Topological-based acoustic emission data analysis for passive corrosion monitoring in prestressed concrete structures

B. Dubuc; A. Ebrahimkhanlou; K. Sitaropoulos; S. Salamone

doi:10.1117/12.2557322

22 April 2020 Topological-based acoustic emission data analysis for passive corrosion monitoring in prestressed concrete structures

B. Dubuc, A. Ebrahimkhanlou, K. Sitaropoulos, S. Salamone

Author Affiliations +

Proceedings Volume 11381, Health Monitoring of Structural and Biological Systems XIV; 113811T (2020) https://doi.org/10.1117/12.2557322
Event: SPIE Smart Structures + Nondestructive Evaluation, 2020, Online Only

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.

Citation Download Citation

B. Dubuc, A. Ebrahimkhanlou, K. Sitaropoulos, and S. Salamone "Topological-based acoustic emission data analysis for passive corrosion monitoring in prestressed concrete structures", Proc. SPIE 11381, Health Monitoring of Structural and Biological Systems XIV, 113811T (22 April 2020); https://doi.org/10.1117/12.2557322

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available