Abstract

Among all the gas disasters, gas concentration exceeding the threshold limit value (TLV) has been the leading cause of accidents. However, most systems still focus on exploring the methods and framework for avoiding reaching or exceeding TLV of the gas concentration from viewpoints of impacts on geological conditions and coal mining working-face elements. The previous study developed a Trip-Correlation Analysis Theoretical Framework and found strong correlations between gas and gas, gas and temperature, and gas and wind in the gas monitoring system. However, this framework's effectiveness must be examined to determine whether it might be adopted in other coal mine cases. This research aims to explore a proposed verification analysis approach—First-round—Second-round—Verification round (FSV) analysis approach to verify the robustness of the Trip-Correlation Analysis Theoretical Framework for developing a gas warning system. A mixed qualitative and quantitative research methodology is adopted, including a case study and correlational research. The results verify the robustness of the Triple-Correlation Analysis Theoretical Framework. The outcomes imply that this framework is potentially valuable for developing other warning systems. The proposed FSV approach can also be used to explore data patterns insightfully and offer new perspectives to develop warning systems for different industry applications.

Details

Title
An FSV analysis approach to verify the robustness of the triple-correlation analysis theoretical framework
Author
Wu, Robert M. X. 1 ; Zhang, Zhongwu 2 ; Zhang, Huan 2 ; Wang, Yongwen 3 ; Shafiabady, Niusha 4 ; Yan, Wanjun 5 ; Gou, Jinwen 6 ; Gide, Ergun 7 ; Zhang, Siqing 8 

 University of Technology Sydney, Faculty of Engineering and Information Technology, Sydney, Australia (GRID:grid.117476.2) (ISNI:0000 0004 1936 7611); Shanxi Normal University, School of Geography, Taiyuan, China (GRID:grid.510766.3) (ISNI:0000 0004 1790 0400) 
 Shanxi Normal University, School of Geography, Taiyuan, China (GRID:grid.510766.3) (ISNI:0000 0004 1790 0400) 
 Shanxi Fenxi Mining Industry (Group) Co. Ltd, Jiexiu, China (GRID:grid.510766.3) 
 Charles Darwin University (Sydney Campus), Faculty of Science and Technology, Sydney, Australia (GRID:grid.1043.6) (ISNI:0000 0001 2157 559X) 
 Shanxi Fenxi Mining Industry (Group) Co. Ltd, Jiexiu, China (GRID:grid.1043.6) 
 Shanxi Fenxi Mining Zhongxing Coal Industry Co. Ltd, Lvliang, China (GRID:grid.1043.6) 
 Central Queensland University, School of Engineering and Technology, Sydney, Australia (GRID:grid.1023.0) (ISNI:0000 0001 2193 0854) 
 Taiyuan Normal University, Taiyuan, China (GRID:grid.443576.7) (ISNI:0000 0004 1799 3256) 
Pages
9621
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2825650480
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.