Vibration Diagnosis Systems for a Cold Rolling Mill Machine
Keywords:
Cold rolling mill, Strip, Vibration, Prediction, Undulation
Abstract
In this work is shown the importance to use a monitoring by vibration system for a cold rolling mill machine. The using of this monitoring vibration system reduce maintenance costs, minimize the impact on operation because is monitoring the rolls, the backup rolls, the coupling shaft, the gears from power system. Another advantage is to preventing damage occurring by detecting signs of abnormalities. The accurate prediction of works parameters is essential for a product quality. Currently, a mathematical model is used. It is important to directly predict the roll force and the other parameters, to compute a corrective coefficient Using a mathematical model, we grove up the possibility to obtain a new quality for laminates strip.
References
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[4]. Pohang Iron and Steel Company Tech.Rep., 2nd Cold Mill Contr. Equipment (PCM part), POSCO, 1989, Korea.
[5]. Lee W., , Improvement of set-up model for tandem cold rolling mill, Tech. Rep. POSCO, 1994, Res.Inst.Sci.Technol.
[6]. Pican N, Alexandre F. and Bresson P., Artificial neural networks for the presetting of a steel temper mill, IEEE Expert, 1996, vol. 11, no. 1. 22-27.
[7]. Portman N., Application of neural networks in rolling mill automation, Iron and Steel Eng., 1995, vol. 72, no. 2, p. 33-36.
[8]. Rosen B., Ensemble learning using decorrelated neural networks, Connections Sci. 1996, vol. 8, p. 373-384.
[2]. Bishop C., Neural Networks for Pattern Recognition. Oxford, 1995, U.K:Oxford Univ. Press.
[3]. Cohn D., Atlas L., Ladner R., Improving generalization with active learning, Machine Learning, 1994, vol. 15, no. 2, p. 201-221.
[4]. Pohang Iron and Steel Company Tech.Rep., 2nd Cold Mill Contr. Equipment (PCM part), POSCO, 1989, Korea.
[5]. Lee W., , Improvement of set-up model for tandem cold rolling mill, Tech. Rep. POSCO, 1994, Res.Inst.Sci.Technol.
[6]. Pican N, Alexandre F. and Bresson P., Artificial neural networks for the presetting of a steel temper mill, IEEE Expert, 1996, vol. 11, no. 1. 22-27.
[7]. Portman N., Application of neural networks in rolling mill automation, Iron and Steel Eng., 1995, vol. 72, no. 2, p. 33-36.
[8]. Rosen B., Ensemble learning using decorrelated neural networks, Connections Sci. 1996, vol. 8, p. 373-384.
Published
2007-05-15
How to Cite
1.
DRAGOMIR S, MĂCUŢĂ S, SPÂNU C. Vibration Diagnosis Systems for a Cold Rolling Mill Machine. The Annals of “Dunarea de Jos” University of Galati. Fascicle IX, Metallurgy and Materials Science [Internet]. 15May2007 [cited 19Apr.2024];30(1):109-13. Available from: https://www.gup.ugal.ro/ugaljournals/index.php/mms/article/view/3187
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