ABSTRACT

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.

摘要

确定和持续监测煤炭的质量参数（近似值和热值分析）对于采矿、发电和贸易目的至关重要。尽管近端分析和热分析对于监测是强制性的，但在线方法使用昂贵的独立设备不断确定这些参数。很少有研究使用煤表面光学变化的图像分析来预测煤质参数。本研究旨在检验煤样表面颜色可能是煤质参数指标的假设。提出了一种通过分析煤样的彩色图像来估计给定煤的灰分含量、固定碳和总热值的新方法。通过近似分析和热分析检查了来自土耳其七个低阶煤田的 35 个煤样。对于这项初步研究，它们被拍摄以获得数字图像，处理以计算每个像素的 RGB 代码为 8 位值和归一化的 RGB 代码，即色度值。分析表明，蓝色和红色色度值与灰分含量、固定碳含量和热值高度相关。