A method for identifying the fire status through ventilation systems using tracer gas for improved rescue effectiveness in roadway drivage of coal mines

被引:13
作者
Lei, Baiwei [1 ]
He, Binbin [1 ]
Zhao, Zidong [2 ]
Xu, Guang [3 ]
Wu, Bing [1 ]
机构
[1] China Univ Min & Technol Beijing, Sch Emergency Management & Safety Engn, Beijing 100083, Peoples R China
[2] Curtin Univ, WA Sch Mines Minerals Energy & Chem Engn, Kalgoorlie, WA 6430, Australia
[3] Missouri Univ Sci & Technol, Dept Min Engn, Rolla, MO 65401 USA
基金
国家重点研发计划;
关键词
Mine fire; Tracer gas; Ventilation; Rescue;
D O I
10.1016/j.psep.2021.05.010
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
When a coal mine fire occurs, the rescue of trapped mine workers is difficult, because some efficient firefighting measures (such as nitrogen injection) cannot be implemented. The development and severity of a fire is difficult to determine, and the integrity of the auxiliary ventilation system may be unknown. These situations pose additional challenges to the trapped mine workers and increase the difficulty level for the rescue team. A novel method using the tracer gas technique is developed to remotely gather information to determine the location and severity of the fire. Laboratory experiments were conducted to understand the tracer gas distribution characteristics when the fire causes damage to the ventilation duct. A mathematical model was developed that uses the tracer gas concentration curve to determine the location and severity of the fire. The model combines the Expectation Maximization (EM) algorithm with the Gaussian Mixture (GM) model. Validated using experimental data, it is demonstrated that the method can determine the fire location with low error. The information collected using this method reflects basic living environmental conditions of the trapped mine workers and provides important input for quickly formulating an effective fire rescue plan that saves lives. (c) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:151 / 157
页数:7
相关论文
共 29 条
[1]  
[Anonymous], 2009, SHILLONG TIMES SHILL
[2]   MAXIMUM LIKELIHOOD FROM INCOMPLETE DATA VIA EM ALGORITHM [J].
DEMPSTER, AP ;
LAIRD, NM ;
RUBIN, DB .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL, 1977, 39 (01) :1-38
[3]  
Francart W.J, 2003, SME ANN C EXP SALT L
[4]  
Guo J, 2019, PROCESS SAF ENVIRON
[5]   A Gaussian-mixture-based image segmentation algorithm [J].
Gupta, L ;
Sortrakul, T .
PATTERN RECOGNITION, 1998, 31 (03) :315-325
[6]   Robust generative asymmetric GMM for brain MR image segmentation [J].
Ji, Zexuan ;
Xia, Yong ;
Zheng, Yuhui .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2017, 151 :123-138
[7]   Localization of a coal seam fire using combined self-potential and resistivity data [J].
Karaoulis, M. ;
Revil, A. ;
Mao, D. .
INTERNATIONAL JOURNAL OF COAL GEOLOGY, 2014, 128 :109-118
[8]   UMAP and LSTM based fire status and explosibility prediction for sealed-off area in underground coal mine [J].
Kumari, K. ;
Dey, Prasanjit ;
Kumar, Chandan ;
Pandit, Dewangshu ;
Mishra, S. S. ;
Kisku, Vikash ;
Chaulya, S. K. ;
Ray, S. K. ;
Prasad, G. M. .
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2021, 146 :837-852
[9]   Comparative study of single inert gas in confined space inhibiting open flame coal combustion [J].
Lei, Baiwei ;
He, Binbin ;
Xiao, Bowen ;
Du, Peiying ;
Wu, Bing .
FUEL, 2020, 265
[10]  
Li K, 2009, COMB C CHIN SOC ENG