Investigation of thermomechanical behavior of a work roll and of roll life in hot strip rolling

An integrated finite element-based model is presented for the prediction of the steady-state thermomechanical behavior of the roll-strip system and of roll life in hot strip rolling. The model is comprised of basic finite-element models, which are incorporated into an iterative-solution procedure to deal with the interdependence between the thermomechanical behavior of the strip and that of the work roll, which arises from roll-strip contact, as well as with the interdependence between the thermal and mechanical behavior. Comparison is made between the predictions and the measurements to assess solution accuracy. Then, the effect of various process parameters on the detailed aspects of thermomechanical behavior of the work roll and on roll life is investigated via a series of process simulations.     

Precision online model for prediction of strip temperature in hot strip rolling

Abstract

Investigated via a series of finite element (FE) process simulation is the effect of diverse process variables on some selected non-dimensional parameters characterising the thermomechanical behaviour of the roll and strip in hot strip rolling. Then, on the basis of these parameters, online models are derived for precise prediction of the temperature changes occurring in the bite zone as well as in the interstand zone in a finishing mill. The prediction accuracy of the proposed models is examined through comparison with predictions from a FE process model.     

Prediction of roll force in skin pass rolling using numerical and artificial neural network methods

A combination of finite element method and neural network methods was used for rapid prediction of the roll force during skin pass rolling of 980DP and 1180CP high strength steels. The FE based commercial package DEFOEM-2D was used to develop a mathematical model of the skin pass rolling operation. Numerical experiments were designed with different process parameters to produce training data for a neural network algorithm. The friction coefficient was considered as an input parameter in the neural network but it was optimised using an iterative method employing an equation that relates the friction coefficient to the rolling force. The load prediction method described in this paper is sufficiently rapid that it can be used in real-time as an adjustment tool for skin pass rolling mills with error within 10% (based on plant data from POSCO).     

基于深度学习的热连轧轧制力预测

摘要：轧制力预报一直是热连轧过程控制模型的核心，浅层神经网络对复杂函数的表示能力有限，而深度学习模型通过学习一种深层非线性网络结构，实现复杂函数逼近。利用深度学习框架TensorFlow，构建了一种深度前馈神经网络轧制力模型，采用BP算法计算网络损失函数的梯度，运用融入Mini batch策略的Adam优化算法进行参数寻优，采用Early stopping、参数惩罚和Dropout正则化策略提高模型的泛化能力。基于上述建模策略，针对宝钢1880热连轧精轧机组的大量轧制历史数据进行了建模实验，对比分析了4种不同结构的前馈网络预测精度。结果表明，相比于传统SIMS轧制力模型，深度神经网络可实现轧制力的高精度预测，针对所有机架的预测精度平均提升21.11%。     

CVC工作辊非对称磨损分析与预报模型建立

 CVC辊形以其较强的凸度控制能力在热连轧中有着广泛的应用,但是CVC辊形不具有均匀磨损的能力,其磨损往往比较严重,且呈现出非对称性。针对该特点提出CVC工作辊非对称磨损的表征方法,利用该方法对某1 800 mm CSP生产线下游机架CVC工作辊非对称磨损情况进行分析。统计结果表明,下游机架工作辊磨损多为非对称形式,并与CVC辊形呈现出一定的对应性。在此基础上,提出辊径对整体磨损影响系数及辊径对轧制力影响系数2个新的磨损模型参数,并建立针对CVC轧辊的非对称磨损预报模型,利用遗传算法对模型参数进行优化,并利用实测数据进行验证,改进后磨损模型精度比常规磨损模型精度平均提高了约35%。     

基于Copula函数的热轧支持辊健康状态预测模型

热轧支持辊的健康状态在带钢板形质量和轧制稳定性控制中起着关键作用,非线性、强耦合、少样本等特点使得热轧支持辊健康状态的预测复杂,目前各大钢厂仍以定期维护和事后维修为主。本文提出了一种支持辊虚拟健康指数的构建方法以及基于Copula函数的复杂工况健康状态预测模型。首先结合支持辊弯窜辊数据表征支持辊健康状态,再使用K-means聚类方法对支持辊工况进行划分,将各工况下过程数据分别构建Copula预测模型,最后根据实际轧制计划的排布顺序融合各工况模型的预测结果。提出的基于Copula函数的预测模型在某钢厂1780热连轧产线得到应用,结果表明,该模型能够准确有效的按照轧制计划实现支持辊的健康状态预测,以更科学的策略指导支持辊更换维护。      

合金钢棒材轧制的平均轧辊半径计算模型

 在合金钢棒材生产中,轧制过程中椭圆与圆孔型对棒材成品的尺寸精度及质量缺陷起决定性作用,在计算轧制工艺规程时一般用平均轧辊半径等效代替轧槽轮廓变化的轧辊半径,因此,平均轧辊半径计算模型的可靠程度对轧制工艺(轧制速度、压下量、轧制力等)的合理选取和产品几何尺寸精度的提升具有重要作用。在现有平均轧辊半径模型基础上,考虑不同合金钢种宽展影响,利用孔型轧制表面轮廓预测模型推导得出变形轧件断面形状与轧制临界点的求解公式,提出了用出口轧件断面面积与临界平均宽度来计算等效矩形平均高度的方法,得到了椭圆与圆孔型平均轧辊半径的新计算模型,并进行了轧制试验验证。试验结果表明,与现有模型相比,新计算模型在一定程度上提高了平均轧辊半径的计算精度。同时,基于合金成分影响系数探究了不同合金钢种轧制变形后的临界点分布对应关系。考虑到孔型侧壁直线的存在,对圆孔型轧制接触状态进行了阶段划分,当合金成分系数较小(碳结钢与珠光体-马氏体钢)时,轧制临界点落于圆弧轧槽上,所有计算模型均有效;当合金成分系数超过1.33(奥氏体钢与铁素体钢)时,轧制临界点扩展至侧壁直线上,原有计算模型失效,轧制工艺参数由新计算模型求解。基于新模型的合金钢种轧制临界分布对棒材轧制钢种变换工艺参数的快速制定具有重要指导意义。     

考虑辊缝变化的板带热轧动态理论模型

精准的轧制模型是生产优质带材的关键,目前常用的热轧模型仅适用于研究静态轧制过程.当面对变厚度轧制及轧机振动等动态轧制过程时,由于常用的静态模型不包含辊缝变化速度参数,因此其模型结构缺乏完整性.为了对动态轧制进行全面深入的研究,需要建立一个包含辊缝变化速度参数的动态轧制模型.基于Orowan方程,同时考虑辊缝变化速度对带...     

热轧带钢平整机工作辊磨损规律

 由于工艺和结构的特殊性,带钢热轧平整机的工作辊磨损演变规律与热连轧过程有显著差别。然而,目前对工作辊磨损的研究主要集中在热轧,对热轧平整机磨损演变规律的研究较少。为此,从热轧平整机工作辊的磨损特点出发,结合现场大量实测磨损数据,分析磨损的形成与发展机理。通过ABAQUS有限元仿真分析软件建立单机架四辊热轧平整机的辊系-轧件耦合计算模型,揭示不同磨损阶段工作辊接触应力对磨损演变的作用规律。通过与某厂1 580 mm热轧平整机的实际数据对比,结果表明,工作辊磨损演变规律能够准确地反映实际生产过程的磨损情况,为热轧平整机轧辊磨损理论的发展与磨损预报模型的进一步优化奠定了基础。     

热镀锌机组沉没辊系受力模型及影响因素

 热镀锌机组沉没辊系在锌锅内工作状态下受力情况复杂,受外界影响较大。充分考虑热镀锌机组设备与其工艺特点,首先分析沉没辊系在工作状态下受力情况,分别建立矫正辊插入量与包角的关系式、基于辊面锌渣沉积厚度的辊面摩擦因数经验模型。随后采用条元离散法建立沉没辊系辊面接触压力、摩擦驱动力矩模型,基于简支梁模型确定沉没辊系轴端支撑力、轴端摩擦阻力矩模型。最后将沉没辊系受力模型应用于国内某热镀锌机组镀锌工艺段,以典型规格带钢确定沉没辊系受力影响因素,并依据机组实际工况及板形要求来确定生产工艺参数的5种不同水平,来分析其对辊系受力状态的影响规律,为沉没辊系工艺优化提供指导依据。结果表明,4种工艺参数对辊系接触压力及摩擦力矩影响都存在差异性,矫正辊插入量与辊面接触压力呈现非线性关系;带钢张力对各辊接触压力影响程度不同,其中沉没辊受到的影响最大,而其余两辊受到张力几乎不影响;辊面平均摩擦因数、带钢速度对辊的接触压力几乎不影响;辊系摩擦驱动力矩、轴端摩擦阻力矩随着矫正辊插入量及辊面平均摩擦因数增大都呈现出不同程度增大。带钢张力与沉没辊摩擦驱动力矩、轴端摩擦阻力矩呈线性变化关系,而带钢张力对其余两辊影响很小。带钢速度对辊系的摩擦驱动力矩、轴端摩擦阻力矩影响很小。     

优化UF轧机重轨辊环参数及提高轧辊利用率

针对万能轧机UF精轧机重轨轧辊辊环利用率低的情况,对轧机轧制工艺参数进行可行性分析,通过采取增大轧辊辊环直径的措施,提高了轧辊辊环的利用率。     

辊式矫直机矫直过程有限元仿真

建立了辊式矫直机的有限元模型,对其矫直过程进行动态有限元仿真。对不同规格的钢板分别进行仿真,将模型中的压下量按实际参数设定,并将其计算结果与实际情况进行比对,检验了模型的可靠性。对其残余应力分布进行分析,得出消除板坯翘曲必须控制长度方向上节点之间的纵向残余应力差值的结论。建立的辊式矫直机的参数化模型,能够方便地调整矫直工艺参数,并对其矫直效果进行分析,对辊式矫直机工艺参数的设定具有一定的指导意义。     

Optimisation of pinch roll load in thin slab continuous casting

Abstract

An analytical model has been developed to investigate the optimum pinch roll load and resulting slab thickness reduction during the continuous casting of a steel, constant thickness, thin slab in a vertical type machine. The pinch roll unit consists of two driven pinch roll sets, which support the solidified hot slab weight and take up the reaction forces owing to slab bending. Optimum conditions prevail when the pinch roll load required to support the slab weight is equally shared by the two pinch roll sets and has the minimum value allowing proper control of the slab speed. The model has been validated by being applied to an existing industrial case of thin slab continuous casting of plain low carbon steel. The effects of pinch roll radius, slab thickness, casting speed, slab temperature and the material carbon percentage on minimum pinch roll load and slab thickness reduction ratio have been investigated. Expressions have been obtained for the optimum pinch roll load and slab thickness reduction ratio related to the prevailing process parameters, which the plant operator can directly apply to determine the optimum pressure setting for the hydraulic cylinders fitted to the movable roll ends. The bending roll load is shown to be small compared with the pinch roll load.     

基于有限元与神经网络的板形调控功效

 针对冷连轧机组中的6辊CVC轧机,利用大型非线性有限元软件MSC.Marc建立仿真模型,对多种轧制条件下轧件的弹塑性变形和辊系的弹性变形进行了耦合计算,得到了6辊CVC冷轧机工作辊弯辊、中间辊弯辊、中间辊横移的板形调控功效离散值。研究了不同轧制工艺参数、轧件参数和轧辊参数对各板形调节机构调控功效的影响规律,并得出相应的板形调控功效系数。以有限元计算结果为样本,利用BP神经网络强大的非线性映射功能,建立了板形调控功效的神经网络计算模型,为板形在线闭环控制模型提供高精度的板形调控功效,解决了有限元计算耗时长,难以满足在线控制要求的问题。     

辊子错位对铸坯鼓肚变形的影响

 由于加工、安装、变形与磨损等原因,连铸机辊列中的辊子会偏离设计位置而产生错位,这对铸坯鼓肚变形产生较大影响。基于高温铸坯黏弹塑性本构方程,建立两辊间距内的铸坯坯壳动态鼓肚数学模型,并利用模型计算试验铸机的铸坯坯壳鼓肚曲线,依照实测数据验证了模型的有效性。根据奥钢联工业连铸机的设备及工艺参数,计算铸机不同扇形段内铸坯坯壳在不同辊子错位量情况下的鼓肚变形,并讨论在辊子发生错位的情况下辊间距对铸坯坯壳固液交界面处最大应变的影响,并给出铸机辊间距的确定方法。     

轧辊磨损过程中的形貌图像特征及分形

 轧辊表面形貌直接影响板带钢产品的表面质量甚至其织构组成。为了定量研究轧辊磨损过程中其表面形貌特征的变化规律,采集了1个磨辊周期内不同轧制阶段的轧辊表面图像信息,基于MATLAB平台,利用图像处理方法对不同阶段的下机轧辊表面图像进行了预处理,提取样本图像的几何形状及纹理特征等17维图像特征参数和分形维数,经过对这些参数的属性约简建立了用于轧辊磨损形貌状态识别的BP神经网络模型。结果表明：等效面积圆半径﹑圆形度﹑纹理熵及二阶矩等轧辊形貌图像特征参数和分形维数可以作为描述轧辊表面形貌的定量指标,并可用BP网络模型对轧辊磨损形貌进行识别预测。为建立轧辊磨损形貌的定量评价体系提供了新途径。     

辊式矫直过程弯辊量对边浪影响的仿真分析

针对辊式矫直过程建立具有边浪特征的带钢有限元仿真模型,通过对比现场工况实测矫直力与有限元模型计算所得的矫直力,得到二者误差在10%以内,验证了有限元模型的精度。分别采用原始曲率补偿法和塑性变形层增加法确定了4种弯辊量设定方案。采用上述方案对浪高为20 mm的带钢进行矫直,对比矫直后带钢平直度情况,得出按最高浪采用原始曲率补偿法计算得到的弯辊量矫直效果最优。同时随着弯辊量的加大,矫直力也随之增加,为现场边浪矫直过程提供了依据。     

基于CF-PSO-SVM的冷连轧非稳态工作辊弯辊模型优化

 板形质量是冷轧带钢重要的技术质量指标,同时工作辊弯辊是改善冷轧带钢板形质量的最有效的控制手段之一。冷连轧机组在高速稳定的轧制过程中板形控制精度能够达到较高的水平,但在升降速非稳态的轧制过程中板形控制效果非常不理想,这也成为制约冷轧带钢产品质量的不利因素。为了提高冷连轧机在升降速非稳态轧制过程中带钢板形的控制精度,在深入研究了冷连轧弯辊力设定原理的基础上,利用智能算法和包括出入口带钢厚度、机架间口张力、轧制速度、中间辊窜辊、带钢宽度、轧辊倾斜以及轧制力等现场实际轧制大数据样本,提出了一种基于粒子群算法优化支持向量机的工作辊弯辊力预测模型。同时阐明了粒子群优化算法和支持向量机的基本原理,引入压缩因子的概念,提升了粒子群算法参数寻优的效率,选取冷连轧机组五机架为研究对象,利用拉依达准则对轧制数据样本进行处理,通过平均绝对误差、均方差误差和平均绝对误差百分比等评价指标对比预测模型的性能。结果表明,改进的预测模型具有良好的模型预测性能和泛化能力,同时根据实际生产数据样本,回归出基于轧制速度和辊间弹性系数的弯辊力缝补偿模型,并验证了模型的有效性,模型的投入降低了板形控制系统的负荷,改善了非稳态轧制过程中的板形控制精度,产品头尾部的质量合格率提高了5.1%。     

New approach for prediction of roll force in rod rolling

Abstract

An approximate model is presented in which the equation for computing roll force in an oval-round (or round-oval) pass rolling sequence has been formulated with a new approach. The fundamental idea considered is to introduce the concept of a weak plane strain condition which gives a two-dimensional approximation of the three-dimensional deformation problem in rod or bar rolling. The generality and robustness of the model have been examined by conducting a two-pass low speed bar rolling experiment and a four-pass continuous high speed rod rolling test with various rolling temperatures, roll gaps (pass height), rolling speeds, and steel grades. The predicted roll forces were in good agreement with those experimentally measured, although the prediction was less good when the roll gap (pass height) varied. The proposed model was very fruitful in solving the three-dimensional deformation problem in rod or bar rolling.     

Optimising tension levelling process by means of genetic algorithms and finite element method

Abstract

This paper presents a method based on genetic algorithms and the finite element method which is useful for automatically adjusting the parameters of a tension levelling process. First, the optimum parameters of the steel to be used in the simulation programme are sought. The process consists of simulating controlled cyclical deformation tests on finite element (FE) models of standard steel test pieces with different laws of cyclical behaviour. Genetic algorithms are used to optimise the parameters of the simulation model so that the behaviour of the material is as close as possible to the results obtained in real experimental tests. This ensures that the behaviour of the material in the FE model is as realistic as possible. The model of behaviour of the material selected is used to design and check out a second tension levelling FE model. Based on this second model, the roll penetration, the lengthwise tension and the strip feedrate are adjusted. There is also optimisation with genetic algorithms so that the final residual tensions in the product are below a specified threshold and as even as possible. For a solution to be considered as valid, it must be confirmed that the steel plate is subject to the tensions envisaged at various process control points. From the best solutions found, the one with the fastest feedrate is selected so as to maximise output.