Experimental investigation of the fracture and damage evolution characteristics of flawed coal based on electric potential and acoustic emission parameter analyses

Abstract

Flawed coal is the most common construction object in the mining process, and understanding its mechanical behavior and damage evolution is crucial for monitoring the stability of underground projects. In this work, uniaxial compression experiments on flawed coal were conducted, and the electric potential (EP) and acoustic emission (AE) signals were recorded synchronously. An in-depth study of the fracture mode and damage evolution characteristics of coal samples based on EP and AE responses was conducted. The results showed that (1) as loading proceeds, the coal body stress increases, the EP and AE values increase, and EP and AE are excited whenever the stress drop phenomenon occurs. With the gradual expansion of the initial flaws, the EP field and AE event distributions show regional differences. High-intensity EP anomaly bands are generated in the path of the main crack formation, and many high-energy AE events are generated. (2) The fractured behavior of the coal sample is dramatically altered by flaw inclination. When the flaw inclination increases, the AE signals show a shift from the common distributions of the six types to the concentrated distributions of the low amplitude–low frequency (LA–LF) and high amplitude–low frequency (HA–LF) types, the coal sample destruction modes are transformed from dominantly tensile to mixed tensile and shear, and the destruction mode is increasingly complicated. (3) It is possible to evaluate and analyze the damage evolution characteristics of the coal samples by defining the coefficient of variation (CV value) of the EP and the b value of the AE. Both a sudden increase in the CV value and a sudden decrease in the b value can be used as precursor information for coal failure. A two-parameter joint monitoring approach can be used to precisely and promptly warn about coal instability damage. The research results can provide theoretical support for the stability assessment of coal structures during the deep coal seam mining process and early warning of the occurrence of dynamic disasters.