Roughness Control of Layer-by-Layer and Alternative Spray Films from Congo Red and PAH via Laser Light Irradiation

Films from congo red (CR) alternated with poly(allylamine hydrochloride), PAH, were prepared by layer-by-layer and alternative spray techniques. In order to investigate the change of roughness induced by laser light irradiation (532 nm), both kinds of films were characterized by using UV-visible spectroscopy and atomic force microscopy (AFM). At dif- ferent irradiation times, layer-by-layer, LbL, films showed small changes in the roughness and irregular behavior, whereas spray films exhibited higher and a regular decreasing of roughness with increasing irradiation time. The higher roughness of spray films as compared with the LbL ones was attributed to different formation mechanisms of the films. The decreasing of the roughness as a function of the irradiation time (exhibited by the spray films) was associated to surface relaxation due to the interplay between photoisomerization of congo red dye and the heating of the sample during the laser light irradiation. The results suggested that the alternative spray technique is the best choose to control of roughness of the films by using light irradiation.

Research on development of surface-roughness variation and control technology of the automotive plates and rolls

Surface roughness considerably influences the stamping and coating performance of the automotive plates;however,the surface roughness of the automotive plates is transferred from the roll during the rolling process.Therefore,the variation and control technology regarding the roughness of the automotive plates and rolls has drawn increasing attention from researchers in China and around the globe.In this study,the research methods,analytical techniques,prediction models,transfer rules,and control technologies regarding the surface roughness of the automotive plates and rolls were reviewed.Among these,an online measurement system for automotive-plate and roll surface roughness has been applied to the production lines of Germany,China,Belgium,Holland,Austria,and other countries and has achieved remarkable results.Online measurement and timely feedback regarding the automotive-plate and roll surface roughness are needed to ensure favorable conditions for the establishment of automotive-plate roughness-control measurement.

Virtual Simulation System with Path-following Control for Lunar Rovers Moving on Rough Terrain

Virtual simulation technology is of great importance for the teleoperation of lunar rovers during the exploration phase, as well as the design of locomotion systems, performance evaluation, and control strategy verification during the R&D phase. The currently used simulation methods for lunar rovers have several disadvantages such as poor fidelity for wheel-soil interaction mechanics, difficulty in simulating rough terrains, and high complexity making it difficult to realize mobility control in simulation systems. This paper presents an approach for the construction of a virtual simulation system that integrates the features of 3D modeling, wheel-soil interaction mechanics, dynamics analysis, mobility control, and visualization for lunar rovers. Wheel-soil interaction experiments are carried out to test the forces and moments acted on a lunar rover’s wheel by the soil with a vertical load of 80 N and slip ratios of 0, 0.03, 0.05, 0.1, 0.2, 0.3, 0.4, and 0.6. The experimental results are referenced in order to set the parameters’ values for the PAC2002 tire model of the ADAMS/Tire module. In addition, the rough lunar terrain is simulated with 3DS Max software after analyzing its characteristics, and a data-transfer program is developed with Matlab to simulate the 3D reappearance of a lunar environment in ADAMS. The 3D model of a lunar rover is developed by using Pro/E software and is then imported into ADAMS. Finally, a virtual simulation system for lunar rovers is developed. A path-following control strategy based on slip compensation for a six-wheeled lunar rover prototype is researched. The controller is implemented by using Matlab/Simulink to carry out joint simulations with ADAMS. The designed virtual lunar rover could follow the planned path on a rough terrain. This paper can also provide a reference scheme for virtual simulation and performance analysis of rovers moving on rough lunar terrains.

基于地形特征时频变换的无人特种车辆速度自适应控制方法

为提高复杂环境下无人特种车辆安全性、自主性及作业能力,面向在崎岖地形下无人特种车辆应用需求,提出一种基于地形特征时频变换的速度自适应控制方法。通过度量地形特征崎岖度、建立崎岖度和车速数学模型,实现无人特种车辆在崎岖地形的自主、自适应车速规划。针对崎岖地形和坡度引起的点云数据失真问题,融合惯性测量单元传感器数据对点云进行补偿,获得了车辆前方地形的精准点云数据;针对可视距离与跟踪精度冲突问题,不同于传统横向曲率计算方式,采用以线到面的方式,将激光雷达纵向剖面点云数据进行时频变换后,在频域内选取次频区域的积分面积作为崎岖度量化值,实现对不同地形下的崎岖度量化;此外,基于上述获得的崎岖度,采用迭代搜索的方式建立速度与崎岖度数学模型,并采用滑动窗口的方式更新崎岖度,实现车速到崎岖度之间的连续映射。以可控震源野外勘探特种车为研究对象,采用上述方法在实际野外地形环境中进行多次实验。实验结果表明,所提出的方法在崎岖地形具有良好的安全性、自主性,可以识别地形和自适应控制车速。

Adaptive Predictive Inverse Control of Offshore Jacket Platform Based on Rough Neural Network

The offshore jacket platform is a complex and time-varying nonlinear system, which can be excited of harmful vibration by external loads. It is difficult to obtain an ideal control performance for passive control methods or traditional active control methods based on accurate mathematic model. In this paper, an adaptive inverse control method is proposed on the basis of novel rough neural networks （RNN） to control the harmful vibration of the offshore jacket platform, and the offshore jacket platform model is established by dynamic stiffness matrix （DSM） method. Benefited from the nonlinear processing ability of the neural networks and data interpretation ability of the rough set theory, RNN is utilized to identify the predictive inverse model of the offshore jacket platform system. Then the identified model is used as the adaptive predictive inverse controller to control the harmful vibration caused by wave and wind loads, and to deal with the delay problem caused by signal transmission in the control process. The numerical results show that the constructed novel RNN has advantages such as clear structure, fast training speed and strong error-tolerance ability, and the proposed method based on RNN can effectively control the harmful vibration of the offshore jacket platform.

电化学加工表面均匀性的多变量统计过程控制

零件表面粗糙度对其使用性能有重要影响。为了解决零件表面单一粗糙度参数不能全面反映零件加工表面缺陷的问题,提出一种将基于相关性分析和主元分析的多变量统计过程控制应用于电化学光整加工零件表面均匀性评价的方法。设计无表面缺陷和有表面缺陷两个样件进行对比实验,在电化学光整加工之后记录两个样件的多项表面粗糙度参数,先进行多个参数的单变量统计过程控制,再对多个粗糙度参数进行相关性分析和主元分析,得到综合评价值绘制统计控制图。对比分析结果表明:对于存在局部缺陷的表面,相比单一粗糙度参数,采用综合评价控制图检测零件表面缺陷更准确;基于相关性分析和主元分析的多变量统计过程控制是评价电化学光整加工零件表面均匀性的有效方法。

壁面粗糙度对隔离段气动性能影响的数值计算

针对粗糙度对隔离段性能影响,本文开展了不同粗糙度大小、不同粗糙度分布对相同背压下隔离段内激波串发展以及对隔离段出口气流参数影响的数值计算。隔离段进口马赫数2.0,总压0.82 MPa,总温840 K。研究结果表明:与光滑壁面相比,整体布置粗糙度时,边界层转捩提前,激波串起始位置向上游移动,隔离段出口气流参数下降;当粗糙带布置在50S时,随着粗糙度的增加,激波串起始位置后移;当粗糙带布置在70S时,随着粗糙度的增加,隔离段出口气流总压恢复系数升高。因此,合理布置粗糙度位置及大小能够使隔离段具有更优的性能。

Electrochemically Deposited CZTSSe Thin Films for Monolithic Perovskite Tandem Solar Cells with Efficiencies Over 17%

In spite of the high potential economic feasibility of the tandem solar cells consisting of the halide perovskite and the kesterite Cu2ZnSn(S,Se)4(CZTSSe),they have rarely been demonstrated due to the difficulty in implementing solution-processed perovskite top cell on the rough surface of the bottom cells.Here,we firstly demonstrate an efficient monolithic two-terminal perovskite/CZTSSe tandem solar cell by significantly reducing the surface roughness of the electrochemically deposited CZTSSe bottom cell.The surface roughness(R_(rms))of the CZTSSe thin film could be reduced from 424 to 86 nm by using the potentiostatic mode rather than using the conventional galvanostatic mode,which can be further reduced to 22 nm after the subsequent ion-milling process.The perovskite top cell with a bandgap of 1.65 eV could be prepared using a solution process on the flattened CZTSSe bottom cell,resulting in the efficient perovskite/CZTSSe tandem solar cells.After the current matching between two subcells involving the thickness control of the perovskite layer,the best performing tandem device exhibited a high conversion efficiency of 17.5%without the hysteresis effect.

基于数控工艺信息挖掘的型腔特征粗加工刀具序列优化决策方法

为有效提升数控加工过程中粗加工刀具的使用效率,提出一种基于数控工艺信息挖掘的型腔特征粗加工刀具序列优化决策方法。首先计算型腔特征的中轴变换表征数控加工的刀具轨迹,探究中轴变换与数控加工的映射机理;然后基于加工规则和中轴变换参数,挖掘隐含在型腔特征中的深层次数控工艺信息;最后综合考虑材料去除量和加工连续性,建立刀具序列决策的多目标优化模型,采用混合蚁群/模拟退火算法进行优化求解。实验结果表明,该方法能够高效、自动生成型腔特征最优粗加工刀具序列,提升企业数控工艺设计智能化水平。

运用Rough集理论研究工艺变量对RTM产品质量的影响(英文)

提出基于Rough集理论的用于研究工艺变量对RTM产品质量影响的一个方法程式,然后通过一个示例表明这一程式的可行性。

Rough集理论及其应用发展

论述了Rough集理论在人工智能、认知科学等领域的应用情况,讨论了Rough集理论的发展前景及趋势.论文中较为重要的创新之处的是,基于粗糙神经网络构造了一种从虚拟的场景图像智能化地直接推测符合主观听感的音质效果参数的模型.

复杂曲面零件的五轴数控加工技术研究

随着科技水平的不断提升,精密复杂曲面零件的应用越来越广泛。曲面驱动是复杂曲面零件加工的重要方法,驱动刀轨的规划直接关系到曲面物理特性的调控,应用五轴数控加工技术能够提升复杂曲面零件的加工质量。文章主要研究复杂曲面零件的五轴数控加工技术,以佛像这个复杂曲面零件为例,分析了曲面驱动刀轨规划、工装方案设计、加工策略以及试制加工过程。在实际加工过程中,技术人员应充分理解驱动刀轨规划思路与原理,在粗加工、精加工中完善刀轨设计,并进行试制加工。

基于Rough集理论的数据库推理通道动态消除

提出了一种基于Rough集理论的数据库推理泄漏通道消除方法。在由数据库中所有数据生成的不完备决策表上,该方法应用Rough集理论,分析提取出敏感和非敏感数据之间的确定性推理关系,以此产生推理控制规则。利用这些规则对数据库系统返回给普通用户的数据动态地做最小修改,防止推理通道的产生。实验结果表明,该方法可扩展性强,在保证较高的数据库安全性的同时提高了数据可用性。

基于WPF的粗糙度测量数据可视化方案

在表面粗糙度测量数据的分析处理中,经常需要将数据可视化为图表等方式,以便观察测量结果和数据处理后的效果,帮助测量人员决定数据处理的后续方案。在WPF(Windows Presentation Foundation)的MVVM(Model-View-ViewModel)开发框架下,使用微软公司提供的Interactive Data Display可视化图形控件,根据粗糙度数据显示的具体需求,扩展了Interactive Data Display控件自定义属性,提供了自适应粗糙度测量数据的显示方法,为用户提供更为直观且清晰的数据可视化方案,帮助用户直观地理解粗糙度测量数据。

一种大型薄板箱体平面铣削方法

在建筑机械中,尤其是国家提倡的模块化建筑,普遍采用薄板零件,尤其是一些箱体构件,其结构并不复杂精度要求也不太高,但由于刚度较差,在装夹过程中和切削力的作用下,易产生变形、震刀,造成尺寸超差、表面粗糙度低和零件铣穿现象。本文从消除应力、减少刀具摩擦力等几方面,及降低焊接及加工过程中的受热变形引起的震动导致加工质量低等几方面提出了薄板箱体在加工过程中震刀难以控制的问题的有效技术方法,解决了相应技术难题。

EDT汽车铝板表面粗糙度影响因素的探究及控制策略

结合EDT汽车板在线实际生产数据,探究了轧辊类型、轧制力大小、压下率大小、轧制速度等对汽车板表面粗糙度的影响。通过对数据的分析,研究最优轧制工艺参数的设定,从而满足客户对不同粗糙度类型的要求。结果表明,轧辊类型是影响汽车板表面粗糙度关键因素;同时,适当的轧制力和压下量能够稳定生产合格的产品;轧制速度与板面粗糙度也存在一定的影响关系。

粗轧板坯自动转钢系统研究与应用

宽厚板生产过程中,其粗轧工艺需控制交叉的锥形辊实现板坯长宽方向的对调,该过程严重依赖人工操作,节奏无法有效控制,制约生产线智能化改造进程。结合视觉检测和自动控制技术设计的粗轧板坯自动转钢系统可有效解决该问题,在粗轧机出入口分别安装视频监控相机,捕捉转钢辊道区域上板坯的状态,利用改进的包含去雾模块的PIDNet(proportional-integral-derivative network)模型提取板坯前景轮廓,通过组合式角度度量方法实时跟踪板坯旋转角度。过程中融合安全限位、位置优选、速度调控、过转修正等策略共同优化转钢控制,保证转钢的安全稳定,自主学习人工经验提升转钢效率。应用结果表明,系统可准确测量板坯角度并实现自动转钢功能,能够替代人工操作,节省能耗,实现智能化生产的目的。

柳钢1450热轧线粗轧板形控制方法探究

柳钢1450热连轧生产线精轧工序头尾穿带稳定性极大程度受到粗轧中间坯板形影响,偶尔发生因来料板形差引发的楔形大、轧破、甩尾等现象。特此结合粗轧区域设备特性探索粗轧板形控制方法,对关键设备采取针对性改进措施,如设备对中精度、压下系统精度、装备配合间隙等,并开发投用板形调整功能适配工艺参数优化,应用于实际生产并取得明显效果。

基于ResNet多特征图融合的钻削表面粗糙度分类方法

传统五面复合数控(CNC)钻削表面粗糙度测量工作复杂,采用人工测量存在较大人为误差。传统多元回归、多项式拟合方法仅采用转速和进给速度参数,数据利用率低且噪声敏感性强;用传统机器学习方法无法有效提取信号的深层复杂特征。针对上述问题,提出了一种基于ResNet模型、频谱图特征与时频图特征融合的钻削表面粗糙度分类预测方法。首先,根据CNC钻削加工理论和企业实际CNC钻削经验确定了CNC钻削加工实验的工艺参数变量;然后,基于SYNTEC CNC系统开发了多源数据采集系统,实时采集了钻削加工过程数据;接着,分析了三轴振动信号的频谱特征和时频特征,验证了振动信号跟表面粗糙度类别的关联性;随后,采用卡尔曼滤波对三轴振动信号进行了降噪处理,采用快速傅里叶变换(FFT)和连续小波变换(CWT)进行了振动信号频谱热图与时频图转换,采用矩阵拼接对三轴振动信号的单轴时频图进行了拼接融合,得到了三轴振动时频图;最后,对频谱热图和时频图进行了卷积运算融合频谱特征与时频特征,并进行了ResNet和其他网络模型如Densenet、Shufflenet和Mobilenet_v3_small等的对比实验。研究结果表明:相对上述其他网络模型,基于ResNet网络模型的表面粗糙度分类正确率提高了约9%,同时也验证了三轴时频特征融合以及频谱特征和时频特征融合方法的正确性。由于模型训练成本低、训练收敛速度快,该方法在轻量级、低成本的CNC机床钻削表面粗糙度预测分类中具有良好的工业应用前景。

煤矿采空区失稳灾害预测及综合防控技术

为减小煤矿采空区失稳灾害的发生概率、保证周边居民生命和财产安全、避免采空区失稳灾害带来大规模的生态破坏现象,对煤矿采空区失稳灾害进行预测和防控。利用粗糙集理论剔除冗余和缺陷信息,结合突变级数法得到失稳灾害预测指标体系,利用熵权理论获得地质、水文、环境、结构指标对应的灾害权重,引入置信度完善预测识别准则,完成失稳灾害预测,在此基础上,采用综合防控技术降低煤矿采空区自然灾害的发生频率。实验结果表明,所提方法的煤矿采空区失稳灾害预测结果精准度高,同时综合防控技术能够有效提高煤矿采空区的安全性。