The team of Near Earth Autonomy and Carnegie Mellon University propose to use active thermography together with novel scan strategies and thermal image processing to efficiently detect subsurface corrosion in military and commercial aircraft using non-contact autonomous drones. The drones will use low size, weight, power, and cost (SWaP-C) heat sources to thermally excite the aircraft surface to observe regions of differential heat transfer within the material that will inform whether corrosion is present underneath, even before it is visible. While active thermography has been explored previously for corrosion detection in laboratory settings, deploying it successfully in the field at scale using drone platforms presents significant challenges. Autonomous drones equipped with thermal imaging cameras and active heating sources provide an innovative approach to corrosion detection that does not require direct contact with the aircraft surface. The active thermography technique involves exciting a small area of the surface with a heat lamp or other controllable heat source, then observing the thermal response using an infrared camera. Defects like subsurface corrosion will interrupt heat flow, showing up as "hot spots" or regions of slower cooling compared to surrounding intact areas. By scanning systematically with a drone, thermal data is gathered far more quickly across large areas compared to manual inspection. Data is sent to the cloud environment for processing, where advanced corrosion detection algorithms analyze the images to detect anomalies. Suspect regions can be marked for further inspection by maintenance personnel. The drone-based approach automates detection, improves coverage compared to spot inspections, and eliminates scaffolding/surface preparation needs. Advanced image processing techniques like pulsed phasing and principal component analysis can help reveal subtle thermal discontinuities caused by hidden corrosion, thereby enhancing sensitivity to subsurface defects. Machine learning algorithms trained on datasets of corroded and healthy structure can automatically detect corrosion with minimal false positives. The heating sources used for active thermography must have low SWaP-C to be suitable for drones. Recent innovations in technologies like heat lamps and directed energy provide compact, energy efficient options for thermally exciting the surface using drones. In summary, a drone-based corrosion detection system with active thermography capability will provide automated, rapid, non-contact inspection without requiring costly downtime for the aircraft. This has the potential to improve safety and decrease maintenance costs through early identification of structural defects before they become critical. Ongoing research aims to further enhance sensitivity, range, and corrosion characterization ability to make active thermography drones even more valuable for the aerospace industry.
