Sub-Surface Defect Depth Approximation in Cold Infrared Thermography

Abstract

Detection and characterisation of hidden corrosion are considered challenging yet crucial activities in many sensitive industrial plants where preventing the loss of containment or structural reliability are paramount. In the last two decades, infrared (IR) thermography has proved to be a reliable means for inspection of corrosion or other sub-surface anomalies in low to mid thickness metallic mediums. The foundation of using IR thermography for defect detection and characterisation is based on active thermography. In this method of inspection, an external excitation source is deployed for the purpose of stimulating thermal evolutions inside objects. The presence of sub-surface defects disrupts the evolution of electromagnetic pulse inside an object. The reflection of altered pulse at the surface can be recorded through thermal camera in the form of temperature anomalies. Through authors’ previous works, cold thermography has shown that it can be a viable defect detection alternative to the most commonly used means of active thermography, known as heating. In the current work, the characterisation of defect dimensions, i.e., depth and diameter, has been explored. A simple analytical model for thermal contrast over defect is used in order to approximate the defect depth and diameter. This is achieved by comparing the similarities of the model and the experimental contrast time-series. A method of time-series similarity measurement known as dynamic time wrapping (DTW) is used to score the similarity between a pair of model and experiment time-series. The final outcome of the proposed experimental setup has revealed that there is a good potential to predict the metal loss of up to 50% in mid-thickness substrate even by deploying a less accurate nonradiometric thermal device and no advanced image processing.