De-bonding detection on a cfrp laminated concrete beam using self sensing-based multi-scale actuated sensing with statistical pattern recognition

This paper reports a novel structural health monitoring (SHM) technique for detecting de-bonding defects between a concrete beam structure and a CFRP (Carbon Fiber Reinforced Polymer) sheet attached to the concrete surface. To achieve this purpose, a multi-scale actuated sensing system with a self-sensing circuit using piezoelectric active sensors was applied to a CFRP laminated concrete beam structure. In the self-sensing based multi-scale actuated sensing system, a wide frequency-band structural response from the self-sensed impedance measurements and a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement were utilized to localize the de-bonding defects. Furthermore, in order to quantify the de-bonding levels, the supervised learning-based statistical pattern recognition was implemented by composing a two-dimensional (2D) plane using the damage indices extracted from the impedance and guided wave features. The different levels of de-bonding defects inflicted artificially on the CFRP laminated concrete beam structure were investigated to confirm the effectiveness of the proposed SHM approach.