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Detection of flexural damage for RC beams using Piezoelectric sensors

Providakis Konstantinos, Voutetaki Maria-Styliani, Ch. Karayannis, C. Chalioris

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Year 2013
Type of Item Peer-Reviewed Journal Publication
Bibliographic Citation Ch. Karayannis, C. Providakis, C. Chalioris, M. Voutetaki, G. Angeli, “Detection of flexural damage for RC beams using Piezoelectric sensors," Smart Struc. and Syst.,vol.15,no.4,pp. 997-1018 ,2013.doi:10.12989/sss.2015.15.4.997
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Structural health monitoring along with damage detection and assessment of its severity level in non-accessible reinforced concrete members using piezoelectric materials becomes essential since engineers often face the problem of detecting hidden damage. In this study, the potential of the detection of flexural damage state in the lower part of the mid-span area of a simply supported reinforced concrete beam using piezoelectric sensors is analytically investigated. Two common severity levels of flexural damage are examined: (i) cracking of concrete that extends from the external lower fiber of concrete up to the steel reinforcement and (ii) yielding of reinforcing bars that occurs for higher levels of bending moment and after the flexural cracking. The purpose of this investigation is to apply finite element modeling using admittance based signature data to analyze its accuracy and to check the potential use of this technique to monitor structural damage in real-time. It has been indicated that damage detection capability greatly depends on the frequency selection rather than on the level of the harmonic excitation loading. This way, the excitation loading sequence can have a level low enough that the technique may be considered as applicable and effective for real structures. Further, it is concluded that the closest applied piezoelectric sensor to the flexural damage demonstrates higher overall sensitivity to structural damage in the entire frequency band for both damage states with respect to the other used sensors. However, the observed sensitivity of the other sensors becomes comparatively high in the peak values of the root mean square deviation index.