TY - JOUR
T1 - The relationship between coal surface chromaticity and coal quality parameters
T2 - a preliminary investigation
AU - Başyiğit, Mikail
AU - Özer, Samet Can
AU - Fişne, Abdullah
N1 - Publisher Copyright:
© 2021 Taylor & Francis Group, LLC.
PY - 2021
Y1 - 2021
N2 - Determining and continuously monitoring the quality parameters (proximate and calorific value analysis) of coal is crucial for mining, power generation, and trading purposes. Although proximate and calorific analyses are compulsory for monitoring, on-line methods continuously determine these parameters using expensive, detached equipment. Few studies predict the coal quality parameters using image analysis of the optical changes of coal surfaces. This study aimed to test the hypothesis that the surface color of coal samples might be an indicator for coal quality parameters. A novel method is proposed to estimate the ash content, fixed carbon, and gross calorific value of the given coals by analyzing the colored images of coal samples. Thirty-five coal samples from seven lower-rank coalfields in Turkey were examined through proximate and calorific analyses. For this preliminary study, they were photographed to obtain digital images, processed to calculate each pixel’s RGB codes as 8-bit values and normalized RGB codes, i.e., chromaticity values. The analyses showed that blue and red chromaticity values are highly correlated with ash content, fixed carbon content, and calorific values.
AB - Determining and continuously monitoring the quality parameters (proximate and calorific value analysis) of coal is crucial for mining, power generation, and trading purposes. Although proximate and calorific analyses are compulsory for monitoring, on-line methods continuously determine these parameters using expensive, detached equipment. Few studies predict the coal quality parameters using image analysis of the optical changes of coal surfaces. This study aimed to test the hypothesis that the surface color of coal samples might be an indicator for coal quality parameters. A novel method is proposed to estimate the ash content, fixed carbon, and gross calorific value of the given coals by analyzing the colored images of coal samples. Thirty-five coal samples from seven lower-rank coalfields in Turkey were examined through proximate and calorific analyses. For this preliminary study, they were photographed to obtain digital images, processed to calculate each pixel’s RGB codes as 8-bit values and normalized RGB codes, i.e., chromaticity values. The analyses showed that blue and red chromaticity values are highly correlated with ash content, fixed carbon content, and calorific values.
KW - chromaticity
KW - Coal quality
KW - coal surface color
KW - gross calorific value
KW - image analysis
UR - http://www.scopus.com/inward/record.url?scp=85107483761&partnerID=8YFLogxK
U2 - 10.1080/19392699.2021.1931148
DO - 10.1080/19392699.2021.1931148
M3 - Article
AN - SCOPUS:85107483761
SN - 1939-2699
JO - International Journal of Coal Preparation and Utilization
JF - International Journal of Coal Preparation and Utilization
ER -