Abstract
The complex dynamics of operational wind turbine (WT) structures challenges the applicability of existing structural health monitoring (SHM) strategies for condition assessment. At the center of Europe’s renewable energy strategic planning, WT systems call for implementation of strategies that may describe the WT behavior in its complete operational spectrum. The framework proposed in this paper relies on the symbiotic treatment of acting environmental/operational variables and the monitored vibration response of the structure. The approach aims at accurate simulation of the temporal variability characterizing the WT dynamics, and subsequently at the tracking of the evolution of this variability in a longer-term horizon. The bi-component analysis tool is applied on long-term data, collected as part of continuous monitoring campaigns on two actual operating WT structures located in different sites in Germany. The obtained data-driven structural models verify the potential of the proposed strategy for development of an automated SHM diagnostic tool.
Highlights
IntroductionThe complexity related to the interacting subsystems of wind turbine (WT) structures (namely the rotating blades, moving yaw mechanism, and pitch angle changes) and the alternating aerodynamic loads redefining the operational regime, result in a complex vibrating system necessitating adoption of efficient monitoring and diagnostic methods
The complexity related to the interacting subsystems of wind turbine (WT) structures and the alternating aerodynamic loads redefining the operational regime, result in a complex vibrating system necessitating adoption of efficient monitoring and diagnostic methods
The novel approach proposed relies on observation of the time-variability of WT structures in a dual-reference time-frame, namely: (a) the short-term scale, relating to periodic fluctuations induced by the rotational nature of components of the WT system itself as well as the nature of the input loads, and (b) the long-term scale, in which phenomena associated to constantly changing loading and environmental conditions perturb structural behavior
Summary
The complexity related to the interacting subsystems of WT structures (namely the rotating blades, moving yaw mechanism, and pitch angle changes) and the alternating aerodynamic loads redefining the operational regime, result in a complex vibrating system necessitating adoption of efficient monitoring and diagnostic methods. Extracted a structural health index for a prototype of an operating 5MW WT, by removing temperature effects from selected natural frequency estimates based on a principal component analysis method Novel strategies integrating both structural response data and influencing agents within mathematical models have proven successful in several recent studies. The first aspect is demonstrated via implementation on two separate operating WT structures located in Germany for an extended period of monitored structural responses and larger set of influencing agents This is accomplished by a bi-component tool, which combines the parametric smoothness priors time varying autoregressive moving average (SP-TARMA) method, for identifying structural performance indicators (short-term framework), with a PCE probabilistic model, for quantifying the uncertainty in the identified structural performance indicators (long-term framework). The results of the presented study demonstrate the effectiveness and high potential of the proposed method for automated condition assessment of large real world structures, operating in a wide range of conditions
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