Enhanced defect identification by image fusion of infrared thermography and ultrasonic phased array inspection techniques

Abstract

Non-destructive testing applications are one of the most crucial steps in maintaining aviation activities in a profitable and timely manner. Infrared thermography (IRT) is a functional technique that uses the thermal radiation/temperature relationship on the inspected structure to ensure efficient detection, in particular when the defect is on a surface or near the surface. Ultrasonic (UT) inspection is an alternative technique that uses the propagation of ultrasound waves into the inspected material for defect detection. While IRT suffers from detectability problems with the increasing structure thickness, UT has inspection limitations on the surface or near-surface area according to applied frequency. Overcoming these limitations of individual methods with the synergistic effect of the fusion approach might provide more precise and apparent marks for defect detection. In this study, decision-level fusion has been applied using the maximum fusion rule to combine unimodal inspection data and compare. Impact-defected Carbon Fiber Reinforced Polymer (CFRP) composite structures have been chosen to represent aerospace structures. The results show the proposed fusion approach is promising in terms of identifying defect location, size and depth to inform further stages such as repair.