Neural network particle sizing in slurries by reflectance spectroscopy

Mingzhong Li, Derek Wilkinson, Markus Schrödl

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Measuring concentration and size of solids in suspension is important in many industries. Even though techniques based on optical transmission measurements have been well developed, they are not always successful in practical applications because low concentration suspensions are needed. A method developed determines particle-size distribution and concentration from reflection measurements in concentrated suspensions using neural networks with particle concentrations up to 10% volume fraction. Based on measured optical reflectance spectra of suspensions with known particle-size distributions and concentrations, a neural network was trained to identify particle-size distribution and volume fraction of suspensions. Training is a time-consuming process requiring presentation of many spectra and their corresponding particle-size distributions and volume fractions to the neural network, but once concluded satisfactorily, the neural network can be used to predict the particle-size distribution and volume fraction of high concentration suspensions rapidly in-situ.

Original languageEnglish
Pages (from-to)2492-2498
Number of pages7
JournalAIChE Journal
Volume48
Issue number11
DOIs
Publication statusPublished - Nov 2002

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