Experimental Study on the Characteristics of Acoustic Emission Source of Rock under Uniaxial Compression

Song, Zhaoyang

doi:10.1088/1755-1315/791/1/012003

Cited by 4 publications

(2 citation statements)

References 5 publications

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“…Some scholars [21][22][23] have conducted laboratory acoustic emission experiments to demonstrate the significant differences in the evolution patterns of microseismic characteristic parameters during the failure process of various rock types. Song [24] investigated the evolution of absolute acoustic emission energy and cumulative acoustic emission energy during the uniaxial compression failure process of granite under different loading rates. Li [25] investigated the mechanical behaviors and the variations in acoustic emission characteristic parameters, including event counts, cumulative counts, and energy, during the uniaxial compression failure process of sandstone.…”

Section: Introductionmentioning

confidence: 99%

Classification of Microseismic Signals Using Machine Learning

Chen,

Cui,

et al. 2024

Processes

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The classification of microseismic signals represents a fundamental preprocessing step in microseismic monitoring and early warning. A microseismic signal source rock classification method based on a convolutional neural network is proposed. First, the characteristic parameters of the microseismic signals are extracted, and a convolutional neural network is constructed for the analysis of these parameters; then, the mapping relationship model between the characteristic parameters of the microseismic signals and the rock class is established. The feasibility of the proposed method in differentiating acoustic emission signals under different load conditions is verified by using acoustic emission data from laboratory uniaxial compression tests, Brazilian splitting tests, and shear tests. In the three distinct laboratory experiments, the proposed method achieved a source rock classification accuracy of greater than 90% for acoustic emission signals. The proposed and verified method provides a new basis for the preprocessing of microseismic signals.

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Section: Introductionmentioning

confidence: 99%

Classification of Microseismic Signals Using Machine Learning

Chen,

Cui,

et al. 2024

Processes

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“…Researchers have also combined AE technology to further study the mechanics and AE characteristics of fissured rock masses (Zhu et al, 2019;Song, 2021). Wang et al (2019) conducted AE tests on the whole and prefabricated fissured sandstone specimens under uniaxial compression.…”

Section: Introductionmentioning

confidence: 99%

Experimental study on the effect of prefabricated fissures on the creep mechanical properties and acoustic emission characteristics of sandstone under uniaxial compression

Wang

Zhang

et al. 2022

Front. Earth Sci.

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This study investigates the effect of prefabricated fissures on the creep mechanical strength and acoustic emission (AE) characteristics of sandstone. Under the same test conditions, indoor uniaxial compression creep AE tests were performed on intact and artificially fissured sandstone specimens using a rock rheometer and a PCI-Ⅱ AE tester controlled with an RLJW-2000 microcomputer. The variation characteristics of strain, long-term strength, number of AE events, AE ringing count, AE energy, and RA value of the two specimens were then analyzed to determine the effect of prefabricated fissures on the creep mechanical properties and AE characteristics of sandstone. The results show that under the same stress level, the instantaneous strain, creep strain, and total strain of the prefabricated fissures specimen was larger than the corresponding values of the intact specimen. The prefabricated fissures exhibited the most significant influence on the creep strain of the specimen, followed by the total strain. The fissures showed the least influence on the instantaneous strain of the specimen. Furthermore, the long-term strength of the prefabricated fissures specimen was only 37.5% of that of the intact specimen. Owing to the influence of the prefabricated fissures, the long-term strength of the sandstone was significantly reduced. In engineering practice, fissures should be noted and analyzed for the potential failure of a formation. Moreover, as the stress level increases, the number of AE events of the specimen also increases. The number of AE events and cumulative AE events generated by the prefabricated fissures specimen at various stress levels is significantly higher than the corresponding values of the intact specimen. The maximum ringing count of the prefabricated fissures specimen was 7.3 times that of the intact specimen, and the maximum AE energy was 3.8 times that of the intact specimen. The cumulative AE ringing count was 1.5 times that of the intact specimen, and the cumulative energy was 4.5 times that of the intact specimen. The prefabricated fissures significantly affect the maximum AE ringing count, maximum AE energy, cumulative AE ringing count, and cumulative AE energy of the specimen. Finally, tensile fissures were the main microcracks generated inside the intact specimen during creep, and shear cracks were secondary. The microcracks generated inside the prefabricated fissures specimen consisted of mixed tension-shear cracks, but mainly consisted of shear cracks with fewer tension cracks. The RA value correlates well with the observed internal microcracks, indicating that the RA value can be used to characterize fractures in sandstone specimens. The RA value has a guiding significance for characterizing the type of internal microcracks in the process of rock creep.

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Evaluation of Rock Burst Propensity and Rock Burst Mechanism in Deep Phosphate Mines: A Case Study of Sujiapo Phosphate Mine, Hubei Province, China

Kang

Xia

Shi³

et al. 2022

Advances in Materials Science and Engineering

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Rockburst is one of the major problems in rock underground engineering and mechanics. To make a risk assessment of rockburst and improve the mine safety index, some evaluation systems for rockburst propensity have been proposed and applied, and progress has been made in the study of high-value mines and single evaluation systems, but these evaluation systems are still immature for deep low and medium grade phosphate mines with more complex influencing factors. Therefore, to solve this problem, this study takes the phosphate mining area of the Sujiapo phosphate mine as the main research object, and combines the characteristics of the deep rockburst of the phosphate mine and its physical and mechanical properties; the evaluation system combines fuzzy mathematical method and multiple evaluation methods to determine the propensity of rockburst of deep mining of Sujiapo phosphate mine. The JSM-500LV SEM and acoustic emission results are used to analyze the microscopic mechanism of rockburst from the morphology and composition of the rocks, and the rationality of the evaluation system is further demonstrated. The study shows that dolomite and phosphorite in the study area are moderate rockburst, and shale has a weak rockburst tendency; because the roof dolomite and phosphorite crystallization degree are higher, the elastic modulus is large. Under the action of external load, the roof dolomite stored more elastic strain energy. Deformation damage consumes less energy. The energy released to the outside world after the damage is large, more likely to occur brittle damage, and the rockburst tendency is high. Therefore, the evaluation system combining multiple evaluation methods can comprehensively determine rockburst in phosphate mines.

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Experimental Study on the Characteristics of Acoustic Emission Source of Rock under Uniaxial Compression

Cited by 4 publications

References 5 publications

Classification of Microseismic Signals Using Machine Learning

Classification of Microseismic Signals Using Machine Learning

Experimental study on the effect of prefabricated fissures on the creep mechanical properties and acoustic emission characteristics of sandstone under uniaxial compression

Evaluation of Rock Burst Propensity and Rock Burst Mechanism in Deep Phosphate Mines: A Case Study of Sujiapo Phosphate Mine, Hubei Province, China

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