Predicting the failure of rock using critical slowing down theory on acoustic emission characteristics.

• The fractal dimension of rock crushing particle size was studied by fractal theory. • The response characteristics of time–frequency domain parameters in rock failure process are analyzed by AE. • AE multi-parameters are calculated by critical slowing down theory to predict rock failure. The joint surfaces and size affect the mechanical behavior and failure precursors of shale. Therefore, this paper studies the mechanical behavior, the response characteristics of acoustic emission (AE) and critical slowing down (CSD) characteristics of AE for shale with different joint surfaces and size. The results show that with an increase in the number of joint surfaces and the size of the sample, the crack initiation stress, uniaxial compressive strength (UCS), peak strain, and fractal dimension decrease. During the plastic stage, the occurrence of a sharp rise in AE ringing count, RA, a low-frequency, high-amplitude AE signal, and a rapid drop in AF can be characteristics of impending sample failure. Variance and autocorrelation coefficients can be used to characterize the CSD phenomenon. The optimal window length and lag step are determined to be 400 and 100, respectively. The CSD characteristics of the autocorrelation coefficient and the variance of multi-AE parameters are obtained. The variance-based early warning time provides short-term early warning, while the autocorrelation coefficient-based early warning time provides early warning. The research results can provide theoretical references for the mechanical design and failure prediction of underground rock engineering. [ABSTRACT FROM AUTHOR]