Image Processing for Automated Flaw Detection in Pulsed Thermography

Infrared (IR) thermography has evolved in recent years from being an emerging nondestructive testing (NDT) technique to a viable approach for both aerospace manufacturing and in-service inspections. One of the drawbacks of thermography techniques is that no standard signal processing has been universally adopted and that different algorithms yield different sizing results. Additionally, the data interpretation is not as simple as with other NDT techniques. In this paper the most common signal processing techniques applied to pulsed thermography, which include derivative processing, pulsed phase thermography and principal component analysis, are applied in an attempt to simplify the damage detection and sizing process. The pulsed thermography experiments were carried out on 25 impacted panels made of carbon fiber epoxy material. Despite using similar panels and the same experiment parameters, the damage detection and sizing processes are not straight forward. It is concluded that some algorithms provide easier detection capability than others. However, on their own, the different algorithms lack the robustness to make the damage detection and sizing processes reliable and fully automated.