Affiliation:
1. School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo 454000, China
2. Henan Key Laboratory for Green and Efficient Mining & Comprehensive Utilization of Mineral Resources, Henan Polytechnic University, Jiaozuo 454000, China
3. School of Emergency Management and Safety Engineering, China University of Mining & Technology, Beijing 100083, China
Abstract
Coal spontaneous combustion (CSC) is a serious threat to the safe mining of coal resources, and the selection of suitable gas indicators to predict the CSC state is crucial for the prevention and control of coal mine fires. In this paper, the temperature-programmed experiment of CSC was first carried out to analyze the gas components and compositions in the oxidative pyrolysis process of three coal samples (lignite, long-flame coal, and lean coal) with different coalification degrees. Subsequently, the spontaneous combustion tendency of these three coal samples was evaluated. Finally, through the variation of gas concentration, gas concentration ratio, and fire coefficient with coal temperature, the indicators suitable for predicting the spontaneous combustion of coal were preferred, and a multi-parameter indicator system was established to make a comprehensive judgment on the spontaneous combustion status of coal. The results show that coal rank is negatively correlated with oxygen consumption rate. The higher the coalification degree of coal, the slower the oxidation reaction and the later the characteristic temperature point appears. The lignite selected in this experiment is a type of coal that is more prone to spontaneous combustion than long-flame coal and poor coal, and the CO concentration, C2H6/CH4, and second fire coefficient R2 can be used as the main indicators for predicting CSC, while the other gases, olefin-alkane ratio and fire coefficient can be used as auxiliary indicators. To some extent, the research content can effectively and accurately determine the stage and degree of coal spontaneous combustion, which has a certain guiding role in predicting CSC.
Funder
Henan Key Laboratory for Green and Efficient Mining and Comprehensive Utilization of Mineral Resources
National Natural Science Foundation of China
key scientific and technological project of Henan Province
Subject
Earth and Planetary Sciences (miscellaneous),Safety Research,Environmental Science (miscellaneous),Safety, Risk, Reliability and Quality,Building and Construction,Forestry
Cited by
1 articles.
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