Abstract
Mastering the precursory information of rock failure is the basis of scientifically predicting rockburst, and AE technology is an effective means to solve this problem. The conventional uniaxial loading and cyclic loading/unloading tests of metagabbro and granite were carried out with GAW‐2000 uniaxial electrohydraulic rigid testing machine to evaluate rockburst proneness. The energy evolution and AE characteristics of rocks with different rockburst proneness during loading are revealed. The results show that the rockburst proneness of granite is obviously stronger than that of metagabbro based on the comprehensive evaluation method of multiple rockburst proneness index. The reasons for different rockburst proneness are analyzed from the perspective of mineral composition and microstructure. Rockburst proneness is positively correlated with energy storage capacity. The elastic energy ratio of granite is obviously larger than that of metagabbro before peak stress. The intensity of AE signals generated in the failure process of strong rockburst rock (granite) is significantly higher than that of moderate rockburst rock (metagabbro). However, the peak frequency bands and amplitude all increase obviously before failure. The b‐value and memory characteristics of rock with different rockburst proneness have obvious similar change rules.
Highlights
With the depletion of shallow resources, a great number of countries have gradually entered the deep mining stage
With the further increase of stress level, the local stress concentration is easy to occur at the edge of large-scale cracks, and microcracks are further developed at the edge of large-scale cracks. e number of microcracks is obviously larger than that of small-scale cracks, and the low-amplitude and low-energy AE signals are released
The AE bvalue increases slightly, which is the main reason for the fluctuating decline under higher stress level
Summary
With the depletion of shallow resources, a great number of countries have gradually entered the deep mining stage. AE signals contain a lot of information about crack propagation and coalescence It could infer internal structure alteration and failure mechanism under different stress levels, and the rockburst could be effectively predicted based on AE signals. AE signals are used to study the evolution process of rock fracture development by characteristic parameters such as ring counting rate, event rate, and energy rate. There are few comparison studies on energy evolution and AE characteristics of rocks with different rockburst proneness during cyclic loading/unloading. Uniaxial cyclic loading/unloading testing is conducted on rocks with different rockburst proneness, and energy evolution and AE characteristics of rocks with different rockburst proneness are obtained. E relationship between damage evolution, energy accumulation and release, and AE precursor information before the failure of rocks with different rockburst proneness is clarified.
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