Conference proceeding
Topological-based acoustic emission data analysis for passive corrosion monitoring in prestressed concrete structures
HEALTH MONITORING OF STRUCTURAL AND BIOLOGICAL SYSTEMS IX, v 11381, pp 113811T-113811T-8
01 Jan 2020
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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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Details
- Title
- Topological-based acoustic emission data analysis for passive corrosion monitoring in prestressed concrete structures
- Creators
- B. Dubuc - The University of Texas at AustinA. Ebrahimkhanlou - Univ Texas Austin, Smart Struct Res Grp, Austin, TX 78712 USAK. Sitaropoulos - The University of Texas at AustinS. Salamone - The University of Texas at Austin
- Contributors
- P Fromme (Editor)Z Su (Editor)
- Publication Details
- HEALTH MONITORING OF STRUCTURAL AND BIOLOGICAL SYSTEMS IX, v 11381, pp 113811T-113811T-8
- Series
- Proceedings of SPIE
- Publisher
- Spie-Int Soc Optical Engineering
- Number of pages
- 8
- Grant note
- 16-337 / Texas Department of Transportation (TxDOT)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:000624394000022
- Scopus ID
- 2-s2.0-85087065590
- Other Identifier
- 991021889908504721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Materials Science, Characterization & Testing
- Mechanics
- Optics