Post-processing Improvement of Lock-in Thermography Study of MCM-L for Better Hidden Defect Localization

This paper examines the impact of post-processing of lock-in thermographic measurement data on the ability to detect and characterize in terms of geometric dimensions and location of specific types of defects in MCM-L. A thermal 3D model of a test specimen with hidden artificial defects is used and simulated lock-in thermography measurement is performed. Qualitative and quantitative assessment was performed of the correct detection and geometric dimensions characterization of the defects. The Shape Difference (SD) criteria was defined and used for qualitative and quantitative assessment of the confidence detection and characterization of defects in MCM-L. A Window Sliding Offset (WSO) approach is performed as method for improvement of the defects characterization quality. This study revel that providing information on the depth and shape of defects through the combined use of infrared thermography measurement and 3D thermal modeling can be used to determine the desired confidence levels of defects detection.