Based on the Characterization of Combustion Gas Generation in High-Temperature Fire Zone and the Analysis of Indicator Preference

Coal spontaneous combustion fire is one of the major safety hazards in coal mining, posing a serious threat to mine safety and personnel lives. Studying the combustion state of fire zones and the generation patterns of indicative gases is conducive to developing targeted control measures, which is of great significance for achieving early warning of coal mine fires and ensuring safe production. However, the temperature prediction ranges based on characteristic gases established in existing studies are relatively low, making it difficult to meet the identification requirements for the entire coal combustion process under high‑temperature and low‑oxygen conditions. To address this issue, this study focuses on the identification of the whole combustion process of coal in high‑temperature low‑oxygen fire zones. Using a fixed‑bed online mass spectrometry experimental platform, coal samples were heated from room temperature to 600°C in a programmed temperature‑raising manner, and the generation patterns of 15 characteristic gases (including carbon oxides, hydrocarbon gases, and their derivative indicators) were systematically analyzed during the heating process of two low‑rank coal samples under three low‑oxygen volume fractions (5%, 9%, and 13%). To screen the key indicators that characterize coal temperature states at different stages, the gray relational analysis and entropy method were further combined to establish an optimization method for selecting indicative gases throughout the entire coal spontaneous combustion process. This study systematically reveals the gas generation rules during the whole process of coal fire combustion and establishes a preferred indicator gas system, providing a theoretical basis for the prediction and monitoring of coal fire combustion.