Optimal configuration strategies for multiple active infrared thermography in defect detection of silicone rubber-epoxy bonded composite materials

Active infrared thermography (AIT) demonstrates significant potential in detecting internal defects in silicone rubber-epoxy bonded composite materials. However, there remains a notable gap in establishing optimal configurations for primary multiple AIT parameters (waveform, frequency, and excitation time) and thermal wave features when detecting interfacial defects. This study conducts a comprehensive comparative analysis of these parameters and features, to determine the optimal multiple AIT configuration strategies. Initially, a thermal response model and various feature extraction algorithms were developed. Subsequently, the effects of modulation frequency and excitation time on feature thermograms were analyzed. Following that, a comparative study on the imaging effects of linear and logarithmic frequency modulation signals across different frequency bands was conducted. Lastly, a theoretical analysis of the optimal modulation methods among different thermal excitation modulations was performed. It was found that single-frequency sinusoidal modulation at 0.01 Hz has the best detection performance for silicone rubber-epoxy bonded composite materials where the silicone rubber is 3 mm thick. The findings provide valuable insights into the optimal configuration of primary AIT parameters and features, offering significant practical implications for real-world detection applications.