Nonlinear time series analysis of limestone rock failure process

Abstract

Nonlinear analysis of the rock mass failure process is a powerful tool for the study of instability and prevention of disaster in rock mass engineering. Nonlinear analysis has rapidly developed in recent decades. We propose a new method to determine the fractal characteristics of the failure process using time series analysis based on an iterative cycle division of the box dimension of fractal theory. We use AE technology to carry out time series analysis of fracture sources in the failure process of rock mass. We show that the disordered failure of rock mass exhibits notable fractal characteristics in the time series. The advantage of this method is that only the time and frequency of AE monitoring are used, resulting in a better identification and classification of damage, compared with traditional natural sequence frequency distribution. In addition, MATLAB numerical simulation analysis shows that these time series fractal dimensions can accurately characterize the failure characteristics of rock mass. In brief, we show the potential for future orderly time analyses of the complex and disorderly process of rock mass failure.