Abstract
Close monitoring of particle size and shape is essential if today’s demanding material requirements for crushed rock aggregates are to be met.
An intelligent mechatronic inspection system is described here. On-line product sampling directs aggregate through an inspection chamber where a novel imaging system digitises the particle geometry. Data processing algorithms extract dimensional data and image features, allowing an artificial neural network classifier to assign qualitative shape descriptors to each particle, thus providing each sampled batch with a breakdown of constituent particle size and shape distributions.
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© 1995 Springer-Verlag/Wien
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Calkin, D.W., Parkin, R.M. (1995). Quarry Aggregates: A Flexible Inspection Method Utilising Artificial Neural Networks. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_54
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DOI: https://doi.org/10.1007/978-3-7091-7535-4_54
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82692-8
Online ISBN: 978-3-7091-7535-4
eBook Packages: Springer Book Archive