A new collaborative research with Charles Darwin University (CDU) and University Technology Sydney (UTS) suggests that better monitoring of wind, gas density, and temperatures in coal mines might help lower the likelihood of disasters.
The study, titled ‘An FSV analysis approach to verify the robustness of the triple-correlation analysis theoretical framework,’ focuses on constructing a gas monitoring system that holistically assesses wind, gas, and temperature conditions.
The initiative utilised data from a significant Global Fortune 500 mining company in China, which owned 46% of global coal output in 2020.
According to co-author and CDU Faculty of Science and Technology Associate Professor Niusha Shafiabady, the study looked at real-time data and found three significant correlations between gas, temperature, and wind.
The research indicated that the framework may be utilised to create a more sensitive gas warning system to minimise the occurrence of gas explosions.
“A significant number (3,284) of coal mines have high gas content at outburst-prone risk levels across almost 26 major coal mining provinces in China,” Associate Professor Shafiabady explained.
“For example on 10 June 2020, a serious coal and gas outburst accident occurred in Liaoyuan, China which resulted in seven deaths and two injuries, with resulted in seven deaths and two injuries, with a direct economic loss of 16.66 million yuan ($3.4 million),” she continued.
She said monitoring coal and rock dynamic hazards in real-time during coal mining operations is critical.
CDU, UTS, Shanxi Normal University, Central Queensland University, Taiyuan Normal University, Shanxi Fenxi Mining Industry Group Co, and Shanxi Fenxi Mining Zhongxing Coal Industry Co conducted the research.
According to Associate Professor Shafiabady, the study’s findings might be applied by mining companies to avert gas incidents.
“The outcomes of this study can also be used in other industries such as chemical industry, oil and gas industry, water treatment plants and semiconductor manufacturing industries,” she said.
“Currently we are working on creating a real-time Artificial Intelligence decision making system with the ability to predict the accidents as an addition to the current designed gas monitoring system,” she added.
