摘要
板形是带钢产品的主要质量指标之一,也是目前最受用户关注的质量指标。因此,板形控制的研究不仅具有重要的理论意义,而且具有很大的实用价值。本文介绍了目前常用的板形控制手段,重点介绍了CVC技术及其板形控制原理,并对CVC轧辊的辊形曲线进行了数学解析,分析得到了轧辊的轴向移动量与轧辊凸度的关系。
目前国内钢铁企业板形控制水平无法给出一个衡量标准,板形的质量标准执行困难,本文提出了一种利用现有轧机控制系统实测的大量板形质量信息执行板形标准的思路,并在此基础上开发了带钢板形质量统计分析软件,该软件已经成功地用于涟钢热轧CSP带钢板形质量评价。
轧辊磨损是板形控制模型中不可忽视的重要部分,但作为板形控制模型一部分的轧辊磨损预报模型,至今尚无精确的理论模型可利用,轧辊磨损的计算基本都采用各种经验公式。这些公式的建立,缺乏理论依据,各自存在着不同的缺点和不足,直接影响了轧辊磨损的预报精度,进而影响板形的控制。本文在大量工作辊实测辊形数据的基础上建立了一个CVC工作辊磨损量的计算模型,模型计算结果和实测结果吻合很好。
The Profile of the hot rolling strip is one of the major quality parameters, and it is also the most concerned quality index. So the research of shape control is important from the view of both theory and production. This paper introduced the major strategy of shape control ,especially the CVC technology and its principle of shape control. The analysis of CVC work roll principle has been conducted and the mathematical model describing the relationship between shift position and roll crown has been obtained in the thesis.
At present, a standard to evaluate the level of shape control has not been given in iron and steel companies. So it is hard to evaluate the control level of shape control in production. A method of executing strip shape standard by using measured strip shape quality data has been given in the paper to solve the difficulty of executing strip shape standard in iron and steel plants. On the basis of above idea, the software for appraising the strip shape in practice has been developed and applied in the CSP hot strip plant, Lianyuan Iron and steel company.
The wear model for work rolls is the important part in shape control models. But so far there have had no accurate theory models to utilize in shape control. Various experience formulae to calculate the work roll wear are used in production. These experience formulae have their special deficiencies, which influence the prediction precision of work roll wear and control effectiveness of shape control. A theoretical calculating model of work roll wear for CVC rolls has been obtained on the basis of a lot of measured data in production plant. The calculating results are in good agreement with experiment data.
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