Early Violent Failure Precursor Prediction Based on Infrared Radiation Characteristics for Coal Specimens Under Different Loading Rates

The early prediction of violent coal-bearing strata failure using effective monitoring is crucial to avoid losses due to catastrophic failures and geological disasters to ensure safe and efficient underground deep coal mining. In this study, the early coal failure precursor was established by researching the application of critical slowing down theory (CSDT) using two infrared radiation (IR) indexes, i.e., variance IR temperature (VIRT) and variance of differential infrared image temperature (VDIIT) under different loading rates. The CSDT parameters: variance and autocorrelation, are evaluated using both indexes in different time window and lag step lengths. The test results revealed that the abrupt and significant fluctuations in variance and autocorrelation for both indexes occurred during rock deformation and before the violent damage. The autocorrelation comparatively shows an obvious reliable fluctuation due to stationarity (show no change in fluctuation before the inflection point), which can be used as a precursor for violent rock failure. It has been shown that the stress level of autocorrelation at the inflection point decreases inversely with the loading rate for both indexes. These stress levels for VIRT are 0.920, 0.890, 0.865, and 0.813 of the σ max under the corresponding loading rates of 0.1, 0.4, 0.7, and 1.0 mm/min, respectively. For VDIIT, at loading rates of 0.1, 0.4, 0.7, and 1.0 mm/min the stress levels are 0.930, 0.892, 0.870, and 0.815 σ max , respectively. Therefore, it has been recommended that the prediction performance of precursory characteristics of IR can be improved by applying the CSDT for an early prediction of rock failure.