Verification of the applicability of the Gaussian mixture modelling for damage identification in reinforced concrete structures using acoustic emission testing

Vidya Sagar, R (2018) Verification of the applicability of the Gaussian mixture modelling for damage identification in reinforced concrete structures using acoustic emission testing. In: Journal of Civil Structural Health Monitoring, 8 (3). pp. 395-415.

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Abstract

This article presents an experimental study on verification of the applicability of Gaussian mixture modelling (GMM) algorithm of acoustic emissions for damage identification in reinforced concrete (RC) structures. Eight RC-flanged beam specimens with different properties were tested subjected to flexural loading. An incremental cyclic load was applied on RC-flanged beam specimens till failure, and simultaneously, the released acoustic emissions (AE) were recorded. It may be required to study crack classification in RC structures, because crack classification studies are useful to predict the structural performance and subsequently to implement the appropriate structural rehabilitation methods. AE belonging to tensile cracking and shear cracking can be studied by a probabilistic approach. It was observed that the line separating the AE clusters belonging to tensile and shear cracks was shifting towards a higher rise angle as the specimen is reaching collapse stage. This observation indicates dominance of shear cracks near the collapse stage. At the loading cycle where yielding occurred in the test specimen obtained by using GMM algorithm for AE, the load cycle entered into heavy damage zone is almost same as per NDIS-2421 damage assessment chart. The results obtained by both GMM algorithms for AE and NDIS-2421 criterion to evaluate the damage in the RC-flanged beams were compared and discussed.

Item Type:	Journal Article
Publication:	Journal of Civil Structural Health Monitoring
Publisher:	Springer Verlag
Additional Information:	The copyright for this article belongs to the Springer Verlag.
Keywords:	Concrete mixtures; Concrete testing; Crack detection; Damage detection; Gaussian beams; Probability; Reinforced concrete; Structural analysis, Crack classification; Damage; Damage assessments; Damage Identification; Gaussian mixtures; Probabilistic approaches; Structural performance; Structural rehabilitation, Acoustic emission testing
Department/Centre:	Division of Mechanical Sciences > Civil Engineering
Date Deposited:	10 Aug 2022 06:29
Last Modified:	10 Aug 2022 06:29
URI:	https://eprints.iisc.ac.in/id/eprint/75493

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