Citation

Yutao Z, Qiang GUO, Yuanbo Z, Yaqing LI, Yali SUN. China Saf. Sci. J. 2024; 34(1): 125-132.

Copyright

(Copyright © 2024, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2024.01.0774

PMID

unavailable

Abstract

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.

Key words: correlation coefficient method, coal spontaneous combustion risk, apparent activation energy, low temperature oxidation, indicator gas, critical temperature

CLC Number:

X936

Language: en