Fatigue fracture quantification in brittle cementitious materials using acoustic emission testing and digital image correlation

Deresse, Nuhamin Eshetu; Sarem, Mina; Nasser, Hussein; François, Stijn; Verstrynge, Els

doi:10.1016/j.conbuildmat.2023.132635

Cited by 4 publications

(2 citation statements)

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“…In the natural time domain, when a segment of a signal contains N events, kth event can be defined using Eq (6), while the normalized energy is specified in Eq (7), and Q k is energy emitted during an event in natural time. Unlike the traditional time domain, where all AE signals under a single envelope are counted as separate events, the natural time domain definition considers the signal that best represents the occurrence of an AE event under a single envelope as a single event.…”

Section: Basic Definitionmentioning

confidence: 99%

“…When a material undergoes inelastic deformation, some of the energy released will propagate through the material in the form of elastic waves, which is known as AE (acoustic emission, AE) [ 7 ]. In recent years, advanced non-destructive testing methods such as AE techniques are particularly suitable for fatigue damage monitoring, mainly because of their high sensitivity to inelastic material changes such as microcracks.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of critical states based on acoustic emission signals during progressive failure of wood

Jia,

LI,

Zhang

et al. 2024

PLoS ONE

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The analysis of critical states during fracture of wood materials is crucial for wood building safety monitoring, wood processing, etc. In this paper, beech and camphor pine are selected as the research objects, and the acoustic emission signals during the fracture process of the specimens are analyzed by three-point bending load experiments. On the one hand, the critical state interval of a complex acoustic emission signal system is determined by selecting characteristic parameters in the natural time domain. On the other hand, an improved method of b_value analysis in the natural time domain is proposed based on the characteristics of the acoustic emission signal. The K-value, which represents the beginning of the critical state of a complex acoustic emission signal system, is further defined by the improved method of b_value in the natural time domain. For beech, the analysis of critical state time based on characteristic parameters can predict the “collapse” time 8.01 s in advance, while for camphor pines, 3.74 s in advance. K-value can be analyzed at least 3 s in advance of the system “crash” time for beech and 4 s in advance of the system “crash” time for camphor pine. The results show that compared with traditional time-domain acoustic emission signal analysis, natural time-domain acoustic emission signal analysis can discover more available feature information to characterize the state of the signal. Both the characteristic parameters and Natural_Time_b_value analysis in the natural time domain can effectively characterize the time when the complex acoustic emission signal system enters the critical state. Critical state analysis can provide new ideas for wood health monitoring and complex signal processing, etc.

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Section: Basic Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%