigue damage. Various researchers have proposed the use of vibration measurements to monitor stresses and fatigue damage in the tower and blades of turbines. This paper proposes a finite element model-based state estimator that explicitly accounts for spatial correlation and the statistical properties of the excitation through knowledge of the underlying power spectral density of the wind loads. The proposed state estimator combines noise contaminated measurements of the structural response with high-fidelity finite element models to estimate the time history of stress and strain throughout the complete structure of the turbine. The approach is used to estimate loads and stresses (and their associated uncertainty) in the tower of the NREL 5MW reference turbine subjected to turbulent wind. In this paper, the method is implemented in a simulated environment where the system is a FAST model of the turbine and the estimator is formulated using a simplified finite element model of the tower. The results show that under these conditions the proposed model-based estimator provides satisfactory tracking capabilities without the need to explicitly measure or estimate wind loads.


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