EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 233 (2021) E3S Web Conf., 233 (2021) 01002 References
Open Access
Issue
E3S Web Conf.
Volume 233, 2021
2020 2nd International Academic Exchange Conference on Science and Technology Innovation (IAECST 2020)
Article Number 01002
Number of page(s) 6
Section NESEE2020-New Energy Science and Environmental Engineering
DOI https://doi.org/10.1051/e3sconf/202123301002
Published online 27 January 2021
  1. ZENG Qiang. Study on the thermal dynamic characteristics of combustion system for coal fires in xinjiang region[D]. Xuzhou: China University of Mining and Technology, 2012. [Google Scholar]
  2. BP (2018) (2018) BP Statistical Review of World Energy [Google Scholar]
  3. HOU Shen-jian, WANG DONG, ZHANG BO, et al. Development of China’s coal rsources exploration in the new era[J]. Journal of Xi’an University of Science and Technology, 2019, 39 (2): 341-346. [Google Scholar]
  4. ZHANG Jianmin, GUAN Haiyan, CAO Daiyong, etc. Research and treatment of underground coal fire in China [M]. Beijing: Coal Industry Press, 2008. [Google Scholar]
  5. WU Jian-ming,ZHANG Jin-hua,WU Yu-guo. Detection on Spontaneous Combustion Area in Surface Mine and Study on Comprehensive Control Technology of Spontaneous Combustion Area[J]. Coal Engineering, 2012(02):53-56. [Google Scholar]
  6. Slavecki R.J. Detection and location of subsurface coal fires; proceedings of the Proceedings of the third Symposium on Remote Sensing of Environment, F, 1964 [C]. [Google Scholar]
  7. Li J., Voight S., Kunzer C., et al. The Progress in Detecting of Coal Fire on Remote Sensing*The first Result of the Joint Sino-German Research Project on Innovative Technologies for Exploration, Extinction and Monitoring of Coal Fires in North China; proceedings of the 2005 Dragon Symposium, F, 2006 [C]. [Google Scholar]
  8. Elick Jennifer-M.. Mapping the coal fire at Centralia, Pa using thermal infrared imagery[J]. International Journal of Coal Geology, 2011, 87(3): 197-203. [CrossRef] [Google Scholar]
  9. Mine Fire Disaster Control Based on Infrared Imaging Technology[J].Coal Science and Technology, 2010, 38(1): 28-30. [Google Scholar]
  10. ZHENG Xuezhao; JIA Yongxiao; GUO Jun; et al, Research status and prospect of coalfield fire monitoring technologies[J]. Industry and Automation, 2019,45(05):6-10+61. [Google Scholar]
  11. ZHANG Xin-hai, NIU Heng, FEI Jin-biao. Using Measuring Radon Method to Detect Spontaneous Fire Location in Bayili Coal Mine[J]. Safety in Coal Mines, 2009, 40(7):29–30. [Google Scholar]
  12. FEI Jin-biao, WEN HU, JIN Yong-fei. Application of radon method in detection of fire area in shallow coal seam[J]. Journal of Xi’an University of Science and Technology, 2018, 38(01): 26-30. [Google Scholar]
  13. Song Yanchao, Wang Junlin, Shang Bing, Cui Hongxing, Wu Yunyun. Study on a new charcoal closed chamber method for measuring radon exhalation rate of building materials[J]. Radiation Measurements, 2020. [Google Scholar]
  14. Determining the Spontaneous Combustion Boundary of Northern Shaanxi Coal Seam Using High Precision Magnetic Method[J]. Advances in Geosciences, 2019, 9(5): 360-367. [CrossRef] [Google Scholar]
  15. ZHANG Xinhai; MIAO Yuhui; ZHANG Duo; et al, Experimental Study on Change Laws of Characteristic Gases and Magnetic in the Process of Coal Spontaneous Combustion[J]. Safety in Coal Mines, 2017,48(03):36-39. [Google Scholar]
  16. Ide Taku-S, Crook N, Orr jr. et al, Magnetomete rmeasurements to characterize a subsurface coal fire[J]. International Journal of Coal Geology, 2011, 87(3): 190-196. [Google Scholar]
  17. WANG Wen-zheng, MA Li-yang, LU Shi-yuan, et al . Forward Modeling for Magnetic Anomaly of Multilayer Burnt Rocks in Coal Fire Area[J]. Science Technology and Engineering, 2013, 13(20): 5924-5926. [Google Scholar]
  18. Shao Z, Wang D, Wang Y, et al. Theory and application of magnetic and self-potential methods in the detection of the Heshituoluogai coal fire, China[J]. Journal of Applied Geophysics, 2014, 104:64-74. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.