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Acoustic Emission Testing in Engineering - Basics and Applications

Christian Grosse, +1 more
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The article was published on 2008-01-01 and is currently open access. It has received 64 citations till now. The article focuses on the topics: Acoustic emission.

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Acoustic Emission Sensor Calibration for Absolute Source Measurements

TL;DR: In this article, the authors describe sensor calibration and signal analysis techniques applicable to the method of acoustic emission (AE) and ultrasonic testing, which are particularly useful for obtaining absolute measurements of AE wave amplitude and shape, which can be used to constrain the physics and mechanics of the AE source.
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A probabilistic approach for damage identification and crack mode classification in reinforced concrete structures

TL;DR: To minimize the maintenance costs and to increase the operation lifetime, researchers and practi... as mentioned in this paper proposed reinforced concrete is subjected to deterioration due to aging, increased load, and natural hazards, which is why reinforced concrete should be replaced with reinforced concrete.
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Characterization of debonding in FRP-strengthened masonry using the acoustic emission technique

TL;DR: In this paper, an acoustic emission (AE) technique is used for investigating the interfacial fracture and damage propagation in GFRP- and SRG-strengthened bricks during debonding tests.
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Fracture process zone characteristics and identification of the micro-fracture phases in recycled concrete

TL;DR: In this article, the influence of recycled aggregate proportion on the characteristics of fracture process was analyzed and three clusters correspond respectively to aggregate fracture, cracking in cement mortar and cracking at the interfacial transition zone were discriminated.
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Toward a probabilistic acoustic emission source location algorithm: A Bayesian approach

TL;DR: In this article, a probabilistic source location algorithm was proposed for acoustic emissions analysis using Bayesian analysis methods with Markov Chain Monte Carlo (MCMC) simulation where all source location parameters were described with posterior probability density functions (PDFs).