Neural network modelling and prediction in multipass steel processing
| Autor: | A W Fraser, A J Morris, E B Martin |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
0209 industrial biotechnology
Engineering drawing Engineering Artificial neural network business.industry Mechanical Engineering Relative motion Process (computing) Mechanical engineering Topology (electrical circuits) 02 engineering and technology Motor torque Industrial and Manufacturing Engineering 020303 mechanical engineering & transports 020901 industrial engineering & automation 0203 mechanical engineering Rolling mill business |
| Zdroj: | Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering. 218:121-132 |
| ISSN: | 2041-3009 0954-4089 |
| DOI: | 10.1243/0954408041323476 |
| Popis: | Operations comprising a sequence of single passes whereby relative motion occurs between a workpiece and a shaping tool on each pass is termed a multipass process. This paper describes the development of a neural network modelling approach for the representation of the complex dynamic interactions that are characteristic of multipass processes. The developments are then applied to a world-scale steel beam rolling mill for the prediction of motor torque and rolling force. Two neural network structures were designed to satisfy different operational requirements. The first was to provide online single pass ahead predictions, while the second was for off-line multipass ahead predictions. Although the results obtained using the ‘best’ single network model were promising, significant prediction improvements were achieved by combining (stacking) multiple neural networks that were trained using different network topologies. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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