Non-destructive quantitative evaluation of delamination depth and thickness in GFRP using microwave reflectometry

Abstract

Glass fiber reinforced polymer (GFRP) laminates are extensively used across various engineering fields. However, the occurrence of internal delamination defects during its production and usage can severely jeopardize equipment safety. Consequently, there's a pressing need to quantitatively detect both the thickness and depth (i.e., the distance from the delamination defects to the GFRP laminates' surface) of these delamination defects. To date, most research efforts fall short in providing an evaluation method that concurrently addresses both defect thickness and depth. In this study, we introduce a far-field quantitative evaluation method based on microwave propagation theory. Unique microwave reflection signals emerge due to variations in defect thickness and depth. By utilizing these distinct signals and incorporating parameters such as signal frequency, defect dimensions, GFRP plate thickness, and its permittivity, we developed a model that relates echo signals to defect characteristics. This model serves as an effective tool for defect detection and quantification. Simulations and experiments validate that our method can simultaneously detect and quantify defect depth and thickness through a single reflection signal. By monitoring changes in microwave reflectivity amplitude, we successfully detected and quantified delamination defect of 30 μm. The quantitative error for defect depth remains below 0.15 mm, with an average error of 0.048 mm. Meanwhile, the error for defect thickness does not exceed 10 μm, averaging at 3.75 μm. Importantly, the theoretical minimum detectable value can reach several microns. Furthermore, this method's detection accuracy remains little affected by the stand-off distance, offering a notable advantage in practical applications.