二次冷轧轧辊表面油膜厚度模型及其影响因素

 为解决现场无法在线测量轧辊表面油膜厚度的问题,考虑二次冷轧机组润滑设备与工艺特点,在阐述了二次冷轧过程轧辊表面油膜厚度形成及演变过程机理的基础上,运用流体动力学原理,建立了一套适合于二次冷轧机组的轧辊表面油膜厚度模型。定量分析了轧制速度、轧辊表面粗糙度、辊间接触最大应力、乳化液初始动力黏度和乳化液压力黏度系数等5个因素对轧辊表面油膜厚度的影响规律。将轧辊表面油膜厚度模型应用到某厂1220二次冷轧机组,并通过对比建立的模型求解得出的轧辊表面油膜厚度与现场离线采用称重法测量得到的轧辊表面油膜厚度结果发现,两者误差小于10%,这表明模型计算精度满足现场使用要求。     

冷连轧过程控制中轧制力和前滑模型的综合自适应

为了提高冷连轧过程控制系统中轧制力模型的设定精度,提出了一种轧制力和前滑模型的综合自适应算法.通过建立综合自适应目标函数,以变形抗力和摩擦系数模型中的自适应系数作为寻优参数,并采用Rosenbrock算法求解目标函数,可以同时得到满足轧制力模型和前滑模型计算精度的自适应系数.该模型自适应算法可成功应用于某1 450 mm冷连轧机组.结果表明,采用该模型的综合自适应算法后,轧制力设定精度显著提高,且满足在线控制要求.     

基于惩罚项的热连轧轧制规程多目标函数优化

为了解决传统热连轧负荷分配优化普遍采用约束方法进行求解时求解步骤繁琐、不容易获得最优解的问题,提出了一种惩罚函数算法.通过引入函数惩罚项,将多目标函数约束求解问题转化为无约束求解问题.建立了带有惩罚项的轧制力、板形、功率和温度的单目标函数,进而采用线性加权求和法建立了综合多目标函数.利用Nelder和Mead单纯形解法则进行求解,简化了求解的步骤,最终得到了兼顾轧制力平衡、板形最优及温度合理的负荷分配方案.实际应用效果表明,与传统负荷分配方式相比,基于多目标优化得到的轧制规程更符合实际生产要求,具有良好的应用前景.     

Algorithm design and application of novel GM-AGC based on mill stretch characteristic curve简

As the spring equation is limited to the accuracy of mill stiffness and the linearity of the mill spring curve, the traditional gaugemeter automatic gauge control （GM-AGC） system based on spring equation cannot meet the requirements of practical production. In allusion to this problem, a kind of novel GM-AGC system based on mill stretch characteristic curve was proposed. The error existing in calculating strip thickness by spring equation were analyzed first. And then the mill stretch characteristic curve which could effectively eliminate the influence of mill stiffness was described. The novel GM-AGC system has been applied successfully in a hot strip mill, the application results show that the thickness control precision is improved significantly, with the novel GM-AGC system, over 98.6% of the strip thickness deviation of 3.0 mm class can be controlled within the target tolerances of ±20 μm.     

Multi-objective optimization of rolling schedule based on cost function for tandem cold mill

In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost fi.mctions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.     

高精度薄带材冷连轧过程智能优化控制

带钢冷连轧控制是系统性极强、技术难度极大、精度要求极高的综合性技术，是保证冷轧带钢产品质量和生产效率的主要手段。东北大学自主开发了冷连轧全套自动化系统，涵盖了轧机主令控制、自动厚度控制、自动板形控制、物流跟踪、模型设定等功能，并研发了高精度数学模型、轧制规程多目标优化算法、加减速过程带钢厚度与张力补偿及轧制工艺优化等先进控制技术。所开发的系统已推广应用到多条冷连轧生产线中，现场应用表明,系统运行稳定，实现了0. 17mm极薄规格带钢高速稳定轧制，厚度偏差小于±2. 5μm，板形标准差小于7I。最后对轧制过程的智能化发展进行了展望。     

高精度薄带材冷连轧过程智能优化控制

带钢冷连轧控制是系统性极强、技术难度极大、精度要求极高的综合性技术,是保证冷轧带钢产品质量和生产效率的主要手段。东北大学自主开发了冷连轧全套自动化系统,涵盖了轧机主令控制、自动厚度控制、自动板形控制、物流跟踪、模型设定等功能,并研发了高精度数学模型、轧制规程多目标优化算法、加减速过程带钢厚度与张力补偿及轧制工艺优化等先进控制技术。所开发的系统已推广应用到多条冷连轧生产线中,现场应用表明,系统运行稳定,实现了0.17 mm极薄规格带钢高速稳定轧制,厚度偏差小于±2.5μm,板形标准差小于7 I。最后对轧制过程的智能化发展进行了展望。     

唐钢1 800 mm 5机架冷连轧机过程控制模型设定系统

简要介绍了唐钢1 800 mm 5机架冷连轧机组的工艺参数、仪表配置及过程控制模型设定系统。从轧制过 程在线数学模型、基于成本函数的多目标优化负荷分配和模型自适应3个方面对该冷连轧过程控制模型设定系统 进行了深入分析研究。现场应用表明,该L2过程控制系统运行稳定,模型设定系统制定的轧制规程合理、模型设 定计算具有非常高的精度,满足在线控制的要求。     

Improved Smith prediction monitoring AGC system based on feedback-assisted iterative learning control

The performance of Smith prediction monitoring automatic gauge control（AGC） system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning control strategy, which learned unknown modeling error by using previous control information repeatedly, was introduced into Smith prediction monitoring AGC system. Firstly, conventional Smith predictor and improved Smith predictor with PI-P controller were analyzed. Secondly, on the basis of establishing of feedback-assisted iterative learning control strategy for improved Smith predictor, process control signal update law and control error were deduced, then convergence condition of this strategy was put forward and proved. Finally, after modeling the automatic position control system, the PI-P Smith prediction monitoring AGC system with feedback-assisted iterative learning control was researched through simulation. Simulation results indicate that this system remains stable during model mismatching. The robustness and response of monitoring AGC is improved by development of feedback-assisted iterative learning control strategy for PI-P Smith predictor.     

酸轧机组高强钢跑偏断带问题控制技术研究

随着汽车工业的发展,汽车用钢的强度不断提升,冷连轧机组传统的压下率分配和板形执行机构的设定方法已经不能满足生产要求。以唐钢1 740 mm冷连轧机组生产汽车用高强钢DP980为研究对象,针对冷连轧过程中频发的带钢跑偏断带问题进行了研究,得到热轧来料的楔形和强度不均、负荷分配不合理导致S₁机架轧制力过高以及轧辊倾斜调整过于灵敏是导致高强钢跑偏断带的主要原因。为此,基于经典遗传算法,以前4机架轧制力平衡为优化目标,对该冷连轧机组压下率进行优化,同时将第1机架轧辊倾斜调整的限制范围和响应速度进行了调整。跟踪了1 760 t共86卷DP980高强钢的生产情况,带钢跑偏概率由40%降低为10%,且S₁机架未出现断带事故;轧制速度由200 m/min以下提升至500 m/min,速度发挥系数提高300%以上,机时产量提高100%,大幅提升了高强钢的生产效率。