Application of hierarchical clustering for classification of coal seams with respect to their proneness to spontaneous heating

Abstract

This paper presents an investigation into the application of hierarchical clustering method for classification of coal seams with respect to their spontaneous heating susceptibility. In this research work, 31 coal samples were collected from different Indian coalfields covering both fiery and non-fiery coal seams of varying ranks spreading over 8 different mining companies. Proximate, ultimate and petrographic analyses have been carried out to determine the intrinsic properties of these samples. Five different experimental methods, viz. crossing point temperature (CPT), differential thermal analysis (DTA), critical air blast (CAB) analysis, wet oxidation potential difference analysis and differential scanning calorimetric (DSC) studies have been used to study the spontaneous heating susceptibility indices of these samples. Correlation studies have been carried out considering the intrinsic properties of coal obtained from proximate, ultimate and petrographic analyses as independent variables, and different susceptibility indices as dependent variables. This study has helped to identify the appropriate intrinsic properties, viz. moisture, volatile matter and ash content, obtained from proximate analysis; and susceptibility indices such as CPT, average slope of stage IIA of DTA thermogram, CAB value and onset temperature obtained from DSC thermogram, for classification of coal seams. By using these parameters, the hierarchical clustering method has been applied to classify the coal seams into four different categories, which will be useful for taking appropriate measures in advance for preventing the occurrence of mine fires.