Monitoring a 5 MW offshore wind energy converter—Condition parameters and triangulation based extraction of modal parameters

Author-Highlights
• New, automated triangulation-based extraction of modal parameters.
• Clear traceability of parameter-sensitivities for automation of presented procedure.
• Verification of modal parameters for several thousand data sets.
• Classification of Eigenfrequencies and condition parameter by Affinity Propagation—64 setups.
• Introduction of a weighted condition parameter, inspection of three-dimensional mode shapes.

The test field alpha ventus is the first operating German offshore parks for wind energy. Twelve Wind Energy Converters (WECs) of the 5 MW-class are installed, both, for commercial and research reasons. Due to upcoming mass production and uncertainties in loads and behaviour, monitoring the foundation of these structures was desired. Two goals addressed are the extraction of modal parameters for model validation and the estimation of condition parameters to allow a hypothesis of the system's state.In a first step the largedatabase is classified by Environmental and Operational Conditions (EOCs) through affinity propagation which is a new approach for Structural Health Monitoring (SHM) on wind turbines. Further, system identification through data driven stochastic subspace identification (SSI) is performed. A new, automated approach called triangulation-based extraction of modal parapeters (TEMP), using stability diagrams, is a key focus of the presented research. Finally, extraction of condition parameters for tower accelerations classified by EOCs, based on covariance driven SSI and Vector Auto-Regressive (VAR) Models, is performed for several observation periods from one to 16 weeks. These parameters and their distributions provide a base line for long term observations.