Abstract
Automatic control of fine coal cleaning circuits has traditionally been limited by the lack of sensors for on-line ash analysis. Although several nuclear-based analyzers are available, none have seen widespread acceptance. This is largely due to the fact that nuclear sensors are expensive and tend to be influenced by changes in seam type and pyrite content. Recently, researchers at VPI&SU have developed an optical sensor for phosphate analysis. The sensor uses image processing technology to analyze video images of phosphate ore. It is currently being used by PCS Phosphate for off-line analysis of dry flotation concentrate. The primary advantages of optical sensors over nuclear sensors are that hey are significantly cheaper, are not subject to measurement variations due to changes in high atomic number materials, are inherently safer and require no special radiation permitting. The purpose of this work is to apply the knowledge gained in the development of an optical phosphate analyzer to the development of an on-line ash analyzer for fine coal slurries. During the past quarter, the current prototype of the on-line optical ash analyzer was subjected to extensive testing at the Middlefork coal preparation plant. Initial work focused on obtaining correlations between ash content and mean gray level, while developmental work on the more comprehensive neural network calibration approach continued. Test work to date shows a promising trend in the correlation between ash content and mean gray level. Unfortunately, data scatter remains significant. Recent tests seem to eliminate variations in percent solids, particle size distribution, measurement angle and light setting as causes for the data scatter; however, equipment warm-up time and number of images taken per measurement appear to have a significant impact on the gray-level values obtained. 8 figs., 8 tabs.
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