Study on the destabilizing damage precursors of cemented tailings backfill based on critical slowing down theory combined with multiple denoising algorithms under consideration of initial defect conditions

Abstract

The cemented tailings backfill (CTB) with initial defects is more prone to destabilization damage under the influence of various unfavorable factors during the mining process. In order to investigate its influence on the stability of underground mining engineering, this paper simulates the generation of different degrees of initial defects inside the CTB by adding different contents of air-entraining agent (AEA), investigates the acoustic emission RA/AF eigenvalues of CTB with different contents of AEA under uniaxial compression, and adopts various denoising algorithms (e.g., moving-average smoothing, median filtering, and outlier detection) to improve the accuracy of the data. The variance and autocorrelation coefficients of RA/AF parameters were analyzed in conjunction with the critical slowing down (CSD) theory. The results show that the acoustic emission RA/AF values can be used to characterize the progressive damage evolution of CTB. The denoising algorithm processed the AE signals to reduce the effects of extraneous noise and anomalous spikes. Changes in the variance curves provide clear precursor information, while abrupt changes in the autocorrelation coefficient can be used as an auxiliary localization warning signal. The phenomenon of dramatic increase in the variance and autocorrelation coefficient curves during the compression-tightening stage, which is influenced by the initial defects, can lead to false warnings. As the initial defects of the CTB increase, its instability precursor time and instability time are prolonged, the peak stress decreases, and the time difference between the CTB and the instability damage is smaller. The results provide a new method for real-time monitoring and early warning of CTB instability damage.

Keywords

initial defects / cemented tailings backfill / critical slowing down / acoustic emission RA/AF values / denoising algorithms

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