Identification of fracture mechanisms in cementitious composites using wavelet transform of acoustic emission signals

Stankevych, Olena; Skal’s’kyi, V. R.; Klym, B. P.; Velykyi, P. P.

doi:10.1016/j.prostr.2022.01.011

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…B ∈ R is the time position of the analysis signal, that is, the time center. It is to ensure that the energy of the function and the mother wavelet is the same under different scales [20][21][22].…”

Section: Continuous Wavelet Transform In Timementioning

confidence: 99%

Signal Analysis of Characteristics Using Passive Acoustic Emission Technique in Gas‐Solid Pipeline Flows

Weigang

2022

Discrete Dynamics in Nature and Society

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This paper investigates a case study of the use of a passive acoustic sensor for online measurement of the dilute phase gas-solid pipeline flows. The acoustic emission sensor is mounted externally on a stainless steel line conveying silica powders. For different experimental conditions, including the solid to air mass ratios from 0.6 to 1.4 and the gas volume flows from 160 to 240 m3/h, the sound signals in the pipeline are discussed using the wavelet transform technique. The measured values of transmission mechanism of two different lengths, 25 mm and 35 mm, are analyzed. The results show that the variation tendency of standard deviations is consistent and that the noninvasive, online acoustic detect technique can be regarded as a satisfactory tool in gas-solid flows.

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Section: Continuous Wavelet Transform In Timementioning

confidence: 99%

Signal Analysis of Characteristics Using Passive Acoustic Emission Technique in Gas‐Solid Pipeline Flows

Weigang

2022

Discrete Dynamics in Nature and Society

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“…Through AE signal frequency-amplitude distribution, Zhao et al [40] proposed an assessment method of rock-salt destruction under the test condition of multilevel cyclic loading. Olena et al [41] identified fracture mechanisms of cementitious composites by using the wavelet transform of AE signals. The peak frequency of acoustic emission signals after wavelet transform as a parameter exhibited good stress memory capabilities for the Kaiser effect [42].…”

Section: Introductionmentioning

confidence: 99%

Wavelet Energy Evolution Characteristics of Acoustic Emission Signal under True-Triaxial Loading during the Rockburst Test

Fu-ding

Hussain

2022

Applied Sciences

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The rockburst simulation test is conducted by utilizing a mineral-containing marble specimen. The loading condition is set to the three directions, each loading on five surfaces except for a single free surface. The whole test procedure is monitored in real time by using a PCI-II acoustic emission monitoring system and a high-speed camera. According to the test outcomes, rockburst is a process in which energy is rapidly released from the free surface. Rock block and rock plate are buckled and ejected from the free surface and a severe rockburst process is accompanied by spray rock powder. An explosion sound can be heard during the process, which can be analyzed by signal processing techniques. The failure mode of the specimen is a splitting-shearing composite failure, and the free surface becomes a rockburst destruction surface. A V-type rockburst pit is formed in the ejection area. The effective acoustic emission signal of the whole test process is decomposed and reconstructed using five-layer wavelets to produce six frequency band sub-signals. In addition, the wavelet energy and its energy distribution coefficients are assessed for various frequency bands, and the proportion of each dominant frequency band within each period is computed. Finally, it was found that the dominant frequency band is 125~250 kHz, while the suboptimal frequency band is 250~500 kHz. The succeeding features are noticed to be used as predicted features for the rockburst disaster. Namely, acoustic emission signals arise in large numbers and the energy distribution coefficient of the dominant frequency band concentrates above 0.4. The proportion of dominant frequency band appears in continuous valley type and keeps below 80%, while the proportion of suboptimal frequency band appears in continuous peak type and keeps above 20%.

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Acoustic-Emission Criterion for Optimizing the Quantity of Fibers in the Concrete Matrix

Skalskyi,

Stankevych

2024

Mater Sci

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Identification of fracture mechanisms in cementitious composites using wavelet transform of acoustic emission signals

Cited by 4 publications

References 13 publications

Signal Analysis of Characteristics Using Passive Acoustic Emission Technique in Gas‐Solid Pipeline Flows

Signal Analysis of Characteristics Using Passive Acoustic Emission Technique in Gas‐Solid Pipeline Flows

Wavelet Energy Evolution Characteristics of Acoustic Emission Signal under True-Triaxial Loading during the Rockburst Test

Acoustic-Emission Criterion for Optimizing the Quantity of Fibers in the Concrete Matrix

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