Title :
Technique of dynamically warning of coalmine gas outburst based on Bayesian network
Author :
Li, Yang ; Mao, Shanjun ; Xie, Hong ; Xu, Hongzhi ; Li, Mei
Author_Institution :
Inst. of Remote Sensing & Geographic Inf. Syst., Peking Univ., Beijing, China
Abstract :
The accident potential of coalmine production has the character of dynamically changing and uncertainty in spatial distribution. In this paper, after comprehensive analysis of the basic data of potential accident and the time series data, combining the coal mine safety management practice, based on mine-specific geographic information system platform, and considering the dynamic changes of ventilation network, the author built the coal mine safety production identify and early warning system based on Bayesian network, which could give early warning of potential underground gas accident, thereby providing better scientific basis for of accidents prevention, and thus reducing the incidence of accidents.
Keywords :
alarm systems; belief networks; coal; geographic information systems; mining; time series; Bayesian network; accident potential; coalmine gas outburst; coalmine production; geographic information system; spatial distribution; time series; ventilation network; warning; Accidents; Bayesian methods; Coal mining; Hazards; Production; Ventilation; Bayesian network; GIS; early warning; ventalition network;
Conference_Titel :
Geoinformatics, 2011 19th International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-849-5
DOI :
10.1109/GeoInformatics.2011.5980784