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Research Article

Classification of Spontaneous Combustion Hazard Levels of Coal with Different Metamorphism Degrees

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Pages 1459-1472 | Received 10 Mar 2022, Accepted 19 Aug 2022, Published online: 25 Aug 2022

References

  • Botao, Q., Z. Xiaoxing, W. Deming, et al. 2021. Research progress of coal spontaneous combustion process characteristics and prevention technology. Coal Sci. Technol 49 (1):66–99.
  • Deming, W. 2018. Thermodynamic disaster in coal mine and its characteristics. J. China Coal Soc 43 (01):137–42.
  • Deming, W., S. Zhenlu, and Z. Yunfei. 2021. Several scientific issues on major thermodynamic disasters in coal mines. J. China Coal Soc 46 (01):57–64.
  • Heping, X., R. Shihua, X. Yachen, and J. Xiaomiao. 2021. Development opportunity of the coal industry towards the goal of carbon neutrality. J. China Coal Soc 46 (07):2197–211.
  • Jun, D., L. Changkui, C. Kai, et al. 2018. Random Forest method of predicting coal spontaneous combustion in gob. J. China Coal Soc 43 (10):2800–08.
  • Jun, D., Y. Yifan, and Z. Xiaowei. 2014. Fuzzy evaluation on risk of coal spontaneous combustion based on AHP. J. Saf. Sci. Technol 10 (04):120–25.
  • Jun, D., B. Zujin, X. Yang, and S. Zeyang. 2020. Present situation and challenge of coal spontaneous combustion disasters prevention and control technology. Saf. Coal Mines 51 (10):118–25.
  • Kumari, K., P. Dey, C. Kumar, S. S. Dewangshu Pandit, M. V. Kisku, G. M. Ray, S. K. Chaulya, S. K. Prasad, and G. M. Prasad. 2021.Umap and lstm based fire status and explosibility prediction for sealed-off area in underground coal mine. Process Saf. Environ. Prot 146: 837–52.doi: 10.1016/j.psep.2020.12.019
  • Lei, C., J. Deng, K. Cao, et al. 2019. A comparison of random forest and support vector machine approaches to predict coal spontaneous combustion in gob. Fuel. 239(1):297–311. doi:10.1016/j.fuel.2018.11.006.
  • Li, C.-Y., L. Zhao, M. Li, Y.-L. Zhao, X.-M. Cui, and H.-B. Chai. 2020. Prediction of surface progressive subsidence and optimization of predicting model parameters based on the Logistic time function. J. Saf. Environ 20 (06):2202–10.
  • Liang, Y. 2020. Challenges and countermeasures for high quality development of China’s coal industry. J. China Coal Soc 46 (01):6–12.
  • Lu, P., G.X. Liao, S. J. H, et al. 2004. Experimental research on index gas of the coal spontaneous at low-temperature stage[j]. J. Loss Prev. Process Ind. 17(3):243–47. doi:10.1016/j.jlp.2004.03.002.
  • Minggao, Y., C. Jiangkun, and J. Hailin. 2013. Comprehensive dividing method and practice of spontaneous combustion “three-zone” in goaf on fully mechanized coal face. J. Henan Polytech. Univ. (Nat. Sci) 32 (2):131–5, 150.
  • Wang, H. B. Z., E. M. Dlugogorski, and E. M. Kennedy. 2003. Pathways for production of CO 2 and CO in low-temperature oxidation of coal. Fuel 17 (1):150–58. doi:10.1021/ef020095l.
  • Wanxing, R., G. Qing, S. Jingtai, et al. 2021. Construction of early warning indicators for coal spontaneous combustion based on statistical characteristics of index gases. J. China Coal Soc 46 (06):1747–58.
  • Wen, H., H. Wang, and W.-Y. Liu. 2020.Comparative study of experimental testing methods for characterization parameters of coal spontaneous combustion. Fuel 275: 117880.doi: 10.1016/j.fuel.2020.117880
  • Xiao, Y., S.J. Ren, D. Jun, et al. 2018. Comparative analysis of thermokinetic behavior and gaseous products between first and second coal spontaneous combustion. Fuel 227:325–33. doi:10.1016/j.fuel.2018.04.070.
  • Xiaoxing, Z., W. Deming, and Y. Xiaodan. 2010. Test method of critical temperature of coal spontaneous combustion based on the temperature. J. China Coal Soc 35 (S1):128–31.
  • Xinghua, M.A., and Z.H.A.N.G. Jinxin. 2014. The comparison among the common normality tests for numerical variables. J. Evid. Based. Med 14 (02):123–28.
  • Xu, X.-C., C.-H. Chen, H.-Y. Qi, R. He, C. You, and G. Xiang. 2000. Development of coal combustion pollution control for SO2 and Nox in China. Fuel Process. Technol 62 (2–3):153–60. doi:10.1016/S0378-3820(99)00116-2.
  • Yuan, M., X. Donghai, S. Bo, and G. Aoxiang. 2020. Statistics and analysis of coal mine production safety accidents in China from 2010 to 2019. Mineral. Eng. Res 35 (04):27–33.
  • Yuping, J. 2013. Forecasting of coal spontaneous combustion based on Algebra Neural Networks. J. Math. Pract. Theory 43 (18):122–28.
  • Zhang, D., X.-X. Cen, W.-F. Wang, J. Deng, H. Wen, Y. Xiao, and C.-M. Shu. 2021.The graded warning method of coal spontaneous combustion in Tangjiahui Mine. Fuel 288: 119635.doi: 10.1016/j.fuel.2020.119635
  • Zhang, Y. T., Y.-B. Zhang, Y.-Q. Li, Q.-P. Li, J. Zhang, and C.-P. Yang. 2020.Study on the characteristics of coal spontaneous combustion during the development and decaying processes. Process Saf. Environ. Prot 138: 9–17.doi: 10.1016/j.psep.2020.02.038
  • Zhijin, Y., W. Hu, C. Xiaokun, et al. 2017. Simulation on ignition source evolution features of large-scale coal spontaneous combustion experiment. Coal Sci. Technol 45 (1):89–93, 141.

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