Acoustic Emission Monitoring of Bond Deterioration in GFRP-Reinforced Concrete Members: An Entropy-Based Approach

Abstract

The primary objective of acoustic emission (AE) monitoring is to accurately detect imminent critical damage, preventing premature failure by analysing the dynamic evolution of AE parameters. This study introduces AE entropy, a distinctive parameter derived from Shannon's entropy, employed to monitor the bond degradation between glass fibre-reinforced polymer (GFRP) rebars and the concrete interface in GFRP-reinforced concrete elements. Characteristic AE parameters have been synchronously collected during flexural bond tests, and information entropy and weighted information entropy, composed of typical AE characteristic parameters based on Shannon’s information entropy theory in the time domain, have been defined. Findings indicate that, with increasing bond stress, the specimens exhibit a trend characterized by "decreasing, stabilizing, and then increasing" in both AE characteristic parameters and weighted information entropy. The information entropy value shows fluctuations during any damage associated with GFRP-concrete bond deterioration. At peak bond stress values, information entropy values experience a rapid surge, indicating significant deterioration. The evolution process of debonding between GFRP rebar and concrete, switching between a chaotic state that develops randomly and an organized state that produces in order, follows specific laws (disordered–ordered–disordered), corresponding well to AE characteristic parameters weighted information entropy. Moreover, entropy values, both individual and weighted, when correlated with bond stress and slip variations in the test specimens, distinctly outline and predict various stress transfer mechanisms between the GFRP bar and concrete. In summary, this research underscores the utility of AE entropy as a valuable tool for damage monitoring in GFRP-reinforced structures. Its ability to capture microstructural deformations positions AE entropy as a promising candidate for improving critical damage identification and preventing premature failure