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Showing papers on "Acoustic emission published in 2022"


Journal ArticleDOI
01 Jun 2022-Energy
TL;DR: In this article , an automatic encoder (AE) extreme learning machine (ELM)-AE-ELM model is proposed to predict the NOx emission concentration based on the combination of mutual information algorithm (MI), AE, and ELM.

68 citations


Journal ArticleDOI
TL;DR: In this paper , an efficient acoustic emission (AE) method was developed for cemented tailings backfill (CTB) to explore the influence of type, length and dosage of fiber over strength, acoustic and fractal characteristics of CTB materials.

61 citations


Journal ArticleDOI
TL;DR: The reliability, advantages, weaknesses, case/material dependency and applicability of each method are compared and tabulated for making a framework for choosing a suitable technique for fatigue crack or damage detection of material or components.

38 citations


Journal ArticleDOI
19 Jan 2022-Minerals
TL;DR: In this paper , the authors studied the nonlinear characteristics of EMR and AE during coal splitting failure using Hilbert-H and multifractal theory, and valuable information pertaining to coal fracture law was revealed.
Abstract: Coal and rock dynamic disasters have been the main concern in underground engineering because these seriously threaten the safety of miners and industrial production. Aiming to improve the EMR and AE monitoring technology, the refined nonlinear characteristics of EMR and AE during coal splitting failure are studied using Hilbert-H and multifractal theory, and valuable information pertaining to coal fracture law contained in EMR and AE waveform was revealed. The results show that the EMR and AE of coal splitting failure are related to the process of coal crack propagation. They possess the same initiation time and frequency band, however, the signal duration of EMR is comparatively longer than AE, and the main frequency of AE is higher than EMR. The EMR of coal splitting failure has the same excitation source as AE; nonetheless, the excited forms display different behavior. In terms of signal duration, the distribution of EMR signal is relatively uniform, the proportion of large-signal is less, the amount of information is more than that of AE, and the multifractal characteristics are more complicated. During the coal splitting failure, AE is mainly generated in the process of wall vibration caused by crack propagation, while the generation of EMR includes piezoelectric effect, charge separation, free charge vibration, charge neutralization and other processes, making EMR more complicated than AE and has a relatively low frequency. The research provides an effective method for studying nonlinear refinement characteristics of coal EMR and AE, and can provide an important basis for the study of the mechanism of EMR generation.

36 citations


Journal ArticleDOI
TL;DR: In this article , triaxial compression and seepage tests were carried out on coal at different gas pressures, and the influence of gas pressure on the mechanical parameters of this coal was analyzed.
Abstract: The mechanical behavior of coal is the key factor affecting underground coal mining and coalbed methane extraction. In this study, triaxial compression and seepage tests were carried out on coal at different gas pressures. The mechanical properties and failure process of coal were studied, as well as the acoustic emission (AE) and strain energy. The influence of gas pressure on the mechanical parameters of this coal was analyzed. Based on the conventional energy calculation formula, the pore pressure was introduced through the effective stress formula, and each energy component of coal containing gas was refined innovatively. The contribution of gas pressure to the total energy input and dissipation during loading was quantitatively described. Finally, the influence of gas pressure on coal strength was theoretically analyzed from the perspectives of Mohr–Coulomb criterion and fracture mechanics. The results show that the total absorbed energy comprises the absorbed energy in the axial pressure direction (positive) and in the confining pressure direction (negative), as well as that induced by the pore pressure (initially negative and then positive). The absorbed energy in the axial pressure direction accounts for the main proportion of the total energy absorbed by coal. The quiet period of AE in the initial stage shortens, and AE activity increases during the pre-peak stage under high gas pressure. The fractal characteristics of AE in three stages are studied using the correlation dimension. The AE process has different forms of self-similarity in various deformation stages.

33 citations


Journal ArticleDOI
TL;DR: In this paper , a convolutional neural network based deep learning architecture is proposed to automatically extract the discrete damage features from the scalogram images and use them to classify damage-source regions in the composite panel.
Abstract: Structural health monitoring for lightweight complex composite structures is being investigated in this paper with a data-driven deep learning approach to facilitate automated learning of the map of transformed signal features to damage classes. Towards this, a series of acoustic emission (AE) based laboratory experiments have been carried out on a composite sample using a piezoelectric AE sensor network. The registered time-domain AE signals from the assigned sensor networks on the composite panel are processed with the continuous wavelet transform to extract time-frequency scalograms . A convolutional neural network based deep learning architecture is proposed to automatically extract the discrete damage features from the scalogram images and use them to classify damage-source regions in the composite panel. The proposed deep-learning approach has shown an effective damage monitoring potential with high training, validation and test accuracy for unseen datasets as well as for entirely new neighboring damage datasets. Further, the proposed network is trained, validated and tested only for the peak-signal data extracted from the raw AE data. The application of peak-signal scalogram data has shown a significant improvement in damage-source classification performance with high training, validation and test accuracy.

31 citations


Journal ArticleDOI
TL;DR: In this article , a review of the existing fatigue damage detection and measurement techniques on the basis of both momentum within the research field and their being considered non-destructive is presented.

31 citations


Journal ArticleDOI
TL;DR: In this paper, a convolutional neural network based deep learning architecture is proposed to automatically extract the discrete damage features from the scalogram images and use them to classify damage-source regions in the composite panel.
Abstract: Structural health monitoring for lightweight complex composite structures is being investigated in this paper with a data-driven deep learning approach to facilitate automated learning of the map of transformed signal features to damage classes. Towards this, a series of acoustic emission (AE) based laboratory experiments have been carried out on a composite sample using a piezoelectric AE sensor network. The registered time-domain AE signals from the assigned sensor networks on the composite panel are processed with the continuous wavelet transform to extract time-frequency scalograms. A convolutional neural network based deep learning architecture is proposed to automatically extract the discrete damage features from the scalogram images and use them to classify damage-source regions in the composite panel. The proposed deep-learning approach has shown an effective damage monitoring potential with high training, validation and test accuracy for unseen datasets as well as for entirely new neighboring damage datasets. Further, the proposed network is trained, validated and tested only for the peak-signal data extracted from the raw AE data. The application of peak-signal scalogram data has shown a significant improvement in damage-source classification performance with high training, validation and test accuracy.

31 citations


Journal ArticleDOI
TL;DR: In this article , the fracture characteristics of high-strength hydraulic concrete subjected to different FT damage (0, 100, 200, 300, 400 FT cycles) are studied by experimental analysis and discrete element method (DEM) simulation.

27 citations



Journal ArticleDOI
01 Jan 2022
TL;DR: In this article , an acoustic emission (AE) source location method for structures containing unknown empty areas (SUEA) is proposed, which identifies the shape, size, and location of empty areas in the unknown region by exciting the active AE sources and using the collected AE arrivals.
Abstract: Acoustic emission (AE) localization plays an important role in the prediction and control of potential hazardous sources in complex structures. However, existing location methods have less discussion on the presence of unknown empty areas. This paper proposes an AE source location method for structures containing unknown empty areas (SUEA). Firstly, this method identifies the shape, size, and location of empty areas in the unknown region by exciting the active AE sources and using the collected AE arrivals. Then, the unknown AE source can be located considering the identified empty areas. The lead break experiments were performed to verify the effectiveness and accuracy of the proposed method. Five specimens were selected containing empty areas with different positions, shapes, and sizes. Results show the average location accuracy of the SUEA increased by 78% compared to the results of the existing method. It can provide a more accurate solution for locating AE sources in complex structures containing unknown empty areas such as tunnels, bridges, railroads, and caves in practical engineering.

Journal ArticleDOI
TL;DR: Increase the signal sampling frequency for AE event identification, use a real-time inverted 3D velocity model and update the PATSEs in real time could be used to further improve the AE event location accuracy.

Journal ArticleDOI
TL;DR: In this article , the authors investigated the macro-meso failure and instability mechanism of cavity-contained granite subjected to increasing-amplitude and decreasing-frequency cyclic loads combined with acoustic emission (AE) and X-ray computed tomography (CT) technique.

Journal ArticleDOI
TL;DR: In this article , the identification and prediction of fatigue crack growth (FCG) of 316LN stainless steel under different stress ratios were investigated by the acoustic emission (AE) technique, and the results showed that three damage stages associated with crack initiation, stable crack growth, and rapid crack growth were accurately identified by using multiple AE parameters during FCG under various load ratios.

Journal ArticleDOI
TL;DR: In this paper , the energy evolution and acoustic emission characteristics of layered sandstone under anchorage in the process of deformation and failure were investigated, and it was shown that anchoring can make layered sandstones store more energy, the stored energy first increases, then decreases with the increase of bedding angle.
Abstract: To study the energy evolution and acoustic emission characteristics of layered sandstone under anchorage in the process of deformation and failure, the sandstone samples from Chuxiong Yi Autonomous Prefecture, Yunnan Province were selected for uniaxial compression testing. The energy evolution in the process of sandstone failure and the spatial fractal characteristics of acoustic emission events in the process of deformation and failure were investigated. Research results show that anchoring can make layered sandstone store more energy, the stored energy first increases, then decreases with the increase of bedding angle; the B value of sandstone under anchorage is generally higher than that of unanchored sandstone in the whole deformation and failure process, and the continuous decline in B value can be used to indicate a precursor to instability and failure; under the action of anchoring, the D value of sandstone (its fractal dimension) also increases, then decreases with the increase of bedding angle. The D value changes within [2, 3]. At a given bedding angle, the D value of anchored sandstone is greater than that of unanchored sandstone, the D value of 30° anchored sandstone increased the most (by 12.33%); the maximum D value occurred in 45° anchored sandstone (reaching 2.72) and the spatial distribution of acoustic emission events and damage of sandstone under anchorage is also more uniform; under increasing stress, the number of acoustic emission events is less widely distributed in the early stage and more densely distributed in the later stage. The growth rate of the D value varies across different peak stress ranges, which is more significant under the action of anchorage. The acoustic emission event counts grow evenly and slowly in the space, and the toughness of sandstone is improved to a certain extent under the action of anchorage.

Journal ArticleDOI
TL;DR: In this paper , multilevel cyclic loading with constant stress intervals on rock salt were conducted under uniaxial compression conditions, and acoustic emission (AE) monitoring and post-test computed tomography (CT) scanning were used to evaluate the damage evolution during the loading process.

Journal ArticleDOI
TL;DR: A Bayesian source localisation strategy that is robust to complexities within composite materials and structures that contain non-trivial geometrical features and demonstrates a favourable performance in comparison to other similar localisation methods.

Journal ArticleDOI
TL;DR: In this paper, multilevel cyclic loading with constant stress intervals on rock salt were conducted under uniaxial compression conditions, and acoustic emission (AE) monitoring and post-test computed tomography (CT) scanning were used to evaluate the damage evolution during the loading process.

Journal ArticleDOI
TL;DR: In this article , the authors performed uniaxial compression tests on sandstone specimens containing three pre-existing flaws at various inclination angles, and the experiment results indicated that the stress-strain curves, mechanical paprameters, acoustic emission and failure pattern of pre-flawed specimen were affected by the preexisting flaws.

Journal ArticleDOI
TL;DR: In this paper , the damage characteristics of Carbon Fiber Reinforced Polymer (CFRP) composites, adhesively bonded in a Single Lap Shear (SLS) configuration, are analyzed using Acoustic Emission (AE) data recorded during the test.

Journal ArticleDOI
TL;DR: In this article, a series of uniaxial creep tests with different creep stage cut-offs on saturated intact sandstones was performed, and the brittle creep mechanism of the specimens was explored microscopically by analyzing P-wave velocity, acoustic emission (AE), and nuclear magnetic resonance (NMR) measurements.

Journal ArticleDOI
TL;DR: In this paper, the damage characteristics are analyzed using Acoustic emission (AE) data recorded during the test, and the most suitable features are selected using a methodology developed based on the Laplacian scores for feature selection.


Journal ArticleDOI
TL;DR: In this article , a methodology combining qualitative analysis employing support vector machine-based acoustic emission (AE) monitoring and quantitative analysis using AE rate process theory was proposed to evaluate masonry damage.

Journal ArticleDOI
TL;DR: In this article , the authors detect weak AE waves of dislocation slip during the compression of Zn micropillars and show that dislocation avalanches and earthquakes are essentially alike.
Abstract: Compression experiments on micron-scale specimens and acoustic emission (AE) measurements on bulk samples revealed that the dislocation motion resembles a stick-slip process - a series of unpredictable local strain bursts with a scale-free size distribution. Here we present a unique experimental set-up, which detects weak AE waves of dislocation slip during the compression of Zn micropillars. Profound correlation is observed between the energies of deformation events and the emitted AE signals that, as we conclude, are induced by the collective dissipative motion of dislocations. The AE data also reveal a two-level structure of plastic events, which otherwise appear as a single stress drop. Hence, our experiments and simulations unravel the missing relationship between the properties of acoustic signals and the corresponding local deformation events. We further show by statistical analyses that despite fundamental differences in deformation mechanism and involved length- and time-scales, dislocation avalanches and earthquakes are essentially alike.

Journal ArticleDOI
01 Aug 2022-Fuel
TL;DR: In this paper , the effect of LN 2 freezing and freeze-thaw on the mechanical properties of coal, the expansion of pores and fractures of coal samples during liquid nitrogen (LN 2 ) freezing and freezing, and the mechanisms causing damage were investigated.

Journal ArticleDOI
TL;DR: In this article , the use of acoustic emission to predict fault detection in rolling mill roller bearings in relation to the gradual rise in defect size was defined, and a bearing test rig was designed and developed to investigate various defects in rolling element bearings in a real-world environment.

Journal ArticleDOI
Hua Zhang, C.Y. Jin, Lei Wang, L. Pan, Xinyue Liu, Shan Ji 
TL;DR: In this article , the effects of loading rate and fiber content on the tensile strength and acoustic emission (AE) characteristics of basalt fiber reinforced concrete (BFRC) in dynamic splitting tests were analyzed by means of parameter analysis.

Journal ArticleDOI
TL;DR: In this article , the effects of water and fissures on rock's mechanical properties and corresponding acoustic emission characteristics were studied. But the results of this paper lay theoretical foundations for monitoring and pre-warning of engineering rock failure in water environment.

Journal ArticleDOI
Liang Shang1
TL;DR: In this article , three types of 3D angle-interlock woven composites, carbon, hybrid and UHMWPE, of the warp and weft orientations are experimentally tested via three-point bending method.