Pattern recognition prediction of coal and gas outburst hazard in the sixth mine of Hebi

被引:2
作者
张宏伟 [1 ]
宋卫华 [1 ]
杨恒 [2 ]
张明杰 [2 ]
机构
[1] College of Resource and Environment Engineering,Liaoning Technical University,Fuxin 123000,China
[2] Hebi Coal Electric Co.,Ltd.,Hebi 458000,China
基金
中国国家自然科学基金;
关键词
coal and gas outburst; multi-factor; prediction units; pattern recognition; probability prediction;
D O I
暂无
中图分类号
TD713 [煤(岩石)与瓦斯突出的预防和处理];
学科分类号
081903 ;
摘要
Based on the systematical analysis influence factors of coal and gas outburst, the main factors and their magnitude was determined by the corresponding methods.With the research region divided into finite predicting units,the internal relation between the factors and the hazard of coal and gas outburst,that was combination model of influence factors,was ascertained through multi-factor pattern recognition method.On the basis of contrastive analysis the pattern of coal and gas outburst between prediction region and mined region,the hazard of every predication unit was determined.The mining area was then divided into coal and gas outburst dangerous area,threaten area and safe area re- spectively according to the hazard of every predication unit.Accordingly the hazard of mining area is assessed.
引用
收藏
页码:248 / 251
页数:4
相关论文
共 50 条
[41]   Coal Mine Rock Burst and Coal and Gas Outburst Perception Alarm Method Based on Visible Light Imagery [J].
Cheng, Jijie ;
Liu, Yi ;
Li, Xiaowei .
SUSTAINABILITY, 2023, 15 (18)
[42]   Stress Distribution Characteristics Near Small Coal Faults and Prediction of Coal and Gas Outburst Risk [J].
Wang, Lin ;
Liu, Jiabin ;
Chen, Xiangjun ;
Guo, Hanxiao ;
Feng, Shuailong .
GREENHOUSE GASES-SCIENCE AND TECHNOLOGY, 2025, 15 (02) :142-153
[43]   Coal mine rock burst and coal and gas outburst perception alarm method based on thermal infrared image [J].
Cheng J. ;
Liu Y. ;
Li X. .
Meitan Xuebao/Journal of the China Coal Society, 2023, 48 (05) :2236-2248
[44]   Coal mine rock burst and coal and gas outburst image perception alarm method based on depth characteristics [J].
Cheng J. ;
Liu Y. .
Meitan Kexue Jishu/Coal Science and Technology (Peking), 2024, 52 (03) :245-257
[45]   Research on Temperature Variation during Coal and Gas Outbursts: Implications for Outburst Prediction in Coal Mines [J].
Zhang, Chaolin ;
Wang, Enyuan ;
Xu, Jiang ;
Peng, Shoujian .
SENSORS, 2020, 20 (19) :1-17
[46]   Particle sizing of coal mine dust by pattern recognition of laser diffraction [J].
Zhao, YL ;
Dong, ZC .
AUTOMATED OPTICAL INSPECTION FOR INDUSTRY, 1996, 2899 :617-621
[47]   Application of in-situ Stress Measurement on Coal and Gas Outburst Regional Prediction [J].
Song Weihua ;
Zhang Hongwei .
PROGRESS IN SAFETY SCIENCE AND TECHNOLOGY, VOL. VIII, PTS A AND B, 2010, 8 :1667-1671
[48]   Regional prediction of coal and gas outburst by geo-dymamic division method [J].
Chen, ZH ;
Duan, KX ;
Zhang, YJ .
PROCEEDINGS IN MINING SCIENCE AND SAFETY TECHNOLOGY, 2002, :403-406
[49]   Coal and gas outburst prediction model based on extension theory and its application [J].
Wang, Wei ;
Wang, Hanpeng ;
Zhang, Bing ;
Wang, Su ;
Xing, Wenbin .
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2021, 154 :329-337
[50]   Study on the law of initial gas expansion energy and its feasibility in coal and gas outburst prediction [J].
Zhongzhong Liu ;
Hanpeng Wang ;
Bing Zhang ;
Shitan Gu .
Environmental Science and Pollution Research, 2023, 30 :60121-60128