Adaptive force–environment estimator for manipulators based on adaptive wavelet neural network

This study focuses on the accurate tracking control and sensorless estimation of external force disturbances on robot manipulators. The proposed approach is based on an adaptive Wavelet Neural Network (WNN), named Adaptive Force-Environment Estimator (WNN-AFEE). Unlike disturbance observers, WNN_AFEE does not require the inverse of the Jacobian transpose for computing the force, thus, it has no computational problem near singular points. In this scheme, WNN estimates the external force disturbance to attenuate its effects on the control system performance by estimating the environment model. A Lyapunov based design is presented to determine adaptive laws for tuning WNN parameters. Another advantage of the proposed approach is that it can estimate the force even when there are some parametric uncertainties in the robot model, because an additional adaptive law is designed to estimate the robot parameters. In a theorem, the stability of the closed loop system is proved and a general condition is presented for identifying the force and robot parameters. Some suggestions are provided for improving the estimation and control performance. Then, a WNN-AFEE is designed for a planar manipulator as an example, and some simulations are performed for different conditions. WNN_AFEE results are compared attentively with the results of an adaptive force estimator and a disturbance estimator. These comparisons show the efficiency of the proposed controller in dealing with different conditions.     

Structural,electronic, elastic,mechanical and thermal behavior of RESn3(RE = Y,La and Ce) compounds: A first principles study

The structural, electronic, elastic, mechanical and thermal properties of the isostructural and isoelectronic nonmagnetic RESn₃ (RE = Y, La and Ce) compounds, which crystallize in AuCu₃-type structure, are studied using first principles density functional theory based on full potential linearized augmented plane wave (FP-LAPW) method. The calculations are carried out within PBE-GGA, WC-GGA and PBE-sol GGA for the exchange correlation potential. Our calculated ground state properties such as lattice constant (a₀), bulk modulus (B) and its pressure derivative (B′) are in good agreement with the experimental and other available theoretical results. We first time predict the elastic constants for these compounds using different approximations of GGA. All these RESn₃ compounds are found to be ductile in nature in accordance with Pugh's criteria. The computed electronic band structures and density of states show metallic character of these compounds. The elastic properties including Poisson's ratio (σ), Young's modulus (E), shear modulus (G_H) and anisotropy factor (A) are also determined using the Voigt–Reuss–Hill (VRH) averaging scheme. The average sound velocities (v_m), density (ρ) and Debye temperature (θ_D) of these RESn₃ compounds are also estimated from the elastic constants. We first time report the variation of elastic constants, elastic moduli, Cauchy's pressure, sound velocities and Debye temperatures of these compounds as a function of pressure.     

激光熔覆制备高熵合金涂层研究进展

激光熔覆具有加热和冷却速度快、稀释度低(<5％)、热影响区小以及可以对表面性质进行精准调整等优点,是当今工业应用较为广泛的表面改性技术之一.利用激光熔覆技术制备高熵合金涂层,既能保证涂层具有简单的相结构和优异的性能,又可使涂层与基体之间获得良好的冶金结合.主要对激光熔覆制备高熵合金涂层的设计准则、性能及提高机理、凝固行为以及数值模拟的研究进行阐述.首先从设计理论方面对高熵合金进行概念阐述,由熵和吉布斯自由能可知,通过增加主元(至少5个)和位形熵来设计元素组成,通过吉布斯自由能控制相的稳定性.其次,对涂层的性能提高机理分类总结,其中高熵合金的四大效应与激光熔覆快冷快热的特点相结合是涂层性能提高的主要原因.此外,还阐述了激光熔覆过程中熔池的凝固行为,包括凝固过程中的晶粒生长方式和液相分离现象,以及其他因素引起的凝固行为变化.之后,对粉末流动特性、熔池温度场和熔覆层性能的数值模拟以及这些模型的缺陷进行综述与分析.最后,总结与展望激光熔覆制备高熵合金涂层研究的发展前景与应用方向.     

基于ADINA钢筋混凝土结构非线性分析

介绍了ADINA中钢筋混凝土的本构模型及破坏准则,讨论了应用ADINA对预应力钢筋混凝土进行非线性分析时,混凝土和预应力钢筋有限元模型以及预应力的处理方式。以一根简支梁为实例,应用ADINA对简支梁进行非线性分析,将其数值计算结果与理论计算结果对比,结果表明ADINA计算的结果比较接近理论值,误差在工程允许范围内,因此可以应用ADINA对预应力钢筋混凝土结构进行非线性分析,对今后进行复杂的预应力混凝土结构非线性分析提供参考价值。     

油水两相流润滑轧机油膜轴承的摩擦行为分析

目的研究含水润滑油对轧机油膜轴承的摩擦学性能的影响。方法选取轧机油膜轴承为研究对象,利用油水两相流体数学模型和弹流润滑方程研究轧机油膜轴承在等温条件下的润滑特性,分析油水两相流体润滑膜的压力、膜厚分别随含水率、滑滚比、轴颈间隙、主轴转速和轧制力的变化关系。结果水介入润滑油之后,随着含水率的增加,油水两相流体的黏度先增加,在含水率为30%左右时达到最大值(0.08 Pa·s),之后又迅速减小,直至接近于纯水的黏度(0.001 Pa·s)。当含水率为30%时,无量纲膜厚达到最大值(0.82),当含水率为90%时,无量纲膜厚达到最小值(0.68)。结论随着含水率的增加,油水两相流体由油包水流型转化为水包油流型,压力变化不大,膜厚先增加后减小,作为润滑剂,油包水流型比水包油流型具有更好的润滑性能,且在流型转变点处的润滑性能最优。随着滑滚比和轧机油膜轴承主轴转速的增加,压力减小,承载能力减弱,膜厚增加,润滑性能增强。随着轴颈间隙和外部轧制力的增加,压力增加,承载能力增强,膜厚减小,润滑性能减弱。     

梯度润湿性ZnOHF薄膜上液滴定向铺展行为

目前对ZnOHF的润湿性相关的研究较少。借助ZnOHF的光响应润湿性转变特性制备梯度润湿性表面,研究该表面上的液滴定向铺展行为,验证应用该表面可提高潮湿环境中的集水量。通过水热法制备花状ZnOHF薄膜,基于其光响应特性对ZnOHF薄膜进行不同时间的紫外光照制备单侧梯度润湿性表面,研究液滴在梯度表面上的定向铺展行为。采用XRD和SEM表征产物的物相组成和微观结构,使用FT-IR表征紫外光照前后ZnOHF薄膜的-OH基团变化,使用接触角测量仪表征ZnOHF薄膜的润湿性,记录液滴的铺展行为。结果表明,在紫外光照射下,薄膜的接触角变化速度先快后慢,3 h即可由152°转化为0°。在梯度表面上水滴以7.42 mm/s的速度从光照起始线向超亲水端定向铺展4.08 mm,与均匀表面（1.16 mm/s）相比铺展速度更快,距离（3.82 mm）更远;梯度表面上的液滴可以克服重力铺展,其速度（3.84 mm/s）依然大于均匀表面。液滴在梯度表面定向铺展的主要驱动力为不平衡的表面张力,不同体积的液滴铺展到光照分界线处均出现加速现象。双侧梯度表面可以使小液滴汇聚于亲水区域,当液滴累积到一定体积时会向下渗透,...     

镍基分支化ZnOHF表面的制备及油水分离性能

目的 解决目前油水分离材料大多存在的制备工艺复杂、设备昂贵、分离效率低、重复使用性差等问题。方法 采用水热法在镍网表面生长分支化羟基氟化锌(ZnOHF)粗糙结构,随后在表面沉积十八烷基三甲氧基硅烷(ODS)分子,得到超疏水/超亲油镍网。利用扫描电子显微镜(SEM)、X射线衍射仪(XRD)和傅里叶变换红外光谱仪(FT–IR)对其表面的微观形貌、组织和表面成分进行表征,利用接触角测量仪表征其静态和动态润湿性能。结果 镍网表面生长的分支化ZnOHF粗糙结构,与低表面能的ODS单分子层协同作用,使该表面对水的接触角高达158°,对油的接触角则为0°,且连续滴加油品时,油会在表面迅速铺展、渗透,并向下滴落。将不同品类的油与水混合,模拟不同情况下的油水分离效果,其分离效率均在95%以上;经过50次重复的油水分离测试后,其油水分离效率仍能保持91%,表现出良好的重复使用性能。结论 实验制备的超疏水/超亲油镍网具有制备方法简单、成本低廉、高效耐用等优点,为含油废水的处理提供了新方法。     

混凝土单轴受拉断裂行为的近场动力学模拟

混凝土的宏观力学行为取决于材料组成及其性质。本文基于键基近场动力学理论建立了多相非均质性的混凝土细观尺度数值模型,研究了单轴拉伸作用下混凝土的宏观力学性能和断裂过程。通过改变粗骨料含量、砂浆强度、粗骨料强度以及界面过渡区强度对模型合理性进行了验证。结果表明:软化段之前的应力-应变曲线能够被很好重现,能准确描述混凝土在单轴拉伸作用下的力学性能和断裂过程;调整数值模型中各相材料的力学参数能够合理模拟出不同类型的混凝土在单轴拉伸作用下的断裂过程。     

Automatic analysis of fuel spray images

Analysis of fuel spray droplets is being conducted in General Motors Research Laboratories to provide real-time information on in-focus droplet sizes and numerical density. This paper introduces a fast and efficient technique for automatic analysis of fuel spray images. The preprocessing stage consists of a global thresholding of the log-edge of the image. The thresholded image is then used as a reference to detect objects in the gray level image, and the recognition of in- and out-of-focus droplets is achieved through a 3-level tree classifier.