Abstract
Gas explosions and outbursts were the leading types of gas accidents in mining in China with gas concentration exceeding the threshold limit value (TLV) as the leading cause. Current research is focused mainly on using machine learning approaches for avoiding exceeding the TLV of the gas concentration. no published reports were found in the literature of attempts to uncover the correlation between gas data and other data to predict gas concentration. This research aimed to fill this gap and develop an innovative gas warning system for increasing coal mining safety. A mixed qualitative and quantitative research methodology was adopted, including a case study and correlational research. This research found that strong correlations exist between gas, temperature, and wind. It suggests that integrating correlation analysis of data on temperature and wind into gas would improve warning systems' sensitivity and reduce the incidence of explosions and other adverse events. A Unified Modeling Language (UML) model was developed by integrating the Correlation Analysis Theoretical Framework to the existing gas monitoring system for demonstrating an innovative gas warning system. Feasibility verification studies were conducted to verify the proposed method. This informed the development of an Innovative Integrated Gas Warning System which was deployed for user acceptance testing in 2020.
Highlights
China is the world’s largest coal producer and has the fourth largest coal reserves
Coal mine methane is produced or emitted in association with coal mining activities either from the coal seam itself or from other gassy formations underground, and has always been considered as a danger for underground coal mining as it can create a serious threat to mining safety and productivity due to explosion risk (Karacan et al 2011, 121)
Fourteen studies focused on temperature, wind, dust, C2H2, CO2, CO, O2, humidity, and other parameters to predict gas concentrations, including Ma and Zhu (2016), Fan et al (2017), Zhang et al (2017), Xia et al (2018), Jo et al (2019), Song et al (2019), Tutak and Brodny (2019), Wang et al (2019), Sun and Li (2020), Wang et al (2020), Zhang et al (2020), Zhang et al (2020a), Zhao et al (2020), and Zhang et al (2021)
Summary
China is the world’s largest coal producer and has the fourth largest coal reserves. Its coal output remained at similar levels in 2020 as in 2019 to 3,690 MT which accounted for about 46% of global coal production (Hutzler 2020; IEA 2020). Coal mine methane is produced or emitted in association with coal mining activities either from the coal seam itself or from other gassy formations underground, and has always been considered as a danger for underground coal mining as it can create a serious threat to mining safety and productivity due to explosion risk (Karacan et al 2011, 121). Gas monitoring systems are deployed widely in China’s coal mine industry. They are believed to have contributed to a decrease in gas accidents from 414, with the death toll reached 2171 in 2005 to 7, with the death toll reached 30 in 2020 (China Coal Safety 2021). Hazardous accidents are still a problem in underground gassy mines and there is a need for more robust monitoring and early-warning systems for improving coal mining safety (Jo et al 2019, 183)
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