Detection and localization of flow separation on wind turbines by means of unsteady thermographic flow visualization

Oehme, Felix; Sorg, Michael; Fischer, Andreas

doi:10.1088/1742-6596/2265/2/022101

Cited by 1 publication

(2 citation statements)

References 13 publications

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“…Parrey et al (2021) improved the detection of the local wedgeshaped premature flow transitions in thermograms from in-service wind turbines, while data acquired during yawed operation was not considered. Oehme et al (2022a), Oehme et al (2022b) studied turbulent flow separation on an operating wind turbine under the assumption of a constant yaw angle. They applied the restricted geometric mapping from Dollinger et al (2019).…”

Section: State Of the Artmentioning

confidence: 99%

“…To verify the geometric mapping algorithm, a wind turbine rotor blade was equipped with aluminum markers, whose positions were known. The details of this setup are documented in Oehme et al (2022a), Oehme et al (2022b). The position of the markers was also determined in a picture of the rotor blades and subsequently fed into the geometric mapping algorithm, which calculates the chord position of the marker.…”

Section: Analysis Of the Error Correction Potentialmentioning

confidence: 99%

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Flow visualization by means of 3D thermography on yawing wind turbines

Fischer,

Parrey,

Balaresque

et al. 2023

Front. Energy Res.

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Thermographic flow visualization is an established tool for analyzing the actual flow behavior of real wind turbines in operation. While the laminar-turbulent flow transition as well as the beginning of flow separation can be localized in the thermographic image of a rotor blade, the corresponding positions on the 3d rotor blade surface are not yet known. To compensate the disturbing cross-influence of the wind turbine motion such as the yawing on the projected chord position of an identified flow feature, a geometric mapping algorithm of the 2d thermographic image on the 3d rotor blade is presented. With no geometric mapping, a significant error can occur depending on the camera location and orientation with respect to the location and orientation of the wind turbine. For the considered example, the maximal chord position error occurs for flow features at a relative chord location between 30% and 40%. If the yaw angle changes between ±30° and no correction is applied, the position error amounts up to ±17% of the chord length when the blade is observed above the nacelle. This example illustrates the necessity for an error correction. After its verification, the geometric mapping approach is applied on a thermographic image series from a field measurement campaign on a yawing wind turbine. For this purpose, the yaw angle is additionally measured with a laser scanner. In comparison with no geometric mapping, the corrected flow visualization of the laminar-turbulent transition during yawing reveals the actual mean chord location that is 20% of the chord length larger, a shift of the chord location that is almost one order of magnitude larger, and a chordwise location increase instead of a decrease. As a result, the geometry mapping is therefore considered applicable to advance thermographic flow visualization for the analysis of flow dynamics on yawing and pitching wind turbines, and in future even during one rotor revolution.

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