Abstract
Previous studies have shown that water can reduce the acoustic emission (AE) energy and other parameters during rock failure. However, the fracture mechanism of rock can be better reflected by analyzing the AE waveform. Therefore, this paper conducted experiments of uniaxial compression on sandstone samples of various water contents and collected AE signals simultaneously. Analyses of fast Fourier transform (FFT) and Hilbert-Huang transform (HHT) were performed on the AE waveform when the sample failed. The results show that as the water content increases, the frequency and intensity of the AE signal will decrease. The influence of water on the intensity of the AE signal is greater than that on the frequency. Through the analysis of the energy mechanism of rock failure, it is pointed out that the frequency and intensity of AE signal are closely related to elastic energy index W ET and burst energy index K E . The research results have guiding significance for the monitoring of rockburst.
Highlights
As the depth of underground engineering increases, the surrounding rock masses suffer higher ground stress, higher temperature, high permeability pressure, and strong disturbance; rock dynamic disasters such as rockburst occur frequently [1, 2]
Hilbert-Huang transform (HHT) analysis was performed on the Acoustic emission (AE) waveforms when the samples failed and compared with the classical waveform analysis method (fast Fourier transform (FFT))
Sandstone samples of different water contents were employed to carry out experiments of uniaxial compression and collect AE signals
Summary
As the depth of underground engineering increases, the surrounding rock masses suffer higher ground stress, higher temperature, high permeability pressure, and strong disturbance; rock dynamic disasters such as rockburst occur frequently [1, 2]. The analysis methods of AE signal during rock failure under load mainly include parameter analysis and waveform analysis [9]. The parameter analysis is a method used to make statistics of the characteristic parameters (including energy and count) of the AE waveform during the rock failure process, which is able to reflect the degree of rock damage [10]. Waveform analysis can directly reflect the rock fracture mechanism [11]. Extensive research [12,13,14,15] shows that the AE signal of rock is mainly manifested as high frequency and low amplitude under lower stress levels; at higher stress levels, low-frequency and highamplitude AE signals will appear accompanied by large-scale fractures in the rock. Zhu et al [17] suggested that the middle-frequency AE signals may be connected with the friction of fracture surfaces
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