Damage identification of brick masonry under cyclic loading based on acoustic emissions

Haris Alexakis; Han Liu; Matthew J. Dejong

doi:10.1016/j.engstruct.2020.110945

Damage identification of brick masonry under cyclic loading based on acoustic emissions

Haris Alexakis, Han Liu, Matthew J. Dejong

Research output: Contribution to journal › Article › peer-review

Abstract

Ageing infrastructure, such as masonry railway bridges, suffers from structural deterioration due to fatigue loading. This paper presents an experimental study of brick masonry deterioration under gradually increasing cyclic loading with the aid of Acoustic Emission (AE) sensors. Two masonry beams were tested in the laboratory under similar stress conditions that masonry arches experience during train loading. An in-house AE monitoring system was developed for this study allowing both feature-based and waveform-based AE analysis. In the lab tests, different modes of damage were activated, such as tensile bond failure, brick and mortar crushing, diagonal shear failure and joint sliding. Feature-based AE analysis shows an increase in cracking rate before brittle failure events that is not necessarily accompanied by an increase in deformation rate. Statistical analysis reveals clear trends in AE results that correlate to different damage stages. The paper discusses how these findings can be leveraged to develop real-time structural alert systems that could provide early warning of damage before a significant increase in dynamic deformation occurs.

Original language	English
Article number	110945
Journal	Engineering Structures
Volume	221
Early online date	25 Jul 2020
DOIs	https://doi.org/10.1016/j.engstruct.2020.110945
Publication status	Published - 15 Oct 2020

Bibliographical note

© 2020, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Funding: This work is being funded by the Lloyd’s Register Foundation, EPSRC and Innovate UK through the Data-Centric Engineering programme of the Alan Turing Institute and through the Cambridge Centre for Smart Infrastructure and Construction. Funding for laboratory tests and the field monitoring installation was also provided by the EPSRC (grant Ref. EP/N021614/1) and by Innovate UK (grant Ref. 920035)

Keywords

Acoustic emission
Asset management
Non-destructive testing
Railway bridge
Smart infrastructure
Structural health monitoring

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10.1016/j.engstruct.2020.110945

Alexakis_et_al_2020_Eng_Struct_Apollo
© 2020, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Accepted author manuscript, 3.49 MBLicence: CC BY-NC-ND 3.0

https://www.repository.cam.ac.uk/handle/1810/306721

Cite this

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abstract = "Ageing infrastructure, such as masonry railway bridges, suffers from structural deterioration due to fatigue loading. This paper presents an experimental study of brick masonry deterioration under gradually increasing cyclic loading with the aid of Acoustic Emission (AE) sensors. Two masonry beams were tested in the laboratory under similar stress conditions that masonry arches experience during train loading. An in-house AE monitoring system was developed for this study allowing both feature-based and waveform-based AE analysis. In the lab tests, different modes of damage were activated, such as tensile bond failure, brick and mortar crushing, diagonal shear failure and joint sliding. Feature-based AE analysis shows an increase in cracking rate before brittle failure events that is not necessarily accompanied by an increase in deformation rate. Statistical analysis reveals clear trends in AE results that correlate to different damage stages. The paper discusses how these findings can be leveraged to develop real-time structural alert systems that could provide early warning of damage before a significant increase in dynamic deformation occurs.",

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N2 - Ageing infrastructure, such as masonry railway bridges, suffers from structural deterioration due to fatigue loading. This paper presents an experimental study of brick masonry deterioration under gradually increasing cyclic loading with the aid of Acoustic Emission (AE) sensors. Two masonry beams were tested in the laboratory under similar stress conditions that masonry arches experience during train loading. An in-house AE monitoring system was developed for this study allowing both feature-based and waveform-based AE analysis. In the lab tests, different modes of damage were activated, such as tensile bond failure, brick and mortar crushing, diagonal shear failure and joint sliding. Feature-based AE analysis shows an increase in cracking rate before brittle failure events that is not necessarily accompanied by an increase in deformation rate. Statistical analysis reveals clear trends in AE results that correlate to different damage stages. The paper discusses how these findings can be leveraged to develop real-time structural alert systems that could provide early warning of damage before a significant increase in dynamic deformation occurs.

AB - Ageing infrastructure, such as masonry railway bridges, suffers from structural deterioration due to fatigue loading. This paper presents an experimental study of brick masonry deterioration under gradually increasing cyclic loading with the aid of Acoustic Emission (AE) sensors. Two masonry beams were tested in the laboratory under similar stress conditions that masonry arches experience during train loading. An in-house AE monitoring system was developed for this study allowing both feature-based and waveform-based AE analysis. In the lab tests, different modes of damage were activated, such as tensile bond failure, brick and mortar crushing, diagonal shear failure and joint sliding. Feature-based AE analysis shows an increase in cracking rate before brittle failure events that is not necessarily accompanied by an increase in deformation rate. Statistical analysis reveals clear trends in AE results that correlate to different damage stages. The paper discusses how these findings can be leveraged to develop real-time structural alert systems that could provide early warning of damage before a significant increase in dynamic deformation occurs.

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Damage identification of brick masonry under cyclic loading based on acoustic emissions

Abstract

Bibliographical note

Keywords

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