Particle Measure Of Coal Powder Based On Microobservation And Image Processing

The physical structure of coal powder is a factor to effect capability for combustion. Investigation on it has important significance for research of preparation and combustion.Along with development of the image processing techniques and improvement of micro-observation, particle detection based on micro-observation and image processing techniques has been brought forward. This thesis applies the detection method to analysis of coal powder. Through image processing of micro image, morphologic eigenvalue can be calculated.Particle morphologic and fractal are applied to process of image processing. Morphologic parameters have been brought forward: area, girth, diameter, shape factor, fractal of edge and fractal of distribution. Particle size gets from statistic of pixel and fractal of particle gets from linear fit of dates. Via statistical data of particle pictures, automatic measure for particle parameters has been realized.After calculation of morphologic parameters, contrast them to conventional characteristics. Then find connection between physical structure and combustion characteristics. The mutative tendency of particle characteristic has been research while morphologic parameters change.Aim at basis feature of particle image, this thesis designs arithmetic for particle and describes arithmetic in detail. This method's computational efficiency and accuracy are better than traditionary measure methods. Also the result of calculation is intuitionistic. As one method for analysis of coal powder, measure by image processing can get morphologic characteristics quickly. This method can be applied to research on combustion characteristics of coal and factors to affect boiler work.