Automatic Classification of Graphite in Cast Iron

Abstract

A method for automatic classification of the shape of graphite particles in cast iron is proposed. In a typical supervised classification procedure, the standard charts from the ISO-945 standard are used as a training and validation population. Several shape and size parameters are described and used as discriminants. A new parameter, the average internal angle, is proposed and is shown to be relevant for accurate classification. The ideal parameter sets are determined, leading to validation success rates above 90%. The classifier is then applied to real cast iron samples and provides results that are consistent with visual examination. The method provides classification resultsper particle, different from the traditionalper fieldchart comparison methods. The full procedure can run automatically without user interference.