Fast Predicting the Washability of Coal Using Digital Image Processing Method

Abstract

Based on the demand of real-time control and digital coal preparation, a pure new MATLAB-based image recognition system was developed to compute the coal particle density distribution through the digital image processing method, 13 of 29 image feature parameters was selected to be most representative image characteristic parameters through the analysis of statistics and graphs. Take the above parameters as the input of RBF neural network, the density level of coal particles could be estimated, combined with the cross-sectional area of coal particles and the ash content of each density level, the washability curve could be drawed. Experement show, the absolute error of the total ash is 0.545%, which meets the China standards of coal preparation(GB/T477-1998); the related coefficients of each indicator in both actual and predicted float-and-sink material are all close to 1, while the curves of λ, β, θ and δ are very similar and the deviation of ξ curve is relatively large.