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Cluster Computing

, Volume 22, Supplement 4, pp 9151–9157 | Cite as

Study on safety early warning system of miner’s physiological indexes

  • Guoxun Jing
  • Fei ZhouEmail author
  • Zhiyang Gao
  • Shaoshuai Guo
Article
  • 51 Downloads

Abstract

Most of the coal mine accidents in China are due to human errors. Human errors are mainly owing to the high tensions of miners’ working conditions and physiological abnormalities, which lead to a series of mishandling. This paper forms physiological index safety early warning system based on the physiological information of coal miners. Physiological data of miners are measured in real time through this method. The data can be statistically analyzed horizontally and vertically to judge the health status of miners and make an early warning to provide an efficient way to reduce the number of accidents.

Keywords

Physiological indicators Environmental factors Early warning Human reliability 

Notes

Funding

Funding was provided by National Natural Science Foundation of China (Grant No. 51474098).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Guoxun Jing
    • 1
    • 2
  • Fei Zhou
    • 1
    Email author
  • Zhiyang Gao
    • 1
  • Shaoshuai Guo
    • 1
  1. 1.College of Safety Science and Engineering of Henan Polytechnic UniversityJiaozuoChina
  2. 2.President’s Office of Anyang Institute of TechnologyAnyangChina

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