Quantitative analysis method for infrared characterization of coal damage under load based on image enhancement and pixel extraction

Abstract

To explore the quantification method of infrared thermal image characteristics in the coal loaded-damage process and better reflect the infrared precursor information and damage evolution of coal, in this paper, a new index based on the color extraction of thermal image pixel points, infrared high-temperature anomaly area ratio (IHAR), is proposed to quantitatively analyze the infrared thermal image characteristics in combination with image processing technology. The results show that: after the denoising and enhancement based on the double-domain decomposition and improved CLAHE algorithm, the infrared thermal image effect is improved; the change of IHAR index is controlled by stress, with significant characteristics of stages, which are synchronized and consistent with the infrared thermal image sequence; The precursors of IHAR show significant increase and fluctuation, and the time point is around 60% to 65% of the peak stress; compared with other infrared indicators, IHAR is better in terms of stage, easy identification of precursors, and validity of damage characterization, which can effectively reflect the evolution process of coal loaded damage, and provide early warning information for coal destabilization monitoring.