Acoustic emission analysis of crack type identification of corroded concrete columns under eccentric loading: A comparative analysis of RA-AF method and Gaussian mixture model

Chen, Zhonggou; Zhang, Guoyi; He, Rui; Tian, Zushi; Fu, Chuanqing; Jin, Xianyu

doi:10.1016/j.cscm.2023.e02021

Cited by 8 publications

(3 citation statements)

References 61 publications

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“…The characteristics of AE signals are widely acknowledged for their pivotal role in improving the interpretability of clustering. As reported by Chen et al (2023), although all AE activities in concrete are attributed to damage events, the classification of AE signals often demonstrates nonlinear separability due to the involvement of multiple mechanisms. Consequently, it is vital to consider the distribution characteristics of AE signals in clustering.…”

Section: Introductionmentioning

confidence: 94%

Damage evolution analysis of concrete based on multi-feature acoustic emission and Gaussian mixture model clustering

Yu,

Liang,

2024

International Journal of Damage Mechanics

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In this work, a novel method for damage evolution analysis of concrete under uniaxial compression is proposed based on the multi-feature acoustic emission (AE) and the Gaussian mixture model (GMM) clustering. The hierarchical clustering algorithm is adopted to select optimal AE parameters, while multiple features of these parameters are generated through the principal component analysis (PCA). Then the concrete damage signals are separated by using the GMM clustering with multiple features. Meanwhile, the waveform signals associated with concrete damage in each cluster are validated using the Fast Fourier transform (FFT) and the continuous wavelet transform (CWT). Finally, the damage evolution process of concrete under uniaxial compression is divided based on the variation of AE characteristics. The results show that the frequency ranges of signals for micro-cracks, mixed cracks and friction of concrete under uniaxial compression are 20–30 kHz, 20–65 kHz, and 100–120 kHz, respectively. The damage process of concrete under uniaxial compression is divided into three stages according to the inflection points of the cumulative energy curve, namely the initial compaction stage, the crack formation stage and the failure stage.

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Section: Introductionmentioning

confidence: 94%

Damage evolution analysis of concrete based on multi-feature acoustic emission and Gaussian mixture model clustering

Yu,

Liang,

2024

International Journal of Damage Mechanics

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“…Many researchers have especially performed laboratory experiments considering different perspectives to study the characteristics of AE from RC members affected by rebar corrosion. For instance, Chen et al used the AE technique to identify cracks in corroded RC columns subjected to eccentric loading [16]. Seye et al used the AE technique to study the fracture performance of corroded RC cylinders subjected to compressive loading [17].…”

Section: Literature Reviewmentioning

confidence: 99%

Fracture Analysis of Short-Scale Corroded/Healthy Reinforced Concrete Beams under Bending Using Acoustic Emission

Seye,

Kawasaki,

Rahimi

2023

Materials

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In this work, the acoustic emission (AE) technique is used to evaluate the fracture process of corroded and healthy reinforced concrete (RC) beams subjected to a monotonic bending test. In fact, many researchers have conducted laboratory experiments considering different conditions to perform rebar corrosion monitoring in RC structures using the AE method. However, previous studies have not investigated the evolution of the bending performance of RC beams at different corrosion degrees, considering the interaction of single rebar with concrete. In this study, healthy and electrically corroded RC beams are evaluated, considering different corrosion levels. The analysis of the moving average of the AE maximum amplitudes was consistent to distinguish four stages of mechanical behavior that the healthy, and corroded specimens with low and medium corrosion levels of 0.9% and 3.2% experienced up to failure. Three damage stages were identified in the case of a high corrosion level of 9.3%. Then, the AE maximum amplitudes were suitable to establish an efficient clustering, which enabled the classification of the fractures into minor, medium, and major classes. Furthermore, the digital analysis method proposed in this study was suitable to visually reveal the influence of the preexisting corrosion-induced damages on the bending failure process of the RC beams.

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“…Among the nondestructive evaluation (NDE) methods (e.g., vision-based [1][2][3], ultrasound [4,5]), acoustic emission (AE) has shown great success [6][7][8][9][10][11][12]. In using AE data, researchers have used RA values versus AF to distinguish the shift in the cracking mechanisms within a structure [13][14][15][16][17][18][19]. Figure 2 illustrates the concept of separating tensile cracks from the shear ones using the RA-AF data.…”

Section: Introductionmentioning

confidence: 99%

An entropy-based probabilistic model for acoustic emission RA-value-average ‎frequency data

Bazrafshan,

Ebrahimkhanlou

2024

Health Monitoring of Structural and Biological Systems XVIII

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This study presents an innovative method for probabilistic modeling of acoustic emission by applying the principles of maximum entropy and utilizing a non-Gaussian probability distribution. The focus is on mathematical modeling of the RA (rise time to amplitude ratio) values versus the average frequency (AF) using a fourth-order non-Gaussian probability distribution. The main goal is to introduce this probabilistic model for AE data and showcase some of its benefits. Specifically, the model can 1) identify cracks at early stages and 2) distinguish between shear cracks and tensile (flexural) cracks within concrete and wood. To confirm the effectiveness of the proposed model, experimental data from acoustic emission tests on a concrete slab and a wood specimen are used. The parameters of the proposed probabilistic model capture the transition from one cracking mode to another. The results demonstrate the model's success in detecting the transition of cracks from tensile to shear at different stages. Capturing the evolution of the cracks is made possible by incorporating the parameter of time alongside the proposed fourth-order probabilistic model. These results indicate that the suggested method is a powerful mathematical approach for probabilistic modeling of RA-AF plots of AE data.

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Acoustic emission analysis of crack type identification of corroded concrete columns under eccentric loading: A comparative analysis of RA-AF method and Gaussian mixture model

Cited by 8 publications

References 61 publications

Damage evolution analysis of concrete based on multi-feature acoustic emission and Gaussian mixture model clustering

Damage evolution analysis of concrete based on multi-feature acoustic emission and Gaussian mixture model clustering

Fracture Analysis of Short-Scale Corroded/Healthy Reinforced Concrete Beams under Bending Using Acoustic Emission

An entropy-based probabilistic model for acoustic emission RA-value-average ‎frequency data

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