TY - GEN
T1 - Acoustic emission and digital image correlation as complementary techniques for laboratory and field research
AU - Carmi, Rami
AU - Vanniamparambil, P. A.
AU - Cuadra, J.
AU - Hazeli, K.
AU - Rajaram, S.
AU - Guclu, U.
AU - Bussiba, Arrie
AU - Bartoli, I.
AU - Kontsos, Antonios
N1 - Publisher Copyright:
© Springer Science+Business Media New York 2015.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - This article presents the advantages of combining Acoustic Emission (AE) and Digital Image Correlation (DIC) in nondestructive testing (NDT) applications focusing on in situ damage monitoring. This data-fusion approach is used herein to characterize the mechanical and damage behavior of a fiber metal laminate (Glare 1A) tested in both tension and fatigue. Furthermore, the approach is used to investigate the structural behavior of partially grouted reinforced masonry walls. The obtained AE datasets were post-processed, in combination with DIC and mechanical information, using signal processing and pattern recognition techniques to investigate progressive failure of the Glare 1A. In the case of the masonry wall specimens, DIC clearly identified critical damage areas as a function of applied loading, while AE was capable to monitor the damage process and reveal changes in the overall behavior. The presented analysis demonstrates the potential of integrating AE and DIC in data-driven damage mechanics investigations at multiple time and length scales.
AB - This article presents the advantages of combining Acoustic Emission (AE) and Digital Image Correlation (DIC) in nondestructive testing (NDT) applications focusing on in situ damage monitoring. This data-fusion approach is used herein to characterize the mechanical and damage behavior of a fiber metal laminate (Glare 1A) tested in both tension and fatigue. Furthermore, the approach is used to investigate the structural behavior of partially grouted reinforced masonry walls. The obtained AE datasets were post-processed, in combination with DIC and mechanical information, using signal processing and pattern recognition techniques to investigate progressive failure of the Glare 1A. In the case of the masonry wall specimens, DIC clearly identified critical damage areas as a function of applied loading, while AE was capable to monitor the damage process and reveal changes in the overall behavior. The presented analysis demonstrates the potential of integrating AE and DIC in data-driven damage mechanics investigations at multiple time and length scales.
UR - http://www.scopus.com/inward/record.url?scp=84910605103&partnerID=8YFLogxK
U2 - 10.1007/978-1-4939-1239-1_56
DO - 10.1007/978-1-4939-1239-1_56
M3 - Conference contribution
AN - SCOPUS:84910605103
T3 - Springer Proceedings in Physics
SP - 605
EP - 622
BT - Advances in Acoustic Emission Technology - Proceedings of the World Conference on Acoustic Emission–2013
A2 - Shen, Gongtian
A2 - Wu, Zhanwen
A2 - Zhang, Junjiao
PB - Springer Science and Business Media, LLC
T2 - World Conference on Acoustic Emission 2013, WCAE 2013
Y2 - 30 October 2013 through 2 November 2013
ER -