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Laboratory Studies on Remote Method to Assess the Damage in Underground Mines after an Emergency
Process Safety and Environmental Protection
  • Baiwei Lei
  • Chenguang Zhao
  • Zidong Zhao
  • Bing Wu
  • Guang Xu, Missouri University of Science and Technology
Abstract

Obtaining fast and accurate access to disaster information for underground mines is key in order to enact safe and effective emergency rescue measures. This study proposes a method to remotely evaluate the damage status in underground mines after a mine accident by using a tracer gas. This discussion includes the laws of migration, mixing and separating the tracer gas in the airway, and the superposition of the tracer gas concentration curve conforms to the Gaussian Mixture Model (GMM), which can be decomposed by the expectation-maximization (EM) algorithm. Based on the EM algorithm, the tracer gas method can assess the location and severity of the airway damage. The results show that the error between the calculated damage location and the actual damage location is very small. In addition, the area ratio of the concentration curve after the decomposition by the EM algorithms is highly correlated with the severity of the airway damage. This study demonstrates that the tracer gases can be used to remotely evaluate the location and severity of a mine accident, which is critical in order to perform successful rescue and emergency management.

Department(s)
Mining Engineering
Keywords and Phrases
  • Concentration curve,
  • Expectation-maximization (EM) algorithm,
  • Gaussian Mixture Model (GMM),
  • Mine accident,
  • Tracer gas
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2021 Elsevier, All rights reserved.
Publication Date
4-1-2021
Publication Date
01 Apr 2021
Disciplines
Citation Information
Baiwei Lei, Chenguang Zhao, Zidong Zhao, Bing Wu, et al.. "Laboratory Studies on Remote Method to Assess the Damage in Underground Mines after an Emergency" Process Safety and Environmental Protection Vol. 148 (2021) p. 1337 - 1345 ISSN: 0957-5820
Available at: http://works.bepress.com/guang-xu/57/