An FSV analysis approach to verify the robustness of the triple-correlation analysis theoretical framework

Robert M.X. Wu, Zhongwu Zhang, Huan Zhang, Yongwen Wang, Niusha Shafiabady, Wanjun Yan, Jinwen Gou, Ergun Gide, Siqing Zhang

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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.

Original languageEnglish
Article number9621
Pages (from-to)1-20
Number of pages20
JournalScientific Reports
Issue number1
Publication statusPublished - Dec 2023


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