Abstract:
Glass Fibre Reinforced polymer (GFRP) composites are being used in a wide range of application areas since these materials are less affected by corrosive environmental conditions and provide longer life with less maintenance. However, there are still some concerns about reinforced polymers, such as the presence of surface and sub-surface defects which influence their in service applications. To detect these defects, InfraRed Thermographic (IRT) methods show their potential usage for Non-Destructive Testing and Evaluation (NDT&E) of composite materials due to their inherent testing capabilities such as remote, whole field, quantitative and qualitative to detect surface and sub-surface defects. Thermal NDT&E is broadly categorized into passive or active approach. In passive approach, the test sample's temperature distribution is monitored in the absence of any external heat stimulus at ambient conditions. However, this may not provide ample thermal contrast to detect the defects located at deeper depths. In order to detect deeper defects inside the test specimen, an active thermography is preferred. This can be carried out by applying an external heat stimulus, to induce enough thermal contrast over the test object. The thermal gradients appear over the material during the active heating due to the changes in thermal properties of defective and sound region leading to the detection of subsurface defects. This present work highlights a spectral reshaping by introducing a Gaussian window on the captured thermal profile in a frequency modulated thermal wave imaging and named as Gaussian Windowed Frequency Modulated Thermal Wave Imaging (GWFMTWI) technique. Further various multi-transform techniques (time and frequency domain based) have been introduced in order to test sub-surface defect detection capabilities in chosen GFRP sample. Comparison has been made with the non-stationary linear frequency modulated thermal wave imaging technique in terms of depth scanning capability. Results obtained from GWFMTWI clearly show better detection potential with improved test resolution and sensitivity.
