A Triple-Correlation Framework for Demonstrating an Innovative Gas Warning System: A Case Study in China

Abstract This research aims to develop an innovative gas warning system for improving production safety in the underground coal mining industry. Coal mining is an important sector for China’s economic development; gas monitoring systems are widely adopted as almost 60% of coal mining accidents are caused by gas. Existing gas monitoring systems mainly focus on simply detecting real-time data obtained from gas sensors. The literature review did not find gas monitoring systems that provide alarms or warnings from the correlation of gas with data from other sensors. This research aims to fill this gap to uncover hidden patterns and correlations between gas and temperature, wind, and dust, and incorporate data analytics into developing an innovative, integrated gas warning system. Correlational research was adopted using 328,320 data outputs obtained from ZhongXing Co. Ltd in Dec 2019. The study found strong relations between gas and temperature, wind, and dust. A Triple-Correlation Theoretical Framework and a Unified Modeling Language (UML) model were developed for an innovative gas warning system. As a result of this research, the ZhongXing Innovative Gas Warning System was developed and deployed for user acceptance testing on 28 Aug 2020.