Evaluation of the acoustic emission 3D localisation accuracy for the mechanical damage monitoring in concrete

Boniface, Antoine; Saliba, Jacqueline; Sbartaï, Zoubir Mehdi; Ranaivomanana, Narintsoa; Balayssac, Jean-Paul

doi:10.1016/j.engfracmech.2019.106742

Cited by 51 publications

(11 citation statements)

References 44 publications

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“…The spatio-temporal evolution of AE events can directly reflect the spatio-temporal evolution of damage and fracture in coal rock, which lays a foundation for the in-depth study of fracture expansion processes and spatial damage patterns. , In this study, all the AE source spatial coordinates were calculated and stored by the PCI-2 AE system, and the AE probe parameters and spatial arrangement are discussed in Section . Before applying CLU to each sample, the real-time wave velocity of the sample was independently measured by the PCI-2 AE system, and the newly measured real-time wave velocity was used as the subsequent three-dimensional positioning original data.…”

Section: Resultsmentioning

confidence: 99%

Strength Degradation and Fracture Propagation of Repeatedly Immersed Artificial Dam Samples under Uniaxial Cyclic Loading–Unloading

et al. 2023

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The use of underground reservoirs is a critical technique for achieving sustainable coal and water resources in many ecologically fragile mines in western China. Concrete samples subject to repeated water immersion and cyclic loading−unloading (CLU) operations were obtained from an underground artificial reservoir dam in Chahasu Colliery to study their strength damage and fracture propagation behavior. The variation in water content of the samples according to immersion times were divided into the rapid growth stage (0−10 h), slow growth stage (10−60 h), and stable stage (>60 h). With an increase in immersion times (IIT), the saturated water content of the coal samples logarithmically increased to 7.02%, and the ultrasonic wave velocity decreased by 10.44%. According to the increasing trend of plastic damage energy density, the total stress−strain curve was divided into four fracture stages. The total energy and elastic energy densities increased nonlinearly with the increase in cycles, whereas the plastic damage energy density first decreased and then increased. The plastic damage energy ratio at the stress peak point of the samples under different sequential times of immersion was 0.18, 0.29, 0.28, 0.58, and 0.61. The initial fracture development and fracture damage thresholds of the samples decreased by 20 and 50% with IIT, respectively. However, the proportion of the fracture closure and initial fracture development thresholds of the samples showed an increasing quadratic trend with IIT. Based on the low ratio of rise time to amplitude and high average frequency, the fracture mode of the samples under repeated water immersion was mainly tensile fracture. Acoustic emission events with energy higher than 10 4 aJ spread from the center with repeated water immersion. When the CLU was greater than 6, the plastic damage energy of the fitted three-dimensional surface increased nonlinearly with IIT. The energy parameter−plastic damage energy ratio was introduced to help develop a theoretical model for describing the complete stress−strain damage evolution of repeatedly immersed concrete samples under CLU. The paper provides technical references for improving the long-term strength design of concrete artificial dams of underground reservoirs.

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Section: Resultsmentioning

confidence: 99%

Strength Degradation and Fracture Propagation of Repeatedly Immersed Artificial Dam Samples under Uniaxial Cyclic Loading–Unloading

et al. 2023

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“…Adaptive meshing algorithm (AMA) was presented by Boniface et al [8], which has the capability to be quickly modified for modeling complex structures. However, compared to other algorithms, AMA performed poorly for errors that were less than 1 cm.…”

Section: ) Source Localization With Known Velocitymentioning

confidence: 99%

State-of-the-Art Review on the Acoustic Emission Source Localization Techniques

Hassan¹,

Mahmood²,

Yahya

et al. 2021

IEEE Access

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The acoustic emission technique has been applied successfully for the identification, characterization, and localization of deformations in civil engineering structures. Numerous localization techniques, such as Modal Acoustic Emission, Neural Networks, Beamforming, and Triangulation methods with or without prior knowledge of wave velocity, have been presented. Several authors have conducted in-depth research in the localization of AE sources. However, existing review papers do not focus on the performance evaluation of existing source localization techniques. This paper discusses these techniques based on the number of sensors used and the geometry of the structures of interest. Furthermore, it evaluates them on the basis of their performance. At the end of this paper, a comparative analysis of existing methods has been presented based on their basic principles, key strengths, and limitations. A deep learning circular sensor cluster-based solution has the potential to provide a low-cost reliable localization solution for acoustic emission sources.

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“…Finally, the corrected value Δθ is solved by equations ( 25) and (26), takes ðθ þ ΔθÞ as the new iteration coordinate, and continues iteration until the error requirement is satisfied; subsequently, the iterative result of Geiger algorithm can be obtained. The detailed step of the proposed method can be summarized as follows:…”

Section: Combination the Geiger Localization Algorithm With Least Squ...mentioning

confidence: 99%

“…Unfortunately, APFFT does not avoid the spectrum leakage and picket fence effect to the maximum, thus it needs to be corrected to obtain more accurate harmonic signal parameters. Moreover, conventional AE source localization methods such as least squares, 24 multiple cross-correlation, 25 and Geiger algorithm 26 have poor adaptability and complex calculation, which further reduce the accuracy of source localization. Specifically, the traditional Geiger algorithm requires a suitable initial value of iteration to obtain the global minimum, which leads to a high dependence on the initial point.…”

Section: Introductionmentioning

confidence: 99%

All-phase fast Fourier transform and multiple cross-correlation analysis based on Geiger iteration for acoustic emission sources localization in complex metallic structures

2021

Structural Health Monitoring

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Nowadays, the localization and identification of acoustic emission (AE) source is widely utilized to structural health monitoring (SHM) of complex metallic structures. However, traditional AE source localization methods are generally difficult to localize and characterize AE sources in plate-like structure that has complex geometric features. To alleviate the problem, a novel AE source localization method based on all-phase fast Fourier transform and multiple cross-correlation analysis is proposed in this article. Moreover, least squares and Geiger iteration algorithm are applied to determine the coordinates of AE sources. In addition, an improved Bayesian information criterion (BIC) version named autoregressive BIC (i.e., AR-BIC) is presented to increase the accuracy of source localization. To validate the performance of the proposed approach, the classical pencil lead break tests are carried out on a 316 L stainless steel with 10 laser cladding layers. Experimental waveforms are generated from AE sources near laser cladding layers, the surface of the structure, and on its edges. Additionally, to evaluate the performance of the proposed approach in three-dimensional AE source localization, an industrial storage tank is used to acquire three-dimensional AE sources through manually striking. Finally, to further verify the effectiveness of the proposed approach, comparisons with conventional AE source location methods (i.e., PAC or SAMOS AE acquisition system, Newton’s method, and multiple cross-correlation based on Geiger algorithm) and two representative approaches (i.e., deep learning and Bayesian methodology) for localizing AE sources generated by complex metallic structures are conducted. The comparative results demonstrate the effectiveness and superiority of the proposed method in AE-based SHM of complex metallic structures.

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Evaluation of the acoustic emission 3D localisation accuracy for the mechanical damage monitoring in concrete

Cited by 51 publications

References 44 publications

Strength Degradation and Fracture Propagation of Repeatedly Immersed Artificial Dam Samples under Uniaxial Cyclic Loading–Unloading

Strength Degradation and Fracture Propagation of Repeatedly Immersed Artificial Dam Samples under Uniaxial Cyclic Loading–Unloading

State-of-the-Art Review on the Acoustic Emission Source Localization Techniques

All-phase fast Fourier transform and multiple cross-correlation analysis based on Geiger iteration for acoustic emission sources localization in complex metallic structures

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