A neural network-based shape control system for cold rolling operations
Publication in refereed journal


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摘要In cold steel rolling, strip shape is crucial to product quality. For modern rolling mills, there are a number of different ways to control the strip shape, including adjusting the side depression, bending the work rolls and axial shifting the middle roll. However, these controls are not independent and hence, must be used with great care. This paper introduces a new method for strip shape control. It takes two steps: the first step is to use an Artificial Neural Network (ANN) to recognize the strip shape pattern. The second step is to apply one or a combination of several controls accordingly. This process may take several iterative steps. The new method is validated on an 8000 KN HC mill. The results demonstrated the new method could reduce the strip Shape error step by step. (C) 2007 Elsevier B.V. All rights reserved.
著者Peng Y, Liu HM, Duc R
期刊名稱Journal of Materials Processing Technology
出版年份2008
月份6
日期20
卷號202
期次1-3
出版社ELSEVIER SCIENCE SA
頁次54 - 60
國際標準期刊號0924-0136
語言英式英語
關鍵詞cold rolling; neural network; pattern recognition; shape control; tension stress
Web of Science 學科類別Engineering; Engineering, Industrial; ENGINEERING, INDUSTRIAL; Engineering, Manufacturing; ENGINEERING, MANUFACTURING; Materials Science; Materials Science, Multidisciplinary; MATERIALS SCIENCE, MULTIDISCIPLINARY

上次更新時間 2021-27-02 於 23:31