Title :
Neural computation in steel industry
Author :
Schlang, Martin ; Feldkeller, Bjorn ; Lang, Bernhard ; Poppe, Thomas ; Runkler, Thomas
Author_Institution :
Corp. Technol. Dept., Siemens AG, München, Germany
fDate :
Aug. 31 1999-Sept. 3 1999
Abstract :
A rolling mill process control system calculates the setup for the mill´s actuators based on models of the technological process. Neural networks are applied as components of hybrid neuro/analytical process models. They are the key to fit the general physical models to the needs of the automation of a specific mill. Present applications include the calculation of the rolling force and strip temperature (hot and cold rolling); prediction of width-spread in the finishing mill; control of strip width shape; and control of the coiling temperature in a cooling train (hot rolling). The authors outline how significant benefits are achieved in rolling mill technology by using neural networks. The work presented here is the result of a close cooperation between Siemens Corporate Technology in Munich and the Industrial Projects and Technical Services Group in Erlangen.
Keywords :
cold rolling; cooling; hot rolling; neurocontrollers; process control; rolling mills; shape control; steel industry; strips; temperature control; Erlangen; Industrial Projects and Technical Services Group; Munich; Siemens Corporate Technology; coiling temperature control; cold rolling; cooling train; finishing mill; general physical models; hot rolling; hybrid neuro-analytical process model; mill actuators; neural computation; neural networks; rolling force; rolling mill process control system; steel industry; strip temperature; strip width shape control; technological process; width-spread prediction; Adaptation models; Analytical models; Cooling; Mathematical model; Neural networks; Strips; Temperature measurement; Industrial application; Neural Networks; Online adaptation; Rolling mills; Steel processing;
Conference_Titel :
Control Conference (ECC), 1999 European
Conference_Location :
Karlsruhe
Print_ISBN :
978-3-9524173-5-5