Abstract-Recognition of coal from other minerals in powder form using terahertz spectroscopy

 

Jingjing Deng, Jan Ornik, Kai Zhao, Enjie Ding, Martin Koch, and Enrique Castro-Camus

 We show micrographs of the powders produced, the bottom of each image shows a ruler with a spacing of 1mm between marks. The samples shown are Siltstone (a) sieve 1 (691 𝜇$\mu$m-1204 𝜇$\mu$m) and (b) sieve 5 (222 𝜇$\mu$m-512 𝜇$\mu$m), as well as Fat coal (c) sieve 1 (691 𝜇$\mu$m-1204 𝜇$\mu$m) and (d) sieve 5 (222 𝜇$\mu$m-512 𝜇$\mu$m

https://www.osapublishing.org/oe/fulltext.cfm?uri=oe-28-21-30943

Currently a significant fraction of the world energy is still produced from the combustion of mineral coal. The extraction of coal from mines is a relatively complex and dangerous activity that still requires the intervention of human miners, and therefore in order to minimize risks, automation of the coal mining process is desirable. An aspect that is still under investigation is potential techniques that can recognize on-line if the mineral being extracted from the mine is coal or if it is the surrounding rock. In this contribution we present the proof of concept of a method that has potential for recognition of the extraction debris from mining based on their terahertz transmission.

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Abstract-Spectral characterization of the key parameters and elements in coal using terahertz spectroscopy

• Honglei Zhan^a, b, 
• Kun Zhao^b, , , 
• Lizhi Xiao^a
• 
  
• http://www.sciencedirect.com/science/article/pii/S0360544215013390

The augmenting necessity of energy saving and environmental protection has led to the increasing technical requirements about on-line monitoring of key parameters and elements in coal. In this study, terahertz spectroscopy combined with PCA (principal components analysis) was employed to analyze nine kinds of coal materials. Due to the strong absorption of the organics with the relatively high C/H ratio, such as aromatic compounds, coals with lower hydrogen content show higher absorption effects in terahertz range. Based on PC1 score calculated by PCA, the anthracite and bituminous coal can be clearly classified, and the clean as well as meagre coals were also distinguished by opposite trends. All the critical points in PCA system are in agreement with those (volatile matter and ash, respectively) classified in international standard of coal classification. In addition, significant elements, including carbon, hydrogen, nitrogen and sulfur, can be directly characterized using PC1 score with linear and non-linear models. This research indicates that the terahertz spectral analysis of key parameters and elements of coal is a promising tool for improving the detection method and advancing the technical innovation in coal processing industry.