Title :
Optimization and simulation of quality properties in paper machine with neural networks
Author :
Lampinen, Jouko ; Taipale, Ossi
Author_Institution :
Dept. of Inf. Technol., Lappeenranta Univ. of Technol., Finland
fDate :
27 Jun- 2 Jul 1994
Abstract :
The final quality of paper depends on many quality and process variables. It is very difficult to find theoretical rules of the behavior of paper properties when variables depend from each other and when the interdependencies are not linear. In this paper we present a neural network based system for estimating the final quality of paper from process measurements. Inverse computation of the network model is used to find a control action that will produce the desired quality. A separate self-organizing map is used to monitor the movement of the operating point of the process and to give a hint of the estimation error of the network
Keywords :
optimisation; paper industry; process control; quality control; self-organising feature maps; estimation error; inverse computation; neural network based system; nonlinear interdependencies; optimization; paper machine; process measurements; quality properties; self-organizing map; simulation; Computer networks; Control systems; Estimation error; Feedforward systems; Intelligent networks; Monitoring; Neural networks; Numerical models; Paper making machines; Proposals;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374818
