Abstract

A thermographic detection and localization of unsteady flow separation on an operating wind turbine of type GE1.5sl is presented and verified by means of tufts flow visualisation. Unsteady flow separation phenomena such as dynamic stall are an undesired flow state as it causes fatigue failures, limits the turbine efficiency and increases noise emissions from the rotor blades. In comparison to available methods for stall detection on wind turbines, the presented infrared thermographic measurement approach is non-invasive, in-process capable and provides a high spatial resolution. On the basis of the thermodynamic response behaviour of the surface temperature in case of unsteady flow events, a two-step signal processing approach is proposed, to achieve the highest possible spatio-temporal resolution in the detection and localisation of stall. First, the identification of distinct maxima of the spatial standard deviation of difference images, enables to determine potential stall events in time. In the subsequent combined image evaluation with a transient approach and a principal component analysis, unsteady flow separation is detected during the occurrence of a strong wind gust with the maximum time resolution (image exposure time) as well as the maximum spatial resolution (image resolution), respectively, despite the limited signal-to-noise ratio compared to wind tunnel experiments. In addition, a geometric assignment of the image data to the rotor blade geometry is conducted, which enables a localization of the separation point on the 3 days rotor blade geometry with a maximal uncertainty of 2.3% of the chord length.

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