Parameters Optimization for Catalyst Centrifugal Spray Drying Process Based on BP Neural Network and Genetic Algorithm

Abstract

Reasonable and effective process parameters in the catalyst centrifugal spray drying are of significance for the quality and industrial production of the catalyst. The overall desirability of fine powder ratio and water evaporation is defined as the goal and the process parameters are optimized based on BP neural network with genetic algorithm, which obtains the better drying performance. The optimization results provide a basis for setting the process parameters of the industrial production of catalyst centrifugal spray drying and improve the quality of the catalyst product.