Developing Chip Size Distribution Conversion Factors for Drum and Stacked Tray Chip Classifiers, 1998 Pulping Conference Proceedings
There are many classifiers used to determine the size distribution of chip samples. Each machine will produce different size distributions for the same sample of chips. Chips were segregated into size classes using two different types of chip classifiers, a drum classifier and a stacked tray classifier. Stepwise regression was used to develop equations to predict the percentages of fines, pins, accepts, and overs for one classifier based on the chip size distributions from another type of classifier. The adjusted R 2 values obtained for the drum classifier prediction equations were 92.0% for fines, 71.5% for pins, 51.2% for accepts, and 95.9% for overs. The adjusted R 2 values obtained for the stacked tray classifier prediction equations were 92.4% for fines, 83.2% for pins, 92.6% for accepts, and 95.4% for overs.
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