Debonding damage detection in CFRP-reinforced steel structures using scanning probabilistic imaging method improved by ultrasonic guided-wave transfer function.

The application of Carbon Fiber Reinforced Polymer (CFRP) in reinforcing steel structures is widely recognized. However, there is relatively little research on the localization and imaging of debonding damage in CFRP-reinforced steel structures. This paper proposes a probabilistic imaging method improved by ultrasonic guided-wave transfer function to localize debonding damage in CFRP-reinforced steel structures. Firstly, this study proposes a waveform feature index that exhibits strong robustness against debonding damages while exhibiting minimal susceptibility to environmental disturbances, which enhances the detection capability for small-scale debonding damages compared to traditional linear indices. Secondly, the proposed method replaces the conventional fixed array with a dynamic scanning approach. This method achieves 2D debonding damage imaging by leveraging information solely from orthogonal directions, which not only drastically reduces the number of sensors but also enables flexible adjustment of the detection area, thereby enhancing its applicability. Thirdly, the proposed waveform feature index is independent of the amplitude of the excitation/receiving signal. Therefore, the proposed method maintains accurate localization of debonding damage during damage imaging detection, regardless of variations in coupling conditions between the sensor and the structure under inspection. The efficacy of the proposed method is validated through comprehensive numerical simulations and experiments. The results demonstrate its ability to accurately detect and localize damage in CFRP-reinforced steel plate structures, offering an effective and precise way for early debonding detection.