Quality classification for Turkish lignites based on moisture & ash contents and color space orientations (RGB)

In the body of this study, ash content, moisture content and calorific values data obtained from various power plants are investigated and a calorific value prediction tool for the Turkish lignites on the basis of statistical methods was proposed. Statistical evaluations were carried out either with single linear regression or multiple linear regression and effect of each parameter was aimed to understand. Statistically obtained results were considered in detail and a calorific value prediction tool for Turkish lignites was proposed. In addition to the statistical analysis, image processing was employed and RGB (Red Green Blue) analysis of the samples was carried out. In order to do so, samples were collected from the various Turkish lignite regions (same regions with the statistical analysis performed). Collected samples were prepared in accordance with the image processing procedure and analyzed in terms of their color space orientations. RGB analysis results were correlated with calorific values of each sample. Finally, moisture & ash content and image analysis results (RGB) were correlated in multi regression models and a new method for the calorific value prediction was proposed.