STUDY ON THE FEATURE OF ELECTROMAGNETIC RADIATION UNDER COAL OXIDATION AND TEMPERATURE RISE BASED ON MULTIFRACTAL THEORY

Fractals ◽  
2019 ◽  
Vol 27 (03) ◽  
pp. 1950038 ◽  
Author(s):  
BIAO KONG ◽  
ENYUAN WANG ◽  
ZENGHUA LI ◽  
WEI LU

During coal oxidation and temperature rise, a significantly large amount of electromagnetic radiation (EMR) signals are generated as a result of thermal deformation and thermal cracking. The generation of EMR signal is the comprehensive embodiment of the physical and chemical changes in coal during its oxidation and subsequent heating. Therefore, the generated signals contain complex and rich messages that can reflect the changes in the internal structure of coal. In this work, the characteristics of EMR signal were analyzed by multifractal theory. Multifractal analysis was used to deconstruct EMR signals. Our preliminary study indicated that the multifractal spectrum of the EMR signal had a feature of small probability event. Further analysis demonstrated that the characteristic parameters of EMR signal are quite different at the later heating stage from those at the early heating stage. At the initial stage of coal spontaneous combustion, the multifractal spectrum of the signal is wider, but when coal combustion is reached, the scale range of EMR signal increases significantly, and its structure changes at different temperature ranges. The research results presented provide a basis for monitoring and presenting an early warning of coal spontaneous combustion risk.

2013 ◽  
Vol 20 (4) ◽  
pp. 709-718
Author(s):  
Yan-Ming Wang ◽  
Wen-Zheng Wang ◽  
Zhen-Lu Shao ◽  
De-Ming Wang ◽  
Guo-Qing Shi

Abstract Coal spontaneous combustion is an extremely complicated physical and chemical changing process. In order to improve the indicator gases detection technology and coal spontaneous combustion monitoring, a novel forecast method for toxic gases emission from coal oxidation at low temperature is presented in this paper. The experiment system is setup combined with frequency-domain terahertz technology and coal temperature programming device. The concentration curves of carbon monoxide and sulphur dioxide gases from coal spontaneous combustion are estimated according to molecule terahertz spectra. The influences of coal rank and oxygen supply on coal spontaneous combustion characteristics are discussed. Both carbon monoxide and sulphur dioxide gases absorption spectra show the characteristic equi-spaced absorption peaks. Results demonstrate that under the condition of lean oxygen, there exists a critical oxygen concentration in the process of coal oxidation at low temperature. Comparing with Fourier infrared spectrum testing, the presented method is highly accurate and more sensitive, especially suitable for early-stage monitoring of the indicator gases produced by coal spontaneous combustion.


Author(s):  
F. A. Golynskaya ◽  
R. A. Nikonov

The paper presents the results of studies of coal spontaneous combustion and forecast of Tainin section of Kansk Deposit of Kansko-Achinsky basin. To this end, a new original methodology has been applied, based on the rank data model and the idea of classifying these data by «proximity» to reference groups of observations. As a result of studying of a geological structure of the investigated layer, physical and chemical researches and the analysis of statistical data on self-ignition of coals, the geological factors of self-ignition of coals and boundary values of their parameters of different degree of danger of self-ignition have been established. Transition from the initial data of a coal bed to a rank scale has been carried out with the use of standards (boundary values) of levels of danger of spontaneous combustion of coals. The obtained data were used in the construction of the self-ignition prediction map of coal bed «Powerful» (Moschnyi) using the program ArcMap 10.2 from the family of geographic information programs ArcGIS.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Li Shen ◽  
Qiang Zeng

AbstractIn the present paper, with using diverse methods (including the SEM, the XRD, the TPO, the FTIR, and the TGA) , the authors analysed samples of the major coal seam in Dahuangshan Mining area with different particle sizes and with different heated temperatures (from 50 to 800 °C at regular intervals of 50 °C). The results from SEM and XRD showed that high temperature and high number of pores, fissures, and hierarchical structures in the coal samples could facilitate oxidation reactions and spontaneous combustion. A higher degree of graphitization and much greater number of aromatic microcrystalline structures facilitated spontaneous combustion. The results from TPO showed that the oxygen consumption rate of the coal samples increased exponentially with increasing temperature. The generation rates of different gases indicated that temperatures of 90 °C or 130 °C could accelerate coal oxidation. With increasing temperature, the coal oxidation rate increased, and the release of gaseous products was accelerated. The FTIR results showed that the amount of hydroxide radicals and oxygen-containing functional groups increased with the decline in particle size, indicating that a smaller particle size may facilitate the oxidation reaction and spontaneous combustion of coal. The absorbance and the functional group areas at different particle sizes were consistent with those of the heated coal samples, which decreased as the temperature rose. The results from TGA showed that the characteristic temperature T3 declined with decreasing particle size. After the sample with 0.15–0.18 mm particle size was heated, its carbon content decreased, and its mineral content increased, inhibiting coal oxidation. This result also shows that the activation energy of the heated samples tended to increase at the stage of high-temperature combustion with increasing heating temperature.


2021 ◽  
Author(s):  
Xin‐xiao Lu ◽  
Xue Xue ◽  
Cheng‐yan Wang ◽  
Guo‐yu Shi ◽  
Yun Xing ◽  
...  

ACS Omega ◽  
2021 ◽  
Vol 6 (10) ◽  
pp. 6681-6690
Author(s):  
Xuanxuan Huang ◽  
Yongliang Xu ◽  
Yan Wang ◽  
Yao Li ◽  
Lanyun Wang ◽  
...  

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