A correlational research on developing an innovative integrated gas warning system: a case study in ZhongXing, China
Article
Article Title | A correlational research on developing an innovative integrated gas warning system: a case study in ZhongXing, China |
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ERA Journal ID | 124658 |
Article Category | Article |
Authors | Wu, Robert M. X. (Author), Yan, Wanjun (Author), Zhang, Zhongwu (Author), Gou, Jinmen (Author), Fan, Jianfen (Author), Liu, Bao (Author), Shi, Yong (Author), Shen, Bo (Author), Zhao, Haijun (Author), Ma, Yanyun (Author), Soar, Jeffrey (Author), Sun, Xiangyu (Author), Gide, Ergun (Author), Sun, Zhigang (Author), Wang, Peilin (Author), Cui, Xinxin (Author) and Wang, Ya (Author) |
Journal Title | Geomatics, Natural Hazards and Risk |
Journal Citation | 12 (1), pp. 3175-3204 |
Number of Pages | 30 |
Year | 2021 |
Place of Publication | United Kingdom |
ISSN | 1947-5705 |
1947-5713 | |
Digital Object Identifier (DOI) | https://doi.org/10.1080/19475705.2021.2002953 |
Web Address (URL) | https://www.tandfonline.com/doi/full/10.1080/19475705.2021.2002953 |
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. |
Keywords | Case study; correlational research; gas monitoring system; machine learning; warning system |
ANZSRC Field of Research 2020 | 460999. Information systems not elsewhere classified |
Public Notes | � 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Byline Affiliations | Shanxi Normal University, China |
Shanxi Fenxi Mining Zhongxin Coal Industry, China | |
GENEW Technologies, China | |
School of Business | |
XiShan Coal Electricity Group, China | |
Central Queensland University | |
Shanxi Kailain Technology, China | |
Zhejiang University, China | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q6w7q/a-correlational-research-on-developing-an-innovative-integrated-gas-warning-system-a-case-study-in-zhongxing-china
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