矿业科学学报 (Feb 2021)

Risk identification, monitoring and early warning of typical coal mine dynamic disasters during the 13th Five-Year Plan period

  • Yuan Liang

DOI
https://doi.org/10.19606/j.cnki.jmst.2021.01.001
Journal volume & issue
Vol. 6, no. 1
pp. 1 – 8

Abstract

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Risk identification, monitoring and early warning of typical coal mine dynamic disasters such as rock burst, coal and gas outburst is the focus and difficulty of coal mine safety production. During the 13th Five-Year Plan period. In order to solve this problem, we carried out the research on the development of key technologies and equipment for risk identification, monitoring and early warning of typical power disasters in coal mines, a new theory of breeding and evolution mechanism and occurrence and development of coal mine dynamic disaster under the effect of mining disturbance and multi-field coupling superposition was established, the intelligent identification theory and early warning method of multi parameter precursory information of typical dynamic disasters in coal mines were put forward; the precursory information acquisition and sensing technology and equipment with fault self-diagnosis, high sensitivity and long calibration period were developed. Through the research of heterogeneous data fusion, ad hoc network, anti-interference and other technologies, the comprehensive collection of man-machine environment parameters and multi information in key areas of coal mines are proposed The new method of common network transmission provides technical support for the safe and trouble free operation of coal mine typical power disaster monitoring and early warning system. An automatic, informatized and intelligent early warning platform is constructed, which realizes the functions of fault self diagnosis, high sensitivity, short response time, long calibration period, anti-interference, etc., and the early warning accuracy is improved to more than 90 %. Through the organic integration of early warning basic research, key technology development and application demonstration has realized online monitoring, intelligent identification and real-time accurate early warning of hidden major disasters in coal mine have been realized.

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