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Effect of propagation distance on acoustic emission fracture mode classification in textile reinforced cement
HighlightsCracking and delaminations/pull-out of TRC are monitored by AE.Multiple sensors are used to examine the effect of wave propagation distance.Basic parameters of AE change with propagation distance.Classification success between different modes decreases for further sensors.Classification boundaries depend on the source-sensor distance.
AbstractTextile reinforced cement (TRC) is a composite material being increasingly used for load bearing applications. Damage in TRC as in all cementitious materials is an important issue in civil engineering. Acoustic emission (AE) exhibits promising outcomes in laboratory and in in-situ monitoring applications. Evaluation of the fracture mode is crucial as generally, shearing phenomena occur later than tensile (bending) cracking and indicate more severe damage. The acoustic signatures of the damage modes influence most of AE parameters including the average frequency AF and RA-value. However, there are no universal classification boundaries between tensile and shear signals mainly due to geometric effects, material properties, as well as sensor location and response function. In order to highlight this problem and discuss the possibility of a solution, the study occupies not only with the evaluation of the damage mode based on AE parameters but in addition uses multiple sensors to investigate the effect of the wave propagation distance. This is crucial in thin cementitious laminates since damping, scattering, reflections and plate wave dispersion seriously distort the signal having a strong effect on the classification result. It is seen that the classification boundaries between tensile and shear fracture should incorporate the information of propagation distance.
Effect of propagation distance on acoustic emission fracture mode classification in textile reinforced cement
HighlightsCracking and delaminations/pull-out of TRC are monitored by AE.Multiple sensors are used to examine the effect of wave propagation distance.Basic parameters of AE change with propagation distance.Classification success between different modes decreases for further sensors.Classification boundaries depend on the source-sensor distance.
AbstractTextile reinforced cement (TRC) is a composite material being increasingly used for load bearing applications. Damage in TRC as in all cementitious materials is an important issue in civil engineering. Acoustic emission (AE) exhibits promising outcomes in laboratory and in in-situ monitoring applications. Evaluation of the fracture mode is crucial as generally, shearing phenomena occur later than tensile (bending) cracking and indicate more severe damage. The acoustic signatures of the damage modes influence most of AE parameters including the average frequency AF and RA-value. However, there are no universal classification boundaries between tensile and shear signals mainly due to geometric effects, material properties, as well as sensor location and response function. In order to highlight this problem and discuss the possibility of a solution, the study occupies not only with the evaluation of the damage mode based on AE parameters but in addition uses multiple sensors to investigate the effect of the wave propagation distance. This is crucial in thin cementitious laminates since damping, scattering, reflections and plate wave dispersion seriously distort the signal having a strong effect on the classification result. It is seen that the classification boundaries between tensile and shear fracture should incorporate the information of propagation distance.
Effect of propagation distance on acoustic emission fracture mode classification in textile reinforced cement
Aggelis, D.G. (author) / El Kadi, M. (author) / Tysmans, T. (author) / Blom, J. (author)
Construction and Building Materials ; 152 ; 872-879
2017-06-28
8 pages
Article (Journal)
Electronic Resource
English
British Library Online Contents | 2017
|British Library Online Contents | 2017
|British Library Online Contents | 2017
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