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

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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.

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Funding

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

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Authors and Affiliations

  1. College of Safety Science and Engineering of Henan Polytechnic University, Jiaozuo, Henan, 454000, China

    Guoxun Jing, Fei Zhou, Zhiyang Gao & Shaoshuai Guo

  2. President’s Office of Anyang Institute of Technology, Anyang, Henan, 455000, China

    Guoxun Jing

Authors
  1. Guoxun Jing
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  2. Fei Zhou
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  3. Zhiyang Gao
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  4. Shaoshuai Guo
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Correspondence to Fei Zhou.

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Jing, G., Zhou, F., Gao, Z. et al. Study on safety early warning system of miner’s physiological indexes. Cluster Comput 22 (Suppl 4), 9151–9157 (2019). https://doi.org/10.1007/s10586-018-2091-5

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  • DOI: https://doi.org/10.1007/s10586-018-2091-5

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