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Correlation analysis and prediction of coal spontaneous combustion risk based on correlation coefficient method
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Yutao ZHANG1, 2, Qiang GUO1, 2, Yuanbo ZHANG1, 2, Yaqing LI1, Yali SUN1
China Safety Science Journal | 2024, 34(1) : 125 - 132
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China Safety Science Journal | 2024, 34(1): 125-132
Safety engineering technology
Correlation analysis and prediction of coal spontaneous combustion risk based on correlation coefficient method
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Yutao ZHANG1, 2, Qiang GUO1, 2, Yuanbo ZHANG1, 2, Yaqing LI1, Yali SUN1
Affiliations
  • 1 School of Safety Science and Engineering,Xi'an University of Science and Technology,Xi'an Shaanxi 710054,China
  • 2 Shaanxi Key Laboratory of Prevention and Control of Coal Fire,Xi'an Shaanxi 710054,China
Published: 2024-01-28 doi: 10.16265/j.cnki.issn1003-3033.2024.01.0774
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In order to shorten the identification time of coal spontaneous combustion tendency,firstly,industrial analyzer and temperature programmed test device were used to measure the coal quality index value and the content of coal spontaneous combustion indicator gas at different temperatures. The critical temperature point of low-temperature oxidation was determined by CO volume fraction. Then,the equation between temperature and oxygen consumption rate was fitted through the Arrhenius formula,and the apparent activation energy of each coal sample at different stages before and after the critical temperature was solved. The correlation between the coal quality index value and the apparent activation energy before and after the critical temperature was analyzed by Pearson correlation coefficient method,and the correlation coefficient was calculated. Finally,the coal quality index value with the largest correlation coefficient was selected,and a multiple linear regression model for calculating the apparent activation energy of coal samples was established to analyze and predict the spontaneous combustion risk of coal. The results show that the correlation coefficients between different components of coal quality and the apparent activation energy before and after the critical temperature are significantly different. The negative correlation coefficients between volatile matter and the apparent activation energy before and after the critical temperature are the largest,which are -0.893 and -0.977 respectively. The positive correlation coefficients between fuel ratio and the apparent activation energy before and after the critical temperature are the largest,which are 0.956 and 0.968 respectively. The fitting degree of the established multiple linear regression model can reach 0.912 5 and 0.933 0.

correlation coefficient method  /  coal spontaneous combustion risk  /  apparent activation energy  /  low temperature oxidation  /  indicator gas  /  critical temperature
Yutao ZHANG, Qiang GUO, Yuanbo ZHANG, Yaqing LI, Yali SUN. Correlation analysis and prediction of coal spontaneous combustion risk based on correlation coefficient method[J]. China Safety Science Journal, 2024 , 34 (1) : 125 -132 . DOI: 10.16265/j.cnki.issn1003-3033.2024.01.0774
Year 2024 volume 34 Issue 1
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doi: 10.16265/j.cnki.issn1003-3033.2024.01.0774
  • Receive Date:2023-08-15
  • Online Date:2025-07-09
  • Published:2024-01-28
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  • Received:2023-08-15
  • Revised:2023-11-20
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    1 School of Safety Science and Engineering,Xi'an University of Science and Technology,Xi'an Shaanxi 710054,China
    2 Shaanxi Key Laboratory of Prevention and Control of Coal Fire,Xi'an Shaanxi 710054,China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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