The quality control of structures and fuselages in both the wind-turbine and solar sectors is a fundamental part that allows a lifetime assessment of their elements, from its initial assembly to the recurring inspection cycles. Automating the active thermography on this scale, cannot be achieved with conventional industrial robots. Unmanned vehicles, such UAVs and UGVs, present distinctive advantages that should certainly be exploited, but, its inherent static motion is one of the main stumbling blocks towards its use in an active thermography inspection. In this paper, a two-step digital stabilization scheme has demonstrated its efficacy in real defects located in both a wind blade and solar panel. The combination of a featurebased registration algorithm and a dense parametric optical flow direct alignment has enabled the pseudo-static reconstruction of the thermograms. The adopted experimental methodology, employing a robot with both halogens and IR camera, subjected to random motions with varying speed and amplitudes, has allowed a direct repeatable comparison of static and stabilized phase images. The phase image contrast comparison of both static and dynamic tests, have been carried out on a flat bottom hole (FBH) wind blade GFRP sample, showing nearly identical phase contrast with marginal differences. Likewise, a real GFRP wind-blade impact delamination defect has also reached a close phase contrast regarding its counterpart, albeit with a decreased contrast. Additionally, the registration algorithm has been used to stitch the individual frames, derived from a dynamic recording of an electroluminescent solar panel, to allow for a unified detection and mapping of defects.
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