MODELING OF A WOODCHIP REFINER USING ARTIFICIAL NEURAL-NETWORK

Neural networks can be an attractive alternative to mathematical model ling of complex and poorly understood processes if input/output data c an easily be obtained. Woodchip refining falls into this category. The mechanism of the refining process is still being studied and no thoro ugh models have yet been developed. A feed-forward neural network is p roposed for modelling of woodchip refiners. The outputs predicted by t he neural network are compared with industrial refiner data. It is als o shown that a modified neural network structure can be used to optimi ze refiner operation and product quality. The advantages and disadvant ages of neural network model application in simulation and optimizatio n of industrial processes are discussed.