Irregular Shape Particle Size Analysis Using Neural Network Approach
Granular materials of irregular shape occur in great variety in nature and in different branches of industry. Chemical engineering processes as catalysis, adsorption, heat exchange and many others using the granular materials are of great practical value. Also many commercial products are of granular type and that is why the characteristics of the granular material is so important. In the paper an optical method, combined with neural network approach, developed for irregular shape particle size analyzing has been presented. The method relies on determination of a relative volume and relative surface of sample particles using grid and random secant methods, respectively. Some experimental data obtained for ammonia synthesis catalyst has also been compared with sieve analysis method results.
KeywordsGranular Material Optical Method Neural Network Approach Relative Surface Image Analysis Technique
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