Application of Artificial Neural Network Techniques for Measuring Grain Sizes during Sugar Crystallisation
نویسندگان
چکیده
This paper discusses the development of a system for the automated real-time measurement of crystal size distributions during crystallisation. An optimised selection of the Daubechies wavelet coefficients is used as input to a Multi–Layer Perceptron artificial neural network to characterise the crystal scale lengths. This technique gives significant advantages over the sampling-based measurements, which require an individual measurement of single crystals. Test results obtained using simulated crystals, and actual images from a crystallisation pan and a laboratory crystaloscope are presented.
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