2000
DOI: 10.1016/s1365-1609(99)00126-4
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Laboratory studies of acoustic emission prior to uniaxial compressive rock failure

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Cited by 87 publications
(39 citation statements)
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“…Figures 5 and 6 show that AE signals were generated from within the siltstone specimens throughout the entire uniaxial compression process until failure occurred, that the stress-strain relationship curves between the change in AE count rate and specimens were consistent, and that the maximum value of AE count rate was near the peak stress value. The total AE count curves had the same tendency and approximate shape as the stress-strain curves, which indicated that the AE count rate could characterize the compressive failure process of rocks; this finding is similar to that found in previous studies [25,[29][30][31][32].…”
Section: Characteristics Of the Ae Countsupporting
confidence: 88%
“…Figures 5 and 6 show that AE signals were generated from within the siltstone specimens throughout the entire uniaxial compression process until failure occurred, that the stress-strain relationship curves between the change in AE count rate and specimens were consistent, and that the maximum value of AE count rate was near the peak stress value. The total AE count curves had the same tendency and approximate shape as the stress-strain curves, which indicated that the AE count rate could characterize the compressive failure process of rocks; this finding is similar to that found in previous studies [25,[29][30][31][32].…”
Section: Characteristics Of the Ae Countsupporting
confidence: 88%
“…The rockburst is a class of rock failure where strain energy is suddenly released by an unstable fracture of rock [1][2][3][4]. Typically occurring in deep underground mines, rockburst is a common disaster.…”
Section: Introductionmentioning
confidence: 99%
“…e peak strength is the macroscopic representation of rock, which cannot reflect internal damage evolution. As an important method in acoustic nondestructive testing, rock internal defects and damage evolution process can be accurately monitored by acoustic emission (AE) detection [16][17][18][19].…”
Section: Introductionmentioning
confidence: 99%