Sub-surface metal loss defect detection using cold thermography and dynamic reference reconstruction (DRR)

Corrosion is considered a destructive phenomenon that affects almost all metals. Active infrared thermography is an online (no result delay) and non-intrusive (no process disruption) method of non-destructive testing (NDT), which has shown profound capabilities of detecting sub-surface metal loss. However, thermal reflections, non-uniform stimulation and lateral heat diffusion will remain as the most undesirable phenomena preventing the effective observation of sub-surface defects. This becomes more challenging when there is no a priori knowledge of the anomalies to effectively distinguish between defective and non-defective areas. In this work, cooling stimulation is considered as the thermal excitation mean as 1- a very few reports in this regard have been mentioned in the body of literature and 2- a dynamic setup was achieved that is found to be effective to minimise the possibility of disrupting reflections or artefacts registered by thermal camera similar to the case of using heating stimulation. A state-of-the-art prototype mechanism was manufactured. This equipment includes a carrier carrying a thermal camera and a cooling medium reservoir operating in reciprocating motion setup. This equipment is able to scan the test piece while cold stimulation is in operation, and immediately after that the camera registers the thermal evolution. An automated contrast enhancement pipeline using a variation of adaptive histogram equalisation (AHE) combined with principal component analysis (PCA) method was developed. The enhanced image results demonstrated the capability of accurately detecting sub-surface metal loss as low as 37.5% as well as an efficiently reconstructed reference (non-defective) area.

Automated summary

Corrosion is a destructive phenomenon affecting almost all metals, and active infrared thermography is an online and non-intrusive method of non-destructive testing that has shown capabilities of detecting sub-surface metal loss. However, challenges such as thermal reflections, non-uniform stimulation, and lack of a priori knowledge hinder the effective observation of sub-surface defects.