【作者】 李杰；

【导师】 何纯玉；

【作者基本信息】 东北大学 ， 材料工程（专业学位）， 2019， 硕士

【摘要】 新国标的实施对热轧带肋钢筋的性能以及金相组织提出了新的要求,为钢铁行业带来了新的机遇和挑战。如何生产出具有满足断面组织和综合性能要求的热轧带肋钢筋,又能在更大程度上降低生产成本,成为钢铁企业和科研人员亟待解决的一个重要问题。本文通过对热轧带肋钢筋冷却过程温度模型的研究,根据生产特点实现了对冷却过程钢筋温度的精准控制,研究结果为在适度减少合金添加的条件下得到合格的组织和性能提供了足够的工艺优化支撑。本文主要的研究内容如下:(1)以传热学基本理论为基础,采用有限差分方法建立热轧带肋钢筋冷却过程温度预测数学模型。将问题模型简化为一维模型,利用有限差分法推导显式形式和隐式形式的差分计算公式,计算不同冷却条件下的钢筋温度分布。(2)通过实际生产过程温度变化数据,建立热轧带肋钢筋冷却过程换热系数的学习方法。基于BP神经网络架构,确定学习算法、隐含层数、输入输出参数,以压力、流量、水温、规格等工业生产数据作为输入,以换热系数作为输出对神经网络进行训练,实现对换热系数的自适应学习。(3)针对生产数据量庞大、采集数据易于受到干扰的特点,研究数据预处理算法。比较数据聚类算法的特点,对生产数据进行测试,实现对数据的清洗和筛选,剔除异常数据,获得可靠的训练样本,为BP神经网络提供准确的训练数据,提高温度模型的预测精度。(4)结合实际生产现场的设备布置与工艺规程,开发温度在线应用模型,实现对不同约束条件下的热轧带肋钢筋温度场的计算与设备状态设定,并通过仪表测量值验证所开发温度场模型的预测精度,为热轧带肋钢筋轧后的适度冷却工艺提供数据支撑,以满足新的国家标准对产品组织性能的要求。本课题通过对热轧带肋钢筋冷却过程温度实现精准的预测,在给出热轧带肋钢筋表面与心部温度偏差限制的条件下,实现了对冷却器的流量设定计算。采用该方法保证了钢筋断面的组织和冷后的性能,对于热轧带肋钢筋合金添加的减量化控制和性能的均一性控制具有重要的理论和实际意义。更多还原

【Abstract】 The implementation of the new national standard puts forward new requirements for the performance and metallographic structure of hot-rolled ribbed bar,which brings new opportunities and challenges to the iron and steel industry.It is an urgent issue to be solved for steel enterprises and researchers to find methods of producing hot-rolled ribbed steel bars which meet the requirements of section structure and comprehensive properties,and reducing the production cost to a greater extent.In this paper,the temperature model of hot-rolled ribbed steel bar during cooling process is studied,and the temperature of steel bar during cooling process is controlled precisely according to the characteristics of production.The research results provide sufficient technological optimization support for obtaining qualified microstructure and properties under the condition of moderate reduction of alloy addition.The main contents of this paper are as follows:(1)Based on the basic theory of heat transfer,a mathematical model for temperature prediction of hot-rolled ribbed bar during cooling process is established by using finite difference method.The problem model is simplified to a one-dimensional model,and the explicit and implicit difference formulas are derived by using the finite difference method to calculate the temperature distribution of steel bar under different cooling conditions.(2)The learning method of heat transfer coefficient of hot-rolled ribbed bar during cooling process is established by the data of temperature change in actual production process.Based on the BP neural network architecture,the learning algorithm,the number of hidden layers,input and output parameters are determined.The industrial production data such as pressure,flow rate,water temperature and specifications are used as inputs,and the heat transfer coefficients are used as outputs to train the neural network,so as to realize the adaptive learning of heat transfer coefficients.(3)Aiming at the large amount of production data and the easy interference of the collected data,the data preprocessing algorithm is studied.By comparing the characteristics of data clustering algorithm,the production data are tested,the data are cleaned and screened,the abnormal data are eliminated,the reliable training samples are obtained,the accurate training data are provided for BP neural network,and the prediction accuracy of temperature model is improved.(4)Combined with the equipment arrangement and process regulation in the actual production site,developing an on-line application model for temperature.The temperature field of hot-rolled ribbed bars under different constraint conditions is calculated and the equipment state is set,and the prediction accuracy of the developed temperature field model is verified by instrument measurements,which provides data support for the moderate cooling process of hot rolled ribbed bars after rolling,so as to meet the requirements of the new national standards for the organization and properties of products.In this paper,the temperature of hot-rolled ribbed bar during cooling process is accurately predicted,and the flow rate of the cooler is set and calculated under the condition that the temperature deviation between the surface and the center of the hot-rolled ribbed bar is limited.This method ensures the microstructure of steel bar section and the properties after cooling,which has important theoretical and practical significance for the reduction control of the alloy addition in hot-rolled ribbed steel bar and the homogeneity control of properties.更多还原