基于神经网络的热带层流基本热流密度的计算

利用现场的数据，采用BP神经元网络预报热连轧层流水冷区集管组内的基本热流密度，将预报的结果用于上、下集管组的热流密度的数学模型计算，进而优化层冷集管组的水冷温降计算数学模型的精度。将结果与采用多元回归方法所得到的结果作比较，表明采用BP神经元网络计算基本热流密度的精度要高于多元回归方法的计算精度，卷取温度的计算值与实测值的标准差比解析回归方法减少了近20％，说明该方法具有良好的在线应用前景。     

带钢热精轧机组机架间冷却控制数学模型

为了提高带钢终轧温度的控制精度，对精轧过程中导致带钢温度变化的热交换过程进行了分析，并以此作为建立机架间冷却控制的传热模型和自学习模型的理论依据。给出了热轧机组机架间在线冷却控制传热模型和自学习模型的算法。通过程序开发对精轧机组内带钢的温度分布进行了离线模拟，取得了较高的模拟精度。所用数学模型具有较好的在线应用前景。     

神经网络预报冷轧带钢表面粗糙度

分析了影响鞍钢冷轧厂冷轧带钢表面粗糙度的主要因素,采用BP神经网络算法建立了预报冷轧带钢表面粗糙度的数学模型,利用鞍钢冷轧厂数据对模型离线应用表明,该数学模型的计算误差率在0~±3%范围内的比例为100%。     

机架间冷却数学模型计算带钢温度分布

为提高带钢终轧温度的控制精度 ,对精轧过程中导致带钢温度变化的热交换过程进行了分析 ,以此作为机架间冷却控制的传热模型和自学习模型的理论依据 ,给出了带钢厂热轧机组机架间冷却在线控制的传热和自学习模型的算法 ,通过程序开发对精轧机组内带钢的温度分布进行了离线模拟 ,终轧温度计算值与实际生产数据符合较好 ,并对所用数学模型的实际计算结果进行了分析     

热轧带钢终轧温度控制数学模型

根据生产现场工艺和设备实际情况，确定了热轧带钢终轧温度的控制策略。基于带钢在机架间温度变化的精确预报模型，通过调节轧制速度或机架问冷却水流量，有效地将带钢温度控制到目标范围内。     

半无头轧制工艺下的精轧宽展预测

为了提高半无头轧制精轧宽展的预测精度，采用BP神经网络方法代替传统数学模型进行宽展预测，并采用改进的BP神经网络算法提高学习速度，与传统数学模型方法得到的预测精度作比较，结果表明采用此方法预测精度更优。     

热连轧精轧宽度自动控制

为了提高热连轧带钢成材率和宽度精度，国外一些钢厂开发了精轧宽度自动控制系统，在精轧机架间设置了测宽仪，利用机架间张力动态调整带钢宽度，实际应用表明，带钢宽度偏差有明显减少。     

基于复合神经网络的热轧变形抗力模型研究

为反映材料化学成分波动对变形抗力的影响效果,基于自适应线性神经网络和径向基神经网络技术,建立了以典型化学成分和机架入口温度作为输入,变形抗力修正系数作为输出的热轧带钢变形抗力修正网络.利用实际生产数据,对奥氏体变形抗力修正网络进行了训练、验证和测试,并与在线模型的自适应值、独立的BP网络和RBF网络的预报值进行了对比....     

CSP轧机压下补偿修正控制技术

CSP轧机是短流程工艺中最重要的设备,保证机架间金属秒流量相等是轧制过程稳定的重要前提.过程控制利用数学模型和动态测量数据相结合,在轧制过程中对压下补偿进行动态修正,以维持机架间的协调关系,提高带钢厚度精度,保证生产过程的稳定性.     

基于BP神经网络的热轧带钢卷取温度预报

 为了提高卷取温度的精度,采用BP神经网络方法并结合大量的现场数据,对热轧带钢层流冷却水冷数学模型中的综合换热系数因子进行预报,将预报结果应用于计算卷取温度的数学模型中,可将卷取温度的计算值控制在目标值的±15 ℃之间,大大提高了卷取温度的精度,具有在线应用的前景。     

一种热带精轧温度控制的简便计算方法

通过所建立的热带终轧过程计算的简化模型和确定的当量间距基本值,计算热带在精轧各机架间的温度。简便计算结果和理论模型计算结果的对比表明,简便计算方法能较精确地计算热带在精轧区的温度。当目标温度发生变化时,用简便计算法可以调整机架间喷嘴状态以适应新的目标值。     

热轧带钢氧化铁皮厚度演变的数值模拟

为了降低热轧结构钢510L氧化铁皮缺陷的发生率,对其热轧过程氧化铁皮厚度的演变进行了数值模拟,研究了精轧入口温度、精轧终轧速度、机架间冷却、层流冷却模式和成品厚度规格对氧化铁皮厚度演变的影响。模拟结果表明:在保证力学性能的热轧工艺条件下,采取较低精轧入口温度、提高终轧速度、投入机架间冷却水、使用前段冷却可有效地降低氧化铁皮的厚度。     

Computed Assisted Design of Models for the Thermomechanical Processing of Steels by means of a New Modelling Tool

A new modelling workbench has been developed for the computation of the microstructural evolution of steels in the course of their thermomechanical processing. Within this graphical user interface, the designer can easily construct a new model by interlinking different modules available in reference libraries, whatever their original informatic framework. This universal platform organises the data flow through the modules integrated in the logical chart. On the basis of a CRM internal library of modules written in FORTRAN, a data block diagram is proposed to compute the through‐thickness temperature profile of a steel hot band during its process in the finishing mill and the corresponding thickness evolution of the oxide scale according to different cooling schemes. For this simulation, a conditional loop is used for the data flow through an interstand cooling module, a module for the computation of the deformation and frictional heat released in the roll gap, and a module for the heat conduction within the roll bite. In a second simulation example, the impact of a heterogeneous temperature pattern at the start of coiling on the final mechanical properties is evaluated with the help of metallurgical models of precipitation of microalloying elements and phase softening for multiphase steels coupled to a thermal model of coil cooling.     

Finishing mill thread speed set-up and control by interval type 1 non-singleton type 2 fuzzy logic systems

Abstract

The set-up of the finishing mill (FM) thread speed to achieve the desired strip temperature as measured by the finish mill delivery temperature sensor is made by an intelligent controller based on interval type 2 fuzzy logic system. The controller calculates the FM thread speed required to achieve the strip FM exit target temperature, and the interstand strip surface temperature profiles. The interval type 2 fuzzy set-up controller uses as inputs the predicted transfer bar FM entry temperature, the transfer bar thickness, the target strip FM exit temperature, the target strip FM exit gauge, last stand draft reduction, last stand work roll diameter, last stand rolling force, %C of strip, and target width. Taking into account that the measurements are modelled as type 1 non-singleton fuzzy numbers, the authors present the so called interval type 1 non-singleton type 2 fuzzy logic system controllers. As reported in the literature, interval type 2 fuzzy logic systems have greater approximation capacity than that of its type 1 counterpart and it has the advantage to develop more robust and reliable solutions than the latter. The experiments of these applications were carried out for three different types of coils, from a real hot strip mill. The results proved the feasibility of the developed system for FM thread speed set-up and control, and for interstand strip temperature profile prediction. Comparisons with the online mathematical based models show that the proposed interval type 2 fuzzy logic system equalises the performance in FM strip thread speed, and temperature set-up and control under the tested conditions characterised by high uncertainty levels.     

Modeling and Analysis of Interstand Tension Control in 6-high Tandem Cold Rolling Mill

The interstand tension control is one of the most important ways to meet tight tolerances for strip product quality during tandem cold rolling process. Using coordinate analysis and parabolic approximation for the mass flow balance principle, the strip velocities eliminating the use of forward slips and backward slips were calculated. In order to reduce the effect of roll eccentricity on the tension measurement, a filter based on bilinear transformation was de- signed. Applying a first-order Taylor series approximation, the transfer function matrix model of interstand tension stress was derived. The actual measurements on-site and the final calculation results showed that the established model had high calculation accuracy and was beneficial for interstand tension control of random cold rolling process.     

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.     

Mathematical model for on-line heat treatment of steel bars

A mathematical model to predict steel bar thermal behaviour during continuous quenching after the finishing mill has been developed. The model includes process variables, such as finishing rolling speed, finishing temperature, rod size and chemical composition, water flowrate and mechanical design of the cooling device. It was found that empirical correlations for the heat-transfer coefficient belonging to water spray systems are suitable to simulate fast cooling employing submerged water-cooling tubes. Martensite depth is strongly influenced by the bar diameter and water velocity inside the submerged tube. Mist spray systems are not as effective as submerged tubes for cooling steel bars, although, the initial cooling rates are higher. The % volume of martensite is a direct function of the self-tempering temperature, and independent of the fast cooling device.     

热连轧精轧温度设定系统及自适应研究

针对宝钢2050 mm热连轧温度设定系统的技术改造,分析研究了现有的精轧机组温度设定系统.基于现场数据采集系统的实测数据,提出了一种空冷温降辐射系数的修正方法,并采用新的指数模型替代原水冷温降模型.同时,为满足现场生产精度和稳定性的需要,建立了精轧机组的短时和长时自适应温度模型.仿真及实验结果表明,改造后温度设定系统的预测精度比原温度设定系统有更高的精度,并且在变钢种变规格轧制时误差波动小.     

轧制-直接淬火参数对Ti-B微合金化低碳Si-Mn钢组织和性能的影响

用0.06%(Ti+B)微合金化(%)0.17C-0.92Si-1.63Mn钢135mm连铸坯在实验室φ500mm中厚板轧机轧成24 mm板材,试验了终轧、开始和终止水冷温度对实验钢组织和力学性能的影响。结果表明,终轧920℃开冷900℃终冷180℃,冷却速度30℃/s和终轧880℃,开冷860℃终冷280℃,冷却速度22℃/s,钢的组织和性能与传统的880℃1h淬火+220℃ 6 h回火的组织和性能相当。