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| Self-learning model of temperature control for plate cooling after rolling based on[k-NN]method |
| ZHENG Fang-yuan |
| Plate Factory， Fujian Sanming Iron and Steel Group Co.， Ltd.，Sanming 365000，Fujian， China |
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Abstract Temperature control of cooling after rolling is a key technology for determining products’ properties during hot plate rolling. Furthermore， the coefficient of heat transfer is a core parameter in temperature control process. It cannot be determined by a fixed mode because there are many complex influence factors. A simple and valid self-learning model is proposed to determine the coefficient of heat transfer. Firstly， characteristic value of influence factors in each range of the coefficient of heat transfer is obtained by using node interpolation. Secondly， the correlationship between target and each cooled plate is found by[k-NN]method. Finally， the coefficient of heat transfer of target plate is estimated through IDW weight average algorithm. The results of applications with real industrial data show the proposed model can increase temperature control precision by about 5% compared with the past.
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Received: 29 December 2015
Published: 11 July 2016
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2016, Vol. 51 
