Acoustic Emission Characteristics of Coal Failure Under Triaxial Loading and Unloading Disturbance

Zhou, Xin; Liu, Xiaofei; Wang, Xiaoran; Liu, Yubing; Xie, Hui; Du, Pengfei

doi:10.1007/s00603-022-03104-2

Cited by 54 publications

(3 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Applying the critical slowing-down theory, Kong et al [18] found that it is easier to identify the variance mutation point in the AE signal prior to coal sample failure compared to the autocorrelation coefficient. In their research, Zhou et al [19] explored the correlation between AE parameters of coal samples and disturbance amplitude. They determined that shear cracking played a significant role in the instability and failure of loaded coal.…”

Section: Introductionmentioning

confidence: 99%

Mechanical Behaviors and Precursory Characteristics of Coal-Burst in Deep Coal Mining for Safety-Sustainable Operations: Insights from Experimental Analysis

Wang,

Zhou

et al. 2024

Sustainability

Self Cite

View full text Add to dashboard Cite

Coalburst, a frequent and severe dynamic disaster, poses significant challenges to the safety and sustainable development of coal mines during deep excavation. To investigate the mechanical behaviors and precursory characteristics of coalburst subjected to in situ stress conditions, multiaxial cyclic loading experiments were conducted on cubic coal specimens, and the effects of different confining pressures on the mechanical parameters and energy evolution were analyzed. Acoustic emission (AE) technology was utilized to study the accumulation process of stress-induced damage and identify the source modes of microcracks. Then, nonlinear fractal theory and critical slowing theory were used to investigate the time-varying precursory characteristics of catastrophic failure in coalburst. The results show that as the confining pressure increases, the coal samples exhibit higher levels of elastic strain energy and dissipative energy, indicating an enhancement of plasticity. The AE count and accumulated energy show a strong correlation with cyclic loads. With an increasing number of cycles, the AE Felicity ratio gradually decreases, indicating a progressive increase in irreversible damage. Shear-mode microcracks also become more prominent with applied stress and confining pressures, as supported by varying AF/RA values of AE signals. The AE signals also follow the Hurst statistical law, and increasing applied stress and confining pressure strengthen this statistical pattern with a higher Hurst index. Throughout the cyclic loading process, certain AE varying trends were observed: the autocorrelation coefficient increased, the fractal dimension gradually decreased, and the variance suddenly increased. These trends serve as early, middle, and short–imminent warning signals, respectively, for the catastrophic failure of the loaded coal sample. These research findings contribute to a deeper understanding of coal failure evolution and provide a basis for early detection and warning of coalburst disasters, which are also essential for promoting the safe and sustainable development of deep coal mining operations.

show abstract

Section: Introductionmentioning

confidence: 99%

Mechanical Behaviors and Precursory Characteristics of Coal-Burst in Deep Coal Mining for Safety-Sustainable Operations: Insights from Experimental Analysis

Wang,

Zhou

et al. 2024

Sustainability

Self Cite

View full text Add to dashboard Cite

show abstract

“…Significant differences are observed in the study of the acoustic emission characteristics of coal samples under different conditions. 1 The mechanical properties and acoustic emission laws of coal samples under different loading directions and joint angles were studied. 2 The acoustic emission (AE) characteristics of coal under different confining pressures are studied using a triaxial compression acoustic emission positioning system.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on the Mechanical Properties and Acoustic Emission Characteristics of Different Bedding High-Rank Coals

Liu

Yang

et al. 2023

ACS Omega

View full text Add to dashboard Cite

Bedding has an important influence on the macroscopic and microscopic mechanical properties of coal, and the mechanical properties of coal and rock mass and acoustic emission characteristics are very important for rock burst monitoring and warning. In order to explore the influence of different beddings on the mechanical properties and acoustic emission characteristics of high-rank coal, using the RMT-150B electrohydraulic servo rock mechanics test system and the DS5 acoustic emission analyzer, the uniaxial compression and acoustic emission characteristics of high-rank coals with different beddings (parallel bedding 0°, oblique bedding 30, 45, 60°, and vertical bedding 90°) were investigated. The results show that the uniaxial compressive strength and deformation modulus of vertical stratified coal samples are the largest, which are 28.924 MPa and 2.95 GPa, while the average values of uniaxial compressive strength and deformation modulus of oblique stratified coal samples are the smallest, which are 10.91 MPa and 1.776 GPa, respectively. With the increase of the bedding angle, the uniaxial compressive strength of high-rank coal decreases first and then increases. The stress−strain process of coal varies greatly with different high stratification grades (parallel bedding 0°, oblique bedding 30°, 45°, 60°and vertical bedding 90°). The loading times of parallel, oblique, and vertical beddings are 700, 450, 370, 550, and 600 s, and the acoustic emission mutation point values are 495, 449, 350, 300, and 410 s. The mutation point value can be used as precursor information to judge the failure of high-rank coal in different beddings. Research results to find the high-rank coal destruction instability prediction method and the index provide a basis; further damage to the acoustic emission testing high order coal provides reference significance; and the use of acoustic emission in the monitoring and early warning of percussive ground pressure, the bedding surface of coal, and the actual stress on site should be considered.

show abstract

“…At present, the main methods of disaster monitoring are rock mechanics methods, which are mainly based on drilling cuttings and stress monitoring. The geophysical methods mainly include the microseismic method, acoustic emission method, and electromagnetic radiation method [6][7][8][9][10][11][12]. There have also been disaster hazard studies based on physical experiments using images [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Coal Mine Rock Burst and Coal and Gas Outburst Perception Alarm Method Based on Visible Light Imagery

Cheng,

Liu,

2023

Sustainability

View full text Add to dashboard Cite

To solve the current reliance of coal mine rock burst and coal and gas outburst detection on mainly manual methods and the problem wherein it is still difficult to ensure disaster warning required to meet the needs of coal mine safety production, a coal mine rock burst and coal and gas outburst perception alarm method based on visible light imagery is proposed. Real-time video images were collected by color cameras in key areas of underground coal mines; the occurrence of disasters was determined by noting when the black area of a video image increases greatly, when the average brightness is less than the set brightness threshold, and when the moving speed of an object resulting in a large increase in the black area is greater than the set speed threshold (V > 13 m/s); methane concentration characteristics were used to distinguish rock burst and coal and gas outburst accidents, and an alarm was created. A set of disaster-characteristic simulation devices was designed. A Φ315 mm white PVC pipe was used to simulate the roadway and background equipment; Φ10 mm rubber balls were used to replace crushed coal rocks; a color camera with a 2.8 mm focal length, 30 FPS, and 110° field angle was used for image acquisition. The results of our study show that the recognition effect is good, which verifies the feasibility and effectiveness of the method.

show abstract

Acoustic Emission Characteristics of Coal Failure Under Triaxial Loading and Unloading Disturbance

Cited by 54 publications

References 57 publications

Mechanical Behaviors and Precursory Characteristics of Coal-Burst in Deep Coal Mining for Safety-Sustainable Operations: Insights from Experimental Analysis

Mechanical Behaviors and Precursory Characteristics of Coal-Burst in Deep Coal Mining for Safety-Sustainable Operations: Insights from Experimental Analysis

Experimental Study on the Mechanical Properties and Acoustic Emission Characteristics of Different Bedding High-Rank Coals

Coal Mine Rock Burst and Coal and Gas Outburst Perception Alarm Method Based on Visible Light Imagery

Contact Info

Product

Resources

About