Optimization of Rolling Process for Bi(2223)/Ag Superconducting Tapes by a Statistical Method

Ag-sheathed (Bi,Pb)(2)SoCa(2)Cu(3)O(x) tapes were prepared by the powder-in-tube method. The influences of rolling parameters on superconducting characteristics of Bi(2223)/Ag tapes were analyzed qualitatively with a statistical method. The results demonstrate that roll diameter and reduction per pass significantly influence the properties of Bi(2223)/Ag superconducting tapes while roll speed does less and working friction the least. An optimized rolling process was therefore achieved according to the above results.

Control Method of Effect of Robust Optimization in Multi-Player Multi-Objective Decision-Making

In the real situations of supply chain, there are different parts such as facilities, logistics warehouses and retail stores and they handle common kinds of products. In this research, these situations are focused on as the background of this research. They deal with the common quantities of their products, but due to their different environments, the optimal production quantity of one part can be unacceptable to another part and it may suffer a heavy loss. To avoid that kind of unacceptable situations, the common production quantities should be acceptable to all parts in one supply chain. Therefore, the motivation of this research is the necessity of the method to find the production quantities that make all decision makers acceptable is needed. However, it is difficult to find the production quantities that make all decision makers acceptable. Moreover, their acceptable ranges do not always have common ranges. In the decision making of car design, there are similar situations to this type of decision making. The performance of a car consists of purposes such as fuel efficiency, size and so on. Improving one purpose makes another worse and the relationship between these purposes is tradeoff. In these cases, Suriawase process is applied. This process consists of negotiations and reviews of the requirements of the purposes. In the step of negotiations, the requirements of the purposes are share among all decision makers and the solution that makes them as satisfied as possible. In the step of reviews of the requirements, they are reviewed based on the result of the negotiation if the result is unacceptable to some of decision makers. Therefore, through the iterations of the two steps, the solution that makes all decision makers satisfied is obtained. However, in the previous research, the effects that one decision maker reviews requirements in Suriawase process are quantified, but the mathematical model to modify the ranges of production quantities of all decision makers simultaneously is not shown. Therefore, in this research, based on Suriawase process, the mathematical model of multi-player multi-objective decision making is proposed. The mathematical model of multi-player multi-objective decision making by using linear physical programming (LPP) and robust optimization (RO) in the previous research is the basis of the methods of this research. LPP is one of the multi-objective optimization methods and RO is used to make the balance of the preference levels among decision makers. In LPP, the preference ranges of all objective functions are needed, so as the hypothesis of this research. In the research referred in this research, the method to control the effect of RO is not shown. If the effect of RO is too big, the average of the preference level becomes worse. The purpose of this research is to reproduce the mathematical model of multi-player multi-objective decision making based on Suriawase process and propose the method to control the effect of RO. In the proposed model, a set of the solutions of the negotiation problem is obtained and it is proved by the result of the numerical experiment. Therefore, the conclusion that the proposed model is available to obtain a set of the solutions of the negotiation problems in supply chain.

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.

Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.

弧齿锥齿轮小轮温滚轧数值模拟及工艺参数优化

针对弧齿锥齿轮现有的工艺加工效率低、疲劳强度不足的问题,提出了一种弧齿锥齿轮小轮温滚轧成形数值模拟和参数优化方法。基于deform-3D有限元仿真软件分析了温滚轧过程中摩擦因子、进给速度、初轧温度等工艺参数对小轮温滚轧成形应力应变的影响规律,结合正交试验完成了工艺参数优化。采用最佳工艺参数组合开展了小轮温滚轧成形试验,对弧齿锥齿轮小轮进行了齿面和齿距检测。结果表明:凸面和凹面总偏差分别为14.4μm、14.1μm,齿距累计总偏差分别为57.0μm、56.3μm,精度等级达到了GB 8级,齿轮的齿面和齿距精度满足热处理后的磨齿加工需求。

计及区间预测信息的含风电电力系统有功多时间尺度协调调度优化方法

间歇性、集群式的风电并入大电网将会增加输电断面功率越限风险,将点预测信息纳入含风电的电力系统调度将不可避免出现“过调度”和“欠调度”。为此,该文提出计及区间预测信息的含风电电力系统有功多时间尺度协调调度优化方法。首先,利用点模型及其预测误差分布构建风电功率区间预测模型;其次,建立具有区间预测信息的风电场有功功率动态分群策略;再次,构建风电集群和自动发电控制(automatic generation control,AGC)机组与非AGC机组等多时间尺度协调的调度策略,通过滚动优化和反馈校正环节协调日前-日内以及实时调度;最后,采用实际风电集群有功功率数据和改进的IEEE-118节点标准测试系统验证所提方法的有效性。研究表明,所提方法不仅可以合理协调风电集群内各个风电场输出功率,还可以协调风电集群功率和AGC机组与非AGC之间的输出功率,有效解决了调度指令与实际输出功率不协调问题。

基于差分进化算法的热轧板坯工艺参数优化

针对热轧生产过程中工艺参数优化问题,提出了一种差分进化算法。首先,构建随机森林回归模型预测质量特征;然后,基于随机森林回归模型的工艺参数重要性排序结果选择待优化的工艺参数;最后,利用差分进化算法优化工艺参数并使用最优结果替换待优化的工艺参数。文章提出以缺陷相对发生率平均降低值和平均降低率作为评价指标,对比研究优化前后的结果,与其他优化算法相比,差分进化算法达到了最优性能。应用分析表明,所提算法进行工艺参数优化后,单位板坯中的缺陷个数均少于25,算法执行平均用时为8.57 s,具有良好的可操作性与应用推广价值。

考虑源荷储协同的主动配电网多时间尺度优化调度

随着分布式能源、柔性负荷和储能装置等资源的不断扩增,配电网逐渐转变成主动参与电网运行的调节与控制的主动配电网。针对储能装置、柔性负荷的利用效率较低等问题,提出一种荷源储协同的优化调度方法。首先,建立一个多时间尺度的主动配电网调度模型,然后以配电网电能质量最佳和最小运行成本为目标函数,以储能约束、网络平衡约束以及柔性负荷约束等作为约束条件。最后通过IEEE-33系统构建主动配电网,建立日前-日内的多时间尺度调度策略,利用随机权重粒子群算法求解多目标优化问题。验证了所提方法的可行性。

基于改进NSGA-Ⅱ的轴承企业生产智能排程

针对轴承企业生产排程难以应对订单动态扰动事件的问题,提出了考虑订单扰动规则和模型算法相结合的生产智能排程方法。考虑订单变更如插单和撤单等扰动因素,制定基于订单扰动的动态排程规则;以准时交付率、设备利用率、加工成本为优化目标,综合考虑生产时序、加工设备和时间等约束,建立生产排程的多目标协同优化模型;利用改进NSGA-Ⅱ对模型进行求解并实现智能排程。实例验证结果表明,与人工排程相比,智能排程在保证交货期最优及各约束条件的情况下,准时交付率提高66.7%,设备利用率提高8.6%,加工成本降低4.3%,能够实时响应普通订单和紧急订单等订单扰动事件,精准预估交货期,快速响应客户需求。

TA2钛管挤轧成形金属变形规律及工艺优化

采用挤轧成形工艺制备TA2钛管,建立了TA2钛管挤轧成形有限元仿真模型,研究了管坯在挤轧成形工艺中的变形过程;探究了轧辊送进角、轧辊公转速度和管坯前进速度对挤轧成形后管坯尺寸精度的影响规律;以管坯几何尺寸精度为评价依据,通过正交模拟试验得到钛管挤轧成形的最优工艺参数。结果表明,管坯的径向应变、周向应变以及轴向应变在挤轧变形区内呈明显三角分布;送进角过大和过小均使得管坯的尺寸偏差增大,管坯的尺寸偏差随着轧辊公转速度的增大而增大,管坯前进速度过小会导致管坯成形质量变差;最优的挤轧工艺参数为送进角6°,轧辊公转速度150 r·min^(-1),管坯前进速度5 mm·s^(-1);基于优化的挤轧工艺参数,成功挤轧出质量良好的TA2钛管。

超声滚压GCr15表面性能模型建立及工艺参数优化

目的基于超声滚压后GCr15试样表面粗糙度和表面硬度与工艺参数之间的数学模型,获取超声滚压GCr15的最佳工艺参数。方法首先,通过单因素试验筛选4个工艺参数的取值范围;其次,建立基于响应曲面的超声滚压GCr15表面硬度及表面粗糙度预测模型;再次,基于遗传算法对2个预测模型进行多目标复合优化,得到最佳工艺参数;最后,针对多目标优化结果进行试验验证。结果在超声滚压处理GCr15时,滚压静压力及滚压次数对试样表面硬度及表面粗糙度的影响极显著,转速的影响不显著;进给量对表面硬度有显著影响,对表面粗糙度的影响不显著。粗糙度模型受到静压力和滚压次数双因子交互作用的影响,硬度模型不受交互作用的影响。基于遗传算法进行多目标优化得到的最佳工艺参数如下:转速为207 r/min,进给量为0.34 mm/r,静压力为0.49 MPa,滚压次数为3。在最佳工艺参数下得到试样的最低表面粗糙度为0.34μm、最高硬度为60.5HRC。结论基于响应曲面法的GCr15超声滚压表面性能预测模型准确有效。采用最优工艺参数能够获得最优表面质量。

圆柱齿轮滚轧成形数值模拟与突耳控制

滚轧成形技术可有效提高金属材料利用率、改善齿轮疲劳强度。对直齿圆柱齿轮的滚轧成形技术进行研究,推导齿面方程,实现了齿面点计算,利用DEFORM软件对直齿圆柱齿轮滚轧成形过程进行了模拟仿真,分析了等效应力场、等效应变场以及滚轧力的变化情况,明晰了各个阶段最大应变发生于坯料齿形中点偏齿根处、应力最大值在模具轮和坯料的接触处这一规律;探索了滚轧中突耳缺陷的形成机制,研究了摩擦因数对突耳的作用规律,实现了面向突耳控制的摩擦因数的优选,为圆柱齿轮的滚轧成形加工提供了理论基础。

中厚板因瓦合金4J36热轧生产工艺优化研究

通过对热轧中厚板4J36成品的表面质量、显微组织及力学性能的观察与分析,对其生产工艺参数进行了优化。结果表明:4J36显微组织室温下为全奥氏体组织,成品近表层存在混晶现象,晶粒大小不一。优化工艺参数后,表层混晶得到有效缓解,内部组织分布均匀,组织晶粒度为7~7.5级。随着在炉时间、开轧及再开轧、终轧温度的降低及轧后冷却速度的增加,热轧中厚板4J36的强度呈现上升的趋势,延伸率呈现下降的趋势,而显微硬度呈现先减小后增大的趋势,但其性能满足标准要求。热轧中厚板4J36最优生产工艺参数为:均热温度1160℃、在炉时间300 min、开轧温度1050℃、再开轧温度855℃、终轧温度820℃、冷速4.5℃/s。

基于ANSYS的大型波纹管辊压成型加工参数优化仿真

为了深入研究波纹管辊压成型机理,提高大口径波纹管制造成功率和生产效率,基于ANSYS软件建立了辊压成型的有限元模型,以直径为3 000 mm的大型波纹管为研究对象,分析辊压过程中相对滑动和偏移等现象,分别研究进给速度、辊轮转速、摩擦系数和辊压次数对成型加工的影响并得出最优加工参数。该加工参数优化方法可指导辊压装备设计和波纹管的实际加工。

卷到卷制程中基于降维观测器的优化状态反馈控制方法

卷到卷(roll-to-roll,R2R)制程普遍应用于柔性材料的量化生产中,其套色精度是产品质量的关键因素。R2R制程是一个多输入多输出、强耦合的复杂生产过程,实现高速高精度套色控制是其基本要求。首先,根据R2R印刷系统的状态空间模型,设计了基于降维观测器的状态反馈控制方法,同时通过粒子群优化算法对状态反馈的极点进行优化,实现了套色误差的高精度控制。将提出的套色控制方法与最新发表的全解耦比例微分(fully decoupled proportional-derivative,FDPD)套色控制方法进行对比,所提方法在套色精度上获得了50%~80%的提升,调节时间缩短了50%~65%,控制量绝对值之和仅为FDPD控制方法的46%~57%,这不仅减少了对执行机构的冲击,也节约了能量。对比结果证实了降维观测器的估值准确性,也表明所提方法能够明显提高控制性能。

面向精度提升与工艺改进的容差分配多目标模型融合方法

在现代机械产品装配容差优化过程中,多以简单加权求和的方式构建多目标容差优化模型,求解效果较差且与装配现场的适用性不强。鉴于此,以装配精度提升与工艺改进为目标导向,首先,考虑配合误差引起的零件上不同关键特征间的位姿变动,构建装配误差传递累积模型与协调尺寸链,精准预测装配误差与多装配体间的协调误差;其次,结合各制造环节误差数据与装配精度累积数据,分别建立加工成本、质量损失、修配成本3个单目标优化模型,并以此提出可避免容差数据优化失衡与优化方向偏离的多目标模型权重参数分配方法,构建多目标容差优化分配模型;最后,采用加速粒子群算法求解得到面向工艺性能提升的各组成环误差数值。以某型航天器分段式机翼对接装配优化为例,在改进产品定位装夹方式之前,机翼对接外形阶差与修配成本分别降低94.68%与83.49%;在使用外形卡板定位后,通过优化使上述两项装配指标分别降低11.21%与8.50%,有效地保障了产品型面装配精度与对接协调质量。

基于滚动优化的电-热-气-冷系统多时间尺度低碳运行

电-热-气-冷多能联供型微网对实现能源可持续发展具有重要的应用价值。针对多能联供系统碳排放量较高和负荷模型预测不准确问题,提出了一种基于滚动优化的电-热-气-冷系统多时间尺度低碳运行策略。首先,建立电-热-气-冷系统设备模型。其次,构建日前与日内两阶段模型,在日前调度阶段引入含赏罚因数的碳交易机制,通过将卷积神经网络(convolutional neural networks,CNN)与双向长短期记忆网络(bi-directional long short term memory,Bi-LSTM)进行结合对风光功率进行预测,并以运行成本最低为目标进行优化。之后,建立日内多时间尺度的优化调度模型,以调度成本最低为目标进行求解。最后,以某市综合能源系统为研究对象进行分析。结果表明,所提出的方法能够有效减少碳排放,提高负荷模型预测的准确度的同时实现多能联供系统的低碳经济运行。

基于模糊数学评定与响应面法优化杏子与玫瑰花酱复合果丹皮的研制

该研究在果丹皮传统配方工艺的基础上对复合果丹皮的辅料添加量配方进行了优化,以杏子和玫瑰花酱为主要原料,以酸味剂、凝胶剂、防腐剂为辅料,研制一款低糖复合果丹皮。采用单因素试验和Box-Behnken响应面优化法得到杏子与玫瑰花酱复合果丹皮的感官评分和杏子与玫瑰花酱的质量比、柠檬酸添加量、复合胶添加量、苯甲酸钠添加量的模型,经验证,模型合理可靠。通过模型系数显著性检验,得到以感官评分为响应值的主效应关系均为柠檬酸添加量>复合胶添加量>杏子与玫瑰花酱的质量比>苯甲酸钠添加量。得出最佳配方为杏子与玫瑰花酱的质量比2∶1、柠檬酸添加量0.2%、复合胶添加量3%、苯甲酸钠添加量0.04%,此配方下得到的感官评分为90.33分,与模型预测值较一致。结果表明,此数学模型较好地预测了杏子与玫瑰花酱复合果丹皮的配方。

螺纹钢切分轧制采用控轧控冷工艺生产实践

螺纹钢生产采用切分工艺,可以降低能耗和提高产能,采用控轧控冷工艺又可以显著降低钢坯合金成本,采用三切分工艺与控轧控冷工艺相结合,会增加技术难度。文章介绍了普通螺纹钢产线对传统三切分工艺进行优化后,与控轧控冷工艺相结合,解决了切分后进行飞剪切头控制稳定性差的问题;并通过进行多次控轧控轧工艺试验,摸索出各处关键温度控制范围,稳定了控轧控冷工艺产品的性能,保证产能与效率的同时降低了合金成本。

全钢载重子午线轮胎0°带束层散线原因分析及改善措施

分析全钢载重子午线轮胎0°带束层散线缺陷发生的原因,通过有限元仿真方法模拟轮胎成型过程中胎面辊压对0°带束层帘线末端散线位置橡胶的影响。通过优化成型辊压参数,减小0°带束层帘线末端散线位置橡胶的应变,使轮胎0°带束层散线缺陷发生率由0.4%降低到0.18%,在提高轮胎质量的同时也创造了良好的经济效益。