A Novel Variable Scale Grid Model for Temperature Self‐Adaptive Control: An Application on Plate Cooling Process after Rolling. Issue 9 (28th January 2016)

• Record Type: Journal Article
• Authors: Zhang, Tian; Xie, Qian; Wang, Bingxing; Wu, Zhiqiang; Wang, Zhaodong; Wang, Guodong
• Is Part Of: Steel research international. Volume 87:Issue 9(2016)
• Page Start: 1213
• Page End: 1219
• Publication Date: 2016-01-28
• Subjects: distance‐weighted method -- plate cooling -- self‐adaptive learning -- temperature control model -- variable scale grid; Steel -- Periodicals; Steel -- Metallurgy -- Periodicals; 669.142
• DOI: 10.1002/srin.201500344
• Languages: English
• ISSNs: 1611-3683

Abstract

Abstract : Plate cooling is a complex process so that it cannot be described by a fixed model. So, the mathematical model requires self‐adaptive ability to comply with the various parameters such as gauges and temperatures of plates. Considering the effect of influence factors on cooling process, an online variable scale grid (VSG) model for cooling is developed. VSG model builds a multi‐dimension space system where each dimension is determined by the effect of each factor on heat transfer. Every plate can find a corresponding point in the space, according to its own process conditions. To guarantee the higher precision of temperature control, it adopts dimensionless treatment for all the factors to avoid the errors caused by different physical units. In order to reduce the computational cost, the technologies of finite element meshing and centroid calculation have been applied. When a new plate comes, the correlations between the new one and historical samples, centroids are described by Euclidean distance. Finally, the target value is estimated through the distance‐weighted average method. The results of experiments and applications with real industrial data show that the proposed VSG is effective in the plate cooling control and has a wide application prospect. Abstract : An online variable scale grid (VSG) self‐adaptive model for cooling temperature control is developed based on distance‐weighted method. It can obviously improve the precision of temperature results by considering the effect of influence factors on heat transfer process and increase the calculated efficiency by using meshing and clustering.