KEYWORDS: Corrosion, Acoustic emission, Data modeling, Data analysis, Diagnostics, Visualization, Data acquisition, Sensors, Structural health monitoring
The potential of topological data analysis (TDA) to aid acoustic emission (AE) in revealing early signs of corrosion in prestressed concrete has recently been demonstrated by the authors. This paper serves to extend the experimental investigation of this structural health monitoring potential. The topological method was evaluated in accelerated corrosion testing of control and weathered prestressed concrete specimens. The results highlight the potential of TDA to aid in extracting corrosion information from AE data. Further, with TDA aiding traditional AE monitoring, there is potential for early and reliable indication of concrete cracking, prior to the appearance of external visual signs. In addition, the results demonstrate the potential generalizability of the method toward existing in-service prestressed concrete structures. Lastly, the AE-based corrosion indicators are combined with a hidden Markov modeling framework. The capability of the framework for automated corrosion diagnostics is demonstrated through training and testing between the two specimens.
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