Validation of Ice Roughness Analysis Based on 3D-Scanning and Self-Organizing Maps
3D-scanning is an established method for the documentation of wing ice accretion. The generated 3D-data can be used to determine specific parameters of interest, like the local ice-thickness, or the surface ice roughness. The surface roughness has significant impact on the heat transfer, and therefore on the icing process itself. Insights into the effects of surface roughness on the ice accretion and the correlated aerodynamical effects contribute to the improvement of icing codes. In this paper, the surface roughness of various test specimens is determined by performing a self-organizing maps (SOM) approach for roughness point cloud analysis on data generated with a 3D-scanner. A validation of the SOM method is achieved by means of focus variation microscopy and a mathematical proof of the utilized SOM algorithm. Different scanning systems from several manufacturers are used to determine the surface of different sandpapers.