TY - JOUR A1 - Chaudhuri, Somsubhro A1 - Stamm, Michael A1 - Lapšanská, Ivana A1 - Lançon, Thibault A1 - Osterbrink, Lars A1 - Driebe, Thomas A1 - Hein, Daniel A1 - Harendt, René T1 - Infrared Thermography of Turbulence Patterns of Operational Wind Turbine Rotor Blades Supported With High‐Resolution Photography: KI‐VISIR Dataset N2 - With increasing wind energy capacity and installation of wind turbines, new inspection techniques are being explored to examine wind turbine rotor blades, especially during operation. A common result of surface damage phenomena (such as leading edge erosion) is the premature transition of laminar to turbulent flow on the surface of rotor blades. In the KI-VISIR (Künstliche Intelligenz Visuell und Infrarot Thermografie—Artificial Intelligence-Visual and Infrared Thermography) project, infrared thermography is used as an inspection tool to capture so-called thermal turbulence patterns (TTPs) that result from such surface contamination or damage. To complement the thermographic inspections, high-resolution photography is performed to visualise, in detail, the sites where these turbulence patterns initiate. A convolutional neural network (CNN) was developed and used to detect and localise turbulence patterns. A unique dataset combining the thermograms and visual images of operational wind turbine rotor blades has been provided, along with the simplified annotations for the turbulence patterns. Additional tools are available to allow users to use the data requiring only basic Python programming skills. KW - Thermography KW - Thermografie KW - Wind energy KW - Leading edge erosion KW - KI PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-615772 DO - https://doi.org/10.1002/we.2958 IS - e2958 SP - 1 EP - 9 PB - Wiley AN - OPUS4-61577 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -