Improvement on Conventional Load Distribution Algorithm in Hot Tandem Mills

Load distribution is a key technology in strip hot rolling process, which influences the coil＇s mierostrueture and performance. Currently, Newton-Raphson algorithm is applied to load distribution of hot tandem mills in many hot rolling plants and has some serious defects such as having a strict restriction on initial iterative calculation value and requiring coefficient matrix of nonlinear equations to be nonsingular. To eliminate these defects and improve the online performance of the process control computer, Newton descendent numeric algorithm is introduced to this field to widen the initial value range and a new model named error conversion algorithm is put forth to deal with special conditions when the coefficient matrix is singular. Furthermore, considering the characteristics of load distribution, a condition of strip thickness distribution abnormality and corresponding solutions are provided which ensure that rolling parameters can be calculated normally. Simulation results show that the improved algorithm has overcome the defects of the Newton-Raphson algorithm and is suitable for online application.

Prediction of Rolling Load in Hot Strip Mill byInnovations Feedback Neural Networks

Because the structure of the classical mathematical model of rolling load is simple, even with the self-adapting technology, it is difficult to accommodate the increasing dimensional accuracy. Motivated by this fact, an Innovations Feedback Neural Networks （IFNN） was presented based on the idea of Kalman prediction. The neural networks used the Back Propagation （BP） algorithm and applied it to the prediction of rolling load in hot strip mill. The theoretical results and the off-line simulation show that the prediction capability of IFNN is better than that of normal BP networks, namely, for the prediction of the rolling load in hot strip mill, the prediction precision of IFNN is higher than that of normal BP networks. Finally, a relative complete rolling load prediction system was developed on Windows 2003/XP platform using the OOP programming method and the SQL server2000 database. With this sys- tem, the rolling load of a 1700 strip mill was calculated, and the prediction results obtained correspond well with the field data. It shows that IFNN is valid for rolling load prediction.

SELF-ALIGNING EVEN LOAD MECHANISM OF MULTI-ROW BEARINGS OF LARGE STRIP ROLLING MILL

The load distribution of multi-row bearings of large strip rolling mill is fully analyzed by 3D contact boundary element method （BEM）. It is found out that bearings are frequently worn out due to serious uneven load on the multi-row rollers. The constraint mechanism of the previous rolling system is found to be unreasonable by theoretical analysis on heavy machinery structure. A mechanism of self-aligning even load for workroll bearing of 2 050 mm hot rolling mill of Baoshan I＆S Co. is developed. This device is manufactured with particular regard to the structure of 2 050 mm hot rolling mill mentioned above. Hence, uneven load on multi-row bearings is greatly relieved and their lives are remarkably prolonged. Meanwhile, theoretical analysis and on-spot tests prove the rationality and validity of the device.

Optimal Design of Deforming Regulation for Compact Continuous Rolling Mill with Balanced Load

If the draught of each mill stand is limited by forced bite condition for compact continuous mill,the rolling load difference between one mill stand and another is very big.If deforming regulation of relative load for each mill stand is approximate to the same,the productive capacity of compact continuous mill can be brought into full play,and also the safety running and the smooth rolling of mill can be ensured.

某铜矿选矿厂半自磨系统磨矿负荷分配研究

半自磨+球磨组成的半自磨系统应用广泛,但在应用过程中半自磨机和球磨机负荷不平衡的情况经常出现。结合某铜矿项目,分析了出现负荷不平衡的原因,并通过优化半自磨机入料粒度、增加格子孔孔缝和开孔率、调整半自磨机排矿产品粒度、优化筛缝尺寸、修改直型格子板为弧形格子板、优化破碎后顽石的返回途径等措施,使得半自磨系统新给矿处理量由39 960 t/d提高至42 500 t/d,半自磨功率保持不变,但球磨机运行功率由9 300 kW提升至11 000 kW,半自磨和球磨负荷分配更加合理。通过对不同优化措施的分析和应用,可为解决其他矿山半自磨流程负荷不平衡问题提供借鉴和参考。

MPS型磨煤机制粉系统动态模型与瞬态运行优化控制研究

为提升MPS型磨煤机制粉系统变出力过程关键参数的控制精度,该文建立并验证制粉系统动态模型,开展控制策略优化研究。在原逻辑基础上,提出考虑煤质水分信息的前馈磨煤机入口一次风温控制回路,以优化控制策略。开展煤质水分增加、给煤速率增加、磨煤机变出力等瞬态过程模拟研究,获得制粉系统关键参数瞬态特征和能耗特性,验证所提出策略的优越性。结果表明:采用优化的控制逻辑后,系统在应对煤质水分突变、煤量突变等扰动时的响应速率增加、磨煤机出口风粉温度波动范围减小50%以上、瞬态能耗下降2.4%。磨煤机在变出力过程中,稳态能耗可降低100 kW以上,制粉过程能耗降低6.82%,瞬态过程中磨煤机出口风温的波动幅度下降50%、响应时间缩短10%以上、可实现瞬态节能5.43%,保障制粉系统的运行安全并降低能耗。在燃煤发电机组中应用提出的制粉系统优化控制逻辑,可降低燃煤发电机组变负荷瞬态过程中负荷率、主汽压力等关键参数的运行偏差,提高机组的运行灵活性。

兼顾排屑与降载作用的叶轮拐角单笔清根刀具

清根加工作为叶轮拐角区域残余材料的补加工工艺,在整体叶轮数控加工中占据十分重要的地位。盖盘叶轮清根加工具有推刀进给、拐角曲面曲率大、切削余量大、空间几何受限等特点。而传统球头铣刀刀尖点切削性能不足,应用于盖盘叶轮清根加工会导致切削载荷大和切屑挤压,造成刀具过早失效、加工表面质量差等问题。本文针对盖盘叶轮清根加工的特点和难点,提出一种面向不同拐角尺寸的具有削顶结构以及大容屑槽结构的刀具,并推导了切削刃的表达式。对传统球头铣刀和新式削顶铣刀进行仿真与实验,结果表明,新式削顶铣刀较传统球头铣刀切削力降载高达77.6%,切削过程更平稳可靠,加工质量更高。

一种新型无磁传感磨机综合检测系统

为解决磨机功耗大、负荷难以预测等问题,提出一种基于无磁传感的球磨机综合检测系统。该系统利用无磁耦合传感技术监测磨机负荷,不受磨机内物料磁性影响,结合更能准确反映磨机真实负荷特性的低功耗滚筒筒壁振动检测单元,通过无线传输将振动数据发送给信号采集单元,解决滚筒筒壁振动检测系统取电难的问题。融合磨机的磨音采集数据,在本地边缘算法单元内借助深度学习对磨机负荷特性进行预测,并反馈给PLC控制器进行给料和加球等实时调节,实现系统的闭环控制,极大提升了磨机效率,稳定生产指标,显著降低系统能耗。该系统在某选矿厂的试用结果证实其对磨机负荷预测识别效果良好。

考虑刀具跳动和非对称磨损的微铣削工件表面形貌模型

刀具跳动与非对称刀具磨损对微铣削工件表面形貌具有显著影响,在充分考虑这一影响因素基础上建立包含刀具跳动和非对称磨损的微铣削工件表面形貌模型,以精准预测微铣削工件表面切削形貌。基于余摆线运动方程研究刀具跳动和非对称性磨损对切屑负载的影响,构建切屑负载模型;根据最小切削厚度和弹性恢复理论,探索切屑负载和刀具磨损对工件底面切削残留高度的作用,并结合切屑负载模型建立包含刀具跳动和非对称磨损的底面切削形貌模型;提出底面形貌模型的三维点云仿真算法。实验结果表明,模型的预测误差在10%~15%,证明该模型能够精准预测微铣削工件底面的切削形貌。

装物料自动装车系统相关技术发展综述

本文对袋装物料自动装车系统的组成、所使用的设备与技术等方面进行综述,通过分析现有技术和研究进展,总结出自动装车系统的优势,并对未来的发展进行展望。

基于变转速磨煤机的机组快速变负荷控制策略研究

由于制粉系统的延迟惯性特性,对锅炉的响应速率有较大影响,改善制粉系统的迟滞性对于提高机组变负荷速率具有重大意义。本文通过系统建模及数据仿真分析了磨煤机变转速对机组响应特性的影响,设计了基于变转速磨煤机的机组快速变负荷控制策略,根据变负荷过程及需求控制磨煤机转速,最大限度地发挥变转速磨煤机的优势,提高机组的变负荷速率响应能力,并通过试验验证了策略的有效性。试验结果表明,在配有变转速磨煤机的机组上采用该套控制策略能够有效提升机组变负荷速率,机组变负荷速率可达3%Pe/min以上,极大地提升了机组的负荷响应能力。

电磁感应加热装置在棒材直轧产线上的应用

棒材直轧工艺充分利用连铸坯余热,不经过传统加热炉工序直接轧制,可降低能源消耗。该工艺对连铸坯的开轧温度控制提出了更高要求,温度不足可能导致轧件扬头或堆钢。为解决这一问题,电磁感应加热装置被引入。相较于传统蓄热加热炉,电磁感应加热装置能够更快速地对连铸坯进行加热,提高效率,减少氧化脱碳。合理的电源功率与频率选择能够在保证加热效率的同时,避免连铸坯表面出现过烧现象。此外,纵磁感应加热装置的表面效应与棒材连铸方坯表面温度低、芯部温度高的温降趋势互补,能够有效进行针对性补温。研究实际生产数据发现,低温环境中使用电磁感应加热装置对连铸坯进行补温可有效降低轧机负荷,使得峰值转矩百分比由80%降至64%。

磨煤机液压变加载改造在火电机组灵活性提升中的应用

介绍了火电机组灵活性改造的重要性和背景,详细论述了中速磨煤机液压变加载改造方案。通过对磨煤机加载方式进行升级改造,不仅可以在线实时调节液压加载力,使磨煤机适应机组负荷快速变化,还可以满足火电机组低负荷运行的要求。

Modeling,Simulation and Experiment of Electro-hydraulic Screw Down Servo System of Seamless Tube Rolling Mill

Electro-hydraulic screw down servo system（HSDS） is widely used in seamless tube rolling mill in western companies.But in Chinese companies,mechanical screw down system（MSDS） is popularly equipped and has a serious disadvantage that the roller would often be locked when it is overloaded.For the purpose of designing the first set of domestic twin-roller,four-cylinder and six-framework electro-hydraulic HSDS of seamless tube rolling mill,an experiment system that can simulate the process of seamless tube rolling is constructed.A digital simulation model of the experiment system is built with AMESim software and validated by comparing the simulation results with experiment results.The sudden load response of the screw piston position is studied with the built model and the experiment system.To improve the HSDS＇s positioning accuracy with large load,a hybrid control scheme of combining load disturbance feedforward compensation（LDFC） method based on servo valve＇s pressure-stroke feature and anti-saturation integral control（ASIC） is proposed.Both results of simulation and experiment indicate that the transient response time of the single-roller HSDS with the proposed scheme decreases from 0.65 s to less than 0.2 s without static error.To improve the system dynamic stiffness and production qualified rate,a flow rate feedforward compensation（FFC） control strategy based on oil compressibility to dynamic position error is proposed.This FFC strategy is validated with experiments in which the transient error caused by sudden load is reduced to less than 25% of that without FFC.By extending the simulation model to HSDS of a twin-roller,four-cylinder rolling mill,analyzing the mill deformation,and applying the LDFC,ASIC and FFC to the HSDS,the dynamic performance and positioning accuracy of compensated multi-roller HSDS at biting moment are predicted.The research results provide a theoretical and experimental basis for the design of HSDS of seamless steel tube rolling mill.

Effect of Load Distribution on Strip Crown in Hot Strip Rolling

In order to establish precision model, a software to calculate the strip crown of four-high hot rolling mill was developedby using affecting function method according to the strip crown calculation theory. The effect of work roll diameter,unit width rolling load, roll bending force, work roll crown, initial strip crown and reduction, etc, on load distributioneffect rate was simulated by using the software. The results show that the load distribution effect rate increaseswith the increase of strip width, work roll diameter, unit width rolling load, roll bending force, work roll crown,initial strip crown and reduction. Based on the simulation results, base value of load distribution effect rate andfitting coefficients of six power polynomial of load distribution effect rate modification coefficient were determinedconsidering all of the above parameters. A simplified mathematical model for calculating load distribution effect ratewas established.

Research on dynamic characteristics of high speed milling force based on discontinuous functions

This paper begins with a consideration of the influence of feed per revolution upon the depth of a cut and the impact of the machining method on the direction of tool pressure average and subsequent description of efficient cutting directions and the methods for load cell orientation. The paper goes further into the key conclusions concerning the dependences of the cutting depth at high-speed milling as in the case of discontinuous functions. It ends with recommendations offered for positioning of load cells for cut-up milling and cut-down milling.

基于相空间重构和PSO-K-means的球磨机负荷状态识别方法

针对球磨机振动信号具有强随机性、非平稳性和非线性等内在特性导致负荷状态难以识别的问题,提出一种基于相空间重构和PSO-K-means的球磨机负荷状态识别方法。首先,利用改进前后的自相关系数算法对Lorenz与Rossler两种混沌时间序列进行数值模拟,得出延迟时间和嵌入维数精准有效的计算方法;其次,验证出球磨机筒体振动信号具有混沌特性后对其时间序列进行相空间重构,恢复出等价的混沌吸引子;接着,针对3种不同负荷状态下的相空间吸引子进行特征提取,分析了关联维数特征量的变化规律;最后,将关联维数作为特征向量输入PSO-K-means聚类模型中对球磨机负荷状态进行分类与识别。结果表明,PSO-K-means聚类模型在负荷状态识别时有较高的精准性,欠负荷、正常负荷、过负荷下识别精度分别为94.2%、96.3%、94.8%。以上结果证实了该方法能够实现对球磨机负荷状态的有效识别。

High Strain-Rate and Shock Response of Carbon SupercompositeTM

This study focuses on assessing the dynamic behaviors of carbon SupercompositeTM laminates when subjected to high strain-rates and air blast loads, using a shock tube for testing. The investigation aims to understand the response of these advanced materials under extreme conditions, which is crucial for applications in aerospace, military, and other high-performance industries. SupercompositeTM (CZE) prepreg, made up of a 3K plain weave carbon fabric with milled carbon fibers as interlaminar reinforcements impregnated with epoxy, is used to create SupercompositeTM (CZE) laminates. A woven carbon composite (CBE) laminate was also created using 3K plain weave Carbon/Epoxy (CBE) prepreg. Both types of laminates were designed and fabricated using the autoclave process. The dynamic behaviors of CZE and CBE laminate under transverse compression loads were evaluated using a modified Split Hopkinson Pressure Bar (SHPB). The study found that the 3D reinforcement with milled carbon fibers significantly affected the dynamic behavior of the CZE laminate. Stereo imaging videos, captured using two SHIMADZU high-speed video cameras in shock tube experiments, recorded the time history of back surface deflection. The plate specimens exhibited low deflections without any visible damage. The experimentally observed center point deflections of the CZE plates decayed sooner than those of the CBE laminates, indicating an improvement in damping due to the presence of 3D reinforced milled carbon fibers. This research shows that optimized utilization of milled carbon fibers as 3D reinforcement can withstand high stress in the thickness direction and higher energy absorption when subjected to impact and high strain-rate loading.

基于自适应VMD-Hilbert的球磨机负荷参数预测

提出一种自适应变分模态分解(VMD)—希尔伯特(Hilbert)边际谱样本熵和最小二乘支持向量机(LSSVM)提取球磨机振动信号组合特征并预测负荷参数的方法。首先,使用自适应VMD的振动敏感信号调制来分解振动,得到反映振动特性的本征模态函数(IMF)分量;之后,进行Hilbert变换,得到边际谱样本熵;最后,将其作为输入特征向量输入到LSSVM,实现球磨机负荷参数预测。试验结果表明:该方法可以有效地提取球磨机的非线性不稳定的信号特征,较为精确地预测球磨机负荷参数。

基于深度宽卷积残差收缩网络的球磨机负荷状态诊断

针对磨矿复杂工况下球磨机负荷状态准确诊断的难题,提出一种基于深度宽卷积残差收缩网络(Deep Wide Residual Shrinkage Networks, DWRSNs)的球磨机负荷状态诊断方法.首先采用宽卷积神经网络提取振动信号短时特征,建立三层深度残差收缩网络,利用软阈值函数进行非线性变换,再基于注意力机制模块自主学习阈值提取面向负荷状态的高级特征,通过全连接层、softmax层实现球磨机负荷状态的准确分类与判别.实测结果证明,本文提出的DWRSNs方法的拟合度、收敛速度及学习能力均优于现有DCNNs、ResNets和DRSNs诊断方法,且提取的振动信号特征具有高代表性,经TSNE可视化后簇内紧密度高、簇间分界明显.本文方法诊断测试集的准确率超过99%,交叉熵损失为0.077 2,相较于现有负荷状态诊断方法具有更高的准确率且诊断耗时更短,可实现球磨机负荷状态的准确判别,为选冶磨矿过程优化控制、提高磨矿效率提供有效、可靠的判据.