高温回火热处理对核级E316L不锈钢焊条熔敷金属性能的影响

对经历610℃恒温16 h高温热处理的E316L不锈钢焊条熔敷金属进行力学性能、抗晶间腐蚀性能和微观结构检验分析,结果表明:E316L不锈钢焊条熔敷金属室温抗拉强度升高,非比例延伸强度下降,断后伸长率下降,室温冲击吸收功下降10 J左右,微观组织中的岛状铁素体发生部分分解,析出相少量增加,但强度、断后伸长率、冲击吸收功、抗晶间腐蚀性能仍符合技术条件的要求,铁素体相基本特征未改变,少量M23C6析出相分布在奥氏体晶粒内部,未发生在晶界的聚集。研究表明,研发的E316L焊条熔敷金属经历610℃恒温16 h高温热处理后,其力学性能和抗腐蚀性能满足技术要求。     

Ni690镍基合金焊条的研制

采用低氢型渣系,开发了工艺性能优良的Ni690焊条.研究了Ni690焊条熔敷金属中Nb和Mn对拉伸性能的影响,结果表明:随着Nb含量从1.15％增加到3.24％,熔敷金属强度增加,断后伸长率下降;随着Mn含量从3.99％增加到4.44％,熔敷金属强度和断后伸长率变化不大.最后进行了Ni690焊条熔敷金属腐蚀试验.结果表...     

9%Ni钢配套焊条熔覆金属的组织和性能研究

针对9%Ni钢使用温度低,抗拉强度高和焊条工艺性不好等问题,研制了以CaO-CaF_2-TiO_2为主的渣系和Ni-Cr-Mo-Mn-W-Nb合金系的焊条。测试了熔敷金属的力学性能,借助光学显微镜、扫描电镜和光谱分析仪对接头组织和化学成分行了分析。结果表明,研制的焊条脱渣性能良好。熔敷金属抗拉强度为648 MPa,屈服强度为442 MPa,断后伸长率为36%,满足9%Ni钢使用要求。焊缝组织为奥氏体基体+析出物,奥氏体塑性好,析出相强化基体,-196℃下平均冲击吸收功为135 J,断口为典型的韧性断裂。     

高强焊条药皮碱度对韧性与扩散氢的影响

通过使用钛硼微合金化以获得韧性组织焊缝、提高焊条药皮碱度以净化焊缝等手段,可使屈服强度级别为785MPa的手工焊条熔敷金属-50℃冲击吸收功AKV平均值超过80J.但焊条药皮碱度过高时,AKV(-50℃)值没有明显增加,而且对降低熔敷金属扩散氢不利.采用对焊条药皮原材料进行分类高温去水处理,对成品焊条多次烘干吸湿烘干处理后,反复测定.结果表明,当焊条药皮碱度在2.2～2.4之间时,熔敷金属可同时具有高屈服强度、高低温冲击吸收功及超低扩散氢.     

核级E309L-16奥氏体不锈钢焊条的研制

核岛主设备核心部件使用的E309L-16奥氏体不锈钢焊条长期依赖进口,严重制约中国核电事业的发展.研究了焊态铁素体含量对熔敷金属经608℃×40 h热处理后断后伸长率的影响,对焊态铁素体含量大于12％的热处理态熔敷金属微观组织进行分析,并研究了热输入和热处理保温时间对熔敷金属拉伸性能的影响,试验结果表明:当铁素体含量大于12％时,δ-铁素体分解很不均匀,导致熔敷金属断后伸长率波动较大,可能会出现断后伸长率小于18％;当铁素体含量增大至17.8％时,δ-铁素体大部分发生分解,并有σ相析出,是导致脆断的原因;热输入和热处理保温时间对熔敷金属的断后伸长率影响不大.     

V含量及回火工艺对高强钢TIG焊熔敷金属组织性能的影响

采用四种不同V含量焊丝对高强钢板进行钨极氩弧焊试验,焊后对熔敷金属进行640 ℃保温2 h的回火处理. 研究了V含量和回火处理对熔敷金属微观组织及力学性能的影响. 结果表明,焊态及焊后回火态条件下,随着V含量的增加,熔敷金属强度升高,延伸率和冲击功降低,经回火处理后,不含V熔敷金属内晶界处析出M₂C碳化物,而含V熔敷金属内析出弥散分布的VC析出相,焊后回火过程中位错回复引起基体软化的作用高于M₂C及VC的析出强化作用,导致回火后强度降低,断后伸长率冲击吸收能量升高. 细小VC具有阻碍位错运动的作用,导致回火后含V熔敷金属仍保留较高的位错密度. 实际应用中应根据熔敷金属性能要求合理选择V含量及焊后回火工艺.     

铁素体含量对309L焊条焊后热处理态拉伸性能影响研究

选用2个批次不同铁素体含量的309L焊条,在不同模拟焊后消应力热处理(SPWHT)保温时间状态下进行熔敷金属拉伸试验。试验结果表明,随着SPWHT保温时间的延长,高铁素体含量焊条的断后伸长率显著下降,低铁素体含量焊条的熔敷金属始终保持较好的塑性。通过试样断口分析、金相组织观察和扫描电镜观察,韧性δ-Fe在SPWHT过程中转变为脆性σ相,是造成高铁素体含量的309L焊条断后伸长率显著下降的主要原因。本研究为新型核电工程用不锈钢堆焊材料的设计、采购和验收提供了重要依据。     

海洋工程用超低氢高韧性焊条CJ557HG的研制

采用回归正交设计法研制了一种海洋工程用钢Q460E配套焊材超低氢高韧性CJ557HG焊条。焊条的工艺性能、力学性能及抗裂性测试表明,设计的焊条具有良好全位置操作工艺性能、力学性能和抗裂性。熔敷金属及对接接头夏比冲击吸收功A_(KV2)≥120 J(-40℃),且韧脆转变温度在-60~-70℃之间,表明具有良好的韧性。水银法测得熔敷金属扩散氢含量值为3.15 mL/100 g,达到超低氢水平。焊缝金属微观组织以针状铁素体为主,同时含有一定量的先共析铁素体和侧板条铁素体组织。     

结构钢焊条熔敷金属化学成分的人工神经网络预测系统

基于Matlab神经网络工具箱，设计了一个用于结构钢焊条熔敷金属化学成分预测的神经网络模型。该模型采用前向神经网络，利用BP算法，建立了熔敷金属化学成分与力学性能之间的关系。用此神经网络，既可预测结构钢焊条熔敷金属化学成分，也为深入研究结构钢焊条化学成分提供了有利的工具。     

T91/P91钢配套焊条CHH717的研制

讨论了影响所研制焊条熔敷金属理化性能的主要因素,尽可能低的S、P、Al等有害杂质含量及合理的合金含量可以得到良好的综合力学性能.经过试验确定了热处理工艺,并通过相变点Ac1的测试得到了印证.试验结果表明,焊条的焊接工艺性良好.熔敷金属的化学成分及力学性能均满足有关标准要求.微观组织观察表明,经760 ℃×2 h回火后其熔敷金属显微组织为回火索氏体.对所研制焊条的熔敷金属进行了625 ℃外推105 h高温持久强度试验,证明此焊条可广泛应用于超(超)临界发电设备用相应耐热钢的焊接.     

Forecasting of mechanical properties of covered electrode containing La/CeO_2 based on fuzzy neutral network

In order to improve the mechanical properties of deposited metal of ilmenite type welding electrode,CeO_2/La rare earth elements were added into electrodes based on E4301 electrode, then electrodes were produced,test plates were welded, and mechanical properties were tested based on National Standards of China. For the sake of solving the problems of large amount of mechanical properties tests, long test cycle and high test cost during the conventional production process of electrode, a prediction model of the mechanical properties of deposited metal based on Takagi-Sugeno(T-S) fuzzy neural network was established. Mn, Si and C contents of medium manganese in electrode, CeO_2, and La contents of electrode and welding speed were selected as input variables of the prediction model, and the tensile strength, lower yield strength, elongation, impact energy and hardness of deposited metal were selected as output variables. Finally,predicting experiment was done under test samples, and results show that average relative prediction error of the tensile strength, lower yield strength, elongation and hardness are 0.91 %, 2.57 %, 4.94 % and 1.94 %, respectively, which reach the need of actual production. The results of prediction show that the mechanical properties of deposited metal of electrode containing rare earth can be forecasted accurately through material composition of electrode and welding parameters based on T-S fuzzy neural network model.     

基于改进的RBF神经网络的热轧板冲击功预报模型

为了对Q345B中厚板的冲击吸收功进行预报并指导生产,采用RBF网络预测冲击吸收功与化学成分、工艺参数、屈服强度及抗拉强度等因素间的关系.针对RBF神经网络的不足,采用改进的遗传算法优化RBF网络结构和权值参数,并建立了基于改进遗传算法的RBF神经冲击功预测模型.实验结果表明,用这种改进的遗传算法优化后的神经网络算法是有效的、可行的.     

应用人工神经网络模型预测Ti＋10V-2Fe-3A合金的力学性能

采用人工神经网络方法建立了Ti-10V-2Fe-3Al合金机械性能预测的神经网络模型。模型的输入参数包括变形温度、变形程度、固溶温度、时效温度等热加工工艺参数和热处理制度。模型的输出为钛合金最重要的5个机械性能指标，即抗拉强度、屈服强度、延伸率、断面收缩率和断裂韧性。与传统回归拟合公式相比，该模型具有容错性好、通用性强等优点。该模型可以预测Ti-10V-2Fe-3Al合金在不同热加工工艺参数和热处理制度下的机械性能，也可以用于优化热加工参数和热处理制度。     

基于BP神经网络的TC11钛合金工艺-性能模型预测

材料工艺与性能的关系具有复杂、非线性交互等特点。本文根据TC11钛合金力学性能与其影响因素之间的映射关系,以大量的试验数据为基础,建立了BP神经网络模型。模型的输入包括锻造温度、锻后冷却方式等热加工工艺参数;输出为常用的力学性能指标,即抗拉强度、屈服强度、延伸率和断面收缩率。运用该模型对TC11钛合金力学性能进行了预测,并通过试验数据对模型的预测精度进行了可靠性验证。同时,运用已建立的神经网络模型对TC11钛合金工艺参数与力学性能的关系进行了分析。结果表明,所建立的力学性能预测模型具有良好的外推能力,并且可以很好地反映出该合金的工艺-性能之间的复杂关系。     

Modeling of mechanical properties of as-cast Mg-Li-Al alloys based on PSO-BP algorithm

Artificial neural networks have been widely used to predict the mechanical properties of alloys in material research.This study aims to investigate the implicit relationship between the compositions an...     

双电极焊条TE4303单弧焊接分析

从焊接效率与节能、微观组织、力学性能、断口形貌等方面对钛钙型双电极焊条(TE4303)单弧焊进行了研究.结果表明,与传统单芯焊条(E4303)电弧焊相比,当采用相同的焊接电流时,TE4303单弧焊熔化系数和熔敷系数可提高1倍,熔化单位重量焊条金属节省电能约20%～30%;TE4303单弧焊对母材热输入小,接头熔合比小,...     

基于自适应模糊神经网络焊接接头力学性能预测

通过对TC4钛合金进行TIG焊,并测定接头的抗拉强度、抗弯强度和断后伸长率,获得网络仿真所需的数据.结合使用BP算法与最小二乘相结合的混合算法,建立了用于焊接接头力学性能预测的自适应模糊神经网络模型.利用该模型进行仿真,其平均误差远小于7%.结果表明,该模型可根据焊接工艺参数对焊接接头的抗拉强度、抗弯强度和断后伸长率等力学性能进行较为准确的预测,并且具有建模快、模型简单、预测速度快、预测精度高,泛化能力强的优点,从而为焊接接头力学性能预测提供了一条有效的途径.     

基于组合模型的MAG焊工艺参数多目标优化

以MAG焊焊接电压、焊接速度、送丝速度为可调工艺参数，开展了三因素三水平全因子平板对接焊和堆焊试验.基于试验数据建立了误差反向传播神经网络、径向基神经网络和克里金模型来预测焊缝余高、接头抗拉强度和冲击吸收能量.模型预测结果显示，所建立模型均能较好的预测焊缝性能，但是没有一个模型能同时最佳预测三种焊缝性能且各模型预测波动较大. 为了进一步提升预测精度和稳定性，将误差反向传播神经网络、径向基神经网络和克里金模型以线性加权法组合. 结果表明，组合模型能提升预测的精度和稳定性.基于组合模型，采用NSGA-II算法实现多目标优化，得到并验证了焊缝余高、接头冲击吸收能量和抗拉强度三者间的非劣解.验证结果表明焊接工艺多目标优化对实现焊缝综合性能整体最优以及焊接精细化应用具有较大的指导意义.     

Effect of normalising heat treatment on microstructure and properties of nickel alloyed C-Mn weld metals

Abstract

Five different basic manual metal arc welding electrodes, containing varying amounts of nickel (from 0 to 3.5%) were deposited in an all weld metal joint. Mechanical testing and microstructure examination was performed in the as deposited and heat treated conditions. The heat treatment was carried out at three different temperatures (930, 980, and 1030° C) for 20 min. The tensile strength was decreased by the heat treatment, but the magnitude of the decrease varied between the weld metals. The impact properties were also affected by the heat treatment. For impact properties, however, a decrease was found at low testing temperatures, whereas an increase was observed at higher testing temperatures. The decrease in tensile strength after normalisation, compared with the as deposited condition, is due to an increasing grain size and a decreasing dislocation content. The strength achieved by the different weld metals in the normalised condition can be explained by the variation in solid solution hardening resulting from differences in the alloying content.Two factors seemed to be especially important in determining the variations in impact properties between weld metals in the as deposited condition. The nitrogen content of the weld metals decreased the impact toughness, whereas increasing nickel content was associated with improved impact toughness. In the normalised condition, reduced at lower testing temperatures, because cleavage fracture started readily in the resulting coarser grains. Furthermore, traces of segregated bands of microphases probably acted as initiation sites for cleavage cracks. At higher testing temperatures, higher impact toughness was obtained, owing to the lower strength of the weld metals. One of the electrodes showed superior impact toughness values to the other electrodes, in both the as deposited and heat treated conditions. The main reason for the high toughness in the as deposited condition was the ability of this electrode to refine previously deposited beads to a high degree. The reason for the high toughness after normalising is still not certain, but it was noted that this weld metal had a very low oxygen content and also a comparatively low volume fraction of segregated microphases. These factors might be important in achieving the very high impact toughness observed.     

熔敷金属力学性能人工神经网络预测法的应用

在实测样本的基础上,用人工神经网络建立了熔敷金属力学性能的预测模型。该模型预测的结果同实验值之间有很好的对应关系。利用该模型研究了杂质元素S,P,O,N和合金元素C,Mn,Ti对熔敷金属低温韧性的影响,并采用正交实验的方法得出了较佳的熔敷金属化学成分。本文的研究为熔敷金属力学性能的设计和控制提供了有效的途径。