Paper
19 April 2013 Gaussian mixture modeling of acoustic emissions for structural health monitoring of reinforced concrete structures
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Abstract
Reinforced Concrete (RC) has been widely used in construction of infrastructures for many decades. The cracking behavior in concrete is crucial due to the harmful effects on structural performance such as serviceability and durability requirements. In general, in loading such structures until failure, tensile cracks develop at the initial stages of loading, while shear cracks dominate later. Therefore, monitoring the cracking modes is of paramount importance as it can lead to the prediction of the structural performance. In the past two decades, significant efforts have been made toward the development of automated structural health monitoring (SHM) systems. Among them, a technique that shows promises for monitoring RC structures is the acoustic emission (AE). This paper introduces a novel probabilistic approach based on Gaussian Mixture Modeling (GMM) to classify AE signals related to each crack mode. The system provides an early warning by recognizing nucleation of numerous critical shear cracks. The algorithm is validated through an experimental study on a full-scale reinforced concrete shear wall subjected to a reversed cyclic loading. A modified conventional classification scheme and a new criterion for crack classification are also proposed.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alireza Farhidzadeh, Ehsan Dehghan-Niri, and Salvatore Salamone "Gaussian mixture modeling of acoustic emissions for structural health monitoring of reinforced concrete structures", Proc. SPIE 8692, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013, 86920B (19 April 2013); https://doi.org/10.1117/12.2008705
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Cited by 2 scholarly publications.
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KEYWORDS
Structural health monitoring

Acoustic emission

Expectation maximization algorithms

Sensors

Atrial fibrillation

Systems modeling

Optical inspection

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