Damage precursor of construction rocks under uniaxial cyclic loading tests analyzed by acoustic emission. (10th May 2019) - Dexing, Li; Enyuan, Wang; Xiangguo, Kong; Haishan, Jia; Dongming, Wang; Muhammad, Ali
Highlights: Uniaxial cyclic loading and unloading tests are carried out on granite and marble specimens. The precursor information of AEs from these specimens are investigated. A proposal that can predict rock failure during loading-unloading process more accurately is put forward. Abstract: Engineering practice shows that rock is commonly loaded cyclically during construction. Acoustic emissions (AEs) are still not effective for use as damage assessment precursors for rocks under cyclic loading-unloading. To explore more accurate damage precursors based on multiple AE indices, uniaxial loading-unloading tests were carried out on granite and marble specimens. The results show that at low stress levels, there are almost no AEs generated in the unloading stage but at higher stress levels, there are numerous AE events in the unloading part of the cycle. In each loading-unloading test, the AE count rate, R AE, of each cycle shows a steadily increasing trend as the test progresses but the rate increases sharply in the last cycle. During the entire loading-unloading series, the AEs exhibited Kaiser effect and Felicity effects and the Felicity ratio, R F, decreases as the cycle number increases. In addition, during rock deformation and failure, the R F variations can be divided into three phases: Phase I, R F > 1 ; Phase II, 0.6 < R F ≤ 1 ; Phase III, R F ≤ 0.6 . The AEs do not show fractal characteristics during the first and second cycles but fractal features begin to appear in the third cycle. The correlation dimension, D, declines rapidly after the third cycle and then continues to decline slightly until the specimen ruptures. Combinations of R AE, R F and D can be used as signals for rock failure warnings and these combined indices can increase the accuracy of rock dynamic disaster predictions, especially for rocks under loading-unloading cycles. The research findings reported here should provide a more efficient method for issuing early warnings for dynamic rock disasters and provide guidance for the development of warning strategies.