Novel Insights on Spatio-Temporal Analysis for Frequency Modulated Thermal Wave Imaging Using Principal Component Analysis on Glass Fibre Reinforced Polymer Material

Abstract

Non-Destructive Testing and Evaluation (NDT&E) is being developed across various segments of the industry for detecting the presence of defects occurring either during the manufacturing or its in-service stage such as cracks, voids, delamination, etc. in a wide variety of materials. Among various NDT&E methodologies, InfraRed Thermography (IRT) gained importance due to its remote, whole-field, safe, and quantitative assessment of industrial and biomaterials. These merits make the IRT a promising approach for inspecting and evaluating various composite structures widely used in aerospace and defense applications. Among the recently introduced IRT techniques, Frequency Modulated Thermal Wave Imaging (FMTWI) ensures the feasibility of implementing moderate peak power heat sources in single experimentation compared to conventional pulse-based and sinusoidally modulated lock-in thermography. The present work enhances the scope of the Principal Component Analysis (PCA)-based IRT named Principal Component Thermography (PCT) by pioneering the application of temporally and spatially reconstructed FMTWI dataset for the first time. This paper explores the PCT-based data processing algorithm to test and evaluate artificially simulated blind hole defects in a Glass Fibre Reinforced Polymer (GFRP) material. The results of PCT obtained for the FMTWI technique highlight the merits of the data-reduced feature map known as Empirical Orthogonal Thermogram (EOT) along with its defect detection capabilities by considering the optimal Principal Component (PC) to reduce the effect of uneven heating on the sample.