Structural Monitoring and Maintenance

  • 제1권1호
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  • Pages.111-130
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  • 2014
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  • 2288-6605(pISSN)
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  • 2288-6613(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Acoustic emission monitoring of damage progression in CFRP retrofitted RC beams

  • Nair, Archana (Department of Civil and Environmental Engineering, Louisiana State University) ;
  • Cai, C.S. (Department of Civil and Environmental Engineering, Louisiana State University) ;
  • Pan, Fang (Department of Civil and Environmental Engineering, Louisiana State University) ;
  • Kong, Xuan (Department of Civil and Environmental Engineering, Louisiana State University)
  • 투고 : 2014.01.30
  • 심사 : 2014.03.21
  • 발행 : 2014.03.25
⟨ 이전 논문 다음 논문 ⟩

초록

The increased use of carbon fiber reinforced polymer (CFRP) in retrofitting reinforced concrete (RC) members has led to the need to develop non-destructive techniques that can monitor and characterize the unique damage mechanisms exhibited by such structural systems. This paper presented the damage characterization results of six CFRP retrofitted RC beam specimens tested in the laboratory and monitored using acoustic emission (AE). The focus of this study was to continuously monitor the change in AE parameters and analyze them both qualitatively and quantitatively, when brittle failure modes such as debonding occur in these beams. Although deterioration of structural integrity was traceable and can be quantified by monitoring the AE data, individual failure mode characteristics could not be identified due to the complexity of the system failure modes. In all, AE was an effective non-destructive monitoring tool that can trace the failure progression in RC beams retrofitted with CFRP. It would be advantageous to isolate signals originating from the CFRP and concrete, leading to a more clear understanding of the progression of the brittle damage mechanism involved in such a structural system. For practical applications, future studies should focus on spectral analysis of AE data from broadband sensors and automated pattern recognition tools to classify and better correlate AE parameters to failure modes observed.

키워드

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피인용 문헌

  1. Application of acoustic emission monitoring for assessment of bond performance of corroded reinforced concrete beams vol.16, pp.6, 2017, https://doi.org/10.1177/1475921716681460
  2. Correlation between acoustic emission distribution and stress variation through the depth of RC beam cross sections vol.150, pp.None, 2014, https://doi.org/10.1016/j.conbuildmat.2017.06.001
  3. Studying Failure Modes of GFRP Laminate Coupons Using AE Pattern-Recognition Method vol.32, pp.4, 2019, https://doi.org/10.1061/(asce)as.1943-5525.0001015
  4. Analysis of acoustic emission signals during fatigue testing of a M36 bolt using the Hilbert-Huang spectrum vol.7, pp.1, 2014, https://doi.org/10.12989/smm.2020.7.1.013
  5. Condition assessment of bridge pier using constrained minimum variance unbiased estimator vol.7, pp.4, 2014, https://doi.org/10.12989/smm.2020.7.4.319