Computer Simulating Calculation on the Microstructure Evolutions during Hot Strip Rolling of C-Mn Steels

The program to predict the microstructure evolutions during hot strip rolling of C-M n steels has been developed in this paper, BV using this program, the microstructure changes with the processing parameters were analysed in detail. showing not only a good agreement of prediction with the measured values, but also entirely possibility to optimize hot strip rolling precess by computer simulation

“Quartus scale” of hot-rolled strip steels and its formation mechanism

The types and growth of various oxide scales formed during the different phases of the production of hotrolled strip steel products are reviewed. Similarities and differences between the ＂tertiary scale＂ on the surface of carbon steels at high temperatures and the oxide scale on pure iron are compared. The micro-structural features of the ＂final oxide scale＂ on the surface of strip steels at room temperature as well as the relationship between these features and the position of the steel coil （plate） and the subsequent processes of recoiling, temper rolling and trimming, etc. are summarized. The actual oxide scales retained on the commercial hot-rolled strip steels at room temperature have been proposed to define as ＂ quartus scale＂ for the first time. The micro-structural development and phase transformation of the initial ＂tertiary scale＂ during and after cooling and coiling are described. The reasons for the ＂tertiary scale＂ on carbon steels differing from the oxide scale formed on pure iron, and the major influencing factors in the formation of various types of ＂quartus scales＂ are analyzed from both thermodynamic and dynamic viewpoints. The development mechanism of ＂ quartus scales＂ is discussed and the potential effects of the ＂ quartus scale＂ state （thickness, constitution, structure and defects）, on the rusting and pickling properties of commercial hot-rolled strip steel, as well as on the mechanical properties of oxide scales are analyzed.

Influence of oxide scales on the corrosion behaviors of B510L hot-rolled steel strips

The influence of oxide scales on the corrosion behaviors of B510 L hot-rolled steel strips was investigated in this study. Focused ion beams and scanning electron microscopy were used to observe the morphologies of oxide scales on the surface and cross sections of the hot-rolled steel. Raman spectroscopy and X-ray diffraction were used for the phase analysis of the oxide scales and corrosion products. The corrosion potential and impedance were measured by anodic polarization and electrochemical impedance spectroscopy. According to the results, oxide scales on the hot-rolled strips mainly comprise iron and iron oxides. The correlation between mass gain and test time follows a power exponential rule in the damp-heat test. The corrosion products are found to be mainly composed of γ-Fe OOH, Fe3O4, ？-Fe OOH, and γ-Fe2O3. The contents of the corrosion products are different on the surfaces of the steels with and without oxide scales. The steel with oxide scales is found to show a higher corrosion resistance and lower corrosion rate.

Effect of hot rolling on the microstructure and impact absorbed energy of the strip steel by CSP

The microstructures and impact absorbed energies at various temperatures were investigated for steel strips hot rolled to thickness reductions of 95.5%, 96.0%, 96.5%, 97.0%, and 97.5%. Results indicate that grain refinement can be realized with an increase in hot rolling reduction. Besides, finer precipitates can be achieved with an increase in hot rolling reduction from 95.5%to 97.0%. The impact absorbed energy decreases with a decrease in testing temperature for steel strips hot rolled to 95.5%, 96.0%, and 96.5%reductions in thickness. However, in the case of steel strips hot rolled to 97.0%and 97.5%reductions in thickness, the impact absorbed energy remained almost constant with a decrease in testing temperature.

Development and future prospect of hot strip rolling technology at Baosteel

Since the 2050 mm hot strip mill was put into operation in 1989, Baosteel has made great achievements in increasing productivity, developing new process technologies and steel products and improving product quality. In the past 18 years from 1989 to 2007 ,Baosteel has constructed five hot strip mills with a total annual capacity of 19.8 Mt. Indices for technology standards, product categories and steel grades, product quality, both technically and economically, take the lead domestically or reached the world class level. As there are many hot strip mills that expected to be put into operation by the end of 2010 ,the overall annual capacity will exceed 30 Mt ,and the product will cover grain oriented （GO） Si steels and alloyed steels.

Mathematical model for cooling process and its self-learning applied in hot rolling mill

Control precision of coiling temperature is one of the key factors affecting the profile shape and surface quality during the cooling process of hot rolled steel strip.For this reason,the core of temperature control precision is to establish an effective cooling mathematical model with self-learning function.Starting from this point,a cooling mathematical model with nonlinear structural characteristics is established in this paper for the cooling process of hot rolled steel strip.By the analysis of self-learning ability,key parameters of the mathematical model could be constantly corrected so as to improve temperature control precision and adaptive capability of the model.The site actual application results proved the stable performance and high control precision of the proposed mathematical model,which would lay a solid foundation to improve the steel product qualities.

Mill scale structure and damp heat corrosion performance of four 510L hot-rolled strips

In this study, the matrix structure, state and composition of the mill scales of four typical domestically made 510L hot-rolled strips were observed and analyzed by means of optical microscopy （OM） ,scanning electron microscopy （SEM） and X-ray diffraction （XRD）. The corrosion behavior of the steels with and without mill scales were investigated by means of hot-humid corrosion tests under the condition of relative humidity （ RH ） of 95% at 50℃ and 70℃, respectively. The results show that the matrix structures, state, composition and thickness of mill scales vary in the strips. The rusting starting time of the specimens with scales is generally a bit longer than that of the specimens without scales, but their corrosion mass-gain is higher. For these two kinds of specimens ,their corrosion rate increases significantly with the increase of temperature. The rusting behavior of the 510L strips produced by various plants is different due to the variations of hot-rolling processes and designed chemical compositions. Various relevant aspects should be taken into account in the evaluation of the corrosion behavior of hot-rolled strips.

基于PCA-RF的热轧带钢板凸度预测

为了满足日益增长的带钢板凸度预测精度和速度要求,建立了一种基于降维的主成分分析(Principal Component Analysis,PCA)协同随机森林(Random Forest,RF)的板凸度预测模型。首先,应用Pauta准则去除异常值,用五点三次平滑公式进行降噪处理;其次采用主成分分析法对数据进行降维,利用载荷矩阵选取关键控制变量;最后利用关键控制变量建立基于随机森林的板凸度预测模型,并与支持向量机回归(Support Vector Regression,SVR)、最近邻(K Nearest Neighbor,KNN)、轻量梯度提升机(light Gradient Boosting Machine,LightGBM)、极端梯度增强(Extreme Gradient Boosting,XGBoost)和梯度提升决策树(Gradient Boosting Decision Tree,GBDT)模型进行比较。结果表明,PCA-RF模型将参数由93维降低到15维,极大地减少了建模时间,且PCA-RF对测试集预测的决定系数(Coefficient of Determination,R^(2))、平均绝对误差(Mean Absolute Error,MAE)和均方根误差(Root Mean Squared Error,RMSE)分别为0.9820、1.4852μm和2.2603μm,均优于其他预测模型,且98%以上样本点的预测误差为-3~3μm,满足板凸度预测的精度要求。从而证明该模型能够通过降维减少建模时间,同时实现了带钢板RF凸度的高精度预测,为热轧带钢板凸度的研究提供了一定的参考。

Optimal design of hot rolling process for C-Mn steel by combining industrial data-driven model and multi-objective optimization algorithm

A successful mechanical property data-driven prediction model is the core of the optimal design of hot rolling process for hot-rolled strips. However, the original industrial data, usually unbalanced, are inevitably mixed with fluctuant and abnormal values. Models established on the basis of the data without data processing can cause misleading results, which cannot be used for the optimal design of hot rolling process. Thus, a method of industrial data processing of C-Mn steel was proposed based on the data analysis. The Bayesian neural network was employed to establish the reliable mechanical property prediction models for the optimal design of hot rolling process. By using the multi-objective optimization algorithm and considering the individual requirements of costumers and the constraints of the equipment, the optimal design of hot rolling process was successfully applied to the rolling process design for Q345B steel with 0.017% Nb and 0.046% Ti content removed. The optimal process design results were in good agreement with the industrial trials results, which verify the effectiveness of the optimal design of hot rolling process.

热轧宽带钢极薄板轧制失稳原因分析与控制

基于鞍钢股份有限公司热轧带钢厂2150ASP生产线轧制情况,对热轧宽带钢极薄板轧制失稳导致的顺折事故进行了分析。结果表明,临近年修末期,精轧机组的设备精度下降,厚度精度下降,F6机架的自动厚度控制液压缸动作幅度大且响应快,导致了顺折事故的发生。通过优化精轧自动厚度控制响应速度、动作限幅以及功能选用,有效解决了轧制失稳导致的顺折问题,顺折事故发生率由0.046%降低至0.011%。

高锰氮奥氏体不锈钢塑性变形机制及组织-性能的研究

研究了Fe-22Cr-25Mn-2Si-0.7N型奥氏体不锈钢在不同工艺条件下的组织结构及其力学性能。此种奥氏体不锈钢,不仅可节约贵重金属镍,且具有较高的强度和塑性,具有在弱腐蚀环境中代替304等含镍不锈钢的可能性。探讨了两种不同的成型条件下这种奥氏体不锈钢的性能。首先,奥氏体不锈钢经过模铸热轧成4 mm的板材,分别在1323,1373和1473 K下固溶处理30 min后淬火至室温。对其力学性能的检测发现,最佳固溶处理温度为1373 K。在此条件下可以得到较好的强度、塑性及成型性综合性能(屈服强度为580 MPa,抗拉强度930 MPa,延伸率为45%,屈强比为0.62)。另外,利用双辊铸轧的方法探讨了这种不锈钢的薄带近终型成形工艺,得到了屈服强度为500 MPa,延伸率为15%的铸态薄带。采用XRD,OM,SEM和TEM对不锈钢的显微组织进行了分析和检测。结果发现,变形孪晶是影响高锰氮不锈钢塑性变形的重要机制。

C-Mn钢热轧带奥氏体再结晶晶粒尺寸的预测

在研究板带控轧控冷过程中钢中显微组织演变过程奥氏体再结晶、碳氮化合物析出、奥氏体相变和组织性能对应关系的物理冶金模型的基础上 ,通过Gleeble 15 0 0热模拟机和计算机模拟计算得出成分(% ) 0 16C ,0 0 6Si,1 30Mn钢在 1173～ 10 81K经 7道次热变形后奥氏体晶粒尺寸为 4 3μm ,同时实测 7道次变形后轧钢组织中奥氏体尺寸为 38μm ,相对误差 13%。计算机模拟计算的奥氏体再结晶晶粒尺寸与实测结果吻合较好。

应用超快冷工艺开发540MPa级C-Mn双相钢试验

介绍了在包钢CSP线上应用超快速冷却工艺开发540MPa级热轧双相钢的工业试验概况;以0．07% C—1．20%Mn—0．15%Si钢为原料,采用薄板坯连铸连轧、层流冷却和超快速冷却工艺,得到厚6mm的热轧双相钢带;其微观组织为铁素体和马氏体,马氏体体积分数为12%,σ_b为555～565MPa,σ_s为335～355MPa,δ为31%～34%,σ_s/σ_b为0．59～0．64,n值为0．18,整卷带钢性能均匀,应用于重型卡车横梁,性能良好。

汽车车轮用高扩孔率热轧复相钢带的研制

设计了一种微合金化的汽车车轮用高扩孔率热轧复相钢,并对其进行了工业试制。采用金相检验、力学性能测试等方法研究了高扩孔率热轧复相钢的显微组织及力学性能。结果表明:试制产品的显微组织主要由贝氏体、铁素体构成,还分布有少量的马氏体、残余奥氏体以及弥散析出的第二相粒子,产品的屈服强度、抗拉强度、断后伸长率分别超过了520,610MPa和24%,屈强比为0.85~0.87,扩孔率达到83%以上,沿板宽方向的扩孔率在10%以内波动;增加Si元素含量能明显改善扩孔性能,同时会影响产品的表面质量,将Si元素的质量分数控制在0.20%左右较为合适;试制产品具有优异的局部成形性、良好的抗疲劳性和焊接性能,在疲劳试验承载力为1700 N·m的条件下,车轮弯曲疲劳寿命达到60万次以上。

基于时域卷积网络的精轧出口厚度预测

以精轧过程为研究对象,引入时域卷积网络算法,构建了基于时域卷积网络的精轧出口厚度预测模型。利用时域卷积网络模型提取精轧过程时序数据的特征信息,通过优化模型结构和参数,提升精轧出口厚度预测性能。实际钢种数据集仿真实验结果表明,相较于传统方法,本文所提出的时域卷积网络算法在均方根误差、平均绝对百分比误差及决定系数等评价指标方面存在较大优势,可为现场工程师提供重要的决策信息。

Ti微合金化400 MPa级光伏支架用钢的开发

详细介绍了山西建龙1500生产线试制400 MPa级光伏支架用热轧钢带的成分设计、工艺路线以及产品质量情况。生产实践表明,按照设计的成分和工艺生产的光伏支架用热轧带钢的组织为铁素体+少量珠光体,拉伸性能和冷弯性能优异,能够满足用户的使用要求。

基于STMR-CNN的热轧带钢表面缺陷检测

为了提高工业热轧带钢表面缺陷检测的检测精度,将深度学习研究领域的前沿技术应用于带钢表面缺陷检测.提出了一种以Swin Transformer作为骨干特征提取网络,级联多阈值结构作为输出层的热轧带钢表面缺陷检测算法.将Transformer结构应用于带钢表面缺陷检测领域,与单纯基于卷积网络的深度学习目标检测算法相比,能够达到更加精确的检测效果.首先,使用Swin Transformer作为骨干特征提取网络代替常规的残差网络结构,增强特征网络对隐含在图像中的深层语义信息的摄取能力.其次设计多级联检测结构,设置逐级的IoU阈值,实现检测精度与阈值提升的权衡.最后使用柔性非极大值抑制(Soft-NMS)、FP16混合精度训练和SGD优化器等训练策略加速模型收敛和提升模型性能.实验结果表明:本文算法在工业热轧带钢数据集(NEU-DET)上相较于YOLOv3、YOLOF、DeformDetr、SSD512和SSDLit等深度学习算法都有更好的检测效果,在裂纹(crazing,Cr)、夹杂(inclusion,In)、斑块(patches,Pa)、麻点(pitted surface,PS)、压入氧化铁皮(rolled-inscale,RS)、以及划痕(scratches,Sc)等表面缺陷检测中训练速度和检测精度都有显著的提升,漏检率显著降低.

轧制温度对SPHC热轧带钢氧化铁皮的影响

针对现场SPHC热轧带钢表面的麻点/坑缺陷,研究了干燥空气中SPHC热轧带钢在实际粗轧至精轧温度范围(830~1080℃)内的氧化行为,利用显微镜对氧化铁皮表面的起泡现象、氧化铁皮横截面的厚度与结构进行分析,预测了氧化铁皮厚度随氧化温度变化的规律.结果表明:当氧化温度为830~1080℃时,SPHC热轧带钢的氧化过程遵循抛物线规律,氧化铁皮厚度随氧化温度的升高而增加;当氧化温度830~930℃时,Fe_(3)O_(4) 层占比随氧化温度的升高而增加,板坯受氧化铁皮影响较小;当氧化温度为930~1030℃时,Fe_(3)O_(4) 层占比大于FeO层占比,氧化铁皮出现起泡现象;当氧化温度为1011℃时,氧化铁皮的增厚速率达到最大,此时氧化铁皮的变形性也最差,带钢极易产生麻点缺陷;适当增加粗轧后的除鳞水量、降低精轧开轧温度,以及关注初始道次轧辊表面质量,可有效避免SPHC热轧带钢表面的麻点/坑缺陷.

热轧卷取机带钢头部堆钢现象分析

带钢卷取时,会因电气设施发生故障、自动控制不够完善、异物卡阻等问题造成设备停机,导致带钢头部出现堆钢现象。针对此,结合自动化控制长期实践经验,对带钢头部堆钢原因进行了分析研究,并制定相应的处理和预防措施,以减少带钢头部堆钢事故的发生。

基于改进斑点鬣狗算法的热轧带钢负荷分配智能优化

针对热连轧过程中由于负荷分配不均匀导致板形控制效果不佳的问题,以传统的轧制机理为基础建立负荷分配均匀、板形良好的目标函数,分别采用斑点鬣狗算法和改进斑点鬣狗算法进行单目标和双目标的负荷分配的优化求解。结果表明,改进斑点鬣狗算法将末机架的相对凸度差从0.000 834 5降低到0.000 014 83和-0.000 026 34,且在允许的范围内,上游机架负荷分配合理,充分发挥了轧机的轧制能力。