학술논문
Using RBF neural networks and a fuzzy logic controller to stabilize wood pulp freeness
Document Type
Conference
Author
Source
IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339) Neural networks Neural Networks, 1999. IJCNN '99. International Joint Conference on. 6:4247-4252 vol.6 1999
Subject
Language
ISSN
1098-7576
Abstract
The quality of paper produced in a papermaking process is largely dependent on the properties of the wood pulp used. One important property is pulp freeness. Ideally, a constant, predetermined level of freeness is desired to achieve the highest quality of paper possible. The focus of this paper is on developing a system to control the wood pulp freeness. A radial basis function (RBF) artificial neural network was used to model the freeness and a fuzzy logic controller was used to control the input parameters to maintain a desired level of freeness. Ideally, the controller will reduce pulp freeness fluctuations in order to improve overall paper sheet quality and production.