Citation

Li Z, Ma Y, Zheng A, He S, Wang F, Zhang X. China Saf. Sci. J. 2020; 30(11): 53-59.

Copyright

(Copyright © 2020, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2020.11.008

PMID

unavailable

Abstract

In order to improve prediction accuracy of coal and gas outburst risk in driving work face, and improve precise management of dangerous areas, firstly, an optimized grey prediction model of coal and gas outburst was constructed and verified by tested data of 1101 and 1102 track driving work faces of Wujia coal mine. Secondly, average relative error of their outburst risk prediction indexes were calculated to be 2. 46% and 1. 2% respectively. Then, fuzzy matter-element early warning model for coal and gas outburst was established with four warning levels of " none, mild, moderate, and severe". Finally, a three-dimensional visualization model for outburst was developed with 3D MAX software, which realized visual display of risks in driving work face. The results show that the optimized model improves prediction accuracy of coal and gas outburst, and and the visualization model can directly decide outburst risks in front of driving work face. © 2020 China Safety Science Journal

Language: zh